Decision-Making and Risk Biases

Zero sum bias

Zero-sum bias is assuming that another person's or group's gain must come at your expense, even when the situation can create value for more than one side.

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Mechanism

How it works

Competition is vivid and many resources are genuinely scarce, so a fixed-pie model is easy to apply. It becomes misleading when productivity, trade, cooperation, innovation, or future growth can change the size or distribution of what is available.

Examples

Where it shows up

  • A team treats another team's automation gain as a threat rather than asking whether it frees capacity for shared work or better service.
  • A negotiation begins with dividing a fixed budget while ignoring changes to scope, timing, risk, or future revenue that could improve both sides' outcomes.
  • A country treats all trade gains elsewhere as its own loss without examining comparative advantage, prices, or overall welfare.
Consequences

What it can distort

  • People reject cooperation, oppose mutual gains, and frame solvable coordination problems as identity conflicts.
  • Leaders may miss distributional questions by pretending every gain is shared—or miss joint gains by pretending every gain is theft.
Countermeasures

How to work around it

  • Map what is fixed, what can grow, and who bears costs or captures gains. Look for value-creating trades before negotiating division.
  • Do not sell 'win-win' as a slogan: make the mechanisms, trade-offs, and distribution explicit.
Caveats

Critiques and limits

Many situations are genuinely zero-sum in the short term: one job opening, one seat, or a fixed pot of money. The bias is applying that structure where evidence supports a more complex or expandable system.

Taxonomy

Fields of impact

Psychology & Social Science
Economics & Finance
Political Science & Public Policy
Evidence

How solid is the research?

Mixed — real but conditional

Research finds fixed-pie perceptions in intergroup, economic, and social judgments, but their accuracy depends on the resource, time horizon, and institutional setting.

Research

Relevant papers

Zero-sum bias: Perceived competition despite unlimited resources

Meegan, D. V. (2010)

Frontiers in Psychology, 1, 191

Belief in a zero-sum game as a social axiom: A 37-nation study

Różycka-Tran, J., Boski, P., & Wojciszke, B. (2015)

Journal of Cross-Cultural Psychology, 46(4), 525-548

Case studies

Real-world patterns.

Real-world examples showing how Zero sum bias manifests in practice

Case study

Siloed Investments: How Zero‑Sum Thinking Let a SaaS Company Lose Revenue and Duplicate Costs

A real-world example of Zero sum bias in action

Context

A mid‑sized SaaS company (≈ $25M ARR) with regional account teams and decentralized budgets was evaluating an investment in a single, centralized customer success platform expected to improve renewals and onboarding speed. Leadership framed the decision as a choice between teams — if one region got a central tool, other regions would 'lose' budget and influence.

Situation

The product and operations leads proposed a $250k integration and training project to unify CRM, onboarding playbooks, and usage analytics across all account teams. Regional managers pushed back, insisting each team should keep its own tools and budget because shared investment would reduce their local headcount or control.

The bias in action

Decision‑makers treated the budget as a fixed pie: a gain for central operations was portrayed as a loss for regional teams. Instead of piloting the centralized platform, leadership approved small, independent tool purchases for each region and cut the central project. Managers hoarded data and resisted cross‑team processes, reinforcing the belief that resources were zero‑sum. The company overlooked that a unified platform could create efficiencies and revenue growth that would expand the pie for everyone.

Outcome

Over the next nine months the company experienced higher churn and slower new‑customer conversion than forecast. Each region bought similar point solutions (duplicate spend), integration efforts stalled, and customer success metrics fragmented — making it harder to scale best practices company‑wide.

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Related biases

Nearby patterns.

Social comparison bias

Social comparison bias is devaluing or avoiding people who threaten our relative status, especially when we control an opportunity they could receive.

Loss aversion

Loss aversion is the tendency for a loss to hurt more than an equivalent gain feels good.

Out-group homogeneity bias

Out-group homogeneity bias is seeing members of another group as more alike than members of our own group: 'they are all the same; we are a collection of individuals.' Distance hides variation while familiarity makes it visible..

In-group bias

In-group bias is favoring people we see as 'us' over people we see as 'them,' even when group membership is arbitrary and the evidence about individuals is equivalent.

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Entry last reviewed 2026-07-19 · sources verified against the published literature — methodology

Zero sum bias - The Bias Codex