The University of Southampton
University of Southampton Institutional Repository

Fast-and-frugal heuristics: analytical models of intuition

Fast-and-frugal heuristics: analytical models of intuition
Fast-and-frugal heuristics: analytical models of intuition
Trust your gut. Do not rely on urges—analyze! Decisions are either logical or psychological… Such popular maxims reveal a complicated, even confused approach to how one should make decisions. The sciences of decision theory and practice suggest that managers should leverage the power of mathematics, whilst also reserving a role for personal insights. But how exactly can that be achieved? Combining analysis and intuition sounds like trying to have one’s cake and eat it too; enticing but impossible. We believe that it is indeed possible to combine analysis and intuition to make decisions. And that doing so in a systematic way is now within reach. A slow yet powerful series of discoveries has culminated in a vision of decision making that brings ever closer together mathematics, psychology and management in the form of analytical models of intuition. The concept that enables these advances is fast-and-frugal heuristics. The present piece (i) provides a background for fast-and-frugal heuristics; (ii) introduces their basics, outlining conditions under which fast-and-frugal heuristics perform well or not; (iii) challenges established beliefs and clears common misconceptions related to fast-and-frugal heuristics; (iv) outlines principles of smart (heuristics-based) management; and (v) surveys open questions to explore how the potential of fast-and-frugal heuristics for management mathematics can be fully realized.
1471-678X
Katsikopoulos, Konstantinos V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba
Gigerenzer, Gerd
95655620-31f2-44ef-bdd6-ddbc5f175b08
Katsikopoulos, Konstantinos V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba
Gigerenzer, Gerd
95655620-31f2-44ef-bdd6-ddbc5f175b08

Katsikopoulos, Konstantinos V. and Gigerenzer, Gerd (2025) Fast-and-frugal heuristics: analytical models of intuition. IMA Journal of Management Mathematics, [dpaf041]. (doi:10.1093/imaman/dpaf041).

Record type: Editorial

Abstract

Trust your gut. Do not rely on urges—analyze! Decisions are either logical or psychological… Such popular maxims reveal a complicated, even confused approach to how one should make decisions. The sciences of decision theory and practice suggest that managers should leverage the power of mathematics, whilst also reserving a role for personal insights. But how exactly can that be achieved? Combining analysis and intuition sounds like trying to have one’s cake and eat it too; enticing but impossible. We believe that it is indeed possible to combine analysis and intuition to make decisions. And that doing so in a systematic way is now within reach. A slow yet powerful series of discoveries has culminated in a vision of decision making that brings ever closer together mathematics, psychology and management in the form of analytical models of intuition. The concept that enables these advances is fast-and-frugal heuristics. The present piece (i) provides a background for fast-and-frugal heuristics; (ii) introduces their basics, outlining conditions under which fast-and-frugal heuristics perform well or not; (iii) challenges established beliefs and clears common misconceptions related to fast-and-frugal heuristics; (iv) outlines principles of smart (heuristics-based) management; and (v) surveys open questions to explore how the potential of fast-and-frugal heuristics for management mathematics can be fully realized.

Text
I-Ma-Man_KKGG - Accepted Manuscript
Restricted to Repository staff only until 21 October 2026.
Request a copy

More information

Accepted/In Press date: 13 October 2025
e-pub ahead of print date: 21 October 2025
Published date: 12 November 2025

Identifiers

Local EPrints ID: 506850
URI: http://eprints.soton.ac.uk/id/eprint/506850
ISSN: 1471-678X
PURE UUID: 97749227-1505-482e-892a-a219c952bcd8
ORCID for Konstantinos V. Katsikopoulos: ORCID iD orcid.org/0000-0002-9572-1980

Catalogue record

Date deposited: 19 Nov 2025 17:32
Last modified: 20 Nov 2025 02:49

Export record

Altmetrics

Contributors

Author: Gerd Gigerenzer

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×