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
от партнера
Университет Боккони
Программа курса: что вы изучите
Неделя
13 ч. на завершение
THE INNOVATION DECISION
We provide a general discussion of innovation as problem-solving and we link the discuss the building blocks of the scientific approach to innovation decisions – from how to formulate the problem, to how to formulate the hypotheses and the theory, and how to test them. The whole discussion will be framed and applied to concrete managerial problems, including a discussion of the specific managerial tools that facilitate the application of a scientific approach to innovation management.
14 видео ((всего 106 мин.)), 3 материалов для самостоятельного изучения, 1 тест
14 видео
Strategic efficiency4мин
What does the scientific approach do: the Galilean manager5мин
Inkdome case5мин
What is innovation7мин
The structure of the innovation decision15мин
Risk and Uncertainty11мин
Type I and type II errors in innovation decisions6мин
Interactive tour of the Museum of Failure3мин
The Building blocks: Theory, Hypotheses, Tests, Analysis12мин
Formulate and apply theories to managerial problems11мин
Tools: business model canvas and other tools8мин
3 материала для самостоятельного изучения
Readings & Videos10мин
Recap slides10мин
Background material (extended slides)10мин
1 практическое упражнение
Week 110мин
Неделя
24 ч. на завершение
THEORY AND DATA FOR INNOVATION MANAGEMENT
We provide more details about the scientific approach and we introduce probabilities to understand how and why certain decisions lead to some outcomes instead of others and how to make better decisions. We also focus on how to formulate and test hypotheses in practice, and how to interpret these tests. We finally discuss how to design and run experiments. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions
16 видео ((всего 140 мин.)), 3 материалов для самостоятельного изучения, 3 тестов
16 видео
Using the organization to set the decision rule7мин
How to derive hypotheses from a theory6мин
Hypotheses and their context [p values don’t always matter]5мин
Cases4мин
Design and logic of hypothesis testing (download the attached datasets)12мин
The use of experiments in innovation management11мин
Randomized Control Trials7мин
Split and multivariate tests12мин
Quasi Experimental Design6мин
Innovation metrics11мин
Metrics validity and reliability5мин
Metrics validity7мин
Metrics reliability8мин
3 материала для самостоятельного изучения
Readings & Videos10мин
Recap slides10мин
Background material (extended slides)10мин
3 практического упражнения
Exercise 115мин
Exercise 215мин
Week 210мин
Неделя
32 ч. на завершение
DATA ANALYSIS
We cover the basics of data analysis, beginning with the distinction between correlation and causality in the analysis of data. We also teach how to make predictions using regression analysis and link these methods to the scientific approach, showing what role these analyses play, how they help to make scientific decisions and why. We complement this with real examples of companies using data to make innovation decisions. We close by discussing how to interpret these analyses and results critically to make sure we understand what we really learn from the analyses and when, how and why we should interpret our results cautiously and critically.
8 видео ((всего 63 мин.)), 3 материалов для самостоятельного изучения, 1 тест
8 видео
Interview with Mimoto: paving the way for electric mobility using a scientific approach8мин
Interview with Eni Gas and Power: leveraging big data to uncover customer preferences8мин
Using data to answer important questions at Google3мин
How firms and startups can gather and analyze data to test hypotheses6мин
Reflection critical evaluation5мин
3 материала для самостоятельного изучения
Readings & Videos10мин
Recap slides10мин
Background material (extended slides)10мин
1 практическое упражнение
Week 310мин
Неделя
42 ч. на завершение
ADVANCED TOOLS FOR INNOVATION MANAGEMENT DECISIONS
This is s a more advanced part in which we discuss causality and provide the students with some broad exposure to big data and machine learning, and we discuss what they can do for managerial decisions.We provide a general wrap-up and conclusion of the course, including a discussion of when the scientific approach is most appropriate or has limitations. This helps to see when to apply it, or when to apply other approaches, including our own gut feelings. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions
7 видео ((всего 53 мин.)), 3 материалов для самостоятельного изучения, 1 тест
7 видео
Instrumental variables: Examples (download the attached datasets)5мин
Data science vs causal links4мин
Machine learning for innovation management decisions5мин
Summary, conclusions, limitations of the scientific approach8мин
3 материала для самостоятельного изучения
Readings & Videos10мин
Recap slides10мин
Background material (extended slides)10мин
1 практическое упражнение
Week 410мин
Преподаватели
Alfonso Gambardella
Professor of Corporate ManagementManagement and Technology
Arnaldo Camuffo
Professor of Business OrganizationManagement and Technology
Chiara Spina
Lecturer and Ph.D. CandidateManagement and Technology
О Университет Боккони
Our ambition is to develop students' potential and foster knowledge in Business, Economics and Law through innovative learning and research activities in a multicultural environment. Bocconi is a community that constantly innovates teaching and learning technologies and that strongly believes in the power of life-long learning and networking.
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