Insegnamento a.a. 2025-2026

Classes: 27 (II sem.) - 28 (II sem.)

Instructors:
Class 27: ARNALDO CAMUFFO, Class 28: ARNALDO CAMUFFO

This course analyzes strategic decision making under uncertainty and offers a comprehensive introduction to “theory-based” strategy and the application of the scientific approach to strategy and entrepreneurship. The course emphasizes strategic problem identification, framing and formulation and illustrates analytic methods and procedures to do so. It analyzes how Board of Directors, Executives, Managers and Entrepreneurs should articulate their strategic visions using theories, causal logics, probabilistic reasoning and experimentation.

1. Strategic decision making

2. The scientific approach

3. Uncertainty

4. Basic Probabilities

5. Bayesian statistics and learning

6. Typologies of strategic decisions

7. Theory-driven strategic decisions

8. Theories of value and bayesian networks

9. Strategic experimentation: actions versus theories

10. Design of experiments

11. AI-augmented theory-driven startegic decisions

12. Case studies and simulations

At the end of the course student will be able to...

Define strategic decision-making under uncertainty
Understand the impact of data, analytics and AI on strategic decisions.
Classify different types of strategic decisions

Generate, formulate, experiment with and select theories of value for strategic problems

Understand strategy deployment and implementation issues in organizations 

At the end of the course student will be able to...

Use Bayesian statistics for Bayesian and Non-Bayesian learning

Apply graph theory and Bayesian Networks to conceptual causal structures

Build theories-of value for businesses

Design experiments to test “theories-of value”