The UXR is on our team. If we were UX researchers on a consumer facing product, it'd be like, those out there are the users and we try to understand what they mean. The engineers offers this really deep subject matter expertise. So that stuff that comes from the social sciences. And we're able to bring that expertise. We run surveys that we think aren't terrible but it's super easy to run a terrible survey. Once you've run a survey, non-response bias analysis is a thing. Right? You need to account for them.
This week we’re joined by Ciera Jaspan and Collin Green, who lead the Engineering Productivity Research team at Google. Ciera and Collin have written several papers from studies they’ve conducted, and this discussion covers the insights from their research as well as their work more broadly at Google.
Discussion points:
- (1:19) About the Engineering Productivity Research team
- (3:57) How the team interacts with the rest of the organization
- (5:58) The different backgrounds included on the team
- (13:11) How Google measures developer productivity
- (18:54) Evaluating discrepancies between qualitative and quantitative data
- (28:40) Google’s quarterly developer survey
- (32:02) Distributing survey results back to the organization
- (40:25) Misunderstandings about surveys
- (43:51) Ciera and Collin’s paper on why measuring productivity is difficult
- (50:35) Reductionist metrics for measuring productivity
- (55:26) Examples of other fields that have struggled with measurement
- (59:00) Google’s study on measuring technical debt
- (1:08:05) Human judgment in measurement
Mentions and links:
Follow Ciera and Collin on LinkedIn
A Human-Centered Approach to Measuring Developer Productivity - Paper, Abi’s summary
Enabling the Study of Software Development with Cross-Tool Logs - Paper
Defining, Measuring, and Managing Tech Debt - Paper, Abi’s summary
Google’s Goals, Signals, Metrics framework - Paper, Abi’s summary