There has recently been a debate over metrics when applied to software testing. Stories of usage and examples have run the whole range from the good, the bad, the ugly to the incomprehensible.
Linda Wilkinson has bravely decided to start a series on metrics and her viewpoints, here. I anticipate a good discussion - if there is any negative feedback I'm sure it'll be given in a professional way - rather than just being unfriendly feedback.
My latest metric
The latest metric that I have used is the pedometer - or step counter. It shows me how many steps I have taken and total elapsed time with a conversion to distance and calories used.
But that's just raw data - I need a certain history and environment in which to interpret the data.
It doesn't tell me about the terain I was walking in.Was it hilly - so some steps counting double for the exertion?Was I walking fast/slow?Was I walking fast and taking lots of breaks or did I do the whole thing in one go?Was I carrying any baggage?Was I pushing or pulling something?How comfortable were my shoes?
If using them, then understand the data - what it's representing, what it's an instance of and question what it's not telling you.
Know and work with examples of what might be deducable from the data.
Know and work with examples of what cannot be deduced from the data.
Know how to deal with data that's missing - sometimes nothing more than to acknowledge it - but that's an important step in itself.
Some would say that the answer to my pedometer problem is to get a better pedometer or ultimately some sort of human-tachometer. However, I just want a simple comparison - something that gives me some background data. It's just data until I can set it in a context with some meaning and I'm happy to do that step.
Even a super-duper-human-tachometer couldn't tell me about my motivation on a given day. The final story always needs the narrative!
Have you thought about the problems and limitations of your metrics?