Seeing the Real Odds When You
Don’t Innovate Alone
Collaborate. Cooperate. Co-create. Co-innovate. The calls to leverage the efforts and capabilities of others in order to accelerate the path to profitable growth are growing louder and louder. Organizations across a wide range of industries have discovered new ways to stitch together a complex web of partners and offer superior value propositions to consumers. The ability to create and manage these innovation ecosystems inspires amazement and praise from customers, and admiration and fear among rivals.
For many companies, however, these co-innovation attempts are costly failures, characterized by broken promises and missed expectations. Why? Because when you rely on partners to enable your success, your success becomes vulnerable to your partners’ progress. Delays and compromises are more likely to occur when the work depends on cooperation.
Competent managers know that success requires obsessive focus on capabilities, customers, and the competition. But too often they fall victim to the blind spot of Co-innovation Risk. While managers have rich processes in place to assess and manage their own execution challenges (“What do I need to do to deliver my project on time, to spec, ahead of the competition?”), they do not fully understand their dependence on their partners’ co-innovation challenges (“What are the hurdles facing the other innovations that must come about for my project to succeed?”).
Regardless of the nature of the complementary innovation—technological (a better battery for electric cars); procedural (a new quality assurance process, a new service interaction); organizational (an integrated selling approach that combines offers from multiple divisions)—co-innovation risk transforms the odds of success. In this chapter we will use Nokia’s journey in 3G telephony to uncover the logic of co-innovation risk, and identify paths to overcome it.
Great Expectations: Telecom in the ’90s
The first generation of commercial mobile telephony emerged in the 1980s. An analog network with devices that were bulky, expensive, and slow, it was primarily used by governments, law enforcement, and the military. The second generation of mobile telephony (2G) was rolled out in the early 1990s. Based on digital signals, this new network was much faster and capable of transmitting both voice and small amounts of data, such as Short Message Service (SMS) text messages. The technology of 2G made it both possible and affordable for mainstream consumers to own a small handset that allowed them to call virtually anyone, anytime, from anywhere. After fifteen years of incubation in niche segments, cellular phones had finally hit the mass market.
Figure 2.1: Motorola’s DynaTAC 8000x was the world’s first portable handheld cellular phone. Introduced in 1983, the phone weighed 1.75 pounds, supported 30 minutes of talk time after 10 hours of charging, and retailed for $3,995. (© Motorola Mobility, Inc., Legacy Archives Collection. Reproduced with permission.)
The 1990s were the heyday of mobile telecom. Across the sector all the players—telecom operators, infrastructure providers, and handset makers—were enjoying record growth and profits thanks to one of the largest explosions of technology in history. Nowhere was this more concentrated than in Scandinavia, where two of the largest players, Finland’s Nokia and Sweden’s Ericsson, lived and competed side by side. Global cell phone use had exploded, and by the year 2000, mobile network operators had over 700 million users around the world.
It was a good time to be at either company, and Jorma Ollila, then CEO of Nokia, presided over an unprecedented wave of growth with sales of mobile systems and handsets growing at 50 percent a year.
But by 1999, leading players across the globe—Nokia and Ericsson in Europe, NEC and Samsung in Asia, and Motorola in the United States—were all bumping up against an unpleasant reality. Customers were beginning to take for granted the incredible technology that allowed for mobile communications, and new rivals were rushing into the space on all sides as barriers to entry fell. In Western Europe the problem was particularly acute. Already almost 70 percent of adults had a mobile phone, which left little room for growth in new customers. How could consumers be convinced not just to trade in their perfectly functional old phones for an updated version, but to be willing to spend significantly more on their next handset? What was Nokia to do to sustain profitable growth?
Nokia’s solution, and the industry consensus, was 3G—a third generation of mobile communications that would enable not just voice but streaming data. Proponents envisioned a world in which consumers could talk on their phone, watch video, and conduct mobile commerce. Suddenly, your phone was not just a phone; it was a portable Internet device, capable of connecting you 24/7 to the World Wide Web.
“This next stage in the growth of the communications business will be in the mobile multimedia and location-based services,” predicted Keiji Tachikawa, the president of NTT DoCoMo—Japan’s leading mobile provider. His company would become the first to launch a global 3G network.
“Just as we did not foresee the development of e-mail, the World Wide Web or other popular services when the PC was first introduced, we do not know what services will eventually emerge for 3G,” said Yrjö Neuvo, executive vice president and chief technology officer at Nokia’s mobile phones division in Helsinki. “But we do know that they will come faster” than they did for the PC. In late 2000, articulating the general expectation, Kurt Hellström, Ericsson’s CEO, predicted a 3G surge, boldly proclaiming that by 2003, the 3G business would match the size of Ericsson’s 2G business.
In this brave new world of 3G, everyone would win. Telecom operators would be able to charge a premium for the extra service, which would make up for declining voice traffic revenues, and handset makers could sell everyone new phones that supported the technology. Customers were thrilled by the prospect of the portable Web, and analysts praised companies for embracing a bold new (and profitable) future. Governments were excited by the prospect of auctioning off spectrum rights—the permission operators would need to transmit their signals—to the highest bidders. And content partners like ESPN, CNN, and the BBC were enthusiastic about the prospect of new revenue streams enabled by delivering information to consumers anytime, anywhere. In a 2000 article, even the historically austere Economist embraced the excitement and expectations for “the intoxicating combination of two of the fastest-growing technologies of all time: the mobile telephone (perhaps a billion subscribers worldwide by 2003) and the Internet (more than 400 million predicted users by 2003). Put those together . . . and you have the justifications for 3G fervor.”
In the rush to bid for 3G licenses in Europe, telecom operators spent more than $125 billion in government-run auctions for spectrum rights. They then spent an estimated additional $175 billion to build out their networks, one-by-one updating the radio towers all across Europe to work on a 3G network. The excitement was palpable, and the expectations were huge.
Armed with this knowledge, Nokia entered the fray to deliver the first 3G handset to the European market. It believed its competition with Ericsson was a classic race for first-mover advantage: that operators and customers would embrace the first quality device to market. But focused as they were on executing better than their competition, they were blindsided by co-innovation risk. As Nokia, and the entire sector, would learn: this was just a race to the starting line. They would need to wait there for years before co-innovators were ready and the real race to profits could begin. Had they used a wider lens, they would have done things differently.
Building a 3G Phone
Nokia had been working on 3G prototypes since the early 1990s, when the early protocols for 3G were being established in Europe. But even with deep expertise in the handset market, the challenges kept growing. It was hard enough to build a 2G phone that could smoothly handle bouncing radio signals from one base station to another, stay powered all day, and fit into a user’s pocket. Delivering a functioning 3G phone entailed heroic innovation efforts on the part of handset makers and their entire supply chain. As one observer noted, “The 3G handsets, on which Europe has wagered much of its tech future, are by far the most complex consumer electronics devices ever designed. To succeed, they must combine the wealth of applications available on a computer with the roving versatility of a mobile phone. The trick is to wedge all of this into a sleek little machine equipped with multiple radio bands and days and days of battery life—and it must sell at an affordable price.”
It was a huge execution challenge, but in the end, Nokia did it. When the company launched the 6650 phone in 2002, it became the world’s first GSM/WCDMA-compliant (compatible with networks throughout Europe and Asia) 3G handset maker. The celebration was intense. They had delivered the product. They had beaten Ericsson. They were first!
But the euphoric welcome for the 3G handset innovation would prove to be completely out of step with the new world that 3G represented. In 2000, Nokia had forecast that by 2002 more than 300 million handsets would be connected to the mobile Internet. The actual number was closer to 3 million (with the vast majority on Japan’s NTT closed DoCoMo network, using DoCoMo—not Nokia—phones). The 300 million target was eventually reached, but not until 2008—a six-year delay that set back not just market adoption but, even more painfully, revenues, profits, and growth.
At the root of Nokia’s mistake was a fundamental misunderstanding of co-innovation risk. The company did not fully appreciate just how dependent the success of its magnificent handset was on the successful commercialization of other innovations yet to be developed by a host of unfamiliar partners. The 3G vision was not one of new and better handsets. It was a vision of an entire mobile lifestyle—personalized videos streamed to your phone, location-based services, automated payment systems, applications to empower a mobile workforce—that was enabled by new and better handsets. But unless and until these other partners delivered on their innovations, Nokia’s 3G handset would create about as much new value as a $400 paperweight.
Assessing Risk
Nokia was a brilliant, innovative company at the height of its powers in the 1990s. And yet it fell into what, in retrospect, seems like an obvious trap. It won its race but missed its goal. How could they get it so wrong? It was not because they underinvested. It was not because executives were undermotivated. And it was not because managers lacked competence. It was because they focused all their energy on executing their own projects and commitments. This is of course admirable, but when your commitments depend on other developments for their success, “simply” executing on your job is not enough.
A lot of things have to be managed, and managed well, for a project to succeed. In assessing execution risk—the magnitude of the challenge associated with completing the project on time and to spec—leaders often have to manage not only their own teams but also an array of other suppliers who provide critical inputs to the project. For example, delivering a 3G handset would require Nokia to develop radically new algorithms for signal processing, new circuit designs for power management, new interface designs, etc., all of which it was capable of doing on its own. But it would also require Nokia’s suppliers to develop new chipsets, more robust memories, batteries . . . the list goes on.
Project managers obsess over specifications and deadlines, finding ways to close the gap between where they are today and where they need to be by a certain date. Aligning, motivating, and cajoling the right people to get on the right team with the right resources is the hallmark of execution. Nokia succeeded in all of these areas, and the company’s ability to deliver its 3G handset was impressive.
Driving the transition from 1G to 2G handsets required just this sort of heroic effort from handset makers. And achieving differentiation in the heyday of 2G was similarly a matter of innovative design integrating innovative components. Here, successfully managing execution risk—delivering better, sleeker handsets with longer battery life and better screens—translated into project success. As soon as a great handset was launched, it was embraced by mobile operators who then passed it on to end users. In the 2G world, the winning formula was both familiar and clear: deliver the right project, on time, to spec, ahead of your rival.
The transition to 3G, however, was of a qualitatively different nature. With 3G, a handset’s value creation depended not just on its own quality but also on the quality and availability of a broad variety of complementary products and services that were key enablers of the vision of mobile data. Here, managing execution risk is necessary, but far from sufficient, to ensure project success. The critical consideration for a handset maker in a 3G world is not just whether it can successfully innovate and deliver a 3G phone, but whether and when actors other than handset makers are going to successfully deliver their own innovations to make the 3G mobile data service vision a reality.
Figure 2.2. Elements of execution risk for a 2G mobile handset.
Consider what it means to offer a service like customized streaming video that delivers live clips of the customer’s favorite sporting events. This is exactly the sort of value-added subscription-based service that was expected to attract users in droves to the 3G network. Of course you need a smartphone. But what else?
You need video conversion software to reformat television images to fit different sized mobile phone screens. Who makes that? Not Nokia.
You need database and router innovations that will allow operators like France Telecom and Vodafone to know which customers signed up for which streams, on which payment plans. Who makes that? Not Nokia.
You need a digital rights management (DRM) solution to assure content owners like ESPN and Disney that their precious intellectual property will not be pirated in the ether. Who makes that? Not Nokia.
Figure 2.3: Execution risk and co-innovation risk for a 3G handset in the real-time streaming video case.
When your ability to successfully commercialize your innovation depends on your partners’ ability to successfully commercialize their own innovations, your approach to assessing and managing risk must change. The extent of your co-innovation risk depends on the joint probability that each of your partners will be able to satisfy their innovation commitments within a specific time frame. How should you assess the probability of success?
Most organizations have an established routine for conducting due diligence—consulting with their managers, double-checking with their suppliers, examining their historical precedents—to develop a confidence level about the likelihood of an initiative’s successful completion (to spec, on time). In ecosystem settings, you must undertake this same level of due diligence with all co-innovators. But it is the way you integrate your separate findings that will shift your perspective.
Imagine yourself at a meeting with three partners to discuss the attractiveness of a potential collaboration. All of you commit to assigning your organization’s best resources to your respective initiatives, and all believe that the likelihood of delivering your part of the solution within one year is very high—85 percent. Assume that these individual estimates are accurate. How confident should you be in the success of this joint venture?
The logic of co-innovation is a logic of multiplication, not averages. The nature of joint probability is that the true likelihood of an event taking place equals the product (not the average) of the underlying probabilities. For example, if I flip a coin, I have a 50 percent chance that it will land on heads. If I flip it four times, I still have a fifty percent chance that it will land on heads in each independent instance, but I have only a 6.25 percent chance that it will land on heads all four times (.5 × .5 × .5 × .5). The same rules apply in co-innovation. While each supplier has a better than eight-in-ten chance of succeeding independently, the chance that they will all jointly succeed at the end of the year is the product of their independent probabilities. In this case, it is 0.85 × 0.85 × 0.85 × 0.85, or 52 percent.
Fifty-two percent. Imagine your typical project review meetings—where everyone is confident in his ability to get the job done. How common is it for confident managers to recognize the frailty of their joint effort?
Now suppose that one of these partners is responsible for a particularly challenging development effort and that his probability of success is 20 percent? With just one weak link among the four, the joint probability tumbles to 0.85 × 0.85 × 0.85 × 0.2, or 12 percent.
Figure 2.4: The difference between independent and joint probabilities.
Twelve percent—let that sink in (but don’t let it sink you). Is 12 percent a bad number? No. There is no such thing as a bad number. There are only bad expectations. Twelve percent is fine, as long as you understand the true probability of success and make your choices based on this knowledge. If the loss is affordable, and there is learning to be had, then maybe it’s a worthwhile bet. If the potential payoff is twenty to one, then a 12 percent bet can be very attractive indeed. There is no problem with making a 12 percent bet, as long as you know it’s a 12 percent bet. The key is to understand the true probability in advance and make sure that, with full knowledge of the risks, you still want to take the bet.
Problems arise when we gloss over co-innovation risk, when we fall into the trap of averages, believing that “since my own initiative has a high chance of succeeding, and since my other three partners are confident too, the total venture is pretty secure.” The trouble begins when we make a 12 percent bet but think that the odds are 85 percent.
Managing Co-innovation Risk
For investors, identifying co-innovation risk is the key to making smarter bets. For managers, identifying co-innovation risk opens up new avenues for action. Beyond the go/no-go decision, recognizing co-innovation risk can also affect the way in which you develop your strategy and manage your initiative. What are some risk-mitigating actions you can take if you see that one or more partners may diminish your chance of success?
One clear option is to add resources—money, talent, or both—to bolster development effort. But whose efforts should you support? Deploying resources to reinforce a weak link in the chain can have a much greater impact on your success than reinforcing your own innovation. A 10 percent increase in your own chances (from 85 percent to 95 percent) may reduce team anxiety, but it moves the joint probability by only 2 percent (from 12 percent to 14 percent). In contrast, increasing your weakest partner’s chances by 10 percent (from 20 percent to 30 percent) changes the joint probability by 6 percent (from 12 percent to 18 percent). The number may look low, but it’s one and a half times as likely to succeed than the initial configuration, and also substantially more likely to succeed than if you focused your efforts in-house. With the joint probabilities becoming clear, it may even make sense to take resources away from your project to bolster the overall effort: if reallocating resources can improve your partner’s chances (from 20 percent to 30 percent) proportionally more than it decreases your own (say, from 85 percent to 75 percent), then you will be increasing the likelihood of success to 16 percent.
Alternatively, you could consider deploying resources to entice multiple parties to work on the same challenge: if we have two partners, each with an independent 20 percent chance, working on the same problem, the expected probability of solving the challenge doubles. The likelihood of success is now 24 percent.
Another option is to reevaluate the vision in order to deliver, at least initially, a more modest value proposition. If your weak link has a probability of success of 20 percent, your total probability is brought down to 12 percent. If you divest yourself of this link altogether—for example, giving up on the notion of customized streaming video content and, instead, settling for noncustomized video channels, which would eliminate the need for the database innovation—then you eliminate its impact on your odds. The probability rises to 61 percent. There is a clear trade-off here: a higher chance of succeeding with a more limited value proposition. But, in some cases, it’s better to accept a smaller win than to risk losing the game entirely. Whether this is the right choice in a given situation will depend on how well your organization can accept risk and how much is at stake with a particular innovation.
Finally, recall that these probabilities do not characterize whether a development effort will ever succeed. With more time and resources, odds increase. Rather, these probabilities characterize whether an effort will succeed in a given time frame. As such, a final lever to manipulate is expectations regarding timing. Opting for a less aggressive timeline may go against the grain, but it gives your slower co-innovators the chance to catch up.
An important note: these numerical values illustrate the argument. In real life, of course, we don’t have access to such precise probabilities. We can, however, use simple assessments of risk—a one-to-five scale or high/medium/low risk across the system—and apply the same logic. In settings where risk levels are more difficult or costly to specify, going through this exercise will help identify which risk components would be of greatest value to explore in depth.
The key is not the numbers. These are here to clarify the intuition of what it means to manage in a world of dependence and joint probabilities. The key is to identify co-innovation risk and its potential effects. With a narrow focus on execution risk, these effects and these choices are hard to see and therefore hard to manage. When we use a wider lens to identify co-innovation risks more clearly, our approach to many strategic choices—scope, timing, partnering, leadership—changes dramatically.
Nokia won the race for the 3G phone, but it was the wrong race. In late 2002, Nokia was first to market with the release of the 6650 in Europe, and in North America soon after. It was a hollow prize. The real race could not begin until the digital services were available. The 6650 was a Ferrari in a world without roads. In the absence of critical complements, the 3G offer was but a shadow of its promised self—a souped-up 2G service rather than the radical shift into a brave new world of mobile digital data service that impelled billions of dollars in investment.
It wasn’t until the late 2000s that the vision of mobile digital services for the mass market finally began to materialize, most notably with the emergence of Apple’s iPhone in 2007. Through 2010, Nokia was the world’s biggest producer of 3G phones. But, as the “smart” in smartphone shifted from the handset hardware to software apps running on the phone, Nokia seemed unprepared. The phones were fine as products but impoverished as solutions. The very essence of the game had changed under their feet.
In his “Burning Platform” memo, outlining the dire straits facing Nokia, newly appointed CEO Steve Elop acknowledged that “the battle of devices has now become a war of ecosystems, where ecosystems include not only the hardware and software of the device, but developers, applications, ecommerce, advertising, search, social applications, location-based services, unified communications and many other things.” It is a battle in which success means attracting and retaining, beyond customers, co-innovators. In February 2011, in acknowledgment of its changed circumstances, Nokia allied with Microsoft, signing on to the latter’s Windows Phone operating system, pulling the plug on the Symbian platform it had nurtured since 1998. The future came, but it came late, and Nokia was not prepared for its implications.
Asking Not If, but When
Nokia’s 3G misadventures with co-innovation risk are far from unique. Philips Electronics’ misadventures with HDTV in the 1980s ended in failure not because the company couldn’t deliver a great television with superior picture quality—it did so beautifully. The problem was the late arrival of high-definition television cameras and transmission standards, which left Philips with a $2.5 billion write-down that shook the financial stability of the company to its core. Philips was right about the vision but wrong about the timing: HDTV was the wave of the future, but the wave didn’t arrive on the mass-market shore until the late 2000s. Unfortunately, being half right provides little comfort in the midst of overall failure. This same story is being repeated today in the saga of three-dimensional television as leading firms like Sony, LG, and Toshiba have made huge investments in a race to the start line, where they wait restlessly for the arrival of 3-D programming—which may or may not come—to unlock the market’s potential.
Too often, managers ask the wrong question when they begin their innovation journeys. In meetings and boardrooms, over lunches and drinks, the talk is focused on “Can we do it?” and “How can it be done?” Whether the vision is customized pharmaceuticals, solar energy generation, an innovative design for a drill bit, or a new line of organic-based shampoos, with enough talent, money, and time, most goals can be achieved. Like Nokia, ambitious companies will time and again set their sights on the next exciting innovation. And, like Nokia’s, success will too often prove ephemeral. Why?
The real question, is not if it can be done, but when. Not just when will we be able to complete the project, but when will we be able to align the necessary ecosystem for the complete value proposition to become a reality. The question of if speaks to success in the abstract. The question of when speaks to returns, to attractiveness, to viability in the concrete. Being right about the vision offers cold comfort if we are wrong about the timing. Bad timing expectations are a core source of innovation failure. But as we will see in chapter 6, understanding the nature of co-innovation can offer powerful clues for setting better timing expectations.
The Good News
Confronting the real odds of success can be jarring. But if we can see the risks clearly—removing them from our blind spot and placing them squarely in our focus—then we can manage them. Not knowing the real odds does not make the risk go away; it simply leads us to set unrealistic goals at the beginning and to suffer the cost of failure at the end.
Co-innovation risk doesn’t make things bad—just different. Once we understand co-innovation risk, the ways in which we prioritize opportunities and threats, the ways we think about market timing and positioning, and the ways we think about designing our offers and mitigating our risks all shift. Indeed, the very ways in which we measure and reward success all change. This is the good news: by seeing what is actually driving the odds of success, we improve our odds of success.