. .

 

Performance Indicator Reference Sheet - 1

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

 

 

 

Year

Targets

Actuals

 

 

Male

Female

Male

Female

 

FY14

21,000

14,000

15, 230

21, 792

 

FY15

30,000

20,000

29, 757

23, 751

 

FY 16

42,900

35,100

48 517

41 048

 

FY17

44,000

36,000

53, 347

50, 337

 

FY18

41,250

33,750

 

 

 

LOP

62,150

50,850

66 085

59 977

 

THIS SHEET LAST UPDATED ON: April , 2018

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Performance Indicator Reference Sheet - 2

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 US Dollar  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

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: /Male: $823.7 /Female: $581.11

 

Rice: / Male: $454 / Female: $437

Rice: / Male: $488.43 / Female: $450.16

Soya: / Male: $411 / Female: $277

Soya: / Male: $595.65 / Female: $565.39

FY 16

Maize: / Male: $680 / Female: $780

Maize: / Male: $1209.38 / Female: $844.36

 

Rice: / Male: $1200 / Female: $1050

Rice: / Male: $914.04 / Female: $804.75

Soya:/ Male: $600/ Female: $500

Soya: :/ Male: $474.03/ Female: $383.15

FY17

Maize: /Male: $720 / Female: $810

Maize: /Male: $794.05 / Female: $711.00

 

Rice: /Male: $1300 / Female: $1150

Rice: /Male: $692.35 / Female: $588.16

Soya: /Male: $650/ Female: $550

Soya: /Male: $572.68/ Female: $504.00

FY18

Maize: /Male: $840 / Female: $790

Maize:

 

Rice:/ Male:  $1,400 / Female: $1,250

Rice:

Soya: /Male: $600 / Female: $700

Soya:

LOP

Maize: /Male: $840 / Female: $790

Maize: /Male: $794.05 / Female: $711.00

 

Rice:/ Male:  $1,400 / Female: $1,250

Rice: /Male: $692.35 / Female: $588.16

Soya: /Male: $600 / Female: $700

Soya: /Male: $572.00 / Female: $504.00

THIS SHEET LAST UPDATED ON:  April , 2018

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Performance Indicator Reference Sheet - 3

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 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

36,452

 

FY 16

45,000

52,577

 

FY17

70,200

85,689

 

FY18

72,000

 

 

LOP

101,700

85,689

 

THIS SHEET LAST UPDATED ON: April , 2018

 

 

Performance Indicator Reference Sheet - 4

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

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

35,000

37179

 

FY 16

45,000

48275

 

FY17

70,200

72659

 

FY18

72,000

 

 

LOP

312,200

158113

 

THIS SHEET LAST UPDATED ON: April , 2018

 

 

Performance Indicator Reference Sheet - 5

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

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

483

 

FY 16

338

366

 

FY 17

338

783

 

FY 18

338

 

 

LOP

450

783

 

THIS SHEET LAST UPDATED ON:  April , 2018