Netflix Broke the Rules and Won According to Stanford Business School Research

STANFORD, Calif.--(Business Wire)--
It isn't often that a business model becomes the subject of a
patent violation suit. But according to research reported today in
Stanford Knowledgebase, that's exactly what happened in 2006 when
Netflix, the pioneer in online video rental, sued Blockbuster, the
giant of the brick-and-mortar video rental companies.

Granted in 2003, Netflix's 31-page patent details a business model
that was a sharp departure from the way video rental companies had
operated for years.

The conventional model works like this: Customers go to a video
rental store and select particular movies to rent. They take the
movies home and must return them by a particular due date or be
charged a late fee.

Netflix, however, patented a subscription model that allows
customers to pay a fixed monthly fee, create an online wish list for
future rentals, and order them over the Internet. The movies come in
the mail and may be kept as long as the customer wants, with no late
fee. Depending on the plan selected, customers can keep as many as
four DVDs at a time, but cannot rent new movies until the older ones
are returned.

The suit accused Blockbuster of copying Netflix's business model,
including the wish list and the basic subscription model itself.
Blockbuster said the patent was so broad, it should not be enforced.

Although the patent contains a good deal of detail about the video
rental business, it is also quite broad, since it applies to "a method
for renting items to customers" and "computer-implemented steps" --
either of which could extend to online rental of non-entertainment
items.

The novelty of the model and the possibility that it might be
applicable to other businesses intrigued Sunil Kumar, the Fred H.
Merrill Professor of Operations, information, and Technology at the
Stanford Graduate School of Business, whose research focuses on
analyzing mathematical models of operations, particularly congestion
phenomena.

Along with colleagues Achal Bassamboo of Northwestern University
and Ramandeep Singh Randhawa of The University of Texas, Austin, he
studied the Netflix model with the goal of determining what effect the
lack of deadlines has on customers. The researchers also wanted to
know the smallest amount of inventory Netflix could carry while still
having enough movies on hand to satisfy customers.

The answers were straightforward: "Netflix got it right by not
imposing deadlines," says Kumar. And the company needs to stock only a
small fraction of the total demand for any one video and still provide
good service. But the method for calculating those answers was fairly
complex. Indeed, nearly all of the 23-page working paper "Dynamics of
new product introduction in closed rental systems" is a mathematical
proof of those seemingly simple conclusions.

Building a model to represent Netflix's business was difficult
because of the enormous number of transactions that occur every day.
Rather than trying to capture so many events, the researchers used an
analogy from engineering -- the behavior of fluids. "Imagine that
Netflix is a huge reservoir that drains and refills as people rent and
return movies," explains Kumar. "We need to know how a system works
with many users, and the alternative (to the fluid model), tracking
individual users, is hopeless. The fluid model is a usable
approximation that works well as the number of users gets large." The
fluid metaphor exists in classical statistics. Proving that it applies
in this business case is a contribution of the paper, he notes.

The Netflix business model contains an interesting set of
tradeoffs. When a customer keeps a movie for an extended period of
time, Netflix is deprived of its use, which is a negative. Deadlines
help ensure prompt return and thus have the benefit of reducing the
number of copies that Netflix needs to stock to provide good service.
But because the customer can't rent another movie until it is returned
(this is known as "max out" and is included in the patent), deadlines
speed up demand for other movies and trigger costs of fulfillment,
such as postage, which Netflix pays. Kumar and his co-workers show
that there is no tradeoff here at all -- not having deadlines is a
win-win.

It's important to note that Netflix isn't flying blind. Customer
"wish lists" give the company real insight into what movies its
customers want. In theory, Netflix could simply stock one movie for
every customer who wants to see it. But that, of course, would be a
terrible business practice. So the question remains: How many copies
of a given movie should the company stock, and is it really better to
eschew return deadlines?

The researchers realized that customer behavior varies. In fact,
it's pretty random. Some people hold movies for a week, others for two
or three weeks. And the behavior of each individual customer varies
from time to time. The timing of new movie releases is also random. It
turns out that those two facts are key to resolving the questions. To
demonstrate why, Kumar uses an analogy familiar to many business
students, "the inspection paradox." Here's how it works:

Suppose we note that taxi cabs pass a given corner on the average
of one every 10 minutes. Then assume I show up at a random time, and
I'm told that a taxi left the corner eight minutes ago. At first
glance, one would assume the next taxi will arrive in two minutes on
average. But that's incorrect; the real answer is much longer, and
depends on the degree of randomness. That's because the 10-minute
interval is an average, so if a customer shows up at a random time,
she is less likely to hit a shorter interval and more likely to hit a
longer interval between taxis.

The release of a new movie is like the appearance of the taxi, and
the customer's readiness to rent another DVD is analogous to showing
up at the corner. The imposition of deadlines would remove some of the
randomness from the equation and push customers to rent faster,
resulting in higher costs. Removing deadlines creates a better balance
of supply and demand, the researchers conclude. In fact, under the
ideal conditions established in Kumar's model, Netflix would only have
to stock a small fraction of any given movie to satisfy customers and
control its costs.

Because the model built by Kumar and his colleagues is just a
model, and not reality, it would be useful to compare the results of
the researchers' simulation to the company's actual results. But
Netflix did not provide the data, citing costs of data collection and
data cleaning, says Kumar.

Even so, the results of the paper raise an interesting question:
If the no-deadline model works for Netflix, would it work for another
type of business? The answer is maybe, says Kumar. For example, it
would not work for a car rental business, since people tend to rent a
car and return it without renting another. But consider the customers
of an equipment rental business. One might rent, say, an air
compressor, at the beginning of a job, and then return it and rent a
backhoe, suitable for a later stage of the job. And that could mean
that a no-deadline policy would work. "It's worth examining," says
Kumar.

And the suit? It was settled out of court in 2007, with the terms
kept under wraps.

(This story reports on research at the Stanford Graduate School of
Business and appears in today's Stanford Knowledgebase, the free
monthly information source for thoughts, ideas and lectures at the
Stanford Graduate School of Business. For related research citations
and to dig deeper, visit
http://www.gsb.stanford.edu/news/knowledgebase.html.)

Stanford Graduate School of Business
Helen Chang, 650-723-3358
chang_helen@gsb.stanford.edu

Copyright Business Wire 2008