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Netflix Innovation

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In the past 12 months, Netflix has gone from Wall Street (and PR) dunce to darling. After announcing they had signed up more than 2 million new U.S. streaming subscribers in the first quarter, the stock surged 25% (at press time). As the CEO of a video compression company, I've enjoyed watching this company develop and am very excited by the opportunities they've uncovered in streaming and original programming. Success has not come easy for Netflix but it never does for disruptive companies.
Past: A Disruptive Start

Anne Marie Knott, a professor of strategy at Washington University and director at Berkeley Research Group, wrote a great piece detailing the company's original strategy.
From her post
"Netflix aimed to kill Blockbuster and started with a simple mission of targeting people who found Blockbuster inconvenient, both because they had to drive there twice within a 24 hour period, and because they had to scan a good portion of the stacks to find movies of interest. Formerly, Blockbuster had an important resource (the store network) that formed an entry barrier. Any firm considering a national chain would find the investment in stores unattractive—they would at best get half the market at lower margins (because the two chains would compete on price). Netflix executed an end run around the entry barrier through an online sales/mail distribution system. Just as Blockbuster's store network served as an entry barrier, Netflix' end run became an adaptation barrier for Blockbuster. Because Blockbuster could already reach the entire market through its storefronts, the returns to investment in mail distribution were negative. The mail order system wouldn't increase sales (it would cannibalize existing sales). Moreover, it might decrease sales of impulse purchases like popcorn or candy. Netflix is a great example of a disruptive innovation. Disruptive innovations are ones that initially target a market niche, typically one being neglected by incumbents. Because disruptive innovations don't serve the entire market, it's feasible for entrepreneurial firms to introduce them. However, there is typically some critical incumbent resource (entry barrier) the entrants can't access. So, rather than trying to scale the entry barrier, entrepreneurial firms execute an end run. What makes this end-run innovation so formidable to the incumbent (and the reason incumbents are often wrongfully accused of being caught off-guard by the innovation) is that adopting the innovation requires duplicating an existing resource investment, which by definition has negative returns. The end run by the entrants forms an adaptation barrier to incumbents.
Present - Leveraging Big Data
Currently, Netflix is continuing its disruptive ways and wreaking havoc on the original programming arena. As The Huffington Post details: Netflix CEO Reed Hastings has a vision for TV that ought to scare studio heads as much as Netflix’s first business--direct-by-mail DVDs--scared Blockbuster. So, what is Netflix’s plan for disruption? The streaming TV network wants to turn into the HBO of Internet TV and started the quest with a show called House of Cards.
As noted by Andrew Leonard writing for Salon:
“House of Cards” is one of the first major test cases of this Big Data-driven creative strategy. For almost a year, Netflix executives have told us that their detailed knowledge of Netflix subscriber viewing preferences clinched their decision to license a remake of the popular and critically well regarded 1990 BBC miniseries. Netflix’s data indicated that the same subscribers who loved the original BBC production also gobbled down movies starring Kevin Spacey or directed by David Fincher. Therefore, concluded Netflix executives, a remake of the BBC drama with Spacey and Fincher attached was a no-brainer, to the point that the company committed $100 million for two 13-episode seasons."
To its technology team's credit, Netflix has taken a long path to get here and has collected a lot of data in hopes of being able to understand their audience. For example last year it was revealed they collect (at least) the following:
- More than 25 million users and about 30 million plays per day
- More than 2 billion hours of streaming video watched during the last three months of 2011 alone
- About 4 million ratings per day
- About 3 million searches per day
- Geo-location data device information identifying time of day and week of user viewing (it now can verify that users watch more TV shows during the week and more movies during the weekend)
- Metadata from third parties such as Nielsen
- Social media data from Facebook and Twitter
Future - Bring on the Copycats
If I get out my crystal ball, I see a flurry of companies like Hulu and YouTube spinning up their own streaming-video businesses. These future bandwidth hogs will further tax an already overloaded system and create a larger problem that may not be easily addressed. As we approach the reality of the coming Exabyte Era, we'll need a fresh band of disruptive companies to step forward and deliver the bandwidth, range and required uptime. Having spent the past decade deep in the video compression trenches, I'm excited by what Netflix has accomplished and amazed by the market's appetite. I can't wait to see what happens next.

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