Creating Flexible Standards: Construct-Based Equivalence

Current impact measurement approaches can be grouped into one of two categories. The first is flexible approaches that emphasize bespoke indicators based on a learning process within the organization. The other category is uniform approaches that seek to create and promote shared indicators. Based on what we know about successful standards in other domains—those with wide and long-lasting adoption—the best approach for impact measurement will be to balance uniformity and flexibility rather than choose one over the other. To achieve this middle ground, Common Approach uses construct-based equivalence.

What is construct-based equivalence?

Construct-based equivalence groups metrics by idea or concept. When items are conceptually the same, it treats them as equivalent or equal, even if they are not measured the same way across organizations. This stands in contrast to measurement-based equivalence, the prevailing approach to social and impact measurement. Under this method, measures are the same enough to be aggregated and compared only if they are measured and defined in the exact same way. Construct-based equivalence succeeds by acknowledging the validity of different interpretations and uses of the same concept.

Would you say this is a photo of plants, or insist on specifying the type and colour of pot? Grouping things by idea or concept is a natural impulse that can be put to good use in measurement.


Take the concept of a job. It is an easy enough concept to understand; almost everyone knows what a job is. However, for organizations looking to help create jobs or facilitate job placements, this concept has a range of definitions.

One company helps neurodivergent workers get out of low-pay manual labour jobs and into high-skill computer programming jobs (from one full-time permanent position to a better full-time permanent position). Another company creates a working environment where disabled people can access part-time flexible jobs with readily accessible accommodations (part-time work provided as the most appropriate work). An impact investor investing in both these organizations will better understand their impact if they focus on the construct equivalence—seeing both companies providing “a good job” rather than measurement equivalence based on criteria like full-time, permanent positions.

The same applies to concepts that carry more precise internal definitions, like demographics. A funder is looking to know how many youths have had significant or transformative opportunities as a result of their funding. Their grantees define the youth demographic differently: a climate action foundation defines youth as 18-24, while a literacy foundation defines youth as 14-20. Using measurement-based equivalence, the funder would decide on one fixed age range to represent the youth demographic and ask all grantees to report their data using this definition. If they chose 18-24, the literacy foundation would have to recalculate their data based on the funder’s definition, creating an additional burden and cutting out an important part of their impact story. Using construct-based equivalence, the funder would adopt a broad concept of youth and aggregate metrics from the different grantees, allowing them to work with the metrics that the grantees are already tracking.

Favouring construct-based equivalence opens a flexible standard to multiple perspectives, which solves many current problems with impact measurement standards. The ability to see data as different but the same enough for aggregation gives impact standards more longevity. As an additional and important bonus, construct-based equivalence also makes it easier to align impact measurement with the priorities of those whose lives are most affected rather than the definitions chosen by funders or standard setters.

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Published February 27, 2024

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