Fall semester, Guest lecture
The growing interest in data-driven decision making is due to two developments: (1) the increasing difficulty to maintain a competitive advantage and (2) the wealth of information collected in corporate databases.
People with strong quantitative skills and in particular, data science teams lead those shift towards a data-driven corporate culture. The Harvard Business Review goes as far as declaring the data scientist as the sexiest of the 21st century: “Data scientists are the key to realizing the opportunities presented by big data. They bring structure to it, find compelling patterns in it, and advise executives on the implications for products, processes, and decisions. They find the story buried in the data and communicate it. And they don’t just deliver reports: They get at the questions at the heart of problems and devise creative approaches to them.” (Davenport/Patil 2012)
However, it is still mysterious to many how data-driven decision making actually works in a business, what tools are used for this, and how these insights help to add value to the business.
We demystify data-driven decision making by giving the stage to practitioners with profound experience in applying quantitative skills on a daily basis.
Guest speakers from well-known companies (e.g., Migros, Swiss International Airlines, ABB, Roche, and European Central Bank), who all graduated at the University of Zurich in recent years, will discuss three key questions:
- Which business problems does the firm solve with the help of the data-driven decision making?
- What’s the toolbox that the business relies on for data-driven decision making?
- How to leverage data-driven decision making to redesign business processes?
Prof. Dr. René Algesheimer
Dr. Markus Meierer
MA students, assigned to “Wahlpflichtbereich BWL 4”
Davenport, T. H., & Patil, D. J. (2012). Data scientist: The sexiest Job of the 21st century. Harvard Business Review, 90 (10), pp. 70-76.
Brynjolfsson, E., & McElheran, K. (2016): The Rapid Adoption of Data-Driven Decision-Making. American Economic Review, 106 (5), pp. 133-139.
Kesavan, S., & Kushwaha, T. (2020): Field Experiment on the Profit Implications of Merchants’ Discretionary Power to Override Data-Driven Decision-Making Tools, Management Science, 66 (11), pp. 5182-5190.
Don’t forget to officially register yourself using the registration tools at the University of Zurich.
The information in the website or syllabus supports the official information in the electronic university calendar (VVZ – Vorlesungsverzeichnis). In case of doubt, the official information at the VVZ is valid.