The question though is how much more I would be willing to pay for yet an even closer, more comfortable, safer shave. After all, at some point, a shave can only get so close before you require medical board certification. And, frankly, I am probably past the point of really knowing the difference. My shaves are already very comfortable, and I rarely nick myself. But, this morning, I noticed I was down to my last blade, and it was starting to feel dull. This means going to the store to endure a process—shopping—that is worse than nicking myself shaving. Apparently, because of theft, my local drug store no longer keeps the razor blades out on display. I will have to go to the counter, wait in line, and then ask a salesperson to get the one I want (which involves reaching across the counter and trying to direct them by pointing). When I get home, I am confronted with what appears to be bullet-proof plastic packaging, presumably again because of theft, that requires a very sharp scissor to open (I have not recently cut myself shaving but I have cut myself opening shaving cartridge packages!).
This example illustrates a common problem—an innovation strategy that may no longer be solving the most important problem for customers. The close, comfortable, and safe shave has become a “given” for me. I want it, but I will not pay more for it. My need for shaving performance is satiated. My need for convenience in acquiring and opening the product is not. I hate that part of the experience, and I would pay to avoid it. My guess is that other men have the same view, and this is why new, purely online players, who offer convenient subscription services like Harry’s and Dollar Shave Club have become so popular. They are offering razor systems (they claim) that are equivalent to traditional brands like Gillette but are cheaper and more convenient to acquire. Last year, Unilever bought Dollar Shave Club for $1 billion.11 We see similar business model innovations happening in other markets where basic product functionality needs have been met, but where customers’ need for convenience has not. Long ago the performance of men’s dress socks probably hit their peak in terms of comfort, appearance, and durability. My willingness to pay more for dress socks based on their physical attributes is limited. If you are in the sock business, it is hard to think of a technological solution to this problem. Socks are not like my iPhone—there are just not a lot of features I am going to pay for. But I will pay more for the convenience of not having to physically go to the store. And that’s why Internet-only vendors like BlackSocks or Tommy John can sell socks and underwear at a price premium. While my needs for “high-performing” socks have long ago been met, my needs for convenience are far from satiated.
As an innovator, you have to be aware where your customers are in terms of their degree of satisfaction along various product attributes. If customers’ needs along particular attributes are not being met, those areas are ripe for continued innovation. If most men feel unsatisfied with their shave, then continued innovation in razor design (more blades, thinner blades, coatings, geometry, etc.) makes sense. This might be routine innovation if it builds off existing technologies or even radical if new technology is needed to create even higher levels of desired performance. But if customer needs are satiated along a particular dimension, continued innovation along this trajectory of performance is going to be less profitable over time because while it is costing you more and more to squeeze out improvements, customers are less and less willing to pay for them. Companies often get this wrong by sticking too long to improving product attributes that are no longer important differentiators for most customers. Clay Christensen has dubbed this “overshooting the market,” and he argues it is exactly what makes companies vulnerable to disruption. His canonical example is the disk drive industry, where leading companies’ obsessive focus on improving storage capacity blinded them to the threat posed by new entrants offering smaller (and cheaper) devices.12 If you have seen signs that customers are less willing to pay for incremental improvements in the attributes that have always been focal points of your value proposition, then you need to think about different attributes. This might lead you to explore alternative technologies that drive improvement in other product attributes. Some needs (like product performance) can be addressed with improvements in technology, but others (like cost or convenience) might require a change in business model.
How much potential does your existing technological paradigm offer for improvement? In every industry at any point in time, there is a technological paradigm: a broadly shared consensus on the critical technical problems and the set of feasible designs, technology configurations, theories and concepts, know-how, materials, methods, and skills required to address those problems.13 The internal combustion engine is an example of a long-established technological paradigm in the auto industry. The internal combustion engine is, of course, a physical artifact, but it also represents a specific body of knowledge and assumptions about focal technical problems (increasing fuel efficiency, reducing emissions, increasing horsepower, etc.) and critical design choices (combustion ratio; the size, number, and configuration of cylinders; piston geometry; fuel-oxygen ratios; ignition timing; etc.). Over time, companies within an industry develop deep expertise in the predominating paradigms.
A lot of technological innovation involves evolutionary refinements and improvements within existing paradigms. Occasionally, though, new paradigms emerge that displace established ones: semiconductors replaced vacuum tubes, and the jet engine replaced the propeller. A shift in paradigm is marked by a change in the fundamental parameters that describe the technology. So, for instance, parameters like compression ratio, cylinder configuration (V6, V8), displacement, and bore and stroke (all pretty basic ways of describing an internal combustion engine) have absolutely no meaning if describing an electric motor.
Routine and disruptive innovation involve evolutionary refinements in your existing technological paradigm, while radical and architectural innovation require exploration of new paradigms. How do you decide whether “sticking to your knitting” (technologically speaking) or exploring new terrain is worth it?
The first consideration is whether there even is a feasible alternative available. Much of the discussion about innovation today focuses on the major upheavals in technological regimes (shifts in paradigms) such as the impact of electrification on autos, the digitization of retail, the potential replacement of fossil fuels with renewable energy, and so on. When such transformations occur, they can have dramatic effects—destroying long-dominant enterprises and altering fundamental aspects of our daily lives. But, in reality, such upheavals happen relatively infrequently. Typically, most technological advances occur through more prosaic evolutionary innovation within a paradigm. This often happens for decades before being punctuated by a paradigm shift.14 For almost a century, the internal combustion engine was essentially the only feasible technological paradigm for powering an automobile. In instances like this, the option of exploring alternative paradigms may not even exist.
In some contexts, fundamental advances in science create new paradigms rich with new opportunities. Think about pharmaceuticals. Until the early 1980s, pharmaceutical innovation was based largely on exploiting long-established technological competences in medicinal chemistry and random screening. Over the past several decades, a series of major scientific upheavals have created several new paradigms for drug discovery, including genetically engineered proteins and monoclonal antibodies, mechanism-based drug design, high throughput screening, combinatorial chemistry, system biology, cell therapy, RNA-interference, messenger RNA, and, most recently, gene editing. If you operate in a context where scientific progress can upend existing paradigms, your technology strategy has to put relatively more emphasis on exploring and absorbing capabilities related to new paradigms.
What about if you operate in a context (like say apparel, shoes, or restaurants) where the existing paradigm is quite mature and progress along existing trajectories has hit diminishing returns? In some cases, there are possible new paradigms that might rejuvenate the industry’s innovation potential. Thirt
y years ago, it was beyond dispute that the auto industry was a technologically mature industry. Innovation focused on incremental refinements of existing concepts and on styling. Today, with alternatively powered vehicles and the potential for self-driving cars, I do not think anyone would say anymore that the auto industry is mature. Advances in bodies of know-how (largely outside the auto industry) have created the potential for paradigm shifts. So if you are in industry that feels a bit “sleepy” technologically, do not be lulled. You still need to keep your eyes open to explore new bodies of knowledge.
But what should you do if your core technologies are mature and you see no alternative technologies that can transform the business (e.g., you are in the apparel industry). In these contexts, it is hard to create a lot of value for customers through technological innovation, and so you need to focus your innovation strategy elsewhere. This is exactly the circumstance that should lead you to consider exploring new business models. Today, we see several technologically mature businesses being transformed by business model innovators, such Warby Parker in eyeglass frames, Uber and Lyft in taxis, Tommy John in men’s underwear, and Airbnb in hotels.
If a potential alternative exists (or could at least be contemplated), a second consideration is the richness of future innovation opportunities in dominant and alternative paradigms. The oil field analogy is helpful once again. Some technological paradigms are like big, unexploited oil fields. They offer plenty of opportunities for productive exploitation. Here, the right innovation strategy is to exploit it through evolutionary innovation. Others are like old fields that have nearly exhausted their possibilities. Innovation is still possible, but R&D investments are hitting seriously diminishing returns. When you are operating in the equivalent of an old oil field, you need to explore potential alternative paradigms (if any exist).
The dominant paradigm for semiconductor design and production since the 1960s has been etching a greater density of ever-smaller transistors into a silicon-based substrate and increasing the rate at which electrons move through circuits (known as clock speed). This has proven to be a remarkably productive paradigm, with a doubling of transistor density occurring approximately every eighteen to twenty-four months. Thus, in the semiconductor business, exploiting Moore’s Law, as it came to be known, has proven to be a very productive innovation strategy. However, like a giant oil field that has been pumped for decades, semiconductor improvements appear to be hitting their physical limits. As the electrons had to move faster through circuits that were ever closer together, heat became a serious problem. This has led to a flattening of microprocessor clock speeds since 2004.15 The other problem is that there are physical limits to how tightly one can pack circuits on a chip—today’s chips have “line widths” that can be measured in atoms, and by 2020 it is expected that quantum effects will make it impossible to scale further. Of course, chipmakers like Intel have proven remarkably creative at circumventing the limits (the demise of Moore’s Law has been predicted since the mid-1980s), but there is no doubt that continued improvements are getting more and more difficult. It is not surprising then that many chip makers and computer companies are exploring alternative paradigms such as quantum computing. In Chapter 4, I will have more to say about timing these types of transitions.
We view shifts in technological paradigms as threatening to incumbents—and for good reason. Extensive academic research demonstrates what many practitioners have experienced firsthand: established companies have a hard time transitioning from their long-held technological paradigms to new ones.16 Part of the problem is cognitive. A paradigm is a way of thinking, and it tends to filter how reality is perceived. Thus, it’s easy for players operating within a paradigm to overestimate the potential of that paradigm relative to the alternatives or to dismiss the alternatives as not feasible. In the mid-1980s, when I was doing research on the then-fledgling biotechnology industry—which was creating an alternative to the century-old medicinal chemistry paradigm of drug discovery—I interviewed many medicinal chemists who expressed skepticism about the potential of molecular-biology-based approaches to revolutionize drug discovery. The large protein molecules and antibodies derived from biotech, they said, would be too hard to manufacture, too hard to administer (they need to be given by injections rather than as pills), and too likely to cause dangerous immune system reactions. To some extent, they were right at the time. Biotech came with much hype, but in the early years the industry witnessed its fair share of failures. What the skeptics missed, however, was that molecular biology had massive improvement potential.
Not all shifts in paradigms are bad for incumbents if they understand the implications and develop an appropriate innovation strategy. Consider the example of the high-end bicycle frame industry. Targeted to biking enthusiasts (you can spot them most Saturday mornings wearing bright, tight Lycra outfits, hanging out in front of coffee shops), high-end bikes typically sell for $2,000 (frame and components), but the prices can go as high as $30,000 for fully customized bikes made from esoteric materials. Most “bicycle” manufacturers are actually bike frame manufacturers: components like brakes, shifters, gears, seats, and wheels are typically made and marketed by specialists like Shimano. Until about thirty years ago, the frames used in high-end bikes were made from alloy steels. Bike frame manufacturers like Pinarello would buy tubes from one of the major suppliers (usually Reynolds or Columbus) and then fabricate frames based on their own designs. Value was created through frame performance (weight, stiffness, strength, etc.). Since scale economies of production were relatively low, many niche players like Pinarello (Italy), Scapin (Italy), Eddie Merckx (Belgium), and Serotta (United States) thrived in the high end of the market.
Starting in the late 1980s and continuing throughout the 1990s and 2000s, carbon fiber—which is both lighter and stronger than steel—emerged as the material of choice for high-end frames. Traditional steel frame producers were not able to make carbon frames for two reasons. First, the technology requires fundamentally different capabilities (e.g., steel frames are welded from individual tubes, whereas carbon-fiber frames are molded as single pieces). Expertise in carbon-fiber fabrication is geographically concentrated in Taiwan, far from the European and American bases of traditional frame builders. Second, because of the required investments in tooling and molds for carbon-fiber frame fabrication, higher volumes were needed for cost-efficient production.
Not surprisingly, carbon-fiber technology led to the demise of many traditional bike producers, as production moved to third-party specialists in Taiwan. Because a few major carbon-fiber producers dominated the value chain, they could charge relatively high prices for production contracts, leaving most bike frame manufacturers with little remaining value. But Pinarello, a leading producer of high-end steel frames near Treviso, Italy, adapted its innovation strategy to take advantage of carbon fiber. Pinarello recognized that, because of carbon fiber’s malleability, it opened up new opportunities for innovative frame architectures and geometries (e.g., carbon-fiber frames can have curved tubes). A $7,000 bike frame can be considered a luxury good. People buy high-end Pinarellos for much the same reason (much richer) people buy Ferraris. They are buying a dream. Unless you race professionally, you really do not need the functional performance of a Pinarello frame, but that is not the point. You buy a bike like a Pinarello because you love the idea of having the same bike a professional rides. Selling that dream means having seductive designs and beautiful paint jobs. Pinarello decided to outsource production to high-quality Taiwanese producers and focus its resources on designing higher-performance and aesthetically attractive frames. The company invested heavily in design, engineering talent, sophisticated computer-aided design tools, and new prototyping methods. It focused production on painting since this has such a big impact on the aesthetic appeal (the company’s highest-priced frames are hand-painted in its Treviso factory).
These new design capabilities not only allowed the company to create new value (more innovati
ve and more beautiful frames increased customers’ willingness to pay), they also provided a powerful means to capture value because they are hard to imitate. While competitors might be able to reverse engineer individual frame designs, the capabilities to design innovative and seductive bike frames is much harder to imitate because they are rooted in a complex set of interdependent elements—like talent, culture, design methods and processes, intellectual property, and experience. Pinarello also uses team sponsorships to bolster its brand and received a big boost in 2016 when its team won the Tour de France. Pinarello illustrates how a major upheaval in technology can create additional opportunities for innovation by an incumbent developing novel capabilities and adjusting its business model.
Where can we create barriers to imitation? Imitation is endemic to innovation-based competition. Every good (value-creating) innovation will quickly attract imitators, and imitation erodes the value you capture. If patents and other legal mechanisms were perfect, imitation would be a nonissue. You would patent (or copyright) your innovation and then sue anyone who dared to violate your intellectual property rights. And, in a perfect world, you would win these suits and get your legal costs back in addition to full damages. Reality is very different. First, the degree to which patents and other legal mechanisms can protect from imitation varies dramatically across technologies.17 In many fields, prior art is so widely diffused that patents are almost impossible to get, or there are simply too many (legitimate) ways for rivals to engineer their way around your patents. Second, some technologies are inherently easier to copy than others because the key insights can be gleaned by making a detailed physical inspection of the product. With few exceptions, it is hard to rely solely on patents and copyrights to stave off imitation. You need to build or find other barriers. That is what companies like Amazon, Apple, Google, and Facebook do. Yes, these companies patent heavily, and they vigorously safeguard and enforce their intellectual property rights—but they also pursue innovation strategies that help protect their value streams from imitation.
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