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Center for Decisions, Models, and Data

Models enable us to comprehend the world, infer beyond the data, and ultimately make better decisions.

The DMD center enables interdisciplinary research on models, be they mathematical representations, mental models, or other frameworks, to help leaders and their organizations better interpret data, uncover new possibilities and improve their decision making. Our approach draws from fields as diverse as data science, analytics, cognitive psychology, sociology, and economics.

The abundance of data and the increasing adoption of intelligent machines raise questions about the future role of human-based decisions in organizations. At the same time, the profound crises the world is experiencing today have highlighted the limits of data-driven predictions and the need to decide even when data are scarce.  

The DMD center is based on the fundamental premise that human decision makers are most effective when they properly leverage their unique ability to model and represent the world. These models enable inferences beyond the data and reveal new courses of action in a way that machines cannot.  The DMD center explores how individuals and organizations can create and apply better models, and how data-driven technologies complement – or hinder – humans’ ability to represent.

Core areas

Human decisions in the age of artificial intelligence

Deciding under data scarcity, leading into the unknown

Governance and responsible analytics

Disruptive models and open innovations

Steering committee

Francis de Véricourt

Professor of Management Science and President's Chair, ESMT Berlin

Center for Decisions, Models, and Data (DMD-Center) 


Gianluca Carnabuci

Professor of Organizational Behavior and Ingrid and Manfred Gentz Chair in Business and Society




Henry Sauermann

Professor of Strategy, POK Pühringer PS Chair in Entrepreneurship



Feedback in the digital age: When do people trust machine-generated feedback more than feedback provided by humans? 

Gianluca Carnabuci

Linus Dahlander

Do machine-based prescriptions affect the mental mindset of decision makers? 

Francis  de Véricourt

Martin Schweinsberg

Human and machine: The impact of machine input on decision making under limited attention 

Caner Canyakmaz

Tamer Boyaci

Francis  de Véricourt


People analytics in the digital age: Modeling men’s and women’s career paths through machine learning

Jan Nimczik

Gianluca Carnabuci

Min Liu

Selected publications

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

Published (2021): Organizational Behavior and Human Decision Processes 165: 228–249

Author(s): Martin Schweinsberg, Michael Feldman, Nicola Staub et al.

Contracting, pricing, and data collection under the AI flywheel effect

Published (2020): ESMT Working Paper No. 20-01 (R1)

Author(s): Francis de Véricourt and Huseyin Gurkan

Search under accumulated pressure

Forthcoming: Operations Research

Author(s): Saed Alizamir, Francis de Véricourt, and Peng Sun

Warning against recurring risks: An information design approach

Published (2020): Management Science 66 (10): 4359–4919
2018 HOCM Best Paper Award

Author(s): Saed Alizamir, Francis de Véricourt, and Shouqiang Wang

Division of labor in collaborative knowledge production: The role of team size and interdisciplinarity

Published (2020): Research Policy 49 (6): 103987

Author(s): Carolin Haeussler and Henry Sauermann

Emergent leadership structures in informal groups: A dynamic, cognitively informed network model

Published (2018): Organization Science 29 (1): 118–133

Gianluca Carnabuci, Cécile Emery, and David Brinberg

Get in touch

Schloßpl. 1, 10178 Berlin, Germany


Center for Decisions, Models, and Data

Diverse ideas that empower
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