Metrics and the Heisenberg quality of gathering data about behavior

All opinions are my own and do not necessarily reflect those of Novo Nordisk

Thinking more about the Global Health Metrics Conference, one element that resonated was that measurement does not occur in a vacuum.  When metrics are gathered, and especially when they are gathered out in the open by global health surveys, for example, there’s the real issue of the act of measuring changing the validity of what’s being measured.  I’ve been thinking about this in the context of hiring and workplace management.  For example, if the media were to report that viewership of Khan Academy videos on YouTube was found to correlate highly with creativity in the workplace, I expect two things would happen.  One, viewership of Khan Academy would spike, and second, the metric would rapidly begin to lose what correlative and predictive power it had.  People would try to game the system.

In Global Health, where countries are incentivized to meet certain milestones, it requires real thought to either make sure the milestones are strongly causally related to the health goals, or else that the metrics undergo continual fine-tuning to ensure the desired effect.  If the metric were something like number of healthcare facilities, a country could ensure that number increases but there wouldn’t necessarily be a concomitant increase in actual health services delivery.  I’m sure these are topics the Global Health community wrestles with every day.

It’s kind of like with relationships.  While on the one hand, we can tell our partners what we want, and often see them do it, on the other hand don’t we really secretly want them to already know and behave accordingly, because somehow that’s more genuine?  It’s certainly why social science researchers often mislead their study subjects on the actual purpose of behavioral experiments.  Or, to quote from the movie Buckaroo Bonzai, “Character is what you are in the dark.”

Ultimately, it seems best to try to measure behavior as closely as possible to the desired outcome.  That’s why baseball is nice.  We want good hitters, and to find good hitters it’s simple:  we measure how well a player can hit.

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