Less Proof, More Imprecision

The pressure to arrive at proof might be getting in the way of thinking bigger, planning longer-term, and acting upstream.

Less Proof, More Imprecision

Publicly-traded companies are regularly criticized for optimizing around their quarterly earnings and not thinking long-term about their business, and I’m beginning to think that the stringent impact metrics imposed upon us (or self-imposed on ourselves) are our sector’s equivalent of quarterly earnings reports.

The pressure to arrive at proof might be getting in the way of thinking bigger, planning longer-term, and acting upstream. For a publicly-traded company to disrupt itself and reinvent its business, it needs to contend with the reactions it will face in the public markets. Non-profits and social enterprises that are held to precise proof-points of impact face similar consequences: they struggle to work upstream into root causes, they are held back from thinking divergently about where the space is trending.

Better to demonstrate to a funder that we can guarantee delivery of 3,000 meals every month at the soup kitchen than to begin some imprecise, upstream work addressing the drivers of homeless that could be difficult to prove. That upstream work might not be effective (in which case funding is lost) and/or that upstream work might be so far upstream that it’s nearly impossible to prove effectiveness (in which case funding is also lost). Our system rewards short-term precision and proof because we are in a rat race that optimizes for the quick-ripening/low-hanging fruit of impact.

I’d suggest those of us in the impact investing, social enterprise, and philanthropic spaces consider two lines of inquiry:

  • At what point are our standards of precision and our thresholds of proof a barrier to real impact instead of an enabler of it? We need to embrace greater imprecision and lower our standards of proof. For example, when the only eligible grantees for a foundation’s “big bet” are those with a randomized control trial, is that a big bet or a safe bet? As long as we operate within the narrow confines of precision, we limit our ability to try experimental or upstream approaches.
  • When is our obsession with precision and proof of impact more about reinforcing our need to be right and less about determining that impact is actually happening? Is it possible that both the obsession with quantitative metrics and the relentless drive towards proof are sometimes more about our own fragile need to know beyond-a-shadow-of-a-doubt that our money and our work are actually effective? What is it about being imprecise that makes us so uncomfortable?