Hi all - stuck a bit at "show me numbers" to care ...
# general
Hi all - stuck a bit at "show me numbers" to care about productivity enablement & productivity engineering, platform teams.... How should one think of this? I fear that one creates tools, but you need the central team to drive adoption before it is a success. So there is demand for tools, but not an end to end look at improvement. Are there any numbers proving business outcomes to becoming more productive? I remember DORA had some reference, but i can't find it now.. just curious on best quantitative proof to care about engineering productivity.
So a while ago I picked up this book and it has a whole chapter about quantifying metrics from feature inception to sending it out to prod
Basically, you just start with Jira or whatever work system you're interested in, and find the first time the idea was entered into that system, and the day it goes to production. Then just treat it like a span in an application trace and break down the span into smaller logical units that make sense.
We're building golden paths and plan to measure those as a proxy for how effective/ineffective our platform is
similar to the trace idea above
Times that a ticket changes state are obvious important markers. Especially states like assigned, in development, testing, and released.
This might give you some insight, not much focus on ROI
You mentioned the DORA research - they have a new home for their research program. They have a model that shows the predictive indicators for specific practices as they relate to outcomes for an organization. https://dora.dev/research/