Running a good survey is more difficult than commonly perceived, as it requires expertise in survey construction, execution, and analysis. Convincing end leaders about the validity of surveys is a common challenge across different industries with technical experts. Highlighting the value of well-constructed surveys in uncovering insights that are difficult to obtain from objective data can be persuasive. Asking expert engineers for their opinions can provide valuable insights due to their integrative thinking and continuous focus on self-improvement. Technical user bases show a strong interest in self-improvement, self-quantification, and incremental change, demonstrating high engagement and interest in optimization compared to non-technical user bases.
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