1.1 Problem definition
- Test your understanding: In the bank example, why was it important to create a database of customer phone numbers?
- Explore: In your own experience, what’s an example of an early project that helped your team build credibility?
1.2 Use case prioritization
- Test your understanding: Why did the insurance company business unit choose the path of having a small team use inexpensive tools to pursue quick, actionable wins instead of launching a large, formal analytics program?
- Explore: In your own experience, what have been the practical obstacles to launching “food truck”–type programs?
1.3 Business intelligence
- Test your understanding: Why do middle managers inside business units sometimes resist projects aimed at creating automated business-intelligence dashboards?
- Explore: What outcomes would you expect to see in companies that neglect to build a common set of management dashboards?
1.4 Cross-industry borrowing
- Test your understanding: According to this section, what did telecom companies learn from credit-card issuers in the early 2000s that helped improve their performance?
- Explore: What’s an example of an insight you have learned about your industry that you believe would be useful to apply in a different industry?
1.5 Alternative data
- Test your understanding: What’s an example of a benefit that a company might gain from using “alternative data” from the investment world, such as anonymized credit-card transaction data?
- Explore: What kinds of companies would benefit the most from using alternative data? For example, do you think using alternative data requires a large number of data scientists, a large number of customers, an experimental culture, other?
1.6 Scaling up innovations
- Test your understanding: According to this section, what factors determine whether an idea will successfully spread throughout a network?
- Explore: The author says, “Stay close enough to your external network to know what’s going on, but far enough away that you’re pursuing a differentiated strategy that plays to your company’s unique strengths and data assets.” In your industry, what’s a practical way to achieve both of these objectives?
1.7 Data creation
- Test your understanding: When creating a customer survey, should you start with a list of data elements that you want to collect, or a list of hypotheses that you want to test? Why?
- Explore: If you could very easily scrape the Internet and collect and organize the data at low cost, what are some sites that you would want to scrape, and what would you do with that data in your organization that you are not already doing today?
1.8 Data monetization
- Test your understanding: In the pay-TV example in this section, what was the benefit that came from putting together anonymized information about the TV channels that customers were watching? Why were TV-viewership-measurement companies willing to pay for this information?
- Explore: What do you think are the main challenges that companies run into when they first try to monetize their data by selling it to external companies?
1.9 Data governance
- Test your understanding: What is the role of a data steward in making sure that data is well governed inside a large organization?
- Explore: When you want to search your organization to find a specific kind of data that would help you, do you go to a tool (such as a link to a data catalog on the company’s intranet), talk to a human expert, or do something else? Does this approach typically work well for you?
1.10 Future-proofing analytics
- Test your understanding: In the pursuit of “data sustainability” and robust analytical practices, why is it useful to collect multiple data sources that provide redundant information about your customers?
- Explore: What is a data set that you rely upon today that is in danger of being unavailable in the future? What steps can you take to mitigate this risk?
1.11 Privacy regulations
- Test your understanding: What is an example of an unintended consequence of the European General Data Protection Regulation (GDPR)?
- Explore: If you had to write a regulation that protected consumers’ privacy and data rights without stifling innovation, what would be the main area you would focus on (e.g., what type of company behavior would you restrict or regulate)?
1.12 Outsourcing analytics
- Test your understanding: Why do external providers of data and analytics sometimes have a cost advantage over in-house operations?
- Explore: What’s an example of a function in your organization that is currently done in house but, according to the seven “factors of the duck,” would be better done by an external provider?
1.13 Defunct tools
- Test your understanding: Why did Google decide to shut down the very useful Google Correlate tool in 2019?
- Explore: What is good argument in favor of aggressively pruning the list of active analytical programs within an organization?
1.14 Intro to superforecasting
- Test your understanding: According to this section, why is it useful in business to have strong forecasting skills?
- Explore: Assume you are an unusually good forecaster, and you predict that a major project at work is going to finish very late and over budget. What actions can you take as a result?
1.15 Customer experience
- Test your understanding: What is one problem with using the Net Promoter Score as a metric outside of the U.S.?
- Explore: Recall the explanation of Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” What’s an example of a metric that has this problem within your organization? What might be done to fix this?
1.16 Overfitting
- Test your understanding: In the media company example, what was one problem with creating a customer segmentation with hundreds of microsegments in order to fight churn?
- Explore: What would be the drawback of going to the other extreme: throwing out all the microsegments and treating all customers exactly alike?
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