Using Data to Make a Hit TV Show

The speech begins with the speaker, Sebastian Wernicke, explaining to the audience that Roy Price was the senior executive with amazon studios. Roy is in charge of finding TV shows for amazon. Sebastian then goes on to explain that Roy needs to find the right TV show for viewers, a well written, addicting TV show if he wants amazon to be successful. The first thing that Roy has to do is select eight shows that are deemed worthy candidates. Then he puts the first episode of each one of these shows online for free. Because the episodes are free, millions of people will see them. While the people watch the episodes, Roy and his crew record the viewers’ actions: when they press play, when they press pause, what parts they skip, or what parts are re-watched. They then record the data that they receive and decide which show would best succeed.

Sebastian explains that one of the first shows that Roy had decided on based off of the data they collected, actually turned out to be an average show, instead of a great big hit like they were hoping for. Sebastian then tells us that at around the same time another man that worked for a different company, Ted, was collecting data in a similar way. Instead of picking candidates, Tom and his team looked at data that had already been collected from Netflix viewers to decide on a show. Then, Tom and his team use that data to pick out information about their audience. What kind of actors, the audience liked, what kind of genre, etc. They then use that data to make a VT show that was very similar to Roy’s. Toms show was a much bigger success.

Them Sebastian asks what happened? The data was similar, why did it not work. If data analysis doesn’t work, what will? Data analysis does not always work. Although it often does, it’s not a perfect system. There is a pattern that shows up in data analysis that works and data analysis that doesn’t. Data analysis is only really good for taking a problem apart, but not so good with putting together an answer. He then says that he thinks that things begin to go wrong when people let data completely drive their decision making. If we really want to be successful, we need to be able to make decisions for ourselves and take risks.

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