Does collecting more data lead to better decision-making? Competitive, data-savvy companies like Amazon, Google and Netflix have learned that data analysis alone doesn’t always produce optimum results. In this talk, data scientist Sebastian Wernicke breaks down what goes wrong when we make decisions based purely on data — and suggests a brainier way to use it.
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Intro
Discuss the question briefly.
- What is your favorite TV series? Why do you like it?
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Watch
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Glossary
- mediocre – of only average quality; not very good
- curve – a line on a graph (whether straight or curved) showing how one quantity varies with respect to another
- undercut – weaken; undermine
- bulge – a rounded swelling which distorts an otherwise flat surface
- nailed it – you completed a task successfully or got something right
- savvy – clever
- sophisticated – developed to a high degree of complexity
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Think about it
Answer the questions below. Pause at times indicated in brackets.
- Who is Roy Price? What does the graph represent? How does it relate to Roy’s job? (2:26)
- How did Amazon make the decision to produce Alpha House? Was it a good decision? (4:00)
- What kinds of decisions are made based on collections of data points? (7:02)
- What example of failure of data-driven decision making does Sebastian present? What were the consequences? (8:11)
- How is data helpful in solving complex problems? What is the other element necessary to solve such problems? (10:18)
- What conclusion does Sebastian reach? Do you agree with him?
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Practice makes perfect
Fill in the blank spaces with the missing words. Use ONE word per blank space.
If someone here in ________ US is in prison, and they apply ________ parole, then it’s very likely that data analysis software from that company will be used in determining whether to grant that parole. So it’s the same principle ________ Amazon and Netflix, but now ________ of deciding whether a TV show is going to be good or bad, you’re deciding whether a person is going to be good or bad. And mediocre TV, 22 minutes, that can be pretty bad, but more years in prison, I guess, even worse.
And unfortunately, there is actually some evidence that this data analysis, despite having lots of data, ________ not always produce optimum results. And that’s ________ because a company like Multi-Health Systems doesn’t know what to do ________ data. Even the most data-savvy companies get it wrong. Yes, even Google gets it wrong sometimes.
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Fill in the blank spaces with the correct form of the words in CAPITAL LETTERS.
In 2009, Google announced that they were able, with data analysis, to predict ________ BREAK of influenza, the nasty kind of flu, by doing data analysis on their Google searches. And it worked ________ BEAUTIFUL, and it made a big splash in the news, including the pinnacle of ________ SCIENCE success: a ________ PUBLISH in the journal “Nature.”It worked beautifully for year after year after year, until one year it failed. And nobody could even tell ________ EXACT why. It just didn’t work that year, and of course that again made big news, including now a retraction of a publication from the journal “Nature.” So even the most data-savvy companies, Amazon and Google, they sometimes get it wrong. And despite all those ________ FAIL, data is moving rapidly into real-life decision-making — into the workplace, law ________ FORCE, medicine. So we should better make sure that data is helping.
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Explore it more
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