What is the basis of competitive advantage in today’s business landscape? Many observers say it is the power to harness information. Best-selling authors Erik Brynjolfsson and Andrew McAfee have argued we are entering the “Second Machine Age,” with information technology as the engine of human progress. The McKinsey Global Institute has called big data the “next frontier for innovation, competition and productivity.” Academic research points to the importance of knowledge sharing, intellectual property, and R&D as the drivers of competitiveness. Firms such as IBM, American Express, and Caesar’s Entertainment have emphasized business analytics and big data as key to their success.1
In this book, we offer a different perspective. We believe the case for information technology, big data, and advanced analytics is overstated. These will of course continue to be important resources for staying in the race, but as information becomes ever more ubiquitous and search costs trend to zero, their capacity to provide any modern organization with a leading edge is diminishing.
That’s not the only problem. Information overload at the individual level leads to distractedness, confusion, and poor decision making. At a corporate level, we end up with analysis paralysis, endless debate, and a bias toward rational, scientific evidence at the expense of intuition or gut feel. These pathologies have a deleterious effect on our companies. They lessen the quality and speed of decision making, delay action, and engender a sterile operating environment in which insightful thinking is quashed unless it is quantifiable. As a result, many companies end up standing still, even as the world around them is speeding up.
So what is the alternative to “Slow-Motion Inc.”? Smart executives understand both the potential and the pitfalls of information. They recognize that the notion of competitive advantage is more fleeting than it used to be. They adopt what we call a fast/forward approach to business: they emphasize decisive action ahead of detailed analysis, and they are comfortable relying on emotional conviction alongside rational judgments.
Consider a few examples.
Amazon’s phenomenal growth, from online bookseller to new economy powerhouse, defies all the established rules about firms focusing on their core competencies. Its success is built on deep insight into the needs of its customers, and an assumption that if you create value for customers, growth and profits will follow. Jeff Bezos, the company’s cerebral founder, started his career developing mathematical models for a hedge fund and is a great believer in systematic analysis. But at the same time, he is known for his “harrowing leaps of faith.” His most important decisions are not based on studies or spreadsheets, they are “nervy gambles on ideas that are just too big to try out reliably in small-scale tests.”2
Or look at WPP, which has transformed itself over the last decade from a stable of old-school ad agencies, such as JWT and Ogilvy & Mather, to the world’s biggest new media communications company, with 40 percent of its revenues coming from its digital businesses, such as Internet and mobile advertising. For an industry built on fresh thinking, creative talent, and client responsiveness, bigger is not always better. So CEO Martin Sorrell allows the operating businesses to retain autonomy and to compete head-on with one another, while also encouraging collaboration when required—what one observer has called the “kiss and punch” model.3 Sorrell is famous for his attention to detail, his micro-managing style of leadership, yet like Jeff Bezos he is also decisive, with many of his largest acquisitions based more on gut instinct than due diligence. WPP’s “weirdly effective mix of order and chaos” has enabled it to steer through the digital revolution more capably than its big rivals, and yet Sorrell feels there is more to do: “We don’t believe that our existing businesses can move fast enough.”
Or consider Oracle, the world’s leading provider of database management software. Back in 2005, CEO Larry Ellison initiated a major project to rework the company’s products as software-as-service applications. Back then, the term cloud computing hadn’t even been invented, and there were many competing views about the future of computing. But Ellison made it a top priority, putting his very best developers onto a project with an uncertain future and a ten-year time horizon. In doing so, he enabled Oracle to develop one of the most comprehensive “cloud” offerings, spanning software, platform, and infrastructure elements. As observed by Thomas Kurian, Oracle president, “the heart of innovation is to decide early—in the middle of the period of ambiguity.”4
You might think this is a tech-sector phenomenon, but increasingly executives in large, mature industries are also embracing the fast/forward mind-set. For example, Swiss drug giant Roche is seeking to give greater decision-making freedom to its R&D scientists. As CEO Severin Schwan says, “We need a culture where people take risks because if you don’t take risks, you won’t have breakthrough innovation.”5 Air Liquide, the Paris-based world leader in industrial gases, has undertaken a major shift in strategy toward innovation and retention, driven by what CEO Benoit Poitier calls the “expertise, audacity and intuition” of its sixty-eight thousand employees.6 Air Liquide, like Roche, is achieving impressive levels of growth in an otherwise stagnant industry.
Or look at Lloyds Banking Group in the United Kingdom. It has put digital working at the heart of its new strategy, following its post-financial-crisis turnaround. In the words of CEO António Horta-Osório, the intention is to “get closer to customers and make the decision cycle happen more quickly.” A thousand-person digital team now reports in directly at board level, with a mandate to make the whole bank more agile. “This is a strategy adapting to the new world,” says Horta-Osório, “We want to create a high-performing organization . . . to be quicker than others to have a competitive advantage.”7
These brief company examples illustrate some important themes. Success in a fast-changing business world is a subtle blend of art and science. Rather than getting bogged down in analysis and introspection, fast/forward companies are open-minded, and they have operating cultures that promote action and experimentation. Their leaders know when to listen to the data and when to be decisive. As Jeff Bezos says, “There are decisions that can be made by analysis. . . . These are the best kinds of decisions! They’re fact-based decisions. Unfortunately, there’s this whole other set of decisions that you can’t ultimately boil down to a math problem,”8 namely the big bets on new businesses like the Kindle or Amazon Web Services.
Riding the Waves of Change
Arguably, decisive action and emotional conviction have always been important traits, but there are trends under way in today’s business world making them more important than ever. To appreciate that, let’s take a historical perspective.
Most casual observers would readily agree that we live in the information age, the period in human history characterized by the shift from traditional industry to an economy based on information computerization. It started with the roll-out of computer technology, and then evolved with subsequent waves of innovation in Internet connectivity and mobile communication.
At an individual level, we know exactly what living in the information age means, from the new ways in which we communicate with others to the transformation of our shopping and entertainment experiences. For better or worse, our teenage children have never bought a newspaper or a CD. Many young people have never visited a library, and really young kids can mistake a magazine for a broken iPad, as they swipe their finger across the cover page to no avail. There is even evidence that the Internet is literally rewiring our brains—increasing our capacity for “visual-spatial” intelligence and for multitasking, while decreasing our skills in concentration and contemplation.9
But what does operating in the information age mean for firms? Or more precisely, what are the characteristics of information-age firms that make them different from industrial-age firms?
First and foremost are the changes in the underlying source of profitability—the business model. In the industrial age, firms typically made money through economies of scale and scope. General Motors, Standard Oil, and Imperial Chemicals Industries got ahead by producing standardized products more efficiently than anyone else. In the information age, firms succeed because they create a constant flow of new products and services that their customers are prepared to pay a premium for. Such offerings typically stem from the smart use of information—economies of skill, rather than scale or scope. From Apple to Novo Nordisk and SAP to Nintendo, the leading firms of the last thirty years have achieved their success by harnessing information, creating knowledge, and attracting talent.
Second is the new internal way of working—the management model. The classical way of operating that took shape during the industrial age was the bureaucracy. This was a model built on standardized rules and procedures and hierarchical oversight—complicated structures inhabited by simple people. By structuring themselves in this way, firms such as General Motors were able to retain control over a complex set of operations and close to three hundred and fifty thousand employees. As the information age took hold through the 1970s and 1980s, tight control over employees became less feasible (as they had direct access to information) and less necessary (as they had the skills to make their own judgments). Gradually, an alternative management model—the meritocracy—emerged. This one was built on personal accountability and mutual adjustment—a simpler structure for more complicated people. Science-based firms, such as Merck and Intel, and professional services firms, such as McKinsey and Goldman Sachs, exemplify this approach.
Management thinking has also reflected this broad transition from the industrial to the information age. The 1920s saw the invention of scientific management, capital budgeting, and the multidivisional structure. In the postwar years we witnessed the rise of operations research, yield management, management by objectives, and matrix organizations. These managerial innovations were basically methodologies for enhancing efficiency and control. Move forward to the 1980s and beyond, and most of the new ideas were about harnessing information more effectively—intellectual capital, knowledge management, open innovation, design thinking, intellectual property rights, empowerment, and corporate venturing.10
The transition from the industrial age to the information age sets up an interesting question: What comes next? If the information age is just another period in human history, then we should not simply assume it lasts forever. The legendary Austrian economist Josef Schumpeter formulated one of the most pervasive principles of economic progress. He called it the cycle of creative destruction—there is always something new coming along that will succeed at the expense of the old. And this logic applies to historical eras as much as to industries or technologies. In fact, it applies to anything from high jumping to coffee bars. So how will historians in a hundred years interpret the period we are living through right now? Are we in the early stages of the information age, or in its twilight years? And what would a potential next age look like?
One influential view says, in essence, that we ain’t seen nothing yet. The changes brought about by the information revolution are still in their infancy. They will continue for many years, and indeed they will accelerate. Ray Kurzweil, the renowned futurist, inventor, and part-time director of engineering at Google, is the high priest of this movement. Born in 1948, Kurzweil has been a leading figure in artificial intelligence for forty-plus years. In his book The Age of Spiritual Machines he put forward the law of accelerating returns—the notion that technological changes are compounding over time, so that computer intelligence will actually overtake human intelligence within our lifetimes. A subsequent book, The Singularity Is Near, took this argument further and provided a specific date, 2045, for the singularity—the point at which progress is so rapid it outstrips humans’ ability to comprehend it. Several recent best-selling books, including Brynjolfsson and McAfee’s Second Machine Age and Martin Ford’s Rise of Robots, have expanded on this argument with bold predictions about how the world of business is being transformed.
For technophiles like Kurzweil, the basis of firm-level competitive advantage for the years ahead is simple: more data, more information, more knowledge. In other words, the competitive edge will come from finding new and better ways of harnessing information. And there are plenty of real cases illustrating this. For example, IBM has pledged its future on a “smarter planet” theme, and on investing hundreds of millions of dollars in its artificial intelligence division, Watson. Indeed, many of the corporate growth stories of the last decade involve companies (Google, Amazon, Facebook) that have been built on superior analytical techniques—figuring out the best algorithm for searching the Web, clever ways of predicting purchasing behavior, and so on.
But where these folks see a world of accelerating change, we see the seed of creative destruction taking hold. To be clear, technological innovation is a big part of our future, and harnessing information will continue to be an important part of every firm’s strategy. But we believe the costs and side effects of the information revolution have not been sufficiently understood. Following are a few quick observations:
• Information is ubiquitous. We can access an obscure piece of information in a matter of seconds while sitting on a train to Paddington station or a beach in Thailand, or during a walking holiday in the Alps.
• Search costs have plummeted. A day’s worth of research in the library or microfiche department in the 1980s might take half an hour today. It takes us longer to find an academic paper in our filing cabinet than to retrieve it online.
• Nothing is secret anymore. Even copyright-protected documents are often freely available. Open-access journals are on the rise. Even state secrets find their way into the public domain, thanks to the likes of whistleblowers such as Edward Snowden and Julian Assange.
• The veracity of online information is increasingly uncertain. For example, one study estimated that only 44 percent of website recommendations relating to infant sleeping were consistent with official guidelines.11 The old saying “Don’t believe everything you read” has taken on a new meaning in the era of information overload. In fact, there are many cases in which even the experts don’t agree on the implications of the facts. Just consider the dispute over global warming or which diet to follow.
Put these points together, and it is clear that information is no longer a “scarce resource” in any sense of the term. Nowadays, information technology is electronic plumbing—available to everyone. Of course, it is still possible for firms to create proprietary insights out of public information, but also this is becoming harder and harder. The idea that firms might generate sustainable competitive advantages through their privileged access to information is surely obsolete. Today, no one has a monopoly on information access—no country, no parent, no business, no teacher, no guru.
Attention!
So then what is the scarce resource in this world? What is the difficult thing to access and control that firms will base their future competitive advantage on? Actually, the answer to this question isn’t that tricky to find. In fact, Nobel Laureate Herbert Simon wrote about it forty years ago: it is our attention, our capacity to focus on and respond in an effective way to the stimuli we receive, that we need to worry about:
[I]n an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention.12
This insight is even more relevant today than it was back in 1971. The more we obsess over the power of information, the more we believe that the answer is in the data, the more blinkered we become. We lose the capacity to move fast, or the capacity to bring an intuitive point of view forward. We become victims of paralysis by analysis.
The negative consequences of having too much information—and too much faith in information—can be exemplified in a single number: 42. If you remember Douglas Adams’s Hitchhiker’s Guide to the Galaxy, this was the answer to the great question of life, the universe, and everything. Unfortunately, this answer had a few weaknesses: it took seven-and-a-half million years to compute (a severe case of analysis paralysis); it was expressed in a sterile, quantitative way with absolutely no context to help the user make sense of it; and as Douglas Adams himself pointed out, the question to which 42 was the answer wasn’t even clear. To figure that out, the computer concluded, they needed to build a bigger computer.
The problem of too much information is played out at multiple levels.
Individuals. We often claim we don’t have enough time in the workday. Actually, our biggest problem is a lack of focus and attention. We can’t make more time, but we can use the time we have in a more structured and productive way. Many people have their e-mail, their Facebook account, or their Twitter feed open all the time, resulting in an intermittent stream of distractions over the course of a working day. Studies have shown that if you are focusing on a difficult task—writing a report or thinking through a complex issue—a single distraction such as an e-mail takes up to twenty minutes to recover from.13
Easy access to information also creates an opposite problem, in that some people lose themselves in the data-collection process. As academics, we live in a “publish or perish” world—we become successful by making sense of what others have done and then building on that by creating our own unique contributions to a field of study. Over the years we have had several colleagues who never figured out when to stop reading and start writing. They became extremely knowledgeable, but they perished because they didn’t put their ideas down on paper. The same thing happens in a corporate context and with similar personal ramifications in a business world inhabited by “the quick and the dead.”
Teams. Have you ever experienced a meeting in which the absence of agreement on a tricky issue was resolved with a decision to collect more information? The answer is obvious—we all have. And did these additional data-gathering efforts resolve things? Again, the reply is self-evident. Difficult decisions by their nature require us to go beyond the data—to make a judgment call on fundamentally uncertain issues—to rely on intuition and gut. These are the kind of situations in which you are choosing between two bad alternatives or two good ones. Managers who crave the security of hard data just end up slowing everything down. You could probably not fit all the studies of decision making that have been done over the years into the Chrysler Building, but they all point us in the same direction. It is clear that lack of information is rarely the problem—when mistakes are made, it is much more likely to be a function of blinkered thinking, lack of character, or poor internal team dynamics, not an absence of data.
Firms. Most companies have a stage/gate process for bringing new products to market, and as time goes by such processes typically become lengthier and more sophisticated. To avoid making costly mistakes, the people running these processes ask for more and more information, and they insist on careful market testing. The result is typically an over-engineered, slow-to-market product. Examples include Lego Universe, an online game that lost out to Minecraft; IBM’s wasted investment in the OS/2 operating system in the 1990s; and the Volkswagen Phaeton, a masterpiece of engineering that never took off. Many big firms have fallen into the same trap over the years, putting their money into the products that “survived” the stage/gate process, only to find themselves beaten to market by nimbler or more market-savvy competitors.
Industries. Every now and then, entire industries are led astray by a fixation on the power of information. Look at the pharmaceutical industry. During the 1990s, the techniques of combinatorial chemistry and high-throughput screening were set to revolutionize the drug discovery process. They allowed researchers to create and test thousands of new organic compounds every year. It was a brute-force approach. The new way of doing things encouraged scientists to try all the possible compounds that might address a disease target. But the results were underwhelming. Big pharma R&D productivity declined through the 2000s. Increasingly, it was the biotech companies, working with “large molecule” biologic drugs rather than “small molecule” compounds, that were bringing the exciting new drugs to market.
Over the last decade, the pendulum has swung back toward a more traditional, hypothesis-driven approach to drug discovery. Under the rubric “rational drug discovery,” this approach seeks to get the best of both worlds. It does so by combining modern analytical techniques with creativity and insight, and it is facilitating some important medical breakthroughs. The lesson is clear—too much faith in the power of computer-based analysis is dangerous.
There are many such instances of firms and industries getting wrapped up in the value of information as an end in itself, rather than as a means to achieving their real objective.
There are other manifestations of this syndrome as well. Consider the old saying “A little learning is a dangerous thing.” As individuals, we are quick to access information that helps us. But we often lack the ability to make sense of it, or to use it appropriately. One of us has a brother who is a medical doctor. He encounters this problem on a daily basis (and we might add, he is not too happy about it). Patients show up with (often incorrect) self-diagnoses derived from spending a couple of hours on the Internet. It is the same in business: senior executives second-guess their subordinates because their corporate IT system gives them line-of-sight down to detailed plant-level data. At a societal level, people believe they have the right to information that is in the public interest (think Wikileaks), but they are rarely capable of interpreting and using it in a sensible way.
We can also think about the consequences of ubiquitous information for customers. Most of us now use sites such as booking.com or expedia.com to book flights and hotels on line, and we are keen to utilize comparison sites like pricerunner.com before making major purchases. Search costs have dropped precipitously. Switching costs are not far behind. In many industries, from air travel and holidays to banking and insurance, customer ignorance and loyalty-by-tradition were the biggest sources of profitability, but this is no longer the case. The transparency created by the Internet has empowered and educated us.
In sum, our argument is straightforward: information is no longer a scarce resource so it cannot be considered a source of competitive advantage for firms.
This is not an argument everyone wants to hear, as it goes against the prevailing wisdom of the last couple of decades. So when confronted with it, many observers say, “Yes, fair enough, information is a commodity. But our goal is to create firm-specific knowledge. This is distinctive and proprietary. Therefore, it serves as the basis of our competitive advantage.” Again, there is some truth to this argument. Think about a patent. It is a piece of codified intellectual property. Many firms also have genuinely distinctive “best practices” that others struggle to replicate. But even here, the story isn’t so simple.
First, knowledge is increasingly shared. Scientific knowledge is created more and more in research teams rather than by lone geniuses. Analysis of academic papers shows the average number of authors rising from 2.5 in 1981 to 5.1 in 2012.14 In physics, the discovery of the so-called Higgs-Boson particle was described in a 2015 paper with 5,154 authors.15 And the more knowledge is shared in the creation process, the harder it is for any one firm to gain proprietary advantage over it.
Second, the generation of new knowledge can end up being an end in itself. Truth be told, at most universities, creating knowledge for its own sake is the norm. Being called the smartest person in the room is a compliment. And that seems fair enough—it is in fact why universities were created in the first place.
But there are plenty of scientists and professionals working in firms today with a similar worldview. There is even a body of management thinking, the “resource-based view of the firm,” that encourages executives to look inside at their own distinctive resources and attributes as a way of justifying their existence.16 Needless to say, this is a dangerous habit to get into—we can all identify things that make us special; the much more important question is whether customers value those things enough to knock on our doors.
Third, knowledge is often defined too narrowly in business circles. The world-famous psychologist Howard Gardner has argued that there are nine types of human intelligence.17 Each one of these therefore has its own associated body of knowledge. But, as you may know, when it comes time to make tricky business decisions, only one of these really counts—the so-called “logical-mathematical” intelligence. This is the one we typically associate with engineers or accountants. It comes in the form of a well-structured business case, with lengthy spreadsheets, sensitivity analyses, and a Net Present Value calculation at the end—the stuff that you typically learn at a business school. A second type, “linguistic intelligence,” is also useful, as it helps us to convey our logical-mathematical evidence in a compelling way.
But what about emotional intelligence? And how do creativity, intuition, and personal feelings find their way into the discussion? Many famous leaders, including GEs Jack Welch, ABB’s Percy Barnevik, and Apple’s Steve Jobs, prided themselves on following their gut instinct, but this is not the norm. Instead, many firms do their best to squeeze out any sort of contribution that cannot be rationalized or quantified. Our view is that this approach is all very well, but it leads to sterile decision making—devoid of any sort of emotional resonance, either with the employees who have to implement it or the customers who have to live with it. And then there is of course the question of how an emotionally impotent leader can engage others—talent, customers, or other stakeholders.
So once again, the secret of corporate success is often the seed of its own downfall. All paradigms come with a best-before date. A single-minded emphasis on logical-mathematical-type knowledge helps firms to create clever and unique offerings, but with a risk that beauty, joy, surprise, spontaneity, and individuality are driven out. In every industry, there is a battle between the more “technical” brands (think Samsung or Toyota) and the “emotional” brands (think Apple or BMW), and while both can be successful, it is the latter group that captures the imagination and typically gets the higher margins as well. In fact, Kevin Roberts, former CEO of Saatchi & Saatchi, calls these lovemarks, rather than brands, because of the emotional resonance they create with their customers and employees.18
The Core Argument
In this book, we are proposing a new way of looking at the drivers of firm success in the information age. In many established firms, there is such an emphasis on information and knowledge for their own sake that people get distracted. Decisions are delayed, and attention becomes fragmented. But there are also some firms in which executives understand both the power and the limits of information. The leaders of these organizations know there are times when getting the “right answer” is imperative. But there are other times when being decisive and intuitive, acting swiftly and experimenting, works better.
Recall our examples of Amazon, WPP, and Oracle at the beginning of this chapter, companies whose leaders have shown how to blend rational and intuitive decision making. Facebook is another example—it’s a company famous for its clever analytical tools for monitoring and influencing our social networking behavior, yet it was still able to acquire WhatsApp in 2014 for $19 billion in record time, and largely on the basis of gut reasoning.
The pharmaceutical industry also exemplifies this point—the traditional big pharma players such as Merck, GSK, and Pfizer have the deep expertise and cutting-edge scientists, but they are losing out to nimbler biotechs such as Gilead and Amgen, and private-equity-style outfits such as Actavis Allergan, who understand that high science and commercial acumen can be successfully combined.
So here is the argument in a nutshell.
In today’s rapidly changing world, it is rarely the firms with the greatest processing power, the smartest data scientists, or the fastest connectivity that come out ahead. Instead, it is the ones that move forward faster than the others by developing the capacity for decisive action—the ability to address opportunities as they emerge, to experiment with new offerings, and to make big bets when called for. But action without direction is a dangerous commodity. To channel it in an effective way, firms also need to develop emotional conviction—to listen to their own intuitive reasoning, and to create meaning for their employees and their customers. To be effective, action needs adrenaline—in sports, in ballet, and in business.
The firms that succeed in this evolving information age will be characterized by decisive action allied to emotional conviction. This success formula can be summarized as fast/forward:
• Fast means alert, agile, experimental, capable of decisive action.
• Forward means proactive and searching, and it also means seeking to create an emotional connection with others.
These twin themes represent the core message in the book, and we will return to them throughout.
However, this is ultimately only one half of the story. It is easy to talk about decisive action and emotional conviction, but it is extremely difficult to enact them in a large, established firm. Traditional ways of working, as noted earlier, guide firms toward reflection and risk-aversion, and people need a very clear alternative model to move away from such habits and norms.
So the other half of our contribution in this book is to outline a new way of working, a new management model, for delivering on this fast/forward imperative.
Consider ING, the Amsterdam-based banking giant with fifty-two thousand employees around the world. ING went through a painful restructuring after the 2008 financial crisis, selling off product lines and rethinking its business model in the face of increasing levels of regulation. But rather than retreat into defensive mode, its executives embarked on an ambitious transformation program—a cleaning up and simplification of its internal processes, and then a strategic push into digital banking using organizing principles more commonly seen in Silicon Valley start-ups than staid European banks.
For the thirty-five hundred HQ employees, the old hierarchical structure was thrown out. In its place, starting in June 2015, people were assigned to autonomous nine-person “squads.” Each squad focused on servicing specific user needs (some internal, some external), with freedom to shape their own work-flow and physical space. The squads were then clustered into “tribes” of linked activities and supported by “agile coaches.”
We describe ING’s story in more detail later in the book. For the moment, the key point is that its new management model, inspired by fast-growing tech companies such as Spotify and Google, is built around addressing customer needs as efficiently as possible: squads are small, their responsibilities are forever changing, team members are empowered, and formal processes are used only when required by law.
This agile way of working requires a very different mind-set—executives have to be prepared to give up their traditional sources of power, and new skills have to be developed throughout the organization. But the benefits in terms of lower costs and higher levels of employee engagement are enormous, as ING has discovered.
The term we use to describe ING’s new management model is adhocracy. While this word has been around for years, it has typically been used in an informal way to describe the opposite of a bureaucracy. We are using a much more precise definition, one that links directly to the preceding arguments. To be specific,
• The default management model of the industrial age was the bureaucracy—in which coordination of activities occurs through standardized rules and procedures, and an individual’s formal hierarchical position is what matters.
• The now-standard management model of the information age is the meritocracy—in which coordination of activities occurs through the mutual adjustment of self-interested parties, and an individual’s knowledge and expertise is what matters.
• The newly emerging model that we believe is now required is the adhocracy—in which coordination of activities occurs around external opportunities, and an individual’s action is what matters, particularly when this is backed by emotional conviction.
We will have much more to say about these three models, but for now it is important to emphasize two points. First, these three models are about relative emphasis. In any organizational setting, formal position, knowledge, and action all matter, but typically one is privileged over the other two. In a traditional bureaucracy, the senior executive calls the shots because of her formal status (literally, the word hierarchy refers to one individual’s legitimate authority over another). In a meritocracy, such as a professional partnership, the person with the best argument holds sway over his fellow partners. And in an adhocracy—picture for example a hospital emergency room or a skunk-works project team—taking action is often more important than discussing or defaulting to the boss.
Second, these three models are “pure types,” meaning that they are easier to identify in theory than in reality. In real firms, you often see a mix of types. For example, an investment bank might have an analyst team that operates as a meritocracy, a trading floor that operates as an adhocracy, and a risk and compliance team that functions as a bureaucracy.
Given these two points, some people say to us, well surely we can be all three at the same time? Why do we have to choose? Our answer is that each model represents a default mode of operating, and for most people the default continues to be the bureaucracy or the meritocracy. When faced with an ambiguous situation, or a crisis, people revert to type, and the old established ways of working take over. So, given everything we have said so far, the challenge firms face today is to figure out—in broad terms—when they need to increase their emphasis on decisive action and emotional conviction, and to explicitly create an adhocracy to support this agenda.
The Fast/Forward Playbook
This book provides you with a blueprint for how to compete in today’s fast-changing business environment. We offer some important theoretical ideas, detailed case-study examples, and also some practical guidance to help you implement the ideas in your own firm. Figure 1.1 summarizes the overall structure of the book.
First we make the case that the world is changing in some surprising ways (Chapter 2). It is customary to point to the increasing levels of knowledge in society and the greater connectivity between individuals and firms. We acknowledge these points, but we also identify some second-order effects that are often ignored and indeed throw up some interesting paradoxes. For example, while each of us individually knows more every year, the rate of growth of knowledge in society is so much greater that actually we are becoming more ignorant, on a relative basis, over time. Similarly, the increasing level of connectivity between individuals, organizations, and economies results in a complex system with nonlinear features, which actually makes the future less predictable. We also do a deep dive into the surprising role of emotional belief in shaping behavior. One might expect advances in science to reduce our attachment to nonrational beliefs, but in fact the opposite seems to be true.
FIGURE 1.1 The Structure of the Book
How do these trends affect the business world? We go back to first principles, to the basic raison d’etre of the business firm, in order to explain how and why they work (Chapter 3). By revisiting these fundamental concepts, we identify three idealized management models, bureaucracy, meritocracy, and adhocracy. As briefly noted earlier, each of these models has a different emphasis, and each works better under certain conditions. And each one brings a different set of choices in terms of how decisions are made, how work gets coordination, how people are motivated, and how leaders do their work.
The second part of the book looks at each of these elements in turn.
A distinctive approach to strategy (Chapters 4 and 5). The classic approach to strategy was to think of a cascade of decisions: What do we want to achieve, Where will we play, How will we win? This logic was reasonably effective in a stable environment, but in a complex, fast-changing world it is too slow and too formulaic. So we need to turn this approach on its head. We develop a reverse-cascade model, in which insights based on interactions with customers drive the reflection-and-sense-making process, which ultimately informs the big-picture strategy. Chapter 4 describes this model in detail, and in particular the iterative nature of the strategy-making process between front-line employees and senior managers. Chapter 5 connects the day-to-day action in the firm with the overall sense of purpose that the firm has vis-à-vis its broader set of stakeholders.
A distinctive approach to organizing (Chapters 6 and 7). We home in on the adhocracy as the structure that enables decisive action and emotional conviction. In the adhocracy, action is privileged over formal position and individual knowledge. To operationalize this approach, firms need to build the appropriate set of structures, processes, and incentive systems. Using a whole range of contemporary examples, we show how this can be done. Chapter 6 focuses mostly on coordination issues, and how it is possible to organize the firm around its opportunities rather than its internal processes. In Chapter 7 we emphasize issues of individual motivation and engagement, and look more closely at the thorny challenge of encouraging well-intentioned failure.
A distinctive approach to leading (Chapters 8 and 9). Leaders who generate strong emotional conviction with their employees and customers are rare, perhaps not surprisingly when most of them are MBAs or engineers. But there are some exceptions to this rule, and in this chapter we describe their guiding principles, in particular the notion of ambidexterity, being able to do two very different things equally well. We also play up the aspects of leaders that are specific to the adhocracy: for example, they have a much greater emphasis on getting things done, learning from trial-and-error, and making a connection with customers than the type of leader who works best in a bureaucracy or meritocracy.
Finally, in Chapter 9, we discuss what fast/forward means for the individual employee working in the middle of a large organization. If you are such an individual, you have an unprecedented opportunity, in today’s business world, to take initiative and to make a difference. We invite you to become a bit more “unreasonable” in how you address and respond to opportunities on a day-to-day basis. Such an approach brings challenges, of course, but it beats taking a passive, fatalistic approach to your career and your working life.
Many of the concepts we are proposing will be familiar to you, but don’t be fooled into thinking they are easy to implement. Our hope is that by pulling these strands of thinking together—across the worlds of strategy, organization, and leadership—it will become easier for you to develop the language and methodologies of a fast/forward approach to business.
1. See E. Brynjolfsson and A. McAfee, The second machine age: Work, progress, and prosperity in a time of brilliant technologies (New York: W.W. Norton, 2014); J. Manyika, M.Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, and A. H. Byers, “Big data: The next frontier for innovation, competition, and productivity,” McKinsey Global Institute Report (May 2011); J. Barney, “Firm resources and sustained competitive advantage,” Journal of Management 17, no. 1 (1991): 99–120; B. Wernerfelt, “A resource-based view of the firm,” Strategic Management Journal 5, no. 2 (1984): 171–180.
2. This quote is taken from A. Deutschmann, “Inside the mind of Jeff Bezos,” Fast Company, August 1, 2004. See also A. Lashinsky, “Amazon’s Jeff Bezos: The ultimate disrupter,” Fortune, November 16, 2012.
3. Quotes in this paragraph are from R. C. Morais, “Kiss and punch,” Forbes, April 21, 2008; see also J. L. Schenker, “WPP’s digital push,” BusinessWeek Online, July 1, 2007.
4. These insights into Oracle’s strategy are taken from speeches by Larry Ellison and Thomas Kurian at the Oracle Open World Conference, San Francisco, October 2015. These speeches can be viewed at https://www.oracle.com/openworld/on-demand/index.html.
5. Quote from C. Copley and B. Hirschler, “For Roche CEO, celebrating failure is key to success,” Reuters News, September 17, 2014.
6. This information is taken from the Air Liquide website, at https://www.airliquide.com/connected-innovation/innovation-showcase.
7. These quotes are taken from E. Dunkley, “Horta-Osório unveils his digital vision for Lloyds Banking Group,” Financial Times, October 28, 2014; and P. Rodeia, “Refocusing and transforming a UK leader: An interview with the group chief executive of Lloyds Banking Group,” McKinsey Quarterly, March 2015.
8. Deutschmann, “Inside the mind.”.
9. N. Carr, The shallows: How the Internet is changing the way we think, read and remember (London: Atlantic Books, 2010).
10. See M. Mol and J. M. Birkinshaw, Giant steps in management (London: Pearson, 2008).
11. J. Rehman, “Accuracy of medical information on the Internet,” Scientific American, August 2, 2012.
12. H. A. Simon, “Designing organizations for an information-rich world,” in Computers, communication, and the public interest, ed. M. Greenberger, 40–41 (Baltimore: Johns Hopkins Press, 1971).
13. R. Friedman, “The cost of continuously checking email,” Harvard Business Review online, July 4, 2014.
14. C. King, “Single-author papers: A waning share of output, but still providing the tools for progress,” ThomsonReuters Science Watch, September 2013.
15. S. Chatrchyan, V. Khachatryan, A. M.Sirunyan, A. Tumasyan, W. Adam, E. Aguilo, T. Bergauer, and others, “Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC,” Physics Letters B, 716, no. 1 (2012): 30–61.
16. This “resource based” view of the firm has become enormous over the past two decades and is arguably the dominant way of thinking about strategy among academic scholars. See articles by Wernerfelt (1984) and Barney (1991); there is also a so-called “knowledge based” view of the firm; see, for example, R. M. Grant, “Toward a knowledge‐based theory of the firm,” Strategic Management Journal 17, no. S2 (1996): 109–122.
17. H. Gardner, Frames of mind: The theory of multiple intelligences (New York: Basic Books, 2011).
18. K. Roberts, Lovemarks: The future beyond brands (New York: powerHouse Books, 2005).
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