Yesterday we saw that a great organization is one that delivers superior performance and makes a distinctive impact over a long period of time.
But how do you measure “superior performance” and “impact”? — especially in the social sectors, where they are hard to quantify and thus largely defy measurement?
Jim Collins answers in Good to Great and the Social Sectors:
For a business, financial returns are a perfectly legitimate measure of performance. For a social sector organization, however, performance must be assessed relative to mission, not financial returns. In the social sectors, the critical question is not “How much money do we make per dollar of invested capital?” but “How effectively do we deliver on our mission and make a distinctive impact, relative to our resources?”
Now, you may be thinking, “OK, but collegiate sports programs and police departments have one giant advantage: you can measure win records and crime rates. What if your outputs are inherently not measurable?
The basic idea is still the same: separate inputs from outputs, and hold yourself accountable for progress in outputs, even if those outputs defy measurement.
Here’s the key point:
It doesn’t really matter whether you can quantify your results. What matters is that you rigorously assemble evidence — quantitative or qualitative — to track your progress.
If the evidence is primarily qualitative, think like a trial lawyer assembling the combined body of evidence. If the evidence is primarily quantitative, then think of yourself as a laboratory scientist assembling and assessing the data.
To throw our hands up and say, “But we cannot measure performance in the social sectors the way you can in a business” is simply lack of discipline.
All indicators are flawed, whether qualitative or quantitative. Test scores are flawed, mammograms are flawed, crime data are flawed, customer service data are flawed, patient-outcome data are flawed.
What matters is not finding the perfect indicator, but settling upon a consistent and intelligent method of assessing your output results, and then tracking your trajectory with rigor.
So when there are aspects of your performance that seem to defy measurement, you aren’t stuck. You just need to think in terms of assembling evidence.
Much of that evidence may be qualitative. But that’s fine — in that case you are just thinking like a trial lawyer rather than a laboratory scientist. Therefore, lack of easily quantifiable performance outputs does not need to preclude your ability to give intelligent thought to identifying a consistent method for assessing results, and tracking them with rigor.