An outcome-based measurement toolkit for data-driven governance of innovation ecosystems

Purpose Despite the increasing prevalence of conceptual models for innovation and entrepreneurship ecosystems, a persistent gap remains in their operationalization through measurable, data-driven frameworks. This paper aims to address that gap by presenting a multilayered measurement architecture and a comprehensive indicator toolkit grounded in the outcome-based ecosystem model. Design/methodology/approach Using a design science research approach, this study develops and tests the toolkit in a high-potential innovation region in Northern Mexico. The framework links ecosystem actors with stages of development along the innovation funnel – from early talent formation to scale-up maturity – and maps measurable indicators across these intersections. Findings The results reveal empirical insights into measurement blind spots, indicator density and coordination challenges. A visual heatmap supports system-level diagnostics, while emerging dashboards translate data into strategic intelligence. Practical implications The toolkit introduces a structured classification of metrics by type, frequency and feasibility, and proposes realistic data collection methods tailored to stakeholders such as governments, universities, venture capital firms and accelerators. This enables outcome-aligned governance systems that support real-time strategic coordination. Originality/value This contribution bridges the gap between conceptual ecosystem theory and actionable governance. It provides both a methodological advancement for ecosystem research and a practical instrument for stakeholders seeking evidence-based strategy, alignment and performance evaluation in complex, multi-actor innovation systems.