[gutnor]

Decision driven from bad data is IMO worse than data-less decision.

Data grants authority to a decision that gut feel driven one doesn't. It is hard to argue against evidence as it should be, but that assume a certain level of quality in the evidence.

Second, if practice doesn't match the expected outcome, the first thing you will look at is what the team is doing wrong, not review the decision as not working.

That said, parent is far from unique in his skepticism, so I think the problem is more often reversed in the industry. Having some data, even flawed can help your company decide to try something new.

[itsoktocry]

>Decision driven from bad data is IMO worse than data-less decision.

What is "bad data", and how is it worse than no data?

[tsimionescu]

Think of things like "lines of code written" or "bugs closed" as measurements of productivity or quality. These are real things that people have used in real published studies - and any conclusion drawn from them is obviously bogus.

[mp05]

Data gathered from a poorly designed study? I don't think it needs explaining why making decisions on nonsense is just that.

[itishappy]

Measurement noise, other experimental errors, small sample size, cherry picking. It's worse than no data because you can draw incorrect conclusions.

Have a really dumb example:

All of the developers I work with are short, therefore all developers must be short, and we could save time by filtering job applicants by height.

(Note: I work with only one developer. He's great!)