Impact measurement and management as governance infrastructure in development finance: Catalytic or extractive?

Abstract

Motivation

Impact measurement and management (IMM) has become a central pillar of development finance, yet concerns persist about whether prevailing approaches support genuinely catalytic outcomes or instead reinforce extractive dynamics. Although efforts to harmonize indicators and strengthen accountability have expanded, less attention has been paid to IMM frameworks themselves, including their design assumptions, embedded power relations, and governance effects.

Purpose

This study aims to assess whether widely used IMM frameworks are structurally aligned with catalytic, system-level change or whether they reproduce extractive logics. It asks how the design of IMM frameworks shapes what is valued, measured, and acted upon in development finance systems.

Approach and methods

The article introduces a diagnostic typology that evaluates IMM systems in three dimensions: IMM design conditions, impact flow dynamics, and systemic feedback and regenerative capacity. Using qualitative, structured content analysis, the study examines a sample of widely used IMM tools and standards to identify recurring design patterns and structural tendencies.

Findings

The analysis identifies design features associated with catalytic IMM, including participatory metric design, adaptive feedback loops, long-term systems thinking, and multi-directional accountability. It also highlights design patterns that signal extractive logic, such as context-free standardization, one-way reporting, and short-term impact horizons. While many frameworks reference systems thinking rhetorically, few operationalize it in ways that enable meaningful adaptation or systemic learning.

Policy implications

By treating IMM frameworks as institutional artefacts rather than neutral technical tools, the article reframes IMM as governance infrastructure. The findings suggest that donors, development finance institutions, and practitioners should prioritize IMM designs that embed participation, adaptive learning, and long-term system stewardship if impact measurement is to support development effectiveness rather than merely verify performance.