zlacker

People use flawed but easily consumable metrics to make almost all decisions.

It takes a lot more effort to collect multiple metrics along different axes, understand the skew/bias of them and make an informed decision.

Visibility and ease of consumption are the most important aspects of a metric if you want people to use it.

>>Zephyr+(OP)
The list in the article, though, was carefully selected to presume competent people doing the decision-making. I totally believe many people use that star count for something... but an "enterprise"? someone investing non-trivial amount should of money? a specifically-"talented professional"? I just find that really difficult to believe. I've sold software to enterprise, I've worked with a number of venture capital funds, and I know a ton of actually-talented professionals... I dare say most of them consider GitHub's social features to be a joke.

The enterprises I deal with cared almost exclusively about stuff like license choices, support contract options, and "invoice billing" ;P. The vetting process I've dealt with at VCs was intense, having worked both sides of that situation; and I know multiple people who have worked data science jobs at such firms to try to better select investments. As for a "talented professional", I can pretty much guarantee they are going to look at your codebase, not the number of stars it has, while they evaluate any number of more reasonable things to judge an opportunity on (commute, pay, management style, etc.). A key property of competent deciders is that they aren't using trivial metrics.