Abstract
Software moves faster every year. Markets shift rapidly, releases are ever more frequent, and languages, APIs, and platforms evolve at a relentless pace. And so interest in productivity, both by developers who want to keep up with these changes, but also by managers and organizations who need to compete, appears entirely rational. Moreover, improving software faster holds even greater promise to the rest of humanity: getting more work done with less effort means may mean an increased quality of life for everyone. In pursuit of productivity, however, there can be unintended consequences from trying to measure it. For instance: Measuring productivity can warp incentives, especially if not measured well; or Sloppy inferences from measurements could result in worse management decisions, rather than better ones. Are these bad enough that we shouldn’t even try to measure it? To find out, let’s do a thought experiment.
Cite
CITATION STYLE
Ko, A. J. (2019). Why We Should Not Measure Productivity. In Rethinking productivity in software engineering (pp. 21–26). Apress Media LLC. https://doi.org/10.1007/978-1-4842-4221-6_3
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