It is often said that “what gets measured gets done.” This common phrase implicitly frames measurement not just as a tool for capturing information about systems but also as an intervention itself. This belief in the transformative power of measurement may partially explain the huge sums of money spent each year by governmental, nongovernmental, and private sector organizations in developing, maintaining, and publicizing measures.

We aren’t referring to the private use of measurement by organizations to evaluate and improve their own internal performance, or randomized controlled trials to measure the effectiveness of a new social service program or data mining to better understand customer behavior. That is a vast and important subject that has been widely explored.

We are focused on the broader use of measures to report on, and hopefully drive, large-scale social change. Consider one of the best-known examples, the Consumer Price Index, or some of the lesser-known ones, such as the Corruption Perceptions Index, the Sustainable Governance Indicators, and the National Health Security Preparedness Index.1 But it’s not just indexes. High school graduation rates, for instance, are an example of individual measures used to hold schools and districts accountable and drive improvement.

As much attention as there is now on using measures to foster social change, it is likely to increase in the future. That’s because our ability to track, measure, and analyze all sorts of things is growing by the day. Low-cost sensors and microprocessors, wireless connectivity, and mobile devices, all connected to the Internet, make it easier and easier to collect data. And ever more powerful and less expensive computing power and data storage make it easier to analyze this growing mountain of data. At the same time, there is a growing push by the government, philanthropists, policy makers, and social change agents to measure and report results, and use the results to drive decision making and foster behavior change.

But for all the attention on and use of data collection and measurement, there is remarkably little discussion or research on how—and under what circumstances—measures actually “work.” The science of measurement remains largely silent on the topic, focusing instead on issues of validity and reliability, and treating the behavioral impacts of measurement as “reactivity to measurement”—a source of measurement error that must be minimized.2

This, then, is a case where theory lags behind practice. Measurement theory focuses mostly on how to find measures that accurately represent systems. This is critical. But funders, government officials, and social innovators also need guidance on using measures to improve systems.

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