Measuring What Matters : Principles for a Balanced Data Suite That PrioritizesProblem-Solving and Learning

Responding effectively and with professional integrity to the many challenges of publicadministration requires recognizing that access to more and better quantitative data is necessary but insufficient.Overreliance on quantitative data comes with its own risks, of which public sector managers should be keenly aware. Thispaper focuses on four such risks. The first is that attaining easy-to-measure targets becomes a false standardof broader success. The second is that measurement becomes conflated with what management is and does. The third isthat measurement inhibits a deeper understanding of the key policy problems and their constituent parts. The fourth isthat political pressure to manipulate key indicators can lead, if undetected, to falsification and unwarranted claimsor, if exposed, to jeopardizing the perceived integrity of many related (and otherwise worthy) measurement efforts.Left unattended, the cumulative concern is that these risks will inhibit rather than promote the core problem-solvingand implementation capabilities of public sector organizations, an issue of high importance everywhere butespecially in developing countries. The paper offers four cross-cutting principles for building an approach to the useof quantitative data—a “balanced data suite”—that strengthens problem-solving and learning in publicadministration: (1) identify and manage the organizational capacity and power relations that shape data management; (2)focus quantitative measures of success on those aspects which are close to the problem; (3) embrace a role forqualitative data, especially for those aspects that require in-depth, context-specific knowledge; and (4) protect spacefor judgment, discretion, and deliberation in those (many) decision-making domains that inherently cannot be quantified.