Regulatory operations metrics: what to measure, what to ignore, and what actually predicts compliance performance
Evaluate candidate metrics against three selection criteria, design a balanced metric set with leading, lagging, and process indicators, and recognize the perverse incentives produced by poorly chosen measures.
Regulatory operations metrics: what to measure, what to ignore, and what actually predicts compliance performance
There is a sentence I repeat to nearly every regulatory operations leader I work with, and I will repeat it to you now because the rest of this lesson depends on you taking it seriously. The metric you measure is the behavior you get. Not the behavior you intended. Not the behavior the policy memo described. The behavior the metric, by its existence, rewards.
A site that measures regulatory submission volume gets more submissions, faster, sometimes at the cost of quality. A site that measures the absence of protocol deviations gets the appearance of zero deviations, sometimes by suppressing the reporting of real ones. A site that measures training hours delivered gets seat time, sometimes detached from any verified competency. None of these outcomes were anyone's stated goal. All of them are direct, predictable consequences of how the metric was framed.
This is not a problem you can solve by working harder at choosing metrics. It is a problem you solve by working slower, applying explicit selection criteria, and being honest about what each candidate measure actually rewards. That is what this lesson is for.
What you will learn
By the end of this lesson, you will be able to: