In 2019, in an effort to improve the efficiency and sustainability of its programming, GAIN’s Workforce Nutrition Programme (WFN) shifted away from the traditional project development and evaluation cycle towards a nimbler "Quality Improvement" (QI) approach. Deployed by the private sector for decades, QI relies on problem identification, repeated rounds of data collection and analysis, and iterative testing and scaling up of possible solutions. WFN initiated the QI approach for projects in Bangladesh, Ghana, India, Kenya, and Mozambique in 2019, and evaluated the experience in 2021-2022. The objective of this Working Paper is to report results of that assessment.
Overall, the method was demonstrated to be feasible, effective, and to have added value in industrial settings. QI’s success appears to have been affected by project context, with factory settings providing the best fit for the method’s iterative testing requirements. The assessment found that an early introduction of QI increased the likelihood of alignment with broader project goals, an improved outcome, and other indicators of a positive experience; there were more challenges where QI was introduced later. Findings suggest that the application of QI may have been affected by how many interventions were included in the broader project, with multi-intervention projects creating a more complex landscape of input and outcome measures, leaving no obvious entry point(s) for application of QI practices.
Despite general success in applying the approach, multiple questions remain. These include how to provide incentives and quality control measures for data collection, how to provide better support to GAIN staff, and how to build QI into deliverables and contractual agreements with implementing partners. Additionally, there is a need to consider whether QI is feasible in non-industrial settings where data collection is not embedded in working practices and work processes are harder to control.