I don't agree with most of the advice in this article but rather than complain let me suggest an alternative.<p>As a line manager, with software engineers reporting directly to you, you should be able to use your personal judgment to understand the productivity of your software engineers. Don't measure it with acronyms, with metrics like the number of commits, or by paying attention to how many hours a week people are working. Pay attention to whether people get things done, and are they getting big important things done, or only little nice-but-not-critical things. Make sure you communicate enough so that individual software engineers understand how you think and what you prioritize.<p>As a manager-of-managers, it is going to be very difficult for you to measure developer productivity. It's tempting to look at metrics like the number of code reviews a developer does. But these can at most be a sanity check, not the core metric to go for.<p>Instead, you can measure productivity of <i>teams</i>. Is the team getting things done, and are they big important things, or only little nice-but-not-critical things? Sometimes, a line manager will insist that everyone on their team is performing excellently, and yet you observe the team overall is not achieving very much. Probably one of the two of you is incorrect, and you should dig in to figure that out. The opposite also happens, where a manager states that everything is a disaster, but you observe that the team has actually delivered a lot.<p>The other thing you can do is to teach your line managers how to judge individual productivity. There's no silver bullet, it's just a natural outcome of having conversations about who is productive and who is not and how to tell and what to do about it, so be sure to have enough of those conversations.<p>None of this is easy to quantify, but the hard truth is, there is no natural mapping from numbers to developer productivity and it is usually a bad idea to try to quantify productivity. You are much better off using human language and intelligent thinking to evaluate productivity, rather than reductionist metrics.