Data-driven decision making, potentials and risks for Project Managers

Good project management is an important support for decision-making in the management of an organization. Today, there is a trend in having transparent and objective decision-making procedures, often based on some calculations like in risk assessment for project prioritization. These methods sound very attractive and have indeed a real potential, but they can also reveal a kind of fake objectivity. Based on real data science projects realized for a large Swiss electricity network supplier and an international food industry machine producer, the potential and limitations of data-driven decision-making will be presented. This will also include some hints and suggestions for project managers and the whole management on how to avoid misleading conclusions.

Our Speaker:

Rodolphe Dewarrat

After studying mathematics and chemistry at the University of Fribourg, Rodolphe Dewarrat was a collaborator of the University of Cambridge during a PostDoc in electronics engineering. His interests in interdisciplinary projects brought him to data science – out of which his own company imsd.ch emerged, and to project management in a long term collaboration with Carine Galli, founder of cubisma.ch.

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