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

We're building golden paths and plan to measure those as a proxy for how effective/ineffective our platform is

Times that a ticket changes state are obvious important markers. Especially states like assigned, in development, testing, and released.

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/