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SDA Bocconi School of Management

Strategic Innovation in the Digital Era

Nov 11—14, 2019
3 days
Milano, Italy
EUR 3900 ≈USD 4391
EUR 1300 per day

How it works

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Description

How do managers decide whether to spend resources to launch an innovation or simply a new project? This is a common managerial problem, faced by any manager. Predicting the outcomes of these decisions is crucial because wrong or right predictions make the difference between successful and unsuccessful projects. The objective of this course is to explain how to use data to make these predictions. This is an important opportunity due to the wide availability of data for managerial decisions raised by the digital revolution. Most often, data presentations and related exercises do not provide good information to the decision-maker because of a lack of effective analyses and interpretations. The course first explains how to frame the problem, and how to formulate hypotheses to predict the outcome of these decisions. It then provides the tools to analyze and interpret the data to support or contradict these predictions, which helps to make better decisions. An important part of the course is practical sessions in which participants use and analyze real data to address concrete managerial problems.

Contents

How can managers make good decisions?

  • Biases, fallacies, and the most common pitfalls in managerial decisions
  • Kannheman’s thinking fast and slow
  • A simple representation of the decision-making process for innovation, start-ups or new projects

A scientific method for managerial and innovation decisions

  • The notion of a “scientific” approach to managerial decisions
  • Rising managerial approaches to decision-making under uncertainty
    • Design Thinking
    • Discovery by Design
    • Real Options
    • Entrepreneurial Experimentation
    • The Lean Start-up Method

Basic tools for analyzing and interpreting managerial and innovation data

  • Random variables, probabilities, distributions
  • Escaping false positives and false negatives in managerial and innovation decisions
  • Correlation vs causality in managerial and innovation decisions
  • Using regression analysis to interpret managerial and innovation data
  • Practical session

Running experiments in your organization

  • Causality in data analysis
  • How to set an experiment and A/B tests
  • Difference-in-difference analyses
  • Practical session

Big data, artificial intelligence and machine learning for managerial and innovation decisions

  • What big data, artificial intelligence and machine learning can do for managerial decision-makings
  • Examples of the use of big data, artificial intelligence and machine learning (pattern recognition, predictions)
  • Practical session

Concluding observations

  • Understanding what data (big or small) can or cannot do for managerial decision-making:
    • Can do: operational efficiency (exploiting data and information to understand how the world is)
    • Cannot do: create innovations (imagine how the world could be)

Who should attend

The audience for the course is middle managers in medium-large firms, as well as entrepreneurs or managers in start-ups or small firms. The course is equally valuable to managers in non-profit organizations, governmental institutions, or any similar institution or organization. The course requires no background in mathematics or statistics. All relevant notions or methods will be explained from very basic concepts. The course will improve the ability for any decision-maker, including those with limited knowledge of data analysis, to make informed decisions using data.

Experts

Curriculum Vitae Professor of Leadership, Organization and Human Resources Degree in Business Administration, University "Ca'' Foscari" of Venice, Italy, 1985 Ph.D. in Business Administration, University "Ca'' Foscari" of Venice, Italy, 1990 Academic position and/or Professional activities F...
Professor of Management and Head of the Department of Management and Technology. I study firm strategy, particularly technology strategy and the impact of innovation on industry structures. I published on national and international journals. My best known book is Markets for Technology (2001, MIT...
Curriculum Vitae Duke University: Fuqua School of Business Ph.D. Business Administration, StrategyMay 2013 Dartmouth College: Thayer School of Engineering M.E.M. Engineering ManagementJune 2007 B.E. Environmental EngineeringJune 2006 Colby College B.A. Computer Science and Mathematical Sci...

Next dates

Nov 11—14, 2019
3 days
Milano, Italy
EUR 3900 ≈USD 4391
EUR 1300 per day

How it works

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