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How is Decision Intel different from ChatGPT or a general AI assistant?

ChatGPT gives one opinion from one model: ungoverned, untraceable, unaudited. Decision Intel is the reasoning audit platform. Most tools audit your data; we audit your reasoning — and catch the fatal blind spots in strategic memos before the committee does. It measures the noise in your reasoning the same way Kahneman did in the insurance underwriter study, simulates an AI boardroom of CEO, CFO, and board personas, runs what-if interventions against a 143-case public reference library, and compounds every confirmed outcome back into a calibrated Decision Quality Index your audit committee can defend. Not a chatbot; a reasoning audit, checkable from memo to outcome.

Which cognitive biases caused Mylan N.V.'s failure?

5 bias patterns are documented in this case, led by Anchoring Bias. The full set: Anchoring Bias, Loss Aversion, Status Quo Bias, Hindsight Bias, Framing Effect. Each is mapped to Decision Intel's 22-bias R²F taxonomy with stable IDs and academic citations.

What is Decision Intel's reasoning audit?

Decision Intel runs a 12-node Recognition-Rigor Framework (R²F) pipeline on strategic memos, detecting cognitive biases from a 22-bias canonical taxonomy and producing a Decision Quality Index (DQI) score. The audit produces a hashed, tamper-evident Decision Provenance Record (DPR) suitable for audit-committee review.

All case studies

FailureHealthcare2016

Mylan N.V.

Mylan EpiPen Pricing Scandal

Estimated impact: $465M DOJ settlement; market share loss to generics

F33

Decision Quality Index (simulated)

Critical · 5 biases detected, 1 toxic combinations

Mylan raised the price of the EpiPen from $57 to $609 (a 400%+ increase) over eight years while CEO Heather Bresch's compensation grew to $19M. The pricing exploited the product's life-saving monopoly status and lack of generic alternatives.

Decision context

Whether to continue systematic annual price increases on a life-saving product with no therapeutic alternatives, and whether the pricing strategy was sustainable politically and commercially.

Decision anatomy

Monetary stakes

Very high

Dissent suppressed

Yes

Time pressure

None

Unanimous consensus

Yes

Decision participants

Dissent encouraged

External advisors

Iterative process

Red = risk factor present · Green = protective factor present

Deep hindsight-stripped analysis coming soon. This case is part of our ongoing backfill to reconstruct what the platform would have flagged at decision time. The summary and bias profile below are drawn from primary sources.

Biases present in the decision

★Anchoring Bias

critical

Loss Aversion

medium

Status Quo Bias

medium

Hindsight Bias

medium

Framing Effect

medium

★ Primary driver · Severity estimated from bias type and decision outcome

3D Decision Knowledge Graph

Mylan N.V. · 5 biases, 1 toxic combination

Drag to rotate · Scroll to zoom · Click to explore

Decision

Critical

High

Medium

Toxic

Bias Intensity Profile

Severity × confidence across 5 detected biases

Toxic combinations

!Status Quo Lock

Loss aversion combined with status quo bias makes even clearly beneficial change feel impossible.

Reference class base rates

Across all 143 curated case studies in our library:

89%

base failure rate

-0%

partial / mixed

11%

base success rate

■ Failure■ Partial■ Success

Lessons learned

Anchoring to annual price increase percentages rather than absolute cost to patients created a trajectory that became politically unsustainable
Loss aversion: once high prices were embedded in revenue forecasts, any reduction felt like a loss rather than normalization
Hindsight bias: the pricing was publicly available for years before it became a political issue — the risk was always present

Source: U.S. Senate Special Committee on Aging hearing (2016); DOJ settlement (2017) (News Investigation)

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Workflows that fire on decisions like Mylan N.V.’s

The same Recognition-Rigor Framework that documents this case audits memos in the same shape — before the outcome forces the lesson.

For CSOs and Heads of Strategic Planning

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Lessons learned

Anchoring to annual price increase percentages rather than absolute cost to patients created a trajectory that became politically unsustainable

Loss aversion: once high prices were embedded in revenue forecasts, any reduction felt like a loss rather than normalization

Hindsight bias: the pricing was publicly available for years before it became a political issue — the risk was always present