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Big Data and the Future of Entertainment Part 2

Last week we posted the first part of a Q & A with Mike Smith and Rahul Teland, coauthors of Streaming, Sharing, Stealing:Big Data and the Future of Entertainment. Here's part 2:

Why has Big Data disrupted the entertainment industry more rapidly and with greater consequence than most other industries?

The two main reasons are access to data and culture. Think about the story Michael Lewis tells in Moneyball. Billy Beane’s decision to replace gut feel decision-making with data-driven decision-making required huge changes in the Oakland A’s organizational culture, and huge innovations in analytics. His leadership changed the game, but it only gave Oakland a year or two of competitive advantage. Everyone else in the league soon caught up.

That might lead you to believe that the entertainment majors will have an easy time catching up to the tech driven entrants: Netflix, Amazon, and Google. But the entertainment majors are facing two key challenges when trying to catch up to the tech firms. First, in Major League Baseball, all of the competitors had to invest in changing their organizational cultures to embrace data-driven mindsets. But in entertainment, Amazon, Netflix, and Google already have data-driven cultures, and it’s going to take many years for the entertainment companies to catch up.

Second, and maybe more important, in baseball, all teams had access to the same data. Any team in the league could go to Elias Sports Bureau or Stats Inc. and buy the data Oakland was using to make their decisions. But in entertainment, Amazon, Netflix, and Google own their customers’ data, and they aren’t sharing that data with anyone else in the industry.

Add to this the fact that Netflix, Amazon, and Google can change the underlying rules of the game by distributing content using on-demand streaming channels that are customized to the tastes of each user, whereas much of the entertainment business relies on a linear broadcast model, and you have all the ingredients for rapid, disruptive change.

How has so much power been retained-with few challengers and for so many decades-by only a few powerful studios, labels and publishing houses?

Market power, and profit, in entertainment has always come from controlling how content was created, distributed, and consumed. The major firms did this by using their scale to control the scarce financial and technical resources necessary to create content, the scarce channel capacity necessary to promote and distribute content, and finally by using copyright to control how their audience was able to access and consume content.

Over the last century, these industries have seen enormous changes in the technologies used to create, distribute, and consume content. But none of these technological changes has affected the major’s control, at least until recently…

What conditions made it possible for game-changers like Netflix, Amazon and Apple/iTunes to disrupt the establishment, legacy companies like Disney-ABC and NBCUniversal, etc.?

The challenge the traditional leaders in entertainment face today is that none of their traditional forms of market scarcity are as “scarce” as they once were. We refer to this as a “Perfect Storm” of change. Technological change has reduced the cost of creating many types of content and democratized access to the tools necessary to make content; long tail markets have eliminated scarcity in what types of content can be distributed to the market; and digital piracy has made it nearly impossible to control how consumers access content.

As these old forms of scarcity were removed, they were replaced by scarcity in customer attention. And this created an opportunity for the platform companies who controlled access to the customer to move into the market, and even vertically integrate into the previously protected space of content creation.

What can any company learn from Netflix’s staggering bet on House of Cards, and how the series became an unprecedented hit?

Netflix’s ability to control customer attention allows it to do many things that are difficult for traditional broadcasters to copy.

Consider the greenlighting process. Many in the industry have concluded that Netflix was able to see the potential of House of Cards before anyone else because Netflix was able to see in their data that there were a lot of fans of Kevin Spacey’s acting, David Fincher’s directing, and many fans of the BBC’s House of Cards. But if you think about it for a second, that can’t possibly be what gave Netflix an advantage over the networks. After all, everyone in the business knows that Mr. Spacey and Mr. Fincher have huge followings, and that the BBC’s House of Cards was a huge hit. Instead, Netflix had something that no one else in the industry was able to access: The ability to know exactly who the Spacey, Fincher, and BBC House of Cards fans were as individuals, and the ability to use their platform to promote content directly to these customers based on their unique preferences.

What inspired you to write Streaming Sharing Stealing?

It’s a combination of our love for great entertainment and great storytelling, and our love of research and evidence-based decision-making. For the last 10 years, we have had the joy of doing research with leading firms in publishing, music, and most recently, with firms in the motion picture industry. Our goal in writing the book is to first explain what has allowed firms in these industries to sustain market power, and then to highlight to our friends in the industry why technological change is eroding the advantages that have sustained their business for so long, and finally to provide them with specific advice for how they can respond to these threats to maintain their leadership in their industries.

How serious is the threat of piracy in the global entertainment marketplace and what can be done to stem this threat?

Piracy is an enormous threat to the entertainment business. First, let’s set the record straight about how piracy impacts legal sales. There have been 25 peer reviewed academic studies on piracy, and 22 of those papers find that piracy results in statistically significant harm to legal sales. The academic evidence is clear: in the vast majority of cases, piracy hurts sales.

But just looking at sales minimizes the real threat from piracy. The real threat of piracy is that it makes it harder for the entertainment industries to execute all of their business models. Every one of the industries’ business models are based on controlling the timing, quality, and usability of how and when users can access content. The problem of piracy is that it makes it much harder to exert this control, and is making all of the traditional industries’ business models less profitable than they once were.

How can managing customer data help reduce risk and marketing costs, and provide competitive advantages in entertainment, or other industries?

In the first scene of House of Cards, Kevin Spacey’s character strangles an injured dog. Netflix’s own data show that a lot of people stopped watching the show after that scene. In a broadcast world, that information might lead you to cut the scene: broadcast space is scarce and you need to get as many people watching as possible. Netflix was able to keep this scene because it isn’t selling a specific program in a specific broadcast slot — it is selling an integrated platform, with no fixed broadcast times. From Netflix’s perspective, viewers who were repulsed by this scene, probably found something else on Netflix that better matched their interests.

Netflix’s data also allowed it to promote House of Cards in new ways. Netflix created separate trailers targeted to customers who they knew had liked Kevin Spacey’s acting, or David Fincher’s directing style, or who liked movies with strong female leads and who might like Kate Mara’s or Robin Wright’s characters.

Rich customer data also allows firms like Netflix to play with different models of how content can be packaged and priced. The point is that Netflix was able to do things with House of Cards that would be difficult or impossible for traditional broadcast channels to copy. And as more customers gravitate towards these platforms, the platforms gain more power in both content distribution and content production.

Does research data from companies like Nielsen or Arbitron have any advantages over the user data retained by companies like Netflix, Amazon and Apple/iTunes that access audience behavior across their content platforms?

There are three main reasons that Nielsen and Arbitron data don’t provide any lasting competitive advantage, and aren’t at all important to companies like Netflix, Amazon, and iTunes.

First, Nielsen and Arbitron data are available to everyone, so it can’t provide any sort of lasting competitive advantage to anyone.

Second, broad demographic characteristics—the sorts of things you get from Nielsen surveys—tell you almost nothing about an individual’s personal tastes. Our tastes are far more diverse than what can be captured from a handful of demographic characteristics.

Third, and most important, survey data drawn from a population doesn’t tell you anything about how to reach individuals within the population. Knowing that 30% of 25-34 year old women like a particular show is much less valuable than knowing exactly who those women are, and having a way to reach them as individuals.

How can artists now take more control of their original content and audiences in this new landscape?

Artists can use online channels to connect with fans, cultivate fan relationships, and even learn from fans. Improv comedians Peter Shukoff and Lloyd Ahlquist (the creators of Epic Rap Battles of History), author Amanda Hocking, and violinist Lindsey Stirling used online resources to launch their careers.

How can businesses in any industry learn from the entertainment industry a better way to drive growth and avoid disruption with digital analytics?

We think this involves going to back to the fundamentals and asking questions like Why has my business been successful? and How is technology changing sources of competitive advantage? For example, in class we ask our students this question in the context of how technology might change the market for higher education, and get fascinating (and frequently terrifying) answers.


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