EQUITABLE FINANCE ACTIVITY ACTIVITY MONITORING, EVALUATION, AND LEARNING PLAN (AMELP) Version 1 / Approved Date: March 24, 2023 Contract Number: 72051422D00003 Activity Start Date and End Date: October 17, 2022 to October 16, 2027 Implemented by: DAI Photo: USAID Colombia 2 EQUITABLE FINANCE ACTIVITY ACTIVITY MONITORING, EVALUATION, AND LEARNING PLAN (AMELP) Approved Version Presented: March 14, 2023 Approved: March 24, 2023 This report was produced for review by the United States Agency for International Development (USAID). It was prepared by DAI Global, LLC, under the contract 72051422D00003. The contents of this report are the sole responsibility of DAI and do not necessarily reflect the views of USAID or the United States Government. Prepared by: EF’s Monitoring, Evaluation & Learning (MEL) Team 3 ACRONYMS ADS Automated Directives System AMELP Activity Monitoring, Evaluation, and Learning Plan API Application Programming Interface CDCS Country Development Cooperating Strategy CLA Collaborating, Learning, and Adapting CMA Complementary Monitoring Approaches CSV Comma Separated Values COP Chief of Party COR Contract Officer Representative DANE Departamento Administrativo Nacional de Estadística DCOP Deputy Chief of Party DMP Data Management Plan DO Development Objective DQA Data Quality Assessment EF Equitable Finance Activity FAG Fondo Agropecuario de Garantías FNG Fondo Nacional de Garantías GDP Gross Domestic Product GOC Government of Colombia HO Home Office IR Intermediate Result KIIs Key Informant Interviews LOA Life of Activity MEL Monitoring, Evaluation and Learning MSMEs Micro, Small, and Medium Enterprises PDET Development Program with a Territorial Approach (Territorial-Focused Development Plans, in English) PIRS Performance Indicator Reference Sheet PITT Performance Indicator Tracking Table PMP Performance Management Plan PPR Performance Plan and Report P&R Pause and Reflect QPR Quarterly Performance Review RFI Rural Finance Initiative 4 TOC Theory of Change USAID United States Agency for International Development USG United States Government 5 TABLE OF CONTENTS 1. OVERVIEW ............................................................................................... 6 1.1. INTRODUCTION ...................................................... 6 1.2. ACTIVITY THEORY OF CHANGE AND RESULTS FRAMEWORK 7 1.3. RELATIONSHIP TO MISSION CDCS .......................... 8 2. MONITORING SECTION ............................................................................ 9 2.1. MONITORING APPROACH ...................................... 9 2.2. PERFORMANCE MONITORING ............................. 10 2.3. CONTEXT MONITORING ....................................... 20 2.4. COMPLEMENTARY MONITORING APPROACHES . 20 3. EVALUATION PLAN................................................................................. 21 3.1. INTERNAL EVALUATIONS ...................................... 21 3.2. EXTERNAL EVALUATIONS ..................................... 21 4. COLLABORATING, LEARNING, AND ADAPTING PLAN ............................... 21 4.1. COLLABORATING .................................................. 21 4.2. LEARNING ............................................................. 23 4.3. ADAPTING ............................................................. 25 5. MANAGING DATA SECTION .................................................................... 25 5.1. DATA COLLECTION ............................................... 25 5.2. DATA STORAGE AND DATA SECURITY .................. 26 5.3. DATA QUALITY ASSESSMENT (DQA) PROCEDURES 26 5.4. DATA ANALYSIS AND REPORTING ........................ 27 6. ROLES AND RESPONSIBILITIES SECTION .................................................. 34 7. ACTIVITY PIRS AND CIRS ......................................................................... 37 ANNEX A: BENEFICIARY FEEDBACK PLAN .......................................................... 109 6 1. OVERVIEW 1.1. Introduction Equitable Finance Activity (EF) is a five-year activity funded by USAID intended to contribute directly to USAID/Colombia’s 2020–2025 Country Development Cooperation Strategy (CDCS) Development Objective (DO)3: Promote Equitable and Environmentally Sustainable Economic Growth. The Activity will contribute to this objective by facilitating and enhancing financial services access, and by creating greater economic equality and a healthier financial environment. The Activity will also contribute towards IR 3.2 More Competitive Licit Economies and IR 3.2.2 Increased private sector investment and access to financial services. While EF builds upon the results of USAID’s Rural Finance Initiative, this new activity balances breadth and depth by not only setting ambitious targets but also emphasizing innovation, gender, social inclusion and learning. In parallel with deepened access to finance in the targeted corridors, EF will work on the demand and the enabling environment for the sustainable provision of formal financial services. The EF Activity Monitoring, Evaluation and Learning Plan (AMELP) provides the foundation for dynamic, impact-oriented, and evidence-based adaptive management and iterative programming in Colombia. The AMELP serves three primary purposes: ● First, it helps DAI and USAID monitor, measure, and report on progress of activities towards achieving the Activity’s objectives, CDCS IRs 3.2 and 3.2.2, and CDCS DO3. ● Second, it outlines activities to ensure regular and continuous learning that enables local stakeholders the ability to scale up successes through EF as well as other programs and partnerships; and ● Third, it supports evidence-based management decisions by USAID/Colombia and DAI to leverage opportunities, amplify impact and help tell the story of the achievements of the Activity’s interventions nationally and more specifically across the priority PDET municipalities. The AMELP describes the processes and approaches that will be used to perform MEL throughout the life of the Activity to track progress towards results, learn from implementation, and adapt implementation based on learning. The plan outlines specific MEL methods and processes for monitoring the activity. It describes the knowledge management and data analysis processes as well as plans for performance, context, and complementary monitoring that embrace regular and frequent assessment of interventions, challenges, opportunities that emerge, and broader market system impacts. Indicators and data collection methods are proposed, as are the analysis and reporting procedures needed to assess achievements of the objectives of the Activity, and internal roles and responsibilities for MEL. The AMELP covers the period from October 2022 to October 2027. It is a living document that will be reviewed annually and as needed to make necessary adjustments to the indicators and MEL approaches. 7 1.2. Activity Theory of Change and Results Framework IF financial capacity, access to financial services, and financial inclusion ecosystems are improved for target communities, AND more long-term private capital is mobilized towards USAID development objectives, THEN underserved populations and businesses will be able to make informed financial decisions THEREBY increasing investment and licit economic opportunities in conflict-affected regions. People and businesses need to have access to affordable financial products that meet their needs to expand and improve their livelihood and business opportunities. A balanced and well-developed financial sector strategy needs to have long-term financing to support its key sectors (micro, small, and medium enterprises (MSMEs), agriculture, housing, clean energy, infrastructure, etc.) for an inclusive economic growth strategy. Exhibit 1. EF Results Framework For EF to achieve the results mapped above, there are several assumptions that will need to hold true. These are outside of the control of the Activity but could risk achieving the results expected. The following are the landscape of key assumptions for EF: ● GOC’s support for the implementation of the Peace Agreement and the already defined PDET strategy is sustained. ● The macroeconomic environment, fiscal and monetary policy, remain stable. ● The mandates and policies of the GOC entities with which EF plans to engage (Finagro, Banco Agrario, Bancoldex, etc.) remain largely the same, i.e. the level of market distortions is not significantly increased ● The GOC does not embark on populist economic policies on a large scale. ● Shocks impacting borrowers remain within normal parameters, are specific to certain regions (e.g., mining strikes only in the Bajo Cauca region) and/or not of significant national scale. ● Internet connectivity in rural dispersed PDET municipalities is real 8 ● Increased incentive to focus on harder-to-reach, underserved populations align with financial institutions’ strategies and market system principles (and not on populist market distortions). ● Security remains at levels that EF and its partners are able to maintain staff, operate and travel in PDET regions. 1.3. Relationship to Mission CDCS The 2020-2025 CDCS goal supports implementation of the Peace Accord, which presents a tremendous opportunity for peace, stability, and prosperity in Colombia. The goal will be achieved through three Development Objectives (DOs). The CDCS’ first DO consolidates peace gains by creating a more cohesive and inclusive society, thereby mitigating the conditions that contribute to violence. The second DO does this by engaging citizens and making government systems more accessible and responsive to citizens’ needs. The third DO will expand licit economies and create new opportunities for Colombians to prosper by contributing to the national economy. The CDCS’s approach is to make governance more inclusive by strengthening transparency and responsiveness of state systems to citizen needs and increasing citizen and migrant participation in the state systems. The CDCS is aligned with the Government of Colombia’s (GOC) peace geography as laid out in the PDETs and the mission’s Regional Integration Strategy and emphasis on aligning interventions facilitate collaboration among USAID-funded activities to achieve greater impact The EF Activity will advance CDCS Development Objective (DO) 3: Promote Equitable and Environmentally Sustainable Economic Growth as demonstrated in the EF Causal Model in Exhibit 2. The Activity will contribute to this objective by facilitating and enhancing financial services access, and by creating greater economic equality and a healthier financial environment. The Activity will also contribute towards IR 3.2 More Competitive Licit Economies and IR 3.2.2 Increased private sector investment and access to financial services. It will do this by providing incentives for the private sector to invest in rural and conflict￾affected areas where the private sector has previously been reluctant to invest. In turn, enhanced private sector investment will increase underserved communities’ access to financial services, and will lead to licit opportunities and job creation. Finally, the Activity will create long-term, sustainable solutions for financing in Colombia, so that the country can achieve its own development goals. 9 Exhibit 2. EF Causal Model 2. MONITORING SECTION 2.1. Monitoring Approach EF’s monitoring approach combines traditional performance monitoring with context monitoring and complementary monitoring. EF will routinely monitor all interventions to assess progress toward expected results and outcomes. Context monitoring will enhance understanding of results and the many dynamic and inter-related external factors that influence EF’s operating environment and provide further evidence for adaptive decision￾making. Complementary monitoring will add another layer to better understand achievements that are harder to anticipate when working in the complex subregions of 10 Colombia in which the Activity operates. Quantitative data collected for performance and context indicators will be analyzed alongside the qualitative information from complementary monitoring to monitor the Activity and inform its adaptive management. Each component of the monitoring plan is described below, including the selected indicators. 2.2. Performance Monitoring EF will routinely monitor all interventions to assess the Activity’s progress toward expected objectives and intermediate results. The Activity will monitor its performance and report to USAID/Colombia on a set of performance indicators. This comprises 6 standard foreign assistance indicators, all of which are included in USAID/Colombia’s Performance Management Plan (PMP) for 2020-2025, 2 mission specific indicators, and 10 indicators customized by the Activity. Most of the data collected for performance monitoring will be done through EF partners. EF’s MEL team will provide templates and trainings to partners to report necessary data to EF. An emphasis will be on overseeing the quality of the data reported through EF partners. In Table 1, for each indicator, we provide a unique code, its class, type, unit of measure, disaggregation(s), and source of data. 11 Table 1. Summary Descriptive Table of Performance Indicators # Code Indicator name Class Type Units of Measurement Disaggregates Source of Data Reporting frequency Objective 1: Increased financial capacity in target communities. IR 1.1 Increased financial capacity among targeted individuals. 1 EF-O1-01 Number of people that have participated in financial education/literacy activities Output Custom People Sex; Age; Location Financial partners’ reports Quarterly IR 1.2 Increased financial capacity among MSMEs. 2 EF-O1-02 Sustainable and scalable business development service/model operationalized Outcome Custom Service/model None Activity monitoring reports Annually 3 EF-O1-03 (EG.5.2.1) Number of firms receiving USG-funded technical assistance for improving business performance [EG.5.2-1] Output Standard Firms Formal/informal; New/continuing; Firm size; Sex of entrepreneur; Age; Location Surveys to firms Quarterly 4 EF-O1-04 (EG.5-3) Number of microenterprises supported by USG assistance [EG.5-3] Output Standard Microenterprises Formal/informal; New/continuing; Sex of entrepreneur; Age; Location Activity monitoring reports Quarterly 12 5 EF-O1-05 (EG.5-16) Approximate number of very poor beneficiaries from USG assistance targeted to reach the very poor [EG.5- 16] Outcome Standard Beneficiaries Type of assistance; Sex; age; location Bank data Quarterly Objective 2: Increased provision of financial services in target communities. IR 2.1: Increased capacity to provide services among financial service providers. 6 EF-O2-01 Number of financial services providers with increased capacity to provide financial services in target geography Outcome Custom Financial service providers Type of financial service provider (bank, micro finance NGO, fintech, etc.); Location Activity monitoring reports Annually 7 EF-O2-02 (PMP 182) Total number of financial services provided through USG-assisted financial intermediaries, including non-financial actors or institutions [mission indicator – 182] (contract: number of financial products) Outcome Custom Financial services New/continuing; Type of financial service; Sector; Location; Activity monitoring reports Annually IR 2.2: Expanded presence of financial service providers in target communities. 8 EF-O2-03 (PMP – 119) Value of USG-supported financial services [mission indicator – 119] Output Custom US$ Million Type of financial service; Productive/ non￾productive; Location; Sector; Population Activity records and administrative data from financial organizations Quarterly 13 9 EF-O2-04 (EG.3.2-27) Value of agriculture-related financing accessed as a result of USG assistance [EG.3.2-27] Output Standard US$ Million Type of financing accessed; Type of financing recipient; Age; Sex; Firm size Activity records and administrative data from financial organizations Quarterly 10 EF-O2-05 (EG.3-2) Number of individuals participating in USG Food security programs [EG.3-2] Output Standard Individuals Sex; Age; Location; Size of MSME Firm records, activity records Quarterly 11 EF-O2-06 (EG.4.2-1) Total number of clients benefiting from financial services provided through USG￾assisted financial intermediaries, including non-financial institutions or actors [EG.4.2-1] Output Standard Clients Type of clients; Location; New/continuing; Type of financial service; Sex; Age; Underserved Activity monitoring reports Annually 12 EF-O2-07 (GNDR-2) Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources (assets, credit, income or employment) [GNDR-2] Output Standard Female participants Location; Numerator; Denominator Activity monitoring reports Annually 13 EF-O2-08 (YOUTH-3) Percentage of participants who are youth (15-29) in USG-assisted programs designed to increase access to productive economic resources [IM￾level] [YOUTH-3] Output Standard Participants Location; Numerator; Denominator Activity monitoring reports Annually IR 2.3: Increased provision of digital services by financial providers. 14 14 EF-O2-9 Number of digital finance products that have been developed, deployed and/or strengthened Output Custom Digital finance products New/Existing Activity monitoring reports Annually 15 EF-O2-10 Percent increase in utilization rate of digital financial products Outcome Custom Percent Financial product; Service provider Activity monitoring reports Annually 16 EF-O2-11 Number of clients using digital financial services Output Custom Clients Type of services; Age; Sex Activity monitoring reports Quarterly Objective 3: An improved ecosystem for the financial inclusion of underserved populations. IR 3.1: Improved collection and use of financial consumer data. 17 EF-O3-01 Framework/guideline in coordination with the GOC, Banca de las Oportunidades, and financial intermediaries covering the quantity, usage, and quality of data for measuring financial inclusion developed Outcome Custom Framework/ guideline None Activity monitoring reports Annually 18 EF-O3-02 Comprehensive and sustainable data management system that facilitates the analysis of information for financial and economic inclusion of at least two underserved population segments implemented Output Custom Data management system None Observatory reports Annually IR 3.2: Enhanced regulatory framework for financial inclusion. 19 EF-O3-03 Number of regulatory recommendations that promote underserved populations’ financial inclusion drafted and adopted by the GOC Outcome Custom Regulatory recommendations Drafted; Adopted Activity monitoring reports Annually 15 Special Objective: Increased mobilization of long-term financial capital for USAID’s priority sectors. 20 EF-SO-01 Value of funds mobilized in FINAGRO’s 2nd tier facility after agreement is reached with FINAGRO and GOC Outcome Custom US$ Million Sector; Location Activity monitoring reports Annually 21 EF-SO-02 Number of innovative/alternative finance instruments proposals that can be implemented to support the mobilization of long-term financial capital towards USAID’s priority sectors (CDCS) Output Custom Proposals Sector; Location Activity monitoring reports Annually Crosscutting 22 EF-CC-01 (PSE-1) Number of USG engagements jointly undertaken with private sector enterprises to support U.S. foreign assistance objectives [PSE-1] Output Standard Engagements Type of engagement; Purpose of engagement; US Foreign Assistance objectives addressed; PPP; Location Activity monitoring reports Annually 23 EF-CC-02 (PMP 40) Value of Mobilized Funds [mission indicator – 40] Outcome Custom US$ Million Resources Origin and type; Location Activity monitoring reports Quarterly 24 EF-CC-03 (PMP 156) Value of Leveraged Funds [mission indicator – 156] Outcome Custom US$ Million Resources Origin and type; Location Activity monitoring reports Quarterly 16 Table 2. Baseline and Targets Table of Performance Indicators # Code Indicator name Units Baseline date Baseline value FY 2023 FY 2024 FY 2025 FY 2026 FY 2027 LOA Objective 1: Increased financial capacity in target communities. IR 1.1 Increased financial capacity among targeted individuals. 1 EF-O1-01 Number of people that have participated in financial education/literacy activities People Dec-22 0 0 17,000 33,000 35,000 15,000 100,000 IR 1.2 Increased financial capacity among MSMEs. 2 EF-O1-02 Sustainable and scalable business development service/model operationalized Service/model Dec-22 No No No No No Yes Yes 3 EF-O1-03 Number of firms receiving USG-funded technical assistance for improving business performance Firms Dec-22 0 0 10 10 25 5 50 4 EF-O1-04 Number of microenterprises supported by USG assistance Microenterprises Dec-22 0 0 5 8 10 7 301 5 EF-O1-05 Approximate number of very poor beneficiaries from USG assistance targeted to reach the very poor [EG.5-16] Beneficiaries Dec-22 0 0 50 100 250 100 500 Objective 2: Increased provision of financial services in target communities. IR 2.1: Increased capacity to provide services among financial service providers. 6 EF-O2-01 Number of financial services providers with increased capacity to provide financial services in target geography Financial service providers Dec-22 0 0 2 2 3 3 10 7 EF-O2-02 Total number of financial services provided through USG-assisted financial intermediaries, including non-financial actors or institutions [mission indicator182] (contract: number of financial products) Financial services Dec-22 0 0 1 2 4 3 10 IR 2.2: Expanded presence of financial service providers in target communities. 1 This target may be updated after initial identification of MSMEs and capacity building activities. 17 # Code Indicator name Units Baseline date Baseline value FY 2023 FY 2024 FY 2025 FY 2026 FY 2027 LOA 8 EF-O2-03 Value of USG￾supported financial services (from list of mission indicators – 119) Total US$ Million Dec-22 0 0 50 150 200 150 550 Productive loans US$ Million Dec-22 0 0 40 120 160 120 440 9 EF-O2-04 Value of agriculture-related financing accessed as a result of USG assistance [EG.3.2-27] US$ Million Dec-22 0 0 0 50 80 20 150 10 EF-O2-05 Number of individuals participating in USG Food security programs [EG.3-2] Individuals Dec-22 0 0 50 100 250 100 500 11 EF-O2-06 Total number of clients benefiting from financial services provided through USG￾assisted financial intermediaries, including non￾financial institutions or actors Total Clients Dec-22 0 0 20,000 30,000 80,000 70,000 200,000 New underserved Clients Dec-22 0 0 20,000 30,000 80,000 70,000 200,000 Women Clients Dec-22 0 0 10,000 15,000 40,000 35,000 100,000 12 EF-O2-07 Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources (assets, credit, income or employment) Female participants Dec-22 0 0 50% 50% 50% 50% 50% 13 EF-O2-08 Percentage of participants who are youth (15-29) in USG-assisted programs designed to increase access to productive economic resources [IM-level] Participants Dec-22 0 0 20% 20% 20% 20% 20% IR 2.3: Increased provision of digital services by financial providers. 18 # Code Indicator name Units Baseline date Baseline value FY 2023 FY 2024 FY 2025 FY 2026 FY 2027 LOA 14 EF-O2-9 Number of digital finance products that have been developed, deployed and/or strengthened. Digital finance products Dec-22 0 0 1 3 4 2 10 15 EF-O2-10 Percent increase in utilization rate of digital financial products Percent Dec-22 0 0 2% 10% 20% 30% 30% 16 EF-O2-11 Number of clients using digital financial services Clients Dec-22 0 0 2,000 3,000 8,000 7,000 20,000 Objective 3: An improved ecosystem for the financial inclusion of underserved populations. IR 3.1: Improved collection and use of financial consumer data. 17 EF-O3-01 Framework/guideline in coordination with the GOC, Banca de las Oportunidades and financial intermediaries covering the quantity, usage, and quality of data for measuring financial inclusion developed Framework/ guideline Dec-22 No No No Yes No No Yes 18 EF-O3-02 Comprehensive and sustainable data management system that facilitates the analysis of information for financial and economic inclusion of at least two underserved population segments implemented. Data management system Dec-22 No No No Yes No No Yes IR 3.2: Enhanced regulatory framework for financial inclusion. 19 EF-O3-03 Number of regulatory recommendations that promote underserved populations’ financial inclusion drafted and adopted by the GOC. Regulatory recommendation s Dec-22 0 0 0 0 1 1 2 Special Objective: Increased mobilization of long-term financial capital for USAID’s priority sectors. 20 EF-SO-01 Value of funds mobilized in FINAGRO’s 2nd tier facility after agreement is reached with FINAGRO and GOC. US$ Million Dec-22 0 0 0 50 80 20 150 21 EF-SO-02 Number of innovative/alternative finance instruments proposals that can be implemented to support the mobilization of long-term financial capital towards USAID’s priority sectors (CDCS). Proposals Dec-22 0 0 1 1 1 0 3 Crosscutting 19 # Code Indicator name Units Baseline date Baseline value FY 2023 FY 2024 FY 2025 FY 2026 FY 2027 LOA 22 EF-CC-01 Number of USG engagements jointly undertaken with private sector enterprises to support U.S. foreign assistance objectives Engagements Dec-22 0 2 6 8 11 12 12 23 EF-CC-02 Value of Mobilized Funds [mission indicator – 40] US$ Million Dec-22 0 0 50 150 200 150 550 24 EF-CC-03 Value of Leveraged Funds [mission indicator – 156] US$ Million Dec-22 0 0 0.5 1 2.5 1 5 20 2.3. Context Monitoring Adaptive management will require EF to constantly adapt depending on the market conditions and other situations that could limit achievements outlined in the results framework. EF will need to understand the context nationally, and in certain cases regionally, to determine problems to address, intervention design, and the need to tailor approaches. Specific context indicators are listed in Table 3. These indicators are directly linked to the landscape assumptions/risks outlined in the introduction section. Although these are risks that are outside the control of the activity, they could impact EF results. Mechanisms will be in place to track the context to help understand EF achievements/shortfalls and adjust if necessary/possible and to try stay on track towards hitting targets. Table 3. Summary of Context Indicators Code Indicator name Units of Measurement Source of Data Reporting Frequency Reference Value Reference Timeframe EF-CX-01 Interest rate (including real interest rate, and inflation rate) Percentage Central Bank Quarterly 11% Q4 CY2022 EF-CX-02 Change in Gross Domestic Product (GDP) Percentage DANE Annually 9.4% November 2022 EF-CX-03 Number of hectares of coca cultivation Hectares UNODC Annually 204,000 2021 EF-CX-04 Average precipitation in depth (mm per year) Mm per year World Bank Annually 2,679 2021 EF-CX-05 Microcredit Portfolio Quality (Arrears) Percentage Superintendencia Financiera de Colombia, Quarterly 9.5% September 2022 2.4. Complementary Monitoring Approaches In addition to performance monitoring and context monitoring, EF will conduct several assessments to inform and steer interventions. Examples of the assessments that are planned to start during year 1 include: an evaluation of financial education programs to evaluate effectiveness and recommend adjustments to curriculum and delivery channels; joint analysis exercise to understand constraints limiting access to BDS for underserved population-owned businesses; rapid assessment of each of the five PDET economic corridors to explore main sectors of economic activity and firms operating in these sectors; mapping of DFS providers, support services, connectivity in target geographies, and enabling environment constraints and enablers; landscape analysis of data assets available on underserved populations in the priority geographies; and market assessment of alternative finance instruments. At the client level, there will be financial diaries, implemented by Javeriana. Financial Diaries will provide a rich and detailed understanding of the financial behavior and needs of low￾income households. EF will also undertake additional monitoring to measure broader market systems change. EF will monitor if similar practices that have been introduced to partner institutions are 21 adopted by other institutions, for example, new products and new points of service. EF will also track if an institution with which we work expands pilots to other regions. As part of this, EF will follow what public policy the government issues that affect finance in PDETs and more broadly. This will be done by monitoring what is going on in the market and policy space, and through data collected as part of the financial observatories and financial inclusion indicators. 3. EVALUATION PLAN 3.1. Internal Evaluations No internal evaluations are planned at this time. 3.2. External Evaluations EFA will provide support to USAID MEL Activity’s prime contractor for any evaluations or studies they conduct, including the Sustainable Ecosystems and Economic Development (SEED) cross projects baseline evaluation that is planned. The type of support includes, but is not limited to the following: ● Reviewing and providing feedback on the draft evaluation Statement of Work (SOW), draft evaluation design, draft data collection instruments, and the draft evaluation report. ● Sharing all project documentation, including the AMELP, work plans, quarterly and annual reports, and others, as requested by the evaluators. ● Sharing data used for performance monitoring. If this includes person-level data, EFA will anonymize the data prior to providing it to the evaluation team. ● Providing written responses to an evaluation self-assessment questionnaire. ● Making staff available to answer questions related to the Activity. ● Supporting the evaluation team in identifying and obtaining access to activity stakeholders, beneficiaries, and sites of operation. ● Supporting the evaluation team in holding stakeholder meetings to discuss and develop recommendations based on evaluation findings. 4. COLLABORATING, LEARNING, AND ADAPTING PLAN 4.1. Collaborating To achieve the activity objectives, DAI’s approach emphasizes engagement with and ownership by a diverse set of stakeholders, including practitioners, donor organizations, the financial sector, the development community, and the GOC. In particular, the activity will emphasize and foster linkages and strengthen connections between and among Financial Intermediaries to support and build capacity for EF and build local ownership and sustainability. To avoid duplication, ensure quality, complement, and integrate into existing projects, and maximize effectiveness, EF will coordinate with other implementers, including other Mission activities in prioritized geographic areas to deepen regional impacts and 22 contribute to USAID/Colombia’s Regional Integration Strategy. Understanding the importance of financial services to spur rural and agriculture development, EF will attempt to target beneficiaries participating in other Mission activities, particularly the Sustainable Agriculture Activity and will be open to collaborate with other activities in close coordination with USAID. We will also coordinate with the Mission’s MEL Activity to share learning and coordinate learning, monitoring, and evaluation processes. See Exhibit 3 for detailed collaboration mechanisms with major EF stakeholders. Exhibit 3. Collaboration Mechanisms Key Collaboration Mechanisms with Stakeholders USAID. We will work in close consultation with the USAID COR and USAID’s MEL advisors throughout the work planning and implementation process, which will include built-in reviews for any necessary course corrections every quarter and as requested. USAID will be invited to routine pause and reflect (P&R) sessions to reflect on learnings and hold joint work planning sessions. EF will also work with USAID’s MEL Activity to incorporate adaptation components to respond to DO3 and to connect with the monitoring, evaluation, and learning efforts of the other activities in the USAID portfolio. Other USAID funded Activities. As articulated in our technical approach, we will collaborate with activities to further support access to financial services and mobilization of capital through routine meetings, information sharing, site visits to learn from other projects, and linking projects to FIs or financial education and BDS providers that EF works with. EF will collaborate with the Community Development and Licit Opportunities, the Land for Prosperity Activity, Colombia Transforma, the Sustainable Agriculture Activity, the Destination Nature Activity, and the Sustainable Economic and Territorial Transformation through participation in USAID’s regional integration strategy working groups to study the barriers that USAID-supported individuals and MSMEs face in accessing fit-for￾purpose formal financial services. EF will also collaborate with the Colombia Climate Finance Activity to explore how its partner FIs and alternative finance instruments can accelerate the deployment of financial products for climate smart projects and businesses. EF will identify areas of collaboration with other activities of the Sustainable Ecosystems and Economic Development (SEED) Office as implementation advances. EF is aware of USAID’s high intensity areas (as reflected in the priority geography included in the AWP) and will work towards closer collaboration with other economic growth and land titling activities to achieve greater impact. Other donor agencies and projects. EF will utilize routine meetings to explore possible synergies and synchronization of effort with the World Bank, the International Finance Corporation (IFC), the Inter￾American Development Bank (IADB), the Canadian International Development Agency, and the Corporación Andina de Fomento (CAF), and other donor projects, including current DAI activities in Colombia such as the UK-funded Strategic Institutional Support to Tackle Illicit Financial Flows in Latin America – (Colombia, Ecuador, and Peru), share assessments/strategic reviews for comment, organized and facilitated by COP Young. EF will join strategic planning coordination through multi￾stakeholder discussion to learn from and to tackle constraints. GOC. EF will coordinate with FINAGRO, BANCOLDEX, Banca de las Oportunidades, FINDETER, the National Agriculture Credit System (Sistema Nacional de Crédito Agropecuario), Superintendence of the Financial System, Central Bank and Fondo Mujer Emprende. EF will sign a Letter of Intent with Banca de las Oportunidades for a comprehensive collaboration across components, will develop Letters of Intent with other GOC entities after the identification of areas of synergy and will mobilize resources from FINAGRO as part of the Special Objective. 23 Mission’s CLA Platform. EF will share results with USAID’s MEL Activity on activities and initiatives to feed into USAID/Colombia’s PMP and planned evaluations and learning activities. Local government. EF will collaborate with municipal and department administrations on financial literacy efforts. 4.2. Learning Under the direction of COP Young, the MEL Manager will oversee the collaborative design and reinforcement of a Learning Agenda integrated into the core of the technical approach and MEL structure, beginning with several baseline assessments and evaluations to inform early-stage programming and building upon the lessons learned from previous activities, including the Rural Financial Initiative (RFI). The Learning Agenda will be the basis for the adaptive management methodology, pulling together all the information needed to inform, adjust, and focus implementation with support from the Activity team and partners. Examples of information sources include assessments, performance monitoring, context monitoring, complexity-aware monitoring, and additional research focused on answering the set of learning questions (See Exhibit 4). A large component of the learning will focus on answering the below learning questions. EF will review the Learning Agenda annually to update the questions as needed and plan activities to carry out the following year. Internal and external learning activities (outlined in Exhibit 5) will be integrated into the work plan to provide an opportunity to reflect on information, lessons learned, and best practices and adapt if necessary. Documentation of lessons and continuous learning will be integrated throughout the program cycle in order to maximize the impact of the project and ensure quality implementation. Learning will include yearly analysis to compare the information of context indicators versus the results of EF’s interventions to determine external factors that may limit EF’s performance. For instance, EF will compare the information produced by Superintendencia Financiera de Colombia on Microcredit Portfolio Quality (Arrears) with EF’s portfolio arrears based on information reported by partner FIs. Learning data will be housed in EF’s database using the Airtable platform, that will allow the team to easily access, review, and share achievements and shortcomings so that USAID’s multiple stakeholders gain an understanding of the returns from the investment in this Activity. A full Learning Agenda will be developed in Y1 and reviewed annually; the formulation process will be iterative and involve collaboration with stakeholders to improve relevance and help ensure buy-in to the learning activities. Exhibit 4. EF Learning Questions # LEARNING QUESTIONS 1 What are the elements of an effective financial education model that result in improved financial capacity? Have people that are part of financial education improved capacity or have a perception of improved capacity? E.g. they feel more comfortable applying for or using a loan, use finance to grow their business. Are there personal features/ characteristics that make a client more successful as recipient of financial services? 24 2 How do financial services (including digital services) and financial education providers leverage the economic corridors to extend services? 3 How are data, market research and product development useful for developing effective strategies to serve women, youth and Indigenous and Afro Colombian populations with financial services in rural areas? 4 What are innovations and best practices that increase, improve, and enhance the rural and agricultural client experience in accessing and utilizing financial services? 5 What incentives are most effective at expanding channels that attract and service more rural/agricultural clients? (this includes agriculture-lending clients under USAID’s food security principles) 6 What policy instruments, operational changes and capacity building efforts are effective at increasing the number and type of financial intermediaries that access and deploy funds from public financial institutions (e.g. FINAGRO, Bancoldex) and risk mitigation instruments (e.g. FAG and FNG)? Exhibit 5. Summary of EF Learning Activities Learning Activities Routine staff meetings. Incorporate reflection into team meetings by asking team members what they have learned and how we can use that information. Quarterly Performance Review Sessions (QPRs). Quarterly internal review meetings with USAID’s participation will cover progress against targets, the learning agenda, and inform planning. These sessions will feed into the quarterly reports. Pause-and-reflect (P&R) sessions on key topics for adaptive management. The MEL team will organize structured P&R sessions on a monthly and ad-hoc basis that follow a common, though flexible, template, and will provide a forum for the core team to: review performance and monitoring data, other learning findings, including from the Learning Agenda; identify and document lessons, successes, and challenges; and make informed decisions about adapting plans and programming when needed. Milestone reviews. EF will establish milestones under the annual work plans to review each intervention with individual partners. At milestone reviews, evidence gathered during performance will be analyzed and, as a result, the intervention may be modified, abandoned, or redefined. Milestone reviews will be conducted collaboratively with selected partners and the COR. Annual P&R/work plan session. EF will conduct joint annual work-planning sessions across the team and with USAID, EF partners, and other external stakeholders to discuss adjustments, share lessons, analyze the political climate, discuss potential project risks and mitigation measures, and identify ways to collaborate more effectively. These sessions will inform the development of the annual work plan. Research and assessments. EF will utilize rapid assessment, landscape analysis, and baseline assessment findings to plan and adapt programming and will continue research and assessments throughout the project to answer the learning questions. 25 Workshops. Both virtual and in-person workshops will be convened around different topics and learnings from interventions will be shared externally with stakeholders. 4.3. Adapting An adaptive management methodology is essential to EF, developing a deliberate, systematic process to review data for reflection and decision-making to address a myriad of predictable and unpredictable challenges, respond to the situation, ramp up and scale down based on information obtained, and quickly respond to USAID requests. The EF team will use all information collected, review the information during the learning activities, analyze progress made toward results, revisit the results framework and assumptions, and make iterative course corrections. We will host work planning and co-creation events with partners and stakeholders. Context and complexity-aware monitoring will provide information on the entire ecosystem of actors and stakeholders. Contextual analysis will help us identify stumbling blocks, or emerging opportunities, that will help EF pivot if the context changes. The MEL Manager will track action plans and their status using USAID’s Pivot Log template. By imbuing an adaptive management methodology and iterative activity cycle with CLA principles, DAI will be able to adapt and/or mitigate potential risks and roadblocks during implementation. 5. MANAGING DATA SECTION 5.1. Data collection The MEL Manager will lead the implementation of the AMELP. This includes developing MEL data collection tools, creating a MEL guide, conducting training to staff and partners on data collection tools and processes, creating and maintaining the MEL data management system, supervising data collection, aggregating and reporting data, as well as ensuring data quality throughout the life of the activity. Data collection methods vary depending on each specific indicator; detailed data collection methods are outlined in the PIRS (Section 7). For output indicators such as training, beneficiary participation in activities, financial products dispersed, etc. the MEL team will ensure that partners have systems to collect data during or immediately following the relevant activity and periodically report aggregate information to DAI. The MEL Team will provide reporting templates and conduct trainings with all partner staff for consistent understanding of the data collection methods and reporting mechanism. This will help increase the quality of data and ensure timely data submission. The MEL Manager will conduct monthly data quality checks to verify quality of data collected and reported and provide guidance when weaknesses are identified. For performance and context indicators, the MEL Team will work to gather data from secondary sources and will develop appropriate methodologies and tools for primary data collection to capture the necessary data from partners to calculate indicators and their respective disaggregation. Additional data collection efforts to support the learning agenda and beneficiary feedback will be conducted. More details will be included in the Learning Agenda and the Beneficiary Feedback annex. Whenever appropriate and feasible, data collected by DAI will be done through DAI Collect, DAI’s internal mobile data collection application. DAI Collect utilizes the 26 open-source data collection software KoboToolbox. Kobo’s open-source code is deployed on DAI servers, allowing safe project data storage within a company managed cloud environment. The ability to build logic into the forms using DAI Collect, adds a layer of data quality. DAI Collect will be used, for example, for quantitative survey data collection and to track beneficiary attendance. To aid analysis, quantitative data will be disaggregated for analysis by sub-categories, such as by age, sex, disability and location, and any other required, whenever applicable and whenever that data is available through partners. 5.2. Data storage and data security EF data management will strictly follow guidance in the USAID Development Data, ADS Chapter 579. Documentation will be stored on the Activity server in a cloud-based system and on DAI’s internal management information systems, TAMIS. Access is password protected and limited to the Activity MEL Team and Management Team. Raw and processed data will be stored, managed, and analyzed in Airtable, which will be the central repository for all of EF’s data. Airtable allows different viewing rights for each user so relevant information can be shared with partners and stakeholders. Dashboards can also be created in Airtable or linked to PowerBI through an Application Programming Interface (API) to easily track progress towards targets and facilitate P&R and Milestone Reviews. Additional data, including context data and data to support tracking of partner level activity will be added as appropriate. Personal identifying information (PII) such as names, sex, phone number, disability status, and address may be collected during activities. In this situation, the activity will not share any PII and will store information separately to add a layer of protection. 5.3. Data quality assessment (DQA) procedures EF will follow DAI’s procedures for conducting a rapid DQA from the DAI Field Operations Manual to support MEL data quality assurance (DQA). The internal DQA procedure includes a rapid and adaptable process that can be utilized by DAI project teams as a quick check on MEL data and validity. The process involves answering a series of brief yes or no questions that can detect weaknesses in data quality and lead to corrective action in MEL processes. DAI will conduct an internal data quality assessment (DQA) annually on all reported data to determine the strengths and weaknesses of the data collected. Findings from the internal DQAs will be used to strengthen the EF MEL system and will be shared with USAID/Colombia. EF staff will also participate in any future USAID-implemented DQAs for the project. In addition to the annual DQA, the MEL Team will use the following tools/processes to control the quality of data and monitoring by field staff and partners: ● Appropriate Data Collection Methods. The EF MEL Team will support partners to collect input, output, and outcome data by activity, disaggregated as appropriate and feasible. The type of activity and indicator will determine appropriate data collection methods and tools, such as anonymized portfolio reports from financial service providers, or direct observation and documentation for training or workshop attendance. Partners will be trained on data collection and reporting methods. 27 ● Enforced Data Quality Standards. PIRS (see Section 7) include exact definitions, a detailed plan for data collection, potential data quality issues and ways to address them, and plans for data analysis and reporting to enforce rigor in data collection. When possible, data will be collected using Airtable forms or DAI Collect, with built in logic and validations to add another layer of data quality. Data will also be reviewed and checked in near real time as data is uploaded. ● Internal quality checks. The EF MEL Manager will conduct monthly data checks to ensure that all data collected and recorded is complete prior to reporting quarterly and annually. ● Quarterly Data Quality Assessments. COP Young will develop a confidential schedule for ‘light’ data quality assessments of project data to be conducted on a quarterly basis to confirm quality of data submitted by partners. EF may also conduct interviews or site visits to gather and verify MEL data or documentation or increase the rigor of MEL data collection and analysis. Externally, EF will support any USAID/third-party DQAs commissioned by the mission. ADS 201 requires a DQA to be conducted at least every three years on the indicators reported in its PPR or other indicators as determined by the mission. In the event the USAID/Colombia conducts a DQA on any of the EF reported indicators, the Activity will provide all cooperation and evidence needed. 5.4. Data analysis and reporting DAI will consolidate and analyze data to inform quarterly and annual reporting and draw conclusions on interventions and results based on actuals versus targets. The exhibit below describes our proposed data collection, analysis, and reporting process for EF. In addition to analysis by project staff, performance data will also be analyzed and assessed in a participatory fashion with USAID and, when deemed appropriate, EF stakeholders i.e., partner financial institutions and associations, government agencies (e.g. Banca de las Oportunidades) and Ministries (e.g. Finance, Agriculture, Commerce). By including these stakeholders in the analysis, we will build local ownership of activities and impact, and build the capacity of these organizations to collect and analyze data. The MEL team will produce data and analysis along with technical reports such as assessments, curricula, tools, and studies. The team will aggregate the deliverables, including lessons learned, and disseminate this information to relevant projects, including those of other donors and sector development projects, to ensure that investments are working synergistically and building a body of evidence that advances service delivery improvements in Colombia. COP Young will keep USAID abreast of problems/issues requiring attention. Real-time information regarding project process, feedback from USAID, innovations, and best practices will be integrated into the data management system. Written performance reports will include data presented in the Performance Indicator Tracking Table (see Table 4 for template). Reports will further ensure that DAI and USAID have a common understanding of how EF is on track to meet project goals and deliverables. We will adjust programming and indicators in response to performance, and in agreement with USAID. All data, including datasets and GIS files, will be submitted to USAID through the DDL function of the DIS (according to ADS 579) and approved reports will be uploaded to the DEC (according to ADS 540). EF will provide, report, and update performance information into MONITOR and training-related information into USAID’s training database. 28 Table 4. Tracking Table for Reporting Performance Indicators Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % Objective 1: Increased financial capacity in target communities. IR 1.1 Increased financial capacity among targeted individuals. EF-O1-01: Number of people that have participated in financial education/literacy activities IR 1.2 Increased financial capacity among MSMEs. EF-O1-02: Sustainable and scalable business development service/model operationalized EF-O1-03: Number of firms receiving USG-funded technical assistance for improving business performance EF-O1-04: Number of microenterprises supported by USG assistance EF-O1-05: Approximate number of very poor beneficiaries from USG assistance targeted to reach the very poor Objective 2: Increased provision of financial services in target communities. 29 Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % IR 2.1: Increased capacity to provide services among financial service providers. EF-O2-01: Number of financial services providers with increased capacity to provide financial services in target geography EF-O2-02: Total number of financial services provided through USG-assisted financial intermediaries, including non-financial actors or institutions [mission indicator 182] (contract: number of financial products) IR 2.2: Expanded presence of financial service providers in target communities. EF-O2-03: Value of USG￾supported financial services (from list of mission indicators – 119) – Total EF-O2-03: Value of USG￾supported financial services (from list of mission indicators – 119) – Productive loans EF-O2-04: Value of agriculture-related financing accessed as a result of USG assistance 30 Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % EF-O2-05: Number of individuals participating in USG Food security programs EF-O2-06: Total number of clients benefiting from financial services provided through USG-assisted financial intermediaries, including non-financial institutions or actors – Total EF-O2-06: Total number of clients benefiting from financial services provided through USG-assisted financial intermediaries, including non-financial institutions or actors – New clients EF-O2-06: Total number of clients benefiting from financial services provided through USG-assisted financial intermediaries, including non-financial institutions or actors – New underserved EF-O2-06: Total number of clients benefiting from financial services provided 31 Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % through USG-assisted financial intermediaries, including non-financial institutions or actors – Women/women owned businesses EF-O2-07: Percentage of female participants in USG￾assisted programs designed to increase access to productive economic resources (assets, credit, income or employment) EF-O2-08: Percentage of participants who are youth (15-29) in USG-assisted programs designed to increase access to productive economic resources [IM￾level] IR 2.3: Increased provision of digital services by financial providers. EF-O2-9: Number of digital finance products that have been developed, deployed and/or strengthened EF-O2-10: Percent increase in utilization rate of digital financial products 32 Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % EF-O2-11: Number of clients using digital financial services Objective 3: An improved ecosystem for the financial inclusion of underserved populations. IR 3.1: Improved collection and use of financial consumer data. EF-O3-01: Framework/guideline in coordination with the GOC, Banca de las Oportunidades and financial intermediaries covering the quantity, usage, and quality of data for measuring financial inclusion developed EF-O3-02: Comprehensive and sustainable data management system that facilitates the analysis of information for financial and economic inclusion of at least two underserved population segments implemented. IR 3.2: Enhanced regulatory framework for financial inclusion. EF-O3-03: Number of regulatory recommendations that promote underserved populations’ financial inclusion drafted and adopted by the GOC. 33 Code- Indicator Name Abbr. Previous FY Current Year (FYXX) Activity Total Progress Observations FYXX Actual FYXX Target Q1 Q2 Q3 Q4 FY Actual FY Target FY Prog. % Total Prog LOA Target Total Prog % Special Objective: Increased mobilization of long-term financial capital for USAID’s priority sectors. EF-SO-01: Value of funds mobilized in FINAGRO’s 2nd tier facility after agreement is reached with FINAGRO and GOC. EF-SO-02: Number of innovative/alternative finance instruments proposals that can be implemented to support the mobilization of long-term financial capital towards USAID’s priority sectors (CDCS). Crosscutting EF-CC-01: Number of USG engagements jointly undertaken with private sector enterprises to support U.S. foreign assistance objectives EF-CC-02: Value of Mobilized Funds [mission indicator – 40] EF-CC-03: Value of Leveraged Funds [mission indicator – 156] 34 Exhibit 6. Reporting Flow 6. ROLES AND RESPONSIBILITIES SECTION The EF MEL team, comprised of a core team of two, will be led by the MEL Manager, in close coordination with the Knowledge Management and Communications Manager and with oversight provided by COP Young. Other Activity staff, such as the Regional and Inclusion Manager and Regional Coordinators, and DAI’s home office staff will provide support to the MEL team. The MEL team will provide coordination, oversight and guidance to provide standardized tools, methodologies and reporting forms. Data collected from performance, context and complexity-aware monitoring along with learning activities will be reviewed quarterly during QPRs with the management and technical staff so they are aware of progress and can share lessons learned and adapt if necessary. The MEL Team will inform the technical staff if activities are not on track and Partner Activities Partner Staff Data collection Data management MEL Team Training Quality assurance, learning Consolidating, calculating, and reporting Objective Leads Data review Learning Reporting Report Monthly Quality Assurance, Management Team (COP, DCOP, HO) Review and reporting Report Monthly Feedback Report Monthly and Quarterly 35 assist them with developing action plans to achieve targets. The MEL Team will also update the AMELP and Learning Agenda to be suitable with the current context. Specific roles and responsibilities are outlined below, followed by a schedule of MEL tasks. The MEL Manager will supervise the MEL team and take overall responsibility for performance monitoring, data quality management, and CLA activities. She will develop all monitoring tools, establish data cleaning and quality assurance protocols, and train DAI and partner staff, as needed. She will lead the Activity’s studies, assessments, and reporting. She will work closely with the Mission’s MEL Activity to ensure all necessary data is collected for the mission’s PMP and Learning Agenda. She will revise and update the AMELP and Learning Agenda annually. The MEL and Database Specialist will work closely with the MEL Manager to support data collection, analysis, and reporting for all EF activities and partners. They will oversee the collection of data via a variety of tools and methodologies for Activity results tracking, reporting, and adaptive learning. They will support the training of partners to ensure they collect and report data based on the interventions. They will clean the data when needed, as per protocols established by the MEL Manager, program forms when necessary, develop and maintain a data management system to manage, clean and analyze data. They will support the MEL Manager with data analysis and reporting. The Knowledge Management and Communications Manager will oversee preparation of contract deliverables and communications materials and events that utilize MEL data and evidence such as presentations, press releases, talking points, fact sheets, case studies, success stories, brochures, profiles, as well as weekly, quarterly, and annual reporting on the project’s progress. He/she will operationalize the Knowledge Management strategy and engage with Banca de las Oportunidades and industry associations to ensure project information products meet the needs of industry stakeholders and adjust the knowledge management strategy as needed. He/she will lead project-wide initiatives to foster continual collaboration, learning and adaptation of the knowledge management strategy to ensure quality and improvement. The Regional and Inclusion Manager and Regional Coordinators will provide technical support and lead on the field analysis and verification. They will assist with developing tools to capture data that allows for analysis with a GESI lens. They will also support other quantitative/qualitative assessments in targeted municipalities to assess effectiveness and inclusion of interventions. They will work closely with other technical specialists to integrate gender and social inclusion across all Activity and MEL components. Table 5. MEL Schedule of Tasks Task Frequency Lead(s) Reviewer(s) Administrative Develop AMELP Once HO MEL Specialist COP Update AMELP Annually MEL Manager COP Develop Learning Agenda Once MEL Manager and HO MEL Specialist COP Update Learning Agenda Annually MEL Manager COP Monitoring Data collection Ongoing MEL and Database Specialist MEL Manager Data cleaning Ongoing MEL and Database Specialist MEL Manager 36 Task Frequency Lead(s) Reviewer(s) Data analysis Ongoing MEL and Database Specialist MEL Manager Data reporting (PITT and narrative reports) Quarterly, Annually MEL Manager COP Data reporting in MONITOR Quarterly MEL and Database Specialist MEL Manager Data reporting in USAID training database (as required) As needed MEL and Database Specialist MEL Manager Submission of data and reports in DDL and DEC As needed MEL Manager COP Data Quality Routine data checks Monthly MEL Manager COP Internal DQAs Annually MEL Manager COP External DQAs TBD USAID External Assessors MEL Manager Evaluations Baseline evaluation Once USAID External Evaluators EF Management Final evaluation TBD USAID External Evaluators EF Management Learning Baseline assessments Y1 Technical team members COP QPRs Quarterly COP and MEL Manager N/A P&R sessions As needed COP and MEL Manager N/A Milestone reviews Annually COP and MEL Manager N/A Annual P&R/work planning Annually COP and MEL Manager N/A Research and assessments TBD Technical team members COP Workshops TBD Technical team members COP 37 7. ACTIVITY PIRS AND CIRS PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O1-01 Number of people that have participated in financial education/literacy activities Name of Development Objective: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the number of people who have participated in financial education and/or financial literacy activities developed, revised and/or provided through USG assistance Financial education/literacy activities include:  Participation in formal in-person or virtual trainings developed or implemented by financial service providers, business service providers, NGOs or other institutions. Virtual training includes platforms, modules and simulators and a plan for people to obtain basic skills in financial management.  Participation in education programs developed or implemented by education institutions, NGOs or other training organizations following Colombia’s policy for economic and financial inclusion education. Financial education is defined as a strategy for cumulative learning about economic concepts with the intention of improving asset management, savings and risk mitigation. Financial literacy is defined as knowledge of basic financial concepts and the skills and attitudes to translate this knowledge into behaviors that improve financial outcomes. Unit of Measure: Number of people. Specific to the reporting period. Data Type: Integer Disaggregated by: Sex, age, location * Ethnicity will not be included as a disaggregation, but EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: EF partners will collect attendance records via sign in sheets at every activity and compile data to report to DAI. It will require partners to track use of on-line and downloaded 38 financial education and literacy programs and applications. Partners will submit monthly reports to DAI through MELAir forms. DAI will compile data from partners into the MELAir. Method of Data Collection and Construction: Partner records. Attendees will sign in during the activity. The sign in records will be maintained by each partner. Partner records of use or downloaded digital programs. Data will be reported to DAI monthly. EF will design a data structure that can be filled in online or upload csv information from partners. All partners collect the data fields from participants when conducting in-person or virtual trainings. Basic information will have the name of the event, the time length of the training, the place where the training was conducted and the information about participants (client ID, sex, age, and location). Information will be transferred in a monthly manner from partners to EF MEL’s Team. Reporting Frequency: Partners will report monthly to DAI. DAI will report data quarterly to USAID. Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 100,000 Fiscal Year Targets: FY2023: 0 FY2024: 17,000 FY2025: 33,000 FY2026: 35,000 FY2027: 15,000 Rationale for Targets: During the first year of implementation EF will reach agreements with financial service providers and education institutions of the target geography to partner, deploy or expand financial education/literacy activities for the target population in a sustainable way. Years 2 to 5 show a bell curve consistent with resource allocation and level of effort. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique attendees and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a participant attends activities organized by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. 39 Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 40 ERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O1-03 Sustainable and scalable business development service/model operationalized Name of Development Objective: EF: O1 – Increased financial capacity in target communities CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR1.2 Increased financial capacity among targeted individuals. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the development and operationalization of one sustainable and scalable business development service/model for MSMEs. The business development service or model will be developed in collaboration with the existing cadre of GOC-supported and private-sector business development providers, financial services industry associations, and municipal or departmental level chambers of commerce. The term “Developed” may include services/models that have been newly developed, improved or materially modified with USG support, such as adding a digital version or distribution method to an existing service/model. Operationalized is defined as the deployment of the business service or model. Sustainable is defined as the service/model being maintained and provided to customers at a certain rate or level without Activity support. Scalable is defined as a service/model that is expanding to additional customers after the end of Activity support. The service/model will be useful to bridge the management and requirement gaps between MSMEs and financial intermediaries. Unit of Measure: Service/model Cumulative Data Type: Yes/No Disaggregated by: None Justification/Utility for Indicator (optional): 41 PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: Sum of service/model. If one is achieved, the results is yes. If none are achieved, result is no. From the technical activity records, EF MEL’s Team will have the supporting information from each model and the qualitative description that supports the category assigned. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: No Baseline Timeframe: Dec 2022 Life of Project Target (LOP): Yes Fiscal Year Targets: FY2023: No FY2024: No FY2025: No FY2026: No FY2027: Yes Rationale for Targets: By the end of the last year, EF will have operationalized a sustainable and scalable business development service/model. Notes on baseline and targets: None QUALITY DATA ISSUES Known Data Limitations: None Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 42 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O1-03 Number of firms receiving USG-funded technical assistance for improving business performance [EG.5.2-1] Name of Development Objective: EF: O1 – Increased financial capacity in target communities CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR1.2 Increased financial capacity among targeted individuals. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: IR 3.2.3 - Expanded production in emerging cultural and environmental value chains CDCS: IR 4.2.2 - Private sector engagement efforts expanded to receptor communities Indicator Type: Standard/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the number of firms receiving USG-funded technical assistance for improving business performance. Firms can be formal or informal. If multiple owners, managers or workers in a single firm receive technical assistance over the reporting period, the reporting operating unit should count that as one benefiting the firm for the reporting period. Technical assistance includes the transfer of knowledge and/or expertise by way of staff, formal or informal skills training, and research work to support quality of program implementation and impact, support administration, management, representation, publicity, policy development and capacity building. The technical assistance should have the explicit goal of improving business performance in terms of profit and revenue or employment through improving management or workers’ generic financial or management practices, or industry or market-specific knowledge and practices. Technical assistance includes both human and institutional resources. Technical assistance does not include financial assistance alone. Technical assistance may be provided in-person, virtually or a mix of both. USG funding: For the purpose of this indicator, OUs can count technical assistance that was delivered in full or in part as a result of USG assistance. This may include providing funds to pay teachers, providing training facilities, or other key contributions necessary to ensure training is delivered. A firm will count towards this indicator when it receives technical assistance the first time and can be counted only once. Unit of Measure: Number of firms. Specific to the reporting period. Data Type: Integer 43 Disaggregated by: * Level of formalization (Formal, informal) - Adds to the indicator * New/continuing (New firms are those that did not receive assistance reportable under this indicator in the previous reporting period; continuing firms are those that received assistance reportable under this indicator in the previous reporting period); * Firms size (Microenterprises employed <=10 people in the previous 12 months, Small enterprises employed 11-50 people, Medium enterprises employed 51-200 individuals, Large enterprises and corporations employed >200 individuals); * Sex (Male producer/proprietor, female producer/proprietor, mixed, other). 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 years old, 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. * Geographic location (municipalities) Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: EF reports and activity records/survey to firms Method of Data Collection and Construction: The data will be collected through reports to EF from partners/service providers. EF will contact firms that have received USG-funded technical assistance for improving business performance to verify the data reported. EF will provide the basic parameters of the indicator to the partners for them to collect primary data. Partners will collect information when they provide technical assistance to their counterparts. The information collected will characterize the firms by level of formalization, size, sex, age and geographic location. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 50 Fiscal Year Targets: FY2023: 0 FY2024: 10 FY2025: 10 44 FY2026: 25 FY2027: 5 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, development of agreements with private sector firms to receive technical assistance and allocation of resources. Notes on baseline and targets: The baseline can be zero (0) for new USG-funded technical assistance for improving business performance. QUALITY DATA ISSUES Known Data Limitations: Potential technical issues when collecting information in surveys. Potential barriers to collect information in target zones that are suffering from conflict and violence problems. Partners will keep records of unique attendees and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a participant attends activities organized by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 45 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O1-04 Number of microenterprises supported by USG assistance [EG.5- 3] Name of Development Objective: EF: O1 – Increased financial capacity in target communities CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR1.2 Increased financial capacity among targeted individuals. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: IR 3.2.1 – Targeted value chains more responsive to market demands Indicator Type: Standard/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator counts the number of microenterprises (whether formal or informal) supported or other livelihood programming as a result of USG assistance. Interventions for the very poor include graduation approaches, financial services targeted to the very poor includes the provision of loans, the acceptance of savings deposits, and payments services such as the provision or cashing of money orders, and other similar services. Social safety net services targeted to the very poor include in￾kind subsidies and cash transfers. A write up on different interventions is found here: HTTPS://WWW.MARKETLINKS.ORG/RESOURCES/REPORT-MICROENTERPRISE-AND￾PATHWAYS-OUT-POVERTY. Micro-enterprises are defined by Law 590 of 2000 as those that do not have more than 10 workers and whose assets are less than 501 legal monthly minimum wages. Unit of Measure: Number of microenterprises. Specific to the reporting frequency. Data Type: Integer Disaggregated by: * Sex (Male entrepreneur/producer/proprietor, Female entrepreneur/producer/proprietor, Other) – Adds to the indicator 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. * New/continuing; * Formal and informal micro enterprises; * Age (15-29 years old, 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 46 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. Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: EF reports and activity monitoring records Method of Data Collection and Construction: Data for this indicator should be collected throughout monitoring reports. Data will be stored in MELAir and automatically summed. EF will provide the basic parameters of the indicator to the partners for them to collect primary data. Partners will collect information when they provide technical assistance to their counterparts. The information collected will characterize the microenterprises by level of formalization, age, sex, location, and either new or existing. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 30 Fiscal Year Targets: FY2023: 0 FY2024: 5 FY2025: 8 FY2026: 10 FY2027: 7/ Rationale for Targets: 6 per corridor Notes on baseline and targets: The baseline should be established from the beginning of the activity and, if necessary, it can be defined as zero value (0). QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique attendees and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a participant attends activities organized by different partners. 47 Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 48 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-01-05 Approximate number of very poor beneficiaries from USG assistance targeted to reach the very poor [EG.5-16] Name of Development Objective: EF: O2 - Increased provision of financial services in target communities CDCS: DO3 - Promote equitable and environmentally sustainable economic growth Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: IR 3.1 - Expanded licit livelihood opportunities Name of Sub-Intermediate Result: Indicator Type: Standard/Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): This is a mandatory indicator for programs that attribute to the microenterprise/livelihoods money in the operational plan. EF will use the Government of Colombia´s Departamento Administrativo Nacional de Estadística (DANE) methodology for monetary poverty (see below). Definition Interventions for the very poor include graduation approaches, financial services targeted to the very poor includes the provision of loans, the acceptance of savings deposits, and payments services such as the provision or cashing of money orders, and other similar services. Social safety net services targeted to the very poor include in-kind subsidies and cash transfers. Business development services may be customized to assist very poor clients to move from subsistence livelihood activities to more commercial activities and prepare to access financing. According to DANE the monetary poverty line is any person who receives below COP $354,031 in a month, and extreme monetary poverty below COP $161,099, in 2022 prices –some adjustments may be required in the following years according to inflation rates. Identification of individuals in poor conditions will follow the DANE methodology as close as possible, taking questions from the Gran Encuesta Integrada de Hogares (GEIH – DANE) and making an estimation of net income where the threshold is set for monetary poverty and extreme monetary poverty. We will run a fast and direct statistical survey to the sample frame of the program that allows us to infer the percentages of monetary poor and extreme monetary poor individuals among direct beneficiaries. DANE: https://www.dane.gov.co/index.php/estadisticas-por-tema/pobreza-y-condiciones-de￾vida/pobreza-monetaria Unit of Measure: Number of beneficiaries Simple sum of individuals Data Type: Integer Disaggregated by: Type of assistance (business development service) Sex (Female, Male, Other, Not Available) 49 Age Location Justification/Utility for Indicator (optional): Information generated by this indicator will be used to monitor and report the achievements linked to the number of individuals whom receive BDS and fall below the very poor threshold given EF’s focus on increasing financial inclusion for marginalized communities and individuals. PLAN FOR DATA COLLECTION Data Source: Firm records, activity records, training participant lists Method of Data Collection and Construction: Data for this indicator will be collected through monitoring reports of EF partners. EF will provide the basic parameters of the indicator to the partners for them to collect primary data, estimate and report to EF based on the key questions of the DANE methodology. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 500 Fiscal Year Targets: FY2023: 0 FY2024: 50 FY2025: 100 FY2026: 250 FY2027: 100 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with other USAID funded projects, particularly the Sustainable Agriculture Activity to complement interventions. Notes on baseline and targets: Targets: Not cumulative QUALITY DATA ISSUES Known Data Limitations: This data will serve for estimating the number of very poor beneficiaries receiving USG assistance for BDS under the monetary poverty definition by GOC. BDS programs do not tend to focus on the very poor. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023 by (DAI MEL Specialist) 50 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-01 Number of financial services providers with increased capacity to provide financial services in target geography Name of Development Objective: EF: O2 - Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.1: Increased capacity to provide services among financial service providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the number of financial service providers with increased capacity to provide financial services in the target geography and/or to the target populations. Financial service providers include banks, non-banks (microfinance institutions, finance companies, digital finance providers, credit unions, cooperatives, NGOs and others) supported through USG assistance or as a result of direct development interventions by the USG. Increased capacity will be measured as result of the development or improvement of:  inclusive financial instruments, products or service for access of underserved populations  the delivery or distribution of a financial product or service  new financing methodologies, including nontraditional agricultural activities and businesses  blended financial system or fund to facilitate financing for high-risk ventures  skills, strategies and communications related to reaching new or EF target market segments, including marginalized populations  client protection and addressing of client grievances In the absence of a clear output, the MEL team will define an index to measure the capacity of partner financial service providers by determining a small set of indicators, measuring their baseline and change at the end of the USG assistance. Target geography: 193 municipalities of the departments of Antioquia, Caquetá, Cauca, Córdoba, Guaviare, Meta, Nariño, Norte de Santander and Putumayo. Unit of Measure: Financial service providers Data Type: 51 Integer Disaggregated by: Type of financial service provider (bank, micro finance NGO, fintech, etc.); Location Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: The MEL team will identify the outputs that indicate achievement of the outcome and as needed identify one or more indicators and capture a baseline and end of activity measurement. EF will build the forms to capture the information about critical factors that show increased capacity and will collect from the final financial services providers, or in case partners are implementing, EF will gather the information through the partner. The information collected will characterize type of financial service provider and the location. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 10 Fiscal Year Targets: FY2023: 0 FY2024: 2 FY2025: 2 FY2026: 3 FY2027: 3 Rationale for Targets: Gradual intervention across years 2 to 5 with 60% of the target to be achieved in years 4 and 5 after a concrete work plan is established with financial service providers. The collaboration with financial service providers will initiate at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES 52 Known Data Limitations: Unknown Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 53 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-02 Total number of financial services provided through USG-assisted financial intermediaries, including non-financial actors or institutions [mission indicator – 182] (contract: number of financial products) Name of Development Objective: EF: O2 - Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.1 Increased capacity to provide services among financial service providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom (mission indicator – 182)/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the total number of financial services, including loans, deposits, payments, insurance, equity investments and advisory services, provided by the USG-assisted intermediaries or as a result of direct development interventions by the USG and referred to in the EF contract as financial products. A financial intermediary is typically an institution such as a bank or non-bank institution (microfinance institution, finance company, digital finance provider, credit union, cooperative, and others). A non-financial institution could be an NGO, business association or value chain actor. Financial services should be counted only once per reporting year. A financial service may be counted once the baseline has been determined. Based on experience with financial intermediaries, to minimize double counting, the indicator will disaggregate new and continuing financial services and limit counting to those offered to the target segments and geographies. New financial services refer to loans, savings accounts, insurance, payments and other financial services that are introduced by USG-assisted financial intermediary to one or more clients during the reporting year. Continuing financial services refer to those same services that continue to be used by clients and were introduced by a USG-assisted financial intermediaries in previous reporting years. Unit of Measure: Number of financial services provided Data Type: Integer Disaggregated by: * New/continuing - (Adds to indicator) * Type of financial service (loan, savings, insurance, equity investment, other) 54 * Type of sector (agricultural, business, retail, other) * Location Justification/Utility for Indicator (optional): This indicator provides a measure of financial system performance by financial services counting offered in the Country or through the assistance of the USG in the Country, contributing to having a positive effect on the economy. Increased financial services provided impact inclusion in the financial sector, appropriate financial service offerings, and easy accessibility. PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: Data for this indicator will be collected throughout monitoring reports. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided by type of service, sector and location. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 10 Fiscal Year Targets: FY2023: 0 FY2024: 1 FY2025: 2 FY2026: 4 FY2027: 3 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, development, adjustment and deployment of financial services and allocation of resources. The development of financial services will start as soon as agreements with financial service providers are reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES 55 Known Data Limitations: Technical weakness to collect information through representative sampling. Some barriers to collect information due to target zones are suffering conflict and violence problems. It may not be possible to define, differentiate and report on savings products due to challenges identified in defining the value and linkages with some other financial products. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 56 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-03 Value of USG-supported financial services [mission indicator – 119] Name of Development Objective: EF: O2 - Increased provision of financial services in target communities CDCS: DO3 - Promote equitable and environmentally sustainable economic growth CDCS: SO4 - Stability in areas impacted by migration from Venezuela Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: IR 3.2 - More competitive licit economies CDCS: IR 4.2 - Increased participation in licit economies Name of Sub-Intermediate Result: CDCS: IR 3.2.2 - Increased private sector investment and access to financial services CDCS: IR 4.2.2 - Private sector engagement efforts expanded to receptor communities Indicator Type: Custom (mission indicator – 119)/Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): This indicator measures the total value of financial services, including loans, deposits, payments, insurance and advisory services provided by USG-assisted intermediaries or as a result of direct development interventions by the USG. For credit products, the entire amount disbursed to clients for commercial loans and microcredit is considered. (Note: According to the definitions of the Financial Superintendence and the Solidarity Economy Superintendent, productive or agricultural loans are classified as commercial or microcredit depending on the amount). Disbursements under renewed loans are also considered. Loans can include diverse credit mechanisms, including value chain financing, such as factoring, leasing, purchase order financing, and agricultural credit cards, etc. Neither consumer credit nor consumer credit cards will be considered. For savings, the sum of deposits will be considered. For remittances, payments and transactions, the amount paid, sent or received by the client through the financial intermediary is considered. For insurance, the premium paid by the client is considered. Equity Investment: An equity investment is defined as the purchase of shares of a company. It provides developmental support and long-term growth capital that private enterprises need. 57 Unit of Measure: USD Million and equivalent Colombian Peso (COP) at an exchange rate of 3500 COP per USD Simple sum. Not cumulative. Data Type: Currency Disaggregated by: * Type of financial services (savings, loans, insurances, equity investment, other) - Adds to the indicator; * Geographic location (municipalities) *Productive/ non-productive; *Sector; *Population Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Reports and activity records of implementing partners, supported with administrative records from financial organizations. Method of Data Collection and Construction: The data will be collected by implementing partners through the activity records and administrative data from financial organizations. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided by type of service, sector and location. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 550 (440 productive loans) Fiscal Year Targets: FY2023: 0 (0 productive loans) FY2024: 50 (40 productive loans) FY2025: 150 (120 productive loans) FY2026: 200 (160 productive loans) FY2027: 150 (120 productive loans) Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to 58 receive technical assistance and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. 80% will be productive loans Notes on baseline and targets: The baseline can be zero (0) for in the cases where financial support has just begun. If there is available information in a previous year, this can be used as baseline. QUALITY DATA ISSUES Known Data Limitations: Potential technical issues when collecting information from financial organizations. Potential barriers to collect information in target zones that are suffering from conflict and violence problems. It may not be possible to define, differentiate and report on savings products due to challenges identified in defining the value and linkages with some other financial products. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 59 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-04: Value of agriculture-related financing accessed as a result of USG assistance [EG.3.2-27] Name of Development Objective: EF: O2 - Increased provision of financial services in target communities CDCS: DO3 - Promote equitable and environmentally sustainable economic growth Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: IR 3.2 - More competitive licit economies Name of Sub-Intermediate Result: CDCS: IR 3.2.2 - Increased private sector investment and access to financial services Indicator Type: Standard/Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): This indicator sums the total COP value of debt (both cash and in-kind loans) and non-debt financing, such as equity financing, disbursed as a result of USG-assistance during the reporting year to producers (farmers, ranchers and other primary sector producers of food and non-food crops, livestock products, fish and other fisheries/aquaculture products, agro-forestry products, and natural resource-based products, 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, including banks, non-banks and cooperatives, and non-financial firms engaged in agriculture (input suppliers, off-takers, etc.) but not by informal groups such as village savings and loan groups that are not formally registered as a financial institution (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). 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. 60 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”. Unit of Measure: USD Million and equivalent Colombian Peso (COP) at an exchange rate of 3500 COP per USD Simple sum. Not cumulative. Data Type: Currency Disaggregated by: Required Disaggregates: * Type of financing accessed (Cash, In-kind, Non-debt) - Adds to the indicator * Type of financing recipient (Retail, Business); If individuals, add the following disaggregates: * Sex (Female, Male, Other) * Age (15-29 years old, 30+) If microenterprises, add the following disaggregates: * Firms size (Microenterprises employed <10 people in the previous 12 months, Small enterprises employed 10-49 people, Medium enterprises employed 50-249 individuals, Large enterprises and corporations employed >250 individuals.); * Sex (Male producer/proprietor, Female producer/proprietor, 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 years old, 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. Note: All required disaggregates must be reported in Monitor Justification/Utility for Indicator (optional): 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. 61 PLAN FOR DATA COLLECTION Data Source: Reports and activity records (Financial institution and investor records or survey of activity participants). Method of Data Collection and Construction: The data will be collected from partners reports related to values of credits, debits, and guarantees accrued with respect to the final beneficiary, will be separately accounted and crossed against other categories (disaggregates) such as sex. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided by type of service, sector and location. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 (It can be “zero” for value of financial services that newly have accessed. If there are available information in a previous year, this can be used as baseline.) Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 150 Fiscal Year Targets: FY2023: 0 FY2024: 0 FY2025: 50 FY2026: 80 FY2027: 20 Rationale for Targets: Gradual intervention across years 3 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and Finagro to mobilize finance for agricultural purposes. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: Baseline can be “Zero” for value of financial services newly provided through of USG assistance. QUALITY DATA ISSUES Known Data Limitations: 62 Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 63 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-05: Number of individuals participating in USG Food security programs [EG.3-2] Name of Development Objective: EF: O2 - Increased provision of financial services in target communities CDCS: DO3 - Promote equitable and environmentally sustainable economic growth Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: IR 3.1 - Expanded licit livelihood opportunities Name of Sub-Intermediate Result: CDCS: IR 3.1.3 - Enhanced job skills to participate in the labor market Indicator Type: Standard/Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): This indicator is designed to capture the breadth of our food security work. This indicator counts participants of Feed the Future-funded programs, therefore EF will collect and report data on project beneficiaries that are being supported by other USAID FtF activities that also receive financial education, BDS and/or financial services through EF. This indicator counts all the individuals participating in agricultural lending interventions, including: ● People reached by community-based micro-finance and financial education through USG assistance; ● Smallholder and non-smallholder producers that EF or its partners reach directly (e.g. through a loan provided); ● ● 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; 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. 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 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. 64 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 anyone 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 of FTF Handbook. Unit of Measure: Number of individuals Simple sum of individuals participating in USG food security programs Data Type: Integer Disaggregated by: * Sex (Female, Male, Other, Not applicable, Not Available) - Adds to the indicator (the unique number of individuals should be entered here (i.e. no double-counting of individuals across disaggregate choices here)), (“Not applicable” (e.g. for household members counted from household-level interventions); * Age (15-29 years old, 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. * Location (municipalities) * Size of MSME Note: All required disaggregates must be reported in Monitor Justification/Utility for Indicator (optional): 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 targeted geographic area survey and performance and impact evaluations rather than through annually reported IM-level indicators. This indicator is an output indicator and is linked to many parts of the Global Food Security Strategy results framework. This indicator will be used to measure progress in the Bureau for Food Security/FTF portfolio review, the FTF Progress Report and country pages, and the International Food Assistance Report (IFAR). PLAN FOR DATA COLLECTION Data Source: Firm records, activity records, training participant lists Method of Data Collection and Construction: Data for this indicator will be collected through collaboration with other projects of the SEED office where beneficiaries receive financial education, BDS and/or financial services. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager 65 TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 500 Fiscal Year Targets: FY2023: 0 FY2024: 50 FY2025: 100 FY2026: 250 FY2027: 100 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and Finagro to mobilize finance for agricultural purposes. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: ● “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 Targets: Not cumulative QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique attendees and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a participant attends activities organized by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Results under this indicator will be dependent on collaboration with other projects of the SEED office where beneficiaries receive food security interventions as defined above. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR 66 This PIRS was last updated 03/13/2023by (DAI MEL Specialist) PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-06 Total number of clients benefiting from financial services provided through USG-assisted financial intermediaries, including non-financial institutions or actors [EG.4.2- 1] Name of Development Objective: EF: Objective 2: Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.1: Increased capacity to provide services among financial service providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural communities Indicator Type: Standard/Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): Clients include any individual or business that accesses a financial service from a USG-assisted intermediary. Financial services include loans, deposits, payments, insurance and advisory services, provided by the USG-assisted intermediaries or as a result of direct development interventions by the USG. A financial intermediary is typically an institution such as a bank or non-bank institution (microfinance institution, finance company, digital finance provider, credit union, cooperative, and others). A non￾financial institution could be an NGO, business association or value chain actor. Clients should be counted only once per reporting year regardless of the number of financial services received during the year. A new client may be counted once the baseline has been determined. A new client is one accessing for the first time a specific financial service provided by the financial intermediary. A client that already has a savings account with a financial intermediary and that acquires a loan for the first time is counted as a new client of loans. However, a client who already has a loan and accesses a new loan or renews a loan in the same credit category (i.e. takes out another micro-loan, takes another commercial loan, etc.), may not be counted as new. Clients of financial services can be individuals or MSMEs. 67 Based on experience with financial intermediaries, to minimize double counting, the indicator will include new and continuing clients in different disaggregations. New clients refer to individuals with new loans, new savings accounts (without loans), insurance, and other non-mandatory financial services. New clients of savings and obligatory insurance products attached to loans should not be included. Loans include any type of commercial loan, excluding, however, any letter of credit, credit card debt, line of credit, overdraft or other forms of revolving debt. Unit of Measure: Number of clients benefiting from financial services provided. Not cumulative. Data Type: Integer Disaggregated by: * Type of clients of financial services (Individuals or MSMEs) - (Adds to indicator) * Geographic location (municipalities); * Type of financial service (loan, savings, payments, insurance, equity investment, other); *Sex (Male producer/proprietor, female producer/proprietor, mixed, other, not available). 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 years old, 30+) *New/continuing *Underserved Justification/Utility for Indicator (optional): This is a standard output indicator in a results framework in which economic opportunity is the objective. This measures financial inclusion and depth of access to financial markets. This indicator provides a reasonably comprehensive measure of the scale of impact, though clearly not the level of impact of the USG’s microfinance activities. This will be used to demonstrate financial inclusion and depth of access to finance. PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: Partners will report number of clients to DAI through MELAir forms on a monthly basis. DAI will compile data from all partners in MELAir and report to USAID on an annually basis. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about clients and services provided by type of service, sector and location. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager 68 TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 200,000 (100,000 women Fiscal Year Targets: FY2023: 0 (0 womenproducer/proprieter) FY2024: 20,000 (10,000 women producer/proprieter) FY2025: 30,000 (15,000 women producer/proprieter) FY2026: 80,000 (40,000 women producer/proprieter) FY2027: 70,000 (35,000 women producer/proprieter) Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. EF will target 50% of the clients to be female or women-owned businesses. Notes on baseline and targets: Targets for total and new underserved are the same – as all clients benefiting from financial services will be new and underserved. QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of clients and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a client accesses financial services from different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Financial entities do not always register client municipality in information systems, sometimes transactions are registered by the branch location where the transaction is booked. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 69 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-02-07: Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources (assets, credit, income or employment) [GNDR-2] Name of Development Objective: EF: O2 - Objective 2: Increased provision of financial services in target communities CDCS: CC - Cross-cutting Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: Gender Name of Sub-Intermediate Result: N/A Indicator Type: Standard/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures percentage of female participants in USG-assisted programs designed to increase access to productive economic resources assets, credit, income, employment, and other. Productive economic resources include: assets, land, housing, businesses, livestock or financial assets such as savings, credit, wage or self-employment, and income. Programs include: • micro, small, and medium enterprise programs; • financial inclusion programs that result in increased access to finance, including programs designed to help youth set up savings accounts This indicator does NOT track access to services, such as business development services or stand￾alone employment training (e.g., employment training that does not also include job placement following the training). Numerator = Number of female program participants Denominator = Total number of male and female participants in the program The resulting percentage should be expressed as a whole number. EF will use the indicator EF-O2-04 to calculate this indicator. Unit of Measure: Percentage of females Data Type: Percentage, no decimals Disaggregated by: * Numerator * Denominator * Location 70 Justification/Utility for Indicator (optional): Information generated by this indicator will be used to monitor and report on achievements linked to broader outcomes of gender equality and female empowerment, and will be used for planning and reporting purposes by Agency-level, bureau-level and in-country program managers. Specifically, this indicator will inform required annual reporting or reviews of the USAID Gender Equality and Female Empowerment Policy and the Joint Strategic Plan reporting in the APP/APR, and Bureau or Office portfolio reviews. This indicator will also be used to report on the Women's Global Development and Prosperity (W-GDP) Initiative. The W-GDP is a White-House led, inter￾agency Initiative prioritized by USAID. Additionally, the information will inform a wide range of gender-related public reporting and communications products, and facilitate responses to gender￾related inquiries from internal and external stakeholders such as Congress, NGOs, and international organizations. The lack of access to productive economic resources is frequently cited as a major impediment to gender equality and women’s empowerment, and is a particularly important factor in making women vulnerable to poverty. Ending extreme poverty, a goal outlined in the Sustainable Development Goals and USAID's Vision to Ending Extreme Poverty, will only be achievable if women are economically empowered. PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: Data will be collected through partner reporting to DAI through MELAir. The unit of measure will be a percentage expressed as a whole number. Numerator = Simple sum of female program participants Denominator = Total number of male and female participants in the program (Simple sum of female program participants / Total number of male and female participants in the program) * 100 The resulting percentage should be expressed as a whole number. For example, if the number of females in the program (the numerator) divided by the total number of participants in the program (the denominator) yields a value of .16, the number 16 should be the reported result for this indicator. Values for this indicator can range from 0 to 100. The numerator and denominator must also be reported as disaggregates EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS). EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 50% 71 Fiscal Year Targets: FY2023: N/A (no clients in 2023) FY2024: 50% FY2025: 50% FY2026: 50% FY2027: 50% Rationale for Targets: Throughout the life of the activity, EF will target at least 50% of clients to be female. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique clients and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a client is served by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Financial entities do not always register client municipality in information systems, sometimes transactions are registered by the branch location where the transaction is booked. Date of Previous Data Quality Assessment (DQA): 2019, 2022 Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 72 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-08 Percentage of participants who are youth (15-29) in USG-assisted programs designed to increase access to productive economic resources [IM-level] [YOUTH-3] Name of Development Objective: EF: O2 - Objective 2: Increased provision of financial services in target communities CDCS: CC - Cross-cutting Name of Intermediate Result: EF: IR 2.2: Expanded presence of financial service providers in target communities. CDCS: Youth Name of Sub-Intermediate Result: N/A Indicator Type: Standard/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): Youth is a life stage when one transitions from the dependence of childhood to adulthood independence. The meaning of “youth” varies in different societies. In Colombia, youth is defined as people between the ages of 10-29. The productive economic resources that are the focus of this indicator are physical assets, such as land, equipment, buildings and, livestock; and financial assets such as savings and credit; wage or self-employment; and income. Programs include: • financial inclusion programs that result in increased access to finance, including programs designed to help youth set up savings accounts This indicator does NOT track access to services, such as business development services or agriculture, food security or nutrition training. The unit of measure for this indicator is a percent. EF will use the indicator EF-O2-07 to calculate this indicator. Unit of Measure: Percentage of participants Data Type: Percent Disaggregated by: Numerator, denominator. Location Justification/Utility for Indicator (optional): Harnessing the energy, potential, and creativity of youth in developing countries is critical for sustainably reducing global hunger, malnutrition, and poverty while reducing the risk of conflicts and extremisms fueled by growing numbers of marginalized and frustrated youth [1]. To achieve the objectives of the U.S. Government Global Food Security Strategy (GFSS) and A Food-Secure 2030 vision, Feed the Future needs to harness the creativity and energy of youth. This indicator 73 will allow Feed the Future to track progress toward increasing access to productive resources for Feed the Future program participants who are youth. Under the GFSS, this indicator is linked to CCIR 4: Increased youth empowerment and livelihoods. [1] “Global Food Security Strategy FY 2017-2021,” September 2016, accessed January 8, 2018, HTTPS://FEEDTHEFUTURE.GOV/SITES/DEFAULT/FILES/RESOURCE/FILES/USG_GLOBAL_FOO D_SECURITY_STRATEGY_FY2017-21_0.PDF This indicator is used to measure progress in the FTF/BFS Portfolio review and may be used for the FTF country pages. PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided by type of service, sector and location. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Partners and activity records will have their datasets with information about people who participated in program and will include data about the numerator and denominator. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 20% Fiscal Year Targets: FY2023: N/A (no clients in FY2023) FY2024: 20% FY2025: 20% FY2026: 20% FY2027: 20% Rationale for Targets: Less than 14% of the population are youth, EF will target 20% of clients to be youth throughout the life of the activity. Notes on baseline and targets: 74 QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique clients and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a client is served by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 75 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-9 Number of digital finance products that have been developed, deployed and/or strengthened. Name of Development Objective: EF: O2: Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.3: Increased provision of digital services by financial providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the number of digital finance products that thanks to the support of EF have been developed, deployed and or strengthened. Digital finance products are financial services enabled by or delivered through digital technology (e.g., mobile phones, cards, point of sale devices, the internet) and include methods to electronically store and transfer funds; to make and receive payments; to borrow, save, insure and invest; and to manage a person's or enterprise's finances. For this indicator EF will support different stages of digital finance products including  Developed: the creation of new digital finance product  Deployed: putting into use already tested digital finance products  Strengthened: a material improvement of existing digital finance products Unit of Measure: Digital finance products Specific to the reporting frequency. Data Type: Integer Disaggregated by: New/Existing Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: 76 Activity monitoring reports Method of Data Collection and Construction: Partners will report to DAI on a monthly basis through MELAir. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 10 Fiscal Year Targets: FY2023: 0 FY2024: 1 FY2025: 3 FY2026: 4 FY2027: 2 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to collaborate in achieving EF’s objectives and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Some digital financial services cannot track the client to a specific geography, although it may be possible to track where transactions take place if they are conducted at a merchant. EF will work with digital financial services providers to identify the relevant geography. Ethnicity will not be included as a disaggregation as this is not used by financial service providers in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Date of Previous Data Quality Assessment (DQA): TBD 77 Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 78 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O2-10 Percent increase in utilization rate of digital financial products Name of Development Objective: EF: O2: Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.3: Increased provision of digital services by financial providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): Digital finance products are financial services enabled by or delivered through digital technology (e.g., mobile phones, cards, point of sale devices, the internet) and include methods to electronically store and transfer funds; to make and receive payments; to borrow, save, insure and invest; and to manage a person's or enterprise's finances. EF will look at utilization rates of deployed and strengthened digital products from indicator EF-O2-07 to determine if the products being developed/strengthened are being used by the target population. Unit of Measure: Percent increase reported cumulatively Data Type: Percent Disaggregated by: Financial product; Service provider Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports. Method of Data Collection and Construction: EF will receive reports from Fintech and other FSPs we work with through MELAir forms on a monthly basis. EF will compile and report annually. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services 79 provided and utilization by financial product. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. EF will put all information together differentiating by service provider. To calculate the increase in utilization, EF will establish a baseline with each partner and calculate the change in the number of transactions over time. To look at the larger impact on the entire sector, EF will also collect data from the GOC – Central Bank or Superintendence. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Life of Project Target (LOP): 30% Fiscal Year Targets: FY2023: 0% FY2024: 2% FY2025: 10% FY2026: 30% FY2027: 30% Rationale for Targets: Gradual intervention across years 2 to 5 with a maximum rate of 30% achieved in years 4 and 5. These targets reflect level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: The indicator will look at utilization rates, but it will not look at frequency of utilization. Some digital financial services are not able to identify the location of the user to determine if they are form the prioritized economic corridors. Date of Previous Data Quality Assessment (DQA): TBD 80 Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 81 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-02-11: Number of clients using digital financial services Name of Development Objective: EF: O2: Increased provision of financial services in target communities. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 2.3: Increased provision of digital services by financial providers. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Output Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): A client is defined as a unique user of digital finance provided by the USG-assisted providers or as a result of direct development interventions by the USG; a single client may have multiple digital accounts. Digital finance products are financial services enabled by or delivered through digital technology (e.g., mobile phones, cards, point of sale devices, the internet) and include methods to electronically store and transfer funds; to make and receive payments; to borrow, save, insure and invest; and to manage a person's or enterprise's finances. Unit of Measure: Number of individuals Data Type: Integer Disaggregated by: *type of services (account holder, payment, credit) * Age * Sex (Female, Male, Other, Unknown) Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Activity Monitoring Reports Method of Data Collection and Construction: EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about services provided. EF will work with partners to create a routine 82 to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 20,000 Fiscal Year Targets: FY2023: 0 FY2024: 2,000 FY2025: 3,000 FY2026: 8,000 FY2027: 7,000 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4. These targets reflect level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Partners will keep records of unique clients and share with EF. However, due to data protection rules, personal identifying information, such as name, ID, etc. cannot be shared. The risk of double counting exists in the case where a client utilizes services provided by different partners. Ethnicity will not be included as a disaggregation as this is not used by financial institutions in Colombia. However, EF will attempt to get information to help inform inclusion. If a solid approach is developed, then EF can re-evaluate including Ethnicity as a disaggregation. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 83 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O3-01 Framework/guideline in coordination with the GOC, Banca de las Oportunidades, and financial intermediaries covering the quantity, usage, and quality of data for measuring financial inclusion developed Name of Development Objective: EF: O3: An improved ecosystem for the financial inclusion of underserved populations. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 3.1: Improved collection and use of financial consumer data. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures EF’s development or improvement of a framework or guideline for measuring financial inclusion that covers the quantity, usage, and quality of data. Framework is defined as conceptual structure intended to serve as a support or guide to measure financial inclusion. Guideline is defined as an outline of standards to measure financial inclusion. Unit of Measure: Framework/guideline Specific to the reporting frequency. Data Type: Yes/No Disaggregated by: None Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: EF will have the information in its records about guidelines and frameworks provided that meet with the standard definition. 84 Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: No Baseline Timeframe: Dec 2022 Life of Project Target (LOP): Yes Fiscal Year Targets: FY2023: No FY2024: No FY2025: Yes FY2026: No FY2027: No Rationale for Targets: By the end of FY2025, a framework/guideline covering the quantity, usage, and quality of data for measuring financial inclusion will be developed. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: The indicator measures if a framework/guideline is developed but not if it is being used. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 85 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O3-02 Comprehensive and sustainable data management system that facilitates the analysis of information for financial and economic inclusion of at least two underserved population segments implemented. Name of Development Objective: EF: O3: An improved ecosystem for the financial inclusion of underserved populations CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 3.1: Improved collection and use of financial consumer data. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the implementation of a comprehensive and sustainable data management system that facilitates analysis of information for financial and economic inclusion of at least two underserved population segments. Data management system is defined as a set of principles or procedures to storage, secure and share data, guide data governance, and manage database and records. The definitions of financial and economic inclusion vary. Basic financial inclusion can be defined as accessing one or more financial services within the financial system. Economic inclusion suggest participating in the national economy, such as participating in the labor market, pursuing a livelihood or operating a business. Underserved population segments are defined as any of the target marginalized groups covered under EF such as women, victims, indigenous peoples, youth, Afro-Colombians, migrants, and LGBTQI+ (lesbian, gay, bisexual, transgender, queer, and intersex) communities. Unit of Measure: Data management system Specific to the reporting frequency. Data Type: Yes/No Disaggregated by: None Justification/Utility for Indicator (optional): 86 PLAN FOR DATA COLLECTION Data Source: Observatory reports Method of Data Collection and Construction: EF’s partners will collect, analyze and use data for each observatory. EF will have the information in its records about observatories meeting the conditions set in the standard definition. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL manager TARGETS AND BASELINE Baseline value: No Baseline Timeframe: Dec 2022 Life of Project Target (LOP): Yes Fiscal Year Targets: FY2023: No FY2024: No FY2025: Yes FY2026: No FY2027: No Rationale for Targets: By the end of FY2025, a data management system will be implemented. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Data use will be difficult to determine. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 87 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-O3-03 Number of regulatory recommendations that promote underserved populations’ financial inclusion drafted and adopted by the GOC. Name of Development Objective: EF: O3: An improved ecosystem for the financial inclusion of underserved populations. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: EF: IR 3.2: Enhanced regulatory framework for financial inclusion. CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator will track the number new or amended of laws, regulation or regulatory guidance that promote underserved population’s’ financial inclusion as a result of USG assistance. Data will be disaggregated and tracked by status – drafted and adopted. Unit of Measure: regulatory recommendations Specific to the reporting frequency. Data Type: Integer Disaggregated by: Drafted; Adopted Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports Method of Data Collection and Construction: EF will track recommendations that have been drafted and adopted by GOC. EF will have the information in its records about recommendations provided to GOC that meet with the standard definition. EF will track implementation of these changes through agreements with GOC entities with which it has letters of intent as well as public documents where regulatory changes are published as available. Reporting Frequency: Annually 88 Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 2 Fiscal Year Targets: FY2023: 0 FY2024: 0 FY2025: 0 FY2026: 1 FY2027: 1 Rationale for Targets: Two new or amended laws or regulations in total will be drafted and adopted, one in FY2026 and another one in FY2027. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: None Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 89 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-SO-01 Value of funds mobilized in FINAGRO’s 2nd tier facility after agreement is reached with FINAGRO and GOC. Name of Development Objective: EF: SO: Increased mobilization of long-term financial capital for USAID’s priority sectors. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Outcome Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator will track the value of funds mobilized by Finagro for the purpose of on-lending as a result of USG assistance. Second – tier facility refers to funds used to provide wholesale loan financial service providers that in turn on-lend those funds to individuals or businesses. This indicator will measure funds provided to Finagro by the government of Colombia (GOC) or other entities that are wholly or partially attributable to USG development interventions. This may include an increase in direct funding to Finagro by the GOC, international financial institutions, donor agencies or the private sector resulting from the Activity’s efforts. Note that this will be a sub-set of the figures reported in EF-02-03. There will be overlap between the two indicators. Unit of Measure: USD Million and equivalent Colombian Peso (COP) at an exchange rate of 3500 COP per USD Specific to the reporting frequency. Data Type: Integer Disaggregated by: Sector; Location Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION Data Source: 90 Activity monitoring reports Method of Data Collection and Construction: Reports from FINAGRO and from partner financial institutions according to USAID’s data records standards. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 150 Fiscal Year Targets: FY2023: 0 FY2024: 0 FY2025: 50 FY2026: 80 FY2027: 20 Rationale for Targets: Gradual intervention across years 3 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with Finagro to mobilize finance for agricultural purposes. Agreements with Finagro will be reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: None Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 91 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-SO-02 Number of innovative/alternative finance instruments proposals that can be implemented to support the mobilization of long-term financial capital towards USAID’s priority sectors (CDCS). Name of Development Objective: EF: SO - Increased mobilization of long-term financial capital for USAID’s priority sectors. CDCS: DO3 – Improved conditions for Inclusive Rural Economic Growth Name of Intermediate Result: CDCS: IR3.2 Increased public and private investment in the rural sector Name of Sub-Intermediate Result: CDCS: Sub IR 3.2.2 Increased private sector investment in target rural; communities Indicator Type: Custom/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator will track the number of proposals for viable financing instruments or structures to attract long-term capital into USAID’s priority sectors, including the financial sector, presented by the Activity to USAID. This includes financing instruments or structures that include USAID’s priority sectors, but may not be solely for those sectors, e.g. for the purpose of mitigating investment risk Innovative or alternative refers to instruments or structures that are not commonly used at present in Colombia and / or have not been used to mobilize capital into USAID’s priority sectors. A viable proposal is one that is considered feasible by with a reasonable amount of technical or financial support. USAID’s priority sectors are those economic or business sectors designated by USAID/Colombia in its Country Development Cooperation Strategy or other officially communicated guidance. Unit of Measure: Proposals Specific to the reporting frequency. Data Type: Integer Disaggregated by: Sector, location Justification/Utility for Indicator (optional): PLAN FOR DATA COLLECTION 92 Data Source: Activity monitoring reports Method of Data Collection and Construction: EF will track proposals. EF will have the information in its records about proposals provided that meet with the standard definition. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 3 Fiscal Year Targets: FY2023: 0 FY2024: 1 FY2025: 1 FY2026: 1 FY2027: 0 Rationale for Targets: One proposal is expected in FYs 2024-2026 Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: None Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 93 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-CC-01 Number of USG engagements jointly undertaken with private sector enterprises to support U.S. foreign assistance objectives [PSE-1] Name of Development Objective: EF: Crosscutting CDCS: CC - Cross-cutting Name of Intermediate Result: CDCS: Engagement and partnerships - Engagement and partnerships Name of Sub-Intermediate Result: N/A Indicator Type: Standard/Output Is this a PPR Indicator? Provided by USAID. DESCRIPTION Precise Definition(s): This indicator measures the breadth of USAID engagement with the private sector for the reporting year. An engagement is defined as a “strategic approach to planning and programming through which [the USG] consults, strategizes, aligns, collaborates, and implements with the private sector for greater scale, sustainability, and effectiveness of development or humanitarian outcome” (see USAID Private Sector Engagement Policy: https://www.usaid.gov/sites/default/files/documents/1865/usaid_psepolicy_final.pdf). An engagement can be tangible (e.g., financial assistance, materials, provision of goods and services) or informational (e.g., convenings, facilitation, strategy development) exchange between a private sector actor and the USG or USG implementer. An engagement counts towards this indicator if the interactions between the USG and the private sector result in a documented exchange (e.g., memorandum of understanding, strategy, activity design documentation) that affects the approach or programmatic strategy or objective in achieving the desired U.S. foreign assistance objective. An engagement can be one convening of private sector actors or a series of interactions with the private sector actor(s). An informational meeting with a business that does not yield documented changes to either the business or the USG’s strategic or programmatic approaches would not count. A Memorandum of Understanding that does not yield changes in the behavior of either the USG or the private sector actor in their approach to the MOU’s stated objective does not count as an engagement. An engagement can have multiple documented purposes: -Strategic Alignment, Project Design and Planning: engagements that advance development of complementary strategies and project design in line with U.S. foreign assistance objective(s) -Advocacy/Strengthening the Enabling Environment: engagements that address regulatory, legislative, and rule of law bottlenecks in a country’s business enabling environment -Harnessing Private Sector Expertise and Innovation: engagements that harnesses innovation, technology, research and development, industry expertise, and/or entrepreneurial skills to achieve development outcomes with or without USG financial commitments -Mobilizing Private Sector Financial Resources: engagements that leverage private-sector funding – including corporate social responsibility and philanthropy assets – or increase access to markets – such as through foreign direct investment or credit guarantees-- to address a U.S. foreign assistance objective with or without USG financial commitments 94 -Technical Assistance to Local Private Sector Actors – engagements that provide capacity building services-- such as training or mentoring/coaching-- to local private sector actors. Engagements with local or international private sector actors that only provide capacity building support to the local private sector is not counted. Multiple USG engagements can occur within an implementing mechanism carrying out an activity. USG engagements can also occur outside any formal procurement process such as actions that aim to identify shared interests or jointly advocate for regulatory reforms and other enabling environment actions. The private sector is defined as “For-profit, commercial entities and their affiliated foundations; financial institutions, investors and intermediaries; business associations and cooperatives; micro, small, medium and large enterprises that operate in the formal and informal sectors; American, local, regional, and multinational businesses; and For-profit approaches that generate sustainable income (e.g., a venture fund run by a non-governmental organization (NGO) or a social enterprise)” (See USAID’s Private Sector Engagement Policy). “Jointly undertaken” is defined an engagement between the USG, or a USG implementer, and the private sector that results in a coordinated action that can be implemented jointly, or separately in parallel. U.S. foreign assistance objective refers to strategic, development, and humanitarian assistance objectives as identified in the Department of State-USAID Joint Strategic Plan and USAID Country Development and Cooperation Strategies. Under the “purpose of joint engagement” and “U.S. foreign assistance objective addressed” disaggregates, count all purposes and objectives that apply to the engagement. These disaggregates do not need to aggregate to the total result reported under the parent indicator. Report the engagement only once under the “market-based engagement” disaggregate. A market￾based approach is defined as the use of business models and leveraging of market forces to solve development and humanitarian challenges without beyond the life of the engagement and without USG assistance. Proof of concept is not need for an engagement to count toward this disaggregate. To be counted, documentation must exist that either market forces were addressed or a business model developed as part of the engagement development process with private enterprise(s). This documentation is typically found in implementation plans, strategy design, or MEL frameworks. Corporate or Private Philanthropies and Foundation engagement with the USG that use business models and leveraging of market forces in the design and implementation of the engagement count as a market-based engagement. A market-based approach can engage low-income people as customers and supply them with products and services they can afford; or, as business associates (suppliers, agents, or distributors), to provide them with improved incomes. Government advocacy and anti-corruption engagements count as non-market based engagement. Note: This indicator is a snapshot indicator and cannot be summed across reporting years to calculate a total for the life of an activity. Engagements that continue beyond the reporting year should be counted for each reporting year that it is active. In this indicator the PPPs and the GDAs are added. Engagements that meet the criteria of a public￾private partnership are reported here under the PPP disaggregation and will also be reported under indicator P-CC-148. With PPPs the US Government (USAID/Colombia) is considered the public sector partner that provides funding. US Government resources must be invested in the common development objective of the partnership. Global Development Alliances (GDAs) are a subset of PPPs. GDA refers to partnerships directly involving USAID and the private sector where they jointly identify, define, and solve key business and development 95 More information "Guide for Monitoring USAID Colombia´s Engagement with Stakeholders" Unit of Measure: Number of engagements This indicator is a snapshot indicator and cannot be summed across reporting years to calculate a total for the life of an activity. Engagements that continue beyond the reporting year should be counted for each reporting year that it is active. Data Type: Integer Disaggregated by: * Type of Engagement (Market-Based, Non-Market Based)- Adds to the indicator; * Purpose of Joint Engagement (Strategic Alignment/Planning, Advocacy/Strengthening the Enabling Environment, Harnessing Private Sector Expertise & Innovation, Mobilizing private sector financial resources, Provided Technical Assistance to the Local Private Sector, Other); * Public-private partnership (P-CC-148) * Geographic location (municipalities); *US Foreign Assistance objectives addressed Note: All required disaggregates must be reported in Monitor Justification/Utility for Indicator (optional): This is an Agency-wide cross-cutting indicator that applies to all sectors and standardized program areas. This indicator will be used to monitor implementation of the USAID PSE Policy, a finding from The Office of Inspector General’s Audit on the USAID PSE Policy. This indicator is linked to USAID’s Private Sector Engagement (PSE) Policy, the DOS-USAID Joint Strategic Plan, and USAID Country Development and Cooperation Strategies. It captures the breadth of private sector engagement to advance U.S. foreign assistance objectives. PLAN FOR DATA COLLECTION Data Source: Activity monitoring records Letters of intent, grant or subk/TA agreements will document the engagements with private sector. Project staff will track the number of letters of intent agreements issued, start and end dates. Method of Data Collection and Construction: Simple sum of current engagements at time of reporting. EF will have the information in its records about engagements that meet with the standard definition. These will include grant agreements, letters of intent and other partnership agreements with private financial service and education providers. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 12 Fiscal Year Targets: FY2023: 2 96 FY2024: 6 FY2025: 8 FY2026: 11 FY2027: 12 Rationale for Targets: Gradual intervention across years 1 to 5 reflecting level of effort, deployment of interventions and agreements with private sector enterprises Notes on baseline and targets: Not cumulative QUALITY DATA ISSUES Known Data Limitations: None identified Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): 2023 CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 97 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-CC-02: Value of Mobilized Funds [mission indicator – 40] Name of Development Objective: EF: Crosscutting CDCS: DO2 - Strengthened governance to meet citizen needs and increase citizen confidence in the state Shared IR 2/3.1 - Improved management of strategic assets for inclusive economic growth CDCS: DO3 - Promote equitable and environmentally sustainable economic growth CDCS: DO4 - Stability in areas impacted by migration from Venezuela Name of Intermediate Result: CDCS: IR 2.1 - Expanded state presence and more effective state systems to deliver community￾prioritized services Shared IR 2/3.1 - Improved management of strategic assets for inclusive economic growth CDCS: IR 3.2 - More competitive licit economies CDCS: IR 4.2 - Increased participation in licit economies Name of Development Objective: EF: Crosscutting CDCS: IR 2/3.1.3 - Expanded access to low cost renewable energy CDCS: IR 3.2.2 - Increased private sector investment and access to financial services CDCS: IR 4.2.2 - Private sector engagement efforts expanded to receptor communities Indicator Type: Mission indicator [40]/Outcome Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): This indicator adds the value of mobilized funds that contribute to USAID and Non-USAID strategies, development objectives or their intersection. Mobilized funds are resources enabled as a result of USAID efforts and invested by public and/or private third-party entities to achieve development objectives (to improve economic, social, institutional, and environmental conditions of individuals and communities). Through its work, USAID serves as a catalyst for unlocking these resources. Mobilization of funds requires a clear and explicit cause-effect relationship between USAID direct actions and the funds mobilized. Actions enabling these funds must have the concrete and intentional purpose to mobilize them. These actions include: building capacity (technical assistance and training); providing a grant; supporting regulation and fiscal policy; providing goods and services; developing assessments, information or data-based initiatives, technical studies and designs; and political lobbying. 98 Mobilized funds are different from leveraged and cost share funds, since they are enabled thanks to USAID efforts but not directly invested in co-funding USAID interventions. Mobilized funds can contribute to USAID and Non-USAID strategies, development objectives or their intersection. Mobilized funds do not include: • Economic monetary flows (sales and income), generated as a result of USAID interventions. • Resources generated by spillover effects and externalities that are indirectly caused by USAID interventions. These resources are not invested due to USAID’s direct interventions given that there is no concrete purpose from USAID to mobilize them. • Committed Funds: An administrative reservation of funds in anticipation of their obligation. There are cases in which the third-party funds invested for a development initiative were only possible because of USAID´s enabling intervention. In these cases, there is a high attribution from USAID in the whole funds invested on that specific development initiative. The total amount of the resources for that initiative should be considered as USAID mobilized funds. There are other cases in which the funds invested for a development initiative were possible because of USAID´s interventions along with the interventions from other stakeholders which also played a critical part in influencing the third party’s investment. In these cases, there is a partial attribution from USAID in the whole funds invested on that specific development initiative. The USAID mobilized funds for that initiative should correspond to a proportion of the total resources invested by the third party in that specific development initiative. Estimations should be developed for calculating this proportion. Resources must be reported only when there is a legally binding document, signed by the legal representative of the third party, that creates a definite commitment to invest the resources. This type of commitment would be equivalent to a USAID Obligation of funds. Each type of third-party partner will have different processes and means of verification for this type of commitment. Unit of Measure: USD Million and equivalent Colombian Peso (COP) at an exchange rate of 3500 COP per USD Simple sum. Data Type: Currency Disaggregated by: * Resources Origin and type: (Private- cash, Private- in kind, Public- cash, Public- in kind, Civil society-cash, civil society- in kind) - Adds to the indicator; * Geographic location (municipalities) Note: All required disaggregates must be reported in Monitor Justification/Utility for Indicator (optional): This indicator contributes to measure the catalytic effect of USAID/Colombia for unlocking the resources of other development actors. USAID, implementing partners, Governments, and Development Community may track more concretely the maximized effect of USAID assistance. PLAN FOR DATA COLLECTION Data Source: Activity monitoring reports. EF will provide the basic parameters of the indicator to the partners for them to generate reports for EF based on primary data they collect. Partners will have data in their core management information systems (MIS) about fund mobilized. EF will work with partners to create a routine to export the data from their MIS and share with EF. That information will be shared according to habeas data rules. Method of Data Collection and Construction: 99 EF will gather and keep record or supportive evidence of sources to account for the reported resources. In-kind resources must be converted to currency values by equivalent current market values of using the respective goods/services, instead of owing them. The monetization process must consider the commercial value of the good or service contributed as well as the depreciation of goods. Reporting Frequency: Quarterly. Only obligated funds into the reporting time frame count toward the indicator. Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 550 Fiscal Year Targets: FY2023: 0 FY2024: 50 FY2025: 150 FY2026: 200 FY2027: 150 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following agreements with private sector firms to receive technical assistance and allocation of resources. Agreements with financial service providers will be reached starting at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Financial institutions sometimes register transactions based on the branch location where the transaction was formalized and disbursed and not the location of clients to whom the funds are provided. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 100 PERFORMANCE INDICATOR REFERENCE SHEET (PIRS) Name of Indicator: EF-CC-03: Value of Leveraged Funds [mission indicator – 156] Name of Development Objective: EF: Crosscutting CDCS: CC - Cross-cutting Name of Intermediate Result: CDCS: Engagement and partnerships - Engagement and partnerships Name of Development Objective: EF: Crosscutting CDCS: CC - Cross-cutting Indicator Type: mission indicator – 156/Outcome Is this a PPR Indicator? TBD DESCRIPTION Precise Definition(s): Leveraged Funds are all resources from public, private and civil society organizations to co-fund or co-invest on common development USAID interventions (development policy, plan, program, pilot, project or activity), even if the funds are not directly transferred to the Implementing Partner. Leveraged Funds do not include the economic flows generated in part or fully as a result of these interventions, for example: benefits such as sales of goods and services. Leveraged Funds must meet the following criteria to each common intervention with USAID: • (i) invested to achieve the same objectives; and, • (ii) within the same timeframe of the intervention co-founded or co-invested To count, Leveraged Funds must be obligated by the Third Party, therefore these do not include funds that are still in an allocated or committed stage. Leveraged Funds must be executed by the Third Party or entity acting on its behalf by transferring them to the Implementing Partner, designated legal entity or funding vehicle, or by shared execution of Activities between the third party and USAID or the Implementing Partner. Therefore, the Third Party and USAID share responsibilities in the execution and risks of the endeavor. Unit of Measure: USD Million and equivalent Colombian Peso (COP) at an exchange rate of 3500 COP per USD Data Type: Currency (USD, COP, Other) Disaggregated by: *Resources Origin and type: (Private- cash, Private- in kind, Public- cash, Public- in kind, Civil society-cash, civil society- in kind) - Adds to the indicator; * Geographic location (municipalities); Note: All required disaggregates must be reported in Monitor 101 Justification/Utility for Indicator (optional): This indicator contributes to measure the catalytic effect of USAID/Colombia for unlocking the resources of other development actors. USAID, Implementing Partners, Governments, and Development Community may track more concretely the maximized effect of USAID assistance. PLAN FOR DATA COLLECTION Data Source: Digital or hard copy official statements, communications, plans or databases from the Third Parties that are publicly available or were provided privately by individuals with the authority to communicate or disclose this information. Method of Data Collection and Construction: EF will gather and keep records or supportive evidence to account for the reported resources. In￾kind resources must be converted to currency values using the equivalent current market values of the respective goods/services. Reporting Frequency: Quarterly. Only obligated funds into the reporting time frame count toward the indicator. Individual(s) Responsible at USAID: COR Individual(s) Responsible at Implementing Partner: MEL Manager TARGETS AND BASELINE Baseline value: 0 Baseline Timeframe: Dec 2022 Life of Project Target (LOP): 5 Fiscal Year Targets: FY2023:0 FY2024: 0.5 FY2025: 1 FY2026: 2.5 FY2027: 1 Rationale for Targets: Gradual intervention across years 2 to 5 with a peak in year 4 reflecting level of effort, deployment of interventions following implementation of grants under the AGIL fund. The first grants will be awarded at the end of year 1. Notes on baseline and targets: QUALITY DATA ISSUES Known Data Limitations: Time offset between issuance or collection of supportive documentation and obligation of reported funds. Some leveraged funds may be at the institutional level and not allocated to specific municipalities where the program operates. Date of Previous Data Quality Assessment (DQA): TBD Date of Future Data Quality Assessment (DQA): TBD 102 CHANGES TO INDICATOR This PIRS was last updated 03/13/2023by (DAI MEL Specialist) 103 Context Indicator Reference Sheet Name of Context Indicator: EF-CX-01 Interest rate (including real interest rate, and inflation rate) Name of Relevant Result(s) (Goal, DO, IR, sub-IR, Project Purpose, Project Output, etc.): Objective 2: Increased provision of financial services in target communities. DESCRIPTION Precise Definition(s): Interest rate: or “nominal interest rate” is a charge for borrowed money generally a percentage of the amount borrowed Real interest rate: an interest rate that has been adjusted to remove the effects of inflation. Once adjusted, it reflects the real cost of funds to a borrower and the real yield to a lender or to an investor. The real interest rates are used to compare interest rates across different macroeconomies and to distinguish the effects of inflation on nominal interest rates. Inflation rate: a rise in prices, which can be translated as the decline of purchasing power over time. The rate at which purchasing power drops can be reflected in the average price increase of a basket of selected goods and services over some period of time, usually expressed as an annualized percentage Unit of Measure: Rate Data Type: Percent Disaggregated by: (Nominal) interest rate; Real interest rate. Rationale for the Context Indicator (how it will be used by the Mission): When interest rates are rising, both businesses and consumers will be less able to access certain financial services PLAN FOR DATA COLLECTION Data Source: Central Bank – Banco de la Republica Method of Data Collection and Construction: Obtained through secondary sources Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR TRIGGER AND BASELINE Baseline Timeframe: Q4 CY2022 Trigger: 5% change over the baseline Rationale for Trigger: An interest rate that increases 5% or more over the baseline would have negative implications in financial system actors to lend and borrow money. Particular effects could be triggered in MSME. 104 DATA QUALITY Known Data Limitations: None. CHANGES TO CONTEXT INDICATOR Changes to Indicator: None Other Notes: THIS SHEET LAST UPDATED ON: 12/23/2022 105 Context Indicator Reference Sheet Name of Context Indicator: EF-CX-02 Change in Gross Domestic Product (GDP) Name of Relevant Result(s) (Goal, DO, IR, sub-IR, Project Purpose, Project Output, etc.): Objective 2: Increased provision of financial services in target communities. DESCRIPTION Precise Definition(s): GDP: measures the monetary value of final goods and services—that is, those that are bought by the final user— produced in a country in a given period of time (say a quarter or a year). It counts all of the output generated within the borders of a country. Unit of Measure: Percent Data Type: Percent Disaggregated by: None Rationale for the Context Indicator (how it will be used by the Mission): The growth rate of real GDP is often used as an indicator of the general health of the economy. In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well. Conversely, a slowing in GDP growth or a decline may indicate a worsening economy for EF’s target population. PLAN FOR DATA COLLECTION Data Source: DANE Method of Data Collection and Construction: Obtain from secondary sources. Reporting Frequency: Annually Individual(s) Responsible at USAID: COR TRIGGER AND BASELINE Baseline Timeframe: November 2022 Trigger: Below 0 Rationale for Trigger: Negative growth in a year can be due to a decline in wage growth and a contraction of the money supply signaling a possible recession or depression with effects in the overall strategy of EF. DATA QUALITY Known Data Limitations: None. CHANGES TO CONTEXT INDICATOR Changes to Indicator: None Other Notes: THIS SHEET LAST UPDATED ON: 12/23/2022 106 Context Indicator Reference Sheet Name of Context Indicator: EF-CX-03 Number of hectares of coca cultivation Name of Relevant Result(s) (Goal, DO, IR, sub-IR, Project Purpose, Project Output, etc.): Goal: To improve the supply and demand of formal financial services in rural, underserved, and conflict regions, and mobilize long-term capital for USAID/Colombia’s programming DESCRIPTION Precise Definition(s): Hectares: a metric unit of square measure, equal to 100 acres Coca production: Colombia is the world’s largest producer of cocaine. In 2021, the area of coca cultivation expanded to 204,000 hectares (504,100 acres). (UNODC) Unit of Measure: Number of hectares Data Type: Integer Disaggregated by: Location Rationale for the Context Indicator (how it will be used by the Mission): Coca cultivation is a proxy indicator for security PLAN FOR DATA COLLECTION Data Source: UNODC Method of Data Collection and Construction: Reporting Frequency: Annually Individual(s) Responsible at USAID: COR TRIGGER AND BASELINE Baseline Timeframe: 2021 Trigger: Increase more than 10% Rationale for Trigger: An increase in more than 10% in the number of coca hectares has negative implications in terms of cocaine production, illicit trade, territorial control and instability that affects the normal operation of markets in EF’s targeted geography. This indicator is a proxy for security as an increase in instability due to coca production may limit operations for financial institutions. DATA QUALITY Known Data Limitations: This is a proxy indicator to determine levels of insecurity. There is an assumption that there is a correlation. CHANGES TO CONTEXT INDICATOR Changes to Indicator: None Other Notes: THIS SHEET LAST UPDATED ON: 12/23/2022 107 Context Indicator Reference Sheet Name of Context Indicator: EF-CX-04 Average precipitation in depth (mm per year) Name of Relevant Result(s) (Goal, DO, IR, sub-IR, Project Purpose, Project Output, etc.): Objective 2: Increased provision of financial services in target communities. DESCRIPTION Precise Definition(s): Average precipitation is the long-term average in depth (over space and time) of annual precipitation in the country. Precipitation is defined as any kind of water that falls from clouds as a liquid or a solid. Unit of Measure: Millimeter (mm) per year Data Type: Integer Disaggregated by: Location Rationale for the Context Indicator (how it will be used by the Mission): The indicator will be used to monitor rainfall conditions to inform agricultural productivity expectations. Since agriculture is a major form of income in EF target geography, agricultural production could impact ability to access financial services or could impact the ability of farmers to meet their obligations with financial entities. PLAN FOR DATA COLLECTION Data Source: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. Method of Data Collection and Construction: Questionnaire Reporting Frequency: Annual Individual(s) Responsible at USAID: COR TRIGGER AND BASELINE Baseline Timeframe: 2021 Trigger: 10% change over the baseline. Rationale for Trigger: Agricultural experts state that a 10% change would likely drastically affect crop yields – triggering a reexamination of end-of-project targets. DATA QUALITY Known Data Limitations: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) through annual questionnaires. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. CHANGES TO CONTEXT INDICATOR Changes to Indicator: None Other Notes: THIS SHEET LAST UPDATED ON: 12/23/2022 108 Context Indicator Reference Sheet Name of Context Indicator: EF-CX-05 Microcredit Portfolio Quality (Arrears) Name of Relevant Result(s) (Goal, DO, IR, sub-IR, Project Purpose, Project Output, etc.): Objective 2: Increased provision of financial services in target communities DESCRIPTION Precise Definition(s): Microcredit is defined under Colombia law, amended from time to time. Arrears: money that is owed and should have been paid earlier. It is usually calculated as a percentage of past due principal payments of all outstanding principal payments. Unit of Measure: Percent Data Type: Percent Disaggregated by: None Rationale for the Context Indicator (how it will be used by the Mission): Microcredit loan portfolio quality is critical as it serves to identify if the sector overall is improving or getting worse in terms of portfolio quality as that may affect growth. If arrears are rising overall lending may be constrained and therefore may affect partners’ lending and EF’s ability to hit targets. PLAN FOR DATA COLLECTION Data Source: Superintendencia Financiera de Colombia Method of Data Collection and Construction: Secondary Reporting Frequency: Quarterly Individual(s) Responsible at USAID: COR TRIGGER AND BASELINE Baseline Timeframe: September 2022 Trigger: 3% increase over the baseline Rationale for Trigger: A worsening of the quality of the loan portfolio may constraint partner’s lending negatively affecting EF’s targets. DATA QUALITY Known Data Limitations: CHANGES TO CONTEXT INDICATOR Changes to Indicator: None Other Notes: THIS SHEET LAST UPDATED ON: 12/23/2022 109 ANNEX A: BENEFICIARY FEEDBACK PLAN EF will continually collect feedback from all stakeholders, including partners and communities, to ensure interventions are going as planned, are implemented with high quality standards, and are contributing to outcomes and ultimately leading to the EF objectives. Feedback will complement data collected through other MEL activities and will be captured using the following methods. Exhibit 7. Beneficiary Feedback Mechanisms Type Description Timeline Pre- and Post￾Training/ Workshop Surveys For any training/workshops sponsored by the activity, EF will administer pre- and post-training/workshop questionnaires to capture beneficiaries’ change in knowledge acquisition, as well as their perceptions of the training. EF will use this feedback to inform revisions to trainings/workshops and enhance their quality and effectiveness. Questions will include, but not be limited to, usefulness of content, anticipated utilization of information learned, level of satisfaction with accessibility, format, and timing of training. Aligned with training/workshop schedule Financial Diaries Using the AGIL fund, information will be gathered and recorded through financial diaries on economic behaviors and digital services needs of underserved population segments – both individuals and MSMEs. Data collected through the diaries will ensure that priorities of underserved populations are understood and incorporated into activities. More importantly, this detailed information will be analyzed and shared with policy makers of relevant GOC counterparts to promote policy improvement and the development of more appropriate tools to achieve financial inclusion in remote rural areas. Continuous, collected and analyzed quarterly Key Informant Interviews (KIIs) EF will identify and interview key stakeholders who are well-placed to provide feedback on particular interventions and/or can serve as examples for possible success stories. This will include collecting feedback from women and vulnerable groups to ensure their priorities are incorporated into activities. Specific questions will be developed for different categories of participants, however, general categories of questions will include: satisfaction of activities/support provided, suggestions for how to improve activities/support provided, successes and challenges faced, perceptions of improvements as a result of participation/support provided, broader changes seen as a result of participation support provided. Annually Applying a learning lens to beneficiary feedback, the activity will use feedback to inform ongoing planning and implementation. For any noteworthy feedback, either positive or negative, the EF MEL team will follow-up where needed to ensure there is sufficient information to respond. The Activity will report beneficiary feedback to USAID via meetings (such as P&R sessions), periodic reports, and success stories. For ethics or compliance issues, DAI has an anonymous hotline and an email address. Reports will be reviewed and responded to appropriately to protect the identity of the stakeholder.