SUBMITTED TO: AOR, USAID/GHANA P.O. Box 1630 Accra, Ghana packah@usaid.gov SUBMITTED BY: ACDI/VOCA Chief of Party #1 Tripoli Street, East Legon Accra, Ghana edormon@acdivocaghana.org WITH: Association of Church Development Projects (ACDEP) Revised July, 2019 This PMP covers activities under USAID Cooperative Agreement No. AID-641-A-14- 00001 Agricultural Development and Value Chain Enhancement Monitoring, Evaluation and Learning (MEL) Plan 1 CONTENTS INTRODUCTION TO THE PROJECT................................................................................................................. 3 ADAPTIVE MANAGEMENT .............................................................................................................................. 5 CRITICAL FUNCTIONS OF THE PERFORMANCE MONITORING, EVALUATION & LEARNING SYSTEM.......... 5 OPERATIONAL CONTEXT AND UNDERLYING CAUSALITY FRAMEWORKS................................................... 5 PROJECT GOALS AND OBJECTIVES .............................................................................................................. 6 TIMELY PROJECT MONITORING ................................................................................................................... 6 MONITORING AND EVALUATION...................................................................................................................... 6 Data Management System............................................................................................................................ 7 Data collection:.............................................................................................................................................. 7 Data storage and analysis:......................................................................................................................... 7 Quality control:.......................................................................................................................................... 7 Reporting, use, and sharing:...................................................................................................................... 8 Collaboration with Donors and Stakeholders ........................................................................................... 8 KNOWLEDGE MANAGEMENT AND LEARNING.............................................................................................. 14 ADVANCE II KM&L goals and objectives.................................................................................................. 14 Guiding principles for KM&L.................................................................................................................... 15 Project roles and responsibilities ............................................................................................................ 16 Staffing and Management....................................................................................................................... 16 DATA QUALITY REVIEWS............................................................................................................................ 18 EVALUATION APPROACH AND ASSESSMENTS .......................................................................................... 18 Final Evaluation..................................................................................................................................... 18 Annual Surveys ..................................................................................................................................... 18 Sampling Method and Size ................................................................................................................. 19 RISKS AND ASSUMPTIONS.......................................................................................................................... 19 Annex 1: FY targets.......................................................................................................................................... 21 Annex 3: Performance Indicator Reference Sheets ........................................................................................ 23 Annex 4: Implementation plan for MEL activities - May 2019 to April 2020 .................................................. 53 2 ACRONYMS ADVANCE II CLA Agricultural Development and Value Chain Enhancement Collaborating, Learning and Adapting CIP CAADP COP Country Investment Plan Comprehensive Africa Agriculture Development Program Chief of Party DCOP Deputy Chief of Party FTF GOG ICT IR ISSER Feed the Future Government of Ghana Information and Communication Technology Intermediate Result Institute for Statistical, Social and Economic Research KM Knowledge Management MEL Monitoring, Evaluation and Learning METSS Monitoring and Evaluation Technical Support Services MoFA Ministry of Food and Agriculture NF PMP Nucleus Farmer Performance Monitoring Plan OB Outgrower business RF TOC WEAI Results Framework (RF) Theory of Change Women's Empowerment in Agriculture Index (WEAI) 3 INTRODUCTION TO THE PROJECT The USAID Agricultural Development and Value Chain Enhancement Feed the Future Activity (ADVANCE II) was awarded to ACDI/VOCA on February 5, 2014 under Cooperative Agreement No. AID-641-A-14-0001. The cost extension phase from May 1, 2019 to April 30, 2020 will enable the project to fully implement and report on results for the 2019 crop season. ADVANCE II contributes to the intermediate results of USAID’s FTF guided by the Global Food Security Strategy (GFSS) Strategic Objective 1 (Inclusive and sustainable agricultural- led economic growth) and Strategic Objective 2 (Strengthened resilience among people and systems). The overall goal of ADVANCE II during the cost extension phase is to achieve sustainable, resilient and inclusive markets for the maize and soybean value chains. The intermediate results are; (i) increased productivity in targeted commodities (maize and soy), (ii) increased market access and trade, and (iii) Strengthened capacity for advocacy and activity implementation (see details in the results framework, Figure 1). The project will focus on behavior change that will ensure that the gains in productivity, formal trade and marketing of maize and soybean are sustained. The project will achieve the desired change by strengthening the outgrower businesses (OBs) and their networks to build trust and engage with the major buyers and processors on a more long-term basis, rather than on an annual/seasonal basis. The project will also continue to ensure that women have equitable access to all project resources, and it will be enhanced through an additional focus on women and youth engagement. The ADVANCE II Monitoring, Evaluation and Learning (MEL) Plan combines the Performance Monitoring Plan (PMP) and the Knowledge Management and Learning (KM&L) Plan into a single guidance document that describes the staff and the details of how the project will establish and implement a system to monitor project activities, collect data, analyze, evaluate, and report on the results to USAID. The MEL Plan details ADVANCE II’s approach to promoting a learning culture and a monitoring and evaluation (M&E) system that promotes project, facilitates evidence-based decision making, sparks innovation and ADVANCE IIs critical information to project management in the given context. The MEL Plan also includes our approach to information and spatial data management and utilization of technology relevant to M&E and lays out the organizational structure (both personnel and workflow) for implementing the project’s M&E system. 4 Figure 1: ADVANCE II Results Framework Critical Assumptions • Coordination With USAID and Non-USAID Programs •Supportive Enabling Environment • Market Demand • OBs, Farmers, Private sector, GOG and other stakeholders as Facilitator of Change Outcomes IR 1.1 • Strengthened systems for service provision and input distribution • Increased adoption of improved technology and productivity-enhancing technologies, • Yield per hectare for maize and soy. Outcomes IR 1.2 • Increased availability and use of Affordable/sustainable services • Improved capacity of women and men to participate in markets • Increased private investment to support value chain development Expanded benefits from market Participation for women and men Outcomes IR 1.3 • Strengthened advocacy capacity of VC actors to address enabling Environment constraints • Strengthened capacity to Implement VC development. Output IR 1.1 • Number of individuals participating in USG food security program • Number of individuals who have applied improved technologies or management practices with USG assistance • Number of additional hectares under improved technologies and management practices. Output IR 1.2 • Value of annual sales of farms and firms receiving USG assistance • Value of agriculture-related financing accessed as a result of USG assistance •Number of value chain actors accessing Finance • Number of individuals participating in group￾based savings, micro-finance or lending programs with USG assistance Output IR 1.3 • Number of organizations with increased performance improvement with USG assistance •Score, in percent, of combined key areas of organization capacity amongst OBs Illustrative Activities IR 1.1: • Assess OB network’ capacity gaps to operate as full business entities without external support • Develop capacity building plan and train OB networks to address gaps • Support the OB networks to develop long￾term plans • Organize review meetings with OBs’ field agents to assess their capacity, extent of implementation of the OBs’ 2018 plans, progress, challenges, successes and lesson learned • Organize capacity building training for OBs’ field agents on identified gaps and on participatory M&E, and basic business analysis • Support OBs who have set up offices to improve their business and management skills • Assist OB networks to partner input dealers to conduct actor-led field demonstrations to train smallholder farmers. • Strengthen linkages between local input dealers, CIAs, OBs and SSPs to expand input distribution Illustrative Activities IR 1.2: • Build OB networks’ capacity in finance, governance and advocacy • Support buyers, OB networks and OBs to invest in produce certification and labelling • Support buyers, OB networks and OBs to invest in a product traceability scheme • Link OBs and their networks to the commodity exchange Illustrative Activities IR 1.3: • Assess capacity of value chain actors to identify gaps in reaching sustainable behavior change • Facilitate working relations between MOFA and OB networks to participate actively in government agricultural programs • Support OB networks to assess their performance against set targets quarterly • Train OB networks on the concept of total quality management (TQM) and support them to implement same • Continue to support zonal OB networks to identify specific advocacy issues and develop advocacy plans to address them • Support OBs networks to create awareness among themselves and their communities about women access to productive farm land • Support OB networks to develop and implement participatory M&E systems Government of Ghana Goal: Sustainably reduce hunger, malnutrition and poverty ADVANCE II Goal: Sustainable, resilient and inclusive markets Intermediate Result 1.1 Increased productivity in targeted commodities (maize and Soy) Intermediate Result 1.2 Increased Market Access and Trade Intermediate Result 1.3 Strengthened capacity for advocacy and activity implementation Cross Cutting Illustrative Activities Outputs Outcomes Cross-cutting Gender: Equitable access to resources and capacity building along target value chains. • Women’s Empowerment in Agriculture Index • Proportion of female participants assisted to increase access to productive economic resources Youth: Youth engaged in agricultural value chains and entrepreneurial activities Environment and Climate Change: Conservation agriculture and climate change techniques promoted Child Labor: Sensitization activities with staff and capacity building modules for local resource partners Objective 1 Inclusive and sustainable agricultural led economic growth Objective 2 Strengthened resilience among people and systems 5 THEORY OF CHANGE For ADVANCE II, the theory of change posits that there are three functions of sustainable, resilience and inclusiveness markets namely - agricultural productivity, market access and trade and strong local capacity of networks and groups to advocate and implement activities. Underpinning the theory is that networks, groups and private sector actors including men, women and youth farmers, are the drivers of sustainability and resilience, while the government of Ghana (GOG) and local stakeholders all as facilitators, catalyzed through the project’s capacity building, learning and investment, and innovation promotion. It is within this framework that the ADVANCE II technical approach has been designed. ADAPTIVE MANAGEMENT Recognizing the complexity of increasing productivity and incomes of smallholders and other actors along the value chain, improving market access, and strengthening capacity of local organizations, the M&E system is structured around a data collection and analysis cycle that also establishes a learning environment for the project. In addition to indicator data, topic-specific questions devised to contribute to a broader program “learning agenda” are articulated; and the methods for obtaining data, individuals responsible, dates, and products anticipated are identified. The project team will use information collected to adapt both our actions and the conceptual framework of the project as needed. The learning agenda goes hand in hand with our normal indicator monitoring and evaluation of methodologies for effectiveness and efficiency. Feedback to and dialogue among beneficiaries, managers, partners, and decision-makers (USAID and the relevant GOG agencies such as MoFA) is a central component and learning review will be held among key actors so that everyone has the opportunity to continuously examine results and learn from the project’s experience. CRITICAL FUNCTIONS OF THE PERFORMANCE MONITORING, EVALUATION & LEARNING SYSTEM This M&E system is set up to fulfill the following functions: • Document evidence relating to reach, coverage and results. • Provide accurate measurement of achievement toward project objectives. • Ensure the quality of data collected and analyzed (providing analytical data necessary to influence sector assistance). • Identify potential problems at early stages so that stakeholders can use data in a timely manner to guide programmatic decisions. • Monitor the accessibility of project interventions and benefits to all sectors of the target population especially to smallholders, women, and other value chain actors. • Improve the overall project strategy through continuous knowledge sharing and learning, considering the views of beneficiaries and other stakeholders and testing evidence of impact. • Document and disseminate achievements and learning; providing to management a learning tool that allows stakeholders to analyze progress, evaluate results and quickly adapt activities as needed. OPERATIONAL CONTEXT AND UNDERLYING CAUSALITY FRAMEWORKS The ADVANCE II MEL system is being established by carefully examining the context of Ghana’s overall agricultural sector development policy and the USAID Ghana mission’s FTF program and the global food security strategy (GFSS) to ensure optimal system performance. 6 The MEL system has been designed to ensure compliance and compatibility with critical policies and projects including, the Comprehensive Africa Agriculture Development Program (CAADP) and the Ministry of Food and Agriculture’s Ghana Agriculture Sector Investment Project (GASIP). Other strategies, policies, and initiatives considered in designing this MEL plan include: • GFSS, the USA Government's global food security strategy • USAID Evaluation Polic • USAID Ghana, Feed the Future Strategy, Monitoring and Evaluation Plan Progress against the p r o j e c t objectives is measured based on the project Results Framework and accompanied by standard FTF performance indicators as updated in August 2018. PROJECT GOALS AND OBJECTIVES The purpose of the ADVANCE II project is to improve the competitiveness of the maize and soybean value chains in northern Ghana. ADVANCE II will achieve this purpose through three sub-purposes: Sub-purpose 1 - Increased agricultural productivity of targeted commodities Sub-purpose 2 - Increased market access and trade of targeted commodities Sub-purpose 3 - Strengthen capacity for advocacy and activity implementation ACDI/VOCA’s development hypothesis to achieve the project purpose is that scaling up of strategic investments in targeted value chains that incentivize innovation and investment, while mitigating risks, will lead to improved competitiveness of the value chains and increase incomes for male and female smallholders. Increased spending and investment on the part of male and female farmers and other value chain actors will multiply new opportunities both inside and outside of agriculture, offering the poor expanded opportunities in the rural non-farm sector and lead to reductions in poverty levels. Details of outcomes, outputs and indicators to track progress are presented in the results framework (see FIGURE 1) MONITORING AND EVALUATION During the cost extension phase, ADVANCE II will adopt a monitoring and evaluation system that will sustainably empower private sector partners, while complying with USAID and ACDI/VOCA’s data quality requirements. It will rely on the ACDI/VOCA market-system-oriented M&E approach and will have the following key pillars: • Facilitative approach: While previously, USAID’s ADVANCE II project mostly collected routine monitoring data directly from the smallholders; during this extension phase, the OB networks and the OBs will take over that responsibility towards an effort to increase their understanding, ownership, and utilization TIMELY PROJECT MONITORING The project team will conduct routine monitoring in order to quantify what has been done; when, where, and how it has been done; and who has been reached. While monitoring is a routine process, staff will also capture the non-routine—behaviors and changes that were not expected (positive and negative deviations)—to analyze their importance. Our field teams will work consistently with key stakeholders to monitor and assess whether activities are being implemented according to schedule; identify what problems, if any, arise during implementation; determine which components of the program are or are not working; and obtain information on the stakeholders’ reactions to the project. This information will routinely be fed back into project planning to ensure adaptive management of project activities and to adjust the causal model if needed. 7 of data for their business management. Therefor they will have a crucial and active role in the project M&E data collection and management process. • Tailored capacity building: To support the networks and OBs to fulfill the responsibility outlined above, the project will develop data management tools tailored to the OBs’ and the networks’ constraints and abilities. The project will also train the networks, the OBs, and their field agents as well as provide constant mentoring and feedback. • Win-win strategy: The data collected by the OB networks will not only be of interest to the project to compliantly track its progress, but also mostly beneficial to the networks and OBs to accurately and timely monitor the state of their businesses. For that purpose, the data collection forms will be short and designed with the networks and the OBs. The data management system will protect data confidentiality and integrity and reinforce the trust that the networks and OBs have in the project. • ICT powered and built off past experience: As described below, the project will select the most user￾friendly ICT based business intelligence tools, combined with offline and online mobile data collection and analysis capabilities. In doing so, the project will take lessons with and for the OBs from our experiences over the years in setting up software and data management processes. • Social inclusion tracking: USAID’s ADVANCE II project will continue to monitor how women and youth participants are affected by, involved in, and benefitting from the project interventions and ecosystem through relevant indicators and learning studies. Data Management System From data collection to its use and reporting, our data management system will ensure that data is reliable, valid, precise, integer and timely. The project has developed quick response code (QR code) to facilitate data collection by outgrower businesses on their services to smallholder farmers. Data collection: Data will be collected both routinely and through surveys. The routine data, such as the OBs service provision to smallholders and sales to buyers will be collected by the OBs through simple forms stored in the OBs’ tablets and android phones. ACDI/VOCA will lead the collection of the survey data which will mostly be on technology application (including climate smart technologies), maize and soy yields, as well as behavior change and sales by the buyers and the input dealers, and the prospects of sustainability of the project’s achievements. The project will set up measures to ensure that data collected will be of satisfactory quality, including minimizing missing data issues, drop down lists, skip features amongst many others. Data storage and analysis: The data collected will be pushed from the mobile devices to the ACDI/VOCA server where it will be automatically processed into live, interactive, user-friendly dashboards. The project will create a set of dashboards to address the project’s M&E data needs. In addition, each network and each OB will have their own dashboards designed with them and accessible from their tablets through a simple button. For that purpose, the project will use the ACDI/VOCA’s Learning, Evaluation, and Analysis Platform (LEAP) combined with Microsoft PowerBi. Quality control: The project’s M&E staff will regularly conduct spot checks to ascertain the quality of the data being collected by the networks. The team will visit each network and their OBs at least twice during the cost extension phase. 8 Figure 2: ODK data collection process Reporting, use, and sharing: The project will submit quarterly and annual reports to USAID as per the schedule in the amended cooperative agreement. Furthermore, we will use the data to inform our decisions on the project’s daily management and on any need to refine our approaches. We will also reinforce the capacity of the networks and OBs to properly understand, navigate and use the data from the dashboards in order to better manage their businesses. We will share the data with USAID after removal of any identifiable information as per the ADS 579. Reporting timeline: • Quarterly Reports: end of January, April and July • Annual Report: end of October • Final project Report: within 90 days of the end of the cooperative agreement Collaboration with Donors and Stakeholders The ADVANCE II project prioritizes coordination with USAID, the Monitoring, Evaluation and Technical Support Services (METSS) Project, other implementing organizations under the Ghana mission’s FTF program and stakeholders to maximize cost effectiveness of data collection, ensure use of existing information, and as much as possible avoid duplication of results tracking. We will continue to work with existing institutions and programs including, but not limited to, MoFA and IFPRI to share data and information. In addition, the project team will conduct meetings with other stakeholders and implementing organizations to share and coordinate data collection to avoid duplicating efforts. In addition, the COP and Monitoring, Evaluation and Learning (MEL) Specialist will produce and share results of technical reports, success stories, lessons learned and other learning documents. Final Report: A final report will be submitted within 90 days of the cooperative agreement termination. Drawing from various studies and reports over the years, the final report will highlight major successes during the agreement period and discuss any shortcomings and difficulties encountered. It will also outline lessons learned and make recommendations for follow-on activities in the future. 9 Table 1: ADVANCE II Revised Performance Monitoring Plan # Sour ce Performance Indicators Definition and unit of Measure Data collection method & Source Disaggregation Frequency of Data Collection LOP Target Indicator Key: I: Impact Indicator OC: Outcome Indicator OP: Output Indicator FTF: Feed the Future indicator CI: ADVANCE II Custom Indicator Goal : Increased the competitiveness of agricultural Value chains in Ghana OP1 FTF Number of individuals participating in USG food security programs Definition: This indicator counts participants of Feed the Future-funded programs, including those we reach directly, those reached as part of a deliberate service strategy, and those participating in the markets we strengthen. . This indicator counts, with some exceptions listed below, all the individuals participating in agriculture and food system activities, including: • Adults that projects or project-supported actors reach directly. • Smallholder and non-smallholder producers that projects or project-supported actors reach directly. • Proprietors of firms in the private sector that the project help strengthen (e.g. agro dealers, aggregators, processors), but not all the employees of those firms; • Producers who directly interact with those USG￾assisted firms (e.g. the producers who are customers of an assisted agro-dealer; the producers from whom an assisted trader or aggregator buys), but not customers or suppliers who are not producers; This indicator does not count the indirect beneficiaries of our activities. Unit of measure: Number (of people) Routine data collection and Surveys Sex Male, Female and Age: youth / adult Type of individual Producers SHF Non-SHF Smallholder =<5Ha Data recorded and reported quarterly NA IR 1.1 Increased productivity of targeted commodities OC1 FTF Yield of targeted agricultural commodities among program participants with USG assistance Definition: Yield is a measure of the total output of production of an agricultural commodity (crop) divided by the total number of units in production (hectares planted of crops), It is a measure of productivity from that farm activity from USG￾assisted producers. Unit of Measure: metric tons Census for firms and survey of a representativ e sample of SHF Commodity: Farm size: Smallholder, Non-smallholder Sex: Male, female Age: 18-29, 30+ Annually NA OC2 FTF Number of individuals in the agriculture system who have applied improved management Definition: This indicator measures the total number of agriculture system actors participating in the USG￾funded activity who have applied improved management practices and/or technologies promoted by the USG anywhere within the food and Census for firms and survey of a representativ Commodity Type of producer/firm (microenterprise, Firm - Small and medium enterprise Firm Large Sex Data recorded and reported annually NA 10 # Sour ce Performance Indicators Definition and unit of Measure Data collection method & Source Disaggregation Frequency of Data Collection LOP Target practices or technologies with USG assistance management practices agriculture system during the reporting year. These individuals can include: • Farmers and other primary sector producers of food crops, • Individuals in the private sector, such as entrepreneurs, input suppliers, traders, processors, manufacturers, distributors, service providers, and wholesalers and retailers; • Individuals in government, such as policy makers, extension workers and natural resource managers; • Individuals in civil society, such as researchers or academics and non-governmental and community organization staff. The indicator tracks those individuals who are changing their behavior while participating in USG￾funded activities. Individuals who attended training or were exposed to a new technology do not count under this indicator unless the individual actually applies what she/he learned. Unit of Measure: Number e sample of SHF OC3 FTF Number of hectares under improved technologies or management practices as a result of USG assistance Definition: This indicator measures the area (in hectares) of land under improved technology during the current reporting year. If a hectare is under more than one improved technology type [e.g. improved seed (crop genetics) and IPM (pest management)], count the hectare under each technology type (i.e. double count). Only Ha under technologies or practices promoted by ADVANCE II will be counted. Unit of Measure: Hectare Survey of a sample of targeted individuals; Project or association records, farm records Type of technology, Sex of farmers Seasonal, according to the crop cycle NA IR 1.2 Increased Market Access and Trade OC4 FTF Value of annual sales of farms and firms receiving USG assistance [IM-level] (USD) Definition: This indicator measures the value of the total amount of sales of products and services by USG-assisted farms and firms during the reporting year within USG-supported agricultural commodity value chains or markets. This indicator also collects additional data points on the value of sales, the number of activity participants, including the number of producers and the number of assisted private sector firms, and, if applicable, the volume of sales( tons) for agricultural commodities (i.e. seed; food, feed crops). Unit of Measure: US Dollar Survey Census for firms and Sample SHF Commodity Type of producer/firm (microenterprise, Firm - Small and medium enterprise Firm Large Sex Annually NA 11 # Sour ce Performance Indicators Definition and unit of Measure Data collection method & Source Disaggregation Frequency of Data Collection LOP Target OP2 FTF Value of agriculture-related financing accessed as a result of USG assistance [IM￾level] Definition This indicator sums the total value of debt (both cash and in-kind loans) and non-debt financing, such as equity financing, disbursed during the reporting year as a result of USG-assistance to producers (individual farmers, cooperatives, etc.), input suppliers, transporters, processors, other MSMEs, and larger enterprises that are in a targeted agricultural value chain and are participating in a USG-funded activity For cash loans, count only loans made by financial institutions and not by informal groups such as village savings and loan groups that are not formally registered as a financial institution. However, the loans counted can be made by any size of financial institution. Unit of Measure: US Dollar Financial institution and investor records and survey of activity of participants FIRST LEVEL Type of financing accessed Debt and Non- Debt SECOND LEVEL Type of debt: Cash, In-kind Size of recipient Sex of producer or proprietor(s): Male, female, mixed Age: 18-29, 30+, mixed Quarterly NA OP3 FTF Number of individuals participating in group-based savings, micro￾finance or lending programs This indicator tracks individual participation in group￾based savings, microfinance, or lending programs. This performance indicator, along with the similar ZOI indicator, tracks financial inclusion. Group-based savings programs are formal or informal community programs that serve as a mechanism for people in poor communities with otherwise limited access to financial services to pool their savings. Unit of Measure: Number Participant ants - based Survey Activity records Female, Male Youth: 15-29, 30+ Product: Type: Savings, Credit Quarterly Annually NA OP4 CI Number of value chain actors accessing finance Definition: Beneficiaries of loan or credits provided by VSLAs and financial institution for start-up business and/or business expansion. Examples of financial services for value chains actors include, but are not limited to, loans, savings schemes, and insurance plans obtained from: Private banks and Microfinance institutions. Unit of Measure: Number Records from Microfinance partners, microenterpri ses and VSLAs Type of actor and sex Annually 300 IR 1.3 Strengthened Local Capacity for Advocacy and Activity Implementation 12 # Sour ce Performance Indicators Definition and unit of Measure Data collection method & Source Disaggregation Frequency of Data Collection LOP Target OC5 FTF Number of organizations with increased performance improvement with USG assistance This indicator measures whether USG-funded capacity development efforts have led to improved organizational performance in organizations receiving organizational performance improvement support. Capacity is the ability of people, organizations and society as a whole to manage their affairs successfully. Capacity development is the process of unleashing, strengthening and maintaining such capacity. Capacity is a form of potential; it is not visible until it is used. Therefore, performance is the key consideration in determining whether capacity has changed. Unit of Measure: Number Survey (census) Type of organization: ● Research and educational ● Producer associations ● Extension organizations ● Private sector firms ● Government agencies ● Non-governmental and not-for profit organizations ● Other Annually NA OP5 FTF Percentage of female participants in USG -assisted programs designed to increase access to productive economic resources 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; • workforce development programs that have job placement activities Unit of Measure: percent expressed as a whole number Participant ants - based Survey Activity records None Quarterly Annually 20% OP6 FTF Percentage of participants in USG- assisted programs designed to increase access to productive economic resources that are youth 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: • value chain activities and market strengthening activities working with micro, small, and medium enterprises; • financial inclusion programs that result in increased access to finance, including programs designed to help youth set up savings accounts • workforce development programs that have job placement activities; • programs that build or secure access to physical assets such as land redistribution or titling; and programs that provide assets such as livestock This indicator does NOT track access to services, such as BDS or training. Unit of Measure: percent expressed as a whole number Participant ants - based Survey Activity records None Quarterly Annually 15% 13 The results framework (see Figure 1) illustrates how each activity contributes to the intermediate results, which in turn will lead to the achievement of increased competitiveness of agricultural value chains in northern Ghana. Our MEL system will track intermediate results to ensure the validity of the logic illustrated in the results framework. The Performance Monitoring Plan (PMP) lists the performance indicators by components and intermediate results that are both ambitious and realistic and which will enable the monitoring of progress towards increased competitiveness of the selected value chains in northern Ghana. For each indicator, the PMP includes the definition, type, source, collection method, and frequency of data as well as tentative annual targets (see Table 1). Further details on definitions and data collection methods are provided in the performance indicator reference sheets. As relevant, the indicators have been disaggregated by geographic region and value chain. Data will also be sex-disaggregated and in line with all the disaggregation levels required for FTF reporting. This level of disaggregation will enable ADVANCE II to thoroughly analyze data, outputs, outcomes and impacts. The PMP will be used by the project team and USAID to monitor progress towards expected targets and results. During the cost extension period we will also disaggregate by youth. The ADVANCE II team will ensure that the M&E activities are carried out in a manner that guarantees data reliability and validity. The project team will present USAID with quarterly achievements against indicator targets for review. Figure 3: ADVANCE II Data flow system 14 KNOWLEDGE MANAGEMENT AND LEARNING The ADVANCE II Knowledge Management and Learning (KM&L) strategy centers on a learning agenda which will operationalize internal learning and inform and guide the conceptual framework of the project. This agenda will be informed by and feed into the global Feed the Future (FTF) learning agenda but will be tailored to support local learning priorities. The learning agenda will facilitate discussion and learning, drive the collection of evidence and findings, improve project management and implementation, and contribute to USAID Ghana, Government of Ghana (GOG) and partners’ good practice in development. ACDI/VOCA defines KM&L to include all the processes and management tools that we use to gather, analyze and channel information into our decision making. This includes managing knowledge within a project as well as managing coordination among donors, implementers, and other sector stakeholders. The project’s theory of change (TOC) and results framework (RF) is the starting point in designing the M&E system, and the KM&L plan, and will guide the development of the ADVANCE II learning agenda. Based on a cycle of planning, implementation, monitoring, research, and re-examination of actions, the ADVANCE II KM&L system will incorporate: • Knowledge management to ensure lessons learned from ADVANCE II are documented and disseminated broadly within USAID, donor agencies and other FTF implementing partners. • Learning and adaptive management to continually adjust ADVANCE II activities to maximize impact while reaching scale, and to facilitate collaborative learning across Ghana development community to strengthen market system approaches. KM&L is interconnected with and highly complementary to monitoring and evaluation (M&E). M&E will not be effective without the managerial practices in place that create a supportive organizational culture of information sharing, learning and performance-driven decision making, which are provided by an effective KM&L system. KM&L findings will feed into the M&E system to assist in tracking progress in meeting the project’s goal and objectives and provide real-time information to enable evidence-based implementation. The project will seek to learn in three areas: 1. The effectiveness of the OB networks to identify business models for producer organizations in the face of new markets and business opportunities. 2. The opportunities and viable entry points for engagement and participation of women and youth in the maize and soybean value chains. 3. The effectiveness in the deployment of ICT and digital technology in the maize and soybean value chains by the project. ADVANCE II KM&L goals and objectives The goal of the ADVANCE II KM&L plan is to operationalize learning in a dynamic, evidence based system. Activities will contribute to the following objectives: 15 Objective 1: To capture learning within the project and the larger FTF community that contributes to improved implementation for value chain projects in Ghana and elsewhere Objective 2: To build the capacity of agricultural sector stakeholders in northern Ghana to effectively use information for a variety of purposes, including sharing information, learning, networking, advocacy, trade promotions, etc. As illustrated in Figure 4, the project will follow the principles of flexible, adaptive management by routinely and systematically using lessons learned in conjunction with data from the M&E system and KM&L efforts to drive the focus and scope of project activities. Guiding principles for KM&L ADVANCE II KM&L interventions will be guided by the following: Critical to project success: KM&L can stimulate effective decision making and problem solving, enable access to high quality information and allow experience to be stored and examined. From project start KM&L must be seen as intrinsic to successful project delivery, and not as an additional task that can be ticked off a checklist. The ADVANCE II M&E team and senior management will actively support knowledge management initiatives; will link them to the PMP; and will provide an environment that is favorable to knowledge sharing. Ongoing process: KM&L is not a one-time fix, but rather a holistic approach to making the most of organizational and sector knowledge. Activities will continue through the life of project, and a measure of success will be when external stakeholders who have experienced positive results from sharing information choose to continue activities without donor support. People centered process: KM&L systems are put in place to capture both explicit knowledge (data that are easily captured, measured and recorded) and tacit knowledge (things that are inherently known or learnt as a result of observations and experiences). While there are increasingly sophisticated tools to support this process, KM&L should remain centered on the people involved, with processes and technology playing supportive functions. Learning related to gender and youth Issues: The results of a gender study “impact assessment on women’s empowerment through the USAID ADVANCE II Project” conducted in June 2019 found that there is increased resilience and empowerment among women from food security and economic empowerment activities, particularly for those women that belong to village savings and loan associations (VLSAs). However, while the OB model has increased women’s access to services, there are multiple constraints women face in leadership positions in agriculture groups, as evidenced by the fact that most of those positions are held by men. The study also found that youth are playing an important role in advisory and extension services as Village level Agro-input Agent (VAAs) – providing information and inputs to male and female producers, although this role can be significantly scaled up. The project has included two indicators; FIGURE 4: ONGOING LEARNING AND ADAPTIVE MANAGEMENT 16 increased access to productive economic resources by women and for the youth. This will enable the project to track the effectiveness of project strategies to reach more youth and improve empowerment of women participants. Behavior change: People are happy to talk about the importance of sharing information, but in reality many are likely to not practice what they preach, either because they tend to hoard information, are suspicious of what they might learn from others, or are not willing to put in the effort to seek out what they do not know. ADVANCE II will seek out incentives to promote engagement in KM&L activities and will consider people’s busy schedules when designing activities in order to motivate them to collaborate and work together. Through collaboration and shared learning, participants will be encouraged to identify innovation drivers. KM&L will serve as a catalyst for innovation by building on existing knowledge. Project roles and responsibilities The monitoring, evaluation and learning system for ADVANCE II will be implemented by a team of well trained and experienced professionals who have the leadership skills and abilities to deliver the highest quality monitoring and evaluation practice. This team has a clear organizational structure, understands their roles, responsibilities, and reporting lines. To foster a results orientation and learning culture, inclusivity is critical in implementation of a monitoring and evaluation system; hence the entire project team will be sensitized to play their roles in tracking and managing project performance. Key areas will revolve around quality control, performance and monitoring for results and impact. Staffing and Management The M&E Team will be composed of the Monitoring, Evaluation and Learning (MEL) Manager and the Management Information System (MIS) specialist based in Accra, and an M&E Coordinator and three regional data clerks. The MEL Manager will be responsible for the overall data quality, coordination of the M&E system rollout and enforcement, and capacity building of project staff, OBs, and OB networks. The MIS Specialist will oversee the design and daily management of the database, the mobile data collection system, and the dashboards. The M&E Coordinator and data clerks will assure the implementation of the whole system in their respective regions. ACDI/VOCA Regional and Headquarters Support: The ADVANCE II MEL team will be supported by ACDI/VOCA headquarters’ M&E unit. The HQ team will periodically review the MEL system and assist the team where necessary. ACDI/VOCA headquarters’ information systems unit will also support the ADVANCE II team to design and manage an MIS database. Team members will be able to tap into ACDI/VOCA’s M&E and communities of practice to access capacity building tools and share lessons learned and best practices with colleagues around the world. RESPONSIBLE PERSONS M&E function is the responsibility of the entire project team - everyone has a role to play. However, as the prime partner, ACDI/VOCA is responsible for coordinating all project M&E activities and producing and using meaningful analyses of aggregated and disaggregated data; the COP and MEL Specialist will be the main points of contact with USAID on M&E issues. 17 Table 2: MEL staffing plan Position Office Responsibilities MEL Specialist Accra - Overall MEL plan design and implementation - Manages the MEL group and ensures that recommendations from the group are implemented timely - Prepares quarterly and annual reports - Conducts internal data quality reviews - Design and coordinate case studies to assess effectiveness of program implementation - Coordinate all project evaluations MIS Specialist Accra - Design and manage the MIS database - Design data collection tools and analyze data in the MIS database. - Supervise the IT Specialist to back up all data weekly as appropriate Project M&E Coordinator Tamale - Oversees field data entry assistant and M&E Interns - Coordinate all data collection across project locations - Validate all data submitted by field M&E data entry assistant, M&E Interns and other field technical staff before accepting in database - Assists and MEL Specialist in implementing the KM&L plan - Back up all data weekly Field M&E and OB Interns Tamale, Wa and Bolgatanga - Coordinates data collection in their respective Regions - Conduct internal data quality reviews - Validate all data entered by the technical staff before accepting into the database - Prepare quarterly and annual reports - Assist in all program evaluations - Back up all data daily All technical field staff All field offices - Routine data collection (as part of normal field activities) and capture in the M&E database - Collect and analyze data from all demonstrations conducted and determine profitability of various practices - Collect data during annual surveys IT Specialist Accra - Provide support for database management - Back up all data daily or weekly as appropriate M&E Staff Training: The MEL Specialist will train the M&E Coordinator; Data Entry Assistant, Interns and technical field staff on the result framework and the use of the MEL Plan. The training will orient staff to the ADVANCE II M&E procedures and will cover basic concepts of M&E management (i.e. data collection, data entry, validation methods, data quality management and reporting requirements). 18 DATA QUALITY REVIEWS At ACDI/VOCA, we recognize that the data we collect informs management and policy decisions at multiple levels, and we diligently strive to provide timely, accurate, valid, complete and reliable information to stakeholders. One of the most significant M&E challenges is ensuring accurate data in a timely manner; issues include double counting across target groups reached through various project activities, missing data, data fraud, aggregation and transcription errors, or simple misunderstanding and misinterpretation of data collection and documentation procedures. To address these challenges, ADVANCE II project staff will work closely with partners on data quality, including collection and management procedures to ensure that the process of capturing, verifying and analyzing data is of the highest standard. Routine data collection will be done by OBs and their agents. Each participant will be coded and each OB and his/her outgrowers will be given identification cards to avoid double counting. Field staff will promote and monitor the proper use of record books by the smallholders and NFs to ensure the quality and accuracy of the data provided. As part of the KM&L plan, an initial M&E workshop will be organized within the first two months of the cost extension period. During the workshop, the project will engage all project and partner staff involved in data collection to create a common understanding of the indicators, their definitions, the data collection protocols and tools, and the data quality assessment procedure, utilizing USAID standard M&E guidelines captured in the project data quality strategy document. The MEL Specialist will conduct an internal rapid data quality assessment to assess the validity, reliability and timeliness of data and, when necessary, adjust the system. The team will also hold formal M&E trainings whenever necessary to address modifications in data collection methodology resulting from the data quality reviews. Furthermore, the ACDI/VOCA HQ M&E Manager will visit the project to conduct a detailed data quality assessment/internal data quality audit. EVALUATION APPROACH AND ASSESSMENTS Opportunities for impact evaluation had been incorporated into the project design and start-up phase to ensure that outcomes can be appropriately measured and attribute causality. The ADVANCE II team will collaborate with the third-party evaluator on the impact evaluation. In addition, the MEL team will conduct an annual outcome survey between August and December 2019. Final Evaluation During the last few months of implementation, USAID will recruit an external evaluator to conduct a study where the baseline data will be compared to outcomes and impacts at the time of the evaluation. This comparison will capture changes in outcome and impact indicators and consequently will provide evidence of progress towards the goal and objectives of the project as described in the results framework. We will share, discuss and document results at closeout workshop events that will be organized with stakeholder participation to ensure that learning is shared beyond the project. Annual Surveys The M&E team will lead the conduct of annual surveys to complement the routine data collection effort. In order to be efficient and accurate, the ADVANCE II team will adopt technologies that enable staff to collect data through mobile applications wherever possible. Some specific indicators that the annual surveys will capture includes yield, gross margins, volume and value of sales as well as various elements of technology adoption. From a stratified sample, we will extrapolate to the total population and enter that data as the total for the population. 19 Sampling Method and Size All smallholder project participants who produce maize, or soybean will constitute the total population and the sampling frame will be this category of beneficiaries as contained in the project’s MIS database. Farmers will be categorized based on the major crop produced. We will adapt a stratified sampling technique to select the sample. We will divide the population first into maize and soybean farmers. We will then obtain a simple random sample from each stratum (commodity). We will further proportionally stratify within each sample based on sex (male and female). The sample will be calculated using the electronic sample size calculator from www.raosoft.com with at least 95% confidence level (5% margin of error) to meet USAID standards. After determining the sample size, we will inflate the sample size by 10% to compensate for respondents that may not be available at the time of data collection. During the annual surveys, GIS technologies will be used as a tool for accurate measurement of farm sizes and proper geo-referencing of data collected. RISKS AND ASSUMPTIONS In order to maximize the effectiveness and efficiency of the ADVANCE II project, the management team, through regular monitoring, will identify and address any risks/challenges that may arise during project implementation. Four challenges relating to market price, weather, gender and the environment are likely to have an impact on project implementation. These are presented below together with a means of monitoring their respective effects on the project to enable early warning and response. Market Demand and Price Fluctuation The MEL plan has been developed with the assumption that certain variables are kept constant. Market demand and price fluctuations are two of the most critical issues in the agricultural sector in Ghana. The cost of inputs may change as a result of global price trends and fluctuations in foreign exchange rates, output prices will also vary with changes in productivity that will impact on supply and subsequently on prices, the extent of which can only be determined with accurate knowledge of price elasticity for the various commodities. Since we do not have accurate information on these factors, we are constrained in predicting price changes over the life of the project and have therefore kept prices constant. Monitoring and Mitigation: To mitigate this challenge, ADVANCE II will monitor early warning indicators, including food prices, fuel and input costs, at global, country and district level from the FAO, WFP and through project site visits. Actual and trends in price changes will be used to estimate prices annually during planning to keep data as close as possible to real situation at any point in time. Weather With irrigation almost nonexistent, Ghana’s agriculture depends largely on climate conditions. Climate change indications, including rise in temperature and delayed (or in recent times earlier than expected) onset of the rainy season, leads to uncertainty with planting time. In recent times there is concern about both a decrease in the number of rainy days as well as rainfall amounts. Another climatic threat is floods, which are becoming an annual occurrence in the north of Ghana, that destroy many crops and livestock in low lying areas. 20 Monitoring and Mitigation: To mitigate this challenge, ADVANCE II will monitor early warning indicators such as rainfall through data we will collect from the Meteorological Department and MoFA at the national and district level. The main mitigating factor against reduced rainfall, however, is to introduce water conservation techniques while advising farmers to avoid low lying areas that are prone to annual flooding to reduce the impact of the phenomenon. Gender and Youth Gender and youth considerations are critical to the success of ADVANCE II because gender and youth roles and relations can both affect and be affected by the outcomes and results of activities. ADVANCE II partners will therefore consider and address how gender relations and youth participation will affect the achievement of sustainable results, as well as how proposed results will affect the relative status of men and women and the youth. Monitoring and Mitigation: Our approach is to identify where youth related constraints occur within the target value chains and design interventions to address them. We are also adopting a targeted approach, making youth and women’s economic and social empowerment a priority of the project. The detailed youth and gender mainstreaming strategy has been captured in the USAID’s ADVANCE II cost extension implementation plan. The MEL team will examine the effectiveness of our youth and gender strategy through focus group discussions and case studies periodically and final evaluations will also assess the effectiveness of the gender and youth strategies and make recommendations for future application. Environmental Impacts Given the nature of agricultural projects, there is potential for negative impacts on the environment, such as destructive use of wetlands, deforestation, encroachment on forest reserves and improper use of agro￾chemicals. Monitoring: The Environmental Monitoring and Mitigation Plan (EMMP) details the specific processes and steps required to monitor and mitigate real and potential environmental effects as a result of project interventions. Throughout implementation, we will identify and categorize activities as low, medium or high risk those that are potentially high risk will undergo a formal environmental review and take the necessary steps to mitigate any real or potential effect. Through ongoing monitoring, we will assess whether potential environmental impacts are properly addressed and will adjust our responses as necessary. We will also incorporate the promotion of sound and sustainable environmental practices into the project’s core activities including assisting medium and large-scale farmers to develop environmental management plans. 21 Annex 1: FY targets # Indicator/ Disaggregation FY14 FY15 FY16 FY17 FY18 Targets FY19 Targets FY20 Current LOP EG.3.2 Number of individuals participating in USG food security programs 35,000 50,000 78,000 80,000 75,000 20,000 5,000 NA Male 21,000 30,000 42,900 44,000 41,250 10,000 2,500 Female 14,000 20,000 35,100 36,000 33,750 10,000 2,500 EG.3-10,11,- 12 Yield of targeted agricultural commodities among program participants with USG assistance - - - - - - - NA Maize - - - - - 3.7 4.0 Soy - - - - 2.0 2.5 EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance 14,000 35,000 45,000 70,200 72,200 75,545 20,000 NA Male - 21,000 24,750 38,610 39,600 37,578 10,000 Female - 14,000 20,250 31,590 32,400 37,967 10,000 EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance 5,000 52,500 45,000 70,200 72,200 59,373 18,000 NA EG.3.2-26 Value of annual sales of farms and firms receiving USG assistance [IM-level] (USD) - 6,780,000 9,320,000 16,940,000 17,880,000 48,276,995 9,624,000 NA Maize - 2,240,000 8,080,000 14,570,000 14,940,000 43,243,67 8,704,000 Soy - 1,600,000 360,000 590,000 810,000 4,592,365 920,000 22 EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance [IM-level] 500,000 1,000,000 1,000,000 1,000,000 800,000 120,000 20,000 NA EG.3.2-29 Number of organizations with increased performance improvement with USG assistance - 9 20 40 50 20 NA NA EG.4.2-7 Number of individuals participating in group￾based savings, micro￾finance or lending programs with USG assistance - - - - - 4,000 1,000 NA GNDR￾2 Percentage of female participants in USG - assisted programs designed to increase access to productive economic resources 20 20 20 YOUTH -3 Percentage of participants in USG- assisted programs designed to increase access to productive economic resources who are youth (19-29) 12 15 15 OP6 Number of value chain actors accessing finance 200 225 225 225 50 0 300 23 Annex 3: Performance Indicator Reference Sheets 24 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result- IR 1: Increased productivity in targeted commodities (maize and Soy) Name of Indicator: EG.3.2 Number of individuals participating in USG food security programs Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2019 and FY2020 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, including those we reach directly, those reached as part of a deliberate service strategy, and those participating in the markets we strengthen. We expect Implementing Partners (IPs) to track or estimate the number of individual participants across different interventions within their own project and to report numbers of participants reached, not number of contacts with the project or project supported actors. This indicator counts, with some exceptions listed below, all the individuals participating in our nutrition, resilience, and agriculture and food system activities, including: • Adults that projects or project-supported actors reach directly through nutrition-specific and community-level nutrition interventions, (e.g. parents and other caregivers participating in community care groups, healthcare workers provided with inservice training on how to manage acute malnutrition), but not children reached with nutrition-specific or community￾based interventions, who are counted under indicators HL.9-1 and HL.9-2 instead; • People reached by productive safety nets, community-based micro-finance and diversified livelihood activities through our assistance; • Members of households reached with household-level interventions (households with new access to basic sanitation through our work, households receiving family-sized rations); • Smallholder and non-smallholder producers that projects or project-supported actors reach directly (e.g. through an irrigation training, through a loan provided, through distribution of drought-tolerant seeds to specific farmers); • Proprietors of firms in the private sector that we help strengthen (e.g. agro dealers, aggregators, processors), but not all the employees of those firms; • Producers who directly interact with those USG-assisted firms (e.g. the producers who are customers of an assisted agro dealer; the producers from whom an assisted trader or aggregator buys), but not customers or suppliers who are not producers; • Participants whose main source of income is labor (e.g. Laborers/non-producer diversified livelihood participants); • People in civil society organizations and government whose skills and capacity have been strengthened by projects or project supported actors; • School-aged children who are recipients of USG school feeding programs; In cases where activities work with multiple individuals in a household, this indicator counts all activity participants in the household, not all members of the household. However, in the case of sanitation services and family-sized rations, all members of the household receiving the sanitation facility or ration can be counted here. An individual is a participant if s/he comes into direct contact with the set of interventions (goods or services) provided or facilitated by the activity. The intervention needs to be significant, meaning that if the individual is merely contacted or touched by an activity through brief attendance at a meeting or gathering, s/he should not be counted as a participant. An intervention is significant if one can reasonably expect,and hold OUs and IMs responsible for achieving progress toward, changes in behaviors or other outcomes for these individuals based on the level of services and/or goods provided or accessed. Producers with increased access to goods, services and markets for their products and who purchase from or sell to market actors that have been strengthened as a result of our activities are considered to have received a significant intervention. Individuals who are trained by an IM as part of a deliberate service delivery strategy (e.g. cascade training) that then go on to deliver services directly to individuals or to train others to deliver services should be counted as participants of the activity—the capacity strengthening is key for sustainability and an important outcome in its own right. The individuals who then receive the services or training delivered by those individuals are also considered participants. However, spontaneous spillover of improved practices to neighbors does not count as a deliberate service delivery strategy; neighbors who apply new practices based on observation and/or interactions with participants who have not been trained to spread knowledge to others as part of a deliberate service delivery strategy should not be counted under this indicator. Value chain facilitative and/or market-system activities may use a two-step process to identify and count participants: 1. The first step involves identifying which private sector firms have been assisted by the activity during the reporting year, and counting the number of proprietors of those firms. 2. The second step, which is only applicable to firms that buy from or sell to producers, is to count the number of producer customers or suppliers of each assisted firm. 25 The total number of participants for that activity is then the sum of the proprietors of the assisted firms and their producer customers/suppliers. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers purchasing certified soy seed (by using a conservative assumption that one sales equals one farmer applying), and then report that number as the number of producer participants. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment in FTFMS. Data provision by assisted firms can be facilitated by entering into written agreements that include reporting and nondisclosure requirements and by showing assisted firms how the information provided is useful and used. Counting producer participants may be more straightforward if the value chain activity is also facilitating extension strategies, e.g. agrodealer agents that require knowing where the customers live and farm. While other Feed the Future indicators, such as "financing accessed", "value of sales," and "individuals applying improved practices" also capture the number of enterprises that contributed results to the indicator, this indicator only counts individual people, i.e. the farmer (not the farm), and the proprietor (not the firm). This indicator does not count the indirect beneficiaries of our activities. An indirect beneficiary is someone who does not have direct contact with the activity but still benefits, such as the population that uses a new road constructed by the activity, neighbors who see the results of the improved technologies applied by direct participants and decide to apply the technology themselves (spillover), or the individuals who hear an activity-supported radio message but don’t receive any training or counseling from the activity. In part, this is because accurate tracking of indirect beneficiaries is challenging by its nature, despite the fact that spillover is a core component of the Feed the Future theory of change. In general, spillover is captured in Feed the Future through measuring changes in population level indicators (e.g. proportion applying improved technologies and management practices) and linking those to the work activities are doing directly. Note that this indicator cannot be summed across years for a project total, since “new” and “continuing” participants are not disaggregated, and thus this will only show a total of individuals reached in any one reporting year. Unit of Measure: Number Disaggregated by: • Sex, (unique count) • Age (unique count) 18 -29 and 30+ , • Type of individual double-counting individuals across types is permitted here • People in government (e.g. policy makers, extension workers, healthcare workers); • Proprietors of USG-assisted private sector firms (e.g. agro dealers, traders, aggregators, processors, service providers, manufacturers); • People in civil society (e.g. NGOs, CBOs, CSOs, research and academic organizations, community volunteers) While private sector firms are considered part of civil society more broadly, only count their proprietors under the "Private Sector Firms" disaggregate and not the "Civil Society" disaggregate • Laborers (Non-producer diversified livelihoods participants); • Producers (e.g. farmers, fishers, pastoralists, ranchers); Producers should be counted under the "Producers" disaggregate, not the "Private Sector Firms" disaggregate o Smallholder (see definition below); o Non-smallholder; Smallholder Definition: While country-specific definitions may vary, use the Feed the Future definition of a smallholder producer, which is one who holds 5 hectares or less of arable land Rational or justification 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 ZOI 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. Type: Output Direction of change: Higher = better PLAN FOR DATA COLLECTION Data Source(s): Regular participation monitoring - Program database Method of data collection and construction: Regular monitoring - Program database. Firm records, activity records, training participant lists, or through census or sampling of participating firms/farms/families/individuals, etc Frequency/Timing of Data Collection: Quarterly Reporting Frequency: Quarterly 26 Estimated cost of data collected: Part of routine M&E reporting costs Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): annually CHANGES TO INDICATOR Changes to Indicator Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE IIM&E Manager and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Manager Reporting of Data: Quarterly/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY18 23,870 Participants within the 17 GFSS districts Year Targets Actuals Male Female Male Female FY19 10,000 10,000 FY20 2,500 2,500 THIS SHEET LAST UPDATED ON: June 3, 2019 27 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result- IR 1: Increased productivity in targeted commodities (maize and Soy) Sub- Intermediate Result- Sub-IR.0: Name of Indicator: EG.3-10,-11,-12 Yield of targeted agricultural commodities among program participants with USG assistance Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 and FY2017 and FY2018If yes link to foreign assistance frame work: Precise Definition(s): Yield is a measure of the total output of production of an agricultural commodity (crop, fish, milk, eggs, live animal offtake[1]) divided by the total number of units in production (hectares planted of crops, area in hectares for pond aquaculture, cubic meters of cage for cage aquaculture, maximum number of animals in the herd/flock during the reporting year for live animals, maximum number of producing cows or hens during the reporting year for dairy or eggs). Yield per hectare, per animal and per cubic meter of cage is a measure of productivity from that farm, fisheries, or livestock activity from USG-assisted producers. Yield is calculated automatically in FTFMS from the following data points, reported as totals across all activity participants, and disaggregated by commodity, then by sex and age of the producer: 1.Total Production (TP): Kg, mt, number, or other unit by participants during the reporting period; 2.Total Units of Production (UP): Area planted in ha (for crops); Area in ha (for aquaculture ponds); Maximum number of animals in herd (for live animals); Maximum number of animals in production (for dairy or eggs); Cubic meters of cages (for open water aquaculture) for participants during the reporting year. Yield per hectare = TP/UP If there is more than one production cycle in the reporting year, the data points for total production (TP) and units of production (UP) should be counted (and summed) each time the land is cultivated. The sum of TP divided by the sum of UP will provide an estimate of the average yield achieved across the different production cycles. Total production is the amount that is produced, regardless of how it was ultimately used. It also includes any postharvest loss (i.e. postharvest loss should not be subtracted from total production.) The preferred units for TP is metric tons The required units for UP is hectare Yield targets should be entered at the commodity level and at the sex and age level under each commodity. Targets do not need to be set for the TP and UP data points. [1] Offtake quantity includes the entire weight of all animals that were sold, slaughtered, gifted or exchanged, including those for home consumption. [2] For tree crops, Number of hectares is recommended as UP, however, Number of trees can also be selected for UP. FTFMS won’t have the capability to convert and aggregate across the different UPs. Reporting Notes: FTFMS DATA ENTRY NOTES: If a sample survey of activity participants is used to collect yield data points, the sample weighted estimate of the total across all participants must be calculated for each data point using appropriate sample weights before being entered into FTFMS. Partners must also enter the number of participants in the activity, disaggregated by commodity and then sex and age of the participant producer. Participants should only be counted once under each commodity regardless of the number of production cycles for the commodity in the reporting year. Data should be entered in FTFMS disaggregated to the lowest level. Partners should enter total production, total units of production, and total number of participants, disaggregated by commodity, then by farm size (for crops) or production system (for livestock), then by sex and by age. This procedure applies for each commodity. These disaggregations are required since the most meaningful interpretation and use of yield information is at the specific commodity level, including the comparison of yield obtained by female and male producers. FTFMS will calculate commodity-specific yield per ha, animal or cubic meter of cage automatically. For example, to report on the yield for maize for small-holder activity participants, partners should enter the following information for the reporting year: Commodity: Maize Farm size: Small-holder Number of participants • total number of female, maize-producing small-holder activity participants; 28 • total number of male, maize-producing small-holder activity participants; • total number of 18-29 year old, maize-producing small-holder activity participants; • total number of 30+ year old, maize-producing small-holder activity participants. Total production • total production in mt on plots managed by female, maize-producing small-holder activity participants; • total production in mt on plots managed by male, maize-producing small-holder activity participants; • total production in mt on plots managed by 18-29 year old maize-producing small-holder activity participants; • total production in mt on plots managed by 30+ year old maize-producing small-holder activity participants. Units of production • total hectares in production managed by female, maize-producing small-holder activity participants; • total hectares in production managed by male, maize-producing small-holder activity participants; • total hectares in production managed by 18-29 year old maize-producing small-holder activity participants; • total hectares in production managed by 30+ year old maize-producing small-holder activity participants Unit of Measure: Crops metric tons Disaggregated by: Commodity, farm size (Smallholder and non smallholder) Sex (male/female and Age (18-29, 30+) Rational or justification for indicator (optional): Improving the yield for farm commodities contributes to increasing agricultural GDP, can increase income when other components of agricultural productivity are in place (e.g., post-harvest storage, value addition and processing, markets), and can therefore contribute to the IR of increasing sustainable productivity and the goal indicator of reducing poverty. Yield of farms is a key driver of agricultural productivity and can serve as a proxy of the overall productivity of these value chains and the impact of interventions when the trend is evaluated over a series of years, and/or appropriate covariates such as inter-annual weather conditions are included in the analysis. In the GFSS Results Framework, this indicator measures Intermediate Result 1: Increased sustainable productivity, particularly through climate-smart approaches. Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Annual outcome survey in conjunction with data collected from a sample of monitored farmers and OBs Method of data collection and construction: Survey: Participant farmer sample surveys ; data collection through producer organizations or farm records, routine activity records, as well as data collection through producer organizations or farm records Frequency/Timing of Data Collection: Annually Reporting Frequency: Annually Estimated cost of data collected: Part of routine M&E reporting costs Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): annually CHANGES TO INDICATOR Changes to Indicator: Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE II M&E Manager and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Manager Reporting of Data: Annually Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes 29 Baseline value FY18 Maize:/ Male:3.78./Female 3.5 2018 Soya: / Male:1.99/Female:2.05 actuals Year Targets Actuals FY19 Maize:/ Male:3.8/Female 3.5 Maize: Soya: / Male:1.9/Female:2.1 Soya: FY 20 Maize:/ male:4.1/Female 3.9 Maize: Soya: / Male:2.3/Female:2.6 Soya: THIS SHEET LAST UPDATED ON: June 3, 2019 30 USAID Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result- IR 1: Increased productivity in targeted commodities (maize and Soy) Name of Indicator: EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance. Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2019 and FY2020 DESCRIPTION Precise Definition(s): This indicator measures the total number of agriculture system actors participating in the USG-funded activity who have applied improved management practices and/or technologies promoted by the USG anywhere within the food and agriculture system during the reporting year. These individuals can include: • Farmers and other primary sector producers of food crops, • Individuals in the private sector, such as entrepreneurs, input suppliers, traders, processors, manufacturers, distributors, service providers, and wholesalers and retailers; • Individuals in government, such as policy makers, extension workers and natural resource managers; • Individuals in civil society, such as researchers or academics and non-governmental and community organization staff. The indicator tracks those individuals who are changing their behavior while participating in USG-funded activities. Individuals who attended training or were exposed to a new technology do not count under this indicator unless the individual actually applies what she/he learned. For example, if an agriculture extension agent attends a gender-sensitive agriculture extension training, he can be counted under this indicator once he applies what he learned by changing the way he reaches out to and interacts with the female farmers to whom he provides extension services. Improved management practices or technologies are those promoted by the implementing partner as a way to increase agriculture productivity or support stronger and better functioning systems. The improved management practices and technologies are agriculture- related, including those that address climate change adaptation or climate change mitigation. Implementing partners promoting one or a package of specific management practices and technologies report practices under categories of types of improved management practices or technologies. This indicator captures results where they were achieved, regardless of whether interventions were carried out, and results achieved, in the ZOI. Management practice and technology type categories, with some illustrative (not exhaustive) examples, include: • Crop genetics: e.g. improved/certified seed that could be higher-yielding, higher in nutritional content (e.g. through biofortification, such as vitamin A-rich sweet potatoes or rice, high-protein maize), and/or more resilient to climate impacts (e.g. drought tolerant maize, or stress tolerant rice); improved germplasm. • Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and transplantation; cultivation practices such as planting density, crop rotation, and mounding. • Livestock management: e.g. improved livestock breeds; livestock health services and products such as vaccines; improved livestock handling practices and housing; improved feeding practices; improved grazing practices, improved waste management practices, improved fodder crop, cultivation of dual purpose crops. • Wild-caught fisheries management: e.g. sustainable fishing practices; improved nets, hooks, lines, traps, dredges, trawls; improved hand gathering, netting, angling, spearfishing, and trapping practices. • Aquaculture management: e.g. improved fingerlings; improved feed and feeding practices; fish health and disease control; improved cage culture; improved pond culture; pond preparation; sampling and harvesting; management of carrying capacity. • Natural resource or ecosystem management: e.g. terracing, rock lines; fire breaks; biodiversity conservation; strengthening of ecosystem services, including stream bank management or restoration or re/afforestation; woodlot management. Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of fungicides; improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and pesticides; crop rotation; aflatoxin prevention and control. • Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase biotic activity and soil organic matter levels, such as soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter, mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control. • Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes. • Agriculture water management - non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that improve water quality. • Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and degraded lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of perennials; practices that promote greater resource use efficiency (e.g. drip irrigation, upgrades of agriculture infrastructure and supply chains). • Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing the severity of the impacts of climate change. Examples include drought and flood resistant varieties; short- 31 duration varieties; adjustment of sowing time; agricultural/climate forecasting; early warning systems; diversification, use of perennial varieties; agroforestry; risk insurance. • Marketing and distribution: e.g. contract farming technologies and practices; improved input purchase technologies and practices; improved commodity sale technologies and practices; improved market information system technologies and practices. • Post-harvest handling and storage: e.g. improved transportation; decay and insect control; temperature and humidity control; improved quality control technologies and practices; sorting and grading, sanitary handling practices. • Value-added processing: e.g. improved packaging practices and materials including biodegradable packaging; food and chemical safety technologies and practices; improved preservation technologies and practices. Other: e.g. improved mechanical and physical land preparation; non-market- and non-climate-related information technology; improved record keeping; improved budgeting and financial management; Improved capacity to repair agricultural equipment; improved quality of agricultural products or technology This indicator endeavors to capture the individuals who have made the decision to apply a particular management practice or technology, not those who have had to do so as a condition of employment or an obligation. For example, if a manager in a company that distributes agriculture produce decides to use refrigerator trucks for transport and plans the distribution route using GIS information to maximize efficiency, both practices that are promoted by the USG-funded activity, the manager is counted as one individual; the five drivers of the newly refrigerated trucks who are driving the new routes are not counted. If the manager and co￾owner together decided to apply these new practices, they are counted as two individuals. Another example would be if a franchise offers a new fertilizer mix developed with USG assistance and makes it available to franchisees, yet those franchisees make the decision whether or not to offer it. In this case both the decision-maker(s) at the franchise level and the franchisees who decide to offer it get counted as individuals applying a new management practice. It is common for USG-funded activities to promote more than one improved technology or management practice to farmers and other individuals, This indicator allows the tracking of the total number of participants that apply any improved management practice or technology during the reporting year and the tracking of the total number of participants that apply practices or technologies in specific management practice and technology type categories. • Count the participant if they have applied a management practice or technology promoted with USG assistance at least once in the reporting year. Count the producer participant who applied improved management practices or technologies regardless of the size of the plot on which practices were applied. • Count each participant only once per year in the applicable Sex disaggregate category and Age disaggregate category to track the number of individuals applying USG-promoted management practice or technology type. If more than one participant in a household is applying improved technologies, count each participant in the household who does so. • Under the Commodity disaggregate, count each participant once under each commodity for which they apply a USG￾promoted management practice or technology type. For example, if a participant uses USG-promoted improved seed for the focus commodities of maize and legume, count that participant once under maize and once under legumes. Count each individual once per management practice or technology type once per year under the appropriate Management practice/technology type disaggregate. Individuals can be counted under a number of different Management practices/technology types in a reporting year. Count a participant once per practice/technology type category regardless of how many specific practices/technologies under that technology type category she/he applied. For example, a project is promoting improved plant spacing and planting on ridges. A participant applies both practices. She/he would only be counted once under the Cultural practices technology type category IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicators EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level], and EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level] if they use clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number and volume of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers applying certified soy seed (by using a conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically validated planting density. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment. However, if an agro-dealer gives away seed packs with the purchase of other inputs as a promotion, more validation would be necessary for the IP to assume farmers purchasing the other input are also applying that seed. If a lead farmer cultivates a plot used for training, e.g., a demonstration plot used for Farmer Field Days or Farmer Field School, the lead farmer should be counted as a participant applying improved practices/technologies for this indicator. In addition, the area of the demonstration plot should be counted under indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level]. However, if the demonstration or training plot is cultivated by a researcher (a demonstration plot in a research institute, for instance), neither the area nor the researcher should be counted under this indicator or indicator EG.3.2-25. Participants who are part of a group or members of an organization that apply improved technologies on a demonstration or other common plot should not be counted under this indicator, the area of the common plot should not be counted under indicator EG.3.2- 25 Number of hectares under improved management practices or technologies with USG assistance [IM-level], and the yield should not be counted under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among program participants with USG 32 assistance [IM-level]. For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25 and EG.3-10, -11, -12) only capture results for land that is individually managed. This is a snapshot indicator, which is designed to capture farmer application only for the reporting year. Individuals who applied a USG activity-promoted management practice before the intervention constitute the baseline. Individuals that still continue to apply the USG activity-promoted during the project period get counted for applying the technology in any subsequent years they apply that technology. However, this also means that yearly totals can NOT be summed to count application by unique individuals over the life of the project. However, there are some cases where group members can be counted under this indicator. For example, as a result of participating in a USG-funded activity, a producer association purchases a dryer and then provides drying services for a fee to its members. In this scenario, any member that uses the dryer service can be counted as applying an improved management practice under this indicator. Note that the list of practice/technology type disaggregates is broader under this indicator than the list of practice/technology type disaggregates under indicator EG.3.2-25 because this indicator tracks application of improved practices/technologies beyond those that are applied to a defined land or water area. Unit of Measure: Number Disaggregated by: Value chain actor type: • Smallholder producers (e.g. farmers, ranchers, and other primary sector producers of food and nonfood crops, livestock products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products) • Non-smallholder producers (e.g. farmers, ranchers, and other primary sector producers of food and nonfood crops, livestock products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products) • People in government (e.g. policy makers, extension workers) • People in private sector firms (e.g. processors, service providers, manufacturers) • People in civil society (e.g. staff and volunteers from non-governmental organizations, community-based organizations, research and academic organizations) • Others Sex, Age (18-29 and 30+ Management practice or technology type Commodity Rational or justification for indicator (optional): Improved management practices and technological change and adoption by different actors throughout the agricultural system will be critical to increasing agricultural productivity and supporting stronger and better functioning systems. This indicator falls under IR 1: Strengthened inclusive agriculture systems that are productive and profitable in the Global Food Security Strategy (GFSS) results framework. . Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Sample survey of activity participants, census of private sector/government participants, activity records, farm records, reports from activity partners, association records, company/organization records Method of data collection and construction: Frequency/Timing of Data Collection: Annually Reporting Frequency: Annually Estimated cost of data collected: Part of routine M&E reporting costs Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): annually CHANGES TO INDICATOR Changes to Indicator: indicator titled changed from “4.5.2(5) Number of farmers and others who have applied improved technologies or management practices as a result of USG assistance” to “EG. 3.2-17 Number of farmers and others who have applied improved technologies or management practices as a result of USG assistance”. Included to the disaggregation is Commodity( FTFMS-only) Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. 33 The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE II M&E Coordinator and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinator Reporting of Data: Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY18 0 Year Targets Actuals FY19 Male:37,578/Female:37,967 FY 20 Male:10,000/Female:10,000 THIS SHEET LAST UPDATED ON: June 3, 2019 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result- IR 1: Increased productivity in targeted commodities (Maize and Soy) Sub- Intermediate Result- Sub-IR.0: Name of Indicator: EG. 3.2-18 Number of hectares under improved technologies or management practices as a result of USG Assistance Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 and FY2017 and FY2018 DESCRIPTION Precise Definition(s): This indicator measures the area in hectares where USG-promoted management practices or improved technologies were applied during the reporting year to areas managed or cultivated by producers participating in a USG-funded activity. Management practices counted are agriculture-related, land- or water-based management practices and technologies in sectors such as cultivation of food or fiber, aquaculture, fisheries, and livestock management, including those that address climate change adaptation and mitigation. Improved management practices or technologies are those promoted by the implementing partner as a way to increase producer’s productivity directly or to support stronger and better functioning systems. The application of both intensive and extensive agriculture-related management practices and technologies in different landscapes are captured under the Type of Hectare disaggregate. The Type of Hectare disaggregates are: crop land, cultivated pasture, rangeland, conservation/protected area, freshwater or marine ecosystems, aquaculture. . Those interventions carried out on crop land, cultivated pasture and aquaculture are considered “intensive”. Those carried on rangeland, conservation/protected area and freshwater or marine ecosystems are considered “extensive”. The same area cannot be counted under more than one Type of Hectare disaggregate category. This indicator captures results where they were achieved, regardless of whether interventions were carried out, and results achieved, in the ZOI. A management practice or technology can be applied under a number of different hectare types. For example, improved grazing practices could take place in cultivated pasture, rangeland, or conservation and mixed-used landscapes, and climate adaptation/climate risk management interventions can be applied in all hectare types. Management practice and technology type categories, with some illustrative (not exhaustive) examples, include: •Crop genetics: e.g. improved/certified seed that could be higher-yielding or higher in nutritional content (e.g. through biofortification, such as vitamin A-rich sweet potatoes or rice, or high-protein maize), and/or more resilient to climate impacts (e.g. drought tolerant maize or stress tolerant rice); improved germplasm. •Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and transplantation; cultivation practices such as planting density, crop rotation, and mounding. •Livestock management: e.g. improved grazing practices, improved fodder crop, cultivation of dual purpose crops. 34 • Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of fungicides; improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and pesticides; crop rotation; alflatoxin prevention and control during production. • Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase biotic activity and soil organic matter levels, such as soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter, mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control. • Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes. • Agriculture water management - non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that improve water quality. • Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and degraded lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of perennials; practices that promote greater resource use efficiency (e.g. drip irrigation). • Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing the severity of climate change. Examples include drought and flood resistant varieties; short-duration varieties; adjustment of sowing time; diversification, use of perennial varieties; agroforestry. • Other: e.g. improved mechanical and physical land preparation. Since it is very common for USG activities to promote more than one improved management practice or technology, this indicator allows the tracking of the number of hectares under the different management practices and technology types and the total unique number of hectares on which one or more practices or technologies has been applied at the activity level. • If a participant applied more than one improved technology during the reporting year, count that area on which the participant applied those technologies under each relevant Management Practice type applied under the relevant Hectare type. However, count the area only once in the applicable Sex, Age and Commodity disaggregate categories under the relevant Hectare type. This will not result in double-counting for the total in FTFMS. • If an activity is promoting a single technology for multiple benefits, the area under the technology may be reported under each relevant category under the Management Practice/Technology Type disaggregate. For example, drought tolerant seeds could be reported under Crop genetics and Climate adaptation/climate risk management depending for what purpose(s) or benefit(s) the activity was promoted. If a participant cultivates a plot of land more than once in the reporting year, the area should be counted each time one or more improved management practice/technology is applied. For example, because of access to irrigation as a result of a USG activity, a farmer can now cultivate two cycles of crops instead of one. If the farmer applies USG-promoted technologies on her/his plot for the two cycles, the area of the plot would be counted twice under this indicator. Note that the farmer would only be counted once under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG If a lead farmer cultivates a plot used for training, e.g. a demonstration plot used for Farmer Field Days or Farmer Field School, the area of the demonstration plot should be counted under this indicator. In addition, the lead farmer should be counted as one individual under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level]. This is a snapshot indicator, which is designed to capture farmer application only for the reporting year. Individuals who applied a USG activity-promoted management practice before the intervention constitute the baseline. Individual that still continue to apply the USG activity-promoted during the project period get counted for applying the technology in any subsequent years they apply that technology. However, this also means that yearly totals can NOT be summed to count application by unique individuals over the life of the project. IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level] and indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level] if they use clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number and volume of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers applying certified soy seed (for example, by using a conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically validated planting density. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment. However, if an agro-dealer gives away seed packs with the purchase of other inputs as a promotion, more validation would be necessary for the IP to assume farmers purchasing the other input would also apply that seed. Demonstration plots cultivated by researchers (a demonstration plot in a research institute, for instance) should not be counted under this indicator nor should the researcher be counted under this indicator or indicator EG.3.2-24. The area of a demonstration or common plot cultivated under improved practices or technologies by participants who are part of a group or members of an organization should not be counted under this indicator, the participants should not be counted under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level], and the yield should not be counted under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among program participants with USG assistance [IMlevel]. 35 For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25, and EG.3-10, -11, -12) only capture results for land that is individually managed. However, communally- or group-managed areas under extensive ”Type of Hectares” disaggregates, such as conservation landscapes or rangeland, can be reported under this indicator under the association-applied category under the Sex and Age disaggregate. Association-applied would be applicable for landscapes where communities or organizations develop and adhere to policies regarding management, harvest, protection, etc. [1] Type of hectare disaggregates defined as: • Crop land: areas used for the production of crops for harvest, including cultivated, harvested, fallow or crop failure. Include home gardens in this category. FTFMS DATA ENTRY NOTES: Please note the commodity must be selected in FTFMS to open the cells for data entry. If a participant sample survey is used to collect data for this indicator, the sample weighted estimate of the total number of hectares across all participants for each Management Practice type and Sex, Age and Commodity disaggregate under each Type of Hectare must be calculated using appropriate sample weights before being entered into FTFMS. Missions and IPs need to select the Type of Hectare first before reporting the number of hectares under the Sex, Age, Commodity, and Management Practice disaggregations. For those that select Other under Type of hectare, please include in the indicator comment a description of the type of landscape and whether the intervention is intensive or extensive. For example, an activity is working with smallholder farmers to increase the application of drought-tolerant maize with the intention of promoting increased climate adaptation, and increase the use of certified seed in soy. The IP would enter the number of hectares under each category as follows after selecting the maize and soy commodities and the crop land Type of Hectare: Type of Hectare: Crop land Sex of participant • total area cultivated by female smallholder farmer activity participants under drought-tolerant maize, certified soy seed, or both • total area cultivated by male smallholder farmer activity participants under drought-tolerant maize, certified soy seed, or both Age of participant • total area cultivated by 18-29 year old smallholder farmer activity participants under drought-tolerant maize, certified soy seed, or both • total area cultivated by 30+ year old smallholder farmer activity participants under applying drought-tolerant maize, certified soy seed, or both Management practice • total area cultivated by activity participants under Crop Genetics practices/technologies (i.e. drought-tolerant maize, certified soy seed or both) • total area cultivated by activity participants under Climate Adaptation practices/technologies (i.e. drought-tolerant maize) Commodity Maize • total area cultivated by activity participants under drought-tolerant maize Soy • total area cultivated by activity participants under certified soy-seed Unit of Measure: Hectares Disaggregated by: Type of hectare, Sex, Age, Management practice of technology type Rational or justification for indicator (optional): Improved management practices on agriculture land, in aquaculture, and in freshwater and marine fisheries will be critical to increasing agricultural productivity. This indicator tracks successful application of technologies and management practices in an effort to improve agricultural productivity, agricultural water productivity, sustainability, and resilience to climate change. In the GFSS results framework, this indicator reports contributions to IR.4: Increased sustainable productivity, particularly through climate-smart approaches. . Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Producers/FBO farm records/ individual processors and beneficiaries Method of data collection and construction: Sample survey of activity participants, activity or association records, reports from activity partners, farm records 36 Frequency/Timing of Data Collection: Seasonal, according to the crop cycle Reporting Frequency: Annually Estimated cost of data collected: Part of routine M&E reporting costs Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): CHANGES TO INDICATOR Changes to Indicator: Indicator title change from “4.5.3(2) Number of hectares under improved technologies or management practices as a result of USG Assistance” to “: EG. 3.2-18 Number of hectares under improved technologies or management practices as a result of USG Assistance” Included in the disaggregation is Commodity(FTFMS only) Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE IIM&E Coordinator and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinator Reporting of Data: Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY18 0 Targets Actuals FY19 59,373 FY 20 18,000 THIS SHEET LAST UPDATED ON: June 3, 2019 USAID Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Name of Indicator: EG.3.2-26 Value of annual sales of farms and firms receiving USG assistance [IM-level] Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 19, FY 20. If yes link to foreign assistance frame work: DESCRIPTION 37 Precise Definition(s): This indicator measures the value in U.S. dollars of the total amount of sales of products and services by USG-assisted farms and firms during the reporting year within USG-supported agricultural commodity value chains or markets. This indicator also collects additional data points on the value of sales in local currency, the number of activity participants, including the number of producers and the number of assisted private sector firms, and, if applicable, the volume of sales (preferably in metric tons) for agricultural commodities (i.e. seed; food, non-food and feed crops; livestock and livestock products, fish). Examples of USG assistance include facilitating access to improved seeds and other inputs, to extension, business development and financial services, and to micro-enterprise loans; providing technical support in production techniques; strengthening linkages to markets; and other activities that benefit producers or private sector firms in the agriculture and food system. Annual sales include all sales by farms and firms participating in USG-funded activities. This includes producers, such as farmers, fishers and ranchers; and private sector non-farm enterprises, such as aggregators, input suppliers and distributors, traders, or processors of the targeted commodity(ies) throughout the value chain. In value-chain-facilitation and other market-strengthening activities, activity participants include the private sector firms with direct contact with the USG-funded activity and the producers and other customers buying from or selling to the USG-assisted firms. Feed the Future recognizes the difficulty and cost to collect sales data directly from producers, especially when working with firms though a market-system approach intended to strengthen the links between producers and firms that purchase from them for onward sales, processing, etc. In these cases, implementing partners may consider collecting data from firms on producers who sold to the firms while collecting data on sales of the firms, rather than attempting to collect sales data from the producers directly. Implementing partners can then report both producer and firm sales under the appropriate disaggregate. “Private sector” includes any privately-led agricultural enterprise managed by a for-profit company. A community-based organization (CBO) or nongovernmental organization (NGO) may be included if the CBO or NGO engages in for-profit agricultural activity. Activity participants may be involved in agricultural production, agro-processing, wholesale or retail sales, fisheries, input supply, or other business activities in USG-assisted value chains and/or markets. Only count sales in the reporting year that are attributable to the USG, i.e. where the USG assisted the individual farmer or firm, or the market actor with which they are engaged directly, and for those value chains/commodities/markets which the USG supports. Sales do not have to take place within a specific geographic area, such as the ZOI. For assisted farms, sales refer to the value and amount of production that is sold, regardless of where the sales take place. For assisted firms, sales include the value of goods and services at the point of sale, not when the sale was contracted. Data should be collected directly from all firms who are receiving USG assistance. Under participants, count the number of assisted producers for whom sales data are available. Include producers reached directly with outreach and those buying from or selling to USG-assisted firms in a systems strengthening approach. For firms, count the USG- assisted firm as the participant. It is essential that a Baseline Year Sales data point be entered. If data on the total value of sales by participant farms or firms prior to USG-funded activity implementation is not available, do not leave the baseline blank or enter ‘0’. Use the earliest Reporting Year Sales actual as the Baseline Year Sales. The number of participants in USG-funded activities often increases over time as the activity rolls out. Unless an activity has identified all prospective participants at the time the baseline is established, the baseline sales value will only include sales made by participant farms and firms identified when the baseline is established during the first year of implementation. The baseline sales value will not include the baselines from farms and firms added in subsequent years. To address this issue, the USG requires reporting the number of participants, both producers and private sector firms for each value chain product or service along with baseline and reporting year sales. These data points can be used to calculate average sales per participant at baseline, disaggregated by farm and firm and assist with interpreting the reasons for an observed growth in the value of sales. To generate meaningful out-year targets for annual sales, targets for number of participants, disaggregated by farm and firm, are also required. The type of Product or Service sold by the producer or firm is the first level disaggregate when reporting. These are broken down into the following disaggregate categories to be selected in FTFMS, with illustrative examples: Products: • Agricultural commodities, which generally include those raw products sold by producers such as staples, legumes, horticulture, livestock, and fish but does NOT include seeds. The specific commodity (maize, mung beans, tomatoes, etc.) needs to be selected. • Inputs: Seeds and planting material. • Inputs: Other non-durable inputs, such as fertilizer and pesticides. • Inputs: Durable equipment and machinery, including land preparation equipment, irrigation equipment, and other equipment or machinery. • Processed products/value added products (post-harvest). The specific commodity does not need to be selected. • Post-harvest storage and processing equipment, including PICS bags and processing machinery. Services: 38 • Business services, including financial, entrepreneurial, legal, and other enterprise/producer strengthening services • Information services: SMS, Radio, TV, print, etc. • Production support services: other services that are sold to farmers, fishers, ranchers and pastoralists, including extension services, veterinary services, rental of equipment, land preparation, warehousing, post-harvest processing Unit of Measure: US Dollar Disaggregated by: Type of productor service (see indicator title for principal types) Type of producer/firm (firms are non-farm enterprises): Producer - smallholder, Producer – non-smallholder, Firm – microenterprise, Firm - Small and medium enterprise, Firm- Large enterprise or corporation. Smallholder Definition: While country-specific definitions may vary, use the Feed the Future definition of a smallholder producer, which is one who holds 5 hectares or less of arable land or equivalent units of livestock, i.e. cattle: 10 beef cows; dairy: two milking cows; sheep and goats: five adult ewes/does; camel meat and milk: five camel cows; pigs: two adult sows; chickens: 20 layers and 50 broilers. The farmer does not have to own the land or livestock. Firm Size Definition. For firms, microenterprises employed <10 people in the previous 12 months, small enterprises employed 10- 49 people, medium enterprises employed 50-249 individuals and large enterprises and corporations employed >250 individuals. Sex of producer or proprietor(s): Male, female, mixed For firms, if the enterprise is a single proprietorship, the sex of the proprietor should be used for classification. If the enterprise has more than one proprietor, classify the firm as Male if all of the proprietors are male, as Female if all of the proprietors are female, and as Mixed if the proprietors are male and female. Age: 18-29, 30+, mixed For firms, if the enterprise is a single proprietorship, the age of the proprietor should be used for classification. If the enterprise has more than one proprietor, classify the firm as 18-29 if all of the proprietors are aged 18-29, as 30+ if all of the proprietors are aged 30+, and as Mixed if the proprietors are from both age groups FTFMS DATA ENTRY NOTES: If a sample survey of participating producers is used to collect data for this indicator, the sample weighted estimate of total baseline or reporting year sales value and volume for all producers under each commodity must be calculated using appropriate sample weights before being entered into FTFMS. Data should be entered in FTFMS disaggregated to the lowest level—i.e. by product/service then by type of producer/firm then by sex and by age under each commodity and type of enterprise. Partners should enter the total volume of sales (metric tons are preferred but partners can select their own units), the total number of participants (assisted producers or assisted firms), and the total value of reporting year sales in USD. Rational or justification for indicator (optional): Value (in US dollars) of sales from assisted farmers and firms in targeted markets is a measure of the competitiveness of those actors. This measurement also helps track strengthened and expanded access to markets and progress toward engagement by farmers and firms throughout the value chain. Improving markets will contribute to Objective One of Inclusive and Sustainable Agriculture-led Economic Growth, which in turn will reduce poverty and thus achieve the goal. This indicator relates to IR 2: Strengthened and Expanded Access to Markets and Trade in the GFSS results framework. Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Data from assisted producers and firms may need to be collected separately. Ideally, this indicator will be collected directly from a census of all participant farms and firms, from recorded sales data and/or farm/firm records. A sample survey-based approach for participant producers within the geographic area reached by the assisted market is also acceptable. Method of data collection and construction: Census of participant firms and sample survey from participant producers Frequency/Timing of Data Collection: Annually Reporting Frequency: Annually Estimated cost of data collected: Part of routine M&E reporting costs Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD 39 Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): CHANGES TO INDICATOR Changes to Indicator: Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE IIM&E Coordinator and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinator Reporting of Data: Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: Baseline data reflects value of sales in the year prior to programming and should be collected through records of assisted firms and/or a sample survey of producers via recall. PERFORMANCE INDICATOR VALUES Notes Baseline Values FY18 0 Year Targets Actuals Notes FY 19 Maize: $43,243,67 Soy: $4,592,365 FY 20 Maize: $8,704,000 Soy: $920,000 THIS SHEET LAST UPDATED ON: June 3, 2019 40 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Name of Indicator: EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___ FY 2019 and FY2020 DESCRIPTION Precise definition(s): his indicator sums the total U.S. dollar value of debt (both cash and in-kind loans) and non-debt financing, such as equity financing, disbursed during the reporting year as a result of USG-assistance to producers (individual farmers, fishers, cooperatives, etc.), input suppliers, transporters, processors, other MSMEs, and larger enterprises that are in a targeted agricultural value chain and are participating in a USG-funded activity. USG assistance may consist of technical assistance, insurance coverage, guarantee provision, or other capacity-building and market-strengthening activities to producers, organizations and enterprises. The indicator counts the value of non-debt financing and both cash and non-cash lending disbursed to the participant, not financing merely committed (e.g., loans in process, but not yet available to the participant). Debt: Count cash loans and the value of in-kind lending. For cash loans, count only loans made by financial institutions and not by informal groups such as village savings and loan groups that are not formally registered as a financial institution [1]. However, the loans counted can be made by any size financial institution from microfinance institutions through national commercial banks, as well as any non-deposit taking financial institutions and other types of financial NGOs. In-kind lending in agriculture is the provision of services, inputs, or other goods up front, with payment usually in the form of product (value of service, input, or other good provided plus interest) provided at the end of the season. For in-kind lending, USAID may facilitate in-kind loans of inputs (e.g., fertilizer, seeds) or equipment usage (e.g. tractor, plow) via implementing partners or partnerships. NOTE: formal leasing arrangements should be captured in non-debt financing section below), or transport with repayment in kind. Non-Debt: Count any financing received other than cash loans and in-kind lending. Examples include: equity, convertible debt, or other equity-like investments, which can be made by local or international investors; and leasing, which may be extended by local banks or specialized leasing companies. This indicator also collects information on the number of participants accessing agriculture-related financing as a result of USG assistance to assist with indicator interpretation. Count each participant only once within each financial product category (debt and non-debt), regardless of the number of loans or non-debt financing received. However, a participant may be counted under each category (debt and non-debt) if both types of financing were accessed during the reporting year. Note: This indicator is related to indicator EG.3.1-14 Value of new USG commitments and private sector investment leveraged by the USG to support food security and nutrition. Where there is a USG commitment such as a grant, guarantee provision, or insurance coverage, the resulting value of debt or non-debt financing accessed by participants of USG-funded activities should be counted under this indicator. The total value of the private sector investment leveraged should be counted under indicator EG.3.1- 14. These two indicators will not be aggregated, thus there is no “double counting.” [1] The value of loans accessed through informal groups is not included because this indicator is attempting to capture the systems-level changes that occur through increased access to formal financial services. Unit of Measure: US Dollar Disaggregated by: Level 1: Type of financing accessed: Debt and Non Debt Level 2. Type of debt: Cash, In-kind Repeat for Debt or Non debt financing: Size of recipient: Individuals/microenterprises; Small and medium enterprises; Large enterprises and corporations. Microenterprises employed <10 people in the previous 12 months, small enterprises employed 10-49 people, medium enterprises employed 50-249 individuals and large enterprises and corporations employed >250 individuals. Sex of producer or proprietor(s): Male, female, mixed If the enterprise is a single proprietorship, the sex of the proprietor should be used for classification. If the enterprise has more than one proprietor, classify the firm as Male if all of the proprietors are male, as Female if all of the proprietors are female, and as Mixed if the proprietors are male and female. Age: 18-29, 30+, mixed If the enterprise is a single proprietorship, the age of the proprietor should be used for classification. If the enterprise has more than one proprietor, classify the firm as 18-29 if all of the proprietors are aged 18-29, as 30+ if all of the proprietors are aged 30+, and as Mixed if the proprietors are from both age groups. Rationale or Justification for Indicator: 41 Increased access to finance demonstrates improved inclusion in the financial sector and appropriate financial service offerings. This in turn will help to expand markets and trade (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. This indicator is linked to IR.2: Strengthened and expanded access to markets and trade of the Global Food Security results framework Type: Output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Financial institution and investor records of participants Method of Data Collection and Construction: Financial institution and investor records or survey of activity participants Frequency/Timing of Data Collection: Quarterly, according to crop cycle Reporting Frequency: Quarterly Estimated Cost of Data Acquisition: Part of routine M&E reporting costs Individual responsible at USAID: AOTR, USAID M&E specialist Individual responsible for providing data to USAID: ACDI-VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment and Name of Reviewer: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments: Annually CHANGES TO INDICATOR Changes to Indicator: Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VCOA M&E Coordinator Presentation of data: Table and Annual Report narrative Review of Data: ACDI/VOCA M&E Manager and HQ M&E Team Reporting of Data: Quarterly, Semi-Annual/Annual Performance Monitoring Report Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Value FY18 0 YEAR Targets Actuals FY19 $120,000 FY20 $20,000 THIS SHEET LAST UPDATED ON: June 3, 2019 42 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-2 : Strengthened resilience among people and systems Intermediate Result 1.1: Strengthened capacity for advocacy and activity implementation Indicator:EG.3.2-29 Number of organizations with increased performance improvement with USG assistance Is this an Annual Report indicator? No ___ Yes __x__, for Reporting Year(s) FY 19 and FY20 DESCRIPTION Precise definition(s): This indicator measures whether USG-funded capacity development efforts have led to improved organizational performance in organizations receiving organizational performance improvement support. Capacity is the ability of people, organizations and society as a whole to manage their affairs successfully. Capacity development is the process of unleashing, strengthening and maintaining such capacity. Capacity is a form of potential; it is not visible until it is used. Therefore, performance is the key consideration in determining whether capacity has changed. Organizational performance improvement reflects a deliberate process undertaken to improve execution of organizational mandates and may include adjusting internal processes, addressing internal or external obstacles, human capital development, establishing linkages, or other relevant efforts. This indicator should only be used when an activity intentionally allocates resources (human, financial, and/or other) toward strengthening organizational capacity and undergoes a deliberate performance improvement process that is documented. The activity’s theory of change should reflect how the process of performance improvement is predicted to improve the outputs or outcomes that an organization produces. With support from the implementing partner, each organization being supported should determine how it will define and monitor performance improvement based on its organizational mandate and strategic goals and objectives. The implementing partner can count an organization under this indicator if: (a) an organization demonstrates that it has undergone and documented at a minimum the following four steps: 1. Obtain organizational stakeholder input to define desired performance outputs or outcomes. 2. Analyze and assess performance gaps (the difference between desired performance and actual performance). 3. Select and implement performance improvement solutions. 4. Monitor and evaluate performance, and an organization demonstrates that its targets for performance improvement have been met or achieved. The implementing partner sets annual targets for this indicator based on how many organizations will have improved organizational performance each year. Organizations may choose their preferred approach and/or tools for documenting the process and achievement of performance improvement targets. The approach and/or tool may be one that has been or is being used by the organization prior to the implementation of USG-funded activities. One example of a broad performance improvement and measurement tool that USAID has endorsed is the Organizational Performance Index (OPI), which can be used for assessing performance across multiple domains. Other examples include university accreditation self-assessments, a balanced scorecard approach, Six Sigma, and many others. Data quality, including reliability and validity of the approach and/or tool, should be documented to the extent possible in the Activity MEL Plan. Unit of Measure: Number Disaggregated by: Type of Organization • Research and educational • Producer associations • Extension organizations • Private sector firms • Government agencies • Non-governmental and not-for profit organizations Type: Outcome Rationale or Justification for Indicator: 43 Capacity development is essential to achieving and sustaining the U.S. Government’s Global Food Security Strategy (GFSS) objectives of inclusive and sustainable agriculture-led economic growth, resilience among people and systems, and a well￾nourished population. This indicator data and supplementing documentation will provide the Feed the Future initiative with a better understanding about the scope and scale of organizational capacity development efforts within the Feed the Future Zones of Influence, as well as outside the Feed the Future ZOIs at organizations that play a significant role in contributing to agriculture-led economic growth (e.g., organizational capacity strengthening of a ministry of agriculture or an agricultural university outside of the ZOI). This indicator data also provides information about which types of organizational performance support its partners need. This indicator is linked to CCIR 6: Improved human, organizational, and system performance of the Global Food Security results framework. Direction of change: Higher is better PLAN FOR DATA COLLECTION Data Source(s): Organization. This includes organizations within the Feed the Future ZOIs, as well as organizations outside the Feed the Future ZOIs that play a significant role in contributing to agriculture-led economic growth, e.g., organizational capacity strengthening of a ministry of agriculture or an agricultural university outside of the ZOI. Method of Data Collection and Construction: Data should be collected using appropriate methods (including relevant questionnaires or other data documentation methods.) Tools and data collection methods should be documented in the Activity Monitoring, Evaluation, and Learning (MEL) Plan. Frequency/Timing of Data Collection: Quarterly Frequency of Reporting: Quarterly Estimated Cost of Data Acquisition: Part of routine M&E reporting costs Individual responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments: Annually CHANGES TO INDICATOR Changes to Indicator: This indicator title changed from 4.5.2(7): “Number of individuals who have received USG supported short￾term agricultural sector productivity or food security training” to “EG. 3.2-1 Number of individuals who have received USG supported short-term agricultural sector productivity or food security training” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE II M&E Coordinator Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinator and ACDI/VOCA headquarters M&E Reporting of Data: Quarterly /Semi-annual/Annual Performance Monitoring Report (PMR) Note on baseline/Targets: Although this is an outcome indicator, the baseline value at the start of activity implementation should be zero because the indicator measures the number of organizations that have improved performance each year (as opposed to measuring a performance improvement score). Organizations can be counted in subsequent years, as long as their performance improved relative to the previous year. PERFORMANCE INDICATOR VALUES Notes Baseline Value FY 18 44 Year Targets Actuals FY19 20 FY20 NA THIS SHEET LAST UPDATED ON: June 3, 2019 45 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Project Output: Indicator EG.3.2-19: Number of individuals participating in group-based savings, micro-finance or lending programs with USG assistance Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) __ FY19 and FY20 DESCRIPTION Precise Definition(s): This indicator tracks individual participation in group-based savings, microfinance, or lending programs. This performance indicator, along with the similar ZOI indicator, tracks financial inclusion. Group-based savings programs are formal or informal community programs that serve as a mechanism for people in poor communities with otherwise limited access to financial services to pool their savings. The specific composition and function of the savings groups group vary and can include rotating loan disbursement. The definition is inclusive of all of the different types of group based savings programs. According to the World Bank, microfinance can be defined as approaches to provide financial services to households and microenterprises that are excluded from traditional commercial banking services. Typically, these are low-income, self-employed or informally employed individuals, with no formalized ownership titles on their assets and with limited formal identification papers [1] [2]. This indicator captures the uptake of financial services by the participants of USG-funded activities. It should be noted that the indicator captures the numbers who are participating but does not say anything about the intensity of participation. Furthermore, while summing the number of individuals participating in savings and credit programs is acceptable as a measure of financial inclusion, saving and credit are functionally different and the numbers participating in each type of program should not be compared against each other. Savings groups have added benefits, like fostering social capital, that also contribute to resilience and a household’s ability to manage risk and protect their well-being. [1]For more on microfinance please refer to the World Bank working paper on microfinance. [2]World Bank FINDEX http://www.worldbank.org/en/programs/globalfindex . Unit of Measure: US Dollar Disaggregated by: • Sex: Female, Male • Age: 18-29, 30+ • Product Type: Savings, Credit • Duration: o New (participated in a savings, micro-finance or lending program for the first time in the reporting year); o Continuing (participated in a savings, micro-finance or lending program in a previous reporting year and continues to participate in a savings, micro-finance or lending program in the current reporting year) Rationale or Justification for Indicator: Access to group- based savings, microfinance, or lending programs is one pathway to a household's financial inclusion. Access to financial services is important for households to diversify their livelihood strategies, protect well-being outcomes and manage risks. This indicator links to IR.6: Improved Adaptation to and Recovery from Shocks and Stresses in the GFSS Results Framework. Type: Output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Activity level, Activity participants Method of Data Collection and Construction: Participant-based survey, activity records Frequency/Timing of Data Collection: Annually Frequency of reporting: Annually Estimated Cost of Data Acquisition: Part of routine M&E reporting costs Individual responsible at USAID: AOTR, USAID M&E specialist 46 Individual responsible for providing data to USAID: ACDI-VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments: Annually CHANGES TO INDICATOR Changes to indicator: Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VCOA M&E Coordinator Presentation of data: Table Review of Data: ACDI/VOCA M&E Manager and HQ M&E Team Reporting of Data: Annual Performance Monitoring Report Notes on Baselines/Targets: Baseline is Zero PERFORMANCE INDICATOR VALUES Notes Baseline value F18 Year Targets Actuals FY19 4,000 FY20 1,000 THIS SHEET LAST UPDATED ON: June 3, 2019 47 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Indicator Title: GNDR-2 Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___ FY 2019 and FY2020 DESCRIPTION Precise definition(s): This performance indicator, “Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources” is a cross cutting U.S. government foreign assistance indicator (indicator GNDR-2), developed to measure performance related to increasing access to productive economic resources by women. The indicator reference sheet for GNDR-2 can be found under the cross cutting program category for gender, on the U.S. Department of State’s Standard Foreign Assistance Indicators website (https://www.state.gov/f/indicators/). For ease of reference, the indicator definition for GNDR-2 can also be found below. Feed the Future Implementing Partners (IPs) and Post teams have the option of reporting directly on GNDR-2 using data that is aligned with the standard GNDR-2 definition, or, to reduce IP burden, can use data from one of the three Feed the Future performance indicator listed under “REPORTING NOTES” below. U.S. government foreign assistance indicator definition for GNDR-2: 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; • workforce development programs that have job placement activities; • programs that build assets such as land redistribution or titling; housing titling; agricultural programs that provide assets such as livestock; or programs designed to help adolescent females and young women 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). The unit of measure will be a percentage expressed as a whole number: • The 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. 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. Unit of Measure: Percentage expressed as a whole number Disaggregated by: None Rationale or Justification for Indicator 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. Women comprise 43 percent of the agricultural labor force in developing countries, yet face persistent barriers limiting their access to productive economic resources. Closing the gap in women’s access to productive economic resources is necessary for Feed the Future to achieve the objective of inclusive and sustainable agricultural-led economic growth. Ending extreme poverty, a goal outlined in the U.S. Government’s Global Food Security Strategy, the Sustainable Development Goals, and USAID's Vision to Ending Extreme Poverty, will only be achieved if women are economically empowered. GNDR-2 can be used to report on applicable activities under objectives in the Feed the Future Results Framework that are designed to increase access to productive economic resources. As a cross-cutting gender indicator, this indicator can also be used to report on applicable activities under any of the Program Categories in the SPSD. 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. 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. This indicator is linked to the Global Food Security Strategy results framework CCIR 3: Increased gender equality and female empowerment. Type: output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Activity records of OBs and other key actors 48 Method of Data Collection and Construction: Participant- based Survey, Activity records Frequency/Timing of Data Collection: Annually Frequency of Reporting: Annually Estimated Cost of Data Acquisition: Part of routine M&E reporting costs Individual responsible at USAID: AOTR, USAID M&E specialist Individual responsible for providing data to USAID: ACDI-VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments: Annually CHANGES TO INDICATOR Changes to Indicator: New indicator Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E specialist will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VCOA M&E Coordinator Presentation of data: Table Review of Data: ACDI/VOCA M&E Manager and HQ M&E Team Reporting of Data: Annual Performance Monitoring Report Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Baseline value FY18 0 Notes Year Targets Actuals FY19 20% FY 20 20% THIS SHEET LAST UPDATED ON: June 3, 2019 49 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Indicator Title: YOUTH-3 Percentage of participants in USG-assisted programs designed to increase access to productive economic resources who are youth (15-29) Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___, FY 2019 and FY2020 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. Based on the Feed the Future youth technical guide, the 10-29 age range is used for youth while keeping in mind the concept of “life stages,” specifically 10-14, 15-19, 20-24, and 25-29 years as put forward in the USAID Youth in Development Policy. Feed the Future activities will primarily cover working age youth ages 15-29. Partners may have different age range definitions for youth based on their specific country contexts. 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: • value chain activities and market strengthening activities working with micro, small, and medium enterprises; • financial inclusion programs that result in increased access to finance, including programs designed to help youth set up savings accounts • workforce development programs that have job placement activities; • programs that build or secure access to physical assets such as land redistribution or titling; and programs that provide assets such as livestock This indicator does NOT track access to services, such as business development services or agriculture, food security or nutrition training. The numerator and denominator must also be reported as data points in the FTFMS. Feed the Future Implementing Partners (IPs) and Post teams have the option of reporting directly on this indicator using data that aligns with the indicator definition, or, to reduce IP burden, can use data from one of the two Feed the Future performance indicators listed below: 1. From indicator EG.4.2-7 Number of individuals participating in group-based savings, micro-finance or lending programs with USG assistance [IM-level]: For the numerator, use data on the number of youth participants. For the denominator, use the total number of participants. Do not include “disaggregates not available”. From indicator EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance [IM-level]: For the numerator, use data on the number of enterprises with all youth proprietors. For the denominator, use the total number of enterprises. Do not include enterprises with a mix of youth (age 15-29) and adults (age 30+) or “disaggregates not available”. To avoid double counting, IPs that are reporting on more than one of the indicators listed above should use data from the indicator with the largest number of participants in the denominator. Unit of Measure: Percent expressed as a whole number. Disaggregated by: None Rationale or Justification for Indicator: 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 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. Type: Output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Activity-level indicator results. Method of Data Collection and Construction: Participants based survey and VSLA and OBs activity records Frequency/Timing of Data Collection: Quarterly. Reporting Frequency: Quarterly Estimated Cost of Data Collection: Part of routine M&E reporting costs Individual responsible at USAID: AOTR, USAID M&E specialist Individual responsible for providing data to USAID: ACDI-VOCA Chief of Party 50 Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment: TBD Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments: Annually CHANGES TO INDICATOR Changes to Indicator: NA Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VCOA M&E Coordinator Presentation of data: Table Review of Data: ACDI/VOCA M&E Manager and HQ M&E Team Reporting of Data: Quarterly, Semi-Annual/Annual Performance Monitoring Report OTHER NOTES Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Baseline Value FY19 0 Notes YEAR Target Result FY19 12 FY20 15 THIS SHEET LAST UPDATED ON: June 3, 2019 51 Performance Indicator Reference Sheet Goal: Sustainable, resilient and incessive markets SO: Inclusive and sustainable agricultural led economic growth Intermediate Result IR-1.2: Increased Market Access and Trade Name of Indicator: 0.00 Number of value chain actors accessing finance (CI) Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 and FY2017 and FY2018 DESCRIPTION Precise Definition(s): Loan or credits provided by financial institution and VSLAs for start-up business and/or business expansion. Examples of financial services for value chains actors include, but are not limited to, loans, savings schemes, and insurance plans obtained from: Private banks, Microfinance institutions and VSLAs Unit of Measure: Number Disaggregated by: 1. Gender-Male and Female, 2. Value Chain Actor Type Rational or justification for indicator (optional): Type: Output Direction of change: Higher is better PLAN FOR DATA COLLECTION Data Source(s): Records from Microfinance partners and microenterprises Method of data collection and construction: Examination and organization of Microfinance service data Frequency/Timing of Data Collection: Quarterly Reporting Frequency: Quarterly Estimated cost of data collection: Individual(s) responsible at USAID: AOTR and USAID/Ghana M&E Specialist Individual responsible for providing data to USAID: ACDI/VOCA Chief of Party Location of Data Storage: ACDI/VOCA ADVANCE II MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): annually CHANGES TO INDICATOR Changes to Indicator: Indicator scope expanded to include loans or credit from VSLAs as well as Loan or credits provided by financial institution for start-up business and/or business expansion. Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE II M&E team will conduct annual data quality reviews. Through this review, we will assess the validity, reliability and timeliness of data. Based on the review, we will modify data collection methodology as needed and update the M&E Plan accordingly. The M&E Coordinator will develop a Data Quality Strategy specific to the ADVANCE II project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE II M&E Coordinator Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinators1and ACDI/VOCA headquarters M&E 52 Reporting of Data: Quarterly/Semi-annual/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Year Targets Actuals Notes Baseline Year FY18 0 FY19 50 FY20 0 THIS SHEET LAST UPDATED ON: June 3, 2019 53 Annex 4: Implementation plan for MEL activities - May 2019 to April 2020 Category and Task Targets Respon sibility MAY JUNE JULY AUG SEPT OCT NOV DEC JAN FEB MA RCH APRIL Project Support: Monitoring and Evaluation 1.1 Staffing and training 1.1.1 Provide additional support to M&E data collection through interns 13 Interns hired to support M&E 1.1.2 Provide support to OB network data management through interns 1 Orientation conducted 1.2 Organize outreach materials and knowledge fora to share project results 1.2.1 Prepare and print communication and other materials 10 bundles of communication material printed 1.2.2 Organize regional fora 3 Regional forums organized 1.2.3 Organize national forum One National forum organized 1.3 Submit updated M&E plan 1.3.1 Develop draft MEL plan MEL plan developed 1.3.2 Submit draft plan to USAID Draft MEL plan submitted to USAID 1.3.3 Receive feedback/comments from USAID MEL plan reviewed and revised 1.3.4 Finalize and submit revised MEL plan Finalized MEL Plan submitted to USAID 1.4 Database design, data capture, storage and use 1.4.1 Design M&E data collection forms M&E data collection forms developed 1.4.2 Design M&E database M&E database developed 1.4.3 Train all field staff and OB Networks on M&E and quality data collection and management processes 20 Staff and at least 70 OBs trained 1.5 Data collection validation and entry 1.5.1 Profiling actors as they are identified Actors profiles updated or augmented 1.5.2 Routine data collection and entry by all staff Routine data collected and electronically stored 54 1.5.3 Design annual productivity survey instrument Annual productivity surv ey instrument designed 1.5.4 Conduct first phase of productivity survey First phase of annual productivity survey completed 1.5.5 Conduct second phase of productivity survey Second phase of annual productivity survey completed 1.5.6 Conduct field data quality review Periodic data quality assessments conducted. 1.5.7 Conduct data quality review by Accra Periodic data review by Accra team conducted 1.5.8 Conduct data quality review by ACDIVOCA HQ Periodic data review by ACDIVOCA HQ team conducted 1.6 Conduct technical review meetings and report on activities 1.6.1 Conduct monthly review meeting of technical staff Monthly review meeting of field technical staff conducted 1.6.2 Conduct quarterly technical review meeting Quarterly Technical Review Meetings conducted 1.6.3 Prepare and submit quarterly and annual reports to USAID Quarterly reports completed and submitted to USAID. Annual report completed and submitted. 1.6.4 Conduct monitoring visits by Snr. Management Accra Regular monitoring visit by Snr Management (Accra) conducted. 1.6.5 Conduct monitoring visits by HQ Regular monitoring visit by Snr Management (HQ) conducted. 1.7 Prepare end of project evaluation by USAID/METSS 1.7.1 Conduct study on OB networks and share report Report on study of OB networks completed and submitted by consultant 1.7.2 Conduct study on gender and youth and share report Updated report on study on gender and youth completed and submitted by consultant 1.7.3 Conduct study on use of ICT and share report Report on study of use of ICT in value chains completed and submitted by consultant 1.7.4 Compile and prepare documents and other materials and systems required Required documents and other materials assembled. 55 for final evaluation by USAID/METSS 1.7.5 Support USAID METSS to conduct final evaluation Final project Evaluation completed by USAID METSS. 1.8 Carry out technical and office close out 1.8.1 Work with ACDI VOCA HQ towards project closeout HQ staff participates in close-out process 1.8.2 Organize in-house meetings on closeout process Internal close-out meetings conducted 1.9 Carry out administrative close out and asset disposition 1.9.1 Compile asset list and develop a disposition plan Asset list and disposition plan finalised 1.9.2 Implement disposition plan based on approval from USAID Disposition of assets completed 1.10. Prepare and submit final project report Final project report submitted