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The Right Way to Measure Productivity (and Why It’s Harder Than it Seems)
Dynamic Measurements
Instead of relying on a fixed standard, regularly tweak and adapt what you measure.
Changing what you're measuring may seem like a drawback, but it really makes your work more robust. Meta-feedback on what you measure stops you from reaching a fragile solution.
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Measuring Productivity: Input vs. Output
There are two extremes of evaluating productivity: Input vs. Output
- Input: The salaryman works long hours and is mostly judged on input. The person is judged by his loyalty and commitment to the company.
- Output: The person is entirely measured on output. His work doesn't track his hours. Repeatedly failing to meet deadlines would get him fired.
Only Judging Outputs
Some consultants are paid when the company profits go up, but no money is owed when there is no profit.
But, early management theorists noticed just having a consultant made people work harder. A consultant can make a fortune, even though the advice is worthless. The problem with the pay-for-results consultant is that the payment comes too soon. An extended period could give better insight.
Big-Picture and Fine-Grained Detailed
A dimension in measuring productivity is looking at the big picture or fine-grained details.
- The big picture: Looking back over the years, how much difference did it make?
- Fine-grained means adding up the hours worked, which gives an immediate measure of progress.
But there is a trade-off. The big picture is slow to measure and may only be visible in the long run.
How to Measure Productivity
What matters most is often the hardest to track. We then measure things we don't care about with the hope that it will give some clarity. The solution:
- Pick a few metrics that will estimate what matters. The metrics should be easy to measure and timely enough to give good feedback. Rewarding only hours may mean paying for a lot of overtime and not much useful work.
- Use meta-feedback to tune your short-term metrics. Your big-picture output is harder and slower to measure, but it serves a role in regularly adjusting which of the short-term metrics will estimate progress. For example, if you track the number of essays written for your productivity, it may be good initially, but the quality may suffer in time. Following the articles' results can indicate if "hours per essay" should also become a metric.
Dynamic Measurements
Instead of relying on a fixed standard, regularly tweak and adapt what you measure.
Changing what you're measuring may seem like a drawback, but it really makes your work more robust. Meta-feedback on what you measure stops you from reaching a fragile solution.
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