The economics, structure, and behavior of platform ecosystems and organizations

The first step is the hardest step

One of the themes used to characterize the transition to platform ecosystems is ‘inverted firms’, as in this recent piece, The Four Biggest Challenges Digital Platforms Need to Address, by Geoffrey Parker, Marshall Van Alstyne, and Peter Evans. In the following excerpt, the authors are discussing the difficulty for traditional, ‘incumbent’ organizations to interact with or negotiate with platform businesses, and even more difficult: to go horizontal, and to reorganize their operations around the principles of platform economics. They identify three gaps in the incumbents’ understanding:

One is the ability to anticipate which markets will transform. Most executives struggle to fully grasp the nature of “inverted firms,” those that move production from inside the organization to outside. They also have yet to learn how to make the transformation happen.

In this essay, I will expand on the concept of the inverted firm. Since launching this publication we’ve used the term platforming to denote the transition from conventional organization and operations to a platform ecosystem-based model. I have somewhat poetically referred to the transition as ‘pulling the business inside out’, which I don’t think is an exaggeration.

The second of the three gaps, according to the authors, is the constraint caused by a shortage of data scientists, who are instrumental in developing the IT transformation associated with platforming. The third gap is closely linked to the first: the incumbents don’t know how to cooperate with ecosystem partners, even for those companies with a great deal of experience in supply-chain relationships.

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Case Study: Incumbents Don’t Get It

Consider the example of Rent The Runway, the platform I detailed in Rent the Runway’s Platform Strategy Becomes Clear. The rental fashion company is best known for its successful subscription model:

where members can spend $159 per month for an ‘endless wardrobe’ — that allows users to receive up to four items at a time. As soon as an item is returned, a new one can be requested. Sounds a lot like the original Netflix DVD rental service, doesn’t it?
The company has grown in a conventional way by broadening its offerings beyond work and dress clothing to include street wear and also adding children’s clothing, and furniture and home decor (through a partnership with West Elm). They have not expanded internationally, as yet, but that is an obvious possibility.
However, late last year Rent the Runway announced RTR Platform, which has opened the doors to true exponential growth.

Rent The Runway formerly had to buy all its inventory from designer brands, but now has decreased that expense as designer partners are coming aboard and relying on the RTR platform for fulfillment, returns, cleaning, and so on, but providing their own inventory.

Rent The Runway’s CEO, Jennifer Hyman, relates how designer firms couldn’t adapt their thinking to rental and platforms:

Ten years ago, I was actively begging designers to consider rental,” Hyman said. “Now most of the interest in Rent the Runway is inbound.

What made them change their minds? First, years had passed and Rent The Runway (RTR) had grown by 2016 to over $100 million of sales, and the market for online clothing rental is projected to grow to $1.9 billion by 2023, according to Allied Market Research.

Secondly, RTR’s platform is throwing off a lot of data, since the subscribers are growing at 160% per year, and now the designers don’t need to hire a bunch of data scientists to build their own infrastructure to gather that data and analyze it: they can rely on RTR for that.

Third, the subscribers are often completely new customers to the designer firms, who might not be willing to spending hundreds or thousands on high fashion, but because of the subscription model the customer will try more clothing, and that data is extremely useful for planning, innovation, and design.

So, the lesson is this: It took ten years for many of the incumbents to get their minds wrapped around the disruption that RTR represented. Following the Amazon model, the upstart that produces no clothing itself creates an online platform with the customer’s needs at the center, grows through network effects on the customer side, and starts out by working with uninvolved clothing manufacturers as a conventional wholesale buyer.

But ten years later, dozens of the clothing manufacturers have moved onto the platform as partners, lured by the deepest value in the ecosystem: data about customer habits, desires, and trends. They are getting closer to the users than they ever did with conventional offline department stores. And to get that connection, they are pulling themselves inside out.

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In Pipelines, Platforms, and the New Rules of Strategy, Marshall W. Van Alstyne, Geoffrey G. Parker, and Sangeet Paul Choudary, make a distinction between conventional, ‘pipeline’ business and platformed business:

Pipeline businesses create value by controlling a linear series of activities — the classic value-chain model. Inputs at one end of the chain (say, materials from suppliers) undergo a series of steps that transform them into an output that’s worth more: the finished product. Apple’s handset business is essentially a pipeline. But combine it with the App Store, the marketplace that connects app developers and iPhone owners, and you’ve got a platform.

In the RTR example, if Jennifer Hyman had simply created an ecommerce site, that would have been a pipeline. But bringing on the designer firms (who are the equivalent of app developers in the Apple model) it became a platform. There are still aspects of pipeline in Apple and RTR — the handsets need to be built, and the clothing fabbed and shipped. But when platforms and pipelines meet in the same market:

the platforms virtually always win.

The researchers catalog three key shifts from pipeline to platform:

  1. From resource control to resource orchestration — in the conventional, pipeline world companies seek advantage by controlling scarce and valuable assets, like metals, real estate and other tangible assets, along with intangibles like intellectual property, trade secrets, and patents. Once pulled inside out, the assets of importance are the ecosystem's: the community of participants and the assets that the members own and contribute, like rooms (Airbnb), clothing (RTR), data (Uber), or ideas (Haier’s open innovation model). As the researchers state, ‘In other words, the network of producers and consumers is the chief asset’.
  2. From internal optimization to external interaction — in pipeline companies, the core effort is to optimize the chain of product-related activities, focusing on price, time-to-market, or other attributes. In platform ecosystems, value is created emergently in the interactions of external producers and consumers. This can drop the costs of production enormously, exponentially for the orchestrator and other participants. So instead of dictating to supply-chain partners what to do, the orchestrator has to persuade partners to play, and ‘ecosystem governance’ becomes central. (Consider Haier’s emphasis on fairness in its ecosystem micro-communities, for example.)
  3. From a focus on customer value to a focus on ecosystem value — while ecosystems are often built around the provisioning of a product or service to an end customer, that is best understood as one of an interrelated set of value exchanges that link the members of the ecosystem together. All in the ecosystem have to derive a proportionate value relative to their involvement and efforts. Think of the customer as first among equals, rather than the be-all-and-end-all.

Obviously, this is more complex than a linear pipeline world, and the complexities are an essential element, not a flaw.

Not explicitly mentioned in this list is the increased likelihood of learning by the members, as an outgrowth of the flow of information among the partners. As platforms grow through network effects, the platform allows for low-cost information capture, as well as increased opportunities for innovation.

As I wrote in On Haier’s Ecosystem Micro-Communities — Part 1,

One of the two engines of ecosystem platforms is the learning engine, the other being the transactions engine (the part that most people think about). The apparent chaos of a network of loosely-connected, but interdependent entities is, in fact, the best sort of learning engine, where the learning comes at low cost and as the outcome of already necessary communications between the parties. This leads to not chaos, but unintended order.

The First Step Is the Hardest Step

The hardest aspect of making the transition to platform thinking is the thinking itself. Adopting the mindset may be harder — especially for successful senior executives in well-established pipeline companies — than what goes on afterward. That explains why the great majority of transitions into the platform economy will be companies that become members of others’ ecosystems instead of creating ecosystems themselves.

Of course, the alternative is not to be in the ecosystem at all and to watch your pipeline dry up.