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Frankfurt School of Finance & Management

Crowd-sourced Predictions

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Description

Behind every informed decision lies a sound prediction. Despite the increasing availability of “big” data and recent advances in algorithmic predictions, the most important strategic decisions still require human judgment. When relevant information is dispersed across people with varying knowledge and expertise, organizations need to address the key questions of crowd-sourced prediction and decision-making:

  • Who are the experts in the crowd?
  • What is the best way to aggregate the experts’ judgments?
  • How can we prevent bias, “gaming,” and groupthink?

This seminar equips the participants with the tools required to answer these questions, allowing them to turn the wisdom of the crowds into superior decisions for the organisation.

Content overview

  • Designing corporate prediction systems
  • Incentivizing effort and truth revelation
  • Recovering truth even if the majority is wrong
  • Identifying experts in a crowd
  • When do algorithms (not) beat intuition?
  • Live simulations to uncover (and fix) human judgment bias
  • Case discussions of real-world prediction systems

Methodology

Case Studies

Who should attend

Managers, Directors

Experts

Mirko Kremer is Professor of Supply Chain Management at the Frankfurt School of Finance & Management since July 2014. He holds a Ph.D. from the University of Mannheim (2008). Before joining Frankfurt School, he was a faculty member at the Pennsylvania State University. His research is on the...
Jens Witkowski is Assistant Professor of Computer Science and Management at the Frankfurt School of Finance & Management. His research focuses on the intersection of data science and economics, with an emphasis on eliciting, aggregating, and evaluating crowd-sourced information. Jens has wor...