Knowledge Note | Institute for Development Impact

The Pathways to Living Income: A Farmer Segmentation Model

The Pathways to Living Income: A Farmer Segmentation Model takes a data-driven approach to categorize farmers based on three key factors: resources, productivity, and empowerment. By identifying specific segments within the farming community, the model enables precise interventions tailored to each group’s unique needs. Whether it’s improving resource access, boosting productivity, or empowering women in decision-making, this model guides program development to help farmers achieve a sustainable living income. Through targeted support, the framework fosters resilience and long-term economic stability for smallholder farmers.

Empowering Decisions With Data: How Data Analysis Drives Esg Compliance And Sustainable Business Practices

In today’s competitive business landscape, evidence-based decision-making is vital for the success and longevity of organizations. It allows companies to identify potential risks and opportunities, allocate resources efficiently, and adapt to changing market conditions. Compliance with environmental, social, and governance (ESG) regulations and industry standards is crucial for mitigating legal and financial risks, and maintaining a loyal and growing customer base. Data analysis plays an essential role in informing business decision-making and ensuring adherence to these regulations and standards, which in turn impacts long-term business performance.

This article, written for the Small Business Association for International Companies (SBAIC) discusses the importance of harnessing data analysis for ESG compliance and sustainable business practices, developing learning agendas for effective ESG compliance management, and provides five illustrative learning questions that can be used to guide ESG and sustainable performance data analysis.

USAID CLA Case Competition Win 2022 – Expanding the Reach of Women + Water in India through Collaboration and Adaptation

I4DI, in collaboration with USAID and Gap Inc, our partners on the Women + Water Alliance, won USAID’s 2022 Collaborating, Learning, and Adapting (CLA) Case Competition. This resource details our submission to that competition, including how we applied CLA best practices to improve and sustain the health and wellbeing of women and communities touched by the apparel industry in India, as well as to empower women to become change agents for water, sanitation, and hygiene (WASH) management in their communities. As a result of our CLA efforts, the number of people empowered to improve their access to drinking water and sanitation through the Women and Water Alliance increased from just under 70,000 to more than 900,000, and ultimately reached more than 2 million people by the end of the activity.

USAID/RFS Activity MEL Plan Webinar

Logic models serve as a potent visual representation of a Theory of Change (ToC), encompassing various forms such as Results Frameworks, results chains, and Logical Frameworks. While not a stringent requirement by USAID at the activity level, the integration of a ToC and logic model in an Activity Monitoring and Evaluation Plan (AMELP) is fervently recommended. This guidance note, part of the RFS Good Practice MEL Notes series, elucidates the alignment of these models with the stated objectives of an activity, set within a particular context. It accentuates the coherence between components of the Activity MEL Plan and the ToC, fostering a comprehensive understanding of development paradigms.

Selecting Performance Indicators – An RFS Good Practice MEL Note

Performance indicators are pivotal for the successful implementation, adaptive management, and optimization of development programs. This guidance note, a part of the RFS Good Practice MEL Notes series, underscores the significance of these indicators in line with USAID’s requirements for Activity MEL Plans. It emphasizes the inclusion of at least one performance indicator for each outcome in an activity’s logic model. Special attention is given to gender equality and female empowerment indicators. This document serves as a beacon for understanding the diverse types of indicators and their integration into the developmental framework.

USAID/RFS Good Practice MEL Notes – Performance Indicator Targets

Performance indicators and their targets play a critical role in successful implementation, adaptive management, and maximizing performance of development programs. A target is defined by USAID as “a specific, planned level of a result to be achieved within a specific timeframe with a given level of resources.” This USAID/RFS Good Practice MEL Note walks readers through RFS good practice examples to facilitate better target setting during the Activity MEL Plan development process and activity implementation. It also provides some guidance on how to adjust targets during implementation and helpful tips for setting performance indicator targets.

USAID/RFS Good Practice MEL Notes – Performance Indicator Reference Sheets

Performance indicators play a critical role in monitoring activity performance and understanding what results are achieved. In essence, Performance Indicator Reference Sheets (PIRS) are worksheets that define indicators and ensure that they generate consistent, high quality data across portfolios. This USAID/RFS Good Practice MEL Note describes how to develop or review PIRS for Activity MEL Plans and highlights several RFS good practice examples. Annex A annotates the links between a standard and an activity PIRS. Annex B provides tips for A/CORs for reviewing PIRS.

USAID/RFS Good Practice MEL Notes – Evaluation Statements of Work

An evaluation Statement of Work (SOW) clarifies the expectations for how an evaluation will be designed and conducted in much the same way that an activity’s scope of work dictates how an activity must be designed and implemented. The developer of an evaluation SOW is in many regards the architect of the evaluation itself. The more detailed and accurate the SOW the
more likely that the evaluation will generate useful and high quality findings, conclusions, and recommendations. This USAID/RFS Good Practice MEL Note provides an overview of the components of a good evaluation SOW, important tips when developing or peer-reviewing
evaluation SOWs, as well as an annotated example of a good evaluation SOW to show the reader how specific good practices were applied effectively in an actual RFS evaluation SOW.

USAID/RFS Good Practice MEL Notes – Disaggregating Monitoring Indicators

Performance indicators play a critical role in monitoring activity performance and
understanding its results. Disaggregating data – or separating it into subgroups – allows
users to understand nuances or trends within the data. This USAID/RFS Good Practice MEL Note provides USAID staff and partners with specific guidance on Agency required disaggregations such as sex dissagregations, as well as good practices and helpful tips to consider when determining which disaggregates to use and how to apply them.

USAID/RFS Good Practice MEL Notes – Performance Indicator Baselines

USAID policy requires baseline data for each of their performance monitoring indicators, but USAID staff and partners often struggle to determine the most appropriate baseline and the best mechanism to establish that baseline. This USAID/RFS Good Practice MEL Note provides USAID staff and partners with specific guidance on what good baselines look like and how to establish them. It walks the user through several common baseline setting scenarios, including examples from RFS-funded activities, as well as helpful tips for establishing performance indicator baselines.