Resource ID: INDIGO-ARES-0071
Link: https://fic.tufts.edu/publication-item/participatory-impact-assessment-a-design-guide/
Seeks to answer the question: “What difference are we making?” through a participatory approach to measuring impact on livelihoods
Offers not only a useful tool for discovering what change has occurred, but also a way of understanding why it has occurred.
Impact goal: Well being, Social impact, Development poverty reduction
Internal/external: Internal
Leader: Feinstein International Center
Method: Surveys, Interviews, Attribution, Operational data, Diff in diff statistical analysis
Output format: Quant but no index
Scale: Meso
Sourcing: Self driven
Time frame: Ongoing, Prospective, Retrospective
Type: Framework
Used in sectors: Charity, Development
Who: Third sector
INDIGO data are shared for research and policy analysis purposes. INDIGO data can be used to support a range of insights, for example, to understand the social outcomes that projects aim to improve, the network of organisations across projects, trends, scales, timelines and summary information. The collaborative system by which we collect, process, and share data is designed to advance data-sharing norms, harmonise data definitions and improve data use. These data are NOT shared for auditing, investment, or legal purposes. Please independently verify any data that you might use in decision making. We provide no guarantees or assurances as to the quality of these data. Data may be inaccurate, incomplete, inconsistent, and/or not current for various reasons: INDIGO is a collaborative and iterative initiative that mostly relies on projects all over the world volunteering to share their data. We have a system for processing information and try to attribute data to named sources, but we do not audit, cross-check, or verify all information provided to us. It takes time and resources to share data, which may not have been included in a project’s budget. Many of the projects are ongoing and timely updates may not be available. Different people may have different interpretations of data items and definitions. Even when data are high quality, interpretation or generalisation to different contexts may not be possible and/or requires additional information and/or expertise. Help us improve our data quality: email us at indigo@bsg.ox.ac.uk if you have data on new projects, changes or performance updates on current projects, clarifications or corrections on our data, and/or confidentiality or sensitivity notices. Please also give input via the INDIGO Data Definitions Improvement Tool and INDIGO Feedback Questionnaire.