SUBMITTED TO: AOR, USAID/GHANA P.O. Box 1630 Accra, Ghana packah@usaid.gov SUBMITTED BY: ACDI/VOCA Chief of Party WITH: Association of Church Development Projects (ACDEP) PAB Consult TechnoServe Revised version – September 2016 This report 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............ 6 OPERATIONAL CONTEXT AND UNDERLYING CAUSALITY FRAMEWORKS..................................................... 7 PROJECT GOALS AND OBJECTIVES ................................................................................................................ 7 TIMELY PROJECT MONITORING ..................................................................................................................... 8 MONITORING AND EVALUATION ..................................................................................................................... 8 Data Collection .......................................................................................................................................... 16 ADVANCE Database................................................................................................................................... 17 Collaboration with Donors and Stakeholders ........................................................................................... 18 Reporting................................................................................................................................................... 18 KNOWLEDGE MANAGEMENT AND LEARNING................................................................................................ 18 ADVANCE KM&L goals and objectives....................................................................................................... 20 Guiding principles for KM&L...................................................................................................................... 20 KM&L implementation plan ...................................................................................................................... 21 Tracking KM&L activities ........................................................................................................................... 26 PROJECT ROLES AND RESPONSIBILITIES..................................................................................................... 28 Staffing and Management......................................................................................................................... 28 DATA QUALITY REVIEWS.............................................................................................................................. 31 EVALUATION APPROACH AND ASSESSMENTS ............................................................................................ 31 Baseline.................................................................................................................................................... 31 Midterm Evaluation................................................................................................................................. 32 Final Evaluation....................................................................................................................................... 32 Annual Surveys ....................................................................................................................................... 32 Sampling Method and Size ................................................................................................................... 33 RISKS AND ASSUMPTIONS............................................................................................................................ 33 Annex 1: FY targets............................................................................................................................................ 36 Annex 2: Indicators Targets Revisions............................................................................................................... 39 Annex 3: Performance Indicator Reference Sheets .......................................................................................... 43 Annex 4: First year’s implementation plan for MEL activities........................................................................... 74 2 ACRONYMS ADVANCE ATT CLA Agricultural Development and Value Chain Enhancement Agricultural Technology Transfer Project Collaborating, Learning and Adapting CIP CAADP COP Country Investment Plan Comprehensive Africa Agriculture Development Program Chief of Party DCOP Deputy Chief of Party FASDEP II Food and Agriculture Sector Development Policy FBO FinGAP Farmer Based Organization Financing Ghana’s Agriculture Project FTF GCAP GOG ICT IR ISSER Feed the Future Ghana Commercial Agriculture Policy Program Government of Ghana Information and Communication Technology Intermediate Result Institute for Statistical, Social and Economic Research KM Knowledge Management MEL Monitoring, Evaluation and Learning MELL Monitoring, Evaluation and Monitoring Leadership METSS MPEP Monitoring and Evaluation Technical Support Services Microenterprise and Private Enterprise Promotion MoFA Ministry of Food and Agriculture NF PMP Nucleus Farmer Performance Monitoring Plan RING RF TOC WEAI Resiliency in Northern Ghana Results Framework (RF) Theory of Change Women's Empowerment in Agriculture Index (WEAI) 3 INTRODUCTION TO THE PROJECT The Agricultural Development and Value Chain Enhancement Project (ADVANCE) is the main value chain project of the USAID Ghana Mission’s Feed the Future (FTF) program. The project was awarded to ACDI/VOCA and three consortium partners (Technoserve, ACDEP and PAB Consult) on 5 th February 2014 and will end on 30th September 2018. ADVANCE contributes to the intermediate results of USAID’s FTF Strategic Objective 3 (Improved nutritional status, especially of women and children) and Strategic Objective 4 (Inclusive agriculture sector growth). The overall goal of ADVANCE is to increase competitiveness of the maize, rice and soybean value chains. The intermediate results are; (i) increased productivity in targeted commodities, (ii) increased market access and trade, and (iii) strengthened local capacity (see details in the results framework, Figure 1). The ADVANCE team will achieve the stated goal of improving value chain competitiveness in the three commodities and directly benefit 100,000 value chain actors, mostly smallholder farmers through increased gross margins and incomes by leveraging new private sector investment. The project team will achieve this through a multidimensional strategic framework that strengthens incentives for investment, builds local capacity and broadens and catalyzes relationships to increase agricultural productivity, expand access to markets and trade and improve the enabling environment. Through the judicious use of technical assistance, training, dynamic facilitation and cost-sharing grant funds the project team will ensure that private sector actors remain the drivers of change, while Government of Ghana (GOG) and local stakeholders are empowered to lead as facilitators through enhanced capacity building and learning . The approach is underpinned by the wealth of knowledge and established relationships developed over the last two years in northern Ghana implementing the first ADVANCE project. The ADVANCE 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 to staff and project stakeholders (partners, donors, host country government and beneficiaries) the details of how the management of ADVANCE will establish and implement a system to monitor, analyze, evaluate, and report on the results of the project to USAID. The MEL Plan details ADVANCE’s approach to promoting a learning culture and an applied monitoring and evaluation (M&E) system that promotes project quality, facilitates evidence-based decision making, sparks innovation and advances 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 RESULTS FRAMEWORK FTF's Ghana Objective Statement: Improve the livelihood and nutritional status of households in Ghana FTF's Ghana Intermediate Result 1: Increased Competitiveness of Major Food Value Chains ADVANCE II Developmental Hypothesis: The scaling up of strategic investments in targeted value chains that incentivize innovation and investment (while mitigating risks) will lead to the improved competiveness of agricultural value chains and increased incomes for male and female smallholders. Increased spending and investment on the part of male and female farmers and other value chains actors will multiply new opportunities both inside and outside of agriculture, offering the poor expanded opportunities in the rural non-farm sector and leading to reductions in poverty Critical Assumptions • Coordination With USAID and Non-USAID Programs •Supportive Enabling Environment • Market Demand • Farmers, Private sector, GOG and other stakeholders as Facilitator of Change Outcomes IR 1.1 • Strengthened systems for service Provision and input distribution • Strengthened incentives for smallholder Investment in new technology, services and practices • Increased adoption of improve d Productivity-enhancing technologies, Services and practices by women and men 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 and Become eligible for USAID funding Output IR 1.1 • Gross margins per hectare for selected crops under marketing arrangements • Number of private enterprises, FBOs, Women’s groups, and associations, receiving USG assistance • Number of individuals who have Received USG supported short-term Agricultural sector productivity or food Security trainings • Number of additional hectares under Improved technologies or management Practices Output IR 1.2 •Value of agricultural and rural loans •Numb r of jobs attributed to program •Value of new private sector investment in agriculture sector or value chain •Number of value chain actors trained (by type of actors) •Number of value chain actors accessing Finance •Number of microenterprise clients who are borrowers •Number of firms operating more Profitably Output IR 1.3 • Number of organizations, enterprises receiving capacity building support against key milestones •Number of organizations, Enterprises identified as high potential for future awards •Score, in percent, of combined key areas of organization capacity amongst USG direct and indirect local implementing partners Illustrative Activities IR 1.1: •Develop Out grower Business Management Program •Support NFs and Aggregators to facilitate out grower credit •Partner with UDS to launch NF Business Intern Program •Facilitate Lead Firm-Out grower Schemes •Build capacity of production service Providers •Increase access to mobile market Information services •Financial literacy for smallholders and FBOs •Develop and disseminate GAP and Conservation farming protocols •Facilitate commercial partners to Implement demonstrations •Collaboration with ICT and private sector to expand agricultural programming and services Illustrative Activities IR 1.2: •Capacity building of partner financial Institutions •Increase bankability of out grower businesses •GGC partnership to manage grains Warehouse receipting system •Improve investment in and access to PHH Equipment and storage facilities •Improve on-farm PHH practices Strengthen transport sector services •BDS provision to lead firms •Expand market linkages with lead firms and NFs •Launch of the Innovation and Investment Incentive (I3) Fund • Organize Agribusiness Fairs and International Investment Conferences •Increase smallholder capacity to market Collectively •Promote female FBO Leadership Illustrative Activities IR 1.3: •Conduct a policy advocacy assessment •Facilitate Advocacy Capacity Building for local institutions including FBOs, associations, and Other stakeholders •Build capacity in Grass-Roots Advocacy •Support GGC national level policy work on grades and standards, weights and measures, non-tariff barriers and cross border trade. •Facilitate investment through district and national investment plans •Facilitate women’s access to l and •Deliver Organizational Capacity Bui ling to build capacity so local organizations can become eligible for USAID funding •Local capacity building through Knowledge management and learning Government of Ghana Goal: Reduce poverty through accelerated agricultural investment and growth ADVANCE II Goal: Increased competitiveness of agricultural value chains Intermediate Result 1.1 Increased productivity in targeted commodities Intermediate Result 1.2 Increased Market Access and Trade Intermediate Result 1.3 Strengthened Local Capacity 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 5 THEORY OF CHANGE For ADVANCE, the theory of change posits that there are three functions of value chain competitiveness - agricultural productivity, market access and trade and enabling environment - that are catalyzed through three dimensions of competitiveness - clear incentives for investment, strong local capacity and mutually beneficial relationships. Within this multidimensional framework, ADVANCE will channel resources through nine specific outcomes utilizing four main implementation principles that impact both the functions and dimensions of value chain competitiveness. Underpinning the theory is that private sector actors, including men and women farmers, are the drivers of competitiveness, while the GOG and local stakeholders are empowered to lead as facilitators, catalyzed through the project’s capacity building, learning and investment, and innovation promotion. It is within this strategic framework that the ADVANCE technical approach has been designed. FIGURE 2: ADVANCE THEORY OF CHANGE 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 the learning environment for the project (see Figure 3). 6 Figure 3: ADVANCE's Adaptive Management System Involving a cycle of planning, implementation, monitoring, research, and subsequent re-examination of actions, it includes a series of feedback loops that provide managers and decision-makers with information on the premise of their choices, results of past management decisions and on present conditions. 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 effectiveness evaluation methodologies. 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 reviews are commonly 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 7 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, taking into account 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 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 to ensure optimal system performance. 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 Food and Agriculture Sector Development Policy (FASDEP II). Other strategies, policies, and initiatives considered in designing this MEL plan include: • Feed the Future, the USA Government's global hunger and food security initiative • USAID Forward: USAID’s Reform Agenda • USAID Evaluation Policy • USAID Ghana, Multi-Year Strategy to Feed the Future (FTF) • USAID Ghana, Feed the Future Strategy, Monitoring and Evaluation Plan • USAID Ghana’s Economic Growth office’s PMP • USAID Ghana and GOG Country Investment Plan (CIP) USAID’s economic growth office has designed a number of projects under the FTF initiative, including the Agricultural Technology Transfer Project (ATT), Financing Ghana’s Agriculture Project (FinGAP), Agricultural Policy Support Project, the Ghana Commercial Agriculture Policy Program (GCAP), and Resiliency in Northern Ghana (RING) Project. ADVANCE is one of the activities under USAID Ghana FTF Intermediate Result (IR) 1: increased competitiveness of agricultural value chains and it focuses on maize, rice and soybean in the north of Ghana. The other USAID activities, their overlap with ADVANCE, and potential challenges have been considered in developing this MEL plan. ADVANCE will coordinate with these other activities to leverage those that benefit our targeted value chains and identify and pursue synergies where there is potential for duplication. USAID Ghana will be instrumental in this process of coordination. Progress against the FTF objectives is measured based on the FTF Results Framework and accompanied by standard FTF performance indicators as updated in September 2013. PROJECT GOALS AND OBJECTIVES The purpose of the ADVANCE project is to improve the competitiveness of agricultural value chains in the North of Ghana. ADVANCE will achieve this purpose by means of three sub-purposes: 8 Sub-purpose 1 - Increased agricultural productivity of targeted commodities Sub-purpose 2 - Increased market access and trade of targeted commodities Sub-purpose 3 - Strengthen local 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 competiveness 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 ACDI/VOCA has developed a multilayered monitoring system that will generate information and analysis that will feed into the learning system and can be used to refine designs and introduce improvements with the goal of achieving meaningful and sustainable results, while providing the project with a powerful tool for adaptive management. The ADVANCE team will develop a multilayered monitoring system that will include collecting routine output data through standardized tools and annual surveys to measure outcome indicators, use various qualitative and quantitative methods needed to gather impact data or investigate unexpected results. The team will also collect and analyze stories describing the most important project outcomes. In addition, to the extent possible, we will triangulate our data and seek secondary data from other stakeholders including the GOG. We will use annual publication on agricultural performance from MoFA (facts and figures) and the Institute for Statistical, Social and Economic Research (ISSER) annual publication on the state of the Ghanaian economy, both of which usually contain data and information on the agricultural sector. 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. 9 Table 1: ADVANCE Performance Monitoring Plan # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 Indicator Key: I: Impact Indicator OC: Outcome Indicator OP: Output Indicator FTF: Feed the Future indicator F: F System Indicator CI: ADVANCE Custom Indicator Goal : Increased the competitiveness of agricultural Value chains in Ghana OP1 CI Number of direct project beneficiaries Definition: An individual is a direct beneficiary if s/he comes into direct contact with the set of interventions (goods or services) provided by the project. 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 beneficiary. Individuals who receive training or benefit from program￾supported technical assistance or service provision are considered direct beneficiaries. Unit of measure: Number Regular Beneficiary activity records into a database. Sex and region Data recorded and reported quarterly 0 LOP: 113,000 45% women IR 1.1 Increased productivity of targeted commodities OC1 FTF Gross margins per hectare for selected crops (in GHS) under marketing arrangements fostered by the activity Definition: The gross margin is the difference between the total value of production of the agricultural product (crop) and the cost of producing that item, divided by the total number of units in production. Gross revenue = average price x total production Net revenue = gross revenue - purchased input cost Gross margin = net revenue divided by area planted Unit of measure: US dollar 1) Baseline and impact Evaluation. 2) Annual survey in conjunction with data collected from a sample of monitored farmers Targeted Value chain and Sex of farmers Data recorded and reported annually Maize Male: 277.21 Female: 289.76 Rice Male: 259.4 Female: 249.98 Soy Male: 316.02 Maize Male: 840 Female: 790 Rice: Male: 1,400 Female: 1,250 Soy Male: 700 Female: 600 1 Targets were revised based on the baseline survey findings and FY14 and FY15 achievements. FY targets are presented in Annex 1 10 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 3) Secondary sources Female: 212.86 OC2 FTF Number of farmers and others who have applied improved technologies and management practices This indicator measures the number of farmers, individual processors (not firms), rural entrepreneurs, managers and traders, natural resource managers, etc. that applied improved technologies and management practices promoted by ADAVANCE II. Annual survey Value chain actor type Technolo gy type Sex Data recorded and reported annually 0 101,700 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 will be counted. Unit of Measure: Number Survey of a sample of targeted individuals; Project or association records, farm records Type of technolog y, Sex of farmers Seasonal, according to the crop cycle 0 312,200 OC4 FTF Number of private enterprises (for profit), producers organizations, water users associations, women's groups, trade and business associations, and Definition: Total number of private enterprises (processors, input dealers, storage and transport companies) producer associations, cooperatives, water users associations, women‘s groups, trade and business associations and community-based organizations (CBOs), including those focused on natural resource management, that applied improved technologies or management practices in areas including management (financial, planning, human resources), member services, Records from assistance sheets Type of organizati on New vs Continuin g Data recorded and reported quarterly 0 450 11 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 community￾based organizations (CBOs) that applied improved technologies or management practices as a result of USG assistance procurement, technical innovations (processing, storage), quality control, marketing, etc. as a result of USG assistance in this reporting year. Unit of measure: Number OP2 FTF Number of private enterprises (for profit), producers organizations, water users associations, women's groups, trade and business associations, and community￾based organizations (CBOs) receiving USG assistance Definition: Total number of private enterprises (processors, input dealers, storage and transport companies) producer associations, cooperatives, women‘s groups, trade and business associations and community-based organizations (CBOs) receiving assistance from ADVANCE. Assistance can include any help provided to either type of organization to expand coverage, services provided, information, etc. Some examples are organizational capacity building, training, other technical assistance, provision of supplies and materials, encouragement and motivation for improvements, etc. Unit of measure: Number Records from assistance sheets Type of organizati on New vs Continuin g Data recorded and reported quarterly 0 600 OP3 FTF Number of individuals who have received USG supported short-term Definition: The number of individuals to whom significant knowledge or skills have been imparted through interactions that are intentional, structured, and purposed for imparting knowledge or skills should be counted. This includes farmers, and Records from training attendance sheet. Type of individual Sex and region Data recorded and reported quarterly 0 80,000 12 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 agricultural sector productivity or food security trainings other primary sector producers who receive training in a variety of best practices in productivity, post-harvest management, linking to markets, etc. It also includes rural entrepreneurs, processors, managers and traders receiving training in application of new technologies, business management, linking to markets, etc., and training to extension specialists, researchers, policymakers and others who are engaged with ADVANCE Unit of measure: Number IR 1.2 Increased Market Access and Trade OC5 FTF Value of incremental sales Definition: This indicator will collect both volume (in metric tons) and value (in US dollars) of purchases from smallholders of targeted commodities for its calculation. The value of incremental sales indicates the value (in USD) of the total amount of agricultural products sold by farm households relative to a base year and can be calculated based on the total value of sales of a product (crop, animal, or fish) during the reporting year minus the total value of sales in the base year. Unit of measure: Value of sales (USD) 1) Baseline and impact Evaluation. 2) Annual survey in conjunction with data collected from a sample of monitored farmers 3) Secondary sources Targeted Value chain Data recorded and reported annually Maize: 466,294 Rice: 369,729 Soya: 319,593 Maize: $53,840,000 Rice: $9,730,000 Soya: $4,310,000 OC6 Number of firms (excluding farms) or NGOs engaged in agricultural and food Definition: Number of firms supported by ADVANCE that have higher net profit in the reporting year than the previous reporting year. Net profit ($) = Sales revenue ($) -Total costs ($) Unit of measure: Number Data will collected from all the MSME/Firms supported using a survey Targeted Value chain Data recorded and reported annually 0 100 13 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 security￾related manufacturing and services now operating more profitably (at or above cost) because of USG assistance questionnair e OP4 FTF Value of agricultural and rural loans Definition: This indicator sum loans made (i.e. disbursed) during the reporting year to producers (farmers, fishers, etc.), input suppliers, transporters, processors, and loans to other MSMEs in rural areas that are in a targeted agricultural value chain, as a result of USG assistance. The indicator counts loans disbursed to the recipient, not loans merely made (e.g. in process, but not yet available to the recipient). The loans can be made by any size financial institution from micro-credit through national commercial bank, and includes any type of micro-finance institution, such as an NGO. Unit of measure: US dollars Secondary sources by reviewing financial institution records Type of loan recipient and by sex Data recorded and reported quarterly 0 4,300,000 OP5 F Value of new private sector investment in agriculture sector or value chain Definition: Investment is defined as any use of private sector resources intended to increase future production output or income, to improve the sustainable use of agriculture-related natural resources (soil, water, etc.), to improve water or land management, etc. “Private sector” includes any privately-led agricultural activity managed by a for-profit formal company. A CBO or NGO resources may Secondary sources (from the private sector engaged I with ADVANCE) None Collected and reported annually TBD 4,000,000 14 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 be included if they engage in for-profit agricultural activity. “Investments reported should not include funds received by the investor from USG as part of any grant or other award. New investment directly encouraged or facilitated by activities funded by the ADVANCE will be counted. Unit of measurement: U.S. dollars OP6 CI Number of value chain actors accessing finance Definition: Loan or credits provided by 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, Microfinance institutions. Unit of measurement: Number Records from microfinance partners and microenterpr ises Region, type of actor and sex Data recorded and reported quarterly 0 300 IR 1.3 Strengthened Local Capacity for Advocacy and Activity Implementation OC7 CI Number of organizations/ enterprises identified as high potential for future awards Definition: Number of local organizations or enterprises who received capacity building from ADVANCE and who meet criteria to receive funding from the USG Unit of measurement: Number Capacity building records and reports Type of organizati on Data recorded and reported quarterly 0 7 OP7 CI Number of organizations/ enterprises receiving capacity building support against key milestones Definition: Number of organizations who received capacity building support from ADVANCE in at least one of the following key areas: Governance, Administration, Human Resources Management, Financial Management, Organizational Management, Program Management and Project Performance Management. Unit of measurement: Number Capacity building records and reports Type of organizati on Data recorded and reported quarterly 0 50 15 # Source Performance Indicators Definition and unit of Measure Data collection method & Source Disag￾gregation Frequency of Data Collection Base￾line LOP Target1 OP8 F Number of awards made directly to local organizations by USAID Definition: Number of Local organization receiving grant from ADVANCE Unit of Measurement: Number USAID Type of organizati on and by value chain Collected and reported annually 0 5 16 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. We will review the results framework and the Theory of Change annually and revise as needed to reflect project learning and environmental changes. 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 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. The ADVANCE 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. Data Collection The ADVANCE project uses a multilayered approach to data collection using both quantitative and qualitative methods, including: 1) Regular data collection by technical staff based in the field; 2) Planned staff site visit reports and qualitative assessments; 3) Use of GIS software to map key actors and beneficiaries; 4) Focus group discussions and key informant interviews; 5) Beneficiary and household surveys; 6) Value chain analyses that inform project strategy to ensure that actors in the value chain remain competitive and relevant; and 7) Triangulation with data from other sources including partners and reputable organizations like ISSER and the Ghana Statistical Service. Forms are being developed for field data collection and procedures put in place to ensure data quality and to guide data quality reviews. Specific information on data collection for each indicator, including data source, method and timing of collection, are outlined in detail in Performance Indicator Reference Sheets of this MEL Plan. The data collection system is illustrated in Figure 4. 17 Figure 4: ADVANCE Data flow system ADVANCE Database For the ADVANCE project, we will design a web-based management and monitoring platform to capture data, store and report on all project indicators and track progress over time. The database will be designed with technical support from ACDI/VOCA’s HQ-based Director of Information Systems in coordination with the MEL Specialist. The system will be designed to address project management and reporting needs and allow for online and offline data entry using simple electronic forms, data storage and automated calculation as well as a real-time update of indicator values. The database will capture the profiles and activities related to ADVANCE farmers, processors, FBOs, nucleus farmers/aggregators, service providers and all other actors benefitting directly from the project. It will capture detailed information on each farmer’s household, the FBO s/he belongs to, the trainings attended, the technologies adopted, his/her farm size, crops cultivated, etc. As per FTF’s guidance, all household related data will be disaggregated by gendered household types, individually by sex and by district and region. The indicator values will be available in real time to both senior project management staff as well as field staff so they can assess the 18 performance of their intervention zones, identify bottlenecks and areas of improvement and make informed decisions on the prioritization of activities. Collaboration with Donors and Stakeholders The ADVANCE 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. Reporting Through regular reporting to USAID, ADVANCE will ensure that project activities, results, challenges and lessons learned are documented and shared in a timely and accurate manner. Per the cooperative agreement, the project team will submit to USAID quarterly performance monitoring reports, the fourth quarterly report being the annual report within 30 days of the end of each reporting period. The performance reports will contain information on: • Comparison of actual accomplishments with the goals, objectives and targets established for the period with explanation for deviations from target; • Case studies; • Success stories and; • Lessons learned or good practices realized during the reporting period. In addition the COP and Monitoring, Evaluation and Learning (MEL) Specialist will produce and share results of value chain analyses, 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 the results of the end of project evaluation, the report will highlight major successes achieved during the agreement period and discuss any shortcomings and difficulties encountered. It will also outline lessons learned and make recommendations for follow￾on activities. Reporting timeline: • Quarterly reports: end of January, April, July and September • Final report: within 90 days of the end of the cooperative agreement KNOWLEDGE MANAGEMENT AND LEARNING The ADVANCE 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, 19 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 project, the M&E system, and the KM&L plan, and will guide the development of the ADVANCE learning agenda. Based on a cycle of planning, implementation, monitoring, research, and re-examination of actions, the ADVANCE KM&L system will incorporate: • Knowledge management to ensure lessons learned from ADVANCE are documented and disseminated broadly within USAID, donor agencies and other FTF implementing partners. • Learning and adaptive management to continually adjust ADVANCE activities to maximize impact while reaching scale, and to facilitate collaborative learning across the Ghana development community to strengthen market systems 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 six areas: 1. Relevance: Are our activities relevant and well-conceived in the context of the project? Can the strategy be improved? 2. Efficiency: Are our activities being implemented in a timely and cost-effective manner? Have resources been used cost-effectively? Do the quantitative and qualitative results justify the resources expended? 3. Effectiveness: To what extent have project outputs been achieved and are these contributing to higher-order changes? What supports and barriers have affected the achievement of outputs and contribution toward outcomes? What are we learning from our experience and how can we improve? 4. Impact: Is there evidence that the project is contributing to improved food security and increased incomes? 5. Sustainability: To what extent is the intervention contributing to building an enabling environment and making systemic changes that will foster continuous and sustained productivity? 6. External utility: To what extent is the project replicable? Might its approaches, methods, and/or content have potential value in other countries or regions or for other subjects? 20 ADVANCE KM&L goals and objectives The goal of the ADVANCE KM&L plan is to operationalize learning in a dynamic, evidence based system. Activities will contribute to the following objectives: 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 5, 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 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 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. We will look for quick wins to demonstrate the usefulness of the exercise to ensure buy-in. 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. FIGURE 5: ONGOING LEARNING AND ADAPTIVE MANAGEMENT 21 Learning related to gender Issues: The results of the recently conducted Women's Empowerment in Agriculture Index (WEAI) show that 72 percent of the women in the implementation area are disempowered. ADVANCE will collaborate with USAID, other USG partners, GOG and other development partners to devise appropriate indicators and learning questions around key issues such as women’s leadership, access to and control over assets, or decision-making authority within the household or community to assist the development community to understand how best to positively impact women’s economic security and sustainable participation in Ghana’s agriculture sector. 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 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 can serve as a catalyst for innovation by building on existing knowledge. KM&L implementation plan In ADVANCE, ACDI/VOCA has developed a system that includes KM&L within the project and KM&L to coordinate learning with other stakeholders. The project’s Monitoring, Evaluation and Learning (MEL) Specialist, Dr. Emmanuel Dormon, will oversee KM&L activities through an internal project committee as well as an external collaborative learning group with stakeholders from the broader development community. Management Steering Committee The ADVANCE Management Steering Committee quarterly meetings with senior project technical staff and technical managers from implementing partners will be central to the KM&L process for ADVANCE. Using data from the multilayered monitoring system described above, we will organize semi-annual project reviews at Management Steering Committee meetings. At these periodic project reviews, we will present the project results in relation to the established targets and objectives, discuss which activities are delivering results and which are not, and dialogue around specific learning questions. Through these meetings, ADVANCE will apply adaptive management by promoting learning, ensuring coordination and synergy among partners, using lessons learned and data from EXAMPLES OF KNOWLEDGE MANAGEMENT INTERVENTIONS: • After Action Reviews • Partner meetings • Collecting best practices • M&E • Internal staff exchange programs • Expertise locators • Collaboration tools (wikis, forums, etc.) • Knowledge audits • Communities of practice and knowledge networks • Learning partnerships • Policy networks • Knowledge centers • Action research • Thematic portals • Open access conferences • Help desks • Advisory services Source: Monitoring and evaluating: knowledge management strategies (IKM Background Paper, 2009) 22 the KM&L efforts to inform and adjust interventions, and, if necessary, update the TOC to maximize outcomes. This system will ensure that annual implementaton plan development is driven by updated value chain analysis, proven best practices and emerging learning drawn from explicit and tacit knowledge capture. The MEL specialist will use the appropriate KM&L tools within the group and with other project staff to extract knowledge and learning. While participation in the Management Steering committee will ensure senior leadership is engaged in KM&L, ADVANCE will also look to create an environment that is conducive to learning and brings in all technical and operational staff. Within the first six months, the MEL Specialist and ACDI/VOCA’s Regional Senior Technical Advisor will carry out 1-day trainings in each of the three field offices for all staff members to introduce the concept, terms and definition of KM&L, KM&L components, and the roles and responsibilities of ADVANCE staff related to KM&L. The MEL Specialist will look for ways to engage staff in the MELL learning agenda (described below) and will make space for sharing knowledge/information during staff meetings. THE MONITORING AND EVALUATION LEARNING AND LEADERSHIP (MELL) GROUP Within the first quarter, the MEL Specialist will set up the MELL Group. Core members will include USAID/Ghana, Monitoring, Evaluation and Technical Support Services (METSS), other USAID/FTF program implementers, and other relevant stakeholders. ADVANCE technical, M&E and gender staff will participate. This coordination with other USG-funded implementers will promote technical learning and will have the added benefit of promoting information sharing, giving projects access to a broad range of qualitative and quantitative data, and preventing duplication of effort. Once the group is formed they will synthesize the KM&L strategy for FTF and other USG investments in North Ghana, and come to a shared understanding of the MELL role. Non-core members include food security actors working in North Ghana. They will be invited to presentations on any research findings, will have access to any studies that come out of the group, and will be encouraged to share their own learning with other group members. MELL Group Members Core Non-core USAID Savannah Accelerated Development Authority (SADA) METSS Northern Rural Growth Program (NGRP) FTF projects Agricultural Value Chain Mentorship Project (AVCMP) • Agricultural Technology Transfer (ATT) Rural and Agricultural Finance Program (RAFiP) • Financing Ghanaian Agriculture Project (FinGAP) Agricultural Value Chain Facility • Agriculture Policy Support (APS) The Rice Sector Support Project (RSSP) • Resiliency in Northern Ghana (RING) Business Sector Advocacy Challenge Fund (BUSAC) II MoFA-Northern Agricultural Sector Working Group University of Ghana Ghana Commercial Agriculture Project (GCAP) University of Development Studies 23 MELL Group Members Core Non-core Ghana Strategy Support Program (GSSP) Council for Scientific and Industrial Research - Savanna Agricultural Research Institute (CSIR￾SARI) West Africa Trade Hub (WATH) Key actors from different nodes of the value chain (NFs, FBOS, input providers, processors/buyers, etc.) Others as they are identified The core group will meet quarterly to promote learning around M&E as a tool to track progress and to maximize cost effectiveness of data collection, ensure use of existing information and avoid duplication of data collection and results tracking where necessary. Meetings will include discussions of challenges in data collection and joint brainstorming of potential solutions, sharing best practices, and dialogue around learning questions. Initial meetings will focus on jointly developing an integrated learning strategy that will help us to better measure whether and how we are contributing to the transformation of Ghana’s agriculture sector. See the textbox on the following page for a list of illustrative questions. Together, the group will validate the questions, select the 3-4 questions to be followed up in year one, and determine a research strategy. During annual reviews the group will discuss adding new questions or updating the current ones if learning is still in progress. Learning will be pursued through a variety of means: o ADVANCE and other FTF project staff can gather data through their work o ACDI/VOCA STTA o Engage local NGO, academic and ministry experts o Encourage USAID Mission to contract out through METSS or a different vehicle o Funded through other vehicles (see textbox above) 24 ILLUSTRATIVE LEARNING QUESTIONS ADVANCE demonstrated that nucleus farmers (NFs) have real profit incentives to support smallholder farmers to increase their yields. ADVANCE II will build on this learning to encourage NFs to provide additional services, including extension. Learning question: What are the most successful, sustainable and cost-effective models for providing agronomic extension to farmers in northern Ghana? ADVANCE learned that women have better yields than men on plots of less than three acres; that men use more fertilizer than women on maize and rice in northern Ghana; and women’s field sizes are generally smaller than men’s. Learning question: What are the underlying factors that contribute to women having higher productivity than men (land size, fertilizer use) and how can the project use these findings to further increase women’s productivity? Gross margin analysis conducted by ADVANCE determined that the ideal maize farm size to maximize returns for the average smallholder farmer is 2-3 acres per farmer. Learning question: How can ADVANCE II use this information to help farmers look at their farming system and decide on an ideal crop mix, taking into account risk and potential returns? ADVANCE demonstrated through SAT loans the ability of smallholder farmer groups to self-finance the purchase of weather-index crop insurance. Learning question: What strategies work best to build demand for weather-index crop insurance, market information, extension, mobile money, and other potentially self-financed services? ADVANCE learned that the most successful NFs have a strong relationship with a lead firm such as Premium Foods or Vester Oil. Learning question: What project strategies are most effective in promoting investment by lead firms in the NFs in their northern Ghana supply chains? ADVANCE observed that male and female aggregators and NFs face financial and operational roadblocks to expanding their operations. Learning question: How can a project help men and women who aggregate and provide services to sustainably manage the burden of growth? Female smallholder farmers were able to increase their production and income with ADVANCE support, enabling them to take on some or all of the responsibility for their families’ education and health care. In most cases, prior to program support the women had to ask the men for money to meet these needs, and were often not successful. Learning question: How does increased work load and income for women impact intra-household dynamics/conflicts? Through ADVANCE ACDI/VOCA facilitated the development of the warehouse receipts system, including the issuing the first warehouse receipts in Ghana. Learning question: What are effective strategies for expanding demand for and access to warehouse receipts? ADVANCE linked just a few individual women beneficiaries to large commercial banks but had more success in linking women’s groups to rural banks. The project learned that women-owned businesses often struggle to achieve the scale or obtain the collateral required to access finance from the formal banking sector. Learning question: What strategies are most successful in helping women-owned businesses achieve the scale required to access formal finance without simply providing a direct handout and creating dependency? 25 To share learning within the project, ADVANCE will draft briefing papers that present evidence￾based lessons learned from the program to be disseminated through the project learning groups and other venues. We will post all studies on the ACDI/VOCA website, and will publish a quarterly newsletter that will be widely disseminated within Ghana and externally to benefit other food security projects. ACDI/VOCA will also apply any learning to our other agriculture and food security projects worldwide, and will look for opportunities to share our learning more broadly at suitable forums such as the Microenterprise and Private Enterprise Promotion (MPEP) seminar series, AgriLinks, FTF Global Learning and Evidence Exchanges, and the SEEP Network Annual Conference. MELL meetings will also provide an opportunity for ADVANCE and other projects to get input from USAID and other group members into the design of M&E systems, including the baseline and midterm evaluation studies and annual surveys. At the completion of each evaluation study, the ADVANCE team will organize a workshop with the MELL group, including non-core members, to share results and evidence-based best practices. In Year 3 and 4, in coordination with METTS, we will host a learning event where members from both groups and relevant external stakeholders are invited to participate. To further develop a learning culture among stakeholders active in the ADVANCE zone of influence around topics including, but not limited to facilitating market-system approaches, integrating gender, facilitating access to finance and providing ag advisory services, etc., we will adapt and deliver existing training modules that ACDI/VOCA developed for USAID staff through ONLINE DATA PLATFORM In order to estimate gross margin data, ADVANCE utilized GIS technology to collect area data and map out beneficiary farms in the three target regions. ADVANCE partnered with the Center for Remote Sensing and Geographical Information Services (CERSGIS) to store and share the spatial data for agricultural projects. This data will remain available and will be updated by CERSGIS for agricultural sector stakeholders and investors to use. Under ADVANCE II we will continue working with MoFA to build the capacity of stakeholders to use, contribute to and sustain the GIS online platform. We will explore how to collaborate with and leverage the Open Data for Agriculture platform as part of the New Alliance for Food Security and Nutrition, which was launched by President Obama and G-8 partners. LEVERAGING EXTERNAL RESEARCH PARTNERS Leveraging Economic Opportunities (LEO) project LEO is a contract implemented by ACDI/VOCA and a set of subcontractors to support USAID programming that fosters inclusive growth through markets. Within the overarching goal of increased market systems performance, LEO’s learning topics can be viewed through two lenses: • Inclusivity –the capacity of market systems to profitably engage and benefit women, the very poor, the food insecure and other vulnerable or marginalized groups; and • Resilience—the ability of market systems to adapt to the changing environment in ways that sustain and even increase benefits to a wide range of system actors. The USAID/Ghana Mission can buy into LEO to support the ADVANCE II learning agenda through a variety of services including research, analytics, local systems developments and evaluations. Women Thrive Worldwide Women Thrive Worldwide advocates for change at the U.S. and global levels so that women and men can share equally in the enjoyment of opportunities, economic prosperity, voice, and freedom from fear and violence. The organization is interested in carrying out research and capacity building activities in Ghana and other FTF countries to drive their advocacy agenda and there may be opportunities for leverage. 26 the Accelerated Microenterprise Advancement Project (AMAP) contract. These modules focus on designing, managing and evaluating value chain programs, and include guidance on how to incorporate Collaborating, Learning and Adapting (CLA) strategies. Participants will build capacity in: • Coordinating and collaborating with stakeholders; • Learning from testing new approaches to identify best practices; and, • Adapting program design and strategies to apply best practices and eliminate what is not working. In addition we will build capacity of local partners and key stakeholders to design and manage CLA activities to ensure strong project management beyond the life of the project. This will empower our local partners and grantees to become more effective learning organizations. Tracking KM&L activities Key activities regarding knowledge management will be tracked as follows: A. Management Steering Committee: 1. # of MSC meetings 2. # of work plans developed and informed by the produced knowledge B. MELL: 1. # of integrated KM&L strategies available; 2. % of implementation of the KM&L strategy operational plan (# of activities implemented during the reporting period/# of activities planned) 3. # of studies and assessments commissioned and number of recommendations that were accepted by the MELL implemented The year one implementation plan for the KM&L is presented in Figure 6 below. 27 Figure 6: Implementation Plan for KM&L Feb (2/5 start date) Mar Apr May Jun Jul Au g Sep t Category and task Person(s)/ organization responsible Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 KM&L within the project Submit draft KM&L plan to USAID Finalize KM&L plan Carry out semi-annual reviews in Management Steering Committee and update KM plan as needed Share learning/knowledge among technical staff Track learning targets KM&L to coordinate learning with other stakeholders Establish MELL group Meet quarterly Hold workshop with core members to refine TOC and RF Review TOC and RF annually with group Jointly develop an integrated learning strategy Identify who is best suited to carry out research based on the learning agenda, and contract it out if external Review learning agenda annually to update/add new questions of interest Publish quarterly newsletter At the completion of the baseline and midterm studies, organize workshops with the MELL group and non-core members to share results and evidence-based best practices 28 PROJECT ROLES AND RESPONSIBILITIES The monitoring, evaluation and learning system for ADVANCE 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 MEL team will be headed by the Monitoring, Evaluation and Learning Specialist, Dr. Emmanuel Dormon who doubles as the Deputy Chief of Party and will be based in the Accra office to ensure easy access to the Ghana mission and respond to urgent data requests but will frequently travel to the intervention area to oversee all aspects of the system. He is delegated by the COP as prime contact with USAID, partners and stakeholders on all M&E issues. Working closely with the ICT team, he will be responsible for overseeing the development and maintenance of the program database. The MEL team leader will be supported by the M&E Coordinator. He will directly oversee and support the field M&E Officers and data entry assistants who are located at ADVANCE project offices in Northern Ghana. The M&E Coordinator will provide overall coordination of data collection by field officers, technical specialists and the M&E Officers. The M&E field Officers will ensure timely field data collection, conduct data quality reviews, and generate periodic reports. Details are presented in Table 2. ACDI/VOCA Regional and Headquarters Support: The ADVANCE MEL team will be supported by ACDI/VOCA headquarters’ M&E unit through the Regional M&E Specialist based in Accra who will provide technical assistance. 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 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, along with the DCOP who doubles as the MEL Specialist will be the main points of contact with USAID on M&E issues. 29 Table 2: MEL staffing plan Position Office Responsibilities MEL Specialist/ DCOP 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 Project M&E Coordinator Accra - Oversees field M&E officers and data entry assistants - Coordinate all data collection across project locations - Validate all data submitted by field M&E officers before accepting in database - Assists and MEL Specialist in implementing the KM&L plan - Back up all data weekly Field M&E Officers 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 GIS Specialist Accra - Lead and coordinate all GIS mapping exercises including annual surveys for gross margin data collection, mapping of locations of NFs, FIs, input firms, FBOs, warehouses etc and presenting the spatial data to assist project management 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; field M&E Officers, Data Entry Assistants and technical field staff on the result framework and the use of the MEL 30 Plan. The training will orient staff to the ADVANCE 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). M&E staffing timeline: • M&E Officers posted to Wa, Bolgatanga and Tamale March 1, 2014 • M&E staff orientation: March 2014 • M&E training April 2014 31 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 project staff will work closely with partners on data quality and 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 staff, but registers will also be filled in at the NF level. Each beneficiary will be coded and each NF and his 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 four months of project start-up. During the workshop, we 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. The ACDI/VOCA Regional M&E Specialist will conduct annual internal rapid data quality assessments to assess the validity, reliability and timeliness of data and, when necessary, make adjustments to 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, ACDI/VOCA HQ M&E staff will visit the project annually to conduct a detailed data quality assessment/internal data quality audit. Finally, a data quality strategy document will be prepared and distributed to all staff by end of May 2014 to ensure proper understanding and adherence to standard operating systems that guarantees data quality. EVALUATION APPROACH AND ASSESSMENTS Opportunities for impact evaluation will be incorporated into the project design and start-up phase to ensure that outcomes can be appropriately measured and attribute causality. The ADVANCE team will conduct a baseline study and will collaborate with the third-party evaluator to complete the midterm and impact evaluation. In addition, the MEL team will conduct annual outcome surveys. Baseline Once the MEL plan is reviewed and approved, the project will hire an external contractor to conduct a baseline study, which will be designed in close collaboration with USAID. The results of this study will be used to test the causal pathways as outlined in the Theory of Change, confirm or modify the targets of key indicators, and lay the groundwork for the impact assessment. 32 The initial assessments and baseline studies will be used to set targets to track output, outcome and impact indicators and will provide the basis of comparison for the midterm review and the final evaluation. The baseline will capture the current climate for business development, growth, investment and innovation. Upon completion of the baseline study, the ADVANCE team will review the indicators and targets in the PMP and make modifications as necessary. Primarily the initial assessments and baseline inventorying will be conducted through 1) desk reviews, 2) targeted investigations, 3) surveys, and 4) interviews and focus groups. The questionnaires and indicators of all baseline components will be gender sensitive to ensure that the impact of interventions on both men and women can be captured throughout the project. Specific data collection techniques, timing and responsibilities will be further refined by the external evaluator and approved by project management before the study commences. The baseline, gender assessment, and value chain assessments will fill in knowledge gaps which will all feed into the first-year learning agenda. Midterm Evaluation At the mid-point of the project, ADVANCE will recruit an external evaluator to assess the project’s progress, effectiveness and efficiency and check whether the project is on track to achieve its stated objectives. This effort will also assess whether the logical pathway of the project (expressed in the Theory of Change) appears to be holding true and facilitate data￾based reflection around the project’s learning questions. The midterm evaluation will adopt a quantitative-qualitative sequential method to better understand if the pathways to the change are established. This innovative and complementary method will generate data necessary for both accountability and learning in a complex environment and project such as ADVANCE. Final Evaluation During the last year of implementation, ADVANCE will collaborate with USAID to 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 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. 33 Sampling Method and Size All smallholder project beneficiaries who produce maize, rice 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, rice 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. Other GIS applications will include geospatial analysis to demonstrate reach and coverage of various services including input supply, financing, markets, and warehouse facilities among others. RISKS AND ASSUMPTIONS In order to maximize the effectiveness and efficiency of the ADVANCE 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 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. 34 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. Monitoring and Mitigation: To mitigate this challenge, ADVANCE 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 Gender considerations are critical to the success of ADVANCE because gender roles and relations can both affect and be affected by the outcomes and results of activities. ADVANCE partners will therefore consider and address how gender relations will affect the achievement of sustainable results, as well as how proposed results will affect the relative status of men and women. Monitoring and Mitigation: Our approach is to identify where gender related constraints occur and for whom within the target value chains and design interventions to address them. We are also adopting a targeted approach, making women’s economic and social empowerment a priority of the project. The detailed gender strategy is being developed and will be submitted in May, with all recommendations incorporated into the MEL Plan and MEL team implementation. The MEL team will examine the effectiveness of our gender strategy through focus group discussions and case studies periodically while the midterm and final evaluations will also assess the effectiveness of the gender strategy 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 35 including assisting medium and large scale farmers to develop environmental management plans. 36 Annex 1: FY targets # Indicator/Disaggregation FY14 FY15 FY16 FY17 FY18 LOP OP1 Number of direct project beneficiaries 35,000 50,000 78,000 80,000 75,000 113,000 Male 21,000 30,000 42,900 44,000 41,250 62,150 Female 14,000 20,000 35,100 36,000 33,750 50,850 OC1 Gross margins per hectare for selected crops US Dollar under marketing arrangements fostered by the activity (USD/ha) Maize Male $333 $680 $720 $790 $790 Female $348 $780 $810 $840 $840 Rice Male $454 $1,200 $1,300 $1,400 $1,400 Female $437 $1,050 $1,150 $1,250 $1,250 Soy Male $411 $600 $650 $700 $700 Female $277 $500 $550 $600 $600 OC2 Number of farmers and others who have applied improved technologies or management practices as a result of USG assistance 14,000 35,000 45,000 70,200 72,200 101,700 Male 21,000 24,750 38,610 39,600 55,935 Female 14,000 20,250 31,590 32,400 45,765 OC3 Number of hectares under improved technologies or management practices as a result of USG assistance 5,000 52,500 45,000 70,200 72,200 312,200 37 # Indicator/Disaggregation FY14 FY15 FY16 FY17 FY18 LOP OC4 Number of private enterprises (for profit), producers organizations, water users associations, women's groups, trade and business associations, and community￾based organizations (CBOs) that applied new technologies or management practices as a result of USG assistance 100 300 338 338 338 450 OP2 Number of private enterprises (for profit), producers organizations, water users associations, women's groups, trade and business associations, and community￾based organizations (CBOs) receiving USG assistance 300 400 450 450 450 600 OP3 Number of individuals who have received USG supported short-term agricultural sector productivity or food security trainings 15,000 30,000 58,500 60,000 56,250 80,000 Male 18,000 32,175 33,000 30,938 44,000 Female 12,000 26,325 27,000 25,313 36,000 OC5 Value of incremental sales (collected at farm-level) attributed to FTF implementation $6,780,000 $9,320,000 $16,940,000 $17,880,000 $67,880,000 Maize $2,240,000 $8,080,000 $14,570,000 $14,940,000 $53,840,000 Rice $2,940,000 $880,000 $1,780,000 $2,130,000 $9,730,000 Soy $1,600,000 $360,000 $590,000 $810,000 $4,310,000 OP4 Value of agricultural and rural loans $500,000 $1,000,000 $1,000,000 $1,000,000 $800,000 $4,300,000 OP5 Value of new private sector investment in agricultural sector or value chain (US$) $800,000 $800,000 $800,000 $800,000 $800,000 $4,000,000 OP6 Number of value chain actors accessing finance 200 225 225 225 300 38 # Indicator/Disaggregation FY14 FY15 FY16 FY17 FY18 LOP OC6 Number of firms (excluding farms) or Civil Society Organizations (CSOs) engaged in agricultural and food security-related manufacturing and services now operating more profitably (at or above cost) because of USG assistance 30 50 75 100 100 OC7 Number of organizations/ enterprises identified as high potential for future awards 3 4 5 7 7 OP7 Number of organizations/ enterprises receiving capacity building support against key milestones 9 20 40 50 50 OP8 Number of awards made directly to local organizations by USAID 2 3 4 5 5 39 Annex 2: Indicators Targets Revisions ADVANCE is kindly requesting USAID to approve the revision of its indicators’ targets. This revision concerns the FY16, FY17 and FY18 targets. In addition, though the project is expected to close in September 2018, due to the production cycle that covers two fiscal years, ADVANCE would like to propose targets for FY19 to be able to report on the 2018 crop year achievements. The proposed revision of each affected indicator is presented below. 4.5(16,17,18) Gross margin per hectare of maize, rice, and soya During the last fiscal years, ADVANCE constantly and significantly overachieved its gross margin targets. This is due to the high rate of improved technologies and management practices by its beneficiaries, which resulted in considerably higher yield. Gross margins (USD/ha) FY15 targets FY15 actuals FY15 achievement FY16 targets FY16 actuals* FY16 achievement* Maize - Male 333 822.70 247.06% 416 558.81 134.33% Maize - Female 348 581.11 166.98% 435 828.41 190.44% Rice - Male 454 588.43 129.61% 648 1,179.14 181.97% Rice - Female 437 450.16 103.01% 625 1,008.72 161.40% Soy - Male 411 594.65 144.68% 474 540.44 114.02% Soy - Female 277 565.39 204.11% 383 476.07 124.30% * Provisional figures In view of this success, ADVANCE would like to increase its out year targets as followed. As previously mentioned, targets for FY19 were added. Current targets Revised targets Gross margins (USD/ha) FY16 FY17 FY18 LOA FY16 FY17 FY18 FY19 LOA Maize 423 507 536 536 700 750 800 800 800 Male 416 499 542 542 680 720 790 790 790 Female 435 522 527 527 780 810 840 840 840 Rice 644 902 1,178 1,178 1,150 1,250 1,350 1,350 1,350 Male 648 908 1,190 1,190 1,200 1,300 1,400 1,400 1,400 Female 625 875 1,121 1,121 1,050 1,150 1,250 1,250 1,250 Soy 437 518 560 560 550 600 650 650 650 Male 474 537 552 552 600 650 700 700 700 Female 383 490 572 572 500 550 600 600 600 4.5.2(5) Number of farmers and others who have applied improved technologies or management practices (ITMP) as a result of USG assistance 40 Initially, ADVANCE targeted an application rate of 70%. However, in the past fiscal years, application peaked to over 90%. In FY16, 98.42% of the men and 94.58% of the women beneficiaries applied one or more land based technologies. These percentages increase to 99.47% and 98.14% respectively for men and women’s application when all technologies and management practices are considered. ADVANCE would like to revise its application rate assumption to 90% for both men and women beneficiaries. In addition, in the current Performance Monitoring Plan (PMP), in order to get the targeted number of farmers and others applying ITMP, these assumed rates were applied to the beneficiaries of the reporting year. However, during the webinar by Bureau of Food Security on October 13, 2015, instructions were given to report the gross margin, application of technologies and incremental sales indicators of a particular fiscal year together, and within the next fiscal year report, should the production to sales cycle cover two fiscal years, which is the case of the project’s targeted crops. This means that application of technologies by FY16 beneficiaries will be reported with their gross margin in the FY17 report. Thus, ADVANCE revised below the number of farmers and others who applied ITMP for each fiscal year, using 90% of the targeted number of beneficiaries of the previous year. FY19 targets were also added to account for the 2018 crop year results. All FY targets and the LOA targets saw an increase, except for FY16. Number of farmers applying ITMP Current targets Revised targets FY16 FY17 FY18 LOA FY16 FY17 FY18 FY19 LOA Total 54,600 56,000 52,500 79,100 45,000 70,200 72,000 67,500 101,700 Male 30,030 30,800 28,875 43,505 24,750 38,610 39,600 37,125 55,935 Female 24,570 25,200 23,625 35,595 20,250 31,590 32,400 30,375 45,765 4.5.2(2) Number of hectares under improved technologies or management practices as a result of USG assistance In the current ADVANCE PMP, the assumption used to set the number of hectares under land based ITMP was an average of 1.5ha by applying individual. However, actual average sizes of land planted were lower than 1ha: 2016 crop year values were at 1 ha for maize, 0.4 ha for rice and 0.71 ha for soya. Therefore, ADVANCE proposes to use 1 ha as targeted value of area under land based ITMP per farmer applying. The corresponding targets are presented in the table below. FY19 targets were added. All FY targets have reduced but this was compensated with the FY19 targets so that the revised LOA targets are higher than the current LOA. Number of ha under ITMP Current targets Revised targets FY16 FY17 FY18 LOA FY16 FY17 FY18 FY19 LOA Total 81,900 84,000 78,750 302,150 45,000 70,200 72,000 67,500 312,200 Male 45,045 46,200 43,313 168,808 24,750 38,610 39,600 37,125 174,335 Female 36,855 37,800 35,438 133,343 20,250 31,590 32,400 30,375 137,865 41 4.5.2(23) Value of incremental sales (collected at farm-level) attributed to Feed the Future implementation ADVANCE would like to revise its incremental sales targets because the initial assumptions they were based on are no longer relevant. Those assumptions relied on the ADVANCE 1 figures and mostly the baseline data. It was estimated that the increase of sales amount by farmer will follow the increase of gross margins, and that this increase will reach almost 100% for maize and soy and 250% for rice, using the baseline values as the starting point. However, as seen in the table below, ADVANCE beneficiaries are currently focusing more on increasing their productivity and efficiencies. They are improving their yields but are planting much smaller plots. This led to an average quantity produced that remains almost unchanged for soy, is reduced for rice but almost doubled for maize. In addition, due to the cedis devaluation of 43% (exchange rate went from 2.66 at baseline to 3.47 at the beginning of 2016, and even 3.8 this May 2016), the average selling price significantly reduced for all crops. The combination of all those factors resulted in average sales per farmer that doubled for maize but decreased for rice and soy compared to baseline. Maize Avg. area (ha) Avg. yield (MT/ha) Avg. production (MT) Avg. price (USD) Avg. sales (USD) Baseline 1.42 1.38 1.97 $347.28 $258.83 FY16 1.00 3.63 3.64 $232.30 $592.34* Rice Avg. area (ha) Avg. yield (MT/ha) Avg. production (MT) Avg. price (USD) Avg. sales (USD) Baseline 1.20 1.61 1.93 $438.58 $433.93 FY16 0.40 3.98 1.61 $342.36 $384.68* Soy Avg. area (ha) Avg. yield (MT/ha) Avg. production (MT) Avg. price (USD) Avg. sales (USD) Baseline 1.27 0.89 1.12 $566.66 $301.36 FY16 0.71 1.83 1.29 $327.33 $297.55* * Estimated figures Thus, the initially planned individual sales increases of 100% to 250% seem unrealistic. Instead, ADVANCE proposes to target a change of 110% for maize, 35% for rice and 25% for soya. The corresponding targets are presented in the table below. FY19 targets were added. Value of incremental sales FY16 FY17 FY18 FY19 LOA Current targets Total $22,080,000 $36,000,000 $68,500,000 $133,360,000 Maize $8,720,000 $14,310,000 $22,740,000 $48,010,000 Rice $9,190,000 $15,710,000 $32,120,000 $59,960,000 Soy $4,170,000 $5,980,000 $13,640,000 $25,390,000 Revised targets Total $9,320,000 $16,940,000 $17,880,000 $16,960,000 $67,880,000 Maize $8,080,000 $14,570,000 $14,940,000 $14,010,000 $53,840,000 Rice $880,000 $1,780,000 $2,130,000 $2,000,000 $9,730,000 42 Soy $360,000 $590,000 $810,000 $950,000 $4,310,000 43 Annex 3: Performance Indicator Reference Sheets 44 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive Agricultural Sector Growth Intermediate Result- IR 0: Sub- Intermediate Result- Sub-IR.0: Name of Indicator: 0.0-0 Number of direct project beneficiaries 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): An individual is a direct beneficiary if s/he comes into direct contact with the set of interventions (goods or services) provided by the project. 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 beneficiary. Individuals who receive training or benefit from program-supported technical assistance or service provision are considered direct beneficiaries (farmers & participants in TOT). Unit of Measure: Number Disaggregated by: Sex and Region Rational or justification for indicator (optional): Type: Output Direction of change: Higher = better PLAN FOR DATA COLLECTION Data Source(s): Regular Beneficiary monitoring - Program database Method of data collection and construction: Regular Beneficiary monitoring - Program database Frequency/Timing of Data Collection: Quarterly Reporting Frequency: Quarterly 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 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCEM&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: Quarterly/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY14 0 Year Targets Actuals Male Female Male Female FY14 21,000 14,000 21,792 FY15 30,000 20,000 15,230 FY 16 42,900 35,100 FY17 44,000 36,000 FY18 41,250 33,750 LOP 62,150 50,850 THIS SHEET LAST UPDATED ON: Sept 14, 2016 45 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive Agricultural Sector Growth Intermediate Result- IR 1.1: Increased productivity of targeted commodities Sub- Intermediate Result- Sub-IR.0: Name of Indicator: EG.3-6 Farmers Gross margins per hectare for selected crops in US Dollars under marketing arrangements fostered by the activity 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): The gross margin is the difference between the total value of small-holder production of the agricultural product (crop) and the cost of producing that item, divided by the total number of units in production (hectares of crops). Gross margin per hectare is a measure of net income for that farm/livestock/fisheries-use activity. Gross margin is calculated from five data points, reported as totals across all direct beneficiaries: 1. Total Production by direct beneficiaries during reporting period (TP) 2. Total Value of Sales (USD) by direct beneficiaries during reporting period (VS) 3. Total Quantity (volume) of Sales by direct beneficiaries during reporting period (QS) 4. Total Recurrent Cash Input Costs (USD) of direct beneficiaries during reporting period (IC) 5. Total Units of Production: Hectares planted for direct beneficiaries during the production period (UP) Partners should enter disaggregated values for the five gross margin data points, disaggregated first by commodity, then by the sex disaggregate categories: male, female, joint and association-applied, as applicable. Commodity-sex layered disaggregated data are required because the most meaningful interpretation and use of gross margin information is at the specific commodity level, including the comparison of gross margins received by female and male farmers. FTFMS will then use the formula below to automatically calculate the average commodity-specific Gross Margin, and the average commodity-specific Gross Margin for each sex disaggregate: In addition to the five data points, partners must enter the number of direct beneficiaries of the activity, disaggregated by commodity and then sex. A direct beneficiary should be counted only once under each commodity regardless of the number of production cycles for the commodity during the reporting year. If a plot of land falls under the disaggregate “jointly-managed”, the number of beneficiaries jointly managing the plot should be counted. In the case of the “association-applied” disaggregate however, neither the association nor the individuals involved in the association can be considered as a direct beneficiary and therefore nothing should be counted Gross margin per ha, per animal, per cage = [(TP x VS/QS) – IC ] / UP For example, for the total production data point, the project should enter total production during the reporting year on plots managed by female, maize-producing, direct beneficiaries; total production on plots managed by male, maize-producing, direct beneficiaries; total production during the reporting year on plots managed jointly by female and male maize-producing, direct beneficiaries, if applicable; and total production on plots managed by groups (“association-applied”) of maize-producing, direct beneficiaries; if applicable. And so forth for total value and total quantity of sales; total cash recurrent input costs; and total hectares, animals or cages for maize. And so forth for other commodities. The FTFMS will automatically calculate weighted by total hectares for the overall commodity (e.g. gross margin/hectare for maize) and for each sex disaggregate category (e.g. gross margin/hectare for female maize-producing direct beneficiaries.) If a direct beneficiary sample survey is used to collect gross margin data points, the sample survey estimates must be extrapolated to total beneficiary estimated values before entry into FTFMS to ensure accurate calculation of weighted average gross margin per commodity across implementing mechanisms at the Operating Unit level and across countries for Feed the Future overall reporting. Note: Gross margin targets should be entered at the commodity level. Targets do not need to be set for each of the five data points. If there is more than one production cycle in the reporting year, farmer’s land area should be counted (and summed) each time it is cultivated, and the other four data points (Total Production, Value and Quantity of Sales, Recurrent Cash Input Costs) summed across production cycles if the same crop was planted. If the production cycle from soil preparation/planting to sales starts in one fiscal year and ends in another, report gross margin in the second fiscal year, once all data points are available. Since the four key agricultural indicators (gross margins, number of farmers applying improved technologies, number of hectares under improved technologies, and incremental sales) are all related, report all four indicators in the second fiscal year in these cases. The unit of measure for Total Production (e.g. kg) must be the same as the unit of measure for Total Quantity of Sales, so that the average unit value calculated by dividing sales value by sales quantity can be used to value total production (TP x VS/QS). If sales quantity was recorded in a different unit of measure than the unit used for total production, sales quantity must be converted to the equivalent quantity in production units prior to entry in FTFMS. For example, if Total Production was measured in metric tons, and Total Quantity of Sales was measured in kg, Total Quantity of Sales should be divided by 1,000 before entering in FTFMS. Input costs included should be those significant cash costs that can be easily ascertained. Attention should be focused on accounting for cash costs that represent at least 5% of total cash costs. (Note, it is not necessary to calculate actual percent contribution of specific inputs to total input costs to determine which inputs account for at least 5% of total cash costs. Partners may simply estimate which inputs would qualify.) Most likely cash input cost items are: purchased water, fuel, electricity, seed, feed or fish meal, fertilizer, pesticides, hired labor, hired enforcement, and hired machine/veterinary services. Capital investments and depreciation should not be included in cash costs. Unpaid family labor, seed from a previous harvest and other in-kind inputs do not have to be valued and should not be included in costs. Unit of Measure: US dollar/Ha Disaggregated by: Commodity, Sex of producer 46 Rational or justification for indicator (optional): Improving the gross margin for farm commodities for small-holders contributes to increasing agricultural GDP, will increase income, and thus directly contribute to the IR of improving production and the goal indicator of reducing poverty.. Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): 1)Baseline and impact Evaluation 2) Annual outcome survey in conjunction with data collected from a sample of monitored farmers Method of data collection and construction: Direct beneficiary farmer sample surveys 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 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: This indicator title changed from “4.5-16 Gross margins per hectare for selected crops US Dollar under marketing arrangements fostered by the activity” to “EG.3-6 Farmers Gross margins per hectare for selected crops US Dollar under marketing arrangements fostered by the activity” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE 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: Annually Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline value FY14 Maize: /Male: 227.21 / Female: 289.76 Rice: /Male: 259.4 / Female: 249.98 Soya: /Male: 316.02 / Female: 212.86 Year Targets Actuals FY15 Maize: /Male: $333 / Female: $348 Maize: Rice: / Male: $454 / Female: $437 Rice: Soya: / Male: $411 / Female: $277 Soya: FY 16 Maize: / Male: $680 / Female: $780 Maize: Rice: / Male: $1,200/ Female: $1,050 Rice: Soya:/ Male: $600 / Female: $500 Soya: FY17 Maize: /Male: $720 / Female: $810 Maize: Rice: /Male: $1,300 / Female: $1,150 Rice: Soya: /Male: $650 / Female: $550 Soya: FY18 Maize: /Male: $790 / Female: $840 Maize: Rice:/ Male: $1,400 / Female: $1,250 Rice: Soya: /Male: $700 / Female: $600 Soya: LOP Maize: /Male: $790 / Female: $840 Maize: Rice: /Male: $1,400 / Female: $1,250 Rice: Soya: /Male: $700 / Female: $600 Soya: THIS SHEET LAST UPDATED ON: Sept 14, 2016 47 48 USAID Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive agricultural sector growth Intermediate Result- IR 1.1: Increased productivity of targeted commodities Sub- Intermediate Result- Sub-IR.0: Name of Indicator: EG. 3.2-17 Number of farmers and others who have applied 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 total number of direct beneficiary farmers, as well as individual processors (not firms), rural entrepreneurs, traders, etc. that applied improved technologies anywhere within the food and fiber system as a result of USG assistance during the reporting year. This includes innovations in efficiency, value-addition, post-harvest management, marketing, sustainable land management, water management, managerial practices, and input supply delivery. Technologies and practices to be counted here are agriculture-related, including those that address climate change adaptation and mitigation (including, but not limited to, carbon sequestration, clean energy, and energy efficiency as related to agriculture). Significant improvements to existing technologies and practices should be counted. Types of technologies: - Crop Genetics: e.g. improved/certified seed that could be higher-yielding, higher in nutritional content (e.g. through bio-fortification, such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or drought tolerant maize, or stress tolerant rice) and/or more resilient to climate impacts; improved germ plasm. - Cultural Practices: e.g. seedling production and transplantation; cultivation practices such as planting density, moulding; mulching. - Pest Management: e.g. Integrated Pest Management, improved insecticides and pesticides, improved and environmentally sustainable use of insecticides and pesticides. - Disease Management: e.g. improved fungicides, appropriate application of fungicides. - 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); improved fertilizer; improved fertilizer use practices; erosion control. - Irrigation: e.g. drip, surface, and sprinkler irrigation, irrigation schemes. - Water Management - non-irrigation-based: e.g. water harvesting, sustainable water use practices, improved water quality testing practices. - Climate Mitigation or Adaptation: e.g. conservation agriculture; carbon sequestration through low- or no-till practices; increased use of climate information for planning, risk reduction, and increasing resilience; increased energy efficiency; natural resource management practices that increase resilience to climate change. - 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 & Storage: e.g. improved packing house technologies and practices, improved transportation, decay and insect control, temperature and humidity control, improved quality control technologies and practices, sorting and grading. - 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-related information technology, improved record keeping, improved budgeting and financial management. If an activity is promoting a technology for multiple- benefits, the beneficiary applying the technology may be reported under each relevant Technology Type category. For example, mulching could be reported under Cultural practices (weed control), Soil-related fertility and conservation (organic content) and Water management (moisture control), depending on how (for what purpose(s)/benefit(s)) the activity is promoted it to the beneficiary farmers. If a beneficiary applied more than one improved technology during the reporting year, count the beneficiary under each technology type (i.e. double-count). However, count the beneficiary only once in the Total w/one or more improved technology category under the Technology Type disaggregate and in the Sex disaggregate. In other words, a beneficiary should be counted once in the totals, regardless of the number of technologies applied during the reporting year. If more than one beneficiary in a household is applying improved technologies, count each beneficiary in the household who does so. Since it is very common for Feed the Future activities to promote more than one improved technology, not all of which are applied by all beneficiaries at once, this approach allows Feed the Future to accurately track and count the uptake of different technology types, and to accurately count the total number of farmers applying improved technologies. See EG.3.2-18 for an example of how to double-count hectares and farmers. If a beneficiary cultivates a plot of land more than once during the reporting year, count the beneficiary once under each type of technology that was applied during any of the production cycles, but not more than once even if a technology is applied in multiple production cycles during the reporting year. For example, because of new access to irrigation as a result of a Feed the Future activity, a farmer can now cultivate a second crop during the dry season in addition to her/his regular crop during the rainy season. Whether the farmer applies Feed the Future promoted improved seed to her/his plot during one season and not the other, or in both the rainy and dry season, s/he would only be counted once in the Crop Genetics category under the Technology Type disaggregate. Note however that the area planted with improved seed should be counted each time it is cultivated under the indicator EG.3-6 Gross margin per hectare and indicator EG.3.2-18 Number of hectares of land under improved technologies. Beneficiaries who are part of a group that apply improved technologies on a demonstration or other common plot, are not counted as having individually applied an improved technology. Instead, the group should be counted as one (1) beneficiary group and reported under indicator EG.3.2-20 Number of for-profit private enterprises, producers organizations… and community-based organizations (CBOs) that applied improved 49 organization-level technologies or management practices. The area of the communal plot should be counted under indicator EG.3-6 Gross margin per hectare and indicator EG.3.2-18 Number of hectares of land under improved technologies. 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 beneficiary for this indicator. In addition, the area of the demonstration plot should be counted under indicator EG.3-6 Gross margin per hectare, if applicable, and indicator EG.3.2-18 Number of hectares of land under improved technologies. However, if the demonstration or training plot is cultivated by extension agents or researchers (a demonstration plot in a research institute, for instance), neither the area nor the extension agent or researcher should be counted under this indicator, EG.3-6, or EG.3.2-18. This indicator counts individuals who applied improved technologies, whereas indicator EG.3.2-20 Number of for-profit private enterprises, producers’ organizations… and community-based organizations (CBOs) that applied improved organization-level technologies or management practices counts firms, associations, or other group entities that applied improved technologies or practices. However, in most cases, this indicator should not count as individuals members of an organization that applied a technology or practice. For example, if a producer association implements a new computer-based accounting system during the reporting year, the association would be counted under indicator EG.3.2-20 Number of for-profit private enterprises, producers organizations…applying, but the members of the producer association would not be counted as having individually-applied an improved technology/practice under this indicator. However, there are some cases where both the group entity should be counted under indicator EG.3.2-20 and its members counted under this indicator. For example, a producer association purchases a dryer and then provides drying services for a fee to its members. In this scenario, the producer association can be counted under EG.3.2-20 and any association member that uses the dryer service can be counted as applying an improved technology/practice under this indicator Unit of Measure: Number Disaggregated by: Value chain actor type, Technology type, Sex, Commodity (FTFMS-only disaggregate) Rational or justification for indicator (optional): Technological change and its adoption by different actors in the agricultural supply chain will be critical to increasing agricultural productivity, which is the Intermediate Result under which this indicator falls. 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: Direct beneficiary farmer sample surveys, standardized group questionnaires and 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 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE 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 FY14 0 Year Targets Actuals FY15 35,000 FY 16 45,000 50 FY17 70,200 FY18 72,000 LOP 101,700 THIS SHEET LAST UPDATED ON: Sept 14, 2016 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive Agricultural Sector Growth Intermediate Result- IR 1.1: Increased productivity of targeted commodities 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) of land cultivated using USG-promoted improved technology(ies) or management practice(s) during the current reporting year. Technologies to be counted here are agriculture-related, land-based technologies and innovations including those that address climate change adaptation and mitigation. Significant improvements to existing technologies should be counted. Examples of relevant technologies and technology types: • 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 rice, or high-protein maize) and/or more resilient to climate impacts; improved germ plasm. • Cultural Practices: e.g. seedling production and transplantation; cultivation practices such as planting density, moulding; mulching. • Pest management: e.g. Integrated Pest Management; appropriate application of insecticides and pesticides • Disease management: e.g. improved fungicides, appropriate application of fungicides • 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); fertilizers, erosion control • Irrigation: e.g. drip, surface, sprinkler irrigation; irrigation schemes • Water management: non-irrigation-based e.g. water harvesting • Climate mitigation or adaptation: e.g. conservation agriculture, carbon sequestration through low- or no-till practices no-till practices • Other: e.g. improved mechanical and physical land preparation. If a beneficiary cultivates a plot of land more than once in the reporting year, the area should be counted each time one or more improved technologies is applied. For example, because of access to irrigation as a result of a Feed the Future activity, a farmer can now cultivate a second crop during the dry season in addition to her/his regular crop during the rainy season. If the farmer applies Feed the Future promoted technologies to her/his plot during both the rainy season and the dry season, the area of the plot would be counted twice under this indicator. However, the farmer would only be counted once under EG.3.2-17 Number of farmers and others who have applied improved technologies. If a group of beneficiaries cultivate a plot of land as a group, e.g. an association has a common plot on which multiple association members cultivate together, and on which improved technologies are applied, the area of the communal plot should be counted under this indicator and recorded under the sex disaggregate “association-applied”. In addition, the association should be counted once under indicator EG.3.2-20 Number of for-profit private enterprises, producer’s organizations… and community-based organizations (CBOs) that applied improved organization-level technologies or management practices. 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.3.2-17 Number of farmers and others who have applied improved technologies. However, if the demonstration or training plot is cultivated by extension agents or researchers, (a demonstration plot in a research institute, for instance) neither the area nor the extension agent or researcher should be counted under this indicator or indicator EG.3.2-17. Technology Type Disaggregation: If more than one improved technology is being applied on a hectare, count the hectare under each technology type (i.e. double-count). In addition, count the hectare under the total w/one or more improved technology category. Since it is very common for Feed the Future activities to promote more than one improved technology, not all of which are applied by all beneficiaries at once, this approach allows Feed the Future to accurately track and count the uptake of different technology types, and to accurately count the total number of hectares under improved technologies. Unit of Measure: Hectares 51 Disaggregated by: Technology type, Sex, Commodity (FTFMS-only disaggregate) Rational or justification for indicator (optional): Tracks successful application of technologies and management practices in an effort to improve agricultural productivity, agricultural water productivity, sustainability, and resilience to climate impacts. 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: Direct beneficiary farmer sample surveys, project or association records and farm records. 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 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCEM&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 FY14 0 Targets Actuals FY15 52,500 FY 16 45,000 FY17 70,200 FY18 72,000 LOP 312,200 THIS SHEET LAST UPDATED ON: Sept 14, 2016 52 USAID Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive Agricultural Sector Growth Intermediate Result- IR 1.1: Increased productivity of targeted commodities Sub- Intermediate Result- Sub-IR.0: Name of Indicator: 4.5.2-42 Number of private enterprises, producers organizations, water users associations, women’s groups, trade and business associations and community-based organizations (CBOs) that applied 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. If yes link to foreign assistance frame work: DESCRIPTION Precise Definition(s): Total number of private enterprises (processors, input dealers, storage and transport companies) producer associations, cooperatives, water users associations, fishing associations, women’s groups, trade and business associations and community-based organizations (CBOs), including those focused on natural resource management, that applied new technologies or management practices at the organization level during the reporting year. Organization-level technologies and management practices include those in areas such as management (financial, planning, human resources), member services, procurement, technical innovations (processing, storage), quality control, marketing, etc. as a result of USG assistance in the current reporting year. Only count the entity once per reporting year, even if multiple technologies or management practices are applied. Any groups applying a technology that was first applied in the previous reporting year and continues to be applied in the current reporting year should be included under “Continuing.” However, if the organization added a new technology or management practice during the reporting year to the ones they continued to apply from previous year(s), they would be counted as “New.” No organization should be counted under both New and Continuing. Application of a new technology or management practice by the enterprise, association, cooperative or CBO is counted as one and not as applied by the number in their employees and/or membership. For example, when a farmer association incorporates new corn storage innovations as a part of member services, the application is counted as one association and not multiplied by the number of farmer-members. Unit of Measure: Number Disaggregated by: Type of organization (see indicator title for principal types) Duration: New, Continuing --New = entity applied a targeted new technology/management practice for the first time during the reporting year --Continuing = entity applied new technology(ies)/practice(s) in a previous year and continues to apply in the reporting year Rational or justification for indicator (optional): Tracks private sector and civil society behavior change to increase agricultural sector productivity. Type: Outcome Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Annual outcome survey Method of data collection and construction: Routine records (business services, grants etc.) 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 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 53 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCEM&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 FY14 0 Year Targets Actuals Notes FY 15 300 FY 16 338 FY 17 338 FY 18 338 LOP 450 THIS SHEET LAST UPDATED ON: Sept 14, 2016 54 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-4: Inclusive agriculture sector growth Intermediate Result 1.1: Increased Productivity of Targeted Commodities Sub-Result IR 1.1 :Enhanced human and institutional capacity development for increased sustainable agricultural sector productivity Name of Indicator: EG.3.2-4 Number of for-profit private enterprises, producers organizations, water users associations, women's groups, trade and business associations, and community-based organizations (CBOs) receiving USG food security related organizational development assistance Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___ FY2014, FY 2015, FY 2016, FY 2017 and FY2018 DESCRIPTION Precise definition(s): Total number of private enterprises, producers’ associations, cooperatives, producers organizations, fishing associations, water users associations, women’s groups, trade and business associations and community-based organizations, including those focused on natural resource management, that received USG assistance related to food security during the reporting year. This assistance includes support that aims at organization functions, such as member services, storage, processing and other downstream techniques, and management, marketing and accounting. “Organizations assisted” should only include those organizations for which implementing partners have made a targeted effort to build their capacity or enhance their organizational functions. In the case of training or assistance to farmer’s association or cooperatives, individual farmers are not counted separately, but as one entity. Unit of Measure: Number Disaggregated by: Level 1: Type of organization (see indicator title for principal types) Rationale or Justification for Indicator: Tracks civil society capacity building that is essential to building agricultural sector productivity Type: Output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Producer/FBO and other beneficiary organization's farm records Method of Data Collection and Construction: Survey/on farm measurements of representative sample of producers/FBOs and other beneficiary organizations. 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 MIS DATA QUALITY ISSUES Date of Initial Data Quality Assessment and Name of Reviewer: TBD 55 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 changed from “4.5.2(11): Number of food security private enterprises (for profit), producers organizations, water users associations, women’s groups, trade and business associations, and community-based organizations (CBOs) receiving USG assistance” to “EG.3.2-4 Number of for-profit private enterprises, producers organizations, water users associations, women's groups, trade and business associations, and community-based organizations (CBOs) receiving USG food security related organizational development assistance” Dropped duration: New/Continuing disaggregate Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 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 Coordinator 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 FY14 0 YEAR Targets Actuals FY15 400 FY16 450 FY17 450 FY18 450 LOP 600 THIS SHEET LAST UPDATED ON: Sept 14, 2016 56 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-4 : Inclusive agriculture sector growth Intermediate Result 1.1: Improved agriculture productivity Sub-Result IR 1.1 :Enhanced human and institutional capacity development for increased sustainable agricultural sector productivity Indicator EG. 3.2-1 Number of individuals who have received USG supported short-term agricultural sector productivity or food security training Is this an Annual Report indicator? No ___ Yes __x__, for Reporting Year(s) FY 2014,FY 2015, FY2016, FY 2017 and FY2018 DESCRIPTION Precise definition(s): The number of individuals to whom significant knowledge or skills have been imparted through interactions that are intentional, structured, and purposed for imparting knowledge or skills should be counted. The indicator includes farmers who receive training in a variety of best practices in productivity, post-harvest management, linking to markets, etc. It also includes rural entrepreneurs, processors, managers and traders receiving training in application of new technologies, business management, linking to markets, etc, and training to extension specialists, researchers, policymakers and others who are engaged in the food, feed and fiber system and natural resources and water management. There is no pre-defined minimum or maximum length of time for the training; what is key is that the training reflects a planned, structured curriculum designed to strengthen capacities, and there is a reasonable expectation that the training recipient will acquire new knowledge or skills that s/he could translate into action. However, Operating Units may choose to align their definition of short￾term training with the TrainNet training definition of 2 consecutive class days or more in duration, or 16 hours or more scheduled intermittently. Count an individual only once, regardless of the number of trainings received during the reporting year and whether the trainings covered different topics. Do not count sensitization meetings or one-off informational trainings. In-country and off-shore training are included. Training should include food security, water resources management/IWRM, sustainable agriculture, and climate change risk analysis, adaptation, mitigation, and vulnerability assessments as they relate to agriculture resilience, but should not include nutrition-related trainings, which should be reported under indicator HL.9-4 instead. Delivery mechanisms can include a variety of extension methods as well as technical assistance activities. This indicator is to count individuals receiving training, for which the outcome, i.e. individuals applying new practices, should be reported under EG 3.1-17 Unit of Measure: Number Disaggregated by: -- Level 1: --Type of individual: • Producers (farmers, fishers, pastoralists, ranchers, etc.) • People in government (e.g. policy makers, extension workers) • People in private sector firms (e.g. processors, service providers, manufacturers) • People in civil society(NGOs, CBOs, CSOs, research and academic organizations) Note: While producers are included under MSMEs under indicators EG 3.2-3, only count them under the Producers and not the Private Sector Firms disaggregate to avoid double-counting. While private sector firms are considered part of civil society more broadly, only count them under the Private Sector Firms and not the Civil Society disaggregate to avoid double-counting. Level 2: Sex: male, female Type: Output Rationale or Justification for Indicator: Measures enhanced human capacity for increased agriculture productivity, improved food security, policy formulation and/or implementation, that is key to transformational development Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): Program training attendance records Method of Data Collection and Construction: Training forms and MIS database Frequency/Timing of Data Collection: Quarterly Frequency of Reporting: Quarterly 57 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 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE 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: Training records with sign in sheets of participants are obtained from the field and reported on as part of the quarterly reports from the field offices. The data is also captured in the ADVANCE MIS. Individuals are counted once for overall participation irrespective of the number of training programs they participated in. PERFORMANCE INDICATOR VALUES Notes Baseline Value FY 14 Year Targets Actuals FY14 15,000 9,052 FY15 30,000 FY16 58,500 FY17 60,000 FY18 56,250 LOP 80,000 THIS SHEET LAST UPDATED ON: Sept 14, 2016 58 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-4 : Inclusive agriculture sector growth Intermediate Result 2: Expanding markets and trade Project Output: Indicator EG.3.2-19: Value of small-holder incremental sales generated with USG assistance Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___Baseline FY 14, FY2015, FY 16, FY17 and FY18 DESCRIPTION Precise Definition(s): This indicator will collect both volume (in metric tons) and value (in US dollars) of purchases from small￾holder direct beneficiaries of targeted commodities for its calculation. This includes all sales by the small-holder direct beneficiaries of the targeted commodity (ies), not just farm-gate sales. Only count sales in the reporting year attributable to the Feed the Future investment, i.e. where Feed the Future assisted the individual farmer directly. Examples of Feed the Future assistance include facilitating access to improved seeds and other inputs and providing extension services, marketing assistance or other activities that benefited small-holders. The value of incremental sales indicates the value (in USD) of the total amount of targeted agricultural products sold by small-holder direct beneficiaries relative to a base year and is calculated as the total value of sales of a product (crop, animal, or fish) during the reporting year minus the total value of sales in the base year. The number of direct beneficiaries of Feed the Future activities often increases over time as the activity rolls-out. Unless an activity has identified all prospective direct beneficiaries at the time the baseline is established, the baseline sales value will only include sales made by beneficiaries identified when the baseline is established during the first year of implementation. The baseline sales value will not include the “baseline” sales made prior to their involvement in the Feed the Future activity by beneficiaries added in subsequent years. Thus the baseline sales value will underestimate total baseline sales of all beneficiaries, and consequently overestimate incremental sales for reporting years when the beneficiary base has increased. To address this issue, Feed the Future requires reporting the number of direct beneficiaries for each value chain commodity along with baseline and reporting year sales. FTFMS uses the baseline sales and baseline number of beneficiaries to establish average sales per beneficiary at baseline. The average sales per beneficiary are multiplied by the number of beneficiaries in each reporting year to create an adjusted baseline sales value. To accurately estimate out-year targets for incremental sales, targets for number of beneficiaries are also required. It is absolutely essential that a Baseline Year Sales data point is entered. The Value of Incremental Sales indicator value cannot be calculated without a value for Baseline Year Sales. If data on the total value of sales of the value chain commodity by direct beneficiaries prior to Feed the Future activity implementation started is not available, do not leave the baseline blank or enter ‘0’. Use the earliest Reporting Year Sales actual as the Baseline Year Sales. This will cause some underestimation of the total value of incremental sales achieved by the Feed the Future activity, but this is preferable to being unable to calculate incremental sales at all. If a direct beneficiary sample survey is used to collect incremental sales data, sample survey estimates must be extrapolated to total beneficiary estimated values before entry into FTFMS to accurately reflect total sales by the activity’s direct beneficiaries. Unit of Measure: Volume (metric tons) Value (USD) Number of direct beneficiaries From these 2 data points, system will calculate incremental sales automatically: [Volume (in metric tons) sold x Crop price in previous year] – [Volume (in metric tons) sold x Crop Price in base year] = Value of incremental sales in current year Disaggregated by: Commodity Rationale or Justification for Indicator: Value (in US dollars) of purchases from small-holders of targeted commodities is a measure of the competitiveness of those small￾holders. This measurement also helps track access to markets and progress toward commercialization by subsistence and semi￾subsistence small-holders. Improving markets will contribute to the Key Objective of increased agricultural productivity and production, which in turn will reduce poverty and thus achieve the goal. Lower level indicators help set the stage to allow markets and trade to expand. Type: Outcome Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): Producers, FBOs, Aggregators/buyers Method of Data Collection and Construction: Examination of sales/purchase records of buyers, processors, producers. Survey of representative sample of producers. 59 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 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: Indicator changed from “4.5.2(23): Value of incremental sales (collected at farm level) attributed to FTF implementation to “EG.3.2-19 Value of small-holder incremental sales generated with USG assistance” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 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 Coordinator and HQ M&E Team Reporting of Data: Annual Performance Monitoring Report Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline value F14 Maize: $ 466 / Rice : $ 369,729 / Soya: 319, 593 Year Targets Actuals Volume (MT) Value(US$) Volume (MT) Value(US$) FY15 $6,780,000 FY16 $9,320,000 FY 17 $16,940,000 FY 18 $17,880,000 LOP $67,880,000 THIS SHEET LAST UPDATED ON: Sept 14, 2016 60 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-4 : Inclusive agriculture sector growth Intermediate Result 2: Increased private sector investment Sub-Result IR1: Indicator Title: Indicator EG.3.2-21 Number of firms (excluding farms) or civil society organizations (CSOs) engaged in agricultural and food security-related manufacturing and services that have increased profits or become financially self-sufficient with USG assistance” Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___Baseline FY 2014, FY2015, FY 2016, FY 2017 and FY2018 DESCRIPTION Precise definition(s): To measure sustainable private sector investment, we will look at profitability of applicable firms and financial self-sufficiency of civil society organizations (CSOs) as a marker of viability. A CSO is financially self-sufficiency when the COS’s annual income is more than annual operating expenses and annual amortization and depreciation of permanent assets. Although profitability or self-sufficiency measured during the period the USG is providing assistance does not demonstrate all aspects of a whether a business or a CSO will remain sustainably successful after withdrawal of USG assistance, it is certainly an important measure of its capacity to function effectively. Only the profitability of firms and self-sufficiency of CSOs who are receiving USG capacity-building assistance that is intended to increase profitability or viability should be tracked. A firm should be counted if it operated more profitably in the reporting year than it did the previous reporting year. A CSO should be counted if it was financially self-sufficient in the reporting year and it had not been financially self-sufficient in the previous reporting year. Unit of Measure: Number Disaggregated by: Type of entity (Firm, CSO) Rationale or Justification for Indicator: A main goal of local capacity building is to leave behind viable businesses and service providers to contribute to the economic growth of the agriculture and food-security sector. Profitability of firms and self￾sufficiency of civil society organizations is one way to demonstrate that viability and sustainability of the businesses/firms/CSOs in which we invest. Type: Outcome Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): MSME/Firms Financial statements Method of Data Collection and Construction: Data will be collected from a sample of MSME/Firms supported using a survey questionnaire 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 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: Indicator title changed from “Indicator 4.5.2(43) Number of firms (excluding farms) or Civil Society Organizations (CSOs) engaged in agricultural and food security-related manufacturing and services now operating more profitably (at or above cost) because of USG assistance” to “EG.3.2-21 Number of firms (excluding farms) or civil society organizations (CSOs) engaged in agricultural and food security-related manufacturing and services that have increased profits or become financially self-sufficient with USG assistance” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 project and the data collection methods, sources and timelines that will be established. 61 PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VCOA M&E Coordinator Presentation of data: Table Review of Data: ACDI/VOCA M&E Coordinator and HQ M&E Team Reporting of Data: Annual Performance Monitoring Report Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Baseline value FY14 0 Notes Year Targets Actuals FY15 30 FY 16 50 FY 17 75 FY 18 100 LOP 100 THIS SHEET LAST UPDATED ON: Sept 14, 2016 62 Performance Indicator Reference Sheet Goal: Increased competitiveness of agricultural value chains in Ghana SO-4 : Inclusive agriculture sector growth Intermediate Result 1.2: Expanding Markets & Trade Sub-Result IR 1.2.4: Improved access to business development and sound and affordable financial and risk management services Indicator Title: EG.3.2-6 Value of agricultural and rural loans as a result of USG assistance Is this an Annual Report indicator? No __ Yes __x__, for Reporting Year(s) ___ FY2014, FY 2015,FY 2016, FY 2017 and FY2018 If yes link to foreign assistance framework: DESCRIPTION Precise definition(s): This indicator sums cash loans made (i.e. disbursed) during the reporting year to direct beneficiary producers (farmers, fishers, etc.), input suppliers, transporters, processors, and loans to other MSMEs in rural areas that are in a targeted agricultural value chain, as a result of USG assistance. The indicator counts loans disbursed to the recipient, not loans merely made (e.g. in process, but not yet available to the recipient). The loans can be made by any size financial institution from micro-credit through national commercial bank, and includes any type of micro-finance institution, such as an NGO. This indicator only counts cash loans; do not include in-kind loans. It also only counts loans made by financial institutions, and not informal groups such as village savings and loan groups that are not formally registered as a financial institutions. Unit of Measure: US Dollars Disaggregated by: Level 1: Type of loan recipient: producers, local traders/assemblers, wholesalers/processors, others. Level 2: Sex of recipient: --Male --Female --n/a For producers, the sex of the loan recipient should be used. For firms, if the enterprise is a single proprietorship, the sex of the proprietor should be used for classification. For larger enterprises, the majority ownership should be used. When this cannot be ascertained, the majority of the senior management should be used. If this cannot be ascertained, use n/a (not available) Rationale or Justification for Indicator: Making more financial loans shows that there is improved access to business development and financial services. This in turn will help expand markets and trade (and ought to also contribute to IR1’s expanding agricultural productivity) which will help achieve the key objective of inclusive (the MSMEs) agriculture sector growth (with agriculture sector being defined broader than just crop production). In turn this contributes to both goals of reducing poverty and hunger. Type: Output Direction of change: Higher= better PLAN FOR DATA COLLECTION Data Source(s): participating FIs Record/ beneficiary records Method of Data Collection and Construction: Examination of loan records of beneficiaries from FIs Frequency/Timing of Data Collection: Quarterly, according to crop cycle 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 Location of Data Storage: ACDI/VOCA ADVANCE 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 63 Changes to Indicator: indicator title changed from “4.5.2-29: Value of Agricultural and Rural Loans” to “ EG.3.2-6 Value of agricultural and rural loans as a result of USG assistance” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 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 Coordinator 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 FY14 0 Notes YEAR Target Result FY14 $500,000 $553,232 FY15 $1,000,000 FY16 $1,000,000 FY17 $1,000,000 FY18 $800,000 LOP $4,300,000 THIS SHEET LAST UPDATED ON: Sept 14, 2016 64 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains in Ghana SO: Inclusive agricultural sector growth Intermediate Result - IR 1.2: Increased Market Access and Trade Sub- Result- IR.1: Name of Indicator: EG.3.2-22 Value of new private sector capital investment in the agriculture sector or food chain leveraged by Feed the Future implementation Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 and FY2017 and FY2018 If yes link to foreign assistance frame work: DESCRIPTION Precise Definition(s): Investment is defined as any use of private sector resources intended to increase future production output or income, to improve the sustainable use of agriculture-related natural resources (soil, water, etc.), to improve water or land management, etc. The “food chain” includes both upstream and downstream investments. The indicator only includes capital investments. It does not include operating capital, for example, for inputs or inventory. Upstream investments include any type of agricultural capital used in the agricultural production process such as animals for traction, storage bins, and machinery. Downstream investments could include capital investments in equipment, etc. to do post-harvest transformation/processing of agricultural products as well as the transport of agricultural products to markets. “Private sector” includes any privately-led agricultural activity managed by a for-profit formal company. A CBO or NGO resources may be included if they engage in for-profit agricultural activity. “Leveraged by Feed the Future implementation” indicates that the new investment was directly encouraged or facilitated by activities funded by ADVANCE 2. Investments reported should not include funds received by the investor from USG as part of any grant or other award. New investment means investment made during the reporting year. Unit of Measure: US Dollars Disaggregated by: None Rational or justification for indicator (optional): Increased investment is the predominate source of economic growth in the agricultural and other economic sectors. Private sector investment is critical because it indicates that the investment is perceived by private agents to provide a positive financial return and therefore is likely to lead to sustainable increases in agricultural production. Agricultural growth is critical to achieving the Feed the Future goal to “Sustainably Reduce Global Poverty and Hunger.” Type: Output Direction of change: Higher is better PLAN FOR DATA COLLECTION Data Source(s): Secondary sources (from the financial records of private sector engaged with ADVANCE) Method of data collection and construction: Examination and organization of financial service data Frequency/Timing of Data Collection: Annually Reporting Frequency: Annually 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 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 65 Changes to Indicator: Indicator title change from “4.5.2-38 Value of new private sector investment in the agriculture sector or food value chain leveraged by FTF implementation” to “EG.3.2-22 Value of new private sector capital investment in the agriculture sector or food chain leveraged by Feed the Future implementation” Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ACDI/VOCA M&E Coordinator Presentation of data: Table and annual report narrative Review of Data: ADVANCE M&E Coordinator and ACDI/VOCA headquarters M&E Reporting of Data: Quarterly/Semi-annual/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Baseline Values FY14 0 Notes Year Targets Actuals FY14 $800,000 $210,216 FY15 $800,000 FY16 $800,000 FY17 $800,000 FY18 $800,000 LOP $4,000,000 THIS SHEET LAST UPDATED ON: Sept 15, 2016 66 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains SO: Inclusive agricultural sector growth Intermediate Result IR-1.2: Increased Market Access and Trade Sub- Result- IR.1: 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 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 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 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 Procedures for Future Data Quality Assessments: To verify the quality and consistency of the data collected and disseminated, the ADVANCE 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE M&E Coordinator Presentation of data: Table and annual report narrative Review of Data: ACDI/VOCA M&E Coordinators1and ACDI/VOCA headquarters M&E 67 Reporting of Data: Quarterly/Semi-annual/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Year Targets Actuals Notes Baseline Year FY14 0 FY15 200 FY16 225 FY17 225 FY18 225 LOP 300 THIS SHEET LAST UPDATED ON: Sept 14, 2016 68 USAID Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains SO: Inclusive Agriculture sector growth Intermediate Result 1.3: Strengthened Local Capacity for Advocacy and Activity Implementation Sub- Result- IR.1: Name of Indicator: Number of organizations/ enterprises identified as high potential for future awards Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016, FY2017 and FY2018 DESCRIPTION Precise Definition(s): Number of local organizations or enterprises who received capacity building from ADVANCE and who meet criteria to receive funding from the USG Unit of Measure: Numbers Disaggregated by: Type of organization and by value chain Rational or justification for indicator (optional): Type: Output Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): ADVANCE field offices, MIS database Method of data collection and construction : Capacity building records and reports Frequency/Timing of Data Collection: Quarterly Estimated coast of data collection: Reporting Frequency: Annually 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 MIS Database DATA QUALITY ISSUES Date of Initial Data Quality Assessments and name of reviewer: TBD and M&E Coordinator Known Data Limitations and Significance (if any): TBD Actions Taken or Planned to Address Data Limitations: TBD Date of Future Data Quality Assessments (optional): TBD 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE M&E Coordinator and ACDI/VOCA headquarters M&E Presentation of data: Table and annual report narrative 69 Review of Data: ACDI/VOCA M&E Coordinator Reporting of Data: Annual Report and Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY14 0 Year Targets Actuals FY15 3 FY16 4 FY17 5 FY18 7 LOP 7 THIS SHEET LAST UPDATED ON: Sept 14, 2016 70 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains SO: Inclusive Agriculture sector growth Intermediate Result 1.3: Strengthened Local Capacity for Advocacy and Activity Implementation Sub- Result- IR.1: Name of Indicator: Number of organizations/ enterprises receiving capacity building support against key milestones Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 ,FY2017 and FY2018 DESCRIPTION Precise Definition(s): Number of organizations who received capacity building support from ADVANCE in at least one of the following key areas: Governance, Administration, Human Resources Management, Financial Management, Organizational Management, Program Management and Project Performance Management. Unit of Measure: Numbers Disaggregated by: Type of organization Rational or justification for indicator (optional): Type: Output Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): ADVANCE field offices, MIS database Method of data collection and construction : Capacity building records in Database and reports Frequency/Timing of Data Collection: Quarterly Estimated coast of data collection: Reporting Frequency: Quarterly 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 MIS Database 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): TBD 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE M&E and ACDI/VOCA Headquarters M&E Presentation of data: Table and report narrative 71 Review of Data: ACDI/VOCA M&E Coordinator Reporting of Data: Quarterly/Semi-annual/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY14 0 Year Targets Actuals FY15 9 FY16 20 FY17 40 FY18 50 LOP 50 THIS SHEET LAST UPDATED ON: Sept 14, 2016 72 Performance Indicator Reference Sheet Goal : Increased competitiveness of agricultural value chains SO: Inclusive Agriculture sector growth Intermediate Result 1.3: Strengthened Local Capacity for Advocacy and Activity Implementation Sub- Result- IR.1: Name of Indicator: Number of awards made directly to local organizations by USAID Is this a Performance Plan and Report indicator? No ___ Yes __x__, for Reporting Year(s), FY 2014, FY 2015, FY2016 and FY2017 and FY2018 If yes link to foreign assistance frame work: DESCRIPTION Precise Definition(s): This indicator counts the number of awards made directly by the USG (not through intermediaries) to local organizations each fiscal year. It excludes awards made to public sector institutions but can include awards made to parastatals or universities. Awards can be either acquisition or assistance. For purposes of indicator reporting, at the time of the award a “local organization” must:1) Be organized under the laws of the recipient country, 2) Have its principal place of business in the recipient country, 3) Be majority owned by individuals who are citizens or lawful permanent residents of the recipient country or be managed by a governing body, the majority of whom are citizens or lawful permanent residents of a recipient country, 4) Not be controlled by a foreign entity or by an individual or individuals who are not citizens or permanent residents of the recipient country Unit of Measure: Numbers Disaggregated by: Type of organization Rational or justification for indicator (optional): Type: Output Direction of change: Higher=better PLAN FOR DATA COLLECTION Data Source(s): USAID records Method of data collection and construction : KII Frequency/Timing of Data Collection: Annually Estimated coast of data collection: Reporting Frequency: Annually 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 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 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 project and the data collection methods, sources and timelines that will be established. PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING Data Analysis: ADVANCE M&E and ACDI/VOCA Headquarters M&E Presentation of data: Table and annual report narrative Review of Data: TBD 73 Reporting of Data: Quarterly/Semi-annual/Annual Performance Monitoring Report (PMR) Notes on Baselines/Targets: PERFORMANCE INDICATOR VALUES Notes Baseline Values FY14 0 Year Targets Actuals FY15 2 FY16 3 FY17 4 FY18 5 LOP 5 THIS SHEET LAST UPDATED ON: Sept 14, 2016 74 Annex 4: First year’s implementation plan for MEL activities Feb Mar Apr May Jun Jul Au g Sept Category and task Person(s)/ organization responsible Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Staffing and training Hire M&E staff Conduct orientation for M&E staff Conduct intensive training for M&E staff MEL plan Develop draft MEL plan Submit draft plan to USAID Receive feedback/comments from USAID Finalize and submit revised MEL plan Evaluations and studies Finalize list of indicators with USAID Advertise and select external M&E contractor for baseline studies Complete baseline studies Database design, data capture, storage and use Design M&E data collection forms Hire programmer to design M&E database Develop data quality strategy 75 Feb Mar Apr May Jun Jul Au g Sept Category and task Person(s)/ organization responsible Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Wk 1 Wk 2 Wk 3 Wk 4 Train all field staff on M&E and quality data collection and management processes Data collection validation and entry Profiling actors as they are identified Routine data collection and entry by all staff Design annual survey instrument Conduct annual survey Data quality reviews Reporting Prepare and submit quarterly reports to USAID