Why Some Platforms Thrive... (PDF)

Why Feng Zhu Professor, Harvard Business School strategy Some Marco Iansiti Professor, Harvard Bu...

Why Feng Zhu Professor, Harvard Business School strategy Some Marco Iansiti Professor, Harvard Business School Platforms Thrive... and What Alibaba, Tencent, and Uber teach us about networks that flourish. The five Others Don’t characteristics that make the difference. Illustrations by SHOUT Harvard Business Review January–February 2019 119  strategy Idea in Brief THE CHALLENGE It’s easier for digital platforms to achieve scale than to maintain it. i THE REASON Five basic network properties shape their scalability, profitability, and ultimately their sustainability. THE INSIGHT Analysis of these properties will help entrepreneurs and investors understand platforms’ prospects for long-term success. n 2016, Didi became the world’s largest ride-sharing company, reaching 25 million trips a day in China and surpassing the combined daily trips of all other ride- sharing companies across the globe. It had arrived at this milestone by merging in 2015 with its domestic rival, Kuaidi, and pushing Uber out of the Chinese market after a fierce, expensive battle. With its competition gutted, Didi gradually began to improve its margins by reducing subsidies to drivers and passengers. 120 Harvard Business Review January–February 2019  Video game consoles exhibit weak network effects. The total number of game titles available isn’t as important as having a few of the right games. So an entrant with only a small technical advantage can steal significant market share. But just as the company began to reach profitability, operation. Lasting competitive advantage hinges more in early 2018, Meituan, a giant player in online-to-offline on the interplay between the platform and the network it services such as food delivery, movie ticketing, and travel orchestrates and less on internal, firm-level factors. In other booking, launched its own ride-hailing business in Shanghai. words, in the digitally connected economy the long-term Meituan didn’t charge drivers to use its platform for the first success of a product or service depends heavily on the three months and afterward took only 8% of their revenues, health, defensibility, and dominance of the ecosystem in while Didi took 20%. Drivers and passengers flocked to the which it operates. new service. In April, Didi struck back by entering the food And as Didi is learning, it’s often easier for a digital delivery market in Wuxi, a city close to Shanghai. What platform to achieve scale than to sustain it. After all, the followed was a costly price war, with many meals being sold advantages that allow the platform to expand quickly work for next to nothing because of heavy subsidies from both for its competitors and anyone else who wants to get into the companies. So much for Didi’s profitability. market. The reason that some platforms thrive while others Didi was taking other hits too. In March 2018, Alibaba’s struggle really lies in their ability to manage five fundamen- mapping unit—Gaode Map, the largest navigation service in tal properties of networks: network effects, clustering, risk China—had started a carpooling business in Chengdu and of disintermediation, vulnerability to multi-homing, and Wuhan. It didn’t charge drivers at all, and in July it began bridging to multiple networks. offering passengers the option of ordering from several ride-hailing services. Meanwhile, Ctrip, China’s largest Strength of online travel service, had announced in April that it had been granted a license to provide car-hailing services Network Effects across the country. The importance of network effects is well known. Econo- Why hadn’t Didi’s immense scale shut down its compe- mists have long understood that digital platforms like Face- tition for ride services in China? Why wasn’t this a winner- book enjoy same-side (“direct”) network effects: The more take-all market, as many analysts had predicted? Moreover, Facebook friends you have in your network, the more likely why do some platform businesses—such as Alibaba, Face- you are to attract additional friends through your friends’ book, and Airbnb—flourish, while Uber, Didi, and Meituan, connections. Facebook also leverages cross-side (“indirect”) among others, hemorrhage cash? What enables digital network effects, in which two different groups of partici- platforms to fight off competition and grow profits? pants—users and app developers—attract each other. Uber To answer those questions, you need to understand the can similarly mine cross-side effects, because more drivers networks a platform is embedded in. The factors affecting attract more riders, and vice versa. the growth and sustainability of platform firms (and digital Less well acknowledged is the fact that the strength of net- operating models generally) differ from those of traditional work effects can vary dramatically and can shape both value firms. Let’s start with the fact that on many digital networks creation and capture. When network effects are strong, the the cost of serving an additional user is negligible, which value provided by a platform continues to rise sharply with makes a business inherently easier to scale up. And because the number of participants. For example, as the number of much of a network-based firm’s operational complexity is users on Facebook increases, so does the amount and variety outsourced to the service providers on the platform or of interesting and relevant content. Video game consoles, handled by software, bottlenecks to value creation and however, exhibit only weak network effects, as we discov- growth usually aren’t tied to human or organizational ered in a research study. This is because video games are a factors—another important departure from traditional hit-driven business, and a platform needs relatively few hits models. Ultimately, in a digital network business, the to be successful. The total number of game titles available employees don’t deliver the product or service—they isn’t as important in console sales as having a few of the right just design and oversee an automated, algorithm-driven games. Indeed, even an entrant with only a small technical Harvard Business Review January–February 2019 121  strategy advantage (and a good business development team) can steal significant market share from incumbents. That explains Network Clustering why in 2001 Microsoft’s new Xbox posed such a threat to In a research proj­ect with Xinxin Li of the University of Sony’s then-dominant PlayStation 2, and why each console Connecticut and Ehsan Valavi, a doctoral student at Harvard has gone up and down in market share, alternately taking the Business School, we found that the structure of a network lead, over the years. influences a platform business’s ability to sustain its scale. Even more critically, the strength of network effects can The more a network is fragmented into local clusters—and change over time. Windows is a classic example. During the more isolated those clusters are from one another—the the heyday of personal computers in the 1990s, most PC more vulnerable a business is to challenges. Consider Uber. applications were “client based,” meaning they actually Drivers in Boston care mostly about the number of riders lived on the computers. Back then, the software’s network in Boston, and riders in Boston care mostly about drivers effects were strong: The value of Windows increased in Boston. Except for frequent travelers, no one in Boston dramatically as the number of developers writing apps for it cares much about the number of drivers and riders in, say, climbed, topping 6 million at the peak of its popularity. By San Francisco. This makes it easy for another ride-sharing the late 1990s Windows seemed entrenched as the leading service to reach critical mass in a local market and take platform. However, as internet-based apps, which worked off through a differentiated offer such as a lower price. across different operating systems, took off, the network Indeed, in addition to its rival Lyft at the national level, Uber effects of Windows diminished and barriers to entry fell, confronts a number of local threats. For example, in New allowing Android, Chrome, and iOS operating systems to York City, Juno and Via, as well as local taxi companies, are gain strength on PCs and tablets. Mac shipments had also giving it competition. Didi likewise faces a number of strong begun to rise in the mid-2000s, increasing more than five- contenders in multiple cities. fold by the end of the decade. This turn of events illustrates Now let’s compare Uber’s market with Airbnb’s. Travelers that when an incumbent’s network effects weaken, so does don’t care much about the number of Airbnb hosts in their its market position. home cities; instead, they care about how many there are in It is possible for firms to design features that strengthen the cities they plan to visit. Hence, the network more or less network effects, however. Amazon, for example, has built is one large cluster. Any real challenger to Airbnb would have multiple types of effects into its business model over the to enter the market on a global scale—building brand aware- years. In the beginning, Amazon’s review systems gener- ness around the world to attract critical masses of travelers ated same-side effects: As the number of product reviews and hosts. So breaking into Airbnb’s market becomes much on the site increased, users became more likely to visit more costly. Amazon to read the reviews as well as write them. Later, It’s possible to strengthen a network by building global Amazon’s marketplace, which allows third parties to sell clusters on top of local clusters. While Craigslist, a classified products to Amazon users, generated cross-side network ad site, primarily connects users and providers of goods and effects, in which buyers and third-party sellers attracted services in local markets, its housing and job listings attract each other. Meanwhile, Amazon’s recommendation system, users from other markets. Facebook’s social games (like which suggests products on the basis of past purchase FarmVille) established new connections among players who behavior, amplified the impact of the company’s scale were strangers, creating a denser, more global, more inte- by continually learning about consumers’ preferences. grated network, which is easier to defend from competition. The more consumers used the site, the more accurate the Both Facebook and WeChat, a popular social-networking recommendations Amazon could provide them. While app in China, have been enhancing their networks by getting not usually recognized as a network effect per se, learning popular brands and celebrities—those with national and effects operate a lot like same-side effects and can increase often international appeal—to create public accounts and barriers to entry. post and interact with users. 122 Harvard Business Review January–February 2019  Which Network Structure Is More Defensible? Some digital networks are fragmented into local clusters of users. In Uber’s network, riders and drivers Airbnb Uber interact with network members outside their home cities only occasionally. But other digital networks are global; on Airbnb, visitors regularly connect with hosts around the world. Platforms on global networks are much less vulnerable to challenges, because it’s difficult for new rivals to enter a market on a global scale. Risk of Disintermediation saw this effect in a study of an online freelance marketplace. As the platform improved its reputation-rating system, trust Disintermediation, wherein network members bypass a hub between clients and freelancers grew stronger, and disin- and connect directly, can be a big problem for any platform termediation became more frequent, offsetting the revenue that captures value directly from matching or by facilitating gains from better matching. transactions. Imagine that you hire a house cleaner from a Some platforms address disintermediation risks by platform like Homejoy and are satisfied with the service. introducing different strategies for capturing value—with Would you really go back to Homejoy to hire the same person varying results. Thumbtack, a marketplace connecting con- again? If a user has found the right match, there’s little incen- sumers with local service providers such as electricians and tive to return to the platform. Additionally, after obtaining guitar teachers, charges for lead generation: Customers post enough clients from a platform to fill his or her schedule, the requests on the site, and service providers send them quotes house cleaner won’t need that platform anymore. This was and pay Thumbtack fees if those customers respond. That exactly the problem that doomed Homejoy, which shut down model captures value before the two sides even agree to work in 2015, five years after it was founded. together and has helped save the company from withering Platforms have used various mechanisms to deter disin- like Homejoy. Thumbtack today is handling over $1 billion termediation, such as creating terms of service that prohibit worth of transactions annually. The downside of its revenue users from conducting transactions off the platform, and model is that it doesn’t prevent the two sides from building a blocking users from exchanging contact information. Airbnb, long-term relationship outside the platform after a match. for example, withholds hosts’ exact locations and phone Alibaba took a different approach with its Taobao numbers until payments are made. Such strategies aren’t e‑commerce platform. When Taobao entered the market, in always effective, though. Anything that makes a platform 2003, eBay’s EachNet had more than 85% of the Chinese more cumbersome to use can make it vulnerable to a com- consumer-to-consumer market. However, Taobao didn’t petitor offering a streamlined experience. charge listing or transaction fees and even set up an instant- Some platforms try to avoid disintermediation by messaging service, Wangwang, that allowed buyers to ask enhancing the value of conducting business on them. They questions directly of sellers and haggle with them in real time. may facilitate transactions by providing insurance, payment In contrast, EachNet charged sellers transaction fees and, escrow, or communication tools; resolve disputes; or monitor because it was concerned about disintermediation, didn’t activities. But those services become less valuable once trust allow direct interactions between buyers and sellers until a develops among platform users—and the strategies can back- sale had been confirmed. Not surprisingly, Taobao quickly fire as the need for the platform decreases. One of us, Feng, took over leadership of the market, and at the end of 2006, and Grace Gu, a doctoral student at Harvard Business School, eBay shut down its Chinese site. Taobao today continues to Harvard Business Review January–February 2019 123  strategy offer its C2C marketplace services free of charge and captures value through advertising revenues and sales of storefront software that helps merchants manage their online businesses. After estimating that it could lose as much as 90% of its business to disintermediation, the Chinese outsourcing marketplace ZBJ, which launched in 2006 with a model of charging a 20% commission, began looking for new revenue sources. In 2014 it discovered that many new business owners used its site to get help with logo design. Typically, the next job those clients would need done was business and trademark registration, which the platform started to offer. Today ZBJ is the largest provider of trademark registration in China—a ser- vice that generates more than $70 million in annual revenue for the firm. The company has also significantly reduced its transaction fees and focused its resources on growing its user base instead of fighting disintermediation. As the experience of ZBJ, which is now valued at more than $1.5 billion, shows, when disintermediation is a threat, providing complementary services can work a lot better than charging transaction fees. Vulnerability to Multi-Homing of trips in a row without rejecting or canceling any or going Multi-homing happens when users or service providers offline during peak hours. And while rides are in prog­ress, (network “nodes”) form ties with multiple platforms (or both platforms provide drivers new requests for pickups “hubs”) at the same time. This generally occurs when very close to current passengers’ drop-off locations, reduc- the cost of adopting an additional platform is low. In the ing the drivers’ idle time and hence the temptation to use ride-hailing industry, many drivers and riders use both, say, other platforms. Yet because of the inherently low cost of Lyft and Uber—riders to compare prices and wait times, and adopting multiple platforms, multi-homing is still rampant drivers to reduce their idle time. Similarly, merchants often in ride sharing. work with multiple group-buying sites, and restaurants with Attempts to prevent multi-homing can also have unin- multiple food-delivery platforms. And even app developers, tended side effects. In one research proj­ect, Feng and Hui Li whose costs are not trivial, still find it makes sense to develop of Carnegie Mellon University examined what happened in products for both iOS and Android systems. 2011 when Groupon retooled its deal counter—which tracks When multi-homing is pervasive on each side of a the amount of people who have signed up for a specific offer platform, as it is in ride hailing, it becomes very difficult for a on its site—to show ambiguous ranges, rather than precise platform to generate a profit from its core business. Uber and numbers. It then became more difficult for LivingSocial Lyft are constantly undercutting each other as they compete to identify and poach the popular merchants on Groupon. for riders and drivers. As a result, LivingSocial started to source more exclusive Incumbent platform owners can reduce multi-homing deals. While Groupon was able to reduce merchant-side by locking in one side of the market (or even both sides). To multi-homing, the research found, consumers became more encourage exclusivity, both Uber and Lyft gave bonuses in likely to visit both sites, because there were fewer overlap- many markets to people who completed a certain number ping deals on them, and it cost little to multi-home. That 124 Harvard Business Review January–February 2019  FURTHER READING “Managing Our Hub Economy” “Alibaba and the Marco Iansiti and Future of Business” Karim R. Lakhani Ming Zeng HBR, September–October 2017 HBR, September–October 2018 finding points to a key challenge platform firms face: mutually reinforce one another’s market positions, helping Reducing multi-homing on one side of the market may each network sustain its scale. Indeed, even after the rival increase multi-homing on the opposite side. platform Tencent offered a competing digital wallet service, Other approaches seem to work better. Let’s look again at WeChat Pay, through its app WeChat, Alipay remained attrac- the video game industry: Console makers often sign exclusive tive to consumers and merchants because of its tight bridging contracts with game publishers. On the platforms’ user side, with Alibaba and Ant Financial’s other services. the high prices of consoles and subscription services, such as As the most successful platforms connect across more and Xbox Live and PlayStation Plus, reduce players’ incentives to more markets, they’re becoming increasingly effective at tying multi-home. Lowering multi-homing on both sides of the mar- together industries. Just as the Alibaba Group moved from ket decreased competitive intensity and allowed the console commerce to financial services, Amazon has moved beyond makers to be profitable. Amazon, which provides fulfillment retail to entertainment and consumer electronics. Platforms services to third-party sellers, charges them higher fees when are thus becoming crucial hubs in the global economy. their orders are not from Amazon’s marketplace, incentivizing them to sell exclusively on it. Amazon Prime, which gives sub- WHEN EVALUATING AN opportunity involving a platform, scribers free two-day shipping on many products, helps the entrepreneurs (and investors) should analyze the basic company reduce online shoppers’ tendency to multi-home. properties of the networks it will use and consider ways to strengthen network effects. It’s also critical to evaluate the Network Bridging feasibility of minimizing multi-homing, building global net- work structures, and using network bridging to increase scale In many situations the best growth strategy for a platform while mitigating the risk of disintermediation. That exercise may be to connect different networks to one another. In will illuminate the key challenges of growing and sustaining any platform business, success hinges on acquiring a high the platform and help businesspeople develop more-realistic number of users and amassing data on their interactions. assessments of the platform’s potential to capture value. Such assets can almost invariably be valuable in multiple As for Didi and Uber, our analysis doesn’t hold out much scenarios and markets. By leveraging them, firms that have hope. Their networks consist of many highly local clusters. succeeded in one industry vertical often diversify into differ- They both face rampant multi-homing, which may worsen as ent lines of business and improve their economics. This is a more rivals enter the markets. Network-bridging opportuni- fundamental reason why Amazon and Alibaba have moved ties—their best hope—so far have had only limited success. into so many markets. They’ve been able to establish bridges just with other highly When platform owners connect with multiple networks, competitive businesses, like food delivery and snack vending. they can build important synergies. Alibaba successfully (In 2018 Uber struck a deal to place Cargo’s snack vending bridged its payment platform, Alipay, with its e-commerce machines in its vehicles, for instance.) And the inevitable platforms Taobao and Tmall, providing a much-needed rise of self-driving taxis will probably make it challenging for service to both buyers and sellers and fostering trust between Didi and Uber to sustain their market capitalization. Network them. Alibaba has also taken advantage of transaction and properties are trumping platform scale. user data from Taobao and Tmall to launch new offerings HBR Reprint R1901J through its financial services arm, Ant Financial—including a credit-rating system for merchants and consumers. And information from that rating system allowed Ant Financial FENG ZHU is the Piramal Associate Professor of Business to issue short-term consumer and merchant loans with very Administration at Harvard Business School. MARCO IANSITI is low default rates. With those loans, consumers can purchase the David Sarnoff Professor of Business Administration at Harvard more products on Alibaba’s e-commerce platforms, and Ali- Business School. He has advised many companies in the technology baba’s merchants can fund more inventory. These networks sector, including Microsoft, Facebook, and Amazon. Harvard Business Review January–February 2019 125 Copyright 2019 Harvard Business Publishing. All Rights Reserved. Additional restrictions may apply including the use of this content as assigned course material. Please consult your institution's librarian about any restrictions that might apply under the license with your institution. For more information and teaching resources from Harvard Business Publishing including Harvard Business School Cases, eLearning products, and business simulations please visit hbsp.harvard.edu.