I saw this image in an issue of the FLUX Review yesterday:
It’s a great visualization of the difference between accuracy and precision.
Accuracy is how close to reality a measurement is, precision is how close measurements are to each other.
Both are valuable, but there is a distinct order of operations needed.
Get accurate first. Then get precise.
If you go for precision first, you’ll spend a lot of time dialing in your measurements, ensuring there’s a logic to them in relation to each other, ensuring you can accurately capture data down to the decimal, and setting up systems to do so.
The scope of your activities will get restricted and locked in based on the needs of the measurements.
Then you go out into the real world and experience a really tight grouping far away from the target, like the second image above.
Better is to just throw the first dart.
Now you’ve got a baseline. You can see how accurate or inaccurate your efforts are. You can adjust the efforts to increase accuracy. After you’ve gotten close to enough the target, you can start to work on precision and tighten your grouping.
The other way around just doesn’t work.
So rather than plotting out detailed OKRs and KPIs and hoping they’re relevant before you get out into the market, go do some stuff first. Throw some darts and base your plans and goals and measurements around the baseline of what you find.