We no longer think in terms of copying the competition. It’s now innovation that moves markets in new directions. We no longer build a business as a group of individuals following a plan or list of repetitive tasks. Rather, we provide an environment in which employees feel motivated, learn, and have the freedom to modernize and evolve the way they work. No longer do we tell employees how to do their jobs. We encourage them to self-organize around the problems they face and to discover new habits that will enable them to find collective solutions.
Society is also advancing astronomically thanks to technologies that are changing the way companies are structured, and this is part of the new challenge leaders are facing.
The Decade of Moore’s Law
In 1965, Gordon Moore predicted that the number of transistors in a processor would double approximately every two years, and that this trend would continue for decades. His assertion is an example of cumulative growth. If we want to understand why companies are changing so rapidly, Moore’s law seems like a good place to start. Keep in mind, though, that this will be only part of the answer.
Let me guess. Your iPhone or equivalent smart device isn’t farther away than arm’s length, perhaps in your pocket as you’re reading this. If so, you probably realize the huge processing power contained within those few square inches. The most sophisticated phones today can process at a rate around 600 gigaflops.
The Gigaflop is a measuring unit for calculating the speed of a microprocessor. 1 Gigaflop equals 1 billion floating-point operations per second.
At the time this book was published, the iPhone X was selling in the United States for about $1,000. It offers the same processing power that would have cost you $12 million in 1997, or $15 trillion in 1984. These devices are incredibly powerful, and more people in the world have access to a smartphone than to drinking water. Realizing this is the first step to understanding how technology is accelerating change and why businesses must find new ways to operate and develop new frameworks to adapt.
The Era of Accelerating Returns
In 1999, Raymond Kurzweil, recognized futurist and the director of engineering at Google, proposed the law of accelerating returns. According to Kurzweil, the rate of change in a wide variety of evolutionary systems tends to increase exponentially when their systems are converted into digital information.
Take, for example, the processing power of your phone or other easily purchased electronic device. That processing power will multiply in a year, regardless of whether it doubles its circuits. This is because everyday discoveries are made that affect the speed of processors. Speed multiplies because devices and people interconnect. Think of domestic appliances that use the web to obtain information, or the possibilities the Internet offers in connecting individuals and ideas. That’s why you must take into account the habits of modern-day society and the impact of computers on the network of people (including smart gadgets, electronics, and software). Every day, tens of millions of people are accessing ever-cheaper technologies with power that will multiply in the next twelve months.
FIGURE 1.1: Kurzweil’s exponential acceleration of results, based on Raymond Kurzweil
In 2023, according to Kurzweil, people will have phones capable of processing the same amount of information as the human brain—and by 2050, of all the brains on the planet combined. This prediction applies not only to phones but to any technological device, including the software a business uses to discover, create, or improve products or services.
Even if you still think Kurzweil’s exponential acceleration is no more than an optimistic prediction, it is clear that the way products evolve is accelerating enormously.
The curve in Figure 1.1 is exponential, even though the line is relatively flat in its early stages. Each increment represents an increase in power between 10 and 100 times. Had we drawn the line cumulatively, it would easily reach Mars from your home.
The previously manual processes in many markets have been transferred to a microprocessor. Take photo processing. Around 1850, it would take weeks or even months to get your wedding photos. The tedious chemical process, done manually, required precise knowledge of the steps and chemical reactions involved. By 1950, the process had been simplified by advances in developing equipment and solutions. This reduced the processing time from weeks to days and required less expertise. But in the 1990s, a momentous event occurred, and photography entered the mainstream consumer’s price range. Photography had changed forever. Can you guess what happened?
FIGURE 1.2: Exponential evolution of photography
In the nineties, processes were digitalized, and cameras became sufficiently powerful at an affordable price. Photographs were transferred from a physical to a virtual form (computerized), becoming ones and zeros. From that moment on, there was an exponential acceleration in development similar to the curve on the Kurzweil graph. At this point, not only was it possible to instantly obtain photographs, but an extremely rapid evolution of the product had been sparked.
Kodak’s first digital camera weighed 3.5 kilos (7.7 pounds) and had a whopping 0.01 megapixels. Today, we carry 17-megapixel cameras in our pockets. We can add special effects, crop images, and retouch photos. We can even make biometric evaluations in a matter of seconds. I will explain later how and why Kodak’s digital-innovation strategy failed.
Every time manual processes pass from physical to digital (that is, composed of ones and zeros), there follows an evolution pattern that involves exponential acceleration. This is why future innovation is difficult to predict, leaving businesses open to constant surprises.
Before we move on, allow me to further illustrate what’s happening to help you better understand why it’s so difficult to predict the near future.
Imagine you and I are on a path, heading to a town on the outskirts of your city, and I ask you to take thirty steps in any direction. I could easily predict where you’d end up, assuming each step is about 80 cm, or 31 inches, long. If I told you that each step had to be twice as long as the previous, you’d end up much farther away, but I’d still be able to guess where you’d end up, because the results are clearly cumulative.
The real challenge comes when I tell you that the length of each step must be exponentially greater than the previous. The first five or six steps would be easy to predict. We could even confuse those first couple of steps with a linear progression, since they’d be quite small. But as you go on, making a prediction would become increasingly more difficult, bearing in mind that the distance between steps 29 and 30 would be about twenty-six times the earth’s orbit! Big jumps like this make it very difficult to guess where you’d be after each step, and it only gets harder. I could predict that step 29 would be large, but I’d have no idea where you’d land.
This is how exponential acceleration impacts on products, and this shift requires that companies adapt faster than ever. Business leaders who rely only on traditional techniques and methods will find it difficult to create an organization that can adapt quickly enough to the current market.
In the early stages of an exponential process, you can use tried-and-tested ways of working, because at this point the process is still linear and cumulative. But once it starts to accelerate, everything changes, and you’ll have to find a new approach if you want your company to succeed.
Digital-product innovation follows an exponential pattern of development. This makes it difficult to know where your product or company will stand in its next version and to predict the direction your competition will take in the coming months. When a process or task is digitalized, its speed goes from zero to a million in a matter of weeks—instead of decades, as we were once accustomed to.
So the problems we face can change at any time, and expectations are altered. This exponential pattern of development impacts on how we interact, and ultimately it influences society as a whole.
Unfortunately, exponential technological growth is counteri
ntuitive to the way our brain perceives the world. We are biologically programmed for life in an environment where events follow each other sequentially, and where evolution is cumulative. Because of this, all too many current business practices make it hard for employees to adapt. So how can you lead business transformation if common practices are becoming obsolete? What direction do you take if the future is so uncertain?
Change requires that we modify the foundation of our company, reason differently, and develop habits that enable us to acquire new skills in record time. But we must first understand why human beings cannot adapt to change so rapidly, and what tricks can be employed to overcome some of the obstacles. There are also social patterns we must examine—patterns derived from how we relate to one another in highly hierarchical organizations and patterns that prevent things from moving faster.
If all this isn’t reason enough to see reality through a different lens, business leaders, consultants, and coaches face a further challenge: technology is constantly learning.
When a Tesla car collided with another vehicle, the company run an update to make sure it wouldn’t happen again in the same way. The change affected not only that one vehicle but all the cars of the same model. The result was rapid, uniform technological “learning.”
But humans learn differently. We have to wait months, or even generations, to pass on learning and ensure that a group of people do not repeat the same mistake. This is why we need techniques that enable us to incorporate and apply learning more rapidly.
Change in the Era of Exponential Acceleration
You probably bought this book in part to learn how to make a change in your business and create a remarkable organization that offers superior products and services. But perhaps you’re not sure whether your company has products that will accelerate exponentially, or you might be unsure how to identify the current stage of your products. If this is what you’re thinking, you’re not alone.
You’re probably familiar with the Kodak company and even have childhood memories involving film that had to be developed. You might remember how it felt when we discovered what good (or bad) photographers we were. Kodak was huge back then. By the late seventies, it had 140,000 employees and a 28-billion-dollar market. It was practically a monopoly, and apart from Fujifilm, few companies dared, or had the strength, to take it on. In the United States, Kodak controlled 90 percent of the cinematographic market and 85 percent of the still-camera market. But only decades later, the company was bankrupt.
Kodak started out producing and selling photography development equipment, gradually moving into cameras for end consumers. In 1975, Steven Sasson, a twenty-four-year-old engineer, fresh out of university, demonstrated the first digital camera. It was bulky and took twenty-four seconds to take a black-and-white photo. Kodak’s management asked Sasson if he could calculate how long it would take for the digital camera to displace the paper-based industry. He came up with an estimate based on Moore’s law, and that’s when the problems began. The existing camera had 0.01 megapixels, and if this number doubled every two years, as Moore predicted, it would take ten to twelve years to reach the two megapixels required for acceptable image resolution. So managers who thought the new digital camera would undermine their chemical and photographic paper business decided to bury the idea.
What these managers failed to realize was that the leap the digital camera would undertake was exponential rather than cumulative, as Moore suggested, and they surely couldn’t have imagined the social impact this would have. Remember the example of the thirty steps? Well, doubling in the digital world is unusually deceptive, and we are not ready for it. Sasson was right in that there would be a disruption of the paper-based photography market, but the impact was to be much greater than he had imagined.
That’s when we learned that digital products, regardless of market niche or technology, accelerate after an initial stage of absolute calm. This means that companies must be ready to adapt ever more rapidly. For some companies, this will entail growing their development teams. For others, it will mean an increase in the list of things to do or shifts in their internal structures to better respond to their markets. The adaptation process might reveal that resources within the organization are scarce. Digital products accelerate exponentially, learn uniformly, and force businesses to be increasingly more flexible each day.
During its initial stages, a digital product evolves slowly, which can mislead people into believing that it will grow in a linear fashion. Although it’s true that at first you can use traditional techniques to manage products, as soon as the evolution curve accelerates, everything changes, and this will catch you off guard if you’re not ready.
Steven Kotler and Peter H. Diamandis, authors of Abundance: The Future Is Better Than You Think, point out that the six Ds of Exponentials have to be considered to identify the stage of acceleration a product has reached. The six Ds are a chain reaction that enable us to recognize what comes next. The following six Ds thereby help us make better, more informed decisions. These six Ds are:
Digitalization
Deception
Disruption
Demonetization
Dematerialization
Democratization
The first step for something to accelerate exponentially, and possibly surprise us, is for its process to go Digital. Once this happens, it can propagate at the speed of light—or at least the speed of the Internet—and become free to reproduce and share. This propagation follows a consistent pattern: an evolution or growth curve that is exponential (although it looks linear in the early stages). In the case of Kodak, once film changed from a physical to a digital medium, its rate of growth turned totally unpredictable.
FIGURE 1.3: The impact of exponential growth and the six Ds
This is followed by the Deceptive growth phase. The first 0.01 megapixel Kodak camera went unnoticed for a long time. It grew from 0.01 to 0.02, 0.04, and 0.08 megapixels, and this certainly seemed linear enough. Again, remember that the first steps in an exponential curve produce small changes and are consequently confused with a linear process, tempting many to use traditional methods to manage growth. No one would want a 0.04 or even a 0.16 megapixel camera. The industry carried on looking the other way, and leadership continued thinking that the product would have no short-term impact.
What comes next is deceptive early growth, or so-called market Disruption. Think back to the steps illustration again. From steps 15 or 20 onward, growth turned unimaginable. As it relates to a specific product, this means that the market is left perplexed. Competing companies won’t know how it was possible that something, in such early stages, could grow so quickly, and they will struggle in deciding how to respond. The first camera was 0.01 megapixels. Then, all of a sudden, it was ten megapixels—and you have to compete with them. Surprise!
You won’t see much change in the early stages of a product. It’s only in later stages that the line begins to curve upward. This is simply the nature of exponential multiplication—things happen slowly before accelerating abruptly.
Because photographs are now bits (Demonetization & Dematerialization), cameras become smaller and begin to be integrated into other devices. At this point, you no longer have a camera. You have a mobile phone with the functionality of a camera, as well as music, and a long list of added functionalities. Think of all the luxury technologies of the eighties that have been dematerialized and are now incorporated into a single device at the same, or much lower, price.
The last phase is Democratization. Technology makes it possible to take pictures without having to buy film, much less develop it. Everything is digital. You can download editing applications for free or at a low cost ($1 to $3 in any app store). The possibilities are endlessly more accessible and affordable. Mobile phones are a classic example of democratization. In the eighties, they were considered luxury technology, products we’d only see on programs
such as Miami Vice. But today, just about anyone can buy one.
The six Ds cycle repeats itself with any product or process that goes digital. If you try to use work methods that do not account for this concept, your method may work reasonably well—until you reach the third stage, Disruption. This will be deceptive at first, because standard metrics will give you the illusion that everything is under control.
Managers and employees may be happy for a few months, drawing up their long-term plans and predictions. However, the situation will turn chaotic as soon as growth of the competing product starts to multiply—exponentially. And that’s when the team will get nervous, and management will mistakenly want to exercise more control to get the results they are hoping for. But more control will not give way to rapid adaptation.
Focusing on a Healthy Organization
If markets are stable and the evolution of innovation is predictable, you could use rigid processes to ensure everything is under control. Problems arise when threats to success cannot be controlled, are mostly unpredictable, and accelerate over time. And we must add the deceptive initial stages, which falsely lead us to believe that a linear evolution is involved. Under this insecurity, you’ll have to look for solutions to enable your business to adapt and thrive.
For several decades, the mantra of successful organizations was to maintain a strategy that aligned people around long-term objectives and well-structured plans. But this promotes neither development nor constant adaptation, and I’ll explain this further in later chapters.
Leading Exponential Change Page 2
