Decision-Making Using Data

Organizations make hundreds of decisions each day. To improve decision quality, organizations store and analyze vast amounts of data. Nevertheless, many executives say their data analytics initiatives produce disappointing results. It doesn’t have to be this way. Data alone is no guarantee for making successful decisions. Organizations need Decision Intelligence, a key ingredient to better connect decisions to data.

Program Objectives

The goal of this program is to provide participants with the insights, tools, and frameworks that are necessary to increase their organizations’ Decision Intelligence.

Demystify intelligence

• What are the fundamental building blocks of intelligence?
• How does human intelligence differ from artificial intelligence?
• How can organizations leverage the strengths of humans and machines?
• What does it mean to make "rational" decisions?
• What is Quantitative Intuition?

Foster intellectual humility

• What is the difference between knowledge and meta-knowledge?
• Why do organizations need a meta-cognitive revolution?
• How does egocentrism interfere with effective decision-making?
• Is it possible to manage uncertainty with confidence?

Lead with decision-driven data analytics

• Why do data-driven decisions so often miss the mark?
• What is the difference between causal-inference and pure-prediction problems?
• How can organizations balance earning and learning in a VUCA world?
• What should be the role of decision-makers versus data analysts?
• How can I better communicate with data analysts?

Analyse and improve decision-making processes

• Who needs to make which decision?
• What is the difference between noise and bias?
• How can organizations use machines to reduce noise and bias?

Regardless of the setting, managerial decisions are necessarily made under conditions of uncertainty. In order to make informed decisions under uncertainty, managers must learn to analyze and understand data concerning relevant variables and relationships and to make inferences and predictions on the basis of such data.

• Leadership
• Decision Making
• Risk Management
• Data-analysis

• Case studies
• Real life examples

Participants will earn a certificate issued by the Luxembourg School of Business.Our school is accredited by the Ministry of Education and member of AACSB (global business education network and association).

Professor

Bart de Langhe is a multidisciplinary expert in behavioral, cognitive, and data science. He obtained bachelor, master, and doctorate degrees in Psychology and Business at KU Leuven (Belgium) and Erasmus University Rotterdam (the Netherlands). Before joining ESADE as a marketing professor in 2017, Bart was on the faculty for six years at the University of Colorado at Boulder (USA). Bart has published numerous articles in leading academic journals, such as Management Science, Journal of Marketing Research, or Journal of Consumer Research. He also writes regularly for managerial outlets such as Harvard Business Review or MIT Sloan Management Review. Bart’s teaching and consulting focus on improving executive decision-making and the development of customer-centric marketing strategies.