Project and product decisions

The decision question

How can a team review a project or product choice without letting outcomes or past investment rewrite the decision?

Reviewed lenses

• Escalation of Commitment – when setbacks lead to more investment in the same course — Sunk-cost effects and escalation of commitment overlap but are not interchangeable. Sunk-cost research asks whether irrecoverable prior investments influence current choices. Escalation of commitment describes persistence or additional resource allocation to a failing course of action and can also be driven by personal responsibility, self-justification, project structure, and other factors.
• Loss Aversion – when a loss can carry more weight than an equivalent gain — Loss aversion is a central component of prospect theory and many studies estimate losses as receiving greater subjective weight than gains around a reference point. However, the effect should not be summarized with one universal coefficient. A 2024 interdisciplinary meta-analysis of 607 estimates reported a mean coefficient near 1.96, while another 2024 meta-analysis of individual risky-choice datasets estimated about 1.31. A 2025 re-analysis of the larger dataset found little evidence of loss aversion in some symmetric, unordered designs, showing that task structure and analysis can materially change the result.
• Sunk Cost Effect – when past costs influence the next choice — The sunk cost effect is a documented tendency for irrecoverable prior investments of money, time, or effort to influence later choices. A meta-analytic review found clear evidence for the effect overall, while also showing that its size and moderators differ between utilization decisions and progress decisions. The effect should not be used to label every choice to continue: future value, switching costs, uncertainty, and how close a project is to useful completion can all be relevant to a forward-looking decision.
• Curse of Knowledge – when what you know distorts what you expect others to know — Knowing more can make it harder to estimate what a less-informed person knows or understands, but the size and mechanism of the effect depend on the task. The useful claim is not that experts are unable to teach beginners; it is that one's own knowledge can contaminate judgments about another person's knowledge unless the perspective gap is made explicit.
• Decoy Effect – when an inferior option changes the comparison between better options — The decoy effect is a well-documented family of context effects in which adding an inferior or otherwise strategically positioned alternative can change choice shares among the original options. The classic attraction effect uses an asymmetrically dominated decoy that is worse than the target but not necessarily worse than the competitor. The effect is not guaranteed: its size depends on the geometry of the options, prior preferences, task design and other moderators, and preregistered replications have found both successful and weak or null results.
• Availability Heuristic – when easy-to-recall examples shape frequency judgments — Availability is a judgment heuristic: people can use how easily examples or scenarios come to mind when estimating frequency or probability. That shortcut is not automatically an error because memorable or accessible examples can correlate with real frequency. Bias appears when accessibility is driven by factors that are not diagnostic of the quantity being judged.
• Confirmation Bias – when a belief shapes how evidence is searched and judged — Confirmation bias is an umbrella label for several ways existing beliefs or hypotheses can influence information search and interpretation. It should not be reduced to one behaviour such as reading only agreeable news, and a preference for confirming tests is not irrational in every task or environment.
• Conservatism Bias – when a probability estimate changes too little — Here, conservatism means under-updating: new evidence changes a probability judgment less than a Bayesian benchmark would predict. It should not be confused with the separate memory phenomenon in this corpus that pulls remembered extreme values toward the middle.
• Default Effect – when a pre-selected option changes what people choose — Pre-selecting an option often increases the chance that people choose it, but the size of the default effect varies greatly across domains and designs. A 2019 meta-analysis of 58 studies found a substantial average effect together with strong heterogeneity, including some studies with little or even reversed effects. Staying with a default should therefore not be treated as a direct measure of strong preference or as proof that the default improved welfare.
• Framing Effect – when equivalent descriptions lead to different choices — Framing research covers several distinct paradigms. Risky-choice framing, where equivalent outcomes are presented as gains or losses, is a well-established effect with substantial evidence across many studies. A classic meta-analysis found a reliable small-to-moderate average effect with strong variation across designs, and later reviews and metastudies support broad generalizability. Attribute framing also has supporting evidence, while goal or message framing is less consistently established. These should not be treated as one identical effect caused by any change in wording.

Decision guides

• Work & project decisions
• Forecasting & future choices
• AI-assisted decisions
• Project estimation & delivery
• Checking claims & misinformation
• Comparing plans & pricing
• Defaults, settings & choice architecture
• Presenting risk & options
• Reviewing KPIs & proxy metrics
• Continue, change, or stop a project

How to use this page

Start with the decision, not with a label for a person. Open the evidence behind the lenses that fit, compare nearby concepts when needed, and keep uncertainty visible.