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Eaapp - Pmp - August 2011 - Final
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Transcript of Eaapp - Pmp - August 2011 - Final
MONITORING AND EVALUATION SERIES
PERFORMANCE MONITORING PLAN (PMP) JANUARY 2010 DECEMBER 2014
July, 2011
This is a living Document and will be updated periodically as required!
ASARECA-EAAPP PMP: 2010-2015
List of AcronymsASARECA CAADP CGIAR COMESA DQA EAC ECA EIAR FAAP FARA KARI M&E MTR NARS NEPAD NGOs PIP PIRS PMF PMIS PMP RCoE Association for Strengthening Agricultural Research in Eastern and Central Africa Comprehensive African Agricultural Development Program Consultative group for international agricultural research Common Markets for Eastern and Southern Africa Data Quality Assessment East Africa community Eastern and Central Africa Ethiopian Institute of Agricultural Research Framework for African Agricultural Productivity Forum for Agricultural Research in Africa Kenya Agricultural Research Institute Monitoring and Evaluation Mid-Term Review National Agricultural Research Systems New Partnerships for African Development Non Governmental Organization Project Implementation Plan Performance Indicator Reference Sheet Performance Measurement Framework Programme Management Information System Performance Monitoring Plan Regional Centre of Excellence
ASARECA-EAAPP PMP: 2010-2015
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Table of Contents
1 Contents List of Acronyms................................................................................................................................................. 2 Table of Contents ............................................................................................................................................... 3 1. Executive summary ................................................................................................................................... 4 2. Introduction ........................................................................................................................................... 5 3. Project Description ................................................................................................................................ 6 4. EAAPPs Results Framework.................................................................................................................. 8 Harmonized Results Framework....................................................................................................................... 9 5. Performance Indicator Reference Sheets ........................................................................................... 11
ASARECA-EAAPP PMP: 2010-2015
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1.
Executive summary
This Performance Monitoring Plan is made as a final document for ensuring effective and performance-based monitoring and evaluation of the EAAPP. Its development followed a thorough review of relevant project documents that were developed after consultation with key stakeholders. The documents consulted included: The Project Appraisal Document (Report No: 48295-AFR); Draft Indicator Reference Document developed during the EAAPP M&E Workshops in Addis Ababa and Nairobi; and Financing Agreements between the four countries (Ethiopia, Kenya, Tanzania, and Uganda) and International Development Association (IDA). This PMP is intended to be a management tool and a living document to be reviewed and revised frequently. It is organized as follows:1.
Section 1: Introduction. This section gives a brief background of EAAPP. It introduces various stages of ASARECAs M&E planning processes, and also shows the ASARECAs five main results areas along the hierarchy of objectives. It concludes with a brief section of the roles of M&E Unit within ASARECA. Section 2: Project Development Objectives and Key Indicators. This section highlights the guiding objectives as well as the associated indicators of the project. Section 3: Program Results Framework. This section summarizes the projects Results (conceptual) Framework. Section 4: Annexes. This PMP is backed up with a series of annexes, namely: 1. Annex 1: Performance Indicator Reference Sheets (PIRS). Following the M&E Workshop on the development of M&E Frameworks, this section is devoted to the indicator reference sheets. These sheets shall be updated periodically, thus showing the progress made against the milestones and targets.2.
2.
3.
4.
Annex 2: Performance Measurement Framework. This framework summarizes the Performance Monitoring Plan thus providing a snapshot of the progress so far made on the project.
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2. Introduction
The East Africa Agricultural Productivity Program (EAAPP) was conceived to meet the International Development Association (IDA) in ensuring the following: (i) support activities that will be coordinated across at least three countries, (ii) generate benefits that spill over country boundaries, (iii) support the Common Market for Eastern and Southern Africa (COMESA), (iv) provide a platform for policy harmonization, and (v) form part of a regional agricultural strategy. EAAPP aims to raise farm incomes, reduce poverty and improve food security by: (i) strengthening Regional Centres of Excellence (RCoE) in agricultural research in Ethiopia, Kenya, Tanzania, and Uganda and (ii) to support these centres in the production of selected varieties of improved seeds and to improve access of poor farmers to more productive plant varieties. Improving agricultural research is Pillar IV of NEPADs Comprehensive Africa Agricultural Development Program (CAADP). At the regional level, EAAPP also provides a vehicle for implementing the agricultural productivity agenda of ASARECA, which was created to enhance regional collective action in agricultural research for development, extension, training, and education. ASARECA has been mandated by COMESA and Forum for Agricultural Research in Africa (FARA) to take lead in coordinating implementation of CAADP Pillar IV and the application of the principles of the FAAP in East Africa. EAAPP focuses on four main commodities Cassava (Uganda), Dairy (Kenya), Rice (Tanzania), and Wheat (Ethiopia). Monitoring and evaluation of the planned activities are coordinated by ASARECA. The RCoE as well as the National Coordinators play a major role in coordinating the project implantation, while the M&E Officers shall ensure effective monitoring, data collection and reporting. Together with all partners involved, ASARECA will lead the development of the broad M&E framework for the project to provide training for partners to facilitate evidence-based and adaptive management. It shall apply its M&E framework, which is in line with the Comprehensive Africa Agricultural Development Program (CAADP) framework that is adopted by many of the Africa Union (AU) member states, to facilitate monitoring and evaluation of EAAPP. ASARECA will ensure that the results targets for the project are monitored and achieved. In order to measure EAAPPs success, ASARECA, in collaboration with the team members from all the four Centres of Excellence, has designed this Performance Monitoring Plan (PMP). For effective M&E, each RCoE has also developed own PMPs. This PMP lays out the monitoring and evaluation system that ASARECA and the RCoEs will implement to determine the projects success. This PMP establishes linkages between (i) the approaches, indicators, milestones and targets described in the Project Appraisal Document; (ii) the activities described in the same document workplan; and (iii) Country Project Implementation Plans (PIPs). The PMP presents and defines project-specific objectives, terminology, beneficiary populations, indicators, measurements, and targets. It also develops the monitoring and evaluation system to be used for data collection, analysis and reporting.
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3. Project Description
Project development objective and key indicators The objectives of the Project are to: Enhance regional specialization in agricultural research Enhance regional collaboration in agricultural training and dissemination; and Facilitate increased sharing of agricultural information, knowledge and technology, across the Recipients boundaries. The objective will be pursued by tracking progress on the following:
Strengthening Regional Centres of Excellence: This component aims at strengthening theinstitutional capacities that are needed to establish RCoEs. Capacity strengthening will focus on the physical facilities and human resources needed to sustain program objectives and outcomes at both the regional and national levels. The main sub-components will focus on: Improving RCoE infrastructure for all the four commodities. This includes: rehabilitation and modernization of physical facilities; developing infrastructure for regional training programs in the commodities; greenhouses; irrigation facilities for research and seed multiplication activities; laboratory equipment; vehicles and farm machinery; library materials; and software and hardware to support information system. Building the human resource capacity of the RCoE. This includes: provision of training (short- and long-term); developing graduate training plans for all commodities; technology dissemination; and filling human resource gaps.
Technology Generation, Training and Dissemination: This component will support technology generation, training, and dissemination that has been agreed at national and regional levels as evidenced by inclusion in an annual regional research plan for each commodity and for training and dissemination. The main sub-components will focus on: Encouraging generation of technology through support to research activities for all the commodities. Carrying out technology dissemination sub-projects for all the commodities, including value addition, marketing and agribusiness. Identifying short term techniques appropriate for broad dissemination and developing training programs Improved Availability of Seeds, Planting Material and Livestock germplasm: This component will support multiplication of seeds and breeds, strengthen the enabling environment for regional seed and breed trade, and improve capacity of seed and breed producers and traders. The main sub-components will focus on: Improving the availability of seeds, planting materials and genetic dairy materials, including expanding the production, storage and distribution of dairy genetic material, and of breeder, pre-basic, basic and commercial seed for targeted commodities, through the provision of works, and technical advisory services. Provision of training and technical advisory services to support the development of existing and establishment of new businesses and agencies involved in the production and supply of seeds, planting materials and breeding services. Supporting the harmonization of seed policies and seed services, building on regional agreements to harmonize national seed policies and regulations to allow the emergence of a regional seed industry. Government seed services (seed testing and certification, plant variety protection, and phytosanitary controls) will also be supported.The achievement of these objectives and sub-components will be measured by the following indicators: Project Outcome Indicators Number of farmers, processors and others who have adopted new technologies on the basis of: Percentage of increase in adoption of new varieties, improved dairy technologies, and management practices; and Percentage of increase in adoption of improved processing and handling methods;ASARECA-EAAPP PMP: 2010-2015 6
Area under improved technologies, and/or number of improved technologies on the basis of: Percentage of increase in land area with seeds of improved cultivars, and Rate of increase in number of improved dairy genetic materials (%); Increase in production and/or productivity at farm level on the basis of percentage of the increase in production or productivity over control technology for all disseminated new technologies. Intermediate Outcome Indicators Increase in research scientists working in regional research projects on the basis of the percentage of total research staff of the RCoE; Increase in the number of new technologies developed by the RCoE; Increase in existing and new technologies disseminated in more than one Program Country; Increase of cultivars for selected commodities registered in more than one Program Country based on the number per selected commodity; Percentage of regional research and training and dissemination activities implemented according to the Annual Regional Research and Budget Plans; Harmonized M&E system for RCoEs in cooperation with ASARECA developed, adopted, and implemented. This PMP is therefore developed to enhance documentation of project outcomes and intermediary results outlined in Section 3 below. It builds on the requirements in the PAD that a comprehensive reference document be developed as a first step in the implementation of the M&E plan. Through this PMP, the following indicators will be periodically tracked: Adequacy of infrastructure, and of human and financial resources in RCoEs; Numbers of new varieties and solutions to identified problems achieved in the 4 commodities; Area planted to improved agricultural technologies in identified priority areas in participating countries; Numbers of improved animals in participating countries; Training of service providers and farmers in new technologies for the selected commodities in participating countries; and Transaction costs associated with flows of technologies across national boundaries.4. Additional Supporting Performance Monitoring Activities
To ensure effective performance monitoring, ASARECA will organize bi-Annual Joint Review Meetings (Portfolio Reviews) with RCoE Coordinators and M&E Officers. These meetings will provide a platform for collective assessment of progress against milestones (according to the Annual Workplan and Budget). These reviews are targeted to lead to management decisions about program and project implementation and feedback. At a minimum, the review will examine the following: Progress made by RCoEs towards the achievement of the PDO and intermediate outcomes Evidence that outputs of activities are adequately supporting the relevant results and ultimately contributing to the achievement of the PDO Adequacy of inputs for producing planned outputs Adequacy of performance indicators selected in the PMP Status and timeliness of input mobilization efforts (e.g. procurement based on the annual procurement plans) Status of critical assumptions and causal relationships defined in the results framework along with the related implications for performance Status of cross-cutting themes and/or synergies between key results Data Quality Assessment (DQA) Procedures The ASARECA M&E Unit will integrate Data Quality Assessment (DQA) into ongoing activities (i.e. combine a random check of partner data with a regularly scheduled site visit). When conducting DQA, the team members (led by ASARECA M&E unit staff) will use a Data Quality Checklist. The key findings
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will be written up in a short memo (as part of the trip report form) and filed in the RCoE Performance Management Files. If the Team identifies any data limitations for the performance indicators (either during initial or periodic assessments), it will correct the limitations to the greatest extent possible. The Team will document any actions taken to address data quality problems in the appropriate Performance Indicator Reference Sheet(s). However, if data limitations prove too intractable and damaging to data quality, the Team will seek alternative data sources, or will develop alternative indicators. Known Data Limitations and Significance (if any) While indicator specific data limitations have been identified in the Indicator Protocols, this section seeks to identify limitations based on data collection, and detail the action taken or planned to address these limitations. The following sample table will be used in tracking the progress made towards addressing these limitations.Data Collection Limitation Validity and reliability of data Lack of consistent terms Lack of objective evaluation criteria Integrity as data or records might have been manipulated Self-reported data may under or over report socially-desirable results Action Planned to Address Data Limitation If possible, provide technical support to improve If possible, standardize data collection forms for uniformity of terms used and data tracked If possible, conduct retreat with implementing partners to discuss and determine evaluation criteria If possible, perform spot checks and independent evaluation to validate data provided by partner agencies This bias is an inherent limitation of most survey research methodologies. While it is difficult to counteract, triangulation with other sources of data will provide points of reference for the estimation of over/under reporting and it would be expected that levels of bias introduced will not vary greatly over time, thus allowing for less biased trend analysis.
Reviewing and Updating the PMP This PMP serves as a living document that ASARECA and the RCoEs plan to use to guide EAAPPs performance management efforts. Therefore, the PMP will be regularly updated to reflect identifiable changes during implementation. Such reviews and updates will preferably be done during the Annual Portfolio Reviews, and will consider the following issues: Are the performance indicators measuring the intended results? and providing the information needed? How can the PMP be improved? However, for uniformity, the EAAPP M&E Team (where necessary) shall propose relevant changes to the PMP regarding indicators or data sources only after receiving No Objection from the Projects Technical Teal Leader (TTL). A clear rationale for proposed adjustments will be clearly documented. However, minor adjustments in the PMP elements (such as indicator definition or responsible individual), are allowed as long as the M&E Unit agrees to do so.5. EAAPPs Results Framework
To ensure effective tracking of performance within EAAPP, a harmonized Results Framework (see table below) was developed. Each RCoE used this framework to develop their own. The following guiding principles were taken into account: Harmonization with M&E systems and indicators of CAADP, ASARECA, and FARA; Focus on process and output indicators; Tracking progress at national and regional levels; and Addressing partnerships and linkages. The consolidated Results Framework focuses on the indicators listed in the PAD, but also gives room for identification of custom indicators (shown in red). These custom indicators allow project implementers to track performance within their RCoE, besides addressing all the standard (mandatory) indicators.
ASARECA-EAAPP PMP: 2010-2015
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Harmonized Results FrameworkOverall Goal Enhanced sustainable productivity, value added, and competitiveness of the sub regional agricultural system. Verifiable Indicators Percent increase in yield of selected commodities Percent increase in labor productivity in selected products Annual growth rate in Total Factor Productivity (TFP) PDO (Purpose) The PDO is to: a) Enhance regional specialization in agricultural research b) Enhance collaboration in agriculture training and technology dissemination; and c) Facilitate increased transfer of agricultural technology, information and knowledge across national boundaries Source of Verification Government statistics Economic Commission for Africa statistics and reports FAO statistics COMESA, EAC and other regional organization reports Selected CGIAR reports and publications External Evaluation & Impact Assessment RCOEs Reports COMESA and EAC Reports ASARECA Reports Review Reports Assumptions Relevant regional and national policies are implemented Governments continue to support agriculture and poverty reduction as priorities Equitable distribution of benefits occurs Agricultural transformation occurs in the ECA region occasioned by technical change
Rate of increase in adoption of new varieties, breeds and management practices (%) Rate of increase in adoption of new handling and processing methods. Rate of increase in number of improved dairy genetic materials (%) Increase in productivity at farm level over control technology for all disseminated new technologies (%). Rate of increase in land area with seeds of improved cultivars (%) Level of stakeholder satisfaction with the technologies and innovations (%) by number of products users (by gender, age, and location )
Presence of effective innovation platforms in the ECA region Availability of inputs Targeted financial services for agriculture exists Appropriate knowledge and technology delivery mechanisms operational Functional advisory systems in place Efficient marketing systems in place
Intermediate Outcomes Component 1: RCoEs RCoEs have improved infrastructure, human, and financial resources to conduct regional research in identified priority areas.
Acquisition of research infrastructure and equipment according to plan (%). Staffing of research effort on regional research projects according to plan (%). Number of staff trained (short- and long-term) and applying skills acquired in conducting EAAPP research for development
Evaluation Reports ASARECA Annual Reports RCOE Annual Reports RCOE Information and Communication priority setting document
Adequate human, physical and financial resources are maintained within NARS and other partners. Government, non-government, regional and national organizations operate effectively at appropriate levels.
Component 2.1: Regional Research Generation of agricultural knowledge and improved agricultural technologies in identified priority areas facilitated
Number of regional agricultural research projects implemented compared to plan. Number of new technologies developed by RCoEs relative to plan Number of demand-driven gender-responsive technologies made available to uptake pathways
Evaluation Reports ASARECA Annual Reports RCOE Annual Reports
Adequate human, physical and financial resources are maintained within NARS and other partners
Component 2.2: Training and Dissemination Availability of knowledge and improved Number of existing and new technologies disseminated inASARECA-EAAPP PMP: 2010-2015
Evaluation Reports
Partnerships and platforms with adequate9
Overall Goal agricultural technologies in identified priority areas in targeted countries as well as other ASARECA member countries improved.
Verifiable Indicators more than one EAAPP country compared to plan (number per selected commodity). Number of regional technology uptake pathways (e.g., web-based information platform, regional radio, TV program, etc.) compared to plan. Level of satisfaction of stakeholders with the technology uptake pathways Number of stakeholders whose capacity building needs have been addressed Component 3: Availability and Access to Seed Farmers access to seeds and planting Number of cultivars for selected commodities registered in materials and dairy genetic materials in more than one EAAPP country (number per selected identified priority areas in targeted commodity). countries as well as other ASARECA Tons of commercial seed of the selected commodities sold member countries improved. by seed companies, farmer organizations, etc. Tons of breeder seed and planting materials of the selected commodities produced by research institutions and private seed companies. Number of doses of livestock semen sold in targeted countries as well as other ASARECA member countries. Tons of breeder seed and planting materials of the selected commodities accessed by stakeholders. Number of relevant policies, laws, regulations, and/or procedures reviewed for harmonization Component 4: Management and Coordination Coordination and management of Regional research and training and dissemination activities regional research activities and implemented according to plan (%). dissemination initiatives in all EAAPP Harmonized M&E system for RCoEs in cooperation with countries enhanced ASARECA developed, adopted, and implemented. NB:
Source of Verification ASARECA Annual Reports RCoE Periodic Reports RCOE Annual Reports RCOE Information and Communication priority setting document Publications Mass media
Assumptions capacity for generation and uptake of technologies and innovations exist Adequate human, physical and financial resources are maintained within NARS and other partners. Government, non-government, regional and national organizations operate effectively at appropriate levels.
Evaluation Reports RCOE Annual Reports Periodic Reports from FAO and other agencies
Partnerships and platforms with adequate capacity for generation and uptake of technologies and innovations exist Adequate human, physical and financial resources are maintained within NARS and other partners. Government, non-government, regional and national organizations operate effectively at appropriate levels. Conducive policy environment maintained
The indicators marked in bold red are Customized to enable the RCoEs track further information to aid in data analysis and inference. They dont appear in the PAD, and thus will not be reported on to the World Bank.
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6. Performance Indicator Reference Sheets
Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 1: Rate of increase in adoption of new varieties, breeds and management practices Indicator Level: Output Outcome X Inputth
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Adoption refers to acceptance and practice of agricultural technology, i.e. implication and continued use. It is the point at which a technology (breeds, new varieties, and management practices) is chosen or selected for use by individuals or organizations. Therefore, rate of adoption will be measured as a percent of the baseline value, and is a function of government policies, technological change, environmental concerns, demographic factors, market forces, delivery mechanism, and availability of information and education, etc. The technologies for tracking include: new varieties of pasture and fodders, new or improved breeds, management practices, models, approaches and systems. This indicator seeks to assess the number of existing and new varieties, breeds, and other selected management practices favored by the stakeholders. In terms of dairy component, for example, the indicator tracks the number of stakeholders practicing modern dairy management practices (such as cut and carry, improved pasture and fodder management weeding, soil fertility improvement, breeding- use of AI, Embryo transfer, de worming, pest control, livestock registration and record keeping). Unit of measure: Percent Disaggregated by: Variety, Cultivars, Clones, Species, Breeds, Agronomic/Husbandry Practices, Gender and Country Justification/Management Utility: This indicator measures the rate at which EAAPP products are accepted and embraced by farmers, researchers, private sector, governments, etc. The fact that these products are taken up by the stakeholders and applied in decision making or production processed with a view of the changing status of resources and behavior is the very essence of EAAPP mandate. In this indicator, increased numbers reflect improvement in agricultural production and/or productivity. It measures adoption rates among key players, viz.: Farmers, researchers, private sector, governments, etc. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Adoption studies at farm level, Review of field reports Data source(s): Adoption Study reports, Private sector partners, Farmers and Farmer-based Organizations, Extension staff/agencies, NGOs, Local Leaders Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis {Principle Component Analysis + Multivariate Analysis} Data Presentation Methods: Tables, Charts, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011.
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BASELINE, TARGETS & ACTUALS: Year Target Value
Actual ValueKen Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total = Eth Tz Ug
Notes
Baseline Year 2010
Dairy
34.5%
Rice
Wheat
Cassava
Dairy
2010Rice
Wheat
New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices
Ken 4% 4% 4% Total = Ken
Eth -
Tz -
Ug -
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Eth
Tz
Ug
Dairy
Rice
Wheat
Eth
Tz
Cassava
Dairy
2011Rice
Wheat
New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices
4% 4% 4% 4%
4%
Ug 4% 4% 4% 4% 4% 4% 4% 4% 4% 4% 4% 4%
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Eth
Tz
Ug
Dairy
Rice
Wheat
Total =
2012ASARECA-EAAPP PMP: 2010-2015 12
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices
Eth
Tz
Dairy
8% 4% 4% 4%
8%
Rice
8%
Wheat
Ug 8% 8% 8% 8% 8% 8% 8% 8% 8% 8% 8% 8%
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Eth
Tz
Ug
Dairy
Rice
Wheat
Total = Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Eth Tz Ug 12% 12% 12% 12% 12% 12% 12% 12% 12% 12% 12% 12%
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Eth
Tz
Ug
Dairy
2013Rice
12% 4% 4% 4%
Dairy
12%
Rice
12%
Wheat
Wheat
Total = Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Eth Tz Ug 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16% 16%
Ken Cassava New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Eth
Tz
Ug
Dairy
2014Rice
16% 4% 4% 4%
Dairy
16%
Rice
16%
Wheat
Wheat
Total = Ken Eth Tz Ug 20% 20% 20%
Ken Cassava New Varieties Breeds Mgt. practices
Eth
Tz
Ug
2015Cassava
New Varieties Breeds Mgt. practices
ASARECA-EAAPP PMP: 2010-2015
13
Dairy
Rice
Wheat
New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices
20% 4% 4% 4%
20%
20%
20% 20% 20% 20% 20% 20% 20% 20% 20%
Dairy
Rice
Wheat
New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices New Varieties Breeds Mgt. practices Total =
Total =
End of Project Target:_________________ This Sheet last updated on: 11th August 2011
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Project Development Objective Enhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundariesIndicator 2: Rate of increase in adoption of new handling and processing methods Indicator Level: Input Output Outcometh
X
Impact
Date of PMP Development:30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Handling and Processing refer to enhanced extraction processes which offer either reduction in processing time, or add value to the quality of product extracted. Improved handling methods minimize waste and improve safe handling for a wide variety of research products. Handling and processing technologies will be considered new if they have not been used before by the stakeholders. Specific handling and processing technologies will be recorded for every stakeholder even when used in combination. Rate of adoption will be measured as a percent of the baseline value. Processing and handling technologies / innovations include: Processing and handling techniques of milk, feed, pasture seed, forage planting material, germplasm and vaccines. This indicator tracks the number of existing and new handling and processing technologies adopted by the stakeholders, as well as the number of stakeholders actually applying these technologies. With respect to dairy, for example, the number of individual farmers and farmers groups doing milk and feed value addition will be tracked. Unit of measure: Percent Disaggregated by: Gender, Country, Handling Methods, Processing Techniques, Management Practices Justification/Management Utility: In this indicator, increased numbers reflect improvement in agricultural production and/or productivity, as well as outreach of agricultural technology promoted by EAAPP. It measures adoption rates among key players, viz.: Farmers, researchers, private sector, governments, etc. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Adoption studies and Field reports Data source(s): Adoption Study reports, Private sector partners, Farmers and Farmer-based Organizations, Extension staff/agencies, NGOs, Local Leaders Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis {Principle Component Analysis + Multivariate Analysis} Data Presentation Methods: Tables, Charts, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesKen Eth Tz Ug
Baseline Year 2010
Cassava Dairy Rice Wheat Total = Ken Eth Tz Total = Eth Tz 4% 4% Total = Eth Tz Ug Ken Cassava Dairy Rice Wheat Total = Ug 4% 4% 4% 4% Ken Cassava Dairy Rice Wheat Total = Ug 8% Ken Cassava Eth Tz Ug Eth Tz Ug Eth Tz Ug
2010
Cassava Dairy Rice Wheat
2011
Cassava Dairy Rice Wheat
Ken 4% -
2012Cassava
Ken -
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15
Dairy Rice Wheat
-
8% Total = Eth Tz 12% 8% Total = Eth Tz 16% 16% Total = Eth Tz 20% 20% Total =
8% 8% 8%
Dairy Rice Wheat Total =
2013
Cassava Dairy Rice Wheat
Ken 8% -
Ug 12% 12% 12% 12%
Ken Cassava Dairy Rice Wheat
Eth
Tz
Ug
Total = Ug 16% 16% 16% 16% Ken Cassava Dairy Rice Wheat Total = Ug 20% 20% 20% 20% Ken Cassava Dairy Rice Wheat Total = Eth Tz Ug Eth Tz Ug
2014
Cassava Dairy Rice Wheat
Ken 16% -
2015
Cassava Dairy Rice Wheat
Ken 20% -
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
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Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 3: Rate of increase in land area with seeds of improved cultivars (%) Indicator Level: Input Output Outcome Xth
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: This indicator refers to the sum of arable land, permanent cropland, and permanent pasture planted with improved cultivars. Increase in area under the commodity by farmers is measured as a percent of the baseline. It also means the number of hectares where improved technologies and/or management practices are being employed, including inputs, management practices, tenure arrangements, and administrative systems. The indicator tracks successful adoption of technologies of technologies and management practices to improve agricultural productivity. Unit of measure: Percent (area is measured in hectares, but the indicator is measured as a rate) Disaggregated by: Ecosystem, Farming Methods, Country, Gender Justification/Management Utility: The rate depicts the speed at which farmers are accepting new seeds of improved cultivars and are willing to expand land being planted with the varieties. Increased land area under improved cultivars addresses the perennial shortages of the commodities (especially forage in the dairy sector). By dedicating land to improved cultivars is a sure indication that action has been taken to ensure availability of high quantity and quality of commodities (e.g. feed for dairy production). It also ensures availability and accessibility of planting suitable and adoptable, for various agro ecological zones and farming systems. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Reports from relevant agencies, field reports, GIS Data source(s): Farm records, field reports, pasture and forage suitability maps, pasture and forage survey reports Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis {Principle Component Analysis + Multivariate Analysis} Data Presentation Methods: Tables, Charts, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesKen Eth Tz Ug
Baseline Year 2010
Cassava Dairy Rice Wheat Total = Ken Eth Total = Tz Ug Ken Cassava Dairy Rice Wheat Total = Tz 4% 4% 4% 4% Ug 4% 4% 4% 4% Ken Cassava Dairy Rice Wheat Total = Tz 8% 8% 8% 8% Ug 8% 8% 8% 8% Ken Cassava Dairy Rice Wheat Eth Tz Ug Eth Tz Ug Eth Tz Ug
2011
Cassava Dairy Rice Wheat
2012
Cassava Dairy Rice Wheat
Ken Eth 4% 4% 4% 4% 4% 4% 4% 4% Total = 4% Ken 8% 8% 8% 8% Eth 8% 8% 8% 8%
2013
Cassava Dairy Rice Wheat
ASARECA-EAAPP PMP: 2010-2015
17
Total = 8% Ken Eth 12% 12% 12% 12% 12% 12% 12% 12% Total = 12% Ken Eth 14% 14% 14% 14% 14% 14% 14% 14% Total = 14% Tz 12% 12% 12% 12% Ug 12% 12% 12% 12%
Total = Ken Cassava Dairy Rice Wheat Total = Tz 14% 14% 14% 14% Ug 14% 14% 14% 14% Ken Cassava Dairy Rice Wheat Total = Eth Tz Ug Eth Tz Ug
2014
Cassava Dairy Rice Wheat
2015
Cassava Dairy Rice Wheat
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
18
Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 4: Rate of increase in number of improved dairy genetic materials (%) Indicator Level: Input Output Outcometh
X
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Increase in number means multiplication of improved dairy germplasm for use by dairy producers. Improved means value addition through genetic manipulation, proper performance recording and pedigree registration. Germplasm means dairy animals of known genetic makeup designed for a specified purpose and environment. This indicator tracks the number of improved dairy genetic materials utilized by the stakeholders, number of stakeholders rearing improved dairy genetic materials, as well as the number of improved genetic materials produced by breeders and relevant producers. The number of improved dairy germplasm registered will also be recorded in all the target countries. Unit of measure: Percent Disaggregated by: Semen, Embryo, Bucks, Bulls, Heifers, Doses Justification/Management Utility: Improved genetic material is developed to address the shortfalls in productivity in the dairy sector. Genetic manipulation will improve the level of performance of the dairy animals in terms of milk production and will increase the overall value of the animals. Multiplication of improved germplasm will enhance availability and accessibility of appropriate genetic material. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Reports from relevant agencies, field reports Data source(s): Animal performance records and studies, Progeny testing records, genetic material production records Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: Genetic Material Production and Recording Institution, RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis, Principle Component Analysis Data Presentation Methods: Tables, Charts, ANOVA tables, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes Baseline Year 2010Ken Semen Embryos Breeding stock Total = Ken Eth Total = Ken Eth 4% 4% 4% 4% 4% 4% Total = 4% Ken Eth 8% 8% 8% 8% 8% 8% Total = 8% Ken Eth Tz Ug Ken Semen Embryos Breeding stock Total = Tz 4% 4% 4% Ug 4% 4% 4% Ken Semen Embryos Breeding stock Total = Tz 8% 8% 8% Ug 8% 8% 8% Ken Semen Embryos Breeding stock Total = Tz Ug Ken Eth Tz Ug 19 Eth Tz Ug Eth Tz Ug Eth Tz Ug Eth Tz Ug
2010
Semen Embryos Breeding stock
2011
Semen Embryos Breeding stock
2012
Semen Embryos Breeding stock
2013
ASARECA-EAAPP PMP: 2010-2015
Semen Embryos Breeding stock
12% 12% 12% 12% 12% 12% Total = 12% Ken Eth 16% 16% 16% 16% 16% 16% Total = 16% Ken Eth 20% 20% 20% 20% 20% 20% Total = 20%
12% 12% 12%
12% 12% 12%
Semen Embryos Breeding stock Total =
2014
Semen Embryos Breeding stock
Tz 16% 16% 16%
Ug 16% 16% 16%
Ken Semen Embryos Breeding stock Total =
Eth
Tz
Ug
2014
Semen Embryos Breeding stock
Tz 20% 20% 20%
Ug 20% 20% 20%
Ken Semen Embryos Breeding stock Total =
Eth
Tz
Ug
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
20
Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 5: Increase in productivity at farm level over control technology for all disseminated new technologies (%). Indicator Level: Input Output Outcome X Impact Date of PMP Development: 30th June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Productivity refers to a ratio of the output to input in relation to land, labor, capital and overall resources employed in agriculture. Similarly, agricultural productivity refers to the difference between resources put into agriculture (land, materials, labor, time, money) and the resources extracted from it (food, money). For example, crop productivity is a function of factors like physiography, soil type, rainfall, irrigation, etc. Productivity data include yields and acreage. Increase in productivity means enhancement of the total farm output and efficiency in resource utilization. The distribution of productivity for every crop will be computed, mapped and interpreted using the following formula:Productivity Index Where: Y = Production of selected crop in a unit area; Yn = Total production of selected crop in entire region T = Area under selected crop in a unit area; Tn = Area under selected crop in entire region Y Yn T Tn 100
Unit of measure: Percent Disaggregated by: Commodity, Country Justification/Management Utility: Since this indicator tracks production per hectare, an increase in productivity will be used to measure the level of food security within the target areas, as well as the contributions of the new technologies. In enhancing income generation PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Surveys; Supervision Mission Data source(s): Farm records, Enterprise records, market reports, market survey reports, Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis, Principle Component Analysis Data Presentation Methods: Tables, Charts, ANOVA tables, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes Baseline Year 2010Rate Ken Eth Tz Total = Ug Rate Ken Eth Tz Ug
Total = Rate Ken Eth Total = Ken Eth Tz Ug -
2010
2011
Rate
Ken Eth Tz 105 105 105 Total = 105 Ken Eth Tz 108 108 108 Total = 108 Ken Eth Tz 110 110 110 Total = 110
Ug 105
Rate
Tz
Ug
Total = Ug 108 Rate Ken Eth Tz Ug
2012
Rate
Total = Ug 110 Rate Ken Eth Tz Ug
2013
Rate
Total = 21
ASARECA-EAAPP PMP: 2010-2015
2014
Rate
Ken Eth Tz 115 115 115 Total = 115 Ken Eth Tz 115 115 115 Total = 115
Ug 115
Rate
Ken
Eth
Tz
Ug
Total = Ug 115 Rate Ken Eth Tz Ug
2015
Rate
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
22
Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 6: Level of stakeholder satisfaction with the technologies and innovations Indicator Level: Input Output Outcome X Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTIONPrecise Definition: Satisfaction refers to contentment or pleasure or fulfillment of a need or desire of stakeholders/end-users. This refers to the end-users being impressed by all or most attributes of a technology, innovation or management practice. The measurement of satisfaction is based on the following criteria for stakeholders: the effectiveness of communications; responding to feedbacks; keeping stakeholders up to date on new initiatives, innovations and technologies. Unit of measure: Percent Disaggregated by: Gender, age and location Justification/Management Utility: Measures the level of satisfaction by end-users of ASARECA technologies and innovations or the extent to which technologies and innovations are accepted and embraced by end-users. This is directly related to adoption which is one of ASARECA mandate.th
Impact
PLAN FOR DATA COLLECTION/ACQUISITIONData Collection Method: Survey personally administered by researchers; personal interview with stakeholders; Supervision Mission. Level of satisfaction will be measured using recognizable scales (e.g. the Likert Scale)
Data source(s): Farm records, Enterprise records, market reports, market survey reports, Frequency and timing of data acquisition: Annual; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTINGData Analysis Methods: Descriptive statistics, Qualitative-Quantitative Data Analysis, Principle Component Analysis Data Presentation Methods: Tables, Charts, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports
Notes on Baselines/Targets:Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011.
BASELINE, TARGETS & ACTUALS: Year Target Value Baseline Year 2010Rate Ken Eth Tz 30% 30% 30% Total = 30% Ken Eth Tz 40% 40% 40% Total = 40% Ken Eth Tz 50% 50% 50% Total = 50% Ken Eth Tz 60% 60% 60% Total = 60% Ken Eth Tz 80% 80% 80% Total = 80% Ken Eth Tz 100% 100% 100% Total = 100% Ug 30%
Actual ValueRate Ken Eth Tz Ug
Notes
Total = Rate Ken Eth Tz Ug
2010
Total = Ug 40% Rate Ken Eth Tz Ug
2011
Rate
Total = Ug 50% Rate Ken Eth Tz Ug
2012
Rate
Total = Ug 60% Rate Ken Eth Tz Ug
2013
Rate
Total = Ug 80% Rate Ken Eth Tz Ug
2014
Rate
Total = Ug 100% Rate Ken Eth Tz Ug
2015
Rate
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011ASARECA-EAAPP PMP: 2010-2015 23
Component 1: Performance Indicator reference Sheet No. 1RCoE has improved infrastructure, human, and financial resources to conduct regional research in identified priority areas Indicator 1.1: Acquisition of research infrastructure and equipment according to plan % Indicator Level: Input Output X Outcometh
Impact
Date of PMP Development:30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Research infrastructure and equipment refer to buildings and other structures required for scientific work (e.g. laboratory, resource centre, resident blocks, hardware, software, vehicles, farm machinery, irrigation facilities, offices, Information and communication technology, laboratory equipment, water systems, greenhouses). Acquisition means procurement and installation of laboratories, structures, equipment and other facilities essential for the research. Unit of measure: Percent; Number Disaggregated by: Type, Number and specifications of infrastructure and equipment. Justification/Management Utility: Acquisition and installation of required research infrastructure and equipment will boost the overall research output in the generation of appropriate dairy technologies. Installation of new laboratory equipment will enhance capacity and quality of research data. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Field surveys; Observations; Review of institutional inventory reports, civil works reports, and procurement reports Data source(s): Partner reports, RCoE reports, Research Institutes/Centres, infrastructure and equipment specifications documents, procurement documents, civil works records & Institutions Inventory Frequency and timing of data acquisition: Quarterly, Bi-annually, Annually, and End of Project Responsibility for Data Collection: RCoE Coordinators; EAAPP Countrys Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP Countrys Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics (Qualitative) Data Presentation Methods: Summary tables, Matrices, Images, Charts and Graphs in technical reports Data Review Methods: Periodic internal reviews at the RCoE Data Reporting Methods: Quarterly, Bi-Annual and Annual Progress Reports and M&E Annual reports based on AWP&B Notes on Baselines/Targets: Baselines: A tool has been developed to assess the current status of the infrastructure and equipment at the various RCoEs. The baseline study focuses on establishing the current condition and number of the various identified infrastructure, such as: farm structures; staff houses; condition of the offices; farm machinery; vehicles; office furniture and equipment; laboratory equipment, etc. The final baseline study report is anticipated in October 2011. Targets: Interim targets have been set against each of the indicators in the PAD. Based on the baseline study reports, targets will be validated, and where possible, reviewed annually, if not at the MTR. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes The baseline study is ongoing, Ken Eth Tz Ug and is due for completion in Civil works 20 October 2011 Baseline Machinery Year Lab equip 10%Office equip 90%[2010]Vehicles Total = Ken 28% 0.3% 0.7% 2% 0.8% Eth Tz 90% 90% 90% 90% 90% Ug Ken Eth Tz 20% 10% 90% 90% Ug 90%
2010
Civil works Machinery Lab equip Office equip Vehicles
Civil works Machinery Lab equip Office equip Vehicles
Total = Ken 11.2% 0.4% 13.3% 2.1% 0.8% Eth 20% 31% 2% 46% Tz 90% 90% 90% 90% 90% Ug 30% 50% 70% 50% 70%
Total = 0 Ken Civil works Machinery Lab equip Office equip Vehicles Total = Tz Ug Ken Eth Tz Ug Eth Tz 20% Ug
2011
Civil works Machinery Lab equip Office equip Vehicles
The processes for the required infrastructural developments and equipment acquisition have commenced in all the countries.
Total =
2012
Ken
Eth
For Kenya, it is expected that civil works and other 2011 planned 24
ASARECA-EAAPP PMP: 2010-2015
Civil works Machinery Lab equip Office equip Vehicles
6% 11.5% 0.4% -
80%
-
80% 50% 90% 100% 100%
60% 60% 85% 85% 100%
Civil works Machinery Lab equip Office equip Vehicles Total =
procurement will be implemented in 2012
Total = Ken 4.6% 5.9% 0.3% Eth 20% Tz 90% 100% 100% 100% 100% Ug 90% 90% 90% 100% 100%
Ken Civil works Machinery Lab equip Office equip Vehicles
Eth
Tz
Ug
2013
Civil works Machinery Lab equip Office equip Vehicles
In Kenya, though most of the procurement is done between 2010-2012, those planned for 2013will still be done as planned
-
Total = Ken 4.8% 5.7% 0.3% Eth Tz 100% 100% 100% 100% 100% Ug 100% 100% 100% 100% 100%
Total = Ken Civil works Machinery Lab equip Office equip Vehicles Total = Tz 100% 100% 100% 100% 100% Ug 100% 100% 100% 100% 100% Ken Civil works Machinery Lab equip Office equip Vehicles Total = Eth Tz Ug Eth Tz Ug
2014
Civil works Machinery Lab equip Office equip Vehicles
-
Total = Ken 100% 100% 100% 100% 100% Eth 100% 100% 100% 100% 100%
2015
Civil works Machinery Lab equip Office equip Vehicles
Total =
End of Project Target:_____100%______________This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
25
Component 1: Performance Indicator reference Sheet No. 2RCoEs have improved infrastructure, human, and financial resources to conduct regional research in identified priority areas Indicator 1.2: Staffing of research effort on regional research projects according to plan (%). Indicator Level: Input Output X Outcometh
Impact
Date of PMP Development:30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Staffing of research effort means identifying, developing and deploying a critical mass of scientists required to drive the research and development process. It also looks at the improvement in human research capacity engaged in regional research, and considers the total number of scientists retained and trained over the total number planned to support the research work. This indicator will track the following: (i) Number of staff and stakeholders equipped with the relevant skills and methods; (ii) Number of staff participating in research in implementation sites; and (iii) Number of staff deployed to bridge skills gaps in Research Centers. Unit of measure: Percent; Number Disaggregated by: Gender; Level of education; Disciplines; Type of training (Short- and long-term) Justification/Management Utility: Developing a critical mass of scientist and stakeholders through training and deployment will assist in bridging the current skills gaps and subsequently enable delivery of research and development outputs and outcomes. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Training Needs Assessment; Surveys; Supervision Mission; Review of Project Documents Data source(s): Skills inventory; Human Resource Records; TNA Reports; Training Plans; M&E Reports; Training Reports; Government Records Frequency and timing of data acquisition: Quarterly, Bi-annually, Annually, and End of Project Responsibility for Data Collection: RCoE Coordinators; EAAPP Countrys Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP Countrys Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics; Qualitative Data Analysis Data Presentation Methods: Summary Tables; Charts; Bar graphs Data Review Methods: Periodic internal reviews at the RCoE Data Reporting Methods: Quarterly, Bi-Annual and Annual Progress Reports and M&E Annual reports based on AWP&B Notes on Baselines/Targets: Baselines: A tool has been developed to assess the current status of staff at the various RCoEs. The final baseline study report is anticipated in October 2011. Targets: Interim targets have been set against each of the indicators in the PAD. Based on the baseline study reports, targets will be validated, and where possible, reviewed annually, if not at the MTR. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesBaseline Year [2010]MSc PhD Others TOTAL Total = 48 Ken Eth Tz 18 5 6 29 Ug 4 5 10 19For Tanzania, 17 researchers acquired skill in writing a winning research proposal, while 5 researchers pursue long-term training. For Kenya, others refer to Bachelor of Science
2010MSc PhD Others TOTAL Ken Eth 15 6 21 Total = 75 Ken Eth 18 4 8 3 26 7 Total = 103 Ken Eth 23 3 12 2 1 36 5 Total = 124 Ken 23 12 Eth 6 4 Tz 18 7 10 35 Ug 4 5 10 19 Ken MSc PhD Others TOTAL Total = 60 Tz 18 7 10 35 Ug 13 5 17 35 Ken MSc PhD Others TOTAL Total = Tz 21 7 20 48 Ug 13 5 17 35 Ken MSc PhD Others TOTAL Total = Tz 21 7 Ug 19 7 Ken MSc PhD Eth Tz Ug Eth Tz Ug Eth Tz Ug Eth Tz 18 7 16 41 Ug 4 5 10 19
2011MSc PhD Others TOTAL
2012MSc PhD Others TOTAL
2013MSc PhD
ASARECA-EAAPP PMP: 2010-2015
26
Others TOTAL
1 6 36 16 Total = 146 Ken Eth 23 10 12 6 1 8 36 24 Total = 161 Ken Eth 23 10 12 6 8 35 24 Total = 127
20 48
20 46
Others TOTAL Total =
2014MSc PhD Others TOTAL Tz 28 8 19 55 Ug 19 7 20 46 Ken MSc PhD Others TOTAL Total = Tz 10 7 17 Ug 19 12 20 51 Ken MSc PhD Others TOTAL Total = Eth Tz Ug Eth Tz Ug
2015MSc PhD Others TOTAL
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
27
Component 2 Performance Indicator Reference Sheet No. 3Component 2.1: Regional Research Generation of agricultural knowledge and improved agricultural technologies in identified priority areas facilitated Indicator 2.1.1: Number of regional agricultural research projects implemented compared to plan Indicator Level: Input Output X Outcome Impact Date of PMP Development:30th June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: This indicator refers to the number of EAAPP supported regional projects that are being implemented in more than one country. These projects are based on all the four commodities, and where possible, embrace the Agricultural Innovation Systems. Within this system, the activities of the researchers relate closely with the economic activities of the stakeholders and target groups (farmers). Unit of measure: Number Disaggregated by: Country; Research Themes; Disciplines Justification/Management Utility: Regional research projects strengthen regional collaboration, networks, exchange of experiences, knowledge, skills and materials which subsequently address regional constraints in the specific commodity sector. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Field surveys; Observations; Review of partner country reports; Interviews with key stakeholders Data source(s): Partner reports; RCoE reports; RCoE Project Checklists and M&E Tools Frequency and timing of data acquisition: Quarterly, Bi-annually, Annually, and End of Project Responsibility for Data Collection: RCoE Coordinators; EAAPP Countrys Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP Countrys Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive Statistics Data Presentation Methods: Summary Tables, Charts and Graphs Data Review Methods: Periodic internal reviews at the RCoE Data Reporting Methods: Quarterly, Bi-Annual and Annual Progress Reports and M&E Annual reports based on AWP&B Notes on Baselines/Targets: Baselines: A tool has been developed to assess the current status of pipeline projects that fit within the regional umbrella. The final baseline study report is anticipated in October 2011. Targets: Interim targets have been set against each of the indicators in the PAD. Based on the baseline study reports, targets will be validated, and where possible, reviewed annually, if not at the MTR. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesNo. of projects 5 -
Baseline Year 2010
Cassava Dairy Rice Wheat TOTAL
Total = No. of projects 7 5 10 6 28 Total = 28 No. of projects 9 5 15 6 35 Total = 35 No. of projects 9 5 14 7 35 No. of projects 5 4 6 15 Total = 15 No. of projects Cassava Dairy Rice Wheat TOTAL Total = No. of projects Cassava Dairy Rice Wheat TOTAL
2011
Cassava Dairy Rice Wheat TOTAL
Cassava Dairy Rice Wheat TOTAL
2012
Cassava Dairy Rice Wheat TOTAL
2013
Cassava Dairy Rice Wheat TOTAL
ASARECA-EAAPP PMP: 2010-2015
28
Total = 35 No. of projects 9 5 14 7 36 Total = 36 No. of projects 9 5 10 7 36 Total = 36
Total = No. of projects Cassava Dairy Rice Wheat TOTAL Total = No. of projects Cassava Dairy Rice Wheat TOTAL Total =
2014
Cassava Dairy Rice Wheat TOTAL
2015
Cassava Dairy Rice Wheat TOTAL
End of Project Target:__________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
29
Component 2.1: Regional Research Performance Indicator reference Sheet No. 4Generation of agricultural knowledge and improved agricultural technologies in identified priority areas facilitated Indicator 2.1.2: Number of new technologies developed by RCoEs compared to plan Indicator Level: Input Output X Outcometh
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Technology is defined as one or a combination of tools; equipment; genetic resources (genetic materials or breeds/varieties); production practices; methodologies/protocols; post-harvest/value addition products & practices; natural resources and biodiversity management practices; crop and animal management/husbandry practices; gathering practices; laboratory techniques and models; marketing practices; and the knowledge and skills needed to use them. They are counted once when used to produce combinations of traits or twice when used in separate experiments to produce two distinct, separate and irreconcilable traits (e.g. early versus late maturity). A new technology is defined as new varieties, breeds, management, and integrated natural resource management practices at farm level as well as improved processing and handling methods by processors and other market intermediaries. These technologies may include those that had been developed earlier, but never adopted by the intended (end) users. Unit of measure: Number (or Percentage) Disaggregated by: Type of technologies (Varieties; Cultivars, Clones Breeds; Management Practices; processing and handling); Country Justification/Management Utility: RCoE is mandated to generate technologies and innovations in order to enhance dairy productivity in the EAAPP countries. The indicator enables the documentation of all technologies that have been generated. This is also useful for informing future technology/innovation activities in agricultural research for development. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Field surveys; Supervision Mission; Observations; Review of partner country reports; Interviews with key stakeholders Data source(s): Partner reports; RCoE reports; RCoE Project Checklists and M&E Tools; Inventory of technology reports Frequency and timing of data acquisition: Quarterly, Bi-annually, Annually, and End of Project Responsibility for Data Collection: RCoE Coordinators; EAAPP Countrys Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP Countrys Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics Data Presentation Methods: Summary tables, Charts and Graphs Data Review Methods: Annually Data Reporting: M&E reports Notes on Baselines/Targets: Baselines: A tool has been developed to assess the current status of technologies developed by the RCoEs. Targets: Interim targets have been set against each of the indicators in the PAD. Based on the baseline study reports, targets will be validated, and where possible, reviewed annually, if not at the MTR. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesTechnology Cassava Dairy Rice Wheat TOTAL Ken Eth Tz Ug
Baseline Year [2010]
Total = Technology Cassava Dairy Rice Wheat TOTAL Ken Eth 8 34 4 10 1 56 Total = 60 Ken Eth 10 54 2 3 1 69 1 Total = 74 Ken Eth Tz 1 1 1 1 4 Ug Technology Cassava Dairy Rice Wheat TOTAL Ken Eth Tz Ug
2010
Total = Tz 1 1 1 1 4 Ug Technology Cassava Dairy Rice Wheat TOTAL Ken 3 11 3 1 Eth Tz Ug
2011
Technology Cassava Dairy Rice Wheat TOTAL
Total = 18 Tz Ug Technology Ken Eth Tz Ug 30
2012Technology ASARECA-EAAPP PMP: 2010-2015
Cassava Dairy Rice Wheat TOTAL
10 1 50 1 2 1 3 1 65 4 Total = 80 Ken Eth 8 1 37 1 2 1 2 1 49 4 Total = 65 Ken Eth 6 1 21 1 1 1 2 2 30 5 Total = 52 Ken Eth 1 33 1 1 2 33 5 Total = 61
2 1 1 1 5
2 1 2 1 6
Cassava Dairy Rice Wheat TOTAL Total =
2013
Technology Cassava Dairy Rice Wheat TOTAL
Tz 1 1 3 1 6
Ug 3 1 1 1 6
Technology Cassava Dairy Rice Wheat TOTAL
Ken
Eth
Tz
Ug
Total = Tz 2 2 3 2 9 Ug 5 1 1 1 8 Technology Cassava Dairy Rice Wheat TOTAL Ken Eth Tz Ug
2014
Technology Cassava Dairy Rice Wheat TOTAL
Total = Tz 1 5 5 2 13 Ug 4 2 2 2 10 Technology Cassava Dairy Rice Wheat TOTAL Ken Eth Tz Ug
2015
Technology Cassava Dairy Rice Wheat TOTAL
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
31
Component 2.2: Regional Training and Technology Dissemination Performance indicator Reference Sheet No. 5 Availability of knowledge of improved agricultural technologies in identified priority areas in targeted countries as well as other ASARECA member countries improvedIndicator 2.2.1: Number of existing and new technologies disseminated in more than one EAAPP country compared to plan (number per selected commodity) Indicator Level: Output X Outcome Impact Input Date of PMP Development: 30th June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: New technology refers to those that have not previously been in use in the target area. This indicator looks at two types of indicators: Number of existing technologies that have not been availed to the targeted stakeholders Number of new technologies generated, tested, and approved that have been disseminated to users Based on this indicator, dissemination refers to the process of transferring technology and information from the point of generation to the point of use. Unit of measure: Number Disaggregated by: Type of technology; Country; variety; Justification/Management Utility: It is anticipated that by availing existing and new technologies, demand for them will be realized thus leading to knowledge used, skills improvement and change in attitude. The end result of this process is change of behavior and improved practices leading to increase production and incomes. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Review of dissemination report; Adoption surveys (qualitative methods); Interviews with implementing partners; Supervision Mission Data source(s): Adoption survey reports; Farmers; field reports; farm records; M&E reports; National Reports Frequency and timing of data acquisition: Bi-annual, Annual MTR and end of project Responsibility for Data Collection: RCoE Coordinators; EAAPP National Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP National Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics (Qualitative analysis) Data Presentation Methods: Reports; Summary tables; Charts; Graphs; Matrices Data Review Methods: Bi-Annual and Annual Planning Meetings; Joint Review Missions Data Reporting Methods: Quarterly; bi-Annual; and Annual Reports; EAAPP Country reports; M&E Annual Synthesis Reports Notes on Baselines/Targets: Baselines: Targets: Other: BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value NotesTechnology Existing New TOTAL Ken Eth Tz Ug
Baseline year 2010
5 Total =
2010
Technology Existing New TOTAL
Ken Eth 3 2 5 1 Total = 6 Ken Eth 5 3 1 2 6 5 Total = 13 Ken Eth 4 2 2 1 6 3 Total = 14
Tz -
Ug -
Technology Existing New TOTAL
Ken
Eth
Tz -
Ug
Total = Tz 2 2 Ug Technology Existing New TOTAL Eth 2 2 4 Total = 9 Ken Eth Ken Tz Ug
2011
Technology Existing New TOTAL
5
2012
Technology Existing New TOTAL
Tz 2 2
Ug 2 1 3
Technology Existing New TOTAL
Tz
Ug
Total =
2013ASARECA-EAAPP PMP: 2010-2015 32
Technology Existing New TOTAL
Ken Eth 5 1 2 2 7 3 Total = 16 Ken Eth 5 3 3 8 3 Total = 19 Ken Eth 7 3 3 10 3 Total = 26
Tz 2 1 3
Ug 2 1 3
Technology Existing New TOTAL
Ken
Eth
Tz
Ug
Total = Tz 1 2 3 Ug 3 2 5 Technology Existing New TOTAL Ken Eth Tz Ug
2014
Technology Existing New TOTAL
Total = Tz 3 3 Ug 3 7 10 Technology Existing New TOTAL Ken Eth Tz Ug
2015
Technology Existing New TOTAL
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
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Component 2.2: Regional Training and Technology Dissemination Performance Indicator Reference Sheet No. 6Availability of knowledge of improved agricultural technologies in identified priority areas in targeted countries as well as other ASARECA member countries improved Indicator 2.2.2: Number of regional technology uptake pathways compared to plan (e.g. web-based information platforms, regional radio, TV program, etc) Indicator Level: Input Output X Outcome Impact Date of PMP Development: 30th June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: A delivery pathway in this context refers to the conduit or passageway for technology (and information) to the target group. The indicator aims at capturing the total number of effective pathways that have been identified and used to transfer the demand-driven technologies to targeted groups. Among the key technology uptake pathways include: Scientific Journals, newspapers, newsletters, magazines, meetings, workshops, conferences, forums briefings, books, TV and Radio programs, talk shows, phone-ins, education and training, demonstration, intermediary organizations (Extension agencies, District Agricultural Officers, NGOs, radio stations), Intermediary Personalities (e.g. MPs, elders), Communities of Practice (CoPs), Internet (websites, e-mail, YouTube), direct mail or physical postage, mobile phones (e.g. text, mobile Apps), etc. Unit of measure: Number Disaggregated by: Type of media; Country (source & destination); type of technology; number; gender; literacy level of targeted end users Justification/Management Utility: Targeted technology and information end users in the region have various characteristics and levels of access to information sources, thus the need to explore various uptake pathways. Similarly, periodic follow up on the regional uptake pathways will provide critical information on the effectiveness of information and technology sharing channels that would have been implemented. The uptake pathways can be refined for improved effectiveness. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Review of dissemination report; Adoption surveys (qualitative methods); Interviews with implementing partners; Supervision Mission Data source(s): Adoption survey reports; Farmers; field reports; farm records; M&E reports; National Reports Frequency and timing of data acquisition: Bi-annual, Annual MTR and end of project Responsibility for Data Collection: RCoE Coordinators; EAAPP National Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP National Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics (Qualitative analysis) Data Presentation Methods: Reports; Summary tables; Charts; Graphs; Matrices Data Review Methods: Bi-Annual and Annual Planning Meetings; Joint Review Missions Data Reporting Methods: Quarterly; bi-Annual; and Annual Reports; EAAPP Country reports; M&E Annual Synthesis Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing to establish the current status of regional technology uptake pathways. This will also be used in enhancing the setting of interim targets for effective project tracking. Targets: Interim targets have been set against each of the indicators within the PAD. These targets will need reviewing especially during the MTR. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes Baseline Year 2010Pathways Ken Eth Tz Ug
Total =
2010
Pathways
Ken Eth 1 Total = 1 Ken Eth 2 2 Total = 6 Ken Eth 4 3 Total = 9 Ken Eth 4 4 Total = 14 Ken Eth
Tz -
Ug -
Pathways
Ken
Eth
Tz
Ug
Total = Tz 1 Ug 1 Pathways Ken Eth Tz 1 Ug
2011
Pathways
Total = Tz 1 Ug 1 Pathways Ken Eth Tz Ug
2012
Pathways
Total = Tz 3 Ug 3 Pathways Ken Eth Tz Ug
2013
Pathways
Total = Tz Ug Pathways Ken Eth Tz Ug 34
2014
Pathways
ASARECA-EAAPP PMP: 2010-2015
4 4 Total = 12
2
2 Total =
2015
Pathways
Ken Eth 4 4 Total = 14
Tz 3
Ug 3
Pathways
Ken
Eth
Tz
Ug
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
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Component 2.2: Regional Training and Technology Dissemination Performance Indicator Reference Sheet No. 7Indicator 2.2.3: Level of satisfaction of stakeholders with the technology uptake pathways Indicator Level: Input Output X Outcometh
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: Stakeholder satisfaction is a measure of how products and services supplied by an institution meets or surpasses client expectations. Level of stakeholder satisfaction is defined as percentage of total clients whose reported usage of a product or service satisfies or exceeds specified goals/expectations. It can also be expressed as a scale (1 as low, 5 as very high satisfaction) Unit of measure: Percent Disaggregated by: Type, Location, Gender and other socioeconomic categories Justification/Management Utility: Stakeholder satisfaction is a measure of effectiveness of a particular technology uptake pathway and provides feedback for refining the dissemination channel. It is stressed on in this indicator as it guides the researchers in measuring their level of contribution to the wants of the target groups. PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Perception studies; User image and attitude studies; Surveys; Supervision Mission; M&E visits Data source(s): Survey reports, Secondary data, M&E reports, bi- and annual project reports Frequency and timing of data acquisition: Bi-annual and annual Responsibility for Data Collection: RCoE Coordinators; EAAPP National Focal Persons; M&E Officers Location of data storage: PCU; RCoE; EAAPP National Focal Persons; M&E unit; ASARECA PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Quantitative and Qualitative Data Analysis Data Presentation Methods: Summary Tables, Charts & Bar graphs Data Review Methods: Data will be reviewed on annual basis. This will be done through review of data collection instruments and quality of data identifying existing gaps. Data Reporting Methods: Annual and bi-Annual performance reports Notes on Baselines/Targets: Baselines: Targets: BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes Baseline Year 2010Pathways Ken Eth Tz Ug
Total =
2010
Pathways
Ken Eth 60% 40% Total = Ken Eth 70% 40% Total = Ken Eth 80% 60% Total = Ken Eth 80% 80% Total = Ken Eth 80% 80% Total = Ken Eth 80% 85% Total =
Tz 60%
Ug 50%
Pathways
Ken
Eth
Tz
Ug
Total = Tz 60% Ug 50% Pathways Ken Eth Tz Ug
2011
Pathways
Total = Tz 60% Ug 60% Pathways Ken Eth Tz Ug
2012
Pathways
Total = Tz 60% Ug 65% Pathways Ken Eth Tz Ug
2013
Pathways
Total = Tz 60% Ug 70% Pathways Ken Eth Tz Ug
2014
Pathways
Total = Tz 60% Ug 75% Pathways Ken Eth Tz Ug
2015
Pathways
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
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Project Development ObjectiveEnhance regional specialization in agricultural research Enhance collaboration in agriculture training and technology dissemination Facilitate increased transfer of agricultural technology, information, and knowledge across national boundaries Indicator 2.2.4: Number of stakeholders whose capacity building needs have been addressed Indicator Level: Input Output X Outcometh
Impact
Date of PMP Development: 30 June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: This indicator refers to the number of individuals to whom significant knowledge or skills have been imparted through formal or informal means. Short-term training refers to trainings totaling no fewer than 8 hours and no more than 3 months in duration, and long term training refers to training lasting more than 3 months. Knowledge or skills gained through technical assistance activities and visits to demonstration or experimentation sites are also included. If the activity provided training to trainers, and if the reporting unit can make a credible estimate of follow-on training provided by those trainers, this estimate will be included. Individuals attending more than one training course will be counted as many times as they attend different courses. Training may take place at individual day sessions, multi-day workshops or through a series of inter-related trainings or workshops. Unit of measure: Number Disaggregated by: Gender of stakeholders and Capacity building needs addressed Justification/Management Utility: This indicator measures enhanced human capacity for policy formulation and implementation which is key to transformational development PLAN FOR DATA COLLECTION/ACQUISITION Data Collection Method: Review of Capacity building records; Partner training reports; Interviews with stakeholders Data source(s): Partner reports, Stakeholders Frequency and timing of data acquisition: Quarterly, bi-Annually, Annually; MTR; End of project Responsibility for Data Collection: RCoE Focal Persons, RCoE Coordinators, PCU, M&E officers Location of data storage: Offices of: RCoE Coordinators; M&E Officers; PCU; EAAPP Country Focal Persons PLAN FOR DATA ANALYSIS, REVIEW & REPORTING Data Analysis Methods: Descriptive statistics, Qualitative Data Analysis, Principle Component Analysis Data Presentation Methods: Tables, Charts, Narratives, Graphs Data Review Methods: Annual Planning and Review meetings Data Reporting Methods: Cumulative (Annual Performance Reports), Mid-term Review Reports, End-of-project Evaluation Reports Notes on Baselines/Targets: Baselines: Baseline studies are ongoing. Tools for the study were jointly developed by ASARECA and the respective RCoEs. Appropriate Baseline Study methodologies were selected (ranging from purposive to multi-stage and random sampling), and respondents identified in conformity with statistical standards. Targets: Efforts have been made to review the targets set at the development of the project in order to adopt them, or set new ones that fit with the actual environment. This process is expected to be completed in August 2011. BASELINE, TARGETS & ACTUALS: Year Target Value Actual Value Notes Baseline Year 2010Ken Male Female TOTAL Total = Ken Eth Tz Ug Male Female TOTAL Total = Ken Eth Tz Ug Male Female TOTAL Total = Ken Eth Tz Ug Male Female TOTAL Total = Total = 37 Total = Ken Eth Tz Ug Total = Ken Eth Tz Ug Ken Eth Tz Ug Eth Tz Ug
2010
Male Female TOTAL
2011
Male Female TOTAL
2012
Male Female TOTAL
2013ASARECA-EAAPP PMP: 2010-2015
Ken Male Female TOTAL
Eth
Tz
Ug Male Female TOTAL
Ken
Eth
Tz
Ug
Total = Ken Eth Tz Ug Male Female TOTAL Total = Ken Eth Tz Ug Male Female TOTAL Total =
Total = Ken Eth Tz Ug
2014
Male Female TOTAL
Total = Ken Eth Tz Ug
2015
Male Female TOTAL
Total =
End of Project Target:___________________ This Sheet last updated on: 11th August 2011
ASARECA-EAAPP PMP: 2010-2015
38
Component 3: Availability and Access to Seed Performance Indicator Reference Sheet No. 8Farmers access to seeds and planting materials and dairy genetic materials in identified priority areas in targeted countries as well as other ASARECA member countries improved Indicator 3.1: Number of cultivars for selected commodities registered in more than one EAAPP country {number per selected commodity} Indicator Level: Input Output X Outcome Impact Date of PMP Development: 30th June 2011 Date of Last PMP Review: 11th August 2011 DESCRIPTION Precise Definition: A cultivar refers to a particular variety of a plant species or hybrid that is being cultivated and/or is recognized as a cultivar under the ICNCP. It also refers to products of research (with potential for further improvements through research) with requisite traits such as distinctiveness, uniformity, stability, high-yielding, and resistance to pests, diseases, and drought, and that have the potential of regional adaptability to different environments and growing conditions. These cultivars include: cassava, pasture, fodder species, varieties and clones, etc. Registered cultivars r