It is about time: Bias and its mitigation in time-saving decisions in software development projects

Lior Fink, Barak Pinchovski

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Estimates of completion times in software development projects are frequently inaccurate, potentially resulting in failure to meet project objectives. The present work aims at empirically investigating whether the time-saving bias, describing the human failure to correctly estimate the relationship between speed increase and time saving, can inform our understanding of the decades-long problem of time estimation in software development. In particular, this work examines whether a decision to save time in a software development project by increasing development speed is biased, whether this bias is observed when the decision is framed using plan-based and agile terminology, and whether the availability of relevant information mitigates this bias. These objectives are addressed in three experimental studies, in which senior information systems students (Study 1) and professional software project managers (Studies 2 and 3) are asked to make time-saving decisions about two similar scenarios, with and without relevant information. The findings confirm the existence of the bias and show that it is more likely to occur under an agile framing than under a plan-based framing, although students are highly biased in both cases. The findings also show that while the bias is mitigated, but not eliminated, when relevant information is included in the scenario, this effect dissipates once the information is no longer included in the following scenario. The accumulated evidence reported here contributes to research on the consequences of cognitive biases for project management decisions.

Original languageEnglish
Pages (from-to)99-111
Number of pages13
JournalInternational Journal of Project Management
Issue number2
StatePublished - 1 Feb 2020


  • Decision making
  • Experiments
  • Software development projects
  • Time-saving bias


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