Abstract
Despite 20 years of increasing acceptance, implementing complexity-appropriate methods for ex-post evaluation remains a challenge: instead of focusing on complex interventions, methods need to help evaluators better explore how policies (no matter how simple) take place in real-world, open, dynamic systems where many intertwined factors about the cases being targeted affect outcomes in numerous ways. To assist in this advance, we developed case-based scenario simulation, a new visually intuitive evaluation tool grounded in a data-driven, case-based, computational modelling approach, which evaluators can use to explore counterfactuals, status-quo trends, and what-if scenarios for some potential set of real or imagined interventions. To demonstrate the value and versatility of case-based scenario simulation we explore four published evaluations that differ in design (cross sectional, longitudinal, and experimental) and purpose (learning or accountability), and present a prospective view of how case-based scenario simulation could support and enhance evaluators’ efforts in these complex contexts.