Traditional metrics prove that you were right. But how do you know when you’re wrong? C’mon, have you ever seen a metric that shows failure? I can slice any set of data to make myself look like a star! But the real value is knowing when I’m wrong.
OKRs (Objectives and Key Results) are very popular nowadays for tracking work to actual outcomes. The Key Results are designed to connect to leading and lagging indicators. But if you are testing a hypothesis, are you always proving you are right?
When metrics are called ‘success factors’ that’s a red flag for me that the group is closed to the possibility of being wrong. Success factors assume that if you are doing your job the metrics will be stellar.
Most organizations have performance tied to pay (don’t get me started) and people are incentivized to do whatever it takes to show that they met or exceeded their success metrics. If that’s my incentive, I’ll never show when I’m wrong.
Companies talk about “failing fast” and “celebrating failure”, but rarely are they willing to commit to metrics that will show them failing. More on the Fallacy of Failure here.
An executive once told me “With the rosy metrics that people come in here with I would think this company is prospering, but we’re not.” Where’ the disconnect?
When I coach organizations to define metrics that matter, I challenge them on how they will know when they’re wrong. That’s the metric that means something. That’s a metric that you can use to drive decisions. Define your thresholds before you get emotionally invested in the solution.
Brain twist: Next time your team is defining metrics or any new endeavor, ask them “How will we know when we’re wrong?”
