In a Volatility, Uncertainty, Complexity, and Ambiguous(VUCA) world, it’s getting harder and harder to stay competitive and relevant in the advent of all the disruption/emerging business models. The road to staying relevant not always starts from within, but many times looking around and seeing how the competition is fairing and what we learn from it.
Howard Yu, author of LEAP has a lot to say about this topic through his book. Let’s dive in.
What factors account for the incredible longevity and prosperity of pioneers in the pharmaceutical industry, particularly Switzerland’s Novartis?
Only when pioneers kept pace as the knowledge base shifted from one discipline to another, as they did in the pharmaceutical industry, were they able to exploit their opportunity and capitalize on their advantage.
But these leaps are fraught with challenges, even when one is armed with rich knowledge. No company can get it right every time. Those who have made it have done so with persistence, audacity, foresight, and sometimes luck. Precisely because this leap is very difficult, the most experienced companies stand a better chance of staying on top. Inventions and discoveries stand on the shoulders of their predecessors; hard-won progress is usually built on experience and prior knowledge.
When Novartis was on the cusp of developing its first targeted drug, Gleevec, which treats a rare form of leukemia, the transition to a new knowledge discipline, namely, bioengineering and genomics, was hardly straightforward.
The size of the market for the treatment for this rare form of leukemia (CML) appeared to be severely limited. CML affects about 8,200 American adults every year, a figure that pales in comparison with the estimated 165,000 cases of prostate cancer and 250,000 cases of breast cancer in the United States. Managers at Novartis were worried that the new drug would offer little financial return, in addition to the clinical uncertainties. The animal studies and clinical trials alone would cost the company between $100 million and $200 million.
It was the CEO who forged ahead with this development. “Ultimately, we are a business, and business decisions are often based on some form of statistical analysis and the chance to make a profit,” he admitted. “But, as a management team, when there is a fair chance that a product on the market will change the practice of medicine, we have a duty to put that product out there . . . I told our head of global technical operation, ‘Money doesn’t matter. Let’s just do it.’”
To leap, the most challenging aspect has always been the impossibility of rendering investment decisions into positive financial forecasts. Only the one at the very top of the company can legitimately say, “Money doesn’t matter. Let’s just do it.”
In LEAP, you reveal the potential payoff for companies who have the courage to cannibalize their own products. What makes Procter & Gamble an outstanding model of successful self-cannibalization?
When the first boxes of Tide went on sale in 1946, it was the first synthetic detergent that could deep-clean clothing—removing mud, grass, and mustard stains “without making colors dull or dingy.” Before Tide was introduced, all soaps were “natural” and made by heating animal or vegetable fats with water and an alkali base. The benefits of a synthetic detergent that makes “white clothes look whiter” were so apparent that Tide outstripped all brands in the market and became the number one detergent in 1949. In the wake of Tide’s entry to the market, P&G would “no longer be a soap company” but “would become an industrial corporation with its future based on technology,” with the number of technical staff tripling that of the pre-Tide year of 1945.
But inside P&G, a convulsive worry over research on synthetic detergent had historically been pervasive. Managers feared that the new products might cannibalize their much-cherished Ivory soap. Yet, Chairman William Cooper Procter, the last family manager of P&G, was a staunch supporter of the work on synthetic detergents. In a memorable remark addressed to his staff, he said, “This [synthetic detergent] may ruin the soap business. But if anybody is going to ruin the soap business, it had better be Procter & Gamble.” Management doubled down on its investment, and the technical center at Ivorydale effectively became one of the first analytical labs in the field of consumer goods. A family firm whose founders stirred cauldrons by hand had now become an enterprise built on three knowledge foundations: mechanical engineering, consumer psychology, and organic chemistry. And it was that combination—the totality of three knowledge disciplines—that had created the unstoppable Tide.
To an outside observer, one form of managerial behavior that was salient throughout the long history of P&G was apparent: the willingness to embrace self-cannibalization. Resistance to this counterintuitive strategy is natural. Managers often fear that a company’s new products and services with lower profit margins may directly cut into the sales of existing products. Money should be invested in products that are clearly most profitable without lowering overall profitability. But to reference a Steve Jobs almost cliché, “If you don’t cannibalize yourself, someone else will.”
Novartis and P&G could not be more different. Novartis spends fearsome amounts of money designing and testing drugs for therapeutic treatment, jumping over the highest regulatory hurdles. P&G creates common household goods that clean. One saves lives; the other helps people look nice. Both companies, however, have thrived for more than a century; both have rewritten the rules in their respective sectors and transformed themselves, not just once but again and again.
What can business leaders learn about reevaluating a company’s foundational strengths from the piano war between Steinway and Yamaha?
When industry knowledge matures, copycats catch up. Because latecomers often inherit a lower cost structure without the legacy assets, they exert competitive pressure on industry pioneers. That’s why Steinway can’t compete against Yamaha, even though it has always made the finest pianos in the world.
To more than 90% of concert artists, including such legendary virtuosos as Vladimir Horowitz, Van Cliburn, and Lang, a Steinway grand piano is the instrument of choice. Arthur Rubinstein, who is considered by many as the greatest pianist of the 20th century, once declared, “A Steinway is a Steinway, and there is nothing like it in the world.”
Despite these remarkable achievements, over the past five decades Steinway’s financial results have been anything but stellar. Its management experienced crises one after another, which characterized a prolonged downward spiral. In 1926, Steinway sold 6,294 pianos, an all-time high; in 2012, it sold just over 2,000. The company changed ownership three times between 1972 and 1996—it was passed by Columbia Broadcasting System (CBS) to a group of private investors led by the brothers John and Robert Birmingham, and then to Selmer Industries, the number one instrument maker band in the United States. All these had already happened before Steinway went public in 1996, to be listed on the New York Stock Exchange, but then it went private when the hedge fund firm Paulson & Co. bought it for $512 million in 2013. Over the same period, Steinway helplessly auctioned off, one after another, many of its buildings that had historically been part of the Steinway Village in northern Astoria in Queens. The original 400-acre campus was slowly chipped away and eventually reduced to a gritty complex of a single redbrick factory building at the end of Steinway Street that we know today.
During post-war reconstruction, Yamaha, which was once an obscure manufacturer, focused on upright pianos to cater to the space-conscious Japanese, producing small home-use pianos that were infinitely different from the Steinway concert grand piano that graces Carnegie Hall or the Smithsonian museums. But inside Yamaha’s factory, manufacturing processes were all but automated, stamping out as much human interference as possible. A computerized system would identify pieces of veneer and direct them through overhead Y-shaped carriers to seven different rim presses, which corresponded to the different sizes of the grand pianos that Yamaha made. Only two employees were needed to guide the veneer to the correct position before a hydraulic cylinder came down with a pneumatic hiss and shaped it into the press. The rim adhesive would then dry in fifteen minutes, thanks to the high-frequency curing method. The entire process was designed with minimal variations in production, a system that couldn’t be more different from that of the heartbreakingly labor-intensive craftsmanship at Steinway and Sons.
By the time Yamaha entered the concert grand segment in 1966, it was already the largest piano builder in the world, with a production volume of 200,000 musical instruments every year, vastly overshadowing Steinway’s 6,000. With a far bigger balance sheet, a diverse set of technologies, and many advanced production techniques, Yamaha could marshal more resources in marketing, distribution, recruitment, and production. The money it gained from the low-end segment became the wellspring that allowed it to enter the top-end segment, the concert grand pianos, the “lifeblood” of Steinway.
Steinway’s difficulties might be mourned only by piano lovers, but there is a lesson in it for all of us. Managers must ask themselves what knowledge discipline is the most fundamental to their company. What is the core knowledge of their business? And how mature or widely available is it?
In LEAP, you urge both start-up entrepreneurs and corporate executives to leverage the seismic shifts around them and dive right into reconfiguring their competencies. Could you offer practical guidance for identifying forces on the horizon that will have a huge impact on a business?
To come up with an integrated strategy, every effective leader must begin with the big questions: What world am I living in? What are the biggest trends in this world? How do I align my company’s activities so that my organization gets the most out of these trends and cushions the worst? Part 1 of LEAP shows us the power of history, which acts as a prism that helps us understand the past so we can leap into new knowledge disciplines. Part 2 of LEAP takes us to the future to point out the two intertwining trends that propel all companies into the 21st century: the inexorable rise of intelligent machines and the emergence of ubiquitous connectivity. As new technologies are introduced, society is continuously transformed, and with it the way we will work in the future. We have observed that connectivity favors a decentralized mode of innovation, smart machines automate expert knowledge, and consequently, managerial activities that will still be ensconced in the human realm demand a higher level of creativity, social understanding, and empathy.
The inevitable is often quite apparent. Companies just need to leap while time is still on their side. Steve Jobs knew this. He said, “Things happen fairly slowly, you know. They do. These waves of technology, you can see them way before they happen, and you just have to choose wisely which ones you’re going to surf. If you choose unwisely, then you can waste a lot of energy, but if you choose wisely, it actually unfolds fairly slowly. It takes years.” Jobs was referring to the time that he waited for broadband for two years, and then when it finally arrived, he jumped into the window of opportunity by releasing the iPod. Countless others jumped earlier than Apple by releasing their own MP3 players but failed miserably. Before the 2000s, music sharing was virtually illegal—on Napster—and it took hours to download an album. With poor connectivity, even the best-designed hardware made was hopelessly sluggish when downloading. Jobs waited for the inevitable improvement of broadband.
This is an important lesson. Successful executives often exhibit a bias for action. But it’s more important to separate the noise from the signal that really pinpoints the glacial movement around us. Carefully listening to the right signals requires patience and discipline. Seizing a window of opportunity, which means not necessarily being the first mover but rather being the first to get it right, takes courage and determination. To leap successfully is to master these two seemingly contradictory abilities. A balanced combination of the discipline to wait and the determination to drive often pays off handsomely. Cultivating this paradoxical ability at the individual and organizational levels is the main objective of LEAP.
Why should every company care about the wisdom of the crowd? What can business leaders in every sector learn about leveraging ubiquitous connectivity from China’s largest social media app, WeChat?
As with all things China, the most astounding aspect of WeChat is its rapid ascent. Skeptics dismiss WeChat as just a Chinese WhatsApp or iMessage. Many people outside the country may not have even heard of this service. Still, there are 938 million monthly active WeChat users, a number larger than the entire population of Europe, let alone that of the U.S.. But the size of the user base “doesn’t tell the whole story,” according to a WeChat executive. “You need to count engagement.” WhatsApp, for instance, has more than 1.2 billion users worldwide. Facebook—WhatsApp’s parent company since 2014—has over 2 billion users. But WeChat has proven itself to be more enticing, as more than 1/3 of its users spend four hours or more per day on this app. By contrast, users average 35 minutes on Facebook, 25 minutes on Snapchat, 15 minutes on Instagram, and one minute on Twitter.
This extreme engagement can be explained in large part by the extremely wide scope of services that WeChat provides. Shaking one’s phone via WeChat is a popular way to find new friends who are also users. Waving it in front of a television allows WeChat to recognize the current program and gives viewers the opportunity to interact. WeChat has effectively rolled Facebook, Instagram, Twitter, WhatsApp, and Zynga into one. Instead of being just a stand-alone messaging app, WeChat is an indispensable mobile tool for booking doctors’ appointments, settling hospital bills, filing police reports, reserving restaurant tables, accessing banking services, holding video conferences, playing games, and much more.
None of these features are invented by WeChat engineers. Most WeChat services are in fact provided by third parties. WeChat’s major breakthrough, therefore, is the realization that a product’s best feature is never invented in-house. Killer apps must be invented by users instead.
While the viability of crowdsourcing has been apparent since the early days of Wikipedia, the high level of connectivity today was barely imaginable a decade ago. The accelerated improvement in how people connect with one another has profoundly changed how smart creatives can collaborate on ever more sophisticated projects, which, in turn, influences nearly every business prospect. What was once the personal foray of a single mind can now be transmitted and distributed widely, allowing a whole community to participate. Instead of relying on a small team of internal experts to painstakingly make important decisions, companies must use crowdsourcing to mass-produce solutions and solve complex problems.
In LEAP, you celebrate the looming force of AI. Why should business leaders embrace intelligent machines? Could you share an example of a leap into the realm of AI that made a company stronger and more humane?
The current development of AI can be likened to the early years of electricity when it replaced steam power in manufacturing. At the turn of the century, most textile factories were still powered by flowing water and waterwheels. Factories that installed steam engines had to use pulleys, belts, rotating shafts, and a host of complex gear systems. Factories were built largely around a rigidly imposed steam engine, impairing any possible workflow efficiency. Interestingly, when manufacturers began to use electricity, engineers couldn’t imagine an alternative layout like the modern-day assembly line. Instead, they grouped electric motors in a big cluster, forgoing the benefit of decentralized power to optimize workflow. It took almost another two decades before manufacturers were able to unleash the full benefits of electricity.
Today, big organizations still think of AI as a cost-cutting measure that substitutes human labor in paper processing. Although this can be all-important, the biggest potential is likely to be augmentation—freeing up managers from white-collar drudgeries so they can engage more in creative and emphatic activities.
The upshot is that artificial intelligence, machine learning, and cognitive computing can exert either a complementary effect or substitutional pressure. But that outcome is not predetermined. Atul Gawande—a celebrated surgeon, writer, and public health researcher—explained exactly why human interaction remains paramount in the age of AI. He shared a simple scenario at a local clinic. “I have pain,” a patient complains. “Where?” the doctor asks. “Hmmm. Well, it’s sort of here.” The patient points with one hand. “Well, do you mean there under your rib cage, or do you mean in your chest, or your stomach . . . ?” To Gawande, this intimate interaction is as much about a patient telling her story as it is about a doctor probing a patient. “It’s more of a narrative than it is a straight set of data.” A physician needs “not only to ask you to take off your clothes, but then to actually have permission to cut you open and do what [he] choose[s] to do inside you.” Trust, empathy, and dialogue are what make health care ever so human—that only we can fully grasp the meaning of compassion, pride, embarrassment, envy, justice, and solidarity.
Sebastian Thrun, a computer scientist and pioneer in self-driving cars explains “When you use a phone, you amplify the power of human speech. You cannot shout from New York to California, and yet this rectangular device in your hand allows the human voice to be transmitted across three thousand miles. Did the phone replace the human voice? No, the phone is an augmentation device.”
As improbable as it may seem, a good example is found in Japan, with a Japanese publisher. Established in the early 1960s, Recruit Holdings started as an advertising company publishing magazines for job seekers. Spurred by the Internet revolution in the early 2000s, the company added business verticals, such as real estate, bridal, travel, beauty salon, and restaurant. By 2015, as Recruit’s digital platforms gained popularity, the company noticed the enormous amounts of online data on types of transactions and end-user behaviors. By establishing an artificial intelligence (AI) research laboratory in Silicon Valley, Recruit’s management started to apply the latest technologies in data analytics and machine learning.
Amid all the changes, one major shift at Recruit was the changing role of sales. In the past, customers placed ads to drive traffic to stores. Today, all the digital platforms are used as new means to improve business efficiency. Sales personnel no longer mindlessly canvass towns, touting advertising space to proprietors. Instead, they collate customer insights and act as champions of technology requirements, effectively multitasking as general problem solvers—a far more varied, sophisticated, and enriching job for employees.
Why is managerial creativity increasingly important?
To gain any groundbreaking insights into marketing, consumer psychology, popular art, or even a mobile app’s user interface, an innovator is still necessary to synthesize human experience, newspaper articles, and stories about how people have reacted, conversed, and complained. Extracting hidden and ambiguous meanings in the social realm requires not just big data, which are often broad and shallow and devoid of emotional meanings, but also small data—the thick and deep information about individuals, for example, about how a sickly child at the hospital is nervously waiting for an MRI scan.
Machine learning and big data concern themselves with correlation, not causation. Under the hood of IBM Watson, for instance, an algorithm establishes many statistically significant relationships but never quite explains why they are so. The way we assess the performance of computer systems can also be misleading. The notion of machine intelligence, strangely enough, remains ill-defined. Scientists tend to evaluate a computer’s performance based on tasks that are difficult for humans, such as playing chess, Go, or Jeopardy! These tasks are unnatural and difficult for humans because they require deliberation and planning—the type of cognitive work that our evolutionary history has endowed us with only most recently. These are not the sort of tasks that human intelligence has evolved for—making very quick decisions using limited sensory data with limited calculation power. Consequently, a computer can play chess far better than it can recognize the face of its opponent.
Precisely because people are more agile and dexterous than the most advanced robots in identifying objects and understanding nuances, the results are always better when computers and humans work together, rather than when either one does it alone, whether it is playing chess or solving other real-world problems. You can try pushing a machine toward the bleeding edge, but it still won’t beat an average machine that works alongside a human. The future is merging machine capability and human consciousness. Each doing their best work and managerial creativity is the human advantage.
How can readers start taking first steps toward making a leap tomorrow?
In order to leap, you must make concrete choices. A bold decision always looks good—until it is proved wrong. To borrow Donald Rumsfeld’s phrase of “unknown unknowns,” executives may not even be aware that they don’t possess a critical piece of information. To facilitate evidence-based decision making, therefore, managers must carry out frequent experimentation to reduce the dark space of ignorance and to arrive at conclusions with the required level of familiarity.
Here’s another way of looking at it. The biggest risk that threatens the survival of a large and complex organization is political infighting and collective inaction. Arguments that play out in the boardroom may be akin to empty rhetoric and amount to nothing more than personal beliefs. Experimentation is the window of truth that will let light in from outside.
And yet market leadership can’t be achieved through an undirected process of boundless experimentation, nor can it result purely from the efforts of skunkworks or corporate ventures directly imported from Silicon Valley. Behind any unfocused effort lies a bleak prognosis: the established organization has become so dogmatic and unchangeable—insidious at worst—that the only way to innovate is to put a few bright people in a dark room, pour in some money, and hope that something wonderful will happen. This freewheeling approach may work well for venture capitalists because they invest to exit, either through initial public offerings (IPOs) or by selling start-ups to large firms. But an established organization should invest and innovate to rejuvenate its ongoing business ahead of its competition. Integration of the old and the new becomes unavoidable. For this reason, sooner or later, the senior executives of an operating company have to call the shots and turn an emergent exploration into a deliberate execution.
Once the winning strategy becomes clear, the company must pursue it aggressively. Not doing so is tantamount to failed leadership.
LEAP began as a historical account, a memoir of Western pioneers. Some of these pioneers failed, some survived, others prospered. But it’s also a playbook for the future. More importantly, it’s a manifesto for how pioneering companies can rethink their businesses, their relationship with their customers, and the reasons they exist. Any organization—large or small—has a set of traditional strengths and important products that have helped build it into what it is today. There is no perfect moment to innovate. But everyone has exactly enough time, starting now.
The future of work means differently to each one of us: some see it as more technology and less human, some expect a more humanized space and some others imagine it to be a no-workplace world. In our journey to unwrap FutureofWork, Work2.org invites leaders from various industries to help our global community to understand what the posterity holds for workers, leaders and organizations. While our team is busy at bringing this fresh ideas directly to you, we would appreciate our community help in making it possible. If you like what you’ve read, we would appreciate if you could spread the word within your circles and let us know if anything you want us to bring into this #FutureOfWork conversation.
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