When Netflix debuted in 1999, it sought to differentiate its DVD rental-by-mail service by not placing limits on the length of time its customers could hold onto a disc. “No late fees” became a rallying cry and eventually forced its biggest competitor, Blockbuster, to follow suit. What no one realized at the time was that this policy, which on its face could have been detrimental to the profitability of the fledgling service, was in fact its secret weapon and probably saved the company untold millions of dollars.
Achal Bassamboo, an associate professor of managerial economics and decision science at Kellogg School of Management, along with co-authors Sunil Kumar, Dean of the University of Chicago Booth School of Business, and Ramandeep Randhawa, an assistant professor at the University of Southern California, uncovered one of the counterintuitive secrets to Netflix’s success by modeling the behavior of Netflix subscribers who want to rent the latest hit movie. Their core discovery is that Netflix’s unique model means that the service has to stock far fewer discs than it would if it imposed late fees on customers. In fact, they found that the longer Netflix allows customers to keep discs, the more profitable the company could be. It is hardly a coincidence that the best answer to the problem of how long a customer should keep a disc—forever—is exactly what Netflix’s model encourages.
“As uncertainty about when a customer will return a disc increases, you need to stock fewer copies of a movie,” Bassamboo says. “This is quite in contrast to what you would normally see, that with more uncertainty you’d have to stock more.”
A staple of operations classes in schools of business and economics is the dogma that uncertainty about when customers will demand an item is always a bad thing, Bassamboo says. But in the specific case of Netflix’s business model, and hardly any others, the opposite is true.
To understand how Netflix actually profits from uncertainty, it is helpful to imagine a handful of idealized Netflix customers, as Bassamboo and his colleagues do in their paper. The only thing all the customers have in common is that when a hot new movie comes out, they all want it. If Netflix imposed late fees on its customers, the company could be sure that every customer who wanted a particular new release would return their last-viewed movie, and automatically be sent that new release, within a narrow window of a few days.
“As uncertainty about when a customer will return a disc increases, you need to stock fewer copies of a movie.”
Bassamboo and his colleagues discovered that for a hypothetical Netflix-like service with late fees, the company would have to stock as many copies of a new release as it has customers. Given that all those customers would probably only rent it once, the company would be hard-pressed to either remain profitable or offer a compelling subscription fee.
On the other hand, when Netflix allows customers to keep DVDs indefinitely, the point in time at which they return old discs and automatically request a hot new release is staggered. Some customers are going to return a disc the day a new release comes out, while others will take a few days or even weeks to return their last movie and request the new one. The longer customers wait to request that next disc, the more times Netflix can rent out individual copies of its new releases. It is this re-use of discs, or “multiplexing,” that makes the Netflix model possible.
Allowing customers to take their time with returns has other benefits for the company’s bottom line, including reduced costs for postage and processing as discs are sent to and from customers.
In order to imagine what this spread out demand looks like, Bassamboo and his co-authors used an exponential rental distribution, where demand peaks quickly, but much of it is shifted to a “long tail” of customers requesting a disc days after it has become available. Assuming this distribution, Netflix must stock copies of a hot new release equal to 38 percent of the customer base that would want to rent it. Bassamboo stresses that this is not a hard prediction of behavior in the real world—for that, he would have to know the actual distribution of demand across time for new releases.
It is not clear whether Netflix’s strategy could work for other subscription or rental businesses. Others are certainly attempting it. Textbook rental is one case that might not fare as well, because demand for textbooks is too structured in time, with students always wanting them around the same time and returning them at the same time, according to the academic calendar.
Rental services for other media, such as novels, might work better. “You want a system similar to Netflix, where you know when you return a book, what’s the next thing you’ll get,” Bassamboo says. “You want to have this uncertainty; you don’t want demand to work like clockwork.” Any business with a subscription model and a lack of incentive for subscribers to return an item will lead to what Bassamboo calls the “multiplexing benefit,” in which a company can maximize the number of times an item can be reissued to customers.
There is even evidence that Netflix maximizes its multiplexing benefit by encouraging users to hold on to their rentals for as long as possible. A class action suit against the company, resolved in 2005, uncovered a practice called “throttling,” in which Netflix would take longer to send discs back to customers who returned them at a higher rate. The company also eliminated a once-popular feature of the site, a page of discs called “Releasing This Week,” which had the effect of encouraging many customers to put new releases at the top of their queue.
Bassamboo notes that his model of how Netflix operates breaks down for streamed movies, an increasingly important part of the company’s business. For streaming, the scarce resource is bandwidth, not number of discs, and customers do not have to wait for a disc to arrive in order to watch their next selection. Yet what endures about the work of Bassamboo and his colleagues is their discovery that there is a business model that violates the fundamental tenet that when it comes to demand, certainty is always a good thing.
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