
Framework Overload: Managing Mental Models Effectively
Analyze framework overload and its effects on decision-making, emphasizing the importance of applied knowledge.
What has been corrected on this page?
Every accepted correction to this page is recorded with the exact change, so readers can see how the page improved over time.
-
Removed five unverifiable, apparently unverified studies (attributed to Potocnik/Edinburgh, Graber/SUNY, Finkelstein/Dartmouth, a 2022 McKinsey survey of 750 tech companies, and a 1984 GM/McKinsey study) that carried specific institutions, sample sizes and statistics with no locatable citation. Replaced each with general, source-free statements of the same qualitative point.
What the page claimedThe article cited a 2018 Potocnik study (14 firms), a 2015 Graber study (583 diagnostic errors), a 2020 Finkelstein study (45 companies, 62% vs 38%), a 2022 McKinsey survey (750 technology companies, 67%), and a 1984 GM/McKinsey study (35% of managers' time), each with precise figures but no verifiable source.
What was correctedRemoved the unverified attributions and unverified statistics; retained the qualitative claim (beyond a moderate framework repertoire, added frameworks stop improving and can degrade decision quality) as general, unattributed statements. Retained the genuinely documented history (Mintzberg's Rise and Fall of Strategic Planning, 1960s-70s corporate planning systems, GM/Sloan/Toyota).
Why: These studies could not be verified in any database or the cited journals and carry the signature of unverified AI-generated citations (specific institution + sample + result, no retrievable source). Editorial policy is to remove unverified sources rather than substitute new ones.
View the full record →
Who checked this page?
1 contributor has checked "Framework Overload: Managing Mental Models Effectively" on When Notes Fly. Each name below links to that person's public CitePep profile, where every contribution they have made is listed with the exact change they proposed.