Matthias Seifert, professor of quantitative methods at IE Business School
Matthias Seifert, professor of quantitative methods at IE Business School has chosen to define the term 'intuition'

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Matthias Seifert is professor of quantitative methods in the operations and technology area at IE Business School. He teaches modules on managerial decision making and advanced quantitative methods in the MBA, Global MBA, PhD, DBA and executive education programmes. Before joining IE, he spent most of his academic life researching and teaching in the UK, where he was affiliated to Cambridge university, the London School of Economics and London Business School.

Prof Seifert is a specialist in the decision sciences. In his research he uses both behavioural experiments and mathematical modelling approaches to study individual and collective decision-making behaviour at times of uncertainty. In particular, his current work addresses questions surrounding the role of cognition in managerial forecasting, risk-taking behaviour following near-miss events as well as the performance of crowd wisdom in complex choice environments.

In the past, he has received the EFMD/Emerald Outstanding Doctoral Research Award, the Toby Jackman Prize for the most outstanding dissertation in any discipline awarded by St Edmund’s College, Cambridge university, as well as various other research awards granted by institutions in Germany, the US, Spain and the UK. Prof Seifert sits on the editorial board of decision analysis published by Informs and his work has appeared in top journals such as Organisational Behaviour and Human Decision Processes, Harvard Business Review and MIT Sloan Management Review, among others. He is also an active member of the Decision Analysis Society (DAS), where he frequently writes about local decision sciences communities around the world.

Prof Seifert has chosen to define the term “intuition”.

Why Prof Seifert thinks that understanding intuition is important

Business forecasts are often based on a combination of statistical model prediction and managerial intuition, explains Prof Seifert. “While the strength of statistical models lies in exploiting information in a rigorous and consistent manner, it would be risky to blindly trust them. Models are only as good as the quality of the data that was fed into them and they typically fail to efficiently account for anomalies in the data,” he says.

“However, where the model fails, managerial intuition can add significant value,” Prof Seifert says, adding that experts rely on their intuition to process new information and adjust model forecasts and are therefore able to improve predictive accuracy.

To view a full definition of what Prof Seifert means when he uses the term intuition, click on the linked term.

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