Marshall Van Alstyne Explains Platform Strategies

At the recent Platform Strategy Summit, Van Alstyne talked about 'extraordinary changes' taking place.


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      Digital Business Transformation

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      Paula KleinCreated by Paula Klein on Sep 21, 2015 in Public Site: MIT IDE

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      Recently, I wrote about one of the talks at the annual conference of the MIT Initiative on the Digital Economy - Only Humans Need Apply by Tom Davenport, based on his recently published book of the same title.  I would now like to discuss another excellent talk at the same conference - How Platforms Change Strategy by Boston University professor Marshall Van Alstyne, also based on a recently published book,Platform Revolution: How Networked Markets are Transforming the Economy and How to Make Them Work for You, co-authored with Geoffrey Parker and Sanjeet Choudary. The three also published a related article in the April issue of the Harvard Business Review.platform-revolution.jpg

       

      Van Alstyne started out his presentation by noting that back in 2007, seven firms controlled 99% of handset profits: Nokia, Samsung, Ericsson, Motorola, LG, RIM and HTC. That same year, Apple’s iPhone was born and began gobbling up market share. By 2015, only one of the former incumbents had any profit at all, while Apple now generated 92% of the industry’s global profits.

       

      What happened? “Is it likely all seven incumbents had failed strategies, run by clueless management, lacking execution capabilities?,” he asked. “Or was something more fundamental happening?… Nokia and the others had classic strategic advantages that should have protected them: strong product differentiation, trusted brands, leading operating systems, excellent logistics, protective regulation, huge R&D budgets, and massive scale. For the most part, those firms looked stable, profitable, and well entrenched.” How can we explain their rapid free fall?

       

      Information and Interactions: Value Creators

      We all know the answer to Van Alstyne’s rhetorical questions: “Apple (along with Google’s competing Android system) overran the incumbents by exploiting the power of platforms and leveraging the new rules of strategy they give rise to. Platform businesses bring together producers and consumers in high-value exchanges. Their chief assets are information and interactions, which together are also the source of value they create and their competitive advantage.”

       

      For the past two centuries, the industrial economy has been driven by supply-side economies of scale. Because of the massive fixed costs of physical assets, firms achieving higher volumes have a lower cost of doing business, which allows them to reduce costs and further increase volumes. Market power is thus achieved by controlling resources, increasing efficiency and fending off competition. “The goal of strategy in this world is to build a moat around the business that protects it from competition and channels competition toward other firms,” notes the HBR article.

       

      In the digital economy, on the other hand, the driving force is demand-side economies of scale. That’s what network effects are all about. Scale is what increases a platform’s value. The more products or services a platform offers, the more users it will attract, helping it then attract more offerings, which in turn brings in more users, which then makes the platform even more valuable. Moreover, the larger the network, the more data is available to customize offerings to user preferences and better match supply and demand, further increasing the platform’s value.platforms2.png

       

      Platforms have long played a key role in the IT industry. IBM’s System 360 family of mainframes, announced in 1964, became the premier platform for commercial computing over the following 25 years by developing a 3rd party ecosystem of add-on hardware, software and service. In the 1980s, the rapid growth of personal computers was largely driven by the emergence of the Wintel platform which attracted a large ecosystem of hardware and software developers. Then in the 1990s, the explosive growth of the Internet drove platforms to a whole new level, connecting large numbers of PC users to a wide variety of web sites and online applications. Platforms have grown even more dramatically over the past decade, with billions of users now connecting via smart mobile devices to all kinds of cloud-based applications and services.

       

      'Frictionless' Participation

      IT has been bringing the power of platforms to an increasing number of industries. By reducing their need to own physical assets, “IT makes building and scaling up platforms vastly simpler and cheaper, allows nearly frictionless participation that strengthens network effects, and enhances the ability to capture, analyze, and exchange huge amounts of data that increase the platform’s value to all. You don’t need to look far to see examples of platform businesses, from Uber to Alibaba to Airbnb, whose spectacular growth abruptly upended their industries.”

       

      For almost 20 years now, e-commerce platforms have been giving physical stores and shopping malls a run for their money. More recently, we’ve seen Uber, - with only 5,000 employees and a valuation of $60 billion - and Airbnb - with 3,000 employees and a valuation of $21 billion - disrupt the transportation and hotel industries respectively.

      It’s instructive to contrast platform-based strategies with those of more classic product strategies.  In a 2008 HBR article, Harvard professor Michael Porter explained that the key to a successful product strategy is to understand and cope with five key competitive forces:

      • rivalry among existing competitors;
      • threat of potential new entrants;
      • threat from substitute products or services;
      • bargaining power of suppliers; and
      • bargaining power of buyers.

       

      “The extended rivalry that results from all five forces defines an industry’s structure and shapes the nature of competitive interaction within an industry,” wrote Porter. But the nature of competition and strategy is quite different in a platform-based business, said Van Alstyne:

       

      • The goal is interactions that yield network effects and provide growth and sustainability, - not protecting market niches or erecting industry barriers.
      • Industry boundaries can be altered as appropriate, - rather than sticking to sharply defined categories.
      • Competition is multi-layered, “more like 3D chess”, - rather than just relaying on product differentiation or lower costs.
      • Competitors are turned into complementors that offer their products or services on the platform - there’s no longer a need to own unique, inimitable resources.

      In a product-based business, “the five forces are relatively defined and stable.  If you’re a cement manufacturer or an airline, your customers and competitive set are fairly well understood, and the boundaries separating your suppliers, customers, and competitors are reasonably clear.”  But, in a platform business, those boundaries can shift rapidly because of shifting dynamics within the platform ecosystem.The platform participants - consumers, producers, providers - are key to value creation.  “But they may defect if they believe their needs can be met better elsewhere…  every platform must induce producers and consumers to interact and share their ideas and resources.  Effective governance will inspire outsiders to bring valuable intellectual property to the platform…  That won’t happen if prospective partners fear exploitation.”

       

      Three Key Shifts

      “With platforms, a critical strategic aim is strong up-front design that will attract the desired participants, enable the right interactions (so-called core interactions), and encourage ever-more powerful network effects… while guarding against threats remains critical, the focus of strategy shifts to eliminating barriers to production and consumption in order to maximize value creation… To that end, platform executives must make smart choices about access (whom to let onto the platform) and governance (or control - what consumers, producers, providers, and even competitors are allowed to do there)…” The transition from a product-oriented strategy to a platform strategy requires three key shifts, note Van Alstyne et al in their HBR article:

       

      • From resource control to resource orchestration. Don’t try to gain competitive advantage by controlling scarce and/or valuable resources “With platforms, the assets that are hard to copy are the community and the resources its members own and contribute, be they rooms or cars or ideas and information. In other words, the network of producers and consumers is the chief asset.”
      • From internal optimization to external interaction. Don’t attempt to create value by optimizing the entire chain of product and service activities. “Platforms create value by facilitating interactions between external producers and consumers. Because of this external orientation, they often shed even variable costs of production.”
      • From a focus on customer value to a focus on ecosystem value. Don’t seek to maximize the lifetime value of individual customers of products and services. “[P]latforms seek to maximize the total value of an expanding ecosystem in a circular, iterative, feedback-driven process.”

       

      Summing up, the speakers note: “The failure to transition to a new approach explains the precarious situation that traditional businesses -from hotels to health care providers to taxis - find themselves in… the writing is on the wall: Learn the new rules of strategy for a platform world, or begin planning your exit.”

       

      This blog first appeared June 14 here. Watch for more updates from the July 15 Platform Strategies Summit.

      By Tom Davenport and Andrew Spanyi

       

      Recently, one of us wrote about the new product development analytics used by Netflix. In a nutshell, the company classified the key attributes of past and current products or services and then they modeled the relationship between those attributes and the commercial success of the offerings. This produced a predictive model that provides the company with guidance about how likely a new product or service is to be successful.

       

      Netflix is not alone in this respect. Procter & Gamble also uses predictive analytics to introduce new products faster than the competition, and the company works diligently on predicting the likelihood of market success for these products. The company integrates virtual reality and 3D design tools to create realisticvirtual prototypes. Moreover, P&G uses data and analytics from focus groups, social media, test markets, and early store rollouts to plan, produce, and launch new products.

       

      As P&G and others have discovered, there is more to commercial success than new product selection.

      New product development is a broad process, with many steps. There is little doubt that smarter decisions are necessary in the entire process;

      a Deloitte study, for example, found that 96 percent of product innovations fail to return the cost of capital, and two thirds fail within two years.

       

      The power of predictive analytics is multiplied when an organization takes an end-to-end process view of new product development (NPD). Idea generation and business case decision making are important. But an end-to-end view of performance in a business-process context provides additional opportunities to apply predictive analytics to improve performance in other areas, such as product development, testing, and launch.

      The new product development process

      The new product development process.

      Analytical methods apply to each of these steps. For example, in the area of product creation, it’s possible to improve performance by classifying key attributes of past success – such as early supplier involvement, broad cross-functional collaboration, use of key metrics to move from one gate to the next, etc. – and then model the relationship between those attributes and the commercial success of the offerings.

       

      Similarly, in the area of new product testing, it’s possible to improve performance by classifying key attributes of past success – such as customer involvement, sales force collaboration, and key metrics, etc. – and then model the relationship between those attributes and the commercial success of the offerings. The same principles apply to planning and executing product launches, where a set of key attributes of past success can provide insight into what needs to be done to assure future success. The key in all of these areas is to collect data on attributes of the NPD process and then relate them to product success in the marketplace. This requires consistency, discipline, and a long-term perspective.

      By taking a process-based view of the performance of NPD, organizations can improve their ability to view things form their customer’s perspective.

      For example, the typical company cares a lot about the cost of new product development and the ROI on their investment, while customers care mostly about other things such as value for money, on-time product introduction (when promised), and quality (works right first time). By taking a customer focused, business-process-based view, organizations can gain new insights into why their NPD performance is below expectations. Analytics can play a big role in overcoming the major obstacles to decision making in NPD, as identified in an Aberdeen Group survey.

       

      As the Aberdeen survey suggests, part of the problem with NPD analytics is that systems that supply data for new product development are fragmented and incomplete. Much of the data necessary for assessing customer demand and competitive responses is external to an organization. Some vendors, such as Signals Group (disclosure: Tom Davenport is an adviser to the company), are now offering systems and external information that support the entire NPD process. In addition, the rise of product lifecycle management (PLM) software from vendors like PTC, Autodesk, Dassault Systems, and Siemens has made it easier to access data from internal systems. PLM data is commonly used for reporting, but it is rarely employed for predictive analytics.

       

      We are just at the beginning of the use of analytics for NPD. Examples such as the Netflix case should spur organizations to begin using these tools to develop more successful new products. From the beginning, however, organizations should adopt an end-to-end process perspective on NPD analytics so that they don’t optimize only a single aspect of the process.

      ______________________________________

       

      Tom Davenport, the author of several best-selling management books on analytics and big data, is the President’s Distinguished Professor of Information Technology and Management at Babson College, a Fellow of the MIT Initiative on the Digital Economy, co-founder of the International Institute for Analytics, and an independent senior adviser to Deloitte Analytics. He also is a member of theData Informed Board of Advisers.

       

      Andrew Spanyi, the author of three books on process improvement and management, is the Founder of Spanyi International Inc.  He has worked in the area of process management for over two decades and he is on the Advisory Board for the Association of Business Process Management Professional (ABPMP). He is also the Editorial Director for BPMInstitute.org.

       

       

      This blog first appeared in DataInformed June 16, 2016 here.

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