Literature DB >> 12858711

Delusions of success. How optimism undermines executives' decisions.

Dan Lovallo1, Daniel Kahneman.   

Abstract

The evidence is disturbingly clear: Most major business initiatives--mergers and acquisitions, capital investments, market entries--fail to ever pay off. Economists would argue that the low success rate reflects a rational assessment of risk, with the returns from a few successes outweighing the losses of many failures. But two distinguished scholars of decision making, Dan Lovallo of the University of New South Wales and Nobel laureate Daniel Kahneman of Princeton University, provide a very different explanation. They show that a combination of cognitive biases (including anchoring and competitor neglect) and organizational pressures lead managers to make overly optimistic forecasts in analyzing proposals for major investments. By exaggerating the likely benefits of a project and ignoring the potential pitfalls, they lead their organizations into initiatives that are doomed to fall well short of expectations. The biases and pressures cannot be escaped, the authors argue, but they can be tempered by applying a very different method of forecasting--one that takes a much more objective "outside view" of an initiative's likely outcome. This outside view, also known as reference-class forecasting, completely ignores the details of the project at hand; instead, it encourages managers to examine the experiences of a class of similar projects, to lay out a rough distribution of outcomes for this reference class, and then to position the current project in that distribution. The outside view is more likely than the inside view to produce accurate forecasts--and much less likely to deliver highly unrealistic ones, the authors say.

Entities:  

Mesh:

Year:  2003        PMID: 12858711

Source DB:  PubMed          Journal:  Harv Bus Rev        ISSN: 0017-8012


  22 in total

1.  N-of-1 Trials in Hypertension Are Feasible, but Are They Worthwhile?

Authors:  Richard L Kravitz
Journal:  J Gen Intern Med       Date:  2019-06       Impact factor: 5.128

Review 2.  Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities.

Authors:  Jessica K Paulus; David M Kent
Journal:  NPJ Digit Med       Date:  2020-07-30

3.  MITIGATING COGNITIVE BIASES IN RISK IDENTIFICATION: Practitioner Checklist for the AEROSPACE SECTOR.

Authors:  Debra L Emmons; Thomas A Mazzuchi; Shahram Sarkani; Curtis E Larsen
Journal:  Def Acquis Res J       Date:  2018-01-01

4.  Confirmation bias in the utilization of others' opinion strength.

Authors:  Andreas Kappes; Ann H Harvey; Terry Lohrenz; P Read Montague; Tali Sharot
Journal:  Nat Neurosci       Date:  2019-12-16       Impact factor: 24.884

5.  Planning and Decision Making for Care Transitions.

Authors:  Silvia Sörensen; Wingyun Mak; Martin Pinquart
Journal:  Annu Rev Gerontol Geriatr       Date:  2011

6.  The structural deficit of the Olympics and the World Cup: Comparing costs against revenues over time.

Authors:  Martin Müller; David Gogishvili; Sven Daniel Wolfe
Journal:  Environ Plan A       Date:  2022-05-31

7.  Clinical decision analysis: Incorporating the evidence with patient preferences.

Authors:  Ilyas S Aleem; Hamza Jalal; Idris S Aleem; Adeel A Sheikh; Mohit Bhandari
Journal:  Patient Prefer Adherence       Date:  2009-11-03       Impact factor: 2.711

8.  Induction with uncertain categories: When do people consider the category alternatives?

Authors:  Brett K Hayes; Ben R Newell
Journal:  Mem Cognit       Date:  2009-09

9.  What is a clinical decision analysis study?

Authors:  Ilyas S Aleem; Emil H Schemitsch; Beate P Hanson
Journal:  Indian J Orthop       Date:  2008-04       Impact factor: 1.251

10.  How dopamine enhances an optimism bias in humans.

Authors:  Tali Sharot; Marc Guitart-Masip; Christoph W Korn; Rumana Chowdhury; Raymond J Dolan
Journal:  Curr Biol       Date:  2012-07-12       Impact factor: 10.834

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.