How and Why to Measure Engineering Productivity in a Large Company (Category Management)

Appeared. record I gave a talk at MTS True Tech Day about engineering productivity. This topic is important for large companies, as it is difficult to understand how effective the organization is. There are general indicators for the whole company, but they

• Show the overall situation in the company and it is difficult to understand the contribution of individual parts of the organization
• Display the results already achieved and with a strong lag - this is approximately consistent with the fact that when driving a car look not into the windshield, but in the rearview mirror. At a major technology company. (Tinkoff has about 10k engineers.) The efficiency of engineers makes a big contribution to the efficiency of the company, so we pay great attention to this.

The performance itself had the following plan. The importance of this issue (I already told it up here.) How I propose to narrow the scope of consideration only by grocery companies and part delivery without discovery

• What approaches were in the academic environment: DORA and Accelerate, SPACE, DevEx - abstracts with links to materials are available here
• Like Bigtech, for example, Google uses the QUANTS approach - abstracts are available here What is on the market in the form of commercial platforms - theses and links here
• Like we do in Tinkoff, here I'll talk about our T-Meter instrument. What are the implications of all this?

The transcript is in article in my blog and in the form of pdf in this channel.

P.S. Since my report is not pitching a funding round for a startup, I decided to exclude the part about the impact of AI on developer productivity, which pulls on a separate report. (recently told VP of Product from GitHub)

#Processes #Management #Performance #Engineering #Software #SoftwareDevelopment #Leadership