The Qualitative Impact Assessment Protocol (QuIP) is an impact evaluation approach that draws on Contribution Analysis. QuIP studies serve to provide an independent reality check of a predetermined theory of change which helps stakeholders to assess, learn from, and demonstrate the social impact of their work. QuIP’s approach places project beneficiaries’ voices at the centre of the evaluation, enabling them to share and feedback their experiences in an open, credible, and respectful way.
The QuIP gathers evidence of a project’s impact through narrative causal statements collected directly from intended project beneficiaries. Respondents are asked to talk about the main changes in their lives over a pre-defined recall period and prompted to share what they perceive to be the main drivers of these changes, and to whom or what they attribute any change - which may well be from multiple sources.
A control group is not required as evidence of attribution is sought through respondents’ own accounts of causal mechanisms linking X to Y alongside Z (key informant attribution) rather than by relying on statistical inference based on variable exposure to X. This narrative data is intended to be triangulated with other data and to complement quantitative evidence on changes in X, Y and Z obtained through routine project monitoring or other methods.
Impact goal: Health, Defence, Housing, Agnostic, Democracy, Education, Well being, SDG oriented, Social impact, Local rejuvenation, Sustainability eco, Development poverty reduction, Employment financial well being
Leader: University of Bath’s Centre for Development Studies (CDS) and Bath SDR
Method: Surveys, Interviews, Focus groups, Theory of change
Output format: Qualitative only
Sourcing: Self driven
Time frame: Retrospective
Used in sectors: Charity, Governance policy, Developed countries
Who: Third sector, Public sector
Please tell us about it
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.