Bocconi University - A Scientific Approach to Innovation Management
- Offered byCoursera
A Scientific Approach to Innovation Management at Coursera Overview
Duration | 14 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
A Scientific Approach to Innovation Management at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 14 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
A Scientific Approach to Innovation Management at Coursera Course details
- How can innovators understand if their idea is worth developing and pursuing? In this course, we lay out a systematic process to make strategic decisions about innovative product or services that will help entrepreneurs, managers and innovators to avoid common pitfalls. We teach students to assess the feasibility of an innovative idea through problem-framing techniques and rigorous data analysis labelled ?a scientific approach?. The course is highly interactive and includes exercises and real-world applications. We will also show the implications of a scientific approach to innovation management through a wide range of examples and case studies.
A Scientific Approach to Innovation Management at Coursera Curriculum
THE INNOVATION DECISION
Welcome to the course
Operation efficiency vs strategic efficiency
What data can and cannot do
Strategic efficiency
What does the scientific approach do: the Galilean manager
Inkdome case
What is innovation
The structure of the innovation decision
Risk and Uncertainty
Type I and type II errors in innovation decisions
Interactive tour of the Museum of Failure
Antecedents of the Scientific Approach
The Building Blocks: THEED
Formulate and apply theories to managerial problems
Tools: business model canvas and other tools
Readings & Videos
Recap slides
Background material (extended slides)
Week 1
THEORY AND DATA FOR INNOVATION MANAGEMENT
Basic tools: probabilities
Conditional probabilities and the Bayes Theorem
The Scientific Approach: Theory and Mechanisms
Using the organization to set the decision rule
The Scientific Approach: summary and its use in practice
How to derive hypotheses from a theory
Hypotheses and their context [p values don?t always matter]
Cases
Design and logic of hypothesis testing (download the attached datasets)
The use of experiments in innovation management
Randomized Control Trials
Split and multivariate tests
Quasi Experimental Design
Innovation metrics
Metrics validity and reliability
Metrics validity
Metrics reliability
Readings & Videos
Recap slides
Background material (extended slides)
Exercise 1
Exercise 2
Week 2
DATA ANALYSIS
Correlation vs causality
Regression analysis: Theory
Regression analysis: Application
Interview with Mimoto: paving the way for electric mobility using a scientific approach
Interview with Eni Gas and Power: leveraging big data to uncover customer preferences
Using data to answer important questions at Google
How firms and startups can gather and analyze data to test hypotheses
Reflection critical evaluation
Readings & Videos
Recap slides
Background material (extended slides)
Week 3
ADVANCED TOOLS FOR INNOVATION MANAGEMENT DECISIONS
Difference-in-difference approach: Theory (download the attached datasets)
Difference-in-difference approach: Examples (download the attached datasets)
Instrumental variables: Theory (download the attached datasets)
Instrumental variables: Examples (download the attached datasets)
Data science vs causal links
Machine learning for innovation management decisions
Summary, conclusions, limitations of the scientific approach
Readings & Videos
Recap slides
Background material (extended slides)
Week 4
FINAL PROJECT
A Scientific Approach to Innovation Management at Coursera Admission Process
Important Dates
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