Methodological bricolage, data pattern detection and realist explanation: A portfolio analysis of inclusive business support

Abstract

This article shows how a realist portfolio analysis was operationalised as part of an evaluation of a donor-funded development programme. This programme supports small and medium-sized enterprises with data analytics and business coaching to make their sourcing and service delivery models more smallholder inclusive. After ranking all projects on relative effectiveness in convincing business owners to change their business model, we applied an iterative, abductive process of realist causal explanation. For the portfolio analysis, we used the realist evaluation question, ‘What works, for whom, under what conditions, and why’ as the key learning question. We then developed a methodological bricolage of variable-based regressions, case-based truth table analyses, reflection workshops and case study interviews to detect candidate casual factors and configurations and distil insights for better targeting of that support. In the realist explanation and theory adjudication, we relied on academic and practical knowledge about the role of organisational social capital in value chains.