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Eval16 - Measuring Agency-Level Results: Can it Work, and Does It Matter? Findings From an InterAction White Paper 

01-05-2017 15:39

International non-governmental organizations (INGOs) that work in many countries and sectors are challenged to measure their results at an agency level. One approach that has been taken by many INGOs is to establish agency-level measurement systems, often based on quantitative indicators, which are often complemented by qualitative data. However, many INGOs have had difficulty designing their systems so that they are feasible to implement and produce meaningful results. To address this, InterAction commissioned a study to better understand and learn from why INGOs set up agency-level measurement systems, how they are designed, what they contain, and how they are used. In this presentation, which covers the first part of the study, drivers, design and use will be discussed. Particularly, the presentation will focus on the range of existing designs and their strengths and weaknesses, as well as what it takes to promote use of the data they produce.

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Can it Work, and Does It Matter? Findings From an InterA...   423 KB   1 version
Uploaded - 01-05-2017
International non-governmental organizations (INGOs) that work in many countries and sectors are challenged to measure their results at an agency level. One approach that has been taken by many INGOs is to establish agency-level measurement systems, often based on quantitative indicators, which are often complemented by qualitative data. However, many INGOs have had difficulty designing their systems so that they are feasible to implement and produce meaningful results. To address this, InterAction commissioned a study to better understand and learn from why INGOs set up agency-level measurement systems, how they are designed, what they contain, and how they are used. In this presentation, which covers the first part of the study, drivers, design and use will be discussed. Particularly, the presentation will focus on the range of existing designs and their strengths and weaknesses, as well as what it takes to promote use of the data they produce.