Posted by: Tayo Akinyemi | February 3, 2012

What Works When You’re Measuring What Works

I’m always happy when I read a piece that “flips the top” in order to examine easy assumptions. Matthew Forti’s article “Ensuring that Scaling What Works Actually Works”, posted at the Stanford Social Innovation Review and on Bridgespan Group’s blog does exactly that. What really resonates with me is his emphasis on understanding the complexities underlying a model’s success.

Most evaluation studies devote little, if any, attention to underlying organizational factors (such as culture and leader characteristics) and contextual factors (such as regulatory climate and the presence of high-capacity partners) that play a role in the model’s success. In the absence of understanding the conditions under which a model worked, organizations or funders often require replicators to follow the original model with full fidelity, potentially precluding important adaptations and improvements that could increase the odds of success.

To his point, if you don’t fully understand why something worked the first time, you’re unlikely to reproduce the initial results.  Perhaps more importantly, as was noted by a commenter, there’s no “one size fits all” approach to measurement.  Nonetheless, two key principles remain fundamental: 1) know what you’re measuring and state it explicitly; and 2) ensure that your measurement approach is appropriate for the scenario you’re operating in.

Easier said than done.

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