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Background: Previous research highlights that common misconceptions aboutdeveloper productivity lead to harmful and inaccurate evaluations of softwarework, pointing to the need for organizations to differentiate between measuresof production, productivity, and performance as an important step that helps tosuggest improvements to how we measure the success of engineering teams.Methodology: Using a card sort, we explored how a Three Layer ProductivityFramework was used by 16 software engineers at a Software Engineering focusedconference to rank measures of success, first in the current practice of theirorganization and second in their individual beliefs about the best ways tomeasure engineering success. Results and discussion: Overall, participantspreferred organizations to 1) continue their prioritized focus on performancelayer metrics, 2) increase the focus on productivity metrics, and 3) decreasetheir focus on production metrics. When asked about the current metrics oftheir organizations, while all roles reported a current focus on performancemetrics, only ICs reported a strong focus on production metrics. When askedabout metrics they would prefer, all roles preferred more performance metricsbut only leaders and ICs also wanted productivity metrics. While allparticipants were aligned on performance metrics being a top preference, therewas misalignment on which specific metrics are used. Our findings show thatwhen measuring developer success, organizations should continue measurementusing performance metrics, consider an increased focus on productivity metrics,and consider a decreased focus on production metrics.

Is Our Organization Actually Measuring Productivity? How Contrasting  Organizational and Individual Measures of Engineering Success is an  Opportunity to Drive Engineering Transformation