By suspending belief—just temporarily—Flagship employees allow themselves to imagine possibilities without constraints. Suspending belief was a behavioral trait of many scientists at Bell Labs, where inventions such as undersea cable, the transistor, and satellite communication were born of ideas raised years before they were considered technologically or scientifically feasible.14 A century before the HondaJet was designed, and about 208 miles east of the company’s Greensboro, North Carolina, development center, two brothers were busy testing their own assumption-busting airplane.
And the breakthrough potential of suspending belief is not limited to technological innovations. Think about all the business model innovations we see today that might have seemed downright crazy at one point. How many times, for instance, did you hear that people will never buy product category X over the Internet? My guess is that you never heard anyone at Amazon say it.
6. Experiment and Iterate: Suspending belief is a first step, but then you quickly need to test your hypotheses and really understand what is true (and not). Fujino first began to question the assumption about over-the-wing engine configurations after digging into some equations of aerodynamic theory contained in long-forgotten textbooks. But this was just his first step. He then tested his hypotheses through analytical calculations, computer simulations, and ultimately physical wind-tunnel tests. Likewise at Flagship: venture hypotheses are quickly tested with rigorous experiments. The point of the experiment is partly to assess validity (is this true?) but partly to point the way to different ideas. Afeyan describes the process at Flagship as converting a “what if” to “something that sounds more like ‘it turns out that you can do this.’” Ideas serve as stepping-stones to other ideas, rather than as candidates to be sorted into “winners” and “losers.”
Early experimentation is critical when questioning sacred assumptions for two reasons. The first is that some of these assumptions turn out to be true. The faster you test your logic, the faster you can discover whether you are on the right or wrong track. Going down blind alleys is part of the discovery process—but the best blind alleys are short ones! Second, as the case of Honda indicates, when you question sacred assumptions, you could face biting skepticism. Sure, you can argue your logic all you want, but, at the end of the day, rigorous experimental data is the best way to start winning converts.
7. Open Things Up: Bill Joy, the cofounder of Sun MicroSystems, once remarked, “No matter who you are, you have to remember that most of the smartest people work somewhere else.” Known as Joy’s Law, this statement reminds us that good ideas for innovation often come from outside your own organization. Sometimes the idea—in the form of a problem definition—comes from a customer, as was the case for Intel and the microprocessor. In some cases, innovative ideas come from partners. One of the most successful food innovations of all time—McDonald’s Egg McMuffin—came from a McDonald’s franchisee who was looking for a way to drive more breakfast traffic to his restaurant.15 Many innovations have their origins in the tinkering of users, a phenomenon documented extensively by Eric von Hippel of MIT.16 Mountain bikes, windsurfers, and surgical instruments are other examples where users—trying to solve their problem (or just looking for a way to have fun)—are the first to come up with innovative concepts. Some ideas come from academic laboratories, suppliers, or even competitors.
Over the past decade, companies have started to open their innovation processes at much larger scale through various types of crowdsourcing platforms. Think about the app stores where you acquire most of the applications for your smartphone. Independent software developers—not the major phone manufacturers like Apple or Samsung or operating systems providers like Microsoft or Google—create more than 99 percent of those apps. In essence, Apple, Samsung, Google, and Microsoft crowdsourced a vital part of the functionality of their products. Why did they do this? After all, these are huge enterprises with ample technical and financial resources to develop relatively simple apps. The answer is that the potential universe of apps is so massive and varied that it would be virtually impossible for any single organization—no matter how large—to figure out all the possible things one might want to do with their smartphone.
My colleague Karim Lakhani has done extensive research on these platforms and has found that they not only dramatically increase the number of people trying to solve a problem (which increases the odds of the problem being solved), but, more importantly, they increase the diversity of problem solvers.17 Contest platforms give companies access to people with skills and from geographies they may never have known or thought about asking. In the wake of the Exxon Valdez oil spill off the coast of Alaska, the company responsible for the cleanup faced a novel problem.18 Because this spill occurred in such cold waters, there was a problem with the “sludge” freezing as the company attempted to pump it from the ocean and onto barges. As you might imagine, solids do not pump well. But how could the crew keep the sludge from freezing in temperatures well below zero? It was a vexing problem that environmental engineers had never encountered before. So the company posted the problem on InnoCentive, an innovation contest platform, where an engineer from the concrete industry immediately saw the solution. In the concrete industry, they use vibrating probes to keep concrete from hardening when it is being poured. He reasoned the same approach would work for ice—if water keeps moving, it has a harder time freezing. The company tried it and it worked. In retrospect, the solution was obvious, but the company never would have thought to ask an engineer from the concrete industry for advice.
Conclusion
There is nothing predictable about transformative innovation. Exploring new technological or market landscapes is fraught with uncertainty. This does not mean, though, that transformative innovation is the outcome of random luck. Transformative innovators do not just stumble onto interesting ideas by pure chance. Instead, their senior leaders design and manage their organizations to increase exposure to a broader palette of problems, perspectives, concepts, technologies, and user experiences. Fundamentally, they value diversity of ideas over sheer quantity. They value the learning that comes from exposure to novel ideas more than the predictability that comes from working in familiar spaces.
Broadening your organization’s capacity to search widely cannot be reduced to a few magic practices. Search capacity is rooted in organizational systems composed of interdependent choices of people, processes, and structures. The capacity to search broadly requires a thoughtful combination of people who bring diverse perspective with processes and structures that facilitate exploration and learning.
Almost everything I discussed to enable broader search is facilitated by scale. Large organizations have the resources to hire a broader portfolio of talent. Larger organizations can invest in multidisciplinary capabilities in a way that is simply outside the reach of smaller companies. Larger organizations have the resources to mitigate risks through parallel efforts. They can attract and work with a broader cross-section of external parties.
Finally, while building a capacity for broader search is a necessary step in becoming a transformative innovator, it is, alas, not sufficient. Novel ideas are the raw material for innovation; having a diverse mixture of ideas sets the stage for transformative innovation. But to take that potential and create truly transformative innovations requires a capability to synthesize diverse ideas into coherent concepts. It is to this capability that we turn to in our next chapter.
6
SYNTHESIS
Bringing the Pieces Together
My six-year-old son loves Legos. This is good because I like to play with Legos too (and now I have a great excuse!). After we finish building a kit (which contains the set of parts and instructions to make a specific design), my son prefers to play with it, rather than to display it on the shelf. The play usually involves some version of good guys fighting with bad guys, and inevitably our creation gets destroyed during the battle. The kid inside me always finds this a bit heartbreaking,
but my son does not seem to mind. He just takes the pieces and throws them in a big red box containing all his other random Lego bricks. Most of our building adventures come from the Legos in the red box. By combining and recombining the dozens of types of blocks in the red box, my son and I can create a seemingly infinite variety of cars, trucks, airplanes, buildings, and of course good guys and bad guys. Whenever we do this, I am reminded of one of the enduring principles of innovation: innovation is not necessarily about creating something new from the ground up. Quite often, innovation involves combining existing ideas and existing components in new ways.
Innovation through combination is all around us. Think about music. With just twelve notes, we can compose every genre of music at every level of sophistication, from Mozart’s symphonies to “Chopsticks” and from opera to rap. Or, to take an even more extreme example from nature: using just four chemical components of the genetic “alphabet” (adenine, thymine, guanine, and cytosine), evolution has created an almost infinite variety of living species, from the tiniest viruses and bacteria cells to humans and sequoia trees.
Innovation through combination is also all around us in products and business models. If you have done a good job with search (discussed in Chapter 5), you have assembled a rich palette of potential ideas for innovation. But none of these ideas on their own are likely to be innovations. It is the rare innovation that germinates from a single idea. To spawn transformative innovations requires an organization to blend multiple strands of seemingly disparate ideas into coherent concepts. I call this process “synthesis.” Like other aspects of innovation, synthesis does not necessarily come naturally to organizations. It is a capability that must nurtured and managed. How to build an organizational capability for synthesis is the subject of this chapter.
Innovation as Synthesis
We often think about transformative innovations as sharp breaks with the past. The transistor looked and worked nothing like the vacuum tube. Personal computers looked and functioned very differently than did the minicomputer and mainframe computers that preceded them. The first iPhone bore no resemblance to the mobile phones available at the time. Even business model innovations can strike us as sharp points of departure. Ordering books (and, later, just about everything else) on the Internet with a few clicks was an experience no one enjoyed before the arrival of online retailing. But if we peer deeper, even the seemingly most radically “new” innovations have roots deeply embedded in the past. The first commercially viable personal computers of the late 1970s, like the Apple II, embodied decades of ideas about computer architectures, microprocessors, memory, software operating systems, computer graphics, input-output devices, and user interfaces. The basic concept of the personal computer—one machine per user—had been around since at least the 1940s. The personal computer synthesized these elements into a new design form. Likewise, many of the basic concepts behind the original iPhone—mobile telecommunication, Internet connectivity of mobile devices, portable music, graphical user interface, solid state storage, and so on—predated the iPhone. But the iPhone brought these together in both a novel and appealing way.
The first genetically engineered drugs of the 1980s were born out of advances in genetics, molecular and cell biology, protein chemistry, analytical chemistry, immunology, and other fields of physiology. The transistor emerged from the confluence of research in solid-state physics, metallurgy and materials science, chemistry, electrochemistry, and electrical engineering. Transformative business model innovations likewise often result from combinations of old and new concepts. In some ways, Uber is like an old-fashioned taxi service. You can request a ride on demand from point A to point B. But it is also a bit like hitchhiking in the sense that the drivers are private individuals willing to offer rides to complete strangers. But it also organizes and monetizes this process through an online platform that makes a market between ride providers and ride seekers. In this sense, it shares a striking resemblance to other online market-making platforms like eBay or Amazon. There is nothing new about taxis, hitchhiking, or market makers. But the combination is new.
Synthesis is an act of creating something new out of the integration or combination of existing components. The idea that innovation is inherently synthetic has deep roots. Joseph Schumpeter, arguably the grandfather of the field of innovation economics, wrote back in 1911:
To produce means to combine materials and forces within our reach. To produce other things, or the same things by a different method, means to combine these materials and forces differently.… Development [or entrepreneurship] in our sense is then defined by the carrying out of new combinations.1
There is quite a bit of empirical evidence from both statistical and detailed case studies highlighting the importance of synthesis in innovation. For instance, drawing from more than two hundred years of patent data, Lee Fleming and Olaf Sorenson found that the most impactful innovations arose from broader combinations of interdependent technological components.2 That is, inventors were more likely to generate breakthroughs when they worked with and integrated a greater variety of ingredients.
Synthesis often involves applying knowledge gleaned in one field (or for one specific problem) to another. Historically, cancer and heart disease were considered different fields because each was considered, biologically, a different problem. Cancer was viewed as a disease of uncontrolled cell growth originating from damaged or abnormal genes. Cardiovascular disease was viewed as a problem of blood vessel blockage caused by lipid deposits. Cancer researchers focused on finding ways to stop cell growth either by outright destruction of cancer cells or intervening in the metabolic processes causing uncontrolled cell growth. Cardiovascular researchers looked for ways to reduce blood lipids. It is not surprising that cancer researchers and cardiovascular researchers rarely, if ever, talked to one another. Today, we know inflammation plays a key role in both. This means that a cancer researcher may be interested in the studies on inflammation conducted by scientists interested in cardiovascular disease and rheumatology (and vice versa). Rebecca Henderson and Ian Cockburn’s detailed analysis of R&D performance in the pharmaceutical industry showed that exploiting such spillovers across disease areas (cancer, cardiovascular, neuroscience, etc.) significantly contributed to research productivity among larger companies.3
Even within academic science, there is evidence that the highest-impact research stems from synthesis across fields. For instance, there is evidence that larger, cross-disciplinary teams are more likely to produce higher-impact research.4 Think about the mapping of the human genome, one of the greatest scientific achievements of the past century. This effort required integrating insights from molecular biology, genetics, biochemistry, protein chemistry, mathematics, computer science and software engineering, and instrumentation engineering. It required not only a lot of people from many different fields but also bringing their insights together in new ways. It is no accident that the discovery of the structure of DNA—about fifty years prior to the mapping of the human genome—was the collaborative effort of a biologist (James Watson), a physicist (Francis Crick), and a biologist and physicist (Maurice Wilkins), with crucial contributions made by a chemist and x-ray crystallographer (Rosalind Franklin).
Exploiting opportunities for synthesis may be critical for creative innovation, but how does synthesis actually happen inside an organization? The laws of chemistry, physics, or biology do not of course govern synthesis within organizations. An artist who mixes red and blue paint will get some shade of purple, the result determined by the chemical reactions between the pigments and the physics of how light is reflected off the molecules. If you control the inputs precisely enough, you can pretty much control the synthesis of the color. Synthesis of ideas into innovations does not happen automatically. In fact, organizations are often designed and managed in ways that actually impede the process.
Having All the Pieces Is Not Enough
I have always been struck by companies that seemed to be ideal
ly positioned to innovate through synthesis but yet were unable to exploit these opportunities. Usually, these were organizations whose business or geographic footprints had exposed them to a diverse set of ideas, technologies, markets, customer problems, or insights that could have formed building blocks for transformative innovation if combined in the right way. And yet they were not able to bring these ideas together.
Early in my career, I consulted for a diversified financial services company. The company was a major provider of transaction services such as record keeping, safekeeping of portfolio assets, trade settlement, and income collection on sales of assets to large institutional investors like pension funds and mutual funds. As this business matured and faced intensifying price competition, the company developed a strategy to differentiate its services to institutional investors. The company reasoned, correctly, that fund managers whose own compensation was based heavily on their risk-adjusted returns would be willing to pay for information that gave them even the slightest edge. And they also understood that the institutions that paid these fund managers would be very interested in better ways to measure risk-adjusted performance. The company was ideally positioned to develop these value-added services. Its custody business gave it access to massive amount of data on transactions, portfolio positions, and performance (in essence, this company had a big data strategy long before anyone knew what big data was). In addition to its trove of data, the company had all the required expertise in-house. Its custody business unit had the deep IT systems development expertise needed to build the requisite software platforms. The company’s investment banking unit had world-class experts in designing sophisticated trading and hedging strategies, creating complex derivatives, and applying the esoteric mathematics of financial valuation and risk. The company’s money management division was on the leading edge of using new trading strategies and financial investments for enhanced portfolio performance. In short, it had all the pieces of the puzzle.
Creative Construction Page 15