Muddy metrics destroy your ability to make good decisions.
A muddy metric is a type of data that is created from variable data points that muddies its meaning. Let's go over an example.
If I have a daily routine of reading, a metric for tracking that routine could be a simple check box. This is known as a binary metric.
Binary metrics can be summed up over a period of time. If I read every day for a whole week, except one, then my reading rate for the week would be 85.7%. If you extend that out to a whole month, only reading 6 days a week, you'd be at a reading rate of 86.6%.
But, how much do I have read to check that box? Is all reading treated equal? Can I trust my metrics for making decisions?
It's up to you to determine this, and this is where the metrics get muddy. Your day-to-day routines will shift. Reading the back of a cereal box is not going to make the cut for checking the box. And reading a lot much deserves a "bigger checkmark" right?
This is just a simple example of where metrics get muddy. But, with more complicated examples, your metrics could actually be working against you without you even knowing it.
Just because you do something every day doesn't mean you're doing it the right way.