Feed the Future Indicator Handbook

Feed the Future

Indicator Handbook

Originally!published:!March!2018!

Revised!version!published:!September!2019!

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ITEM

PAGE

Acronyms & Definitions

List of Indicators w/ hyperlinks to page locations

Introduction

Definition sheets (“Indicator Reference Sheets” or “IRS”) for all Indicators

53 Performance Indicators

25 Context Indicators

205

Appendix 1: List of Indicators by the FTF Results Framework

256

Appendix 2: List of Changes from the July 2016 version to the March 2018 version

of the FTF Handbook

262

Appendix 3: List of Changes from the original March 2018 version of the FTF

Handbook to this revised September 2019 version

279

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▪ BFS = Bureau for Food Security

▪ F = Office of Foreign Assistance Resources at the Department of State

▪ FAQ = Frequently Asked Questions

▪ FTF = Feed the Future

▪ FTFMS = Feed the Future Monitoring System

▪ GFSS = Global Food Security Strategy

▪ HQ = Headquarters

▪ IM = Implementing Mechanism (equivalent to a project or activity outside of USAID)

▪ IRS = Indicator Reference Sheet (the definition of an indicator)

▪ M&E = Monitoring and Evaluation

▪ MEL = Monitoring, Evaluation, & Learning

▪ OP = Operational Plan (annual budget planning document done in

FACTSInfo/NextGen)

▪ OU = Operating Unit (can be a USAID Bilateral Mission, Regional Mission,

Headquarters Office, Country post team, regional post team, and/or Washington-based

Feed the Future interagency bureaus and offices)

▪ PIRS = Performance Indicator Reference Sheet

▪ PPR = Performance Plan & Report (annual performance reporting document done in

NextGen)

▪ TA = Technical Advisor

▪ USAID = United States Agency for International Development

▪ ZOI = Zone of Influence (targeted geographic area where we work)

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Indicator #

Indicator TITLE & Link to Definition Sheet

Page #

EG-c

Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP [ZOI-

level]

EG-d *

Prevalence of Poverty: Percent of people living on less than $1.90/day 2011

PPP [National-level]

EG-e

Prevalence of moderate and severe food insecurity in the population, based on the Food

Insecurity Experience Scale (FIES) [ZOI-level]

EG-f *

Prevalence of moderate or severe food insecurity in the population, based on the Food

Insecurity Experience Scale (FIES) [National-level]

EG-g

Percent of households below the comparative threshold for the poorest quintile of the

Asset-Based Comparative Wealth Index [ZOI-level]

EG-h

Depth of Poverty of the Poor: Mean percent shortfall of the poor relative to the $1.90/day

2011 PPP poverty line [ZOI-level]

EG.3-2

Number of individuals participating in USG food security programs [IM-level]

EG.3-10, -11, -12

Yield of targeted agricultural commodities among program participants with USG

assistance [IM-level]

EG.3-e

Percent change in value-added in the agri-food system ("Ag GDP+") [National-level]

EG.3-f

Abbreviated Women's Empowerment in Agriculture Index [ZOI-level]

EG.3-g

Employment in the agri-food system [National-level]

EG.3-h

Yield of targeted agricultural commodities within target areas [ZOI-level]

EG.3.1-1

Kilometers of roads improved or constructed as a result of USG assistance [IM-level]

EG.3.1-14

Value of new USG commitments and private sector investment leveraged by the USG to

support food security and nutrition [IM-level]

EG.3.1-c

Value of targeted agricultural commodities exported at a national level [National-level]

EG.3.1-d

Milestones in improved institutional architecture for food security policy achieved with

USG support [Multi-level]

EG.3.2-2

Number of individuals who have received USG-supported degree-granting non-nutrition-

related food security training [IM-level]

EG.3.2-7

Number of technologies, practices, and approaches under various phases of research,

development, and uptake as a result of USG assistance [IM-level]

EG.3.2-24

Number of individuals in the agriculture system who have applied improved management

practices or technologies with USG assistance [IM-level]

EG.3.2-25

Number of hectares under improved management practices or technologies with USG

assistance [IM-level]

EG.3.2-26

Value of annual sales of producers and firms receiving USG assistance [IM-level]

105

EG.3.2-27

Value of agriculture-related financing accessed as a result of USG assistance [IM-level]

110

EG.3.2-28

Number of hectares under improved management practices or technologies that promote

improved climate risk reduction and/or natural resources management with USG

assistance [IM-level]

114

CBLD-9

Percent of USG-assisted organizations with improved performance [IM-level]

116

EG.3.2-a

Percent of producers who have applied targeted improved management practices or

technologies [ZOI-level]

120

EG.3.3-10

Percent of female participants of USG nutrition-sensitive agriculture activities consuming

a diet of minimum diversity [IM-level]

126

EG.4.2-7

Number of individuals participating in USG-assisted group-based savings, micro-finance

or lending programs [IM-level]

129

EG.4.2-a

Percent of households participating in group-based savings, micro-finance or lending

programs [ZOI-level]

131

EG.10.4-7

Number of adults with legally recognized and documented tenure rights to land or marine

areas, as a result of USG assistance [IM-level]

134

EG.10.4-8

Number of adults who perceive their tenure rights to land or marine areas as secure with

USG assistance [IM-level]

136

ES.5-1

Number of USG social assistance beneficiaries participating in productive safety nets [IM-

level]

138

HL.8.2-2

Number of people gaining access to a basic sanitation service as a result of USG

assistance [IM-level]

140

HL.8.2-5

Percent of households with soap and water at a handwashing station on premises [IM-

level]

142

HL.8.2-a

Percent of households with access to a basic sanitation service [ZOI-level]

144

HL.8.2-b

Percent of households with soap and water at a handwashing station on premises [ZOI-

level]

147

HL.9-1

Number of children under five (0-59 months) reached with nutrition-specific interventions

through USG-supported programs [IM-level]

150

HL.9-2

Number of children under two (0-23 months) reached with community-level nutrition

interventions through USG-supported programs [IM-level]

154

HL.9-3

Number of pregnant women reached with nutrition-specific interventions through USG-

supported programs [IM-level]

157

HL.9-4

Number of individuals receiving nutrition-related professional training through USG-

160

supported programs [IM-level]

HL.9-a

Prevalence of stunted (HAZ < -2) children under five (0-59 months) [ZOI-level]

162

HL.9-b

Prevalence of wasted (WHZ < -2) children under five (0-59 months) [ZOI-level]

165

HL.9-d

Prevalence of underweight (BMI < 18.5) women of reproductive age [ZOI-level]

168

HL.9-h *

Prevalence of stunted (HAZ < -2) children under five (0-59 months) [National-level]

171

HL.9-i

Prevalence of healthy weight (WHZ ≤ 2 and ≥-2) among children under five (0-59

months) [ZOI-level]

174

HL.9.1-a

Percent of children 6-23 months receiving a minimum acceptable diet [ZOI-level]

177

HL.9.1-b

Prevalence of exclusive breastfeeding of children under six months of age [ZOI-level]

180

HL.9.1-d

Percent of women of reproductive age consuming a diet of minimum diversity [ZOI-level]

183

GNDR-2

Percentage of female participants in USG-assisted programs designed to increase

access to productive economic resources [IM-level]

186

RESIL-1

Number of host government or community-derived risk management plans formally

proposed, adopted, implemented or institutionalized with USG assistance [IM-level]

189

RESIL-a

Ability to recover from shocks and stresses index [ZOI-level]

192

RESIL-b

Index of social capital at the household level [ZOI-level]

196

RESIL-c

Percent of households that believe local government will respond effectively to future

shocks and stresses [ZOI-level]

200

YOUTH-3

Percentage of participants in USG-assisted programs designed to increase access to

productive economic resources who are youth (15-29) [IM-level]

203

FTF Context-1

Percent of households below the comparative threshold for the poorest quintile of the

Asset-Based Comparative Wealth Index [National-level]

206

FTF Context-2 *

Average income of small-scale food producers, by sex and indigenous status (SDG

indicator #2.3.2) [National-level]

[n/a]- SDG

FTF Context-3 *

Volume of production per labour unit by classes of farming/pastoral/forestry enterprise

size (SDG indicator #2.3.1) [National-level]

[n/a]- SDG

FTF Context-4 *

Percentage of 15-29 year olds who are Not in Education, Employment or Training (NEET)

(SDG indicator #8.8.6) - [National-level]

[n/a]- SDG

FTF Context-5

Prevalence of wasted (WHZ < -2) children under five (0-59 months) [National-level]

209

FTF Context-6

Depth of Poverty of the poor: Mean percent shortfall relative to the $1.90/day 2011 PPP

poverty line [National-level]

211

FTF Context-7

U.S. government humanitarian assistance spending in areas/populations subject to

recurrent crises [Recurrent crisis areas (if data not available, National)]

214

FTF Context-8

Number of people in need of humanitarian food assistance in areas/populations subject

216

to recurrent crises [Recurrent crisis areas (if data not available, National)]

FTF Context-9

Percent of people who are ‘Near-Poor’, living on 100 percent to less than 125 percent of

the $1.90 2011 PPP poverty line [ZOI-level]

218

FTF Context-10

Risk to well-being as a percent of GDP [National-level]

223

FTF Context-11

Yield of targeted agricultural commodities [National-level]

225

FTF Context-12

Average Standard Precipitation Index score during the main growing season [ZOI-level]

227

FTF Context-13

Average deviation from 10-year average NDVI during the main growing season [ZOI-

level]

229

FTF Context-14

Total number of heat stress days above 30 °C during the main growing season [ZOI-

level]

232

FTF Context-15 *

Proportion of agricultural area under productive and sustainable agriculture (SDG

indicator #2.4.1) [National-level]

[n/a]- SDG

FTF Context-16

Prevalence of healthy weight (WHZ ≤ 2 and ≥-2) among children under five (0-59

months) [National-level]

234

FTF Context-17

Prevalence of underweight (BMI < 18.5) women of reproductive age [National-level]

237

FTF Context-18 *

Prevalence of undernourishment (SDG indicator #2.1.1) [National-level]

[n/a]- SDG

FTF Context-19

Percent of children 6-23 months receiving a minimum acceptable diet [National-level]

239

FTF Context-20

Prevalence of exclusive breastfeeding of children under six months of age [National-

level]

242

FTF Context-21

Percent of women of reproductive age consuming a diet of minimum diversity [National-

level]

244

FTF Context-22

Food security and nutrition funding as reported to the OECD DAC [Global-level]

247

FTF Context-23

Share of agriculture in total government expenditure (%) [National-level]

249

FTF Context-24

Proportion of total adult rural population with secure tenure rights to land, (a) with legally

recognized documentation and (b) who perceive their rights to land as secure [National-

level]

251

FTF Context-25

Percent of women achieving adequacy across the six indicators of the Abbreviated

Women’s Empowerment in Agriculture Index [ZOI-level]

253

* Marks those that are also a Sustainable Development Goal (SDG) indicator – see details on SDG linkage below

1567289:6;25&

The Feed the Future Indicator Handbook presents the set of performance management

indicators for phase two of the U.S. Government’s (USG’s) Feed the Future initiative, guided

by the Global Food Security Strategy (GFSS). The set of indicators described in this

Handbook are designed to measure progress against each result in the Feed the Future

results framework (Figure 1). This results framework and the indicators identified at each level

of this logic model help

us monitor the causal

flow from outputs to

project outcomes to

population - or system-

level - outcomes to

impacts, and supports

our ability to assess the

plausible contribution of

our actions to the

achievement of our

impact. We will use

indicator results,

including from custom

indicators, and

performance narratives

collected initiative-wide

to monitor progress and

system change along the

impact pathway reflected

in the Feed the Future

results framework, to

Feed the Future’s

ultimate goal of

sustainably reducing

global hunger, malnutrition and poverty; and to support adaptive management, decision-

making and resource allocation.

Country post teams, regional post teams, and Washington-based Feed the Future interagency

bureaus and offices are all referred to as Operating Units (OUs), and are “housed” under each

USG interagency partner that reports performance data for Feed the Future. OUs and their

implementing partners (IPs) use the Feed the Future standard indicators, appropriate custom

indicators, and performance narratives to manage, adapt and report on performance of

individual implementing mechanisms (IMs)

and to monitor progress towards applicable

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

An IM “is a means of implementing a project to achieve identified results, generally through the use of a legally binding relationship established between an executing

agency (generally a U.S. Government agency like USAID or a host government agency) and an implementing entity (contractor, grantee, host government entity, public

outcomes and impacts in country- and IM-specific impact pathways and logic models. In

addition, OUs and IPs use impact and performance evaluations to complement the monitoring

tools above as a vital component of the Feed the Future Monitoring, Evaluation, and Learning

(MEL) framework. Evaluation is not discussed in this handbook.

At the goal level, we will measure hunger, malnutrition, and poverty among the population in

Feed the Future target countries and in the Zone of Influence (ZOI). The ZOI is the targeted

sub-national regions/districts where the USG intends to achieve the greatest household- and

individual-level impacts on poverty, hunger, and malnutrition. In addition to tracking at the ZOI

level, tracking goal level indicators at the national level helps capture our contributions to

system-level change and better support partner countries in their attainment of the Sustainable

Development Goals (SDG). At lower levels of the results framework, indicators measure

results at the national or ZOI population level, agriculture and food system level, and among

project participants. Appendix 1 shows how the indicators are organized under the Feed the

Future results framework.

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The Feed the Future phase two indicators include two categories of indicators: standard performance

indicators and standard context indicators.&&

+6?58?78&><7327B?5:<&;58;:?627@&!

Standard performance indicators measure results for which OUs are held accountable and

against which annual or multi-year targets are set.

All standard performance indicators are required-as-applicable (RAA) to ensure consistency of

reporting and meaningful aggregation of results. The impact indicators of the goal and three

objectives of the Feed the Future Results Framework are applicable to and thus required for all

Feed the Future target country OUs. In addition, all OUs receiving Feed the Future funding are

required to report on all indicators at the intermediate result (IR) or cross-cutting intermediate

result (CCIR) level to which a Feed the Future-funded project

contributes results. In other

words, if an OU expects a project to generate results that are measured by the indicator, the

OU must establish a baseline, set targets, and report results for the indicator. (See Appendix 1

to identify which indicators are associated with the Feed the Future goal, objectives, IRs and

CCIRs).

The standard performance indicators fall into three categories, based on the level at which

data for the indicator are collected: (1) Implementing Mechanism (IM), (2) Zone of Influence

(ZOI), and (3) National. (See Table 1 below.)

158;:?627@&327&,<C;25?D&?58&ED2F?D&G72H<:6@!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

The term “project” is used broadly in this document, and includes what is called an “activity” in USAID.

10!

While some standard performance indicators are relevant to regional and global Washington-

based investments and should be adopted as appropriate, many are not. Given the unique

nature of regional and global investments, as outlined in the forthcoming Feed the Future

regional guidance, these IMs should be monitored using primarily custom indicators tailored to

each OU’s and IM’s specific theory of change as articulated through a logic model, and

therefore a set of standard regional indicators will not be developed at this time. The USAID

Bureau for Food Security (BFS) can assist regional and Washington-based OUs in!the

development of logic models and identification of indicators as needed. If multiple OUs identify

similar custom indicators, these may become standard indicators in future versions of this

Handbook.

1B>D<B<56;5C&.<:=?5;@BID<J<D&158;:?627@K These 26 indicators monitor progress and results of

specific IMs and represent results among the people and organizations who participate in the

project’s interventions. IM-level indicators are collected by IPs and reported annually across all

Feed the Future countries regardless of status. OUs should assign them to all IMs that are

expected to produce results measured by that indicator. All IM-level indicators should only

report results achieved in that reporting year; they are not reported cumulatively.

L'1ID<J<D&158;:?627@K There are 20 indicators that measure conditions among the population in

the ZOI, collected in target countries through a population-based survey. These are reported at

baseline and through interim surveys every three years thereafter. Ten of these indicators

measure impacts (and an outcome in one case) at the goal or strategic objective levels, and

thus are required for target countries because country plans require inclusion of all three

objectives. The remaining 10 are RAA, required for target countries only if programming is

relevant to the indicator. Aligned countries that choose to define a ZOI are encouraged to

monitor, set targets, and report on all relevant ZOI-level indicators.

ZOI indicators are also collected in resilience focus areas subject to recurrent humanitarian

crisis

, and by USAID’s Office of Food for Peace in development food security activity

programming areas

. Both of these geographic areas might overlap in part or in whole with the

target or aligned country ZOI, but a disaggregation of these areas is needed for other

management purposes.

*?6;25?D&158;:?627@K There are six indicators that represent national-level conditions. Four are

applicable to target countries, and two are applicable for all Feed the Future countries. See

Table 1. The four that are applicable only to target countries are only reported when data are

available from primary or secondary data sources. OUs are not required to directly fund data

collection for national-level indicators, however, investment in strengthening national data

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

In 2019, the countries with resilience to recurrent crisis areas will be Burkina Faso, Democratic Republic of Congo, Ethiopia, Haiti, Kenya, Mali, Niger,

Nigeria, Somalia, S. Sudan, Uganda and Zimbabwe.

In 2018, Food for Peace development programs are implemented in the resilience zones in Ethiopia, Niger, Mali, and Uganda; and in Bangladesh,

Burkina Faso, Burundi, Democratic Republic of the Congo, Guatemala, Haiti, Malawi, Madagascar, Nepal and Zimbabwe.!

11!

systems capacity to collect timely and quality data is encouraged to support the country’s

capacity to make informed policy, investment, and programmatic decisions.

Three national-level indicators are goal-level indicators of hunger, stunting, and poverty, and

are required for all target countries. These three are also Sustainable Development Goal

(SDG) indicators, against which countries set targets and monitor progress. Feed the Future is

designed to support countries in the achievement of their goals, and our targets for these

indicators will be the same as the countries’ SDG targets. Also required for target countries is

the value added in the agriculture and food system indicator. The employment indicator,

however, is RAA. Both indicators will be computed by the BFS and provided to the target

country OUs.

The final national-level indicator – exports of targeted commodities, and one multi-level

indicator - milestones in improved institutional architecture, are RAA for all Feed the Future

countries, and, if applicable, should be reported by Feed the Future OUs annually.

$;5M?C<&62&6=<&+0E&158;:?627@K&&As referenced above, we have included several SDG indicators in

the Feed the Future phase two set of indicators. An SDG indicator is defined as Tier one (“Tier

I”) if a definition exists and data for the indicator are available. Tier II indicators have been

defined, but data for them are not yet widely available. Tier III indicators still need to de

defined. All of our goal level SDG indicators are Tier I, while the context SDG indicators are a

mix of Tier I and Tier III. The metadata, i.e. PIRS, for Tier I and Tier II SDG indicators are

available at https://unstats.un.org/sdgs/metadata/.

Table 1: Feed the Future Performance Indicators by Level: Zone of Influence, National, and

Implementing Mechanism (53 total Performance Indicators)

Zone of Influence (20 of 53 indicators)

● EG-c Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP*

● EG-e Prevalence of moderate and severe food insecurity in the population, based on the Food Insecurity Experience Scale

(FIES)*

● EG-g Percent of households below the comparative threshold for the poorest quintile of the Asset-Based Comparative

Wealth Index*

● EG-h Depth of Poverty of the Poor: Mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line*

● EG.3-f Abbreviated Women's Empowerment in Agriculture Index*

● EG.3-h Yield of targeted agricultural commodities within target areas

● EG.3.2-a Percent of producers who have applied targeted improved management practices or technologies

● EG.4.2-a Percent of households participating in group-based savings, micro-finance or lending programs

● HL.8.2-a Percent of households with access to a basic sanitation service

● HL.8.2-b Percent of households with soap and water at a handwashing station on premises

● HL.9-a Prevalence of stunted (HAZ < -2) children under five (0-59 months)*

● HL.9-b Prevalence of wasted (WHZ < -2) children under five (0-59 months)*

● HL.9-d Prevalence of underweight (BMI < 18.5) women of reproductive age*

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

ZOI indicators marked with an asterisk (*) are required for Feed the Future target countries; the remaining ZOI indicators are required-as-applicable.

12!

● HL.9-i Prevalence of healthy weight (WHZ ≤ 2 and ≥-2) among children under five (0-59 months)*

● HL.9.1-a Percent of children 6-23 months receiving a minimum acceptable diet

● HL.9.1-b Prevalence of exclusive breastfeeding of children under six months of age

● HL.9.1-d Percent of women of reproductive age consuming a diet of minimum diversity

● RESIL-a Ability to recover from shocks and stresses index*

● RESIL-b Index of social capital at the household level

● RESIL-c Percent of households that believe local government will respond effectively to future shocks and stresses

National (6 of 53 indicators)

● EG-d Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP

● EG-f Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale

(FIES)

● EG.3-e Percent change in value-added in the agri-food system ("Ag GDP+")

● EG.3-g Employment in the agri-food system

● EG.3.1-c Value of targeted agricultural commodities exported at a national level

● HL.9-h Prevalence of stunted (HAZ < -2) children under five (0-59 months)

Multi-level (1 of 53 indicators)

● EG.3.1-d Milestones in improved institutional architecture for food security policy achieved with USG support

13!

Implementing Mechanism (26 of 53 indicators)

● EG.3-2 Number of individuals participating in USG food security programs

● EG.3-10,11,12 Yield of targeted agricultural commodities among program participants with USG assistance

● EG.3.1-1 Kilometers of roads improved or constructed as a result of USG assistance

● EG.3.1-14 Value of new USG commitments and private sector investment leveraged by the USG to support food security

and nutrition

● EG.3.2-2 Number of individuals who have received USG-supported degree-granting non-nutrition-related food security

training

● EG.3.2-7 Number of technologies, practices, and approaches under various phases of research, development, and uptake

as a result of USG assistance

● EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or

technologies with USG assistance

● EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance

● EG.3.2-26 Value of annual sales of producers and firms receiving USG assistance

● EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance

● EG.3.2-28 Number of hectares under improved management practices or technologies that promote improved climate risk

reduction and/or natural resources management with USG assistance

● CBLD-9 Percent of USG-assisted organizations with improved performance t

● EG.3.3-10 Percent of female participants of USG nutrition-sensitive agriculture activities consuming a diet of minimum

diversity

● EG.4.2-7 Number of individuals participating in USG-assisted group-based savings, micro-finance or lending programs

● EG.10.4-7 Number of adults with legally recognized and documented tenure rights to land or marine areas, as a result of

USG assistance

● EG.10.4-8 Number of adults who perceive their tenure rights to land or marine areas as secure with USG assistance

● ES.5-1 Number of USG social assistance beneficiaries participating in productive safety nets

● HL.8.2-2 Number of people gaining access to a basic sanitation service as a result of USG assistance

● HL.8.2-5 Percent of households with soap and water at a handwashing station on premises

● HL.9-1 Number of children under five (0-59 months) reached with nutrition-specific interventions through USG-supported

programs

● HL.9-2 Number of children under two (0-23 months) reached with community-level nutrition interventions through USG-

supported programs

● HL.9-3 Number of pregnant women reached with nutrition-specific interventions through USG-supported programs

● HL.9-4 Number of individuals receiving nutrition-related professional training through USG-supported programs

● GNDR-2 Percentage of female participants in USG-assisted programs designed to increase access to productive economic

resources

● RESIL-1 Number of host government or community-derived risk management plans formally proposed, adopted,

implemented or institutionalized with USG assistance

● YOUTH-3 Percentage of participants in USG-assisted programs designed to increase access to productive economic

resources who are youth (15-29)

14!

+6?58?78&:256<N6&;58;:?627@!

Standard context indicators provide information that helps to interpret performance results.

They are only required for target countries, but aligned countries are also encouraged to track

the population-level impact and outcome context indicators. Target country OUs are not held

accountable for changes in these indicators and no targets are set for context indicators. Data

should be reported as they become available from primary or secondary data sources; OUs

are not required to collect primary data for context indicators. Context indicators will be used in

standard processes like annual portfolio reviews and to interpret changes in the population-

based survey data captured at the national or ZOI level.

There are 25 standard context indicators. They are measured at the global (one indicator),

national (17 indicators), ZOI (five indicators) and resilience area/national (two indicators)

levels. USAID’s Bureau for Food Security will track the global food security and nutrition official

development assistance funding and ZOI-level agro-ecological indicators; all target countries

should track the national- and remaining ZOI-level context indicators and report on them when

data are available from primary or secondary data sources.

Two context indicators - of humanitarian need and assistance - are compiled by BFS and

tracked by OUs in selected countries with areas and populations subject to recurrent

humanitarian crisis, at the resilience zone level if data are available, otherwise at the national

level. See Table 2.

Table 2: Feed the Future Context Indicators by Level: Global, National, Zone of Influence, and

Resilience to Recurrent Crisis areas (25 total Context Indicators)

National (17 of 25 indicators)

● FTF Context-1 Percent of households below the comparative threshold for the poorest quintile of the Asset-Based

Comparative Wealth Index

● FTF Context-2 ** Average income of small-scale food producers, by sex and indigenous status (SDG indicator #2.3.2)

● FTF Context-3 ** Volume of production per labour unit by classes of farming/pastoral/forestry enterprise size (SDG indicator

#2.3.1)

● FTF Context-4 * Percentage of 15-29 year olds who are Not in Education, Employment or Training (NEET) (SDG indicator

#8.8.6)

● FTF Context-5 Prevalence of wasted (WHZ < -2) children under five (0-59 months)

● FTF Context-6 Depth of Poverty of the poor: Mean percent shortfall relative to the $1.90/day 2011 PPP poverty line

● FTF Context-10 Risk to well-being as a percent of GDP

● FTF Context-11 Yield of targeted agricultural commodities

● FTF Context-15 ** Proportion of agricultural area under productive and sustainable agriculture (SDG indicator #2.4.1)

● FTF Context-16 Prevalence of healthy weight (WHZ ≤ 2 and ≥-2) among children under five (0-59 months)

● FTF Context-17 Prevalence of underweight (BMI < 18.5) women of reproductive age

● FTF Context-18 * Prevalence of undernourishment (SDG indicator #2.1.1)

● FTF Context-19 Percent of children 6-23 months receiving a minimum acceptable diet

● FTF Context-20 Prevalence of exclusive breastfeeding of children under six months of age

● FTF Context-21 Percent of women of reproductive age consuming a diet of minimum diversity

● FTF Context-23 Share of agriculture in total government expenditure (%)

● FTF Context-24 Proportion of total adult rural population with secure tenure rights to land, (a) with legally recognized

documentation and (b) who perceive their rights to land as secure

15!

Zone of Influence (5 of 25 indicators)

● FTF Context-9 Percent of people who are ‘Near-

Poor’, living on 100 percent to less than 125 percent of

the $1.90 2011 PPP poverty line

● FTF Context-12 Average Standard Precipitation Index

score during the main growing season

● FTF Context-13 Average deviation from 10-year

average NDVI during the main growing season

● FTF Context-14 Total number of heat stress days

above 30 °C during the main growing season

● FTF Context-25 Percent of women achieving

adequacy across the six indicators of the Abbreviated

Women’s Empowerment in Agriculture Index

Recurrent crisis areas (if data not

available, National) (2 of 25

indicators)

● FTF Context-7 U.S. government

humanitarian assistance spending in

areas/populations subject to recurrent

crises

● FTF Context-8 Number of people in

need of humanitarian food assistance

in areas/populations subject to

recurrent crises

Global

(1 of 25 indicators)

● FTF Context-22

Food security and

nutrition funding as

reported to the

OECD DAC

* Indicates an SDG indicator in TIER I status, i.e. a definition exists and data for the indicator are available.

** Indicates an SDG indicator in TIER II status, i.e.!a definition exists but data are not regularly produced by

countries.

)9@62B&158;:?627@!

Feed the Future’s standard performance indicators are designed to capture key steps in the

theory of change as reflected in the Feed the Future results framework, with an emphasis on

outcome and impact indicators. However, each OU should have its own prospectively

designed and continuously updated detailed logic model that clearly articulates how its

activities lead to the desired outputs, outcomes, and impacts. It is unlikely that the set of

standard Feed the Future performance indicators will be sufficient to monitor progress along

that logic model, and to support learning and adaptation at an OU or IM level; therefore,

custom indicators should be used.

Custom indicators and custom disaggregates under standard indicators will likely be needed to

capture key steps in the OU’s context- and intervention-specific logic model, although each

step does not necessarily require an associated indicator. OUs and their partners can develop

new custom indicators. They should also consider using ZOI-level indicators or proxies for

those indicators as custom indicators to monitor key outcomes and impacts among project

participants. For example, a poverty assessment tool based on population-based poverty data

could be used to quantify a proxy indicator for poverty prevalence for IMs that are aiming to

reduce poverty among participants. This can strengthen the plausible association between

results among participants and changes measured at the ZOI level. Finally, OUs and IPs could

use archived indicators from Feed the Future phase one; these indicators are listed in

Appendix 2 for reference, and their definitions can be found in the old publication of the July

2016 version of the Handbook (https://feedthefuture.gov/resource/feed-future-handbook-

indicator-definitions). The forthcoming guidance on monitoring for inclusive market system

development will also contain a list of suggested custom indicators for market system

facilitation activities.

16!

0?6?&@297:<@&327&L'1&;58;:?627@&!

The preferred source of data for the ZOI population-based indicators is primary data collected

via a representative population-based survey conducted in the ZOI

using the Feed the Future

ZOI Survey Guidance and Survey Methods Toolkit,

hence collecting data for all applicable

ZOI indicators in a single survey instrument.

1B>D<B<56;5C&.<:= ? 5;@ B&;58;:?627@&O1.P!

1.&;58;:?627&95;J<7@<&;@&>72H<:6&>?76;:;>?56@&

IM-level indicators measure results obtained with participants, defined as individuals,

enterprises, organizations, and other entities that participate in Feed the Future projects,

including those reached directly, those reached as part of a deliberate service delivery

strategy, and those participating in the markets we strengthen.

An individual or entity is a

participant if she/he/it comes into direct contact with the set of interventions (goods or services)

provided or facilitated by the project. The intervention or set of interventions needs to be

significant. An intervention is significant if one can reasonably expect, and hold OUs and IPs

responsible, for achieving measurable progress toward changes in behaviors or other

outcomes for individuals or entities receiving or accessing the goods or services provided by

the intervention. As an example, producers with increased access to goods, services, and

markets for their products and who purchase from or sell to market actors that have been

strengthened as a result of our projects are considered to have received a significant

intervention, and therefore are considered participants of market strengthening projects.

However, if a person or entity is merely contacted or touched by a project or activity through

attendance at a meeting or gathering, she/he/it should not be considered a participant.

IPs must consider as participants and report results for the producers who directly interact with

the firms assisted by the project (e.g. the producers who are customers of an assisted agro-

dealer, the producers from whom an assisted trader or aggregator buys). IPs are not required

to monitor and report on customers or suppliers who are not producers (e.g. other types of

customers of assisted market actors that do not buy from or sell directly to producers). We

direct IPs to take this approach in order to reduce their reporting burden in the already-

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

USAID's Office of Food for Peace development food security activity programming areas may or may not overlap in part or in whole with the target or

aligned country ZOI.

See https://agrilinks.org/post/feed-future-zoi-survey-methods.

The definition of the universe covered by IM-level indicators has not fundamentally changed from Feed the Future phase one. We changed from using

the term project “direct beneficiaries” to using the term project “participants” to describe the universe captured by IM-level indicators to better align with

market system-based approaches. The revised terminology also more clearly communicates that those with whom we work are active participants in their

country’s development journey, to their own and others’ benefit.

The exception are IM indicators that count results directly achieved by the project, e.g. EG.3.1-1 Kilometers of roads improved or constructed as a result

of USG assistance, rather than results achieved with project participants.!

17!

challenging market system facilitation project monitoring context. However, we still want to

capture information on the group - producers - that is critical to reach and about which we are

most concerned on our likely pathways to impact. We recognize that allowing for the exclusion

of other types of customers and suppliers from our reporting may underestimate our total

impact.

In cases where projects work with multiple individuals in a household, IM indicators only

measure results for the participants in the household, not all of the members of the household.

The only exception is in the case of sanitation services and family-sized rations, where all

members of the household receiving the sanitation facility or ration are considered project

participants.

G?76;:;>?56@&A=2&67?;5&26=<7&>?76;:;>?56@&

Individuals who are trained by an IM as part of a deliberate service delivery strategy (e.g.,

cascade training) should be counted as participants of the activity—the capacity strengthening

is key for sustainability and an important outcome in its own right. As these participants then

go on to deliver services directly to individuals, or to train others to deliver services, the

individuals who receive the services or training delivered by the original participants should

also be considered participants (with the exception of the non-producer customers or suppliers

in the market system strengthening project context mentioned above).

)2956;5C&;58;J;89?D@&A=2&>?76;:;>?6<&;5&B27<&6=?5&25<&(<<8&6=<&(9697<&>72H<:6&&

Individuals can benefit from more than one intervention under a Feed the Future project. For

example, a producer who is purchasing inputs from an assisted firm may also be participating

in community-level nutrition interventions implemented by an integrated agriculture-nutrition

project. We expect IPs to track or estimate the number of individual participants across

different interventions within their own project and to report numbers of participants under

relevant indicators, not number of contacts with the project. Where multiple Feed the Future

projects are reaching and reporting on the same population, OUs reporting aggregated OU-

level results should track and/or estimate the extent of double-counting, and adjust the OU

total prior to reporting.

We do not at this time have any recommended tools or approaches to eliminate double-

counting of participants, other than that described in the HL.9-1 children under five reached by

nutrition-specific interventions indicator PIRS. However, where an OU has activities that are

targeting the same population, we would expect that they are co-locating and coordinating

across work plans, and that there should be a good sense on the ground of the extent of

overlap of participants, in part because it should be deliberate and planned for in the logic

model.

Where IMs from more than one OU are targeting the same population, e.g. where a bilateral

OU is funding a centrally-managed project to work with bilateral OU’s project, the bilateral OU

could coordinate with the central OU and agree that the bilateral project will be responsible for

18!

collecting data and reporting on all of the farm-level indicators or disaggregates, and that the

centrally-managed IM will restrict its reporting only on outputs and outcomes among actors

with whom they work directly.

158;7<:6&F<5<3;:;?7;<@&

Spontaneous spillover of improved practices to neighbors does not count as a deliberate

service delivery strategy; neighbors who apply new practices based on observation and/or

interactions with participants who have not been trained to extend knowledge to others as part

of a deliberate service delivery strategy are not considered participants and should not be

included under IM-level indicators. This is because IM-level indicators do not measure results

among the indirect beneficiaries of our activities. An indirect beneficiary is someone who does

not have direct contact or interaction with the project or the actors whom the project is

supporting, but still benefits. This includes the population that uses a new road constructed by

the project, neighbors who see the results of the improved technologies applied by direct

participants and decide to apply the technology themselves, or individuals who are only lightly

touched by a project intervention, such as someone who hears a project-supported radio

message but receives no training or counseling nor has any further interaction with the project

or project-supported actors.

Accurate tracking of indirect beneficiaries is challenging by nature, despite the fact that

spillover is a core component of the Feed the Future theory of change. In general, spillover is

captured in Feed the Future through measuring changes in ZOI population-level indicators

(e.g. Percent of producers who have applied targeted improved management practices or

technologies) and through performance and impact evaluations. We also encourage the use of

custom indicators to track changes specific to the project’s theory of change that go beyond

direct participants. This may include using innovative primary or secondary data sources or

methods.

.<?@97;5C&7<@9D6@&23&B?7M<6&@Q@6<B&@67<5C6=<5;5C&>72H<:6@&

Feed the Future, guided by the GFSS, places strong emphasis on inclusive and sustainable

market system development to achieve its goal of sustainably reducing poverty, hunger, and

malnutrition. Inclusive and sustainable market system development approaches work to

improve three key components: a core market, supporting functions, and the formal and

informal rules governing interactions. These facilitative approaches aim to address the

underlying causes of poor performance in specific markets that matter to people living in

poverty in order to create lasting changes that have a large-scale impact.

Inclusive and sustainable market system development presents challenges in monitoring for

scale and breadth of impact. Oftentimes the producer we are aiming to assist (e.g. a

smallholder farmer) is not the actor with whom we work directly (e.g. a manufacturer), although

both are considered project participants. Rules of the market system are governed by the

relationships and incentives of market players, and are dynamic, complex, and hard to

quantify. Feed the Future indicators described in this handbook capture some of the outcomes

19!

of market system development. However, understanding the process of systemic change (the

“how” to the “what”) is also critical to our learning and will require use of custom indicators.

As a result, Feed the Future is promoting a multi-pronged approach to monitor market systems

change that provides the space and tools necessary to measure progress.

● We promote mixed methods monitoring to measure market system changes to

accommodate the size, complexity, and context of the market system. To better

understand the depth and scale of impact due to facilitated interventions in the market

systems, programs are encouraged to look at qualitative methods, such as system

mapping, outcome harvesting, and most significant change stories.!

● The new set of indicators better reflects the results of some aspects of market systems

development work. This includes a heavier focus on national-level indicators as well as

other indicators that can help show the impact of some of the facets of a stronger

market system.!

● Adding custom indicators and indicator disaggregates will be necessary to track the

specific results sought in a project’s theory of change. This is especially important since

all projects should be designed to strengthen markets, and the set of standard

indicators presented in this Handbook only capture a portion of the changes seen in a

market system. BFS and the interagency are working on developing essential guidance

and examples that will assist missions to measure market systems changes. This

guidance will be made available later in the year.!

)2DD<:6;5C&;58;:?627&8?6?&25&>7289:<7&>?76;:;>?56@&23&B?7M<6&@Q@6<B&@67<5C6=<5;5C&>72H<:6@&

Monitoring results for producer participants reached through market-strengthening projects can

be particularly challenging. This is because IPs typically use a facilitative approach, where

products and services are delivered to producers by assisted private sector firms. The firms

are the logical source of information about the producers to whom they sell and from whom

they purchase, but they may not have comprehensive customer or supplier lists or may not

want to share the information. Building a loyal customer and supplier base, which is a

profitability strategy promoted by many value chain activities, is greatly facilitated if a list of

customers and suppliers is available. So helping assisted firms to set up and maintain such

lists has both programmatic and M&E benefits and is encouraged. Data provision by assisted

firms can be facilitated by entering into written agreements that include reporting and non-

disclosure requirements

and by helping assisted firms understand the business case for

collecting the information.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Nondisclosure agreements must allow access to the data for USG-funded performance and impact evaluations.

20!

Measuring results among producer participants should be more straightforward if the market-

strengthening project is also facilitating extension strategies, e.g. assisting agro-dealer agents,

who need to know where their customers live and farm. Extension and other customer

outreach approaches are important to reinforce advice provided by the agro-dealer to her/his

customers, or to provide the repeated contacts with smallholder producers needed for them to

successfully apply the improved technologies and management practices promoted by the

activity.

If collecting the data from assisted firms required for some indicators is not possible, IPs

should consider the concept of a "market shed"

or "catchment area" to identify the

geographic area that defines the population to be reached by the market being strengthened,

and then conduct a survey among that population of producers who are participating in the

market, and thus would be considered project participants. For example, a project is

encouraging agro-dealers to use community agents to bring fertilizers closer to the target

population and thus expanding the market shed of these fertilizer suppliers. The project could

define the geographic area as the expanded market to be reached over time, and use surveys

to collect baseline and annual data for applicable producer-level indicators from the population

in that geographic area.

158;:?627 &0 ;@? C C 7< C ? 6< @ &&

Reporting of disaggregates is required for all indicators. Targets should be set for IM-level

indicators at the overall indicator and the disaggregate level. Targets are not required for the

ZOI-level indicator disaggregates; they are only required at the overall indicator level.

E<2@>?6;?D&8?6?&

Geospatial data that identify the location of our activities are extremely useful for performance

analysis, particularly for examining where results are or are not achieved, whether

environmental or climatic factors are affecting performance, and how activity results compare

to impact-level results in the ZOI. Use of custom location disaggregates allow OUs and IPs to

understand the spatial distribution of indicator results. In addition, IPs are required to track and

enter geocodes or geospatial coordinates for their activities in the Feed the Future Monitoring

System (FTFMS), as appropriate within security considerations. The location data component

of FTFMS has greatly improved from previous years, in that it now allows for entry of location

data down to the more-granular Admin 5 level, as well as lat/long coordinates, the ability to

“bulk upload” several location data points at once through use of a standard template, and the

ability to export all location data in machine-readable form for ease of pulling into a mapping

platform, such as ArcGIS Online (“AGOL”), etc. Trainings on data entry and use of these new

location features will be provided, including a “How to” video on the FTFMS Resources website

(https://agrilnks.org/ftfms.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

See, for example, http://harvestchoice.org/labs/market-sheds!

21!

!=<&(<<8&6=<&(9697<&.25;627;5C&+Q@6<B&O(!(.+P&

The Feed the Future Monitoring System (FTFMS) is part of an interagency effort to consolidate

USG reporting on Feed the Future projects. FTFMS indicator data and performance narratives

are the official results for Feed the Future. They provide the foundation for public documents

like the Feed the Future Progress Report and they inform decisions on future programming,

policy planning, and budget allocations. Eleven USG agencies partner on food security efforts

for Feed the Future and six of those agencies have historically contributed data to FTFMS,

including the U.S. Agency for International Development (USAID), the U.S. Department of

Agriculture (USDA), the Millennium Challenge Corporation (MCC), Peace Corps, the U.S.

African Development Foundation (USADF), and the Department of Treasury, which manages

our USG contributions to the Global Agriculture and Food Security Program (GAFSP) and the

International Fund for Agricultural Development (IFAD). All partner agencies, even if they do

not contribute indicator data to the FTFMS, write an annual Global Agency Performance

Narrative (GAPN) that is included in the annual Implementation Plan submitted to Congress

each fall, per the Global Food Security Act of 2016.

Each USG partner agency has a different organizational structure, and therefore reports into

FTFMS at varying levels. For example, USAID enters data into FTFMS at the activity level (via

"Implementing Mechanisms" or "IMs"), while other agencies may report at the post, project, or

global level.

As mentioned above, OUs and IPs should design and use custom indicators as a way to better

capture progress toward objectives and outcomes that are not fully covered by the standard

indicators. FTFMS allows for the uploading of documents that contain custom indicator

information (e.g. baseline, targets, actuals), and OUs and IPs are strongly encouraged to do

so. While archived indicators will continue to be included in FTFMS and can be assigned to

IMs as custom indicators, other custom indicators cannot be programmed into FTFMS at this

time. We are working to redesign FTFMS to more easily incorporate custom indicators and

disaggregates in addition to the standard indicators, and any progress on this effort will be

communicated.

%56<7;5C&L'1&G#+&;58;:?627&8?6?&;5&(!(.+!

Feed the Future target countries, and possibly some aligned countries, have a focused

geographic area, the ZOI, where the population-based survey is conducted to monitor ZOI

indicators. Countries with populations subject to recurrent crisis and/or Food for Peace (FFP)

development programming also have geographic areas in which programming is targeted and

ZOI indicator data are collected, which may or may not overlap with the ZOI in target or aligned

countries. FTFMS allows for data entry for each ZOI indicator under three programming areas:

1) Target (or aligned) country ZOI, 2) FFP development program area, and 3) Resilience to

recurrent crisis areas. OUs or their M&E contractors should enter ZOI indicator values and

population numbers under the appropriate area type.

22!

Values for the ZOI indicators are entered into FTFMS by the OU or the OU’s survey

implementer under the mechanism titled “High Level Indicators – [COUNTRY NAME]”, which is

pre-programmed into FTFMS for each OU. In addition to entering the ZOI indicator values, the

estimated total population and population by disaggregate categories must be entered for the

relevant programming area. For example, the prevalence of poverty indicator measures the

percent of people in the ZOI with average per capita consumption under $1.90/day. The

relevant population numbers to enter are the estimated total population of individuals in each

gendered household type for the relevant programming area (Target/Aligned Country ZOI,

FFP, or resilience programming area). In contrast, the prevalence of households with

moderate or severe hunger measures the percent of households, not individuals, so the

relevant population numbers to enter are the estimated number of households of each

gendered household type in the ZOI, FFP, or resilience programming area. Stunting,

underweight, and wasting are all measured for children under 5. The relevant population

numbers to enter are the estimated number of male and the estimated number of female

children under 5 years of age in the ZOI, FFP, or resilience programming area. It is important

that OUs ensure that information on the population in the ZOI, FFP, or resilience programming

area under the different ZOI indicator disaggregates is provided by the survey implementer.

Use of the mandatory ZOI Survey Report Template

will ensure that all required information is

included in the report.

Note: Sometimes sample surveys are used to collect data for IM-level indicators, and in this

case IPs must ensure that survey estimates are appropriately sample-weighted (weights are

applied to “sample estimates” to generate “population estimates”) and, where necessary,

extrapolated to the total participant level prior to entering the data into FTFMS under their

specific IM (not under the “High Level Indicators – [COUNTRY NAME]” mechanism, which is

only reserved for reporting on OU-level totals).

%56<7;5C&5?6;25?DID<J<D&;58;:?627&8?6?&;5&(!(.+ !

As described above for ZOI population-based indicators, estimated population numbers are

also required when entering national-level population-based performance and context

indicators into FTFMS. In addition, OUs should include the source of the national-level data

and the year the data were collected in an Indicator Comment. This information is needed

because national-level data collected in a different year or with a different method from the ZOI

data may not be comparable and differences between them must be interpreted with caution.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

See https://agrilinks.org/post/feed-future-zoi-survey-methods.

23!

!7?5@;6;25;5C&62&6=<&(<<8&6=<&(9697<&>=?@<&6A2&;58;:?627@

Existing IMs that end on or before September 30, 2019 are not required to shift to the phase

two indicators, although they are encouraged to adopt new indicators if feasible. Existing IMs

that end after September 30, 2019 are required to adopt all applicable new indicators, working

with their A/CORs and AO/CO to make the transition in accordance with their agreement or

contract. New IMs (i.e. those awarded in late 2017 or later) are required to use all applicable

new indicators.

IMs and OUs were required to set FY19, FY20, and FY21 targets for the new indicators during

the FY18 results reporting in October 2018. IMs and OUs will be required to report FY19

results for the new indicators when FTFMS opens for FY19 results reporting in October 2019.

If IMs or OUs had FY18 results to report for any of the new indicators in October 2018, they

were highly encouraged to do so, as long as the results being reported fully aligned with the

new indicator definitions. For indicators that are revised from phase one as opposed to

completely new, IMs or OUs should only report on one version of the indicator in any given

year to avoid double-counting, and should only report on the revised indicator or disaggregate

if reporting fully aligns with the definition. See the list of these ‘pairs’ of old indicators that have

revised versions in the new set, plus a full list of all the indicators and what happened during

the transition in Appendix 2, as well as at this link:

https://www.agrilinks.org/sites/default/files/quick_reference_pairs_of_fy18_indicators_and_not

es_on_all_indicators_fy18.xlsx.

If existing IMs adopting new outcome indicators can provide a baseline from existing data on

old indicators, they should do so, entering the appropriate source year of the data from the old

indicator as the baseline year for the new indicator. See Appendix 2 for a list of Feed the

Future phase one indicators that could inform the baseline for Feed the Future phase two

indicators. Otherwise, existing IMs adopting new outcome indicators can leave the baseline

information blank.

! &

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

USAID FFP has a different timeline for indicator transitioning and will communicate with implementing partners directly.!

24!

+9BB?7Q&6?FD<&23&6=<&67?5@;6;25T!

Type / Age of

Implementing

Mechanism (IM)

What was done in FTFMS for FY

2018

(Oct/Nov 2018)

What to do in FTFMS for FY 2019

(Oct/Nov 2019)

Already-awarded and

operating IMs that end

on or before

September 30, 2019

• Report results achieved during FY2018

on the current set of old (i.e. Feed the Future

phase one) indicators

• Set targets for any remaining project

years on the current set of old indicators

• Report results and set targets on the existing

set of old indicators until the IM ends

Already-awarded and

operating IMs that end

after September 30,

2019

• Report results achieved during FY2018

on the current set of old indicators

• Report results achieved in FY2018 on any

new (i.e. Feed the Future phase two)

indicators if complete indicator definition is met

• Set targets for any remaining project

years on the set of new FTF phase two

indicators

• Set targets for any remaining project

years on any old indicator on which the IM

wishes to continue reporting (then delete

remaining old indicators from FTFMS)

• Report results achieved during FY2019 on

the new set of FTF phase two indicators

• Set targets for remaining project years on the

new set of FTF phase two indicators

• Report results and set targets on any

continued reporting on any old indicator on which

the IM wishes to continue reporting

(1)

New activities that

haven't ever reported

on old indicators

(1, 2)

• Report results achieved during FY2018

(2)

on the new set of indicators

• Set targets set for out-years on new set of

indicators

• Continue reporting results and targets on the

new set indicators

(1) Old indicators will still be available in FTFMS, but would be considered custom, if used.

(2) New activities or IMs, depending when they started, may not have results achieved during FY2018 to report on, but

should still set targets for the out-years and begin reporting results in FY19, or as early as applicable.

25!

)=?5C<@&62&6=<&(<<8&6=<&(9697<&>=?@<&25<&;58;:?627@&6=?6&A;DD&:256;59<&62&

F<&7<>276<8&958<7&(<<8&6=<&(9697<&>=?@<&6A2&

See Appendix 2 for a list of changes and clarifications to Feed the Future phase one indicators

that will continue to be reported on under phase two. Where changes to the indicator

definitions are such that it is not!appropriate to compare results reported under the phase one

indicator to results reported under the phase two indicator, the phase two indicator has been

assigned a new number, and the phase one indicator has been dropped.

(27<;C5&"@@;@6?5:<&+6?58?78&158;:?627&?58&G<7327B?5:<&GD?5&?58&,<>276&

OGG,P&,<> 27 6;5C &(U SA ID 'o n ly)&

ZOI- and national-level indicators do not appear in the F Master List of PPR Indicators for

selection by OUs, even though they follow a similar numbering scheme for consistency. OUs

can include them in the PPR as custom indicators. These indicators are included in FTFMS,

however, and Feed the Future target country OUs, and aligned country OUs if applicable,

should report on all required and RAA ZOI- and national-level indicators under the mechanism

titled “High-Level Indicators [COUNTRY NAME]”, available for each OU in FTFMS.

BFS and the Bureau for Global Health will assign IM-level indicators to the OUs in the PPR

based on their programming and Mission objectives. OUs can opt out of reporting on these

indicators in the PPR by providing a justification as to why the indicator is not applicable. OUs

are encouraged to report on appropriate custom indicators in the PPR.

While indicators are reported at the IM-level in FTFMS, they are only reported at the

aggregated OU-level in the PPR, i.e. the contributions of all activities’ results for an indicator

summed up for an OU total. FTFMS provides a PPR report that does this aggregation

automatically so that data can more easily be copied and pasted into the PPR. Note, however,

that this aggregation simply adds up all results from contributing IMs for each indicator. It does

not remove any double-counting of results in cases where more than one IM is reporting

results for the same participants. For example, if one IM is providing training in application of

improved agronomic practices and a second is strengthening traders and aggregators, the

same producers could be participating in both projects and being counted twice. OUs should

adjust for any double-counting before entering the aggregated total for the indicator into their

PPR.

158;:?627 @&? 5 8 &.<?@97< @ &U 5 8 < 7&0<J<D2> B<56&

Several indicators and other measures were put into a “Placeholder” or “Under Development”

category during the development of this new Handbook. Here are brief status updates on

each of those:

26!

G2D;:Q&.?67;N

A Country Policy Progress Indicator is under development to measure the progress a country

has achieved in completing prioritized policy changes that will accelerate agriculture and food

system growth and transformation. The measure will be based on empirical data detailed in

the 12 Feed the Future target country policy matrices developed in concert with policy

stakeholders in each country. The policy progress indicator value will be computed using data

on the level of progress for each policy action reported in the policy matrix on an annual basis:

on hold, behind target, on target, or complete. This policy progress indicator complements

indicator “EG.3.1-d Milestones in improved institutional architecture for food security policy

achieved with USG support [Multi-level]”, which looks at milestones toward an improved policy

system. The two indicators will relate the performance of the policy system with actual policy

changes, including both development and implementation of priority policies.

,<@;D;<56&+Q@6<B@

We are working with several stakeholders to conceptualize and identify indicators for different

dimensions of a resilient agri-food system, particularly related to resilient markets, risk

management, and ecological systems. We have added the World Bank indicator 'Risk to Well-

Being' as a context indicator, and continue to work on identifying indicators for market system

resilience and ecological systems resilience.

)?>697;5C&8;>D2B?6;:&<33276@&J;?&5?77?6;J<&!

Diplomatic efforts by the USG on food security are critical to the success of the initiative, even

though executed and measured differently than traditional development activities.

We had originally proposed an indicator “Value of funding to support food security and nutrition

committed through bi-, tri-, and multi-lateral partnerships in which the USG participates [IM or

Partnership-level]”, but have decided to drop that indicator as one not best-suited for capturing

the nuances and complexities of our diplomatic work. Instead, we will collect results of our

diplomatic efforts in narrative form, which will ensure the information is systematically and

institutionally captured as part of the formal MEL system.

Specifically, our commitment to tracking results of global diplomatic work through other

avenues will include a narrative overview on the work done by the State Department’s Office of

Global Food Security (S/GFS) and a dedicated section in the GFSS Implementation Report on

the results the USG achieved during the previous year through global diplomatic efforts, similar

to what was included in the 2018 Global Engagement Report here:

https://www.feedthefuture.gov/resource/u-s-government-global-food-security-strategy-

implementation-report-of-2018/ (see pp. 32-34 highlighting multilateral efforts).

We can build on this example to make sure that each year we are showcasing the vital

contributions Feed the Future agencies and departments make in advancing the global

agenda.

27!

G%,(',."*)%&1*01)"!',+

28!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Goal: Sustainably reduce global hunger, malnutrition, and poverty

INDICATOR TITLE: EG-c Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP [ZOI-level]

DEFINITION:

This GFSS goal-level indicator is one of the measures of the Sustainable Development Goal 1 (SDG 1) “End Poverty in all its forms

everywhere”. Also called the poverty headcount index, it measures the proportion of the population that is counted as poor:

Where is the number of people in the population, is the per capita consumption (or income) of individual “i” in the population, and

z is the poverty line. I is an indicator function equal to one if the expression in parentheses is true and zero otherwise.

So, if consumption of an individual is less than the poverty line, she/he is counted as poor, while if it is equal or above the poverty line,

she/he is not counted as poor.

The applicable poverty line is $1.90 per person per day at 2011 PPP, which is the current international extreme poverty line (the $1.90

per person per day at 2011 PPP has replaced the $1.25 at 2005 PPP in 2015). The indicator follows the World Bank PovCalNet

methodology to measure poverty in individual countries in a way that is comparable across countries. See Ferreira et al. (2015)

for more

details on the current methodology and explanations on how the methodology was adjusted over time.

The indicator uses household-level consumption data from a ZOI representative household survey. Hence, while the indicator reports the

percent of people in the ZOI that are poor, data are actually not collected at the individual level. Instead, average daily consumption of a

household is divided by the number of household members to come up with an average daily per capita consumption estimate for the

household. In this approach, every household member is assumed to have an equal share of total consumption, regardless of age and

potential economies of scale. In practice, the indicator is calculated by dividing the total sample-weighted number of people in poor

households by the total sample-weighted number of people in all sample households with consumption data. The result is multiplied by

100 to get a percent.

Consumption data are usually used instead of income data because of the difficulty in accurately measuring income, and because

consumption is easier to recall and more stable over time than income, especially among agricultural households. Data are collected

using the household consumption module of either the Living Standards Measurement Survey (LSMS) or the Feed the Future ZOI survey

depending on the vehicle used to collect the population-based indicators. Through the survey, data on consumption are collected on food

and non-food household items, whether purchased or produced by the household, durable goods use and replacement value, and housing

costs and characteristics (for more details, see the Feed the Future ZOI survey consumption module from the core questionnaire

(Reference: https://agrilinks.org/post/feed-future-zoi-survey-methods). A consumption aggregate is calculated by summing all household

consumption, valued in local currency after bringing them to a common recall period (as the relevant time frame varies between the

different consumption categories). Durable goods are incorporated into the consumption aggregate by estimating a value of services that

the household derives from the durable goods over the time period, as the appropriate measure of the consumption of these goods.

Similarly, housing is included in the aggregate by estimating or imputing a rental value of the dwelling used by the household, whether it is

owned, rented, or otherwise occupied. For more details on the calculation of the consumption aggregate, see Guide to Feed the Future

Statistics (Reference: https://agrilinks.org/post/feed-future-zoi-survey-methods).

Individual household average daily per capita consumption is compared to the international poverty line of $1.90 2011 PPP to determine if

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Ferreira, F., et al., A Global Count if the Extreme Poor in 2012: Data Issues, Methodology, and Initial Results, World Bank Policy Research Working

Paper #7432, October 2015: https://openknowledge.worldbank.org/handle/10986/22854

29!

a household is poor (consumption falls below the poverty line) or non-poor (consumption is equal to or above the poverty line). To do the

comparison, the international poverty line must be converted to the country local currency unit (LCU) using the 2011 Purchasing Power

Parity (PPP) exchange rate. Using exchange rates based on PPP conversion factors (instead of market exchange rates) allows adjustment

for price differences between countries, such that a dollar has the same purchasing power across countries. The 2011 PPP conversion

factors for Feed the Future target countries are presented in Table 1 below. These were obtained from the World Bank, World

Development Indicators: http://databank.worldbank.org.

The $1.90 poverty line converted to local currency using the 2011 PPP must then be converted to the local prices prevailing the year, and

month of the survey using the country’s Consumer Price Index (CPI). The government official source for CPI data should be used.

To calculate the local currency equivalent to the $1.90 poverty line at the prices prevailing during the year of the survey, the general

formula is as follows:

Where the subscript ‘t’ refers to the year, or month and year as relevant, when the survey was conducted.

RATIONALE: This indicator is one of the measures for the goal of the Global Food Security Strategy to: “Sustainably reduce global hunger,

malnutrition, and poverty”. All three objectives and underlying intermediate results and cross-cutting intermediate results seek to contribute

one way or the other to reduce poverty in the GFSS Zone of Influence. This indicator allows for comparison across countries and for

tracking the number of poor in the population targeted by USG interventions. This indicator is one of the SDG 1 “End Poverty in all its

forms everywhere” indicators and is linked to the Global Food Security Strategy Goal: Sustainably reduce global hunger, malnutrition, and

poverty.

UNIT:

Percent

DISAGGREGATE BY:

Gendered household type:

Male and Female Adults (M&F), Adult Female No Adult Male (FNM), Adult Male No Adult Female

(MNF), Child No Adults (CNA)

TYPE: Impact

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected from a random sample of households in the ZOI (i.e. the targeted

sub-national regions/districts where the USG intends to achieve the greatest household-

and individual-level impacts on poverty, hunger, and malnutrition.)

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Primary data: The national statistics office under the LSMS-ISA+ national data systems strengthening

activity or an M&E contractor.

Secondary data: M&E contractor or Post staff

 DATA SOURCE:

Primary data: Primary data are collected via a population-based survey conducted in the ZOI using the

Feed the Future Survey Methods Toolkit (https://agrilinks.org/post/feed-future-zoi-survey-methods)

Secondary data: National poverty survey, if the data were collected within the previous two

years. Location variables are used to identify records corresponding to the ZOI in the secondary data

set, and the secondary data analysis is then conducted using those records.

30!

 FREQUENCY OF

COLLECTION:

Data should be collected at baseline, and during each subsequent ZOI-level population-based survey

thereafter.

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where the USG

intends to achieve the greatest household- and individual-level impacts on poverty, hunger, and

malnutrition),

2) Office of Food for Peace development program areas, and

3) Resilience to recurrent crisis areas.

 BASELINE INFO:

A baseline is required, and the value is from the FTF phase two baseline ZOI survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter ZOI-level values under the “High Level Indicators – [COUNTRY NAME]”

mechanism in the FTFMS.

• Enter the year that data were collected in the field under the Indicator Comment. If field data collection spanned two years, enter

the year field data collection began.

• Enter the value of the prevalence of poverty at the $1.90 2011 PPP threshold for the overall indicator and for each GHHT

disaggregate category under the appropriate ZOI/area category (Target or Aligned Country ZOI, FFP development program

area, or Resilience to recurrent crisis area).

• Enter the total number of people in the ZOI/area and for each GHHT disaggregate category in the appropriate ZOI/area category

(Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area),

For example, a GFSS Target Country entering data from the Feed the Future ZOI baseline survey would enter:

1. Year of field data collection in the Target Country ZOI [in the Indicator Comment]

2. Sample-weighted percent of people living on less than $1.90/day 2011 PPP in the Target Country ZOI

3. Total number of people in the Target Country ZOI

4. Sample-weighted percent of people in M&F households living on less than $1.90/day 2011 PPP in the Target Country ZOI

5. Total number of people in M&F households in the Target Country ZOI

6. Sample-weighted percent of people in FNM households living on less than $1.90/day 2011 PPP in the Target Country ZOI

7. Total number of people in FNM households in the Target Country ZOI

8. Sample-weighted percent of people in MNF households living on less than $1.90/day 2011 PPP in the Target Country ZOI

9. Total number of people in MNF households in the Target Country ZOI

10. Sample-weighted percent of people in CNA households living on less than $1.90/day 2011 PPP in the Target Country ZOI

11. Total number of people in CNA households in the Target Country ZOI

31!

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

___________________________________

* To inflate/deflate the national poverty line to the ZOI survey year, multiply the value by the CPI ratio as follows:

Where is the year of the survey used by the host country government to calculate the national poverty line and is the ZOI

survey year.

Table 1: PPP 2011 Conversion Factor, Private Consumption

(LCU per international $)

GFSS Target Countries

PPP 2011

Bangladesh

24.849

Ethiopia

5.439

Ghana

0.788

Guatemala

3.873

Honduras

10.080

Kenya

35.430

Mali

221.868

Nigeria

79.531

Niger

228.753

Nepal

25.759

Senegal

246.107

Uganda

946.890

Source: World Bank, World Development Indicators, Updated 11/15/2017

32!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Goal: Sustainably reduce global hunger, malnutrition, and poverty

INDICATOR TITLE: EG-d Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP [National-level]

DEFINITION:

This GFSS goal-level indicator is one of the measures of the Sustainable Development Goal 1 (SDG 1) “End poverty in all its form

everywhere”. Also called the poverty headcount index, it measures the proportion of the population that is counted as poor:

Where is the number of people in the population, is the per capita consumption (or income) of individual “i” in the population, and

z is the poverty line. I is an indicator function equal to one if the expression in parentheses is true and zero otherwise.

So, if consumption of an individual is less than the poverty line, she/he is counted as poor, while if it is equal or above the poverty line,

she/he is not counted as poor.

The applicable poverty line is $1.90 per person per day at 2011 PPP, which is the current international extreme poverty line (the $1.90

per person per day at 2011 PPP has replaced the $1.25 at 2005 PPP in 2015). The indicator follows the World Bank PovCalNet

methodology to measure poverty in individual countries in a way that is comparable across countries. See Ferreira et al. (2015)

for more

details on the current methodology and explanations on how the methodology was adjusted over time.

The indicator uses household-level consumption data from a nationally representative household survey. Hence, while the indicator

reports the percent of people in the country that are poor, data are actually not collected at the individual level. Instead, average daily

consumption of a household is divided by the number of household members to come up with an average daily ‘per capita’ consumption

estimate for the household. In this approach, every household member is assumed to have an equal share of total consumption,

regardless of age and potential economies of scale. In practice, the indicator is calculated by dividing the total sample-weighted number of

people in poor households by the total sample-weighted number of people in all sample households with consumption data. The result is

multiplied by 100 to get a percent.

Consumption data are usually used instead of income data because of the difficulty in accurately measuring income, and because

consumption is easier to recall and more stable over time than income, especially among agricultural households. Data are collected using

the household consumption module of the Living Standards Measurement Survey (LSMS) or another nationally representative household

survey with a complete household consumption module. A consumption aggregate is calculated by summing all household consumption,

valued in local currency, after bringing them to a common recall period (as the relevant time frame varies between the different

consumption good categories). For more details on the calculation of the consumption aggregate, see here: https://agrilinks.org/post/feed-

future-zoi-survey-methods.

Individual household average daily per capita consumption is compared to the international poverty line of $1.90 2011 PPP to determine if

a household is poor (consumption falls below the poverty line) or non-poor (consumption is equal to or above the poverty line). To do the

comparison, the international poverty line must be converted to the country local currency unit (LCU) using the 2011 Purchasing Power

Parity (PPP) exchange rate. Using exchange rates based on PPP conversion factors (instead of market exchange rates) allows adjustment

for price differences between countries, such that a dollar has the same purchasing power across countries. The 2011 PPP conversion

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Ferreira, F., et al., A Global Count if the Extreme Poor in 2012: Data Issues, Methodology, and Initial Results, World Bank Policy Research Working

Paper #7432, October 2015: https://openknowledge.worldbank.org/handle/10986/22854

33!

factors for Feed the Future target countries are presented in Table 1 below. These were obtained from the World Bank, World

Development Indicators: http://databank.worldbank.org.

The $1.90 poverty line converted to local currency using the 2011 PPP must then be converted to the local prices prevailing the year and

month of the survey using the country’s Consumer Price Index (CPI). The government official source for CPI data should be used.

To calculate the local currency equivalent to the $1.90 poverty line at the prices prevailing during the year of the survey, the general

formula is as follows:

Where the subscript ‘t’ refers to the year, or month and year as relevant, when the survey was conducted.

RATIONALE: This indicator is the equivalent of EG-c: Prevalence of poverty at the ZOI level. Because Feed the Future phase two

emphasizes market linkages, systemic changes, and the enabling environment, this indicator measures the impact beyond the ZOI from

economy-wide effects of Feed the Future interventions. Reporting poverty level in the entire country also allows for comparing the socio-

economic situation in the Zone of Influence to the situation at the national level, and track differential changes happening in the ZOI. This

indicator aligns with the SDG1, “End poverty in all its forms everywhere” and is linked to the Global Food Security Strategy Goal:

Sustainably reduce global hunger, malnutrition, and poverty.

UNIT:

Percent

DISAGGREGATE BY:

Gendered Household Type (if possible):

Male and Female Adults (M&F), Adult Female No Adult Male (FNM), Adult Male No Adult Female

(MNF), Child No Adults (CNA)

TYPE: Impact

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected in a national-level, population-based, representative, random

sample survey.

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Primary data: The national statistics office under the LSMS-ISA+ national data systems strengthening

activity

Secondary data: The M&E contractor or Country Post staff

 DATA SOURCE:

Primary data: Primary data are collected via a nationally representative population-based poverty

survey

Secondary data: Population-based surveys used by official statistics to report on prevalence of poverty,

such as the Living Standard Measurement Survey (LSMS).

 FREQUENCY OF

COLLECTION:

As data are available.

 BASELINE INFO:

The baseline is the value from the most recent national survey.

34!

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter National-level values under the “High Level Indicators – [COUNTRY

NAME]” mechanism in the FTFMS.

• Enter the source of data and the year that data were collected in the field under the Indicator Comment. If field data collection

spanned two years, enter the year field data collection began.

• Enter the value for the overall indicator and for each GHHT disaggregate category, if possible.

• Enter the total number of people in the country and for each GHHT disaggregate category, if possible.

• If indicator data for the GHHT disaggregate is not available, enter the data under the “Disaggregates Not Available” option under

the GHHT disaggregate.

Enter:

1. Year of field data collection and source of data [in the Indicator Comment]

2. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold in the country

3. Total number of people in the country

4. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold among people in M&F households in the country

5. Total number of people in M&F households in the country

6. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold among people in FNM households in the country

7. Total number of people in FNM households in the country

8. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold among people in MNF households in the country

9. Total number of people in MNF households in the country

10. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold among people in CNA households in the country

11. Total number of people in CNA households in the country

OR, if data on GHHT are not available, enter:

1. Year of field data collection and source of data [in the Indicator Comment]

2. Sample-weighted prevalence poverty at the $1.90 2011 PPP threshold in the country

3. Total number of people in the country

4. Sample-weighted prevalence of poverty at the $1.90 2011 PPP threshold among people in ‘disaggregates not available’

households (which will be the same as the value entered under #1)

5. Total number of people in ‘disaggregates not available’ households in the country (which should equal the total number of

households in the country)

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

35!

▪ National-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as

custom indicators.

Table 1: PPP 2011 Conversion Factor, Private Consumption

(LCU per international $)

GFSS Target Countries

PPP 2011

Bangladesh

24.849

Ethiopia

5.439

Ghana

0.788

Guatemala

3.873

Honduras

10.080

Kenya

35.430

Mali

221.868

Nigeria

79.531

Niger

228.753

Nepal

25.759

Senegal

246.107

Uganda

946.890

Source: World Bank, World Development Indicators, Updated 11/15/2017

36!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Goal: Sustainably reduce global hunger, malnutrition, and poverty

INDICATOR TITLE: EG-e Prevalence of moderate and severe food insecurity in the population, based on the Food Insecurity

Experience Scale (FIES) [ZOI-level]

DEFINITION:

The indicator measures the percentage of households that experienced food insecurity at moderate and severe levels during the 12

months prior to data collection. The severity of the experience of food insecurity is defined as a measurable latent trait (a characteristic that

is not directly observable, but can be measured indirectly, for example by taking into account behavioral and psychological experiences, in

this case around food insecurity). It is measured through the Food Insecurity Experience Scale (FIES), a measurement scale established

by the Food and Agriculture Organization (FAO) of the United Nations. The indicator is based on an estimation of the probability that each

household belongs to a specific category of food insecurity severity (moderate and severe), as determined by the household’s position on

the scale.

[1]

The inability to access food results in a series of experiences and conditions that are common across cultures and socio-economic

contexts. These experiences range from being concerned about the possibility of obtaining enough food, to the need to compromise on the

quality or the diversity of food consumed, to being forced to reduce the intake of food by reducing portion sizes or skipping meals, to the

extreme condition of feeling hungry and not having the means (money or other resources) to access food. The new FIES global indicator

for measuring food insecurity (access) is calculated from answers to a set of eight questions that covers a range of severity of food

insecurity.

[2]

The questions refer to difficulty in accessing food due to lack of money or other resources, and reflect the food-related

behavior and experiences of the household. The questions are as follows:

1. During the past 12 months, was there a time when you or others in your household were worried you would not have enough

food to eat because of a lack of money or other resources?

2. During the past 12 months, was there a time when you or others in your household were unable to eat healthy and nutritious

food because of a lack of money or other resources?

3. During the past 12 months, was there a time when you or others in your household ate only a few kinds of foods because of a

lack of money or other resources?

4. During the past 12 months, was there a time when you or others in your household had to skip a meal because there was not

enough money or other resources to get food?

5. During the past 12 months, was there a time when you or others in your household ate less than you thought you should

because of a lack of money or other resources?

6. During the past 12 months, was there a time when your household did not have food because of a lack of money or other

resources?

7. During the past 12 months, was there a time when you or others in your household were hungry but did not eat because there

was not enough money or other resources for food?

8. During the past 12 months, was there a time when you or others in your household went without eating for a whole day because

of a lack of money or other resources?

The response categories for each of the questions include ‘Yes (1),’ ‘No (0),’ and ‘Refused.’ Cases with ‘Refused’ are excluded from the

analysis.

The prevalence of food insecurity is calculated using the one-parameter logistic model, also known as the Rasch model, which is the

simplest formulation for an Item Response Theory-based model.

[3]

The Rasch model assumes that households’ responses to each of the

eight binary questions (0/1) are conditionally independent (meaning that the only statistical link between them is the fact that all of them

contribute to measure only one and the same food insecurity latent trait), and that each question has the same discrimination power with

respect to food insecurity severity. Based on these assumptions, the model uses conditional maximum likelihood procedures to generate

estimates of both the questions’ and households’ severity parameters.

[4]

Provided the data are consistent with the Rasch model

37!

assumption, the estimated household severity parameters are defined on a continuous, interval-level scale of the severity of food insecurity

(latent trait). An interval scale is one where the difference between points on the scale is measurable and consistent.

Households are assigned to categories of severity after statistically determining appropriate thresholds that define the categories. Based

on the application of the FIES in more than 140 countries in 2014-2016, FAO has suggested cross-nationally comparable thresholds that

correspond to the severity level of the 5

question “Ate less than should” (to separate “mild” from “moderate” levels of severity) and of the

question “Did not eat for a whole day” (to separate “moderate” from “severe” levels) for global monitoring purposes. Adopting these

thresholds (after adjusting the country’s metric to make the country-specific scale’s severity parameters comparable to the global standard

scale and thus to other Feed the Future target countries as well), households with a sample-weighted sum of the probabilities of being

between the severity level of the 5

item on the FIES global reference scale (adjusted on the country’s metric) and the 7

item, inclusive

are assigned to the “moderate” category of food insecurity, while households with a sample-weighted sum of the probabilities of being

greater than or equal to the severity level of the 8

item on the FIES global reference scale (adjusted on the country’s metric) are assigned

to the “severe” food insecurity category.[5]

[1] Technical resources, including the datasets and the FIES statistical program, are available at the FAO’s Voices of the Hungry website. An e-learning course

that provides guidance on the collection and analysis of data, and on how the information provided by the FIES can be used to inform and guide policy, is also

available: http://www.fao.org/elearning/#/elc/en/course/SDG212.

[2] For detailed definition and background, refer to FAO’s Voices of the Hungry paper, Methods for Estimating Comparable Prevalence Rates of Food Insecurity

Experienced by Adults throughout the World.

[3] For details about item response theory in the context of food security measurement, refer to Introduction to Item Response Theory Applied to Food Security

Measurement.

[4] For details on assumptions and technical computations, refer to Introduction to Item Response Theory Applied to Food Security Measurement.

[5] The 5

item refers to the question, “In the past 12 months, did you eat less than you thought you should?”, and the 8

item refers to the question “In the past

12 months, did you go a whole day without eating?” on the global reference scale developed by FAO’s Voices of the Hungry project. Note: The severity threshold

for moderate to severe food insecurity has been recently updated from the 4

to the 5

item by FAO. The key resource document from the FAO, titled “The Food

Insecurity Experience Scale-Development of a Global Standard for Monitoring Hunger Worldwide”, has not been revised yet.

RATIONALE:

This indicator is one of the measures for the goal of the Global Food Security Strategy to “Sustainably reduce global hunger, malnutrition,

and poverty”. All three objectives and underlying intermediate results and cross-cutting intermediate results seek to contribute one way or

another to reduce hunger in the ZOI. This indicator aligns with the SDG 2: End hunger, achieve food security and improved nutrition and

promote sustainable agriculture. Most existing food insecurity indicators focus on potential consequences of food insecurity (e.g., nutrition

outcomes), adequacy of diet (food consumption scores, dietary diversity), or physical experience and behavior (e.g., household hunger

scale). The food insecurity prevalence based on FIES measures the access dimension of food security based on households’

psychological and behavioral experience with accessing food in the desired quantity, quality, and continuity. The FIES was developed to

complement existing food and nutrition indicators; hence, when used in combination with other existing indicators, it will offer a more

comprehensive understanding of causes and consequences of food insecurity. The analytic treatment of the data through the Rasch model

based on sound statistical methods allows for testing the quality of the data with respect to their validity and reliability and ensures that the

indicator estimates are comparable across cultural and socio-economic contexts. Disaggregating into moderate and severe levels of food

insecurity experience provides additional information. This indicator is linked to the Global Food Security Strategy Goal: Sustainably

reduce global hunger, malnutrition, and poverty.

UNIT:

Percent

DISAGGREGATE BY:

Gendered Household Type:

Male and Female Adults (M&F), Adult Female No Adult Male (FNM), Adult Male No Adult Female

(MNF), Child No Adults (CNA)

38!

Level of Severity:

Moderate, Severe

TYPE: Impact

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected from a random sample of households in the ZOI (i.e. the targeted

sub-national regions/districts where the USG intends to achieve the greatest household- and person-

level impacts on poverty, hunger, and malnutrition.)

 WHO COLLECTS DATA

FOR THIS INDICATOR:

The national statistics office under the LSMS-ISA+ or an M&E contractor.

 DATA SOURCE:

Primary data are collected via a population-based survey conducted in the ZOI using the Feed the

Future Survey Methods Toolkit (https://agrilinks.org/post/feed-future-zoi-survey-methods).

 FREQUENCY OF

COLLECTION:

Data should be collected at baseline, and during each subsequent ZOI-level population-based survey

thereafter.

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where the USG

intends to achieve the greatest household- and individual-level impacts on poverty, hunger, and

malnutrition),

2) Office of Food for Peace development program areas, and

3) Resilience to recurrent crisis areas.

 BASELINE INFO:

A baseline is required, and the value is from the FTF phase two baseline ZOI survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter ZOI-level values under the “High Level Indicators – [COUNTRY NAME]”

mechanism in the FTFMS.

• Enter the year that data were collected in the field under the Indicator Comment. If field data collection spanned two years, enter

the year field data collection began.

• Enter the value for the overall indicator and for each GHHT disaggregate category under the appropriate ZOI/area category

(Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

39!

• Enter the total number of households in the ZOI/area and for each GHHT disaggregate category in the appropriate ZOI/area

category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

For example, a GFSS target country entering data from the Feed the Future ZOI baseline survey would enter:

1. Year of field data collection in Target Country ZOI [in the Indicator Comment]

2. Sample-weighted prevalence of moderate and severe food insecurity in the Target County ZOI

3. Total number of households in the Target Country ZOI

4. Sample-weighted prevalence of moderate and severe food insecurity among M&F households in the Target Country ZOI

5. Total number of M&F households in the Target Country ZOI

6. Sample-weighted prevalence of moderate and severe food insecurity among FNM households in the Target Country ZOI

7. Total number of FNM households in the Target Country ZOI

8. Sample-weighted prevalence of moderate and severe food insecurity among MNF households in the Target Country ZOI

9. Total number of MNF households in the Target Country ZOI

10. Sample-weighted prevalence of moderate and severe food insecurity among CNA households in the Target Country ZOI

11. Total number of CNA households in the Target Country ZOI

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

40!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Goal: Sustainably reduce global hunger, malnutrition, and poverty

INDICATOR TITLE: EG-f Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity

Experience Scale (FIES) [National-level]

DEFINITION:

The indicator measures the percent of households that experienced food insecurity at moderate and severe levels during the 12 months

prior to data collection. The severity of the experience of food insecurity is defined as a measurable latent trait (a characteristic that is not

directly observable, but can be measured indirectly, for example by taking into account behavioral and psychological experiences, in this

case around food insecurity). It is measured through the Food Insecurity Experience Scale (FIES), a measurement scale established by

the Food and Agriculture Organization (FAO) of the United Nations. The indicator is based on an estimation of the probability that each

household belongs to a specific category of food insecurity severity (moderate and severe), as determined by the household’s position on

the scale.[1]

The inability to access food results in a series of experiences and conditions that are common across cultures and socio-economic

contexts. These experiences range from being concerned about the possibility of obtaining enough food, to the need to compromise on the

quality or the diversity of food consumed, to being forced to reduce the intake of food by reducing portion sizes or skipping meals, to the

extreme condition of feeling hungry and not having the means (money or other resources) to access food. The new FIES global indicator

for measuring food insecurity (access) is calculated from answers to a set of eight questions that covers a range of severity of food

insecurity.[2] The questions refer to difficulty in accessing food due to lack of money or other resources, and reflect the food-related

behavior and experiences of the household. The questions are as follows:

1. During the past 12 months, was there a time when you or others in your household were worried you would not have enough

food to eat because of a lack of money or other resources?

2. During the past 12 months, was there a time when you or others in your household were unable to eat healthy and nutritious

food because of a lack of money or other resources?

3. During the past 12 months, was there a time when you or others in your household ate only a few kinds of foods because of a

lack of money or other resources?

4. During the past 12 months, was there a time when you or others in your household had to skip a meal because there was not

enough money or other resources to get food?

5. During the past 12 months, was there a time when you or others in your household ate less than you thought you should

because of a lack of money or other resources?

6. During the past 12 months, was there a time when your household did not have food because of a lack of money or other

resources?

7. During the past 12 months, was there a time when you or others in your household were hungry but did not eat because there

was not enough money or other resources for food?

8. During the past 12 months, was there a time when you or others in your household went without eating for a whole day because

of a lack of money or other resources?

The response categories for each of the questions include ‘Yes (1),’ ‘No (0),’ and ‘Refused.’ Cases with ‘Refused’ are excluded from the

analysis.

The prevalence of food insecurity is calculated using the one-parameter logistic model, also known as the Rasch model, which is the

simplest formulation for an Item Response Theory-based model.[3] The Rasch model assumes that households’ responses to each of the

eight binary questions (0/1) are conditionally independent (meaning that the only statistical link between them is the fact that all of them

contribute to measure only one and the same food insecurity latent trait), and that each question has the same discrimination power with

respect to food insecurity severity. Based on these assumptions, the model uses conditional maximum likelihood procedures to generate

estimates of both the questions’ and households’ severity parameters.[4] Provided the data are consistent with the Rasch model

41!

assumption, the estimated household severity parameters are defined on a continuous, interval-level scale of the severity of food insecurity

(latent trait). An interval scale is one where the difference between points on the scale is measurable and consistent.

Households are assigned to categories of severity after statistically determining appropriate thresholds that define the categories. Based

on the application of the FIES in more than 140 countries in 2014-2016, FAO has suggested cross-nationally comparable thresholds that

correspond to the severity level of the 5

question “Ate less than should” (to separate “mild” from “moderate” levels of severity) and of the

question “Did not eat for a whole day” (to separate “moderate” from “severe” levels) for global monitoring purposes. Adopting these

thresholds (after adjusting the country’s metric to make the country-specific scale’s severity parameters comparable to the global standard

scale and thus to other Feed the Future target countries as well), households with a sample-weighted sum of the probabilities of being

between the severity level of the 5

item on the FIES global reference scale (adjusted on the country’s metric) and the 7

item, inclusive

are assigned to the “moderate” category of food insecurity, while households with a sample-weighted sum of the probabilities of being

greater than or equal to the severity level of the 8

item on the FIES global reference scale (adjusted on the country’s metric) are assigned

to the “severe” food insecurity category.[5]

[1] Technical resources, including the datasets and the FIES statistical program, are available at the FAO’s Voices of the Hungry website. An e-learning course

that provides guidance on the collection and analysis of data, and on how the information provided by the FIES can be used to inform and guide policy, is also

available: http://www.fao.org/elearning/#/elc/en/course/SDG212.

[2] For detailed definition and background, refer to FAO’s Voices of the Hungry paper, Methods for Estimating Comparable Prevalence Rates of Food Insecurity

Experienced by Adults throughout the World.

[3] For details about item response theory in the context of food security measurement, refer to Introduction to Item Response Theory Applied to Food Security

Measurement.

[4] For details on assumptions and technical computations, refer to Introduction to Item Response Theory Applied to Food Security Measurement.

[5] The 5

item refers to the question, “In the past 12 months, did you eat less than you thought you should?”, and the 8

item refers to the question “In the past

12 months, did you go a whole day without eating?” on the global reference scale developed by FAO’s Voices of the Hungry project. Note: The severity threshold

for moderate to severe food insecurity has been recently updated from the 4

to the 5

item by FAO. The key resource document from the FAO, titled “The Food

Insecurity Experience Scale-Development of a Global Standard for Monitoring Hunger Worldwide”, has not been revised yet.

RATIONALE:

This indicator is one of the measures for the goal of the Global Food Security Strategy to “Sustainably reduce global hunger, malnutrition,

and poverty”. All three objectives and underlying intermediate results and cross-cutting intermediate results seek to contribute one way or

another to reduce food insecurity. Because Feed the Future phase two emphasizes market linkages, systemic changes, and the enabling

environment, this indicator measures the impact beyond the ZOI from economy-wide effects of Feed the Future interventions. Reporting

food insecurity in the entire country also allows for comparing the food insecurity situation in the ZOI to the situation at the national

level, and track differential changes happening in the ZOI.

This indicator is one of the indicators used to monitor SDG 2: End hunger, achieve food security and improved nutrition and promote

sustainable agriculture. Most existing food insecurity indicators focus on potential consequences of food insecurity (e.g., nutrition

outcomes), adequacy of diet (food consumption scores, dietary diversity), or physical experience and behavior (e.g., household hunger

scale). The food insecurity prevalence based on FIES measures the access dimension of food security based on households’

psychological and behavioral experience with accessing food in the desired quantity, quality, and continuity. The FIES was developed to

complement existing food and nutrition indicators; hence, when used in combination with other existing indicators, it will offer a more

comprehensive understanding of causes and consequences of food insecurity. The analytic treatment of the data through the Rasch model

based on sound statistical methods allows for testing the quality of the data with respect to their validity and reliability and ensures that the

indicator estimates are comparable across cultural and socio-economic contexts. This indicator is linked to the Global Food Security

Strategy Goal: Sustainably reduce global hunger, malnutrition, and poverty.

42!

UNIT:

Percent

DISAGGREGATE BY:

Gendered Household Type (if possible):

Male and Female Adults (M&F), Adult Female No Adult Male (FNM), Adult Male No Adult Female

(MNF), Child No Adults (CNA)

Severity:

Moderate, Severe

TYPE: Impact

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected in a national-level, population-based, representative, random

sample survey.

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Primary data: The national statistics office under the LSMS-ISA+ national data systems strengthening

activity

Secondary data: The M&E contractor or Country Post staff

 DATA SOURCE:

Primary data: Primary data are collected via a nationally representative population-based survey

Secondary data: Population-based surveys used by official statistics offices to report on this SDG

indicator, such as the Living Standard Measurement Survey (LSMS) or FAO Voices of the Hungry

project. Note that the FAO Voices of the Hungry/Gallup World Poll FIES data are collected from

individuals and thus measures food insecurity at the individual-level rather than household-level.

Since the ZOI-level FIES indicator is measured at the household level, these differences in methods

need to be taken into account when comparing national-level to ZOI-level results if FAO Voices of the

Hungry data are used.

 FREQUENCY OF

COLLECTION:

As data are available.

 BASELINE INFO:

The baseline is the value from the most recent national survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter National-level values under the “High Level Indicators – [COUNTRY

NAME]” mechanism in the FTFMS.

• Enter the source of data and the year that data were collected in the field under the Indicator Comment. If field data collection

spanned two years, enter the year field data collection began.

• Enter the value for the overall indicator and for each GHHT disaggregate category, if possible.

43!

• Enter the total number of households in the country and for each GHHT disaggregate category, if possible.

• If indicator data for the GHHT disaggregate is not available, enter the data under the “Disaggregates Not Available” option under

the GHHT disaggregate.

Enter:

1. Year of field data collection and source of data [in the Indicator Comment]

2. Sample-weighted prevalence of moderate and severe food insecurity in the country

3. Total number of households in the country

4. Sample-weighted prevalence of moderate and severe food insecurity among M&F households in the country

5. Total number of M&F households in the country

6. Sample-weighted prevalence of moderate and severe food insecurity among FNM households in the country

7. Total number of FNM households in the country

8. Sample-weighted prevalence of moderate and severe food insecurity among MNF households in the country

9. Total number of MNF households in the country

10. Sample-weighted prevalence of moderate and severe food insecurity among CNA households in the country

11. Total number of CNA households in the country

12. Sample-weighted prevalence of households with moderate food insecurity in the country

13. Sample-weighted prevalence of households with severe food insecurity in the country

OR, if data on GHHT are not available, enter:

1. Year of field data collection and source of data [in the Indicator Comment]

2. Sample-weighted prevalence of moderate and severe food insecurity in the country

3. Total number of households in the country

4. Sample-weighted prevalence of moderate and severe food insecurity among ‘disaggregates not available’ households (which will

be the same as the value entered under #1)

5. Total number of ‘disaggregates not available’ households in the country (which should equal the total number of households in

the country)

6. Sample-weighted prevalence of households with moderate food insecurity (if data on severity are not available, leave blank)

7. Sample-weighted prevalence of households with severe food insecurity (if data on severity are not available, leave blank)

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ National-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

44!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Objective 1: Inclusive and sustainable agricultural-led economic growth (Cross-

linked to Objective 2: Strengthened resilience among people and systems)

INDICATOR TITLE: EG-g Percent of households below the comparative threshold for the poorest quintile of the Asset-Based

Comparative Wealth Index [ZOI-level]

DEFINITION:

This indicator reflects the percentage of households in the Feed the Future Zone of Influence (ZOI) whose ownership (or lack thereof) of

selected assets places the household below a fixed threshold (with a value of -0.9080) that defined the poorest quintile (bottom 20 percent)

in the comparative baseline wealth index that was used to create a cross-nationally, cross-temporally comparable asset-based wealth

index, the Comparative Wealth Index (CWI). Use of a fixed threshold across ZOIs is possible because the CWI is an index with a value

that is relative to the baseline wealth index that is used for comparison. This means that the index score and thresholds can be compared

across ZOI surveys and over time.

The CWI is calculated according to the methodology specified in Rutstein and Stavetieg 2014

[1]

using the following standard household-

level asset variables, plus selected additional country-specific asset variables if any are specified: employment of domestic servants;

ownership of agricultural land and size of land; number of people per sleeping room; house ownership; water source; toilet facility (type

and shared status); floor material; roof material; wall material; cooking fuel; access to electricity; and possession of radio, television, mobile

phone, non-mobile telephone, computer, refrigerator, watch, bicycle, motorcycle or scooter, animal-drawn cart, car or truck, boat with a

motor, bank account, cows, other cattle, horses, donkeys, mules, goats, sheep, chicken or other poultry, or fish.

In the interest of preserving data quality, it is important to minimize the number of questions in the ZOI Survey questionnaire; however,

Post teams may find that there are important country-specific assets that are not reflected in the core ZOI Survey questionnaire. For

selecting country-specific assets, Post teams should consider whether there are assets typical of the country that, were they not included

in the wealth index, would produce an inaccurate reflection of wealth ownership in the country. When identifying this small number (2-3) of

country-specific assets, it is important to try to ensure that there is a balance in the extent to which those assets represent both urban and

rural types of wealth and are accessible to both urban and rural populations (e.g., a watch), and to avoid including assets that are

dependent on infrastructure requirements that are already captured in the core assets (like electricity). However, one can also consider

achieving balance in asset selection by choosing two important assets that represent distinctly rural (e.g., camel ownership) and urban

(e.g., in-home WiFi access) types of wealth.

[1]

Rutstein, Shea, and Sarah Staveteig. 2014. Making the Demographic and Health Surveys Wealth Index comparable. DHS Methodological Reports No. 9. Rockville,

Maryland, USA: ICF International. https://www.dhsprogram.com/pubs/pdf/MR9/MR9.pdf

RATIONALE:

Asset ownership – reflecting a household's stocks of wealth – has been shown to be a better predictor of long-run household welfare than

consumption, income, or other flow-type indicators of household economic well-being (Filmer and Pritchett 1998, Little et al. 2006), which

are unable to distinguish a household's structural (longer-term, foundational), as opposed to stochastic (short term, transitory), position on

a continuum of future-looking household economic well-being (Carter and Barrett 2006). Ownership of productive (either social or

economic) assets often determine a household’s or individual’s future capacity to earn income and withstand shocks (Little et al. 2006).

Asset accumulation, protection, and management before and during shocks is therefore seen as critical to avoid asset divestment that can

undercut a household's productive potential, resulting in reduced resilience to current and future shocks. The number and type of assets a

household owns is associated with household resilience across national contexts, indicating that asset accumulation can serve as a buffer

against shocks (e.g., Jalan and Ravallion 2002, Dercon 2004).

In addition to providing a snapshot in time of how wealthy or poor a particular household is relative to a common wealth distribution, the

CWI can help to assess the following: 1) whether the economic situation in a given country has improved over time, 2) whether

45!

improvements in key indicators are due to general improvements in economic status or to the effects of government programs focused on

the poorer sectors of the population, and 3) whether international funding of development programs is reaching the poorer sectors of the

population. However, because the ZOI Surveys are cross-sectional, the CWI reflects the situation for the population in the ZOI at the time

of the survey and cannot indicate whether a specific household has moved up or down the asset-based wealth gradient over time. In the

Global Food Security Strategy results framework, this indicator is linked to Objective 1: Inclusive and sustainable agricultural-led economic

growth and cross-linked to Objective 2: Strengthened resilience among people and systems.

References:

Carter, M.R. and C.B. Barrett. 2006. The economics of poverty traps and persistent poverty: An asset-based approach. Journal of Development Studies,

42(2):178-199.

Dercon, S. 2004. Growth and shocks: evidence from rural Ethiopia. Journal of Development Economics, 74: 309–329.

Filmer, D. and L. Pritchett. 2001. Estimating wealth effects without expenditure data - or tears: An application to educational enrolments in states of India.

Demography, 38 (1), pp.115-132. Jalan, J., Ravallion, M., 2002. Geographic poverty traps? A micro model of consumption growth in rural China. Journal of

Applied Econometrics, 17, 329–346.

Little P, Stone M, Moguesc T, Castrod A, Negatue W. 2006. 'Moving in place’: Drought and poverty dynamics in South Wollo, Ethiopia. Journal of Development

Studies, 42(2):200–225.

UNIT:

Percent

DISAGGREGATE BY:

Gendered Household Type:

Male and Female Adults (M&F), Adult Female No Adult Male (FNM), Adult Male No Adult Female

(MNF), Child No Adults (CNA)

TYPE: Outcome

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected from a random sample of households in the ZOI (i.e. the targeted

sub-national regions/districts where the USG intends to achieve the greatest household-

and individual-level impacts on poverty, hunger, and malnutrition).

 WHO COLLECTS DATA

FOR THIS INDICATOR:

The national statistics office under the LSMS-ISA+ national data systems strengthening activity or an

M&E contractor.

 DATA SOURCE:

Data are collected via a population-based survey conducted in the ZOI using the Feed the Future

Survey Methods Toolkit (https://agrilinks.org/post/feed-future-zoi-survey-methods). USAID/BFS will

provide support upon request to compute the indicator.

 FREQUENCY OF

COLLECTION:

Data should be collected at baseline, and during each subsequent ZOI-level population-based survey

thereafter.

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where the USG

intends to achieve the greatest household- and individual-level impacts on poverty, hunger, and

malnutrition),

2) Office of Food for Peace development program areas, and

46!

3) Resilience to recurrent crisis areas.

 BASELINE INFO:

A baseline is required, and the value is from the FTF phase two baseline ZOI survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter ZOI-level values under the “High Level Indicators – [COUNTRY NAME]”

mechanism in the FTFMS.

• Enter the year that data were collected in the field under the Indicator Comment. If field data collection spanned two years, enter

the year field data collection began.

• Enter the indicator value for the overall indicator and for each GHHT disaggregate category under the appropriate ZOI/area

category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

• Enter the total number of households in the ZOI/area and for each GHHT disaggregate category in the appropriate ZOI/area

category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

For example, a GFSS target country entering data from the Feed the Future ZOI baseline survey would enter:

1. Year of field data collection in Target Country ZOI [in the Indicator Comment]

2. Sample-weighted percent households falling below the fixed threshold for the poorest quintile of the comparative wealth index in

the Target Country ZOI

3. Total number of households in the Target Country ZOI

4. Sample-weighted percent of M&F households falling below the fixed threshold for the poorest quintile of the comparative wealth

index in the Target Country ZOI

5. Total number of M&F households in the Target Country ZOI

6. Sample-weighted percent of FNM households falling below the fixed threshold for the poorest quintile of the comparative wealth

index in the Target Country ZOI

7. Total number of FNM households in the Target Country ZOI

8. Sample-weighted percent of MNF households falling below the fixed threshold for the poorest quintile of the comparative wealth

index in the Target Country ZOI

9. Total number of MNF households in the Target Country ZOI

10. Sample-weighted percent of CNA households falling below the fixed threshold for the poorest quintile of the comparative wealth

index in the Target Country ZOI

11. Total number of CNA households in the Target Country ZOI

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

• ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

47!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Objective 2: Strengthened resilience among people and systems

INDICATOR TITLE: EG-h Depth of poverty of the poor: Mean percent shortfall of the poor relative to the $1.90/day 2011 PPP

poverty line [ZOI-level]

DEFINITION:

This indicator measures how deeply poor are poor people within the ZOI. Specifically, the depth of poverty of the poor measures, on

average, how far below the $1.90 (2011 PPP) consumption per person per day poverty threshold are the poor in the ZOI.

When calculating this indicator, the applicable poverty threshold is $1.90 per person per day, converted into local currency units (LCU) at

the 2011 PPP exchange rate, then inflated using the country’s Consumer Price Index from 2011 to the time period when the population-

based survey was implemented. The use of PPP exchange rates ensures that the poverty line applied in each country has the same

purchasing power. The procedure for converting values expressed in local currency into PPP adjusted U.S. dollars is explained in the

Performance Indicator Reference Sheet for EG-a Prevalence of Poverty: Percent of people living on less than $1.90/day 2011 PPP.

Households whose per capita expenditure is equal to or greater than the poverty threshold are not included in the calculation of this

indicator.

The steps to calculate the depth of poverty of the poor are:

1. Subtract each poor household’s per capita expenditure in LCU from the poverty threshold of $1.90 in LCU

2. Divide by $1.90 in LCU to obtain the household’s proportional shortfall from the poverty line

3. Multiply each poor household’s proportional shortfall by the number of household members then sum across all poor households

4. Sum the number of household members in poor households

5. Divide (3) by (4) and multiply by 100 to obtain the depth of poverty of the poor expressed as a percent of the $1.90 per person

per day poverty line.

Note: This indicator differs from the Depth of Poverty indicator used by the World Bank and used previously by Feed the Future. As

modified, this indicator only tracks the depth of poverty of households under the poverty threshold, rather than including all households and

assigning non-poor households a shortfall of zero. Including the poor and non-poor households means the depth of poverty can decrease

either because poor households have crossed the poverty threshold or because poor households have become less poor. One of the

limitations of removing the non-poor households from the calculation is that it is possible that the depth of poverty of the poor may increase

over time as previously poor households cross the poverty threshold, leaving only households that may have started with deeper levels of

poverty. Changes in this indicator must be analyzed in conjunction with changes in the prevalence of poverty indicator to capture that

dynamic.

RATIONALE:

The depth of poverty of the poor indicator is a complement to the prevalence of poverty indicator. Both indicators are necessary to obtain a

complete picture of the poverty situation in a particular geographical area. Depth of poverty of the poor is particularly important for

programs that target vulnerable communities where many households are not only below the poverty line, but well below the poverty line,

including programs that target people and places subject to recurrent humanitarian crises. The depth of poverty of the poor indicator allows

one to identify the extent to which poor individuals fall below the poverty line and is therefore more sensitive than poverty prevalence in

capturing progress among those well below the poverty line. Depth of poverty of the poor is a topline measure for FFP development

programs and for USAID's effort to build resilience to recurrent crises in targeted areas of the Horn of Africa and Sahel to which Feed the

Future programs contribute. In the Global Food Security results framework, this indicator is linked to Objective 2: Strengthened resilience

among people and systems.

48!

UNIT:

Percent

DISAGGREGATE BY:

Gendered Household Type: Male and Female Adults (M&F), Adult Female No Adult Male (FNM),

Adult Male No Adult Female (MNF), Child No Adults (CNA)

TYPE: Impact

DIRECTION OF CHANGE: Lower is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected from a random sample of households in the ZOI (i.e. the targeted

sub-national regions/districts where the USG intends to achieve the greatest household- and people-

level impacts on poverty, hunger, and malnutrition.)

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Primary data: The national statistics office under the LSMS-ISA+ national data systems strengthening

activity or an M&E contractor.

Secondary data: M&E contractor or Country Post staff

 DATA SOURCE:

Primary data: Primary data are collected via a population-based survey conducted in the ZOI using

the Feed the Future Survey Methods Toolkit (https://agrilinks.org/post/feed-future-zoi-survey-

methods).

Secondary data: National survey if the data were collected within the previous two years. Location

variables are used to identify records corresponding to the ZOI in the secondary data set, and the

secondary data analysis is then conducted using those records.

 FREQUENCY OF

COLLECTION:

Data should be collected at baseline and during each subsequent ZOI-level population-based survey

thereafter.

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where the USG

intends to achieve the greatest household- and individual-level impacts on poverty, hunger, and

malnutrition),

2) Office of Food for Peace development program areas, and

3) Resilience to recurrent crisis areas.

 BASELINE INFO:

A baseline is required, and the value is from the FTF phase two baseline ZOI survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• USAID Missions or the M&E contractor should enter ZOI-level values under the “High Level Indicators – [COUNTRY NAME]”

mechanism in the FTFMS.

• Enter the year that data were collected in the field under the Indicator Comment. If field data collection spanned two years, enter

49!

the year field data collection began.

• Enter the indicator value for the overall indicator and for each GHHT disaggregate category under the appropriate ZOI/area

category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

• Enter the total number of people in the ZOI/area and for each GHHT disaggregate category in the appropriate ZOI/area category

(Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

For example, a GFSS target country entering data from the Feed the Future ZOI baseline survey would enter:

1. Year of field data collection in the Target Country ZOI [in the Indicator Comment]

2. Sample-weighted mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line in the Target Country ZOI

3. Total number of people in the Target Country ZOI

4. Sample-weighted mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line among M&F households in

the Target Country ZOI

5. Total number of people in M&F households in the Target Country ZOI

6. Sample-weighted mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line among FNM households in

the Target Country ZOI

7. Total number of people in FNM households in the Target Country ZOI

8. Sample-weighted mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line among MNF households in

the Target Country ZOI

9. Total number of people in MNF households in the Target Country ZOI

10. Sample-weighted mean percent shortfall of the poor relative to the $1.90/day 2011 PPP poverty line among CNA households in

the Target Country ZOI

11. Total number of people in CNA households in the Target Country ZOI

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

50!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element 3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – Output: could be applicable to many parts of results framework.

INDICATOR TITLE: EG.3-2 Number of individuals participating in USG food security programs [IM-level]

DEFINITION:

This indicator is designed to capture the breadth of our food security work. This indicator counts participants of Feed the Future-funded

programs, including those we reach directly, those reached as part of a deliberate service strategy, and those participating in the markets

we strengthen. We expect Implementing Partners (IPs) to track or estimate the number of individual participants across different

interventions within their own project and to report numbers of participants reached, not number of contacts with the project or project-

supported actors.

This indicator counts, with some exceptions listed below, all the individuals participating in our nutrition, resilience, and agriculture and food

system activities, including:

● Adults that projects or project-supported actors reach directly through nutrition-specific and community-level nutrition

interventions, (e.g. parents and other caregivers participating in community care groups, healthcare workers provided with in-

service training on how to manage acute malnutrition), but not children reached with nutrition-specific or community-based

interventions, who are counted under indicators HL.9-1 and HL.9-2 instead;

● People reached by productive safety nets, community-based micro-finance and diversified livelihood activities through our

assistance;

● Members of households reached with household-level interventions (households with new access to basic sanitation through our

work, households receiving family-sized rations);

● Smallholder and non-smallholder producers that projects or project-supported actors reach directly (e.g. through an irrigation

training, through a loan provided, through distribution of drought-tolerant seeds to specific farmers);

● Proprietors of firms in the private sector that we help strengthen (e.g. agrodealers, aggregators, processors). Employees of these

firms are also counted if they are reached directly with a USG-assisted service such as training;

● Producers who directly interact with those USG-assisted firms (e.g. the producers who are customers of an assisted agrodealer;

the producers from whom an assisted trader or aggregator buys), but not customers or suppliers who are not producers;

● Participants whose main source of income is labor (e.g. Laborers/non-producer diversified livelihood participants);

● People in civil society organizations and government whose skills and capacity have been strengthened by projects or project-

supported actors;

● School-aged children who are recipients of USG school feeding programs;

In cases where activities work with multiple individuals in a household, this indicator counts all activity participants in the household, not all

members of the household. However, in the case of sanitation services and family-sized rations, all members of the household receiving

the sanitation facility or ration can be counted here.

An individual is a participant if s/he comes into direct contact with the set of interventions (goods or services) provided or facilitated by the

activity. The intervention needs to be significant, meaning that if the individual is merely contacted or touched by an activity through brief

attendance at a meeting or gathering, s/he should not be counted as a participant. An intervention is significant if one can reasonably

expect, and hold OUs and IMs responsible for achieving progress toward, changes in behaviors or other outcomes for these individuals

based on the level of services and/or goods provided or accessed. Producers with increased access to goods, services and markets for

their products and who purchase from or sell to market actors that have been strengthened as a result of our activities are considered to

have received a significant intervention.

Individuals who are trained by an IM as part of a deliberate service delivery strategy (e.g. cascade training) that then go on to deliver

services directly to individuals or to train others to deliver services should be counted as participants of the activity—the capacity

strengthening is key for sustainability and an important outcome in its own right. The individuals who then receive the services or training

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delivered by those individuals are also considered participants. However, spontaneous spillover of improved practices to neighbors does

not count as a deliberate service delivery strategy; neighbors who apply new practices based on observation and/or interactions with

participants who have not been trained to spread knowledge to others as part of a deliberate service delivery strategy should not be

counted under this indicator.

Value chain facilitative and/or market-system activities may use a two-step process to identify and count participants:

1. The first step involves identifying which private sector firms have been assisted by the activity during the reporting year, and

counting the number of proprietors of those firms.

2. The second step, which is only applicable to firms that buy from or sell to producers, is to count the number of producer

customers or suppliers of each assisted firm.

The total number of participants for that activity is then the sum of the proprietors of the assisted firms and their producer

customers/suppliers. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could

use data on the number of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers

purchasing certified soy seed (by using a conservative assumption that one sales equals one farmer applying), and then report that

number as the number of producer participants. All assumptions underlying the indicator estimates should be documented annually in an

Indicator Comment in FTFMS.

Data provision by assisted firms can be facilitated by entering into written agreements that include reporting and nondisclosure

requirements and by showing assisted firms how the information provided is useful and used. Counting producer participants may be more

straightforward if the value chain activity is also facilitating extension strategies, e.g. agrodealer agents that require knowing where the

customers live and farm.

While other Feed the Future indicators, such as "financing accessed", "value of sales," and "individuals applying improved practices" also

capture the number of enterprises that contributed results to the indicator, this indicator only counts individual people, i.e. the farmer (not

the farm), and the proprietor (not the firm).

This indicator does not count the indirect beneficiaries of our activities. An indirect beneficiary is someone who does not have direct

contact with the activity but still benefits, such as the population that uses a new road constructed by the activity, neighbors who see the

results of the improved technologies applied by direct participants and decide to apply the technology themselves (spillover), or the

individuals who hear an activity-supported radio message but don’t receive any training or counseling from the activity. In part, this is

because accurate tracking of indirect beneficiaries is challenging by its nature, despite the fact that spillover is a core component of the

Feed the Future theory of change. In general, spillover is captured in Feed the Future through measuring changes in population level

indicators (e.g. percent applying improved technologies and management practices) and linking those to the work activities are doing

directly.

Note that this indicator cannot be summed across years for a project total, since “new” and “continuing” participants are not disaggregated,

and thus this will only show a total of individuals reached in any one reporting year.

USAID: Each IP should report on the number of individuals participating in their specific IM. Then the OU should report on the Mission-

wide total number of unique participants reached across all IMs. This will require estimating and removing double counting and overlap

among IMs. Please see reporting notes below.

Interagency: Each activity / grant / project should report on the number of individuals participating in that activity / grant / project that year.

In the case where more than one activity / grant / project exists per country / post, then the overall number of individuals participating in the

country should also be reported, after any double-counting is removed. Please see reporting notes below.

RATIONALE:

Understanding the reach of our work and the breakdown of the individuals participating by type, sex, and age will better inform our

programming and the impacts we are having in various sectors or in various demographic groups. This understanding can then make us

more effective or efficient in reaching our targeted groups. Understanding the extent of spillover and scale is also very important, but this

will be assessed as a part of the ZOI survey and performance and impact evaluations rather than through annually reported IM-level

52!

indicators. This indicator is an output indicator and is linked to many parts of the Global Food Security Strategy results framework.

UNIT:

Number (of people)

DISAGGREGATE BY:

 Sex: the unique number of individuals should be entered here (i.e. no double-counting of

individuals across disaggregate choices here)

● Male;

● Female;

● Not applicable (e.g. for household members counted from household-level interventions);

● Disaggregates Not Available

 Age Category: the unique number of individuals should be entered here (i.e. no double-counting

of individuals across disaggregate choices here)

● School-aged children (only to be used for counting those reached by USG school feeding

programs; report the total reached with school feeding regardless of actual age);

● 15-29;

● 30+;

● Not applicable (e.g. for household members counted from household-level interventions);

● Disaggregates Not Available

Note: Children under five reached with nutrition interventions are counted under HL.9-1

 Type of Individual: double-counting individuals across types is permitted here

● Parents/caregivers;

● Household members (household-level interventions only), such as new access to basic

sanitation and/or receipt of family rations;

● School-aged children (i.e. those participating in school feeding programs);

● People in government (e.g. policy makers, extension workers, healthcare workers);

● People in USG-assisted private sector firms (e.g. agrodealers, traders, aggregators,

processors, service providers, manufacturers)

● People in civil society (e.g. NGOs, CBOs, CSOs, research and academic organizations,

community volunteers)

While private sector firms are considered part of civil society more broadly, only count

their proprietors under the "Private Sector Firms" disaggregate and not the "Civil

Society" disaggregate

● Laborers (Non-producer diversified livelihoods participants);

● Producer: Smallholder (see definition below);

● Producer: Non-smallholder;

● Producer: Aquaculture;

● Producer: size Disaggregates Not Available

Producers (e.g. farmers, fishers, pastoralists, ranchers) should be counted under

one of the "Producers" disaggregate, not the "Private Sector Firms" disaggregate

Smallholder Definition: While country-specific definitions may vary, use the Feed

the Future definition of a smallholder producer, which is one who holds 5 hectares

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or less of arable land or equivalent units of livestock, i.e. cattle: 10 beef cows;

dairy: two milking cows; sheep and goats: five adult ewes/does; camel meat and

milk: five camel cows; pigs: two adult sows; chickens: 20 layers and 50 broilers.

The farmer does not have to own the land or livestock.

● Type of Individual Not Applicable

● Type of Individual Disaggregates Not Available

TYPE: Output

DIRECTION OF CHANGE: Higher is better.

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level, activity participants

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Firm records, activity records, training participant lists, or through census or sampling of participating

firms/farms/families/individuals, etc.

 FREQUENCY OF

COLLECTION:

Annual

 BASELINE INFO:

● “Zero” for individual IMs newly starting;

● “Current number of individuals participating” for IMs with ongoing work that will now include this

indicator;

● “Summation of all reported baseline values” (after removing double-counting) for the OU overall

reporting

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

● Enter the unique number of individuals participating under the “Sex” and “Age Category” disaggregates, and FTFMS will sum up

the overall total. Then enter the number of individuals under the "Type of individual", where double-counting is permitted.

o The total under the “Sex” disaggregate should match the total under the "Age Category" disaggregate, but may not

match the total under the “Type of Individual” disaggregate if double-counting was included there.

● Under each Disaggregate category, the “Not applicable” option can be used when breaking the number of individuals down by

that disaggregate category is not necessary, such as in household-level interventions (see example below).

● Under each Disaggregate category, the "Disaggregates Not Available" option can be used if that piece of information is not

known about the individual. However, it is required where possible to disaggregate by sex and age, so please use this option

sparingly and only when necessary.

*** IMPORTANT NOTE ***

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• USAID: Each Implementing Mechanism (IM) should count the individuals with whom it works with and report that

number under their IM in FTFMS, being careful to enter the unique number (no double-counting) under the “Sex” and

“Age Category” disaggregates. Then, the USAID Mission should aggregate across IMs to report an overall Mission-

wide total, after removing any double counting of individuals being reported by more than one IM, and report that total

under the Mission's placeholder IM titled "High-level Indicators – [COUNTRY NAME]", using the same disaggregate

categories.

• Interagency Partners: After entering the “number of individuals participating” for each of your activities / grants /

projects in FTFMS, then enter an overall agency-level number of “individuals participating” in each country where you

work that sums up all of your participants and removes any double counting under the “Total Participants” entry listed

under each country in FTFMS.

REPORTING EXAMPLES:

 Example 1: In Malawi there is a group of 30 caregivers/mothers are part of a Care Group that provides training and support on

breastfeeding, childcare, nutrition, etc. This Care Group is also used as an entry point to reach those same caregivers/mothers

to do agricultural training on improved practices for their groundnut crop. In this case, the same people are receiving two

intervention types.

o The Implementing Partner should list the unique number of caregivers/mothers (which is 30) disaggregated into their

“Sex” and “Age Category”. The total under the “Sex” disaggregate would be 30, and the total under the “Age Category”

would be 30, i.e. they should match.

o Then, under the “Type of Individual” category, they would enter the number 30 under both the “Mothers/Caregivers”

type and the “Producers” type, since this group of 30 people is both. Even though adding up these types would look

like 60 people, we allow double-counting here, and will be able to take the unique number of individuals (the 30 people)

from the “Sex” and “Age Category” disaggregates.

 Example 2: Food for Peace (FFP) provides family-sized rations and the mother of one family is the direct recipient who picks up

the ration, which she takes back to feed her whole household, which has 5 members including her. In this case, all members of

the household should be counted, since they will all be receiving the ration; but breaking down that number by sex or age is likely

not feasible, so we have provided a “Not applicable” option to use under this Disaggregate category.

o To enter the data from this example where the woman’s household had 5 members including her, enter the number 5

in the “Not applicable” option under the “Sex” and under the “Age Category” disaggregates. It is not necessary to

breakdown the household members by their sex or age.

o Then under the “Type of Individual” disaggregate, enter 5 under the “Household members” option.

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

● Only the Mission-wide total (which removes any double-counting from the summation of all contributing IMs) as reported under

"High-level Indicators – [COUNTRY NAME]" is reported into the PPR.

55!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG 3: Agriculture

INITIATIVE AFFILIATION: Global Food Security Strategy - IR 4: Increased sustainable productivity, particularly through climate-smart

approaches

INDICATOR TITLE: EG.3-10,-11,-12 Yield of targeted agricultural commodities among program participants with USG assistance

[IM-level]

DEFINITION:

Yield is a measure of the total output of production of an agricultural commodity (crop, fish, milk, eggs, live animal offtake

[1]

) divided by the

total number of units in production (hectares planted of crops, area in hectares for pond aquaculture, cubic meters of cage for cage

aquaculture, total number of animals in the herd/flock during the reporting year for live animals, maximum number of producing cows or

hens during the reporting year for dairy or eggs). Yield per hectare, per animal and per cubic meter of cage is a measure of productivity

from that farm, fisheries, or livestock activity from USG-assisted producers.

Yield is calculated automatically at the commodity level in FTFMS from the following data points, reported as totals by commodity across

all activity participants, and then disaggregated by farm size for crops or production system for livestock, then by sex and age of the

producer:

1. Total Production (TP): Kg, mt, number, or other unit by participants during the reporting period (see preferred units below);

2. Total Units of Production (UP): Area planted in ha (for crops); Area in ha (for aquaculture ponds); Total number of animals in the

herd for the reporting year, which can be calculated by collecting the number of animals in the herd at the beginning of the

reporting year plus any additional including, births, purchases or those acquired by any other means during the reporting year

OR collecting the number of animals in the herd at the end of the year plus the number of animals that died or were offtaken (for

live animals); Maximum number of animals in production (for dairy or eggs); Cubic meters of cages (for open water aquaculture)

for participants during the reporting year.

Yield is Total Production (TP) / Units of Production (UP), i.e. TP / UP per commodity.

If there is more than one production cycle in the reporting year, the data points for total production (TP) and units of production (UP) should

be counted (and summed) each time the land is cultivated, animal products are produced or the cages are used if the same commodity

was produced. The sum of TP divided by the sum of UP will provide an estimate of the average yield achieved across the different

production cycles.

Total production is the amount that is produced, regardless of how it was ultimately used. It also includes any postharvest loss (i.e.

postharvest loss should not be subtracted from total production.)

The preferred units for TP by commodity type are:

● Crops: metric tons

● Pond aquaculture: kilograms

● Cage aquaculture: kilograms

● Dairy: liters of milk

● Eggs: number of eggs

● Livestock: weight in kilograms of entire animals which were offtake

The required units for UP by commodity type are:

● Crops: hectare

● Tree crops: hectare is recommended

[2]

17T

● Pond aquaculture: hectare of surface area

● Cage aquaculture: cubic meter of cage

56!

● Dairy: maximum number of milking animals during the reporting year

● Eggs: maximum number of producing hens during the reporting year

● Livestock: total number in herd, flock, or other group during the reporting year

For partners working in livestock value chains, there is an additional disaggregation of livestock production system to support meaningful

analysis of outcomes. Select the system that is the best fit for the livestock activity intervention. There are four production systems:

Rangeland; mixed crop-livestock; urban/peri-urban; and intensive/commercial production.

Rangelands (pastoral, transhumant, agro-pastoral, silvo-pastoral, and extensive grasslands)

● Livestock and livestock-crop systems in which production is extensive with low stocking rates (typically <10 TLUs per hectare)

and there is a degree of herd mobility in the grazing system beyond the farm for at least part of the production cycle.

● Typically in arid and semi-arid zones, with rainfall dependent (forage) growing seasons less than 180 days per year.

Mixed crop-livestock (ruminants, pigs and poultry and small stock such as rabbits and guinea pigs and animals kept principally for

traction including oxen, buffalo and equids)

● Integrated crop and livestock production where crop and livestock systems rely on one another for inputs and exist in a

fixed rural location, typically a small holding or farmstead. For example, a system where at least some of the livestock feed

comes from crop residues and by-products produced on-farm.

Urban/peri-urban (including poultry, small scale dairy, small and large ruminants, pigs, micro-stock, small scale fattening operations)

▪ Livestock are kept in close proximity to human population centers. Land holdings are small and/or include confined, caged

and landless production systems

▪ Small to medium scale, variable levels of intensification (from a single animal to a mid-sized enterprise such as a small peri-

urban cow dairy or small-scale fattening operator).

▪ Production may target home consumption, local markets or both.

Intensive/ commercial production (large pig and poultry production units, also includes ruminant fattening, large dairying and large-scale

dry lots)

▪ Operate at considerable scale and are highly commercialized with significant financial investments and technical inputs in

specialized housing, feeding, animal health and marketing approaches.

▪ Animals are typically housed and fed formulated, nutritionally balanced rations.

(Scale of operation, level of technical inputs and capital investment distinguishes from the urban/peri-urban category).

Yield targets should be entered at the commodity level, then at the farm size (crops) or production system (livestock) level, and then at the

sex and age level under each commodity. Targets do not need to be set for the TP and UP data points.

For the crop, fish, dairy and egg value chains, absolute yield values for yield at the IM-level and yield at the ZOI-level (which is indicator

EG.3-h) aren’t comparable due to different periods of recall and the methods of computation; however, trends in changes over time may be

similar.

For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25, and EG.3-10, -11, -12) only capture results for land that is

individually managed.

[1] Offtake quantity includes the entire weight of all animals that were sold, slaughtered, gifted or exchanged, including those for home

consumption.

[2] For tree crops, Number of hectares is recommended as UP, however, Number of trees can also be selected for UP. FTFMS does not

have the capability to convert and aggregate across the different UPs.

57!

RATIONALE:

Improving the yield for farm commodities contributes to increasing agricultural GDP, can increase income when other components of

agricultural productivity are in place (e.g., post-harvest storage, value addition and processing, markets), and can therefore contribute to

the IR of increasing sustainable productivity and the goal indicator of reducing poverty. Yield of farms, fisheries, and livestock is a key

driver of agricultural productivity and can serve as a proxy of the overall productivity of these value chains and the impact of interventions

when the trend is evaluated over a series of years, and/or appropriate covariates such as inter-annual weather conditions are included in

the analysis. In the GFSS Results Framework, this indicator measures Intermediate Result 1: Increased sustainable productivity,

particularly through climate-smart approaches.

UNIT:

Preferred TP units of measure:

Crops: metric tons

Pond aquaculture: kilograms

Cage aquaculture: kilograms

Milk: liters of milk

Eggs: number of eggs

Live animals: kilograms of animal offtake.

These TP units of measure are preferred,

however, in FTFMS users can select a

different unit of measure for TP under the

drop-down box or select “other” if

needed. If conversion factors are

available, FTFMS will convert other units

of measure to the preferred TP unit of

measure.

Required UP units of measure:

Crops: hectare

Tree crops: hectare is recommended

Pond aquaculture: hectare

Cage aquaculture: cubic meter of cage

Milk: maximum number of milking

animals

Eggs: maximum number of producing

hens

Live animals: total number in herd, flock,

or other group.

DISAGGREGATE BY:

For crops:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Farm size: Smallholder, Non-smallholder

THIRD LEVEL

Sex: Male, female

Age: 15-29, 30+

While country-specific definitions may vary, use the Feed the Future definition of a

smallholder crop producer, which is one who holds 5 hectares or less of arable land. The

farmer does not have to formally own the land.

For aquaculture:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Sex: Male, female

Age: 15-29, 30+

For livestock, dairy, and eggs:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Production system: Rangelands; mixed crop-livestock; urban/peri-urban; and

intensive/commercial production

THIRD LEVEL

Sex: Male, female

Age: 15-29, 30+

TYPE: Outcome

DIRECTION OF CHANGE: Stable and/or increasing is better

MEASUREMENT NOTES:

 LEVEL OF COLLECTION:

Activity-level, activity participants, targeted commodity/fisheries/livestock products

58!

 WHO COLLECTS DATA FOR THIS

INDICATOR:

Implementing partners

 DATA SOURCE:

Participant farmer/fisher/rancher sample surveys

; data collection through producer

organizations or farm records, routine activity records, as well as data collection through

producer organizations or farm records.

 FREQUENCY OF COLLECTION:

Annually, recommended to collect as close to post-harvest to optimize recall

 BASELINE INFO:

Baselines are required. Baseline data reflects the yield of targeted commodities in the year

prior to programming. If that information is not available, yield information collected during the

activity’s first year can serve as baseline.

REPORTING NOTES:

FTFMS DATA ENTRY NOTES:

If a sample survey of activity participants is used to collect yield data points, the sample weighted estimate of the total across all

participants must be calculated for each data point using appropriate sample weights before being entered into FTFMS.

Partners must also enter the number of participants in the activity, disaggregated by commodity and then sex and age of the participant

producer. Participants should only be counted once under each commodity regardless of the number of production cycles for the

commodity in the reporting year.

Data should be entered in FTFMS disaggregated to the lowest level. Partners should enter total production (TP), total units of

production (UP), and total number of participants, disaggregated by commodity, then by farm size (for crops) or production system (for

livestock, dairy, eggs), then by sex and by age. This procedure applies for each commodity. These disaggregations are required since the

most meaningful interpretation and use of yield information is at the specific commodity level, including the comparison of yield obtained by

female and male producers. FTFMS will calculate commodity-specific yield automatically.

For example, to report on the yield for maize for small-holder activity participants, partners should enter the following information for the

reporting year:

Commodity: Maize

Farm size: Small-holder

Number of participants

● total number of female, maize-producing small-holder activity participants;

● total number of male, maize-producing small-holder activity participants;

● total number of 15-29 year old, maize-producing small-holder activity participants;

● total number of 30+ year old, maize-producing small-holder activity participants.

Total production

● total production in mt on plots managed by female, maize-producing small-holder activity participants;

● total production in mt on plots managed by male, maize-producing small-holder activity participants;

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

While no particular methodology is required, crop cuts or farmer recall for determining TP and tablets with GPS capabilities for determining the number

of hectares for UP are recommended. Guidance for the ZOI-wide population-based surveys can help inform activity-level data collection for this indicator

and can be found at: https://agrilinks.org/post/feed-future-zoi-survey-methods.

59!

● total production in mt on plots managed by 15-29 year old maize-producing small-holder activity participants;

● total production in mt on plots managed by 30+ year old maize-producing small-holder activity participants.

Units of production

● total hectares in production managed by female, maize-producing small-holder activity participants;

● total hectares in production managed by male, maize-producing small-holder activity participants;

● total hectares in production managed by 15-29 year old maize-producing small-holder activity participants;

● total hectares in production managed by 30+ year old maize-producing small-holder activity participants.

Yield would then be calculated as mt / ha of maize.

To report on the yield of cattle managed in a mixed crop-livestock production system, partners should enter the following data points:

Commodity: Cattle, live

Production system: mixed crop-livestock production system

Number of participants

● total number of female, cattle-managing activity participants in the mixed crop-livestock production system;

● total number of male, cattle-managing activity participants in the mixed crop-livestock production system;

● total number of 15-29 year old, cattle-managing activity participants in the mixed crop-livestock production system;

● total number of 30+ year old, cattle-managing activity participants in the mixed crop-livestock production system.

Total production

● total kg of cattle offtake managed by female activity participants in the mixed crop-livestock production system;

● total kg of cattle offtake managed by male activity participants in the mixed crop-livestock production system;

● total kg of cattle offtake managed by 15-29 year old activity participants in the mixed crop-livestock production

system;

● total kg of cattle offtake managed by 30+ year old activity participants in the mixed crop-livestock production

system;

Units of production

● total number of cattle in the herd (in the reporting year) managed by female activity participants in the mixed crop-

livestock production system;

● total number of cattle in the herd (in the reporting year) managed by male activity participants in the mixed crop-

livestock production system;

● total number of cattle in the herd (in the reporting year) managed by 15-29 year old activity participants in the

mixed crop-livestock production system;

● total number of cattle in the herd (in the reporting year) managed by 30+ year old activity participants in the mixed

crop-livestock production system.

Yield would then be calculated as kgs of offtake / total number in herd of cattle.

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ Yield at the IM-level is no longer a PPR indicator. Target Country Missions should include, at a minimum, custom yield indicators

in the PPR for the same commodities for which ZOI-level data are collected.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3: Agriculture

INITIATIVE AFFILIATION: Global Food Security Strategy – Objective 1: Inclusive and sustainable agricultural-led economic growth

INDICATOR TITLE: EG.3-e Percent change in value-added in the agri-food system ("Ag GDP+") [National-level]

DEFINITION:

This indicator measures the change in value added (Gross Domestic Product or GDP) generated by the entire agri-food sector (Ag GDP+):

it combines agriculture GDP reported annually in the National Accounts (the National Accounts is the standard accounting system used to

measure and report the economic activity of a country) and the portion of downstream sectors that can be linked back to agriculture

production. The agri-food sector includes all of agriculture; agricultural processing; intermediate inputs used in agriculture and agricultural

processing; a portion of trade and transport services; and a portion of hotels and catering services.

The Ag GDP+ measure is defined as the sum of the following five components:

1. Agriculture (ISIC 01-03): All value-added generated in the agricultural sector, including forestry and fishing

2. Manufacturing (ISIC 10-12): All value-added generated by agricultural processing, including meat, fish, dairy, milling, beverages,

tobacco, animal feeds, and other food processing

3. Trade and transport sector (ISIC 45-53): The portion of GDP from the trade and transport sector associated with transactions of

agricultural and processed products, estimated using the share of agriculture and agricultural processing in total transaction cost

margins

4. Intermediate inputs: The portion of GDP generated by domestic producers of goods and services used in agriculture and

agricultural processing, estimated using the share of these two sub-sectors in total input demand

5. Hotel and Catering (ISIC 45-47): A portion of GDP generated in the hotels and catering sector associated with meals prepared

and purchased outside of the household (e.g., restaurants and food stalls), estimated using the share of agriculture and

agricultural processing inputs in total input purchases by the hotel and catering sector.

The Ag GDP+ measure does not include:

● Domestic work: The value-added generated by cooks or other domestic help hired by households

● Multiplier effects of second (or higher) round of production: For example, the value-added generated by the inputs used in the

production of agricultural and agricultural processing inputs.

To calculate AgGDP+, up-to-date national accounts and a country-level Social Accounting Matrix, or SAM, are required. A country-level

SAM is an economy-wide data framework that captures the detailed economic structure of a country. It combines various national

datasets, such as supply-use tables, household budget surveys, labor force surveys, and manufacturing surveys, to create a large

accounting table where the “economic accounts”, (production, households, inputs, government, and external trade – imports and exports)

are linked to each other. A SAM follows double-entry accounting principles (incomes are recorded along rows and expenditures along

columns) and each account’s total revenue (row total) equals total expenditures (column total) (Randriamamonjy & Thurlow, 2017: 2015

Social Accounting Matrix for Tanzania). Some components of the AgGDP+ measure are obtained directly from the national accounts

(agricultural production value added, for instance), while others are obtained by estimating from the SAM the value added generated

through specific sectoral linkages (the portion of hotel and catering associated with meals prepared and purchased by households outside

of the home, for instance). AgGDP+ is obtained by summing the value added of the different components over one year.

The indicator is calculated as the percent change in AgGDP+ between the reporting period and the baseline, ), as follows:

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RATIONALE:

Successful agricultural transformation leads to a greater share of agriculture-related value-added generated outside of agriculture itself.

Measuring agricultural GDP alone is not enough to track changes in the agriculture landscape as it underestimates the returns to

investments in agricultural modernization. This indicator captures renewed efforts under the GFSS to (i) measure the impact of

investments in agricultural value chains beyond agricultural production; and (ii) extend investments toward a market system approach, and

not just target agriculture production and productivity and is linked to Objective 1: Inclusive and sustainable agricultural-led economic

growth of the Global Food Security Strategy results framework.

UNIT:

Percent

DISAGGREGATE BY:

Ag GDP+ components: Agriculture; Manufacturing; Trade and Transport; Intermediate inputs; Hotel and

Catering

TYPE: Impact

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

National level

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Bureau for Food Security Implementing Partner for Post teams

 DATA SOURCE:

Secondary data: National accounts (GDP by sector) and country-level SAM (different data sources)

 FREQUENCY OF

COLLECTION:

Baseline estimates will be calculated for 2017; new estimates will be calculated every three years

thereafter

 BASELINE INFO:

A baseline is required.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

1. Enter the baseline Ag GDP+ estimate and the baseline year (the year to which the data apply.

2. Enter subsequent “actual” Ag GDP+ estimates under the “reporting year” when the estimate is available

3. Add a note in the “Indicator Comment” stating the year to which the “actual” estimate applies

4. FTFMS will automatically calculate the percent change from baseline

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ National-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Category EG: Economic Growth

INITIATIVE AFFILIATION: Global Food Security Strategy – Objective 1: Inclusive and sustainable agricultural-led economic growth

INDICATOR TITLE: EG.3-f Abbreviated Women's Empowerment in Agriculture Index [ZOI-level]

DEFINITION:

The Women’s Empowerment in Agriculture Index (WEAI) measures the empowerment, agency and inclusion of women in the agriculture

sector. The WEAI is administered to the self-identified primary female and male decision makers within the same household and to the

self-identified primary female decision maker in households with female but no male adults. Thus the “women” whose empowerment is

captured by the WEAI are primary decision-making females in households with male and female adults and with female adults only. The

WEAI comprises two sub-indices: The Five Domains of Empowerment (5DE), and the Gender Parity Index (GPI). The 5DE assesses the

degree to which women are empowered in five domains of empowerment in agriculture: (1) decisions about agricultural production; (2)

access to and decision-making power about productive resources; (3) control over the use of income; (4) leadership in the community; and

(5) time allocation. The 5DE also takes into account the percent of women who are empowered in the individual domains that do not meet

the empowerment threshold. The weight of the 5DE in the WEAI score is 0.90. The GPI measures gender parity within surveyed

households, and reflects the percent of women who are equally as empowered as men in their households. For those households that

have not achieved gender parity, the GPI shows the empowerment gap that needs to be closed for women to reach the same level of

empowerment as men. The weight of the GPI in the WEAI score is 0.10.

The Abbreviated WEAI (A-WEAI) is a shorter, streamlined version of the original WEAI. All five domains are retained, but the 10 indicators

in the original WEAI are reduced to six in the A-WEAI, and therefore it takes, approximately 30 percent less time to administer than the

original WEAI. The weights of the sub-indices from the original WEAI (5DE = 0.90, and GPI = 0.10) are also retained. The A-WEAI

includes a simplified 24-hour recall time module that collects only primary activities and streamlined sections on production decisions and

resources. A comparison of the domains and indicators in the original WEAI and the A-WEAI can be found in Table 1.

Table 1: WEAI and A-WEAI indicators (indicator weights in parentheses)

DOMAIN

WEAI: 10 indicators

A-WEAI: 6 indicators

Production

● Input in productive decisions (1/10)

● Autonomy in production (1/10)

● Input in productive decisions (1/5)

Resources

● Ownership of assets (1/15)

● Purchase, sale, or transfer of assets (1/15)

● Access to and decisions on credit (1/15)

● Ownership of assets (2/15)

● Access to and decisions on credit (1/15)

Income

● Control over use of income (1/5)

Leadership

● Group membership (1/10)

● Speaking in public (1/10)

● Group membership (1/5)

Time

● Workload (1/10)

● Leisure (1/10)

● Workload (1/5)

In addition to the required ZOI-level A-WEAI indicator, operating units (OU) are also encouraged to collect the A-WEAI, or domains and/or

indicators within the A-WEAI, as a custom indicator at the Implementing Mechanism level. For more information on A-WEAI background,

survey design and data collection, index construction (including Stata do files), and analysis, please refer to the A-WEAI Instructional

Guide found here: https://www.ifpri.org/sites/default/files/a-weai_instructional_guide_final.pdf.

RATIONALE:

Women play a critical and potentially transformative role in achieving inclusive and sustainable agricultural-led economic growth, yet

continue to face persistent obstacles and economic constraints. The A-WEAI measures the empowerment, agency, and inclusion of

women in the agriculture sector in an effort to identify ways to overcome those obstacles and constraints. The A-WEAI was developed to

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track changes in women’s empowerment levels that occur as a direct or indirect result of interventions under Feed the Future. This

indicator is linked to Objective 1: Inclusive and sustainable agricultural-led economic growth of the Global Food Security Strategy results

framework.

UNIT:

Score

DISAGGREGATE BY:

Age Category:

18-29;

30+

TYPE: Impact

DIRECTION OF CHANGE: Higher scores are better.

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Data for this indicator are collected from a random sample of primary female decision makers in

households in the ZOI (i.e. the targeted sub-national regions/districts where the USG intends to

achieve the greatest household- and people-level impacts on poverty, hunger, and malnutrition.) For

OUs reporting on the A-WEAI as a custom indicator, data for this indicator are collected at an activity

level.

 WHO COLLECTS DATA

FOR THIS INDICATOR:

The national statistics office under the LSMS-ISA+ national data systems strengthening activity or an

M&E contractor. For OUs reporting on the A-WEAI as a custom indicator, data for the A-WEAI are

collected by the Implementing Partner, or an Independent Evaluator.

 DATA SOURCE:

Data are collected via a population-based survey conducted in the ZOI using the Feed the Future

Survey Methods Toolkit (https://agrilinks.org/post/feed-future-zoi-survey-methods).

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where the USG

intends to achieve the greatest household- and individual-level impacts on poverty, hunger, and

malnutrition),

2) Office of Food for Peace development program areas, and

3) Resilience to recurrent crisis areas.

For OUs reporting on the A-WEAI as a custom indicator at an activity-level, data are collected via a

sample survey of activity participants. (Note: Collecting the A-WEAI at an activity-level is optional.)

 FREQUENCY OF

COLLECTION:

Data should be collected at baseline, and during each subsequent ZOI-level population-based survey

thereafter.

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 BASELINE INFO:

A baseline is required, and the value is from the FTF phase two baseline ZOI survey. For OUs

reporting on the A-WEAI as a custom indicator, baseline value is zero.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• Missions or the M&E contractor should enter ZOI-level values under the “High Level Indicators - [COUNTRY NAME]” mechanism

in the FTFMS.

• Enter the year that data were collected in the field under the Indicator Comment. If field data collection spanned two years, enter

the year field data collection began.

• Enter the indicator value for the overall indicator, for each sub-index, and for each age group disaggregate category under the

appropriate ZOI category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent crisis area).

• Enter the total number of primary female adult decision makers in the ZOI/area and for each age group disaggregate category in

the appropriate ZOI/area category (Target or Aligned Country ZOI, FFP development program area, or Resilience to recurrent

crisis area).

For example, a GFSS target country entering data from the Feed the Future ZOI baseline survey would enter:

1. Year of field data collection in the Target Country ZOI [in the Indicator Comment]

2. Sample-weighted A-WEAI score in the Target Country ZOI

3. Total number of primary female adult decision makers in the Target Country ZOI

4. Sample-weighted 5DE score in the Target Country ZOI

5. Sample-weighted GPI score in the Target Country ZOI

6. Sample-weighted A-WEAI score for women 18-29 years old in the Target Country ZOI

7. Total number of primary female 18-29 year old decision makers in the Target Country ZOI

8. Sample-weighted A-WEAI score for women 30+ years old in the Target Country ZOI

9. Total number of primary female 30+ year old decision makers in the Target Country ZOI

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

• ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

65!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3: Agriculture

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.3: Increased employment and entrepreneurship

INDICATOR TITLE: EG.3-g Employment in the agri-food system (“Ag EMP+”) [National-level]

DEFINITION:

This indicator estimates the total number of people who are working in the agri-food system in a given year. The agri-food system

includes: 1) all of agriculture; 2) agricultural processing; 3) intermediate inputs used in agriculture and agricultural processing; 4) the

portion of trade and transport services associated with transactions of agricultural products and agricultural processed products; and 5) the

portion of hotels and catering services associated with meal prepared and purchased outside of the household. This indicator is an

extension of the Ag GDP+ indicator (EG.3-e Percent change in value-added in the agri-food system ("Ag GDP+")).

In the base year (t=0), employment (number of people) in each of the five components of the agri-food sector is derived using available

employment data (from recent labor surveys, household surveys, and censuses). The sum of employment in each sector is the overall

indicator Ag EMP+.

Employment is then divided by the GDP in each of these sectors to derive an employment-to-GDP ratio (employment per dollar of GDP in

sector i, in year t=0). Every three years thereafter when the indicator Ag GDP+ is calculated, base year employment-to-GDP ratios are

multiplied by the estimated current GDP values to derive current employment in each of the five components of the agri-food system.

When new data on employment are available, employment-to-GDP ratios should be re-estimated, as they are expected to change over

time as an economy transforms.

RATIONALE:

Successful agricultural transformation leads to a greater share of agriculture-related employment outside of agriculture itself. Measuring

agricultural employment alone is not enough to track changes in the agriculture landscape as it underestimates the returns to investments

in agricultural modernization. This indicator allows us to capture renewed efforts under the GFSS to (i) measure the impact of investments

in agricultural value chains beyond agricultural production; and (ii) extend investments toward a market system approach, and not just

target agriculture production and productivity. This indicator is linked to IR 3 Increased employment and entrepreneurship in the Global

Food Security Strategy results framework.

UNIT:

Number of people

DISAGGREGATE BY:

Ag GDP+ components: Agriculture; Manufacturing; Trade and Transport; Intermediate inputs; Hotel

and Catering

TYPE: Impact

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

National level

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Bureau for Food Security Implementing Partner for Country Post teams

 DATA SOURCE:

Secondary data: AgGDP+ indicator data and national employment data (labor survey; household

66!

survey; census)

 FREQUENCY OF

COLLECTION:

Baseline estimates will be calculated for 2017; new estimates will be calculated every three years

thereafter

 BASELINE INFO:

A baseline is required.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

1. Enter the baseline Ag EMP+ estimate and the baseline year (the year to which the data apply)

2. Enter subsequent “actual” Ag EMP+ estimates under the “reporting year” when the estimate is available

3. Add a note in the “Indicator Comment” stating the year to which the “actual” estimate applies

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ National-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

67!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3: Agriculture

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.4: Increased sustainable productivity, particularly through climate-smart

approaches

INDICATOR TITLE: EG.3-h Yield of targeted agricultural commodities within target areas [ZOI-level]

DEFINITION:

Yield is the measure of the total output of production of an agricultural commodity (crop, fish, milk, eggs, live animal offtake

) divided by the

total number of units in production (hectares planted of crops, area in hectares for pond aquaculture, cubic meters of cage for cage

aquaculture, number of animals in the herd/flock for live animals, number of producing cows or hens for dairy or eggs). Yield per hectare,

per animal and per cubic meter of cage is a measure of productivity from individual producers of a crop, fisheries, or livestock, averaged

across the ZOI, including FTF participant producers and others.

For data collection and quality considerations, when collecting yield data as part of the ZOI population-based survey, BFS recommends

that yield data be collected on no more than three priority commodities at the ZOI level.

For selecting commodities, Post teams should focus on those where programming is intended to have the greatest impact on productivity

gains and can include crops, fisheries or livestock. For livestock, select the production system where programming is most likely to be

targeted and then select up to two species (if there are two or more species as priority value chains) over which to collect information

within that production system. See the list and description of the production systems below.

Yield of a particular commodity (reporting average yield across commodities is not meaningful) is calculated as the average producer-level

yield across all producers of the commodity in the ZOI. To do so, the yield of each individual producer in the sample is calculated by

dividing his/her total production of the commodity (TP) by the number of units of production (UP).

1. Total Production (TP); Kg, mt, number, or liters during the previous season for crops, previous month for fish, previous year for

live animals or meat, or previous day for milk, eggs

2. Total Units of Production (UP): Area planted in ha in the previous season for crops; current area of pond in ha for aquaculture

ponds; current cubic meters of cages for open water aquaculture; total number of animals in herd, calculated as the current

number of animals in the herd plus the number of animals that died or were offtaken (sold, slaughtered, loaned, gifted,

exchanged, or consumed within the household) over the previous year for live animals; number of animals in production the

previous day for dairy or eggs

3. Producer-level yield per hectare, per animal, or per cubic meter of cage (PY) = TP/UP

These individual producer-level yields are sample-weighted, then summed across all sampled producers (with relevant data) and divided

by the sample-weighted total number of producers of that particular commodity.

4. ZOI-level yield per hectare, per animal, or per cubic meter of cage (ZY) = sum of PY / sum of producers

Hence the indicator provides an estimate of the average producer-level yield for a particular commodity, and not an average ZOI-level yield

(which would be calculated as the sample-weighted sum of production divided by the sample-weighted sum of units of production).

Total production is the amount that is produced, regardless of how it was ultimately used. It also includes any postharvest loss (i.e.

postharvest loss should not be subtracted from total production.)

The units for TP by commodity type are:

● Crops: metric tons17

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● Pond aquaculture: kilograms1

● Cage aquaculture: kilograms1

● Dairy: liters of milk1

● Eggs: number of eggs1

● Livestock: weight in kilograms of entire animals which were offtaken (sold, slaughtered, loaned, gifted, exchanged, or consumed

within the household)

The units for UP by commodity type are:

● Crops: hectare

● Tree crop: hectare is recommended

[1]

● Pond aquaculture: hectare of pond area

● Cage aquaculture: cubic meter of cage

● Dairy: current number of milking animals

● Eggs: current number of producing hens

● Livestock: total number in herd, flock, or other group

The ZOI-level indicator is reported by commodity, then by the farm size for crops or production system for livestock disaggregate (see

below), then by sex and age of the producer.

For Posts working in livestock value chains, there is an additional disaggregation of “livestock production system” to support meaningful

analysis of outcomes. Select the system that best fits the Country Post programming. There are four production systems: Rangeland;

Mixed crop-livestock; Urban/peri-urban; and Intensive/commercial production.

Rangelands (pastoral, transhumant, agro-pastoral, silvo-pastoral, and extensive grasslands)

▪ Livestock and livestock-crop systems in which production is extensive with low stocking rates (typically <10 TLUs per hectare)

and there is a degree of herd mobility in the grazing system beyond the farm for at least part of the production cycle.

▪ Typically in arid and semi-arid zones, with rainfall dependent (forage) growing seasons less than 180 days per year.

Mixed crop-livestock (ruminants, pigs and poultry and small stock such as rabbits and guinea pigs and animals kept principally for

traction including oxen, buffalo and equids)

▪ Integrated crop and livestock production where crop and livestock systems rely on one another for inputs and exist in a

fixed rural location, typically a small holding or farmstead. For example, a system where at least some of the livestock feed

comes from crop residues and by-products produced on-farm.

Urban/peri-urban (including poultry, small scale dairy, small and large ruminants, pigs, micro-stock, small-scale fattening operations)

▪ Livestock are kept in close proximity to human population centers. Land holdings are small and/or include confined,

caged and landless production systems

▪ Small to medium scale, variable levels of intensification (from a single animal to a mid-sized enterprise such as a small peri-

urban cow dairy or small-scale fattening operator).

▪ Production may target home consumption, local markets or both.

Intensive/commercial production (large pig and poultry production units, also includes ruminant fattening, large dairying and large-scale

dry lots)

▪ Operate at considerable scale and are highly commercialized with significant financial investments and technical inputs in

specialized housing, feeding, animal health and marketing approaches.

▪ Animals are typically housed and fed formulated, nutritionally balanced rations. (Scale of operation, level of technical inputs and

capital investment distinguishes from the urban/peri-urban category).

For crops, fish, dairy, and egg value chains, IM-level and ZOI-level yield values are not comparable due to different periods of recall and

different methods of computation, however trends over time may be similar.

69!

Yield targets should be entered at the commodity level, at the farm size for crops or production system for livestock, and at the sex and

age level under each commodity. Targets do not need to be set for the TP and UP data points.

[1]

For tree crops, Number of hectares is recommended as UP, however, Number of trees can also be selected for UP. FTFMS won’t have the capability to

convert and aggregate across the different UPs.

RATIONALE:

Improving the yield for farm commodities for smallholders contributes to increasing agricultural GDP, can increase income when other

components of agricultural productivity are in place (e.g., post-harvest storage, value addition and processing, markets), and can therefore

contribute to the IR of increasing sustainable productivity and the goal indicator of reducing poverty. Collecting yield at the ZOI level will

enable an examination of agriculture productivity changes beyond those for producers that directly participate in USG programming. This

indicator will demonstrate outcomes that have scaled beyond participants to have an effect at the ZOI level and illustrate a stronger link

between gains in productivity and increases in income. Yield of farms, fisheries, and livestock is a key driver of agricultural productivity

and can serve as a proxy of the productivity of these value chains and the impacts of interventions when the trend is evaluated over a

series of years and/or appropriate covariates such as inter-annual weather conditions are included in the analysis. In the GFSS Results

Framework, this indicator measures Intermediate Result 1: Increased sustainable productivity, particularly through climate-smart

approaches.

UNIT:

TP units of measure:

Crops: metric tons

Pond aquaculture: kilograms

Cage aquaculture: kilograms

Milk: liters of milk

Eggs: number of eggs

Live animals: kilograms of animal offtake.

UP units of measure:

Crops: hectare

Tree crops: hectare (recommended)1

Pond aquaculture: hectare

Cage aquaculture: cubic meter of cage

Milk: number of productive animals

Eggs: number of producing hens

Live animals: number in herd, flock, or other

group.

DISAGGREGATE BY:

For crops:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Farm size: Smallholder, Non-smallholder

THIRD LEVEL

Sex: Male, female

Age: 15-29, 30+

While country-specific definitions may vary, for the ZOI-level indicator, a smallholder crop

producer is defined as one whose household holds 5 hectares or less of arable land. The

farmer does not have to formally own the land.

For aquaculture:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Sex: Male, female

Age: 15-29, 30+

For livestock:

FIRST LEVEL

Commodity: see commodity list in FTFMS

SECOND LEVEL

Production system: Rangelands; mixed crop-livestock; urban/peri-urban; and

intensive/commercial production

THIRD LEVEL

Sex: Male, female

Age: 15-29, 30+

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TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Population-based, ZOI-level, producers of targeted commodities.

 WHO COLLECTS DATA FOR THIS

INDICATOR:

LSMS-ISA World Bank Grant or M&E contractor conducting the ZOI-level population-

based survey.

 DATA SOURCE

Primary data collected through a population-based survey or LSMS-ISA covering the

ZOI. For crops and pond aquaculture, TP is obtained from farmer recall and UP from

direct measurement using a tablet computer with GPS capabilities (recommended), while

for livestock and crate aquaculture, both TP and UP are obtained from farmer recall, as

noted in the Feed the Survey Methods guidance.

 FREQUENCY OF COLLECTION:

Data should be collected at baseline, and in each subsequent ZOI-level survey

thereafter. Data should be collected as close to post-harvest as possible to optimize

recall.

ZOI refers to three types of ZOIs:

1) the target or aligned country ZOI (i.e. the targeted sub-national regions/districts where

the USG intends to achieve the greatest household- and individual-level impacts on

poverty, hunger, and malnutrition),

2) Office of Food for Peace development program areas, and

3) Resilience to recurrent crisis areas.

 BASELINE INFO:

Baseline data reflects the yield of targeted commodities in the ZOI in the production year

covered by the Feed the Future phase two ZOI survey.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

• Missions or M&E contractor should enter ZOI-level values under the "High Level Indicators – [COUNTRY NAME]" mechanism in

FTFMS.

• The sample-weighted estimate of the total across all ZOI producers must be calculated for each disaggregated data point using

appropriate sample weights before being entered into FTFMS.

• The following data points need to be entered: total production, units of production, and estimated number of producers

cultivating/managing the targeted commodity in the ZOI, disaggregated by commodity; then for crops disaggregated by farm

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Guidance documents can be found at: https://agrilinks.org/post/feed-future-zoi-survey-methods

71!

size and for livestock disaggregated by production system; then by sex (male, female) and by age. Commodity-specific data,

disaggregated by sex and by age, are required because the most meaningful interpretation and use of yield information is at the

specific commodity level, including the comparison of yield obtained by female and male producers. FTFMS will calculate

commodity-specific yield per ha, animal or cubic meter of cage automatically.

• Data should be entered in FTFMS disaggregated to the lowest level—i.e. by commodity then by sex and age. The procedure

applies for each commodity.

For example, to report on the yield for maize, for smallholders, the following information for the reporting year is entered:

Commodity: Maize

Farm size: Smallholder

Number of producers

● estimated number of smallholder female maize producers in the ZOI

● estimated number of smallholder male maize producers in the ZOI

● estimated number of 15-29 year old smallholder maize producers in the ZOI

● estimated number of 30+ year old smallholder maize producers in the ZOI

Average yield

● mean yield in mt per hectare on plots managed by smallholder female maize producers

● mean yield in mt per hectare on plots managed by smallholder male maize producers

● mean yield in mt per hectare on plots managed by smallholder 15-29 year old maize producers

● mean yield in mt per hectare on plots managed by smallholder 30+ year old maize producers

To report on the yield of cattle managed in a mixed crop-livestock production system, enter the following data points:

Commodity: Cattle, live

Production system: mixed crop-livestock production system

Number of producers

● total estimated number of female producers who manage cattle in the mixed crop-livestock production system in the ZOI

● total estimated number of male producers who manage cattle in the mixed crop-livestock production system in the ZOI

● total estimated number of 15-29 year old producers who manage cattle in the mixed crop-livestock production system in the

ZOI

● total estimated number of 30+ year old producers who manage cattle in the mixed crop-livestock production system in the

ZOI

Average yield

● mean yield in kg of offtake per head of cattle managed by female producers in the mixed crop-livestock production system

● mean yield in kg of offtake per head of cattle managed by male producers in the mixed crop-livestock production system

● mean yield in kg of offtake per head of cattle managed by 15-29 year old producers in the mixed crop-livestock production

system

● mean yield in kg of offtake per head of cattle managed by 30+ year old producers in the mixed crop-livestock production

system

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ ZOI-level indicators are not included in the PPR master indicator list. Missions may include them in PPR reporting as custom

indicators.

72!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3.1: Agricultural Enabling Environment

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.2: Strengthened and expanded access to markets and trade

INDICATOR TITLE: EG.3.1-1 Kilometers of roads improved or constructed as a result of USG assistance [IM-level]

DEFINITION:

A road opens up transport from rural spaces where rural-based production activities, such as agriculture, are taking place and connects,

either directly or indirectly, with population centers and market activity. A road “improvement” indicates that the U.S. Government

intervention significantly improved the ease of commercial transport along that road, while “constructed” refers to a new road.

To count, a road need not be paved with cement or asphalt but should significantly facilitate the transport of goods compared to the

previous situation without the road or without the road improvement. Only count those roads improved or constructed during the reporting

year.

RATIONALE:

The linkage of rural communities to markets is considered a crucial means of increasing agricultural and other rural-based production.

Roads improve access of rural communities to food at reasonable prices and to markets for their produce and to health and nutrition

services and allow greater off-farm employment opportunities. This indicator is linked to Global Food Security Strategy – IR.2:

Strengthened and expanded access to markets and trade.

UNIT:

Kilometers

DISAGGREGATE BY:

Construction type: Improved, Constructed (new)

TYPE: Output

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity level; only those roads improved or constructed with U.S. Government assistance

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Direct measurement, activity records

 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

Baseline is zero

REPORTING NOTES

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – CCIR 1: Strengthened global commitment to investing in food security

INDICATOR TITLE: EG.3.1-14 Value of new USG commitments and private sector investment leveraged by the USG to support

food security and nutrition [IM-level]

DEFINITION:

The indicator includes new long-term capital investments (e.g., property, plant, and equipment and other fixed assets) and new operating

capital investments (e.g., inputs or inventory) leveraged by the USG. Private sector co-investment - both cash and in-kind - for

implementing specific activities (e.g., resulting from a successful GDA application) should also be included. It includes both upstream and

downstream investments. Upstream investments include any type of agricultural capital used in the agricultural production process such as

inputs (e.g., seeds, fertilizer, pesticides, etc.) and machinery. Downstream investments could include capital investments in equipment

used for post-harvest transformation or processing of agricultural products or the transport of agricultural products to markets. In-kind

investments, which should be valued at market rates, could include legal or business development services.

“New USG commitments” refers to funds in the form of a direct loan, part of a grant, or other award designed to leverage additional funds

from private sector organizations. Subsidies paid to structure a guarantee or insurance product do not count as new USG commitments.

For multi-year activities, commitments are recorded at the outset of the activity, if made prior to the start of the activity, or during the year

when they are made, if commitments are received during implementation of an activity.

“Private sector” includes for-profit formal companies managing nutrition, agriculture, and/or food system-related activities. A community-

based organization (CBO) or nongovernmental organization (NGO) investment may be included if the CBO or NGO engages in for-profit

nutrition, agriculture, and/or food system-related activities.

“Investment” is defined as any use of private sector resources intended to increase future production, output, or income, etc. Investments

are recorded on a yearly basis, as they are made. In-kind investments are recorded at market value in USD.

“Leveraged by the USG” indicates that the new investment was directly encouraged or facilitated by activities supported by the Feed the

Future initiative. Usually, the Feed the Future activities will take the form of a grant, direct loan, guarantee, or insurance coverage from the

USG (see examples below).

Examples:

Overseas Private Investment Corporation (OPIC)/United States International Development Finance Corporation (USIDFC):

1. OPIC provides political risk insurance on a $40 million equity investment by a U.S. investor in a large-scale commercial farm in

Zambia that produces wheat, maize, barley and soya. OPIC is insuring 90% of the investment, or $36 million. The farm’s

expansion is also financed by a $10 million loan from a local commercial bank and a $5 million loan from the International

Finance Corporation of the World Bank Group directly to the Zambian farm. The investment and loan funds will be used to

expand and upgrade the farm’s irrigation system and other infrastructure improvements. The total private sector capital

leveraged is $50 million, consisting of the sum of the U.S. equity firm’s investment ($40 million) and the local commercial debt

($10 million). The debt and equity investments are reported in the year in which they are made. The IFC’s $5 million is not

included, as it is money from a multi-lateral, and is not considered “private sector investment,” nor is it “leveraged” by OPIC.

2. OPIC provides a $10 million direct loan to a U.S.-based NGO to expand its working capital lending to small farmers and co-ops

located in South America. The $40 million expansion also includes $20 million raised through private placement bonds and $10

million in cash equity from the NGO. In this example, the total new USG commitment is $10 million and the private capital

leveraged by the OPIC investment is $30 million. These investments are reported in the year in which they are made.

United States Agency for International Development (USAID):

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1. USAID provides a 50% loan portfolio guarantee to a U.S.-based impact investor to expand its portfolio into small and growing

businesses in the agriculture sector in Feed the Future target countries. The guarantee will cover 50% of investments made, up

to a total of $17.5 million in investments. The total amount of private sector capital leveraged that could be reported is $17.5

million. The private capital leveraged actually reported is the amount that was actually invested, and is reported in the year

in which the investments are made.

RATIONALE:

Increased investment is the predominate source of economic growth in the agricultural and other economic sectors. Private sector

investment is critical because it indicates that the investment is perceived by private agents to provide a positive financial return and

therefore is likely to lead to sustainable improvements in agricultural market systems. Agricultural growth is critical to achieving the Feed

the Future (FTF) goal to “Sustainably Reduce Global Hunger, Malnutrition and Poverty.” This indicator is linked to CCIR: Strengthened

global commitment to investing in food security in the GFSS Results Framework.

UNIT:

U.S. Dollars

Note: Convert local currency to U.S.

Dollars at the average market foreign

exchange rate for the reporting year or

convert periodically throughout the

year if there is rapid devaluation or

appreciation.

DISAGGREGATE BY:

Type of investment:

● USG commitment amount (using "commitment" to include funding in the form of

direct loans or a grant);

● Private sector partner leveraged amount (using "leveraged" to include both cash

and in-kind investment valued at market rates from the private sector partner)

TYPE: Output

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level; new commitments and investment leveraged within reporting year by the USG

activity

 WHO COLLECTS DATA FOR

THIS INDICATOR:

US Government agencies and implementing partners

 DATA SOURCE:

Private sector financial records, program data, and US Government agency records

 FREQUENCY OF COLLECTION:

Annually (USG commitments are only reported once, in the year they are made)

 BASELINE INFO:

Baseline is zero

REPORTING NOTES

75!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2: Agriculture Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy - IR.2: Strengthened and expanded access to markets and trade

INDICATOR TITLE: EG.3.1-c Value of targeted agricultural commodities exported at a national level [National-level]

DEFINITION:

This indicator tracks the value exports from a country in U.S. dollars on a national-level, including those being exported within the region

and beyond. It can include both formal and informal trade, food and non-food agricultural commodities.

Targeted commodities are those the Country Post is focusing on for value chain and market system strengthening. Other agriculture

commodities supported by Country Post programming can be reported on as desired.

The intent of this indicator is to monitor exports in targeted agricultural commodities relevant to Post programming. It includes exports

attributable to USG interventions and those outside of direct U.S. Government attribution. Reporting is limited to what is available from

national statistics agencies.

RATIONALE: Increased agricultural trade is one of the end results of efficient markets. This indicator reports progress on IR 2:

Strengthened and expanded access to markets and trade of the GFSS results framework.

UNIT:

US dollars

DISAGGREGATE BY:

Commodity

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

National-level

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners or Post staff

 DATA SOURCE:

The data is collected from national statistics agencies once available.

 FREQUENCY OF

COLLECTION:

Annual

 BASELINE INFO:

For commodities the Country Post is already supporting, the baseline year is 2017. For commodities

subsequently identified by the Country Post, the baseline year is the year before interventions begin.

REPORTING NOTES

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FTFMS DATA ENTRY NOTES:

• Report the data in FTFMS the year it becomes available. Please enter the year the data covers in the indicator comment, as a

time lag is very common.

• Please enter the following data points in FTFMS:

o Value (in U.S. dollars)

o Volume (in metric tons) sold

• Note: Convert local currency to U.S. dollars at the average market foreign exchange rate for the reporting year.

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ FTFMS reporting requires specific commodity to be selected. For PPR reporting, commodities are clustered into commodity

groups and reported under these groups, which are: horticulture; animal products; cereal; oilseeds; dry grain pulses and

legumes; roots, tubers and other staples; other. FTFMS will produce aggregated totals for the indicator and for each commodity

group disaggregate for entry in FACTSInfo.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.1: Agricultural Enabling Environment

INITIATIVE AFFILIATION: Global Food Security Strategy – CCIR 5: More effective governance, policy, and institutions

INDICATOR TITLE: EG.3.1-d Milestones in improved institutional architecture for food security policy achieved with USG

support [Multi-Level]

DEFINITION:

This performance indicator reports on milestones in improved institutional architecture for food security policy achieved. Institutional

architecture (IA) broadly refers to “the entities and processes for policy formulation and implementation”

, and more specifically in this

case to those for food security policy. IA for food security policy reflects both the capacity of specific types of organizations (such as

ministries, policy think tanks, citizen interest groups and district governments) operating at different levels (international, regional, national,

or sub-national) and the processes through which these organizations interact towards a common food security goal (such as through

inter-ministerial processes, scorecard reviews, or decentralization). A milestone is a ‘positive change’ that marks a significant achievement

in the development of better performing, more effective policy systems and describes how the change contributes to improved policies and

policy outcomes within a GFSS country or regional plan. Food security policy is multi-sectoral and interdisciplinary, and includes policies

on agriculture, nutrition, resilience, and other related areas that affect food security.

Operating Units (OUs) are the primary reporting unit for this indicator. OUs should report milestones achieved during the past fiscal year

with USG funding. OUs are responsible for identifying the relevant milestones achieved working with their implementing partners, donor

coordination groups, inter-agency committees, and other stakeholders. The milestones should align strategically with country or

stakeholder priorities.

A milestone can relate to changes in organizations and processes leading to improved policy making and implementation at various levels:

sub-national or local, national, regional, or international. It is expected that Washington-based OUs will report on milestones that are at the

international, regional, or national levels; regional OUs will report on milestones that are at the regional or national levels; and bilateral OUs

will report on milestones that are at the national or sub-national levels; although there can be exceptions.

There are six core IA policy elements that are considered key for a robust food security policy institutional architecture

. These core IA

policy elements are described below and in more detail in Annex 1 to this PIRS. The milestones reported should fit in one or more of these

policy elements. These elements are not mutually exclusive and some overlap exists between them.

Milestones should be reported annually in a table (see template on Agrilinks here: https://www.agrilinks.org/post/institutional-architecture-

assessment-food-security-policy-change), with the following information provided in a concise way for each milestone achieved: brief

description of the milestone; the timeline i.e., the fiscal year the milestone is achieved; the level of implementation (see paragraph above);

what primary and secondary (if more than one) IA policy element(s) the milestone can be associated with; where does the milestone fit

within USG strategic objectives; what was the role of the USG support; what stakeholders were supported in achieving the milestone; and

what source(s) of information is available to document the milestone. Although this indicator reports milestones achieved in the past fiscal

year, the template allows some flexibility to also list milestones the OU is actively working on but are yet to be achieved. In this case, the

timeline column should reflect the fiscal year when the OU expects the milestone to be achieved. These milestones should be recorded

year after year in the annual reporting table until they are achieved. If a milestone was dropped, a quick explanation as to why it was

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

GFSS Implementation Guidance for Policy Programming (https://www.feedthefuture.gov/resource/global-food-security-strategy-technical-guidance-on-

policy-programming/)

Additional background information and resources are available on Agrilinks: https://www.agrilinks.org/post/institutional-architecture-assessment-food-

security-policy-change

78!

dropped should be provided in the “Notes” column.

IA Policy Elements

● Policy Element 1: Predictability of the Guiding Policy Framework –the effectiveness of the legislative process and the extent to

which the relevant laws, regulations, and policies governing the policy development process are transparent, predictable and

consistently applied.

o Illustrative Milestones: Establishment of parliamentary access to food security expertise; Comment period for draft law

established; Citizen groups have regular and reliable access legislative processes and documentation.

● Policy Element 2: Policy Development and Coordination – the capacity and effectiveness of the organizations and entities to

initiate and develop food security policy and the strengthening of the relationships among these entities.

o Illustrative Milestones: Facilitation of the formation of a joint sector food security committee in the Prime Minister’s

office (national); a regional protocol for coordinating staple food data (regional level); Planned schedule of meetings

between Planning, Finance and Agriculture Ministries; Intergovernmental coordination forum established and

operational (e.g. meets regularly, shares information, takes decisions).

● Policy Element 3: Inclusivity and Stakeholder Consultation – the degree of inclusivity in consultation with key groups critical to

the food security sector and the extent to which the different groups are engaged, including groups across government, the

private sector and among non-governmental organizations.

o Illustrative Milestones: Concerted efforts resulting in farmer association membership in an apex society (sub-national

level), support to a representative civil society association focused on food security priorities (sub-national/national);

Civil society and producer group platform for input to agricultural policy and program development; Joint sector review

(JSR) committee established; inclusive policy dialogues formalized.

● Policy Element 4: Evidence-based Analysis – the capacity and effectiveness of the organizations, processes, and fora

responsible for collecting and analyzing data, and the extent to which evidence is used to inform or revise policy change.

o Illustrative Milestones: Improved dissemination of agricultural data across multiple Ministries; Improved timeliness and

availability of food security-related surveys and survey analysis; Public access to data on performance of the

agriculture and food security sectors (e.g. dashboard monitoring systems; website data publication).

● Policy Element 5: Policy Implementation – the detail of implementation plans, alignment with line ministry and agency

responsibilities, adequate funding, and quality of monitoring and evaluation plans

o Illustrative Milestones: Improved budget justification for policy implementation; resources allocated for programs

commensurate with objectives; Capacity of local government authorities to implement programs strengthened;

Monitoring system for program and policy impacts established.

● Policy Element 6: Mutual Accountability – the effectiveness of the process by which multiple partners (such as government,

donors, private sector and civil society organizations) agree to be held responsible for the commitments that they have voluntarily

made to each other. It relies on trust and partnership around shared agendas. Mutual accountability is supported by evidence

that is collected and shared among all partners. The principle of mutual accountability is expected to stimulate and broaden the

practice of benchmarking, mutual learning and harmonization of national development efforts, while encouraging a greater level

of trans-boundary cooperation and regional integration.

o Illustrative Milestones: CAADP Joint Sector Review successfully completed; Donor mapping tool providing input on

donor investments available; Joint metrics established for monitoring food security performance.

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RATIONALE:

A country’s capacity to undertake transparent, inclusive, predictable, and evidence-based policy change is fundamental to improving food

security outcomes. Investing in strengthening a country’s IA for food security policy is a GFSS priority as it provides a foundation for

building the systemic capacities for managing a multi-sectoral food security program. The importance of good governance and

accountable institutions in delivering on predictable and transparent policy change is widely recognized

20, 21

. Data collected for this

indicator will contribute to an improved understanding of the importance of policy IA and will be used in conjunction with other policy-

related GFSS data to identify relationships between the policy system and policy changes. This indicator provides an opportunity to track

the types of milestones and achievements OUs are delivering to improve systems, processes, and relationships that influence food

security policy. This indicator is linked CCIR 5: More effective governance, policy, and institutions of the Global Food Security Strategy.

UNIT:

1/0 (if a table is available or not)

DISAGGREGATE BY: (disaggregates in table only; not on indicator screen)

Level: Sub-national; national; regional; and international

IA policy element: Predictability of the Guiding Policy Framework;

Policy Development and Coordination; Inclusivity and Stakeholder Consultation; Evidence-based

Analysis; Policy Implementation; Mutual Accountability

TYPE: Outcome

DIRECTION OF CHANGE: N/A

MEASUREMENT NOTES

 LEVEL OF COLLECTION

Sub-national, national, regional, or international

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Country Post staff and BFS

 DATA SOURCE:

Data will be collected by relevant OU/Country Post/BFS officers engaged in activities supporting IA

achievements

 FREQUENCY OF

COLLECTION:

Annual

 BASELINE INFO:

N/A

REPORTING NOTES

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Most recent arguments and evidence can be found in ‘Why Nations Fail?’ by D. Acemoglu and J. Robinson, Deckle Edge, 2012.

IFPRI. Global Food Policy Reports.!

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FTFMS DATA ENTRY NOTES:

• This indicator does not have a quantitative component. It is reported via a standard table with the required information

concerning the milestones achieved during the reporting year. A template table can be downloaded from Agrilinks or from the

indicator data entry screen in FTFMS.

• For USAID, individual IPs/IMs should not fill out data for this indicator. Rather, data on policy work should be provided to the

USAID Mission/OU for compilation and entry into the table.

• The completed table should be uploaded in FTFMS under the IM titled “High-level indicators -- [COUNTRY NAME]” by clicking

the “Other Reporting Documents” tab on the “Enter or View Narratives” screen.

• Additional documentation and supporting evidence should also be uploaded under “Other Reporting Documents”.

• On the data entry screen, OU should enter 1 if a table was uploaded and 0 if not, to alert reviewers to look into “Other Reporting

Documents” to download the information.

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ANNEX 1: Institutional Architecture Policy Elements & Illustrative Sub-elements

Policy Element 1: Predictability of the Guiding Policy Framework

Clearly Defined and Consistent Policy Framework: The policy framework impacting food security policy-making is clearly defined, and consistently

applied and enforced from year to year.

Predictability and Transparency of the Policy Making process: The policy development process is transparent in accordance with the rules contained

within the country’s constitution, basic law, and elsewhere in the formal legal framework.

Clear and Functional Legislative System: There is a legislative capacity to deal with food security change, and the legislative requirements are clearly

defined and predictable.

Appropriate Dispute Resolution Process/Judicial Framework: The judicial system is perceived as fair and effective, and there is an appropriate

system for dispute resolution where conflicts arise relating to food security policy.

Clearly defined Institutional Responsibilities: Institutional responsibilities are clearly defined, consistently applied, and predictable from year to year.

Policy Element 2: Policy Development & Coordination

Approved Food Security Strategy/Investment Plan: There is an approved/official multi-sectoral, multi-year food security plan developed, which

specifies priorities and objectives, and addresses the roles of various contributors, including across government, the private sector, and CSOs. The vision

and strategy to improve food security is clear.

Predictable Policy Agenda and Priorities Developed: The policy items required to achieve the national food strategy have been identified and

documented, i.e., specific policy objectives exist.

Annual Work Plans: There is an annual work plan that identifies objectives and activities in regard to policy development.

Coordination Process: There is an entity, such as a coordination unit or task force, that has defined membership and meets regularly to discuss, develop

and coordinate food security policy development (and oversee cross-sector coordination).

Secretariat/Administrative Support Function: There is an adequate staff capability to perform required support processes, including coordination,

meeting management, communication, and document management. This may be a stand-alone secretariat, or a responsibility within an existing entity.

Technical Capacity: There are work groups, or technical committees, that have the authority and capacity to perform the following functions: identify

policy and technical challenges/issues, develop sector- or project-specific policies/strategies, consult within the sector and draft funding proposals. There

should be active participation by the private sector and CSOs on the technical work groups (as appropriate).

Political Support and Approval: There is a line of authority/participation by high-level decision-makers above the ministerial level so as to enable

efficient political support for the passage and development of new policies, e.g. involvement of prime minister’s office (especially for policies that cut

across sectors, e.g. trade and agriculture).

Engagement of Parliament/Legislative Body: There is engagement from the country’s legislative entity to debate and engage on food security issues,

and to sponsor and advocate for the required legal/policy changes.

Policy Element 3: Inclusivity and Stakeholder Consultation

Inclusive Participation within the Policy Coordination Management Entity: The main coordination entity has: a) clear goals and participation from key

government ministries (beyond just Ministry of Agriculture) and; b) some representation from non-government entities, particularly from donors.

Outreach and Communications: There is a process for interacting with stakeholders and sharing information. This could include regular public “forums”,

a website of key information and other mechanisms.

Private Sector Participation – Opportunity/Space: The private sector is provided meaningful opportunity to participate in policy formulation and strategy

discussions. This could be through participation in the management/steering committee, in technical work groups and/or through other forums.

Communications and interactions should be two-way, and access to key information should be readily available.

Private Sector Participation – Capacity to Participate: Some organizations representing the private sector have the capacity to participate in

government-led discussions on food policy. This is to say they are able to represent their members, they are able to articulate and communicate policy

positions, and they are able to provide some level of evidence-based analysis to support their viewpoints.

Participation of CSOs – Opportunity/Space: The CSO sector, including representation from women’s associations and farmers associations, is

provided meaningful opportunity to participate in policy formulation and strategy discussions. This could be through participation in the

management/steering committee, in technical work groups and/or through other forums. Communications and interactions should be two-way, and

access to key information should be readily available.

Participation of CSOs – Capacity to Participate: Some organizations representing civil society, including representation from women’s associations and

farmers associations, have the capacity to participate in government-led discussions on food policy. This is to say they are able to represent their

members, they are able to articulate and communicate policy positions, and they are able to provide some level of evidence-based analysis to support

their viewpoints.

Policy Element 4: Evidence-based Analysis

Economic and Financial Analysis Completed as a Component of Planning: National food security priority policy initiatives/investment plans are based

on economic and financial analysis, including independent policy analysis. The analysis is available for public review.

Performance Monitoring Measures and Targets Developed: The national food security policies/plans include specific objectives, performance

indicators, and targets exist to monitor the accomplishment of the objectives.

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Quality Data Exists for Policy Monitoring: There is a database of quality statistics that is used to routinely report and analyze progress in achieving

objectives. (Analysis to be conducted by USDA – and not as part of this assessment framework.)

Quality Data is Available for Policy Making: Data on the performance of the agriculture sector and the food security are publicly available and shared in

a timely manner. This information is available for others to use and analyze.

Inclusion of Analysis in the Policy Development Process: Evidence-based analysis is considered and used to develop policy priorities/policy

proposals.

Capacity to Monitor Policy Implementation and Results: The government has the ability to review data on policy performance and produce an analysis

of the policy’s effectiveness. A policy analysis function/unit exists and has adequate and skilled staff, and is sufficiently funded. If required, specific

analysis can be outsourced to specialized firms or consultants as needed (case-by-case).

Annual Performance Measurement Report Produced and Reviewed: Evidence-based analysis is produced to review policy effectiveness (for

implemented policies). A formal review session is held, and includes key development partners (including principal donors and multilateral partners, such

as FAO and IFPRI). Recommendations are developed as a result of the review and incorporated into subsequent plans.

Independent Analysis Capacity Exists: There exists an independent capacity to analyze food security data and use the analysis to make policy

recommendations and engage in policy discussion and advocacy. Such an analysis could be conducted by a research institute, university or similar non-

governmental/objective organization. This capacity should be engaged in the government's policy development and review process as, for example,

through papers, forums or participation introduced in official policy review and discussion meetings.

Policy Element 5: Policy Implementation

Implementation Plans Developed: The overall food security strategy has been broken down into programs and projects that have: a) a sufficient level of

detail to permit implementation; b) have been “packaged” into priority projects that can be managed by ministerial units; and 3) “packaged” priorities can

be translated into funding proposals to gain support for projects/programs from development partners (to address financing gaps).

System in Place to Analyze Implementation Capacity Constraints: An analysis of institutional, workforce, system and financial constraints is

conducted. Critical implementation constraints are identified; a work plan is developed to address constraints; and implementation actions are moved

forward (and periodically reviewed).

Food Security Policy Priorities Aligned with Work Plans of Line Ministries: The priority policy and associated objectives of the national food security

strategy are broken down into specific programs and projects (with a sufficient level of detail) so that policy actions can be implemented by line ministries.

The plans of individual ministries, and units within ministries, align with overall national strategy and its policy objectives.

Policy Implementation Budget Committed by Host Country: Resources are committed by the host country to implement the identified policy agenda.

Over time, the country’s budget is adjusted to provide adequate financing for the implementation of actions required to implement policy priorities. Budget

documents, including budget proposals, are released fully and in a timely manner.

Supplemental Implementation Funds Secured: Proposals can be submitted, and funds secured, to address financing gaps. Funds may come from

multilateral funds (such as GAFSP), regional organizations, bilateral donors and the private sector.

Monitoring and Evaluation: Capacity exists within the public sector, private sector, or civil society to review the effectiveness and impact of policy

changes. Sector reviews are performed and other research evidence is collected. There is a system to share, store, and access the findings from these

reviews.

Policy Element 6: Mutual Accountability

A Forum Exists for Regularly Scheduled Donor-Government Meetings: These meetings discuss policy and programs and set priorities. Meetings

may include, for example, Joint Sector Reviews, sector working groups or other similar arrangements.

Joint Policy Priorities Developed: A document exists that articulates the shared policy objectives between the government and the donor community.

Monitoring System Exists: Performance measures exist (for the performance commitments of the government and for the performance commitments of

the donors). There is a schedule for reviewing and documenting progress – at least on an annual basis.

Donor Coordination – Alignment and Harmonization: There is a process for donor participation in the food security policy process and for aligning

government and donor objectives and priorities. Donor programs should contribute directly to host country strategies, plans, and objectives. This may

include the signing of cooperation frameworks that indicate a joint commitment to specific policy change goals.

Private Sector Accountability: The government provides feedback to the private sector on the performance of the food security program (including the

private sector’s role) and provides an opportunity for dialogue on the program and its performance.

CSO Sector Accountability: The government provides feedback to the CSO sector on the performance of the food security program (including the role of

CSOs) and provides an opportunity for dialogue on the program and its performance.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – Output: could be applicable to many parts of results framework.

INDICATOR TITLE: EG.3.2-2 Number of individuals who have received USG-supported degree-granting non-nutrition-related

food security training [IM-level]

DEFINITION:

This indicator measures the number of people who are currently enrolled in or have graduated during the reporting year from a degree-

granting technical, vocational, associate, bachelor, master, or Ph.D. program. Degree candidates being supported through partial

fellowships or exchange programs can be counted toward this indicator. A person who completes one degree-granting program in the

fiscal year and is currently participating in another degree-granting program should be counted only once, no matter the length of either

degree-granting program; she/he should be counted under the Continuing disaggregate.

Non-nutrition-related food security training includes training in areas such as agronomy, crop science, climate science, plant pathology,

rural sociology, anthropology, agricultural economics, agricultural engineering, seed science and systems, bioinformatics, and conflict and

conflict resolution. It does not include nutrition-related trainings; nutrition-specific and nutrition-sensitive training should be reported under

HL.9-4.

This indicator measures individuals receiving degree-granting training; individuals applying new practices based on their training should be

reported under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or

technologies with USG assistance [IM-level].

RATIONALE:

Measures enhanced human capacity for policy formulation, technology development and research/education capacity building and

implementation, which is key to transformational development. This is an output indicator and could be applicable to many parts of the

Global Food Security Strategy results framework.

UNIT:

Number

DISAGGREGATE BY:

Sex: Male, Female

Duration:

● New = the individual received U.S. Government-supported long-term training for the first time during

the reporting year

● Continuing = the individual received U.S. Government-supported long-term training in the previous

year and continued to receive it in the reporting year

TYPE: Output

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES:

 LEVEL OF

COLLECTION:

Activity-level, direct beneficiaries

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 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Activity training records

 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

Baseline is zero

REPORTING NOTES:

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2 Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – Output: could be applicable to many parts of results framework.

INDICATOR TITLE: EG.3.2-7 Number of technologies, practices, and approaches under various phases of research,

development, and uptake as a result of USG assistance [IM-level]

DEFINITION:

This indicator tracks the progression of new or significantly improved technologies, practices, and approaches through research and

development (R&D) to the demonstrated uptake by public or private sector stakeholders. The R&D process should be hypothesis driven,

testable, and independently replicable. The technologies, practices, and approaches under R&D should have the potential to achieve

significant improvements in reducing poverty, hunger, and malnutrition versus existing alternatives. The technology, practice, or approach

should be one that can clearly be articulated as having the potential to reach and benefit a smallholder farmer, other individual, or

household at some point in the future. New or significant improvements to existing, food security-related technologies, practices, and

approaches are to be counted. An improvement would be significant if, among other reasons, it served a new purpose or allowed a new

class of users to employ it. Examples include a new blend of fertilizer for a particular soil type or proper sequencing of interventions to

increase the adoption of a new technology. Diagnostic research or research focused on identifying the root cause of an issue should not

be counted under this indicator. Support through USG assistance includes human, financial, institutional support, in full or in part, for the

discovery, research, development, testing, or making available for uptake by the public and private sector.

The technology, practice, or approach is disaggregated first into R&D categories, then into the phase of research. Definitions and

illustrative examples of technologies, practices, and approaches by R&D category are:

● Plant and Animal Improvement Research: Includes trait, marker, and gene discovery for agriculturally important

characteristics, coupled with application of conventional breeding and/or advanced biotechnological approaches for the genetic

improvement of plant and animal species. Products include improved germplasm (varieties, breeds, etc.) that is higher-yielding,

more resilient to biotic and abiotic stresses, higher in nutritional content (e.g. biofortified crops such as vitamin A-rich sweet

potatoes, high-protein maize, or improved livestock breeds), and/or possesses improved market or processing traits.

● Production Systems Research: Includes Integrated Pest Management (including grafting), Sustainable Intensification (e.g.

mechanization, small-scale irrigation, planting schedules, soil management), livestock management, post-harvest and food

safety technologies; management practices for feed or food, Natural Resource Management, and vaccines and animal health

services. Products include new land preparation, harvesting, processing and product-handling and food safety technologies and

practices including packaging and storage methods; sustainable water and land management practices; and sustainable

aquaculture and fisheries practices.

● Social Science Research: Includes research concerning the effectiveness of agricultural policy options (policy research);

research on the socio-behavioral, socioeconomic, or sociopolitical factors that influence decision-making; economic research on

products or approaches that overcome barriers to farmer investment in or adoption of improved technology and management

practice, etc. (economic research); research or creation of new/improved tools for market access, including financial and

insurance products (market access research); and nutrition research. Products include new risk management approaches, such

as the integration of partially-subsidized index insurance into social safety nets that cost-effectively increase the resilience of

vulnerable households; and approaches to effectively and sustainably change nutrition behaviors or the adoption of improved

seeds.

See Annex 1 at the end of this PIRS for guidance on counting and reporting technologies, practices, and approaches by category.

A description of the four phases of research and development is below. Technologies, practices and approaches should be reported under

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each phase reached during the reporting year. It is not required that all technologies, practices and approaches pass through all four

phases to be reported under the indicator nor is it essential that all investments start at Phase I. For example, a seed variety that is only

being field-tested for country-level adaptation and then submitted for country-level certification would only be tracked through Phases II

and III. However, any technology, practice, or approach that is reported under Phase IV must have been previously reported under Phase

I, II, or III during the life of the activity.

As the indicator is purposefully defined broadly to ensure that a full range of technologies, practices, approaches and uptake modalities

can be captured, no assumptions should be made regarding comparability of the level or type of uptake across technologies, practices, or

approaches, or the value or depth of support for and by the public and/or private sectors for any technology, practice, or approach.

In some cases more than one OU may count the same technology or practice. This would occur if the technology or practice were

developed, for instance, in collaboration with a U.S. university under a mechanism funded by one operating unit and then passed through a

regional collaboration mechanism funded by a different operating unit to other countries. If multiple OUs are co-funding development of the

same technology, practice or approach under the same R&D mechanism, they should coordinate with the COR/AOR to decide which OU

should report on the indicator in FTFMS on behalf of all contributing OUs. We discourage individual OUs reporting prorated results based

on funding proportions in these cases.

Four phases of research, development, and uptake:

Phase I - Under research as a result of USG assistance: Count new technologies, practices, or approaches under research in the

current reporting year. Technologies and management practices are under research when the process to develop or support the

development of the product is conducted under ideal or controlled conditions such as a laboratory or greenhouse. Note that for non-biotech

crops, much or all of this phase might be conducted outdoors and in soil, and yet be considered to be in controlled conditions; these

attributes do not make this work “field testing.” Additionally, livestock research conducted on-station and in confined settings would also be

considered to be in controlled conditions. For social science research, only theoretical, efficacy, or secondary data research on a specific

approach (e.g. the use of index insurance to increase on-farm investment) that could significantly improve development outcomes should

be counted.

Phase II - Under field testing as a result of USG assistance: “Under field testing” means that research has moved from focused

development, where a promising technology or practice has been identified, to broader testing of effectiveness under conditions intended

to resemble those that the potential users of the new technology will encounter. Testing might be done in the actual facilities or fields of

potential users, or it might be in a facility set up to duplicate those conditions to prove expected performance or superiority to current

technologies or practices. For biotechnology research, a change of location from a contained laboratory or greenhouse to a confined field

with the receipt of a permit indicates that the research has completed the “under research” phase and moved into the “under field testing”

phase. The goal of this phase is to achieve a documented ‘real world’ assessment of potential performance and feasibility, by accumulating

technical information and test results that indicate that the expected performance is achievable. Some technologies may have legal

requirements for the collection, submission, and approval of assessment data, which must be satisfied before completing this Phase.

Social science research conducted through a randomized controlled trial (RCT) or quasi-experimental pilot for identification of

effectiveness or causal impact should be counted under this phase.

Phase III - Made available for uptake as a result of USG assistance: Count technologies, practices or approaches that are ready to be

taken up or adopted by a public or private sector entity, which would then disseminate the technology, practice or approach to end users in

a manner that promotes sustainable, widespread adoption at the population level (e.g. hundreds of thousands to millions, depending on

the technology or practice and context). This phase does not count the number of technologies and practices actually transferred by public

or private entities, including implementing partners. Completing a research activity or transferring a technology, practice, or approach to

another researcher for continued R&D activities do not in themselves constitute having made something available for uptake. Conditions

may need to be met before a technology, practice, or approach can move into the public domain such as licensure, certification, or policy

guidelines and this Phase captures technologies, practices, and approaches that have met these conditions. It must have passed all

required regulatory approvals such that intermediaries and end users (i.e. service input providers, farmers) are able to use and

disseminate it legally. Any technology, practice, or approach made available for uptake in a previous year should not be included, unless

the availability has increased in geographic scope (i.e. made available for uptake in another country) in this reporting period.

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Phase IV – Demonstrated uptake by the public and/or private sector: A technology, practice, or approach has “demonstrated uptake”

if any public- and/or private-sector actor has institutionalized or provided support for dissemination, independent of USG assistance, at

any point during the reporting period. This phase aligns with the Foreign Assistance indicator for Science, Technology, Innovation, and

Research 11 (STIR-11). As a result, it does not include uptake by the end user (i.e. individual customers or farmers) or by bilateral or

multilateral donor organizations (e.g. USAID Missions). End users applying new technologies are measured under EG.3.2-24. While

technologies, practices, and approaches are often delivered successfully through donor pathways, the goal is to identify a sustainable

pathway for delivery through the public or private sector. Examples of demonstrated uptake include a) non USAID financial support

provided through public, private, or public-private agreements (i.e. non-revenue monies from non-donor sources) for dissemination

including - but not limited to - private investments, grants, loans, funds, or government bonds; b) incorporation/institutionalization of an

approach into a host country government’s national or sub-national guidelines, policies, or other legal frameworks; c) market introduction

such as the technology or practice being offered for sale; and, d) distribution or delivery of a technology or practice to an end-user via the

public and/or private sectors such as by agricultural extension agents.

A technology, practice or approach should be reported each year it is actively in Phase I or Phase II during the mechanism’s life of activity.

A technology, practice, or approach reported under Phase III and IV should be counted only once per country by each Implementing

Partner across the life of the activity, and should be reported on during the first reporting year when the technology, practice or approach is

made available for uptake (Phase III) or has demonstrated uptake (Phase IV). It should only be counted once in Phase IV for each country

regardless of whether the private sector and the public sector have both demonstrated uptake of the technology, practice or approach, or

whether multiple private or public sector actors have done so. In some cases, multiple IPs may have provided support in Phase I, II, or III

and IV for a technology, practice or approach. Each IP may report on the technology, practice or approach at each of the phases it

supports, even if this results in multiple IPs counting the same technology, practice, or approach in the same phase in the same country.

This indicator does not count whether a technology, practice or approach has ever been made available for uptake or been taken up in the

past - only whether that technology, practice or approach has been made available for uptake or has demonstrated uptake by the public

and/or private sectors during the life of the activity.

Total number of unique technologies: Alongside tracking the progress of technologies, practices and approaches across four phases of

research and development, FTFMS also captures the number of unique technologies. Since a single technology, practice or approach can

reach more than one phase in a single year, the system allows the reporting of that technology, practice, approach in multiple phases (i.e.,

double-counting within a category, across phases). FTFMS captures the counts of each unique technology, practice or approach

supported by category in a single year. While you can double-count the same technology in each of the different phases it reaches in a

single year, you cannot double count the same technology across categories.

The public sector includes non-governmental organizations, public sector higher education institutions, recipient country governments (i.e.

any department, office, subdivision, or other entity within the national or sub-national government of the country where the technology,

practice, or approach is supported), and other organizations that are part of the public sector but not included in the categories above. The

private sector includes private organizations (i.e. businesses and corporations; business, industry and trade associations; corporate

foundations; social enterprises; financial institutions, investors, and impact investors), private philanthropy (i.e. private foundations and

philanthropists), and other organizations that are part of the private sector but not included in the categories above. A blended adoption

includes uptake by both the public and private sectors. This could be simultaneous uptake by both, or separate uptake by each, during a

reporting period. However, the technology, practice or approach would only be reported once in both of these scenarios.

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RATIONALE:

According to the USAID Scientific Research Policy (2014), research allows USAID to develop, test, refine and evaluate the acceptability

and cost-effectiveness of new and improved products, tools, approaches and interventions that focus on the key concerns of developing

countries. Research also helps inform policy, strategic direction of programs, and methods to overcome barriers to implementation in

developing country settings by strengthening the evidence-base for development. The U.S. Government Global Food Security (GFS)

Research Strategy frames research programming in terms of a Research and Development (R&D) pipeline, in which new or significantly

improved technologies advance through phases of research before being transferred to technology-scaling partners for dissemination and,

ultimately, widespread adoption by developing-country beneficiaries. The R&D pipeline contains innovative, scalable products and

practices to improve productivity, nutrition, and resilience in Feed the Future partner countries. This indicator tracks the four phases of

research and development and aligns with the cross-cutting contributions of research under the Global Food Security Strategy (GFSS)

results framework.

UNIT:

Number

DISAGGREGATE BY:

Category of Research

-Plant and Animal Improvement Research

-Production Systems Research

-Social Science Research

Within each category disaggregate by phase of development:

-Under research as a result of USG assistance

-Under field testing as a result of USG assistance

-Made available for uptake as a result of USG assistance

-Demonstrated uptake by the public and/or private sector with USG assistance

TYPE: Output (phases 1,2,3);

Outcome (phase 4)

DIRECTION OF CHANGE: Progress to a higher phase is usually better.

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level; only those technologies under development with USG support

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Activity records, reports or surveys

 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

Baseline is zero

REPORTING NOTES

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FTFMS DATA ENTRY NOTES:

FTFMS will sum the unique number of technologies, practices, and approaches entered by research category. Within each category,

technologies / practices / approaches can be double-counted across the phases reached that year, so a summation will not be done of the

phases.

Any data reported under Phase III and IV must include the specific technology, practice, or approach in an Indicator Comment in FTFMS.

Phase IV information must also include an explanation of which Phase(s) (I, II, and/or III) received USG support before there was

demonstrated uptake by the public or private sector. Details for all technologies, practices, and approaches in Phase III and IV will also be

collected for the Research Rack Up database through a separate survey instrument.

Annex 1: Guidance on counting technologies, practices, and approaches by phase of research

As indicator EG.3.2-7 Number of technologies, practices, and approaches under various phases of research, development, and uptake as

a result of USG assistance is broadly inclusive of different disciplines of food security research and development (R&D) and uptake, it is

necessary to further define how technologies, practices, and approaches are categorized in each category. Thus, the following chart was

created to further define the categories of technologies, practices, and approaches as well as how to count them at each phase.

Category of

Research

Phase of

Research

Type of

Technology,

Practice or

Approach

What to Count

Plant and Animal

Improvement

Phase I: Under

research

Novel gene with

known major effect(s)

on specific traits.

Each unique gene or genetic element identified that controls the

expression of a specific major function in the plant or animal.

Transgene or genetic

element for improved

trait

Each unique transgene or genetic element with a known function in the

plant system.

Tissue-specific gene

promoter identified

and validated

Each gene promoter with its own unique sequence and function in the

plant or animal (but see note below under gene constructs).

Molecular genetic

marker linked to

genes controlling

specific traits

Each molecular marker identified and linked to a particular gene with a

major effect that is related to a specific function/trait (but see note below

under gene constructs).

Transformation-ready

gene constructs

Each gene construct capable of being used in transformation can be

counted as a separate technology. Note: If a gene and/or promoter are

included in a construct for transformation, they should not also be

counted separately.

QTL for major effects

identified and

validated

Mapped and/or phenotyped for desired trait. Each QTL in a specific

position on the linkage group and related to a specific trait can be

counted as a separate technology. Used in association mapping studies.

Panel of genes or

markers used in

association studies

Each SNP panel used in association mapping studies.

Phenotyping and

crossing block

population

Population of lines or breeds with improved trait to be used in

phenotyping and large crossing blocks. Counts are number of

populations (not lines). For further genetic/breeding studies under Phase

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Research line with

improved trait

(Introgression, SP,

RIL, NIL)

Lines for research: Introgression lines, lines of self-pollinate crops, RIL,

NIL with desired specific genes/QTLS/marker loci/traits incorporated in a

background phenotype. Includes MPS and mapping populations. The

improved trait, the genetic control of the trait and the genetic background

of the lines are important points to consider in counting lines. A group of

lines identified for the same trait with the same genetic system and

derived from the same parents should be taken as one technology.

However, lines identified for a different trait from the same population

may be counted as separate technology for further genetic/breeding

studies under Phase I.

Plant line for gene

pyramiding

Each group of lines containing the unique gene for pyramiding.

Inbred, DH, hybrid

lines with desired

traits

Breeding populations: Doubled haploid lines (DHLs), inbred lines (hybrid

parents), hybrids with desired traits. Last step of Phase I. A group of

DHLs identified for the same trait with the same genetic system and

derived from the same bi- parents should be taken as one technology.

However, DHLs identified for a different trait from the same population

should be counted as separate technology. Each inbred line or hybrid

with its own features can be counted as a separate technology.

Plant germplasm

accession with

specific trait

Each accession identified as a source of gene(s) for a specific trait,(e.g.

heat, drought, growth, and disease tolerance)

Animal germplasm

accession

Each accession identified as a source of gene(s) for a specific trait,(e.g.

heat tolerance, disease resistance and productivity)

Transgenic line with

improved trait

Each transgenic line with its own desirable attribute for further use. Note

– distinct events with the same construct in the same background

material do not constitute multiple technologies. Count each construct in

a particular background (not each event) as ready for field testing; Last

step of Phase I.

Animal line with

specific trait as

sources of genes

Count each line with desirable attribute for further use (e.g. heat

tolerance, disease resistance and productivity).

Phase 2 - Under

field testing

Conventional plant

genotype or line

under field testing

Each new and superior genotype or line over the standard check for a

specific trait with field performance data under end-user conditions.

Breeds or lines with

improved traits under

field testing

Each new and improved line over the standard check for a specific trait

with field performance data under end-user conditions.

Transgenic line under

field testing

Each new and improved transgenic line over the standard check for a

specific trait with field performance data under end-user conditions.

Conventional variety

submitted for

regulatory approval

Improved conventional variety for which regulatory approval or

certification is actively being sought so that it may be commercially

released. Last step of Phase II.

Transgenic variety or

breed submitted for

regulatory approval

Improved transgenic variety for which regulatory approval or certification

is actively being sought so that it may be commercially released. Last

step of Phase II.

Phase 3 - Made

available for

uptake

Varieties, cultivars,

lines, and breeds

Each variety, improved line, or breed made available for dissemination

during the reporting year may be counted as a separate technology. To

be considered Phase III, the technology must have passed all approvals

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(e.g. variety registration, certification, biosafety approvals) such that

intermediaries and end users (e.g. service/input providers and farmers)

are able to disseminate or use them legally.

Phase 4 -

Demonstrated

uptake by the

public and/or

private sector

Varieties, cultivars,

lines, and breeds

Demonstrated uptake includes any support for, or adoption by, the public

and/or private sector at any point during the reporting period. Examples

include procurement or accessing sources of non USAID financial

support provided through public, private, or public-private agreements

(i.e. non-revenue monies from non-donor sources) to disseminate the

technology, including - but not limited to - private investments, grants,

loans, funds, or government bonds; market introduction; or, delivery via

public and/or private sectors such as by agricultural extension agents.

This does not include utilization by end users (i.e. individual customers

or farmers) or by donor organizations (i.e. USAID Missions).

Production

Systems

Research

Production

Phase I - Under

research

N/A

Includes identification of appropriate candidate practices and system

components and significant improvements in existing practices, working

under idealized conditions.

Phase 2 - Under

field testing

N/A

New/improved system components or management practices in field

testing under end-user conditions.

Phase 3 - Made

available for

uptake

N/A

New/improved system component or formal recommendations ready for

dissemination to farmers, including guidance for where the practice is

appropriate and other conditions for use. To be considered Phase III, the

new/improved system component must have passed all required

regulatory approvals such that end users (e.g. service/input providers

and farmers) are able to use them legally.

Phase 4 -

Demonstrated

uptake by the

public and/or

private sector

N/A

Demonstrated uptake includes any support for, or adoption by, the public

and/or private sectors at any point during the reporting period. Examples

include institutionalization/incorporation into a host country government’s

national or sub-national guidelines, policies, or other legal frameworks;

market introduction; or, delivery via public and/or private sectors such as

by agricultural extension agents. This does not include utilization by end

users (i.e. individual customers or farmers) or by donor organizations

(i.e. USAID Missions).

Social Science

Research

Phase I - Under

research

N/A

Theoretical, efficacy or secondary data social science research finding

on an innovative approach for use by other researchers. Examples of

theoretical research on a specific innovation include a paper outlining the

potential positive impacts of smart subsidies on fertilizer take-up or how

integrating subsidized index insurance into public safety net programs

can increase resilience more cost-effectively than alternatives. Basic

research on poverty dynamics or determinants of food security would not

be included in Phase 1.

Phase 2- Field

Testing

N/A

Count each approach undergoing a randomized controlled trial (RCT) or

experimental/quasi-experimental pilot for testing effectiveness or causal

impact of the approach. Only the first field test of any given approach

should be counted.

Phase 3 - Made

available for

uptake

N/A

Social science research finding on an approach or innovation available

for uptake by development programs and the public and private sector.

Examples include policy guidelines or recommendations, a formal

training with training materials, or evidence-based toolkits. Only the first

such instance will be counted per approach or innovation.

Phase 4 -

Demonstrated

N/A

Demonstrated uptake includes any support for, or adoption by, the public

and/or private sectors at any point during the reporting period. Examples

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uptake by the

public and/or

private sector

include incorporation/institutionalization into a host country government’s

national or sub-national guidelines, policies, or other legal frameworks;

or, delivery via public and/or private sectors such as by agricultural

extension agents. This does not include utilization by end users (i.e.

individual customers or farmers) or by donor organizations (i.e. USAID

Missions).

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.1: Strengthened inclusive agriculture systems that are productive and

profitable

INDICATOR TITLE: EG.3.2-24 Number of individuals in the agriculture system who have applied improved management

practices or technologies with USG assistance [IM-level]

DEFINITION:

This indicator measures the total number of agriculture system actors participating in the USG-funded activity who have applied improved

management practices and/or technologies promoted by the USG anywhere within the food and agriculture system during the reporting

year. These individuals can include:

● Farmers, ranchers and other primary sector producers of food and nonfood crops, livestock and livestock products, fish and

other fisheries/aquaculture products, agro-forestry products, and natural resource-based products, including non-timber forest

products such as fruits, seeds, and resins;

● Individuals in the private sector, such as entrepreneurs, input suppliers, traders, processors, manufacturers, distributors, service

providers, and wholesalers and retailers;

● Individuals in government, such as policy makers, extension workers and natural resource managers;

● Individuals in civil society, such as researchers or academics and non-governmental and community organization staff.

The indicator tracks those individuals who are changing their behavior while participating in USG-funded activities. Individuals who

attended training or were exposed to a new technology do not count under this indicator unless the individual actually applies what she/he

learned. For example, if an agriculture extension agent attends a gender-sensitive agriculture extension training, he can be counted under

this indicator once he applies what he learned by changing the way he reaches out to and interacts with the female farmers to whom he

provides extension services.

Improved management practices or technologies are those promoted by the implementing partner as a way to increase agriculture

productivity or support stronger and better functioning systems. The improved management practices and technologies are agriculture-

related, including those that address climate change adaptation or climate change mitigation. Implementing partners promoting one or a

package of specific management practices and technologies report practices under categories of types of improved management practices

or technologies. The indicator should count those specific practices promoted by the activities, not just any improved practice. Even then,

baseline values could be quite high, especially if a wide range of practices is included in the list of promoted practices. If that happens, IPs

should look at the disaggregated prevalence of individual practices to identify ones that are already widely applied and remove those from

the list (and from plans to promote) and recalculate the indicator without the already common practices.

This indicator captures results where they were achieved, regardless of whether interventions were carried out, and results achieved, in

the ZOI.

Management practice and technology type categories, with some illustrative (not exhaustive) examples, include:

● Crop genetics: e.g. improved/certified seed that could be higher-yielding, higher in nutritional content (e.g. through bio-

fortification, such as vitamin A-rich sweet potatoes or rice, high-protein maize), and/or more resilient to climate impacts (e.g.

drought tolerant maize, or stress tolerant rice); improved germplasm.

● Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and

transplantation; cultivation practices such as planting density, crop rotation, and mounding.

● Livestock management: e.g. improved livestock breeds; livestock health services and products such as vaccines; improved

livestock handling practices and housing; improved feeding practices; improved grazing practices, improved waste management

practices, improved fodder crop, cultivation of dual-purpose crops.

● Wild-caught fisheries management: e.g. sustainable fishing practices; improved nets, hooks, lines, traps, dredges, trawls;

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improved hand gathering, netting, angling, spearfishing, and trapping practices.

● Aquaculture management: e.g. improved fingerlings; improved feed and feeding practices; fish health and disease control;

improved cage culture; improved pond culture; pond preparation; sampling and harvesting; management of carrying capacity.

● Natural resource or ecosystem management: e.g. terracing, rock lines; fire breaks; biodiversity conservation; strengthening of

ecosystem services, including stream bank management or restoration or re/afforestation; woodlot management.

● Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of fungicides;

improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and pesticides; crop

rotation; aflatoxin prevention and control.

● Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase biotic

activity and soil organic matter levels, such as soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter,

mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control.

● Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes.

● Agriculture water management - non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that

improve water quality.

● Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while

preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and degraded

lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of

perennials; practices that promote greater resource use efficiency (e.g. drip irrigation, upgrades of agriculture infrastructure and

supply chains).

● Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing

the severity of the impacts of climate change. Examples include drought and flood resistant varieties; short-duration varieties;

adjustment of sowing time; agricultural/climate forecasting; early warning systems; diversification, use of perennial varieties;

agroforestry; risk insurance.

● Marketing and distribution: e.g. contract farming technologies and practices; improved input purchase technologies and

practices; improved commodity sale technologies and practices; improved market information system technologies and

practices.

● Post-harvest handling and storage: e.g. improved transportation; decay and insect control; temperature and humidity control;

improved quality control technologies and practices; sorting and grading, sanitary handling practices.

● Value-added processing: e.g. improved packaging practices and materials including biodegradable packaging; food and

chemical safety technologies and practices; improved preservation technologies and practices.

● Other: e.g. improved mechanical and physical land preparation; non-market- and non-climate-related information technology;

improved record keeping; improved budgeting and financial management; Improved capacity to repair agricultural equipment;

improved quality of agricultural products or technology.

This indicator endeavors to capture the individuals who have made the decision to apply a particular management practice or technology,

not those who have had to do so as a condition of employment or an obligation. For example, if a manager in a company that distributes

agriculture produce decides to use refrigerator trucks for transport and plans the distribution route using GIS information to maximize

efficiency, both practices that are promoted by the USG-funded activity, the manager is counted as one individual; the five drivers of the

newly refrigerated trucks who are driving the new routes are not counted. If the manager and co-owner together decided to apply these

new practices, they are counted as two individuals. Another example would be if a franchise offers a new fertilizer mix developed with USG

assistance and makes it available to franchisees, yet those franchisees make the decision whether or not to offer it. In this case both the

decision-maker(s) at the franchise level and the franchisees who decide to offer it get counted as individuals applying a new management

practice.

It is common for USG-funded activities to promote more than one improved technology or management practice to farmers and other

individuals, This indicator allows the tracking of the total number of participants that apply any improved management practice or

technology during the reporting year and the tracking of the total number of participants that apply practices or technologies in specific

management practice and technology type categories.

● Count the participant if they have applied a management practice or technology promoted with USG assistance at least once in

the reporting year. Count the producer participant who applied improved management practices or technologies regardless of the

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size of the plot on which practices were applied.

● Count each participant only once per year in the applicable Sex disaggregate category and Age disaggregate category to track

the number of individuals applying USG-promoted management practice or technology type. If more than one participant in a

household is applying improved technologies, count each participant in the household who does so.

● Under the Commodity disaggregate, count each participant once under each commodity for which they apply a USG-promoted

management practice or technology type. For example, if a participant uses USG-promoted improved seed for the focus

commodities of maize and legume, count that participant once under maize and once under legumes.

● Count each individual once per management practice or technology type once per year under the appropriate Management

practice/technology type disaggregate. Individuals can be counted under a number of different Management

practices/technology types in a reporting year.

o For example:

▪ If a participant applied more than one improved technology type during the reporting year, count the

participant under each technology type applied.

▪ If an activity is promoting a technology for multiple benefits, the participant applying the technology may be

reported under each relevant Management practice/technology type category. For example, a farmer who is

using drought tolerant seeds could be reported under Crop genetics and Climate adaptation/climate risk

management depending for what purpose(s) or benefit(s) the activity is being promoted to participant

farmers. For example, if a private enterprise invested in newer, more efficient machinery to process or

otherwise improve the raw product that is also intended to reduce emissions intensities, this practice would

be counted under “value-added processing” and “climate mitigation”.

▪ Count a participant once per reporting year regardless of how many times she/he applied an improved

practice/technology type. For example, a farmer has access to irrigation through the USG-funded activity and

can now cultivate a second crop during the dry season in addition to the rainy season. Whether the farmer

applies USG-promoted improved seed to her plot during one season and not the other, or in both the rainy

and dry season, she would only be counted once in the Crop Genetics category under the Management

practice/technology type disaggregate (and once under the Irrigation category.)

▪ Count a participant once per practice/technology type category regardless of how many specific

practices/technologies under that technology type category she/he applied. For example, a project is

promoting improved plant spacing and planting on ridges. A participant applies both practices. She/he would

only be counted once under the Cultural practices technology type category.

IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicators EG.3.2-24 Number

of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level],

and EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level] if they use

clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to

strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number and volume of certified soy

seed sales by assisted firms during the reporting year to estimate the number of farmers applying certified soy seed (by using a

conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically

validated planting density. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment.

However, if an agrodealer gives away seed packs with the purchase of other inputs as a promotion, more validation would be necessary

for the IP to assume farmers purchasing the other input are also applying that seed.

If a lead farmer cultivates a plot used for training, e.g., a demonstration plot used for Farmer Field Days or Farmer Field School, the lead

farmer should be counted as a participant applying improved practices/technologies for this indicator. In addition, the area of the

demonstration plot should be counted under indicator EG.3.2-25 Number of hectares under improved management practices or

technologies with USG assistance [IM-level]. However, if the demonstration or training plot is cultivated by a researcher (a demonstration

plot in a research institute, for instance), neither the area nor the researcher should be counted under this indicator or indicator EG.3.2-25.

Participants who are part of a group or members of an organization that apply improved technologies on a demonstration or other common

plot should not be counted under this indicator, the area of the common plot should not be counted under indicator EG.3.2-25 Number of

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hectares under improved management practices or technologies with USG assistance [IM-level], and the yield should not be counted

under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among program participants with USG assistance [IM-level].

For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25 and EG.3-10, -11, -12) only capture results for land that is

individually managed.

This is a snapshot indicator, which is designed to capture farmer application only for the reporting year. Individuals who applied a USG

activity-promoted management practice before the intervention constitute the baseline. Individuals that continue to apply the USG activity-

promoted management practice during the project period get counted for applying the technology in any subsequent years they apply that

technology, even if they weren’t directly touched by the intervention in the reporting year (if the IP continues to track information on former

participants). However, this also means that yearly totals can NOT be summed to count application by unique individuals over the life of

the project.

However, there are some cases where group members can be counted under this indicator. For example, as a result of participating in a

USG-funded activity, a producer association purchases a dryer and then provides drying services for a fee to its members. In this scenario,

any member that uses the dryer service can be counted as applying an improved management practice under this indicator.

Note that the list of practice/technology type disaggregates is broader under this indicator than the list of practice/technology type

disaggregates under indicator EG.3.2-25 because this indicator tracks application of improved practices/technologies beyond those that

are applied to a defined land or water area.

RATIONALE:

Improved management practices and technological change and adoption by different actors throughout the agricultural system will be

critical to increasing agricultural productivity and supporting stronger and better functioning systems. This indicator falls under IR 1:

Strengthened inclusive agriculture systems that are productive and profitable in the Global Food Security Strategy (GFSS) results

framework.

UNIT:

Number

DISAGGREGATE BY:

FIRST LEVEL

Value chain actor type:

▪ Smallholder producers (e.g. farmers, ranchers, and other primary sector producers of food

and nonfood crops, livestock products, wild fisheries, aquaculture, agro-forestry, and natural

resource-based products)

▪ Non-smallholder producers (e.g. farmers, ranchers, and other primary sector producers of

food and nonfood crops, livestock products, wild fisheries, aquaculture, agro-forestry, and

natural resource-based products)

▪ People in government (e.g. policy makers, extension workers)

▪ People in private sector firms (e.g. processors, service providers, manufacturers)

▪ People in civil society (e.g. staff and volunteers from non-governmental organizations,

community-based organizations, research and academic organizations)

▪ Others

Note: Only count producers under the "Producers" disaggregate and not the "Private Sector

Firms" disaggregate to avoid double-counting. While private sector firms are considered part of

civil society more broadly, only count them under the "Private Sector Firms" disaggregate and not

the "Civil Society" disaggregate to avoid double-counting.

Smallholder Definition: While country-specific definitions may vary, use the Feed the Future

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definition of a smallholder producer, which is one who holds 5 hectares or less of arable land or

equivalent units of livestock, i.e. cattle: 10 beef cows; dairy: two milking cows; sheep and goats:

five adult ewes/does; camel meat and milk: five camel cows; pigs: two adult sows; chickens: 20

layers and 50 broilers. The farmer does not have to own the land or livestock.

SECOND LEVEL

Sex: Male, Female

Age: 15-29, 30+

Management practice or technology type: Crop genetics, Cultural practices, Livestock

management, Wild-caught fisheries management, Aquaculture management, Natural

resource or ecosystem management, Pest and disease management, Soil-related fertility

and conservation, Irrigation, Agriculture water management-non-irrigation based, Climate

mitigation, Climate adaptation/climate risk management, Marketing and distribution, Post-

harvest handling and storage, Value-added processing, Other

Commodity (See list in FTFMS):

Activities promoting sustainable intensification or those where multiple commodities are

involved (e.g. transportation), where counting participants by commodity is complicated

and/or not meaningful are not required to disaggregate participants by commodity, and

should use the "Not applicable" category under the Commodity disaggregate.

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level, activity participants

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Sample survey of activity participants, census of private sector/government participants, activity

records, farm records, reports from activity partners, association records, company/organization

records

 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

The baseline is the number of participant producers and other actors applying improved management

practices or technologies promoted by the activity at the start of the activity.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

Please note the commodity(ies) must be selected in FTFMS to open the cells for data entry. The specific commodity needs to be selected

for producers in FTFMS. Other value chain actor types need to select “Not Applicable” in the commodity selection box on the ‘Select

Indicators and Commodities’ screen in FTFMS.

If a participant sample survey is used to collect data for this indicator, the sample weighted estimate of the total number of activity

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participants for each Management Type and for the Sex, Age and Commodity disaggregates must be calculated using appropriate sample

weights before being entered into FTFMS.

For example, an activity is working with smallholder farmers to increase the application of drought-tolerant maize to increase productivity

as well as increase climate adaptation, and increase the use of certified seed in soy. The IP would enter the number of individuals under

each category as follows after selecting the maize and soy commodities:

Value chain actor type: Smallholder producer

Sex of participant

● total number of female smallholder farmer activity participants who are applying drought-tolerant maize, certified soy seed, or

both

● total number of male smallholder farmer activity participants who are applying drought-tolerant maize, certified soy seed, or both

Age of participant

● total number of 15-29 year old smallholder farmer activity participants who are applying drought-tolerant maize, certified soy

seed, or both

● total number of 30+ year old smallholder farmer activity participants who are applying drought-tolerant maize, certified soy seed,

or both

Management practice

● total number of smallholder farmer activity participants who applied Crop Genetics practices/technologies (i.e. drought-tolerant

maize, certified soy seed or both)

● total number of smallholder farmer activity participants who applied Climate Adaptation practices/technologies (i.e. drought-

tolerant maize)

Commodity

Maize

● total number of smallholder farmer activity participants who applied drought-tolerant maize

Soy

● total number of smallholder farmer activity participants who applied certified soy seed

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ FTFMS reporting requires specific commodity to be selected. For PPR reporting, specific commodities are not disaggregated;

commodities are clustered into commodity groups and reported under these groups.

▪ FTFMS will produce aggregated totals for the indicator and for each disaggregate and commodity group for entry in FACTSInfo.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.4: Increased sustainable productivity, particularly through climate-smart

approaches

INDICATOR TITLE: EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance

[IM-level]

DEFINITION:

This indicator measures the area in hectares where USG-promoted improved management practices or technologies were applied during

the reporting year to areas managed or cultivated by producers participating in a USG-funded activity. Management practices counted are

agriculture-related, land- or water-based management practices and technologies in sectors such as cultivation of food or fiber,

aquaculture, fisheries, and livestock management, including those that address climate change adaptation and mitigation. Improved

management practices or technologies are those promoted by the implementing partner as a way to increase producer’s productivity

and/or resilience.

The application of both intensive and extensive agriculture-related management practices and technologies in different landscapes are

captured under the Type of Hectare disaggregate. The Type of Hectare disaggregates are: crop land, cultivated pasture, rangeland,

conservation/protected area, freshwater or marine ecosystems, aquaculture, and other[1]. Intensive interventions are those where

higher levels of inputs, labor and capital are applied relative to the size of land. Extensive interventions are those where smaller amounts

of inputs, labor and capital are applied relative to the size of land. For example, an intervention working to increase the production of

fingerlings in aquaculture is considered intensive while using improved grazing practices for livestock in a rangeland landscape would be

considered extensive. Those interventions carried out on crop land, cultivated pasture and aquaculture are considered “intensive”. Those

carried on rangeland, conservation/protected area and freshwater or marine ecosystems are considered “extensive”. The same area

cannot be counted under more than one Type of Hectare disaggregate category.

This indicator captures results where they were achieved, regardless of whether interventions were carried out, and results achieved, in

the ZOI.

A management practice or technology can be applied under a number of different hectare types. For example, improved grazing practices

could take place in cultivated pasture, rangeland, or conservation and mixed-used landscapes, and climate adaptation/climate risk

management interventions can be applied in all hectare types.

Management practice and technology type categories, with some illustrative (not exhaustive) examples, include:

● Crop genetics: e.g. improved/certified seed that could be higher-yielding or higher in nutritional content (e.g. through bio-

fortification, such as vitamin A-rich sweet potatoes or rice, or high-protein maize), and/or more resilient to climate impacts (e.g.

drought tolerant maize or stress tolerant rice); improved germplasm.

● Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and

transplantation; cultivation practices such as planting density, crop rotation, and mounding.

● Livestock management: e.g. improved grazing practices, improved fodder crop, cultivation of dual-purpose crops.

● Wild-caught fisheries management: e.g. sustainable fishing practices.

● Aquaculture management: e.g. pond culture; pond preparation; management of carrying capacity.

● Natural resource or ecosystem management: e.g. biodiversity conservation; strengthening of ecosystem services, including

stream bank management or restoration or re/afforestation; woodlot management.

● Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of fungicides;

improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and pesticides; crop

rotation; aflatoxin prevention and control during production.

● Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase biotic

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activity and soil organic matter levels, such as soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter,

mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control.

● Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes.

● Agriculture water management - non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that

improve water quality.

● Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while

preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and degraded

lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of

perennials; practices that promote greater resource use efficiency (e.g. drip irrigation).

● Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing

the severity of climate change. Examples include drought and flood resistant varieties; short-duration varieties; adjustment of

sowing time; diversification, use of perennial varieties; agroforestry.

● Other: e.g. improved mechanical and physical land preparation.

Since it is very common for USG activities to promote more than one improved management practice or technology, this indicator allows

the tracking of the number of hectares under the different management practices and technology types and the total unique number of

hectares on which one or more practices or technologies has been applied at the activity level.

● If a participant applied more than one improved technology during the reporting year, count that area on which the participant

applied those technologies under each relevant Management Practice type applied under the relevant Hectare type. However,

count the area only once in the applicable Sex, Age and Commodity disaggregate categories under the relevant Hectare type.

This will not result in double-counting for the total in FTFMS.

● If an activity is promoting a single technology for multiple benefits, the area under the technology may be reported under each

relevant category under the Management Practice/Technology Type disaggregate. For example, drought tolerant seeds could be

reported under Crop genetics and Climate adaptation/climate risk management depending for what purpose(s) or benefit(s) the

activity was promoted.

● If a participant cultivates a plot of land more than once in the reporting year, the area should be counted each time one or more

improved management practice/technology is applied. For example, because of access to irrigation as a result of a USG activity,

a farmer can now cultivate two cycles of crops instead of one. If the farmer applies USG-promoted technologies on her/his plot

for the two cycles, the area of the plot would be counted twice under this indicator. Note that the farmer would only be counted

once under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management

practices or technologies with USG assistance [IM-level].

If a lead farmer cultivates a plot used for training, e.g. a demonstration plot used for Farmer Field Days or Farmer Field School, the area of

the demonstration plot should be counted under this indicator. In addition, the lead farmer should be counted as one individual under

indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies

with USG assistance [IM-level].

The indicator should count those specific practices promoted by the activities, not any improved practice. Even then, baseline values could

be quite high, especially if a wide range of practices is included in the list of promoted practices. If that happens, IPs should look at the

disaggregated prevalence of individual practices to identify ones that are already widely applied and remove those from the list (and from

plans to promote) and recalculate the indicator without the already common practices.

This is a snapshot indicator, which is designed to capture application on hectares only for the reporting year. Hectares where a USG

activity-promoted management practice was applied before the intervention constitute the baseline. Hectares where the USG activity-

promoted management practice is applied during the project period get counted and in any subsequent years where that technology is

applied. However, this also means that yearly totals can NOT be summed to count application on unique hectares over the life of the

project.

IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicator EG.3.2-24 Number

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of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level]

and indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level] if they

use clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to

strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number and volume of certified soy

seed sales by assisted firms during the reporting year to estimate the number of farmers applying certified soy seed (for example, by using

a conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically

validated planting density. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment.

However, if an agrodealer gives away seed packs with the purchase of other inputs as a promotion, more validation would be necessary

for the IP to assume farmers purchasing the other input would also apply that seed.

Demonstration plots cultivated by researchers (a demonstration plot in a research institute, for instance) should not be counted under this

indicator nor should the researcher be counted under this indicator or indicator EG.3.2-24. The area of a demonstration or common plot

cultivated under improved practices or technologies by participants who are part of a group or members of an organization should not be

counted under this indicator, the participants should not be counted under indicator EG.3.2-24 Number of individuals in the agriculture

system who have applied improved management practices or technologies with USG assistance [IM-level], and the yield should not be

counted under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among program participants with USG assistance [IM-

level].

For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25, and EG.3-10, -11, -12) only capture results for land that is

individually managed. If more than one participant is involved in cultivating the same plot of land, the area of the plot should be divided by

the number of participants cultivating it. The divided area where the individual applied improved management practices and technologies

should then be reported under the appropriate sex and age categories.

Additionally, rangelands, conservation/protected areas, and freshwater or marine ecosystems under the ”Type of Hectares” disaggregate

that are communally- or group-managed , can be reported under this indicator. These cases should be reported in the association-applied

category under the Sex and Age disaggregate. Association-applied would be applicable for landscapes where communities or

organizations develop and adhere to policies regarding management, harvest, protection, etc.. Only extensive agriculture-related

management practices and technologies should count as association-applied, and not association-applied management practices and

technologies on crop lands, cultivated pasture, or aquaculture.

[1] Type of hectare disaggregates defined as:

▪ Crop land: land used for the production of crops for harvest, regardless of whether the crop that was cultivated was harvested or

lost. Include home gardens in this category.

▪ Cultivated pasture: land where forage crops are primarily grown for grazing

▪ Rangelands: land on which the native vegetation (climax or natural potential plant community) is predominantly grasses, grass-

like plants, forbs, or shrubs suitable for grazing or browsing use.

▪ Conservation/protected areas: terrestrial areas that are protected because of their recognized, natural, ecological or cultural

values. The protected status may fall into different categories and include strictly protected to those that allow for some limited

human occupation and/or sustainable use of natural resources, such as agroforestry, collection of non-timber forest products,

etc.

▪ Fresh-water and marine ecosystems: aquatic areas that include freshwater, such as lakes, ponds, rivers, streams, springs, and

freshwater wetlands, and water with higher salt content, such as salt marshes, mangroves, estuaries and bays, oceans, and

marine wetlands.

▪ Aquaculture; areas dedicated to the breeding, rearing and harvesting of aquatic animals and plants for food.

▪ Other: Areas that don’t fit into these categories. Please describe the Hectare type in the indicator comment.

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RATIONALE:

Improved management practices on agriculture land, in aquaculture, and in freshwater and marine fisheries will be critical to increasing

agricultural productivity. This indicator tracks successful application of technologies and management practices in an effort to improve

agricultural productivity, agricultural water productivity, sustainability, and resilience to climate change. In the GFSS results framework,

this indicator reports contributions to IR.4: Increased sustainable productivity, particularly through climate-smart approaches.

UNIT:

Hectare

DISAGGREGATE BY:

FIRST LEVEL

Type of Hectare:

▪ Crop land,

▪ Cultivated pasture,

▪ Rangeland,

▪ Conservation/protected area,

▪ Freshwater or marine ecosystems;

▪ Aquaculture,

▪ Other

SECOND LEVEL:

Sex: Male, Female, Association-applied

Age: 15-29, 30+, Association-applied

Management practice or technology type (see description, above): Crop genetics, Cultural practices,

Livestock management, Wild-caught fisheries management, Aquaculture management, Natural

resource or ecosystem management, Pest and disease management, Soil-related fertility and

conservation, Irrigation, Agriculture water management-non-irrigation based, Climate mitigation,

Climate adaptation/climate risk management, Other

Commodity (see list in FTFMS): Activities promoting sustainable intensification or those where

multiple commodities are involved where counting hectares is complicated and not meaningful are not

required to disaggregate by commodity, and should use the "Disaggregates not available" category

under the Commodities disaggregate.

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level; only those hectares affected by U.S. Government assistance, and only those newly

brought or continuing under improved technologies/management during the current reporting year

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Sample survey of activity participants, activity or association records, reports from activity partners,

farm records

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 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

The baseline is the area under improved management practices and technologies promoted by the

activity at the start of the activity.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

Please note the commodity must be selected in FTFMS to open the cells for data entry.

If a participant sample survey is used to collect data for this indicator, the sample weighted estimate of the total number of hectares across

all participants for each Management Practice type and Sex, Age and Commodity disaggregate under each Type of Hectare must be

calculated using appropriate sample weights before being entered into FTFMS.

Missions and IPs need to select the Type of Hectare first before reporting the number of hectares under the Sex, Age, Commodity, and

Management Practice disaggregations. For those that select Other under Type of hectare, please include in the indicator comment a

description of the type of landscape and whether the intervention is intensive or extensive.

For example, an activity is working with smallholder farmers to increase the application of drought-tolerant maize with the intention of

promoting increased climate adaptation, and increase the use of certified seed in soy. The IP would enter the number of hectares under

each category as follows after selecting the maize and soy commodities and the crop land Type of Hectare:

Type of Hectare: Crop land

Sex of participant

● total area cultivated by female smallholder farmer activity participants under drought-tolerant maize, certified soy seed, or both

● total area cultivated by male smallholder farmer activity participants under drought-tolerant maize, certified soy seed, or both

Age of participant

● total area cultivated by 15-29 year old smallholder farmer activity participants under drought-tolerant maize, certified soy seed,

or both

● total area cultivated by 30+ year old smallholder farmer activity participants under applying drought-tolerant maize, certified soy

seed, or both

Management practice

● total area cultivated by activity participants under Crop Genetics practices/technologies (i.e. drought-tolerant maize, certified

soy seed or both)

● total area cultivated by activity participants under Climate Adaptation practices/technologies (i.e. drought-tolerant maize)

Commodity

Maize

● total area cultivated by activity participants under drought-tolerant maize

Soy

● total area cultivated by activity participants under certified soy-seed

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DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ FTFMS reporting requires specific commodity to be selected. For PPR reporting, commodities are clustered into commodity

groups and reported under these groups. FTFMS will produce aggregated totals for the indicator and for each disaggregate and

commodity group for entry in FACTSInfo.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy - IR.2: Strengthened and expanded access to markets and trade

INDICATOR TITLE: EG.3.2-26 Value of annual sales of producers and firms receiving USG assistance [IM-level]

DEFINITION:

This indicator measures the value in U.S. dollars of the total amount of sales of products and services by USG-assisted farms and firms

during the reporting year within USG-supported agricultural commodity value chains or markets. This indicator also collects additional

data points on the value of sales in local currency, the number of activity participants, including the number of producers and the number

of assisted private sector firms, and, if applicable, the volume of sales (preferably in metric tons) for agricultural commodities (i.e. seed;

food, non-food and feed crops; livestock and livestock products, fish).

Examples of USG assistance include facilitating access to improved seeds and other inputs, to extension, business development and

financial services, and to micro-enterprise loans; providing technical support in production techniques; strengthening linkages to markets;

and other activities that benefit producers or private sector firms in the agriculture and food system.

Annual sales include all sales by farms and firms participating in USG-funded activities. This includes producers, such as farmers, fishers

and ranchers; and private sector non-farm enterprises, such as aggregators, input suppliers and distributors, traders, or processors of

the targeted commodity(ies) throughout the value chain. In value-chain-facilitation and other market-strengthening activities, activity

participants include the private sector firms with direct contact with the USG-funded activity and the producers and other customers

buying from or selling to the USG-assisted firms. Feed the Future recognizes the difficulty and cost to collect sales data directly from

producers, especially when working with firms though a market-system approach intended to strengthen the links between producers

and firms that purchase from them for onward sales, processing, etc. In these cases, implementing partners may consider collecting data

from firms on producers who sold to the firms while collecting data on sales of the firms, rather than attempting to collect sales data from

the producers directly. Implementing partners can then report both producer and firm sales under the appropriate disaggregate.

“Private sector” includes any privately-led agricultural enterprise managed by a for-profit company. A community-based organization

(CBO) or nongovernmental organization (NGO) may be included if the CBO or NGO engages in for-profit agricultural activity. Activity

participants may be involved in agricultural production, agro-processing, wholesale or retail sales, fisheries, input supply, or other

business activities in USG-assisted value chains and/or markets.

Only count sales in the reporting year that are attributable to the USG, i.e. where the USG assisted the individual farmer or firm, or the

market actor with which they are engaged directly, and for those value chains/commodities/markets which the USG supports. Sales do

not have to take place within a specific geographic area, such as the ZOI.

For assisted farms, sales refer to the value and amount of production that is sold, regardless of where the sales take place.

For assisted firms, sales include the value of goods and services at the point of sale, not when the sale was contracted. Data should be

collected directly from all firms who are receiving USG assistance.

Under participants, count the number of assisted producers for whom sales data are available. Include producers reached directly with

outreach and those buying from or selling to USG-assisted firms in a systems strengthening approach. For firms, count the USG-

assisted firm as the participant.

It is essential that a Baseline Year Sales data point be entered. If data on the total value of sales by participant farms or firms prior to

USG-funded activity implementation is not available, do not leave the baseline blank or enter ‘0’. Use the earliest Reporting Year Sales

actual as the Baseline Year Sales.

The number of participants in USG-funded activities often increases over time as the activity rolls out. Unless an activity has identified all

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prospective participants at the time the baseline is established, the baseline sales value will only include sales made by participant farms

and firms identified when the baseline is established during the first year of implementation. The baseline sales value will not include the

baselines from farms and firms added in subsequent years. To address this issue, the USG requires reporting the number of participants,

both producers and private sector firms for each value chain product or service along with baseline and reporting year sales. These data

points can be used to calculate average sales per participant at baseline, disaggregated by farm and firm and assist with interpreting the

reasons for an observed growth in the value of sales. To generate meaningful out-year targets for annual sales, targets for number of

participants, disaggregated by farm and firm, are also required.

The type of Product or Service sold by the producer or firm is the first level disaggregate when reporting. These are broken down into the

following disaggregate categories to be selected in FTFMS, with illustrative examples:

Products:

▪ Agricultural commodities, which generally include those raw products sold by producers such as staples, legumes, horticulture,

livestock, and fish but does NOT include seeds. The specific commodity (maize, mung beans, tomatoes, etc.) needs to be

selected.

▪ Inputs: Seeds and planting material.

▪ Inputs: Other non-durable inputs, such as fertilizer and pesticides.

▪ Inputs: Durable equipment and machinery, including land preparation equipment, irrigation equipment, and other equipment or

machinery.

▪ Processed products/value added products (post-harvest). The specific commodity does not need to be selected.

▪ Post-harvest storage and processing equipment, including PICS bags and processing machinery.

Services:

▪ Business services, including financial, entrepreneurial, legal, and other enterprise/producer strengthening services

▪ Information services: SMS, Radio, TV, print, etc.

▪ Production support services: other services that are sold to farmers, fishers, ranchers and pastoralists, including extension

services, veterinary services, rental of equipment, land preparation, warehousing, post-harvest processing

RATIONALE:

Value (in US dollars) of sales from assisted producers and firms in targeted markets is a measure of the competitiveness of those actors.

This measurement also helps track strengthened and expanded access to markets and progress toward engagement by farmers and

firms throughout the value chain. Improving markets will contribute to Objective One of Inclusive and Sustainable Agriculture-led

Economic Growth, which in turn will reduce poverty and thus achieve the goal. This indicator relates to IR 2: Strengthened and Expanded

Access to Markets and Trade in the GFSS results framework.

UNIT:

US Dollar

DISAGGREGATE BY:

FIRST LEVEL

Type of product or service: choose from list

SECOND LEVEL

Type of producer/firm (firms are non-farm enterprises): Producer - smallholder, Producer

– non-smallholder, Firm – microenterprise, Firm - Small and medium enterprise, Firm-

Large enterprise or corporation.

Smallholder Definition: While country-specific definitions may vary, use the

Feed the Future definition of a smallholder producer, which is one who holds 5

hectares or less of arable land or equivalent units of livestock, i.e. cattle: 10

beef cows; dairy: two milking cows; sheep and goats: five adult ewes/does;

camel meat and milk: five camel cows; pigs: two adult sows; chickens: 20

layers and 50 broilers. The farmer does not have to own the land or livestock.

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Firm Size Definition. For firms, microenterprises employed <10 people in the

previous 12 months, small enterprises employed 10-49 people, medium

enterprises employed 50-249 individuals and large enterprises and

corporations employed >250 individuals.

THIRD LEVEL

Sex of producer or proprietor(s): Male, female, mixed

For firms, if the enterprise is a single proprietorship, the sex of the

proprietor should be used for classification. If the enterprise has

more than one proprietor, classify the firm as Male if all of the

proprietors are male, as Female if all of the proprietors are female,

and as Mixed if the proprietors are male and female.

Age: 15-29, 30+, mixed

For firms, if the enterprise is a single proprietorship, the age of the

proprietor should be used for classification. If the enterprise has

more than one proprietor, classify the firm as 15-29 if all of the

proprietors are aged 15-29, as 30+ if all of the proprietors are aged

30+, and as Mixed if the proprietors are from both age groups.

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity level, those producers and firms directly assisted by USG

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partner

 DATA SOURCE:

Data from assisted producers and firms may need to be collected separately. Ideally, this indicator

will be collected directly from a census of all participant farms and firms, from recorded sales data

and/or farm/firm records. A sample survey-based approach for participant producers within the

geographic area reached by the assisted market is also acceptable. Implementing partners or

missions should work with assisted firms to ensure that appropriate information is provided.

 FREQUENCY OF

COLLECTION:

Annually

 BASELINE INFO:

Baseline data reflects value of sales in the year prior to programming and should be collected

through records of assisted firms and/or a sample survey of producers via recall.

REPORTING NOTES

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FTFMS DATA ENTRY NOTES:

If a sample survey of participating producers is used to collect data for this indicator, the sample weighted estimate of total baseline or

reporting year sales value and volume for all producers under each commodity must be calculated using appropriate sample weights

before being entered into FTFMS.

Data should be entered in FTFMS disaggregated to the lowest level—i.e. by product/service then by type of producer/firm then by sex

and by age under each commodity and type of enterprise.

Partners should enter the total volume of sales (metric tons are preferred but partners can select their own units), the total number of

participants (assisted producers or assisted firms), and the total value of reporting year sales in USD.

For example, to report on the value of sales from assisted smallholder farmer in the rice value chain, partners should enter the following

information for the reporting year:

Product/Service: Agricultural Commodity: Rice

Type of Producer/firm: Producer – smallholder

Total value of sales (in US dollars)

● total value of rice sold from plots cultivated by female program participants in US dollars;

● total value of rice sold from plots cultivated by male program participants in US dollars;

● total value of rice sold from plots cultivated by 15-29 year old program participants in US dollars;

● total value of rice sold from plots cultivated by 30+ year old program participants in US dollars.

Total volume of sales

● total volume sold from plots cultivated by female, rice-producing program participants in [selected unit];

● total volume sold from plots cultivated by male, rice-producing program participants in [selected unit];

● total volume sold from plots cultivated by 15-29 year old rice-producing program participants in [selected unit];

● total volume sold from plots cultivated by 30+ year old rice-producing program participants in [selected unit].

Number of participants

● total number of female, rice-producing program participants;

● total number of male, rice-producing program participants;

● total number of 15-29 year old, rice-producing program participants;

● total number of 30+ year old, rice-producing program participants.

To report on value of sales of assisted small enterprises selling fertilizer spraying services to producers, enter the following data points.

Product/Service: Production Support Services

Type of Enterprise: Firm - Small enterprise

Total value of sales (in US dollars)

● total value of fertilizer spraying services sold by participant small enterprises in US dollars

● total value of fertilizer spraying services sold by participant small enterprises with all male proprietors in US dollars

● total value of fertilizer spraying services sold by participant small enterprises with all female proprietors in US dollars

● total value of fertilizer spraying services sold by participant small enterprises with male and female proprietors (i.e.

mixed) in US dollars

● total value of fertilizer spraying services sold by participant small enterprises with all proprietors aged 15-29 years in

US dollars

● total value of fertilizer spraying services sold by participant small enterprises with all proprietors aged 30+ years in

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US dollars

● total value of fertilizer spraying services sold by participant small enterprises with proprietors from both age groups

(i.e. mixed) in US dollars

Volume of sales

● n/a

Number of participant enterprises

● total number of participant small enterprises with all male proprietors

● total number of participant small enterprises with all female proprietors

● total number of participant small enterprises with male and female proprietors (i.e. mixed)

● total number of participant small enterprises with all proprietors aged 15-29 years

● total number of participant small enterprises with all proprietors aged 30+ years

● total number of participant small enterprises with proprietors from both age groups (i.e. mixed)

Note: Convert local currency to U.S. dollars at the average market foreign exchange rate for the reporting year or convert periodically

throughout the year if there is rapid devaluation or appreciation.

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ FTFMS reporting requires specific commodity to be selected. For PPR reporting, commodities are clustered into commodity

groups and reported under these groups.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Area EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.2: Strengthened and expanded access to markets and trade

INDICATOR TITLE: EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance [IM-level]

DEFINITION:

This indicator sums the total U.S. dollar value of debt (both cash and in-kind loans) and non-debt financing, such as equity financing,

disbursed during the reporting year as a result of USG-assistance to producers (individual farmers, fishers, cooperatives, etc.), input

suppliers, transporters, processors, other MSMEs, and larger enterprises that are in a targeted agricultural value chain and are

participating in a USG-funded activity. USG assistance may consist of technical assistance, insurance coverage, guarantee provision, or

other capacity-building and market-strengthening activities to producers, organizations and enterprises. The indicator counts the value of

non-debt financing and both cash and non-cash lending disbursed to the participant, not financing merely committed (e.g., loans in

process, but not yet available to the participant).

Debt: Count cash loans and the value of in-kind lending. For cash loans, count only loans made by financial institutions and not by informal

groups such as village savings and loan groups that are not formally registered as a financial institution

[1]

. However, the loans counted can

be made by any size financial institution from microfinance institutions through national commercial banks, as well as any non-deposit

taking financial institutions and other types of financial NGOs. In-kind lending in agriculture is the provision of services, inputs, or other

goods up front, with payment usually in the form of product (value of service, input, or other good provided plus interest) provided at the

end of the season. For in-kind lending, USAID may facilitate in-kind loans of inputs (e.g., fertilizer, seeds) or equipment usage (e.g. tractor,

plow) via implementing partners or partnerships. NOTE: formal leasing arrangements should be captured in non-debt financing section

below), or transport with repayment in kind.

Non-Debt: Count any financing received other than cash loans and in-kind lending. Examples include: equity, convertible debt, or other

equity-like investments, which can be made by local or international investors; and leasing, which may be extended by local banks or

specialized leasing companies.

This indicator also collects information on the number of participants accessing agriculture-related financing as a result of USG assistance

to assist with indicator interpretation. Count each participant only once within each financial product category (debt and non-debt),

regardless of the number of loans or non-debt financing received. However, a participant may be counted under each category (debt and

non-debt) if both types of financing were accessed during the reporting year.

Note: This indicator is related to indicator EG.3.1-14 Value of new USG commitments and private sector investment leveraged by the USG

to support food security and nutrition. Where there is a USG commitment such as a grant, guarantee provision, or insurance coverage, the

resulting value of debt or non-debt financing accessed by participants of USG-funded activities should be counted under this indicator. The

total value of the private sector investment leveraged should be counted under indicator EG.3.1-14. These two indicators will not be

aggregated, thus there is no “double counting.”

[1]

The value of loans accessed through informal groups is not included because this indicator is attempting to capture the systems-level

changes that occur through increased access to formal financial services.

RATIONALE:

Increased access to finance demonstrates improved inclusion in the financial sector and appropriate financial service offerings. This in turn

will help to strengthen and expand markets and trade, IR.2 of the Global Food Security results framework (and also contributes to

Intermediate Result [IR] 3 Increased employment, entrepreneurship and small business growth) and to achieve the key objective of

inclusive agriculture-led economic growth (with agriculture sector being defined broader than just crop production). In turn, this contributes

to the goals of reducing poverty and hunger.

111!

UNIT:

U.S. Dollars

Note: convert local currency to

U.S. Dollars at the average

market foreign exchange rate for

the reporting year or convert

periodically throughout the year

if there is rapid devaluation or

appreciation.

DISAGGREGATE BY:

FIRST LEVEL

Type of financing accessed: Debt

SECOND LEVEL

Type of debt: Cash, In-kind

THIRD LEVEL

Size of recipient: Individuals/microenterprises; Small and medium enterprises;

Large enterprises and corporations.

Microenterprises employed <10 people in the previous 12 months, small

enterprises employed 10-49 people, medium enterprises employed 50-

249 individuals and large enterprises and corporations employed >250

individuals.

Sex of producer or proprietor(s): Male, female, mixed

If the enterprise is a single proprietorship, the sex of the proprietor

should be used for classification. If the enterprise has more than one

proprietor, classify the firm as Male if all of the proprietors are male, as

Female if all of the proprietors are female, and as Mixed if the

proprietors are male and female.

Age: 15-29, 30+, mixed

If the enterprise is a single proprietorship, the age of the proprietor

should be used for classification. If the enterprise has more than one

proprietor, classify the firm as 15-29 if all of the proprietors are aged 15-

29, as 30+ if all of the proprietors are aged 30+, and as Mixed if the

proprietors are from both age groups.

FIRST LEVEL

Type of financing accessed: Non-debt

SECOND LEVEL

Size of recipient: Individuals/microenterprises; Small and medium enterprises; Large

enterprises and corporations.

Microenterprises employed <10 people in the previous 12 months, small

enterprises employed 10-49 people, medium enterprises employed 50-249

individuals and large enterprises and corporations employed >250 individuals.

Sex of producer or proprietor(s): Male, female, mixed

If the enterprise is a single proprietorship, the sex of the proprietor should be used

for classification. If the enterprise has more than one proprietor, classify the firm

as Male if all of the proprietors are male, as Female if all of the proprietors are

female, and as Mixed if the proprietors are male and female.

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Age: 15-29, 30+, mixed

If the enterprise is a single proprietorship, the age of the proprietor should be used

for classification. If the enterprise has more than one proprietor, classify the firm

as 15-29 if all of the proprietors are aged 15-29, as 30+ if all of the proprietors are

aged 30+, and as Mixed if the proprietors are from both age groups.

TYPE: Output

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level, activity participants

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Financial institution and investor records or survey of activity participants

 FREQUENCY OF

COLLECTION:

Annually reported

 BASELINE INFO:

Baseline is zero

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

Partners will need to enter the value of financing accessed in U.S. dollars, the value of financing accessed in local currency and the

number of recipient enterprises that accessed the finance for each of the disaggregates.

For example, an activity is working to increase cash loans available to small and medium agro-enterprises in the soy value chain. The IP

would enter the value of cash loans and the number of enterprises under each relevant disaggregate category as follows after selecting the

Debt disaggregate:

Type of financing accessed: Debt

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Type of debt

● Value in US$ of cash debt disbursed

Size of recipient

● Value in US$ of loans disbursed to the participant small and medium soy agro-enterprises

Sex of recipient

● Value in US$ of loans disbursed to participant soy agro-enterprises with all male proprietors

● Value in US$ of loans disbursed to participant soy agro-enterprises with all female proprietors

● Value in US$ of loans disbursed to participant soy agro-enterprises with proprietors of both sexes (i.e. mixed)

Age of recipient

● Value in US$ of loans disbursed to participant soy agro-enterprises with all proprietors aged 15-29 years

● Value in US$ of loans disbursed to participant soy agro-enterprises with all proprietors aged 30+ years

● Value in US$ of loans disbursed to participant soy agro-enterprises with proprietors in both age groups (i.e. mixed)

Number of recipients

● Number of participant soy agro-enterprises

● Number of participant soy agro-enterprises with only male proprietors

● Number of participant soy agro-enterprises with only female proprietors

● Number of participant soy agro-enterprises with proprietors of both sexes (i.e. mixed)

● Number of participant soy agro-enterprises with all proprietors aged 15-29 years

● Number of participant soy agro-enterprises with all proprietors aged 30+ years

● Number of participant soy agro-enterprises with proprietors of both age groups (i.e. mixed)

DIFFERENCES BETWEEN FTFMS AND PPR (USAID only):

▪ Only enter the Value of Financing Accessed in U.S. Dollars. The Local Currency and Number of Recipients data points are not

required in the PPR. FTFMS will produce aggregated totals of the Value of Financing Accessed in U.S. Dollars for the indicator

and for each disaggregate for entry in FACTSInfo.

114!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – CCIR 2: Improved climate risk, land, marine, and other natural resource

management (cross reference to CCIR5: More effective governance, policy and institutions)

INDICATOR TITLE: EG.3.2-28 Number of hectares under improved management practices or technologies that promote improved

climate risk reduction and/or natural resources management with USG assistance [IM-level]

DEFINITION:

This indicator measures the area in hectares where USG-promoted management practices or improved technologies that reduce climate risk

and improve land, marine, and other natural resources management were applied during the reporting year to areas managed or cultivated

by producers participating in a USG-funded activity.

Management practices counted are agriculture-related, land- or water-based management practices and technologies in sectors such as

cultivation of food or fiber, aquaculture, fisheries, and livestock management that address climate change adaptation and mitigation,

specifically including those that seek to bring about benefits relating to climate change adaptation/climate risk management, climate

mitigation and improved natural resource and ecosystem management. Improved management practices or technologies are those promoted

by the implementing partner as a way to increase producer’s productivity directly or to support stronger and better functioning systems.

This indicator captures results where they were achieved, regardless of whether interventions were carried out, and results achieved, in the

ZOI.

This indicator reports on the unique number of hectares from a subset of three of indicator EG.3.2-25 Number of hectares under improved

management practices or technologies with USG assistance [IM-level] management practice category disaggregates. The examples under

each category below are illustrative but not exhaustive.

▪ Natural resource or ecosystem management: e.g. biodiversity conservation; strengthening of ecosystem services, including

stream bank management or restoration or re/afforestation; woodlot management.

▪ Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while

preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and degraded

lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of perennials;

practices that promote greater resource use efficiency (e.g. drip irrigation).

▪ Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing

the severity of climate change. Examples include drought and flood resistant varieties; short-duration varieties; adjustment of

sowing time; diversification, use of perennial varieties; agroforestry.

Indicator EG.3.2-25 is first disaggregated by Type of Hectare, and under Type of Hectare, by Management Practice and Technology Type

disaggregate categories. The same area cannot be counted under more than one Type of Hectare disaggregate category. But a

management practice or technology can be applied under a number of different hectare types. For example, climate adaptation/climate risk

management interventions can be applied in all hectare types.

Because it is possible that the same area is reported under more than one of the three indicator EG.3.2-25 management practice or

technology type categories under a given Type of Hectare, IPs must ensure that they eliminate any double-counting of hectares across the

three categories before reporting a unique number of hectares under this indicator. For example, an IP is working on a livelihoods project

where the interventions are supporting diversification and use of agroforestry products and participatory management detailing sustainable

use practices for the adjacent mixed-use protected area. The area is reported under both the natural resource or ecosystem management

and climate adaptation/climate risk management categories under indicator EG.3.2-25. The IP should only count the hectares in the mixed-

use protected area once under this indicator.

115!

The area of a demonstration or common plot cultivated under improved practices or technologies by participants who are part of a group or

members of an organization should not be counted under this indicator, since for cultivated cropland, this indicator captures land that is

individually managed. However, communally- or group-managed areas under extensive Type of Hectares disaggregates, such as

conservation landscapes or rangeland, can be reported under this indicator under the association-applied category under the Sex and Age

disaggregate. Association-applied would be applicable for landscapes where communities or organizations develop and adhere to policies

regarding management, harvest, protection, etc.

RATIONALE:

Improved management practices on agriculture land, in aquaculture and in freshwater and marine fisheries relating to improved natural

resource or ecosystem management and those practices that bring benefits related to climate mitigation and climate adaptation are critical for

ensuring that smallholder producers and their communities are taking steps to safeguard themselves against climate and weather

disturbances. This indicator tracks application of practices that can support producers and the landscapes where they live to proactively

protect themselves against climate disturbances while promoting better management of the natural resources and healthy ecosystems. In the

GFSS results framework, this indicator reports contributions to CCIR 2: Improved climate risk, land, marine, and other natural resource

management and is cross-linked to CCIR 5: More effective governance, policy and institutions.

UNIT:

Number

DISAGGREGATE BY:

None

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Activity-level; only those hectares affected by U.S. Government assistance, and only those newly

brought or continuing under improved technologies/management during the current reporting year

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners

 DATA SOURCE:

Sample survey of activity participants, activity or association records, reports from activity partners, farm

records

 FREQUENCY OF

COLLECTION:

Annually

 BASELINE INFO:

The baseline is the area under improved management practices and technologies that support improved

climate risk reduction and/or natural resources management that are promoted by the activity at the start

of the activity.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

The data for this specific indicator is derived from three disaggregates from indicator EG.3.2-25. Implementing partners are expected to

report on the unique number of hectares within these three disaggregates. For example, if an IP is reporting on the improved management

practices and technologies for the same hectare under two or all of these three disaggregates, that hectare should be counted only once.

116!

Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element EG.3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – CCIR 6: Improved human, organizational, and system performance

INDICATOR TITLE: CBLD-9 Percent of USG-assisted organizations with improved performance [IM-level]

DEFINITION:

This indicator measures whether USG-funded capacity development efforts have led to improved organizational performance in

organizations receiving organizational capacity development support. Capacity is the ability of people, organizations and society as a

whole to manage their affairs successfully. Capacity development is the process of unleashing, strengthening and maintaining such

capacity. Capacity is a form of potential; it is not visible until it is used. Therefore, performance is the key consideration in determining

whether capacity has changed. Organizational performance improvement reflects a deliberate process undertaken to improve

execution of organizational mandates to deliver results for the stakeholders the organization seeks to serve.

This indicator should only be used when an activity intentionally allocates resources (human, financial, and/or other) toward strengthening

organizational capacity and undergoes a deliberate performance improvement process that is documented. The activity’s theory of change

should reflect how the process of performance improvement is predicted to improve the delivery of products or services that an

organization produces. With support from the implementing partner, each organization being supported should determine how it will define

and monitor performance improvement based on its organizational mandate, mission, and strategic priorities.

The implementing partner sets annual targets for this indicator based on how many organizations will achieve improved organizational

performance each year. An organization can be counted as having improved organizational performance if it meets the following

conditions:

(a) As reflected in the activity theory of change, resources (human, financial, and/or other) were allocated for organizational capacity

development.

(b) An organization demonstrates that it has undergone and documented a process of performance improvement, including the

following four steps:

(i) Obtaining organizational stakeholder input to define desired performance improvement priorities,

(ii) Analyzing and assessing performance gaps (the difference between desired performance and actual performance),

(iii) Selecting and implementing performance improvement solutions (or the development interventions), and

(iv) Monitoring and measuring changes in performance.

Organizations may choose their preferred approach and/or tools for documenting the process and achievement of performance

improvement. The approach and/or tool may be one that has been or is being used by the organization prior to the implementation of USG-

funded activities. One example of a broad performance improvement and measurement tool that USAID has endorsed is the

Organizational Performance Index (OPI), which can be used for assessing performance across multiple domains. Other examples include

university accreditation self-assessments, a balanced scorecard approach, Six Sigma, and many others. The data quality, including

reliability and validity of the approach and/or tool, should be documented to the extent possible in the monitoring and evaluation plan

(specifically the Activity MEL Plan for USAID).

Targets should be set and results should be reported using this formula for the overall indicator and each of the disaggregates:

● Numerator = number of organizations with improved performance

● Denominator = number of USG-assisted organizations receiving organizational capacity development support

Only one organization type should be selected for each organization receiving USG-funded capacity development assistance. Organization

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type should reflect the primary type of organization with which an organization identifies. Additional description of the mission and function

of each assisted organization (such as type of services provided, role of organization in a relevant sector, etc.) should be included in the IM

Performance Narrative.

RATIONALE:

Capacity development is essential to achieving and sustaining the U.S. Government’s Global Food Security Strategy (GFSS) objectives of

inclusive and sustainable agriculture-led economic growth, resilience among people and systems, and a well-nourished population. This

indicator data and supplementing documentation will provide the Feed the Future initiative with a better understanding about the scope and

scale of organizational capacity development efforts within the Feed the Future Zones of Influence, as well as outside the Feed the Future

ZOIs at organizations that play a significant role in contributing to agriculture-led economic growth (e.g., organizational capacity

strengthening of a ministry of agriculture or an agricultural university outside of the ZOI). This indicator data also provides information

about which types of organizational performance support its partners need. This indicator is linked to CCIR 6: Improved human,

organizational, and system performance of the Global Food Security results framework.

UNIT:

Number

DISAGGREGATE BY:

• Numerator = number of organizations with improved performance

• Denominator = number of USG-assisted organizations receiving organizational capacity

development support

Both the numerator and denominator should be disaggregated by type of organization.

Type of organization:

● Education (higher education, secondary, primary)

● Research institutions (non-degree granting)

● Cooperative (formal and registered private sector firm that serves members voluntarily

united to meet common needs and aspirations through joint ownership and democratically

controlled business)

● Producer group (informal, unregistered group of producers who aggregate product to

access markets)

● Faith based organizations

● Governmental agencies (at national or sub-national levels)

● Health service delivery sites (hospital, clinic, community, pharmacies)

● Private sector firms

● Non-governmental and not-for profit organizations

● Other

TYPE: Outcome

DIRECTION OF CHANGE: N/A

118!

MEASUREMENT NOTES

 LEVEL OF COLLECTION:

Organization. This includes organizations within the Feed the Future ZOIs, as well as organizations

outside the Feed the Future ZOIs that play a significant role in contributing to agriculture-led

economic growth, e.g., organizational capacity strengthening of a ministry of agriculture or an

agricultural university outside of the ZOI.

 WHO COLLECTS DATA

FOR THIS INDICATOR:

Implementing partners that implement activities under which resources have been allocated to work

with organizations to strengthen organizational capacity for improved performance.

 DATA SOURCE:

Data should be collected using appropriate methods (including relevant questionnaires or other data

documentation methods.) Tools and data collection methods should be documented in the Activity

Monitoring, Evaluation, and Learning (MEL) Plan.

 FREQUENCY OF

COLLECTION:

Annual

 BASELINE INFO:

Although this is an outcome indicator, the baseline value at the start of activity implementation should

be zero because the indicator measures the number of organizations that have improved

performance each year (as opposed to measuring a performance improvement score). Organizations

can be counted in subsequent years, as long as their performance improved relative to the previous

year.

REPORTING NOTES

FTFMS DATA ENTRY NOTES:

Contractors and recipients who implement activities fully or partially funded by Feed the Future should upload documentation

demonstrating that the conditions identified above (a through c) have been met for each organization being reported as having improved

performance. The CBLD-9 supplementary worksheet available at https://agrilinks.org/ftfms may be used as documentation, and users

should upload the completed worksheet on the “Other Reporting Docs” tab on the “Enter or View Narratives” screen in FTFMS

Targets should be set and results should be reported using this formula for the overall indicator and each of the disaggregates:

● Numerator = number of organizations with improved performance

● Denominator = number of USG-assisted organizations receiving organizational capacity development support

Both the numerator and denominator should be disaggregated by type of organization.

Only one organization type should be selected for each organization receiving USG-funded capacity development assistance. Organization

type should reflect the primary type of organization with which an organization identifies. Additional description of the mission and function

of each assisted organization (such as type of services provided, role of organization in a relevant sector, etc.) should be included in the IM

performance narrative.

PPR DATA ENTRY NOTES (USAID only):

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The CBLD-9 Indicator Narrative must include the mission and function of each assisted organization (such as type of services provided,

role of organization in a relevant sector, etc.), as well as the tools or other approach used to monitor and measure performance. Narratives

may also address the following:

• Describe which organizational stakeholder input was obtained to define desired performance improvement priorities and the

process for obtaining input.

• Describe how performance gaps (the difference between desired performance and actual performance) were assessed and

analyzed.

• What is the key performance indicator or area for performance improvement that was being addressed? Describe the

performance improvement solutions that were selected and how they were implemented.

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Performance Indicator Reference Sheet (PIRS)

SPS LOCATION: Program Element 3.2: Agricultural Sector Capacity

INITIATIVE AFFILIATION: Global Food Security Strategy – IR.1: Strengthened inclusive agriculture systems that are productive and

profitable

INDICATOR TITLE: EG.3.2-a Percent of producers who have applied targeted improved management practices or

technologies [ZOI-level]

DEFINITION:

This indicator measures the percent of producers (e.g. farmers, ranchers and other primary sector producers of food and nonfood crops,

livestock products, fish and other fisheries/aquaculture products, agro-forestry products, and natural resource-based products, etc.) who

have applied improved management practices and/or technologies anywhere within the food and fiber system in the Feed the Future ZOI

in the reporting year.

Improved management practices or technologies are those promoted by Feed the Future implementing partners as a way to increase

agriculture productivity or support stronger and better functioning systems. The improved management practices or technologies are

agriculture-related including those that address climate change adaptation or climate change mitigation. Specific management practices

and technologies are reported under category types of improved management practices or technologies.

The universe of management practices and technologies promoted by USG programming can be large and collecting information on each

one would make the data collection process unmanageable. Therefore, Feed the Future recommends that Post teams prioritize and

narrow the set of management practices and technologies for which they collect information at the ZOI level.

Post teams will need to work with Implementing Partners to determine the set of management practices/technologies that have been

promoted in the past, that are currently being promoted and that will be promoted to the best of their knowledge at baseline, and not

include just any improved practice. Even then, baseline values and application rates could be quite high, especially if a wide range of

practices is included in the list of promoted practices. If that happens, Post teams should look at the disaggregated prevalence of individual

practices to identify ones that are already widely applied and remove those from the list (and from plans to promote) and recalculate the

indicator without the already common practices.

Post teams should consider their theory of change and implementation approach to strengthening inclusive agriculture systems that are

productive and profitable (the GFSS IR-1 on which this indicator reports progress) to determine the prioritized set of practices and

technologies on which to collect data at the ZOI level; for which commodities, when relevant; and from which producers. The approach

might entail working to increase productivity of specific value chains through commodity-specific packages of promoted practices. The

programming could also aim at strengthening targeted input or output markets system-wide (e.g. a specific input supply chain), which

impact a number of commodities.

Depending on the Post team’s approach, the universe of management practices/technologies on which to collect data can be defined and

focused by a combination of information pertaining to the:

▪ Promoted package of management practices/technologies that are relevant to the three value chain commodities prioritized for

collection of yield data (see indicator EG.3-hYield of targeted agricultural commodities within target areas [ZOI-level]).

▪ Practices relevant to system-wide programming that may apply to producers of all commodities (e.g. purchasing fertilizer from

an agro-dealer, sustainable diversification).

▪ Management practices/technologies that the mission expects will have the greatest spillover or have the greatest ability to scale

at the ZOI-level (either specific commodity-focused or system-wide).

Management practice and technology type categories, with some illustrative (not exhaustive) examples, include:

● Crop genetics: e.g. improved/certified seed that could be higher-yielding, higher in nutritional content (e.g. through bio-

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fortification, such as vitamin A-rich sweet potatoes or rice, high-protein maize, drought tolerant maize, or stress tolerant rice)

and/or more resilient to climate impacts; improved germplasm.