Ask HN: Data-driven tech debt investment
I've talked to two engineers in the last few weeks who work at companies that:
1. Use a combination of per-team/service metrics to decide when to invest in paying down tech debt. For example: incidents/pages over a trailing window, DORA metrics, engineer ratings of the difficulty of working with the service, etc. 2. Enforce paying down tech debt for a team/serviceif those metrics go above a certain defined threshold. For example, teams with a high tech debt score at Company A are no longer allowed to develop new features. At Company B, high tech debt teams automatically get a tech debt-related OKR for the next quarter instead of a feature OKR.
In all my past roles, deciding to invest in tech debt was a judgement call and led to some significant frustration or even attrition when leadership and engineers didn't agree on how bad tech debt or ops pain was. It's exciting to imagine a better alternative, and both engineers I was talking to felt like it worked well at their company. However, I can also imagine ways it might not work well: Goodhart's law etc.
So HN, have you tried this sort of approach? Did it work?