Tue. Jan. 15th [Deck] - Intro to the course and its activities
- Explore this web site. What do you think Digital Innovation is? And - just as important - why is that important to you and your career? Bring your questions about the course (if any) to class.
Thu. Jan. 17th [Deck] - Innovation cycles: Moore's and Gartner's
- Read: Darwin and the Demon: Innovating Within Established Enterprises. In the DigiLibrary. Find alternative ways to access the readings if you cannot get to the Digilibrary.
- Read: Gartner (2018). Understanding Gartner’s Hype Cycles. Read the first 12 pages. In the DigiLibrary.
- Treasure hunt: see if you can find find the 2018 Hype Cycle (HC) for Emerging Technologies, from the Gartner database (not the pdf in the digilibrary). Just take a pic of it with your phone. Try the interactive features of the HC.
Tue. Jan. 22nd [Deck] - Disruption: theory and practice
- Read: What is disruptive innovation? In the DigiLibrary. Find alternative ways to access the readings if you cannot get to the Digilibrary.
- Read: J. Gans (2016). The disruption dilemma. Medium.com
Thu. Jan. 24th [Deck] - Value creation and capture
- Watch: How to design, test and build business models
canvasses (BMCs). Osterwalder is the inventor of the BMC. Osterwalder demonstrate how to apply the BMC to Nespresso.
In class we will apply to other companies.
In class, you might be asked to 1) explain what the components of a BMC are; 2) apply them to a specific business case.
- Read: Create more value. In the DigiLibrary. Pay particular attention to the table describing how a business model can be changed to capture more value. Make sure that you understand the various techniques described in the table.
Tue. Jan. 29th [Deck] - Cloud computing
- Read: What every CEO needs to know about the cloud. In the DigiLibrary. Be prepared to give a clear answer to the questions: what is the cloud, exactly? Why should business management care?
- Read: How cloud computing is changing management. An update to the McAfee piece.
Thu. Jan. 31th [Deck - joint with previous] - Cloud computing
I felt that discussion on Tue did not clarify sufficiently what cloud computing is for everyone in class (my fault). So, I want to take a step back and revisit the topic, which is critical to understand modern digital innovation. The following links contain alternative definitions of cloud computing by the main vendors. Rater than focusing on subtle differences, come up with your own understanding of what the cloud/cloud computing is. Find examples of computing that is not cloud computing. If anything is not clear - write down a few questions and in class we will try to answer them.
- Watch: What is cloud computing? - by Salesforce. Non-technical, emphasis on business benefits
- Watch: What is the cloud? as fast as possible (only first 4 minutes)
- Read: What is cloud computing? A beginner’s guide - Microsoft Azure (just this first web page)
- Read and watch: What is cloud computing? Amazon Web Services (AWS). Read only the first page
- Read: What Do You Do When Employees Start Using a Free Cloud Service?
Tue. Feb. 5th [Deck] - Artificial Intelligence.
- Read: McCarthy J. (2007). What is AI? / Basic Questions, where Prof. McCarthy, the founder of modern AI, answers the most commonly asked questions about the discipline. Skip the last Q&A.
- Read: Artificial intelligence for the real world. In the DigiLibrary.
- Search and post: find a *cool* video on a real world AI application, classify it as an example of the three kinds identified by Davenport, and post the link to S:\Grazioli\DIGITAL INNOVATION COMM4250\AI videos. Name the link "yourlastname-AI app name/type" e.g., grazioli-Amazon chatbot.
Thu. Feb. 7th [Deck] - Machine Learning.
- Read: The Business of Artificial Intelligence. In the DigiLibrary.
- Read: An Executive guide to AI. Find and explore the major types of machine learning.
Tue. Feb. 12th [Deck] - Deep learning: Neural Networks.
- Watch: But what is a neural network? This is the best video that I could find in terms of striking a balance between being rigorous and relatively accessible. What you will see is that machine learning gets very mathematical very quickly. Hang on! Try to develop some intuition about neural nets and what they really are, and bring to class some questions.
- Watch: Watson visual recognition. This short video describes one deep learning algorithm offered by IBM Watson.
- Read: Autoglass bodyrepair. This case study describes how an insurance business used deep learning.
Thu. Feb. 14th [Deck] - AI Risks and Opportunities
- Read: How to stop computers being biased. If you have trouble navigating the link, try the the DigiLibrary.
- Read: How Health Care Changes When Algorithms Start Making Diagnoses. If you have trouble navigating the link, try the DigiLibrary.
- Read: How Health Care Changes When Algorithms Start Making Diagnoses. In the DigiLibrary.
Tue. Feb. 19th [Deck] - The Internet of things
- Read: Digital Ubiquity. In the DigiLibrary.
- Read: How smart connected products are transforming companies. In the DigiLibrary.
These two readings are rather heavy. Lots of details, examples and companies. Do not get lost in the details. Try to extract the big ideas. The good news is that these readings count for both Tuesday and Thursday.
Tue. Feb. 21th  - The Internet of things
- Same readings as assigned for the previous meeting.