CHAPTER 2
Spark: Acceleration of the Vicious Cycle

Before we move forward to examine how to blow up your best practices and what new attitudes to adopt, it's worth taking a step back to consider why unknowingly pursuing conventional wisdom has become a path to almost assured failure.

At both the individual and corporate level, the enabling belief for conventional wisdom is anchored in the perception of permanence – the idea that nothing's going to change, or, if it does, that it will change slowly and predictably. And that has been – until recently – a perfectly reasonable belief system. For the vast majority of business history, companies have simply needed to “evolve” to compete effectively. The pace of change has been such that we have only needed gradual adaptation in order to survive; we haven't really needed to consider existential threat.

Put simply, most businesses have operated in a state of linear and evolutionary change. That will change, replaced by something that feels much more disruptive and revolutionary. And the average businessperson is devastatingly ill-equipped to face this new world. If you're not feeling a sense of urgency, you should.

The evidence is undeniable that, even in the past five years, the rise of technology and all things digital has fundamentally altered business landscapes and notions of what we have long held to be true. The advancement of technology is making possible the breaking down of long-standing barriers or allowing companies to replicate customer value propositions at fractions of the costs, or creating goods or services that couldn't have existed not so long ago, and the clock speed of this transition is happening fast because of computing power.

Microfactories that leverage additive manufacturing and crowdsourcing allow new players to challenge scale and scope advantages from day one. We can drive radical improvements in efficiency in completely new ways using technologies such as robotic process automation. New business models founded on data proliferation destroy traditional assumptions about what a cost structure and operating system need to look like. And executives are suddenly discovering that the constraints and trade-offs with which they have been grappling are now extinct.

Consider the case of getting a custom-made shirt. Not too long ago, you would have needed to go to a tailor who would take your measurements. The tailor got paid for their expertise. Now, all that time and cost can be replicated by a camera on a smartphone (this is, for instance, the value proposition of the service M Tailor).

The outcome for the consumer is still the same – a custom-made shirt. But the cost has dramatically shifted. This is an example of disruption in practice. It's not that the tailor was doing anything wrong. It's that technology has enabled the ability to replicate (and perhaps augment, if you consider convenience and time for measurement) what they do and at a considerably lower cost.

Or consider the case of a typical retail business. A prototypical business model was to try to create substantial presence within a given footprint to create the likelihood that customers would notice and ultimately visit and purchase from your store. However, advances in technology and forward thinking have given the consumer what they appear to really want – the ability to have nearly endless selection, the convenience of not leaving their house, and good enough delivery times. What was once an advantage has been turned into an Achilles' heel – too much cost deployed against something the consumer no longer values.

We simply can't presume that the future will unfold at the same pace as the past has – this is true not only for our companies and industries but also for the larger macroeconomic context. Consider the story of the steady spread of globalization – the cross-border movement of goods, services, capital, and labor that has been growing for decades. While experts predict the same steady progress in the future, what if “developed” nations don't gradually turn from service-based economies to information-based ones but do so suddenly? What if “emerging” economies skip development stages altogether? What if new technologies such as robotics and artificial intelligence render supply chain professionals obsolete within five years?

But it's not a question of if something is going to happen. It's a question of when.

To put it even more bluntly: Uber ate the global taxi industry. And you're hoping it won't happen to your business. But it will, and soon.

THE IMPACT OF EXPONENTIALS

Founded by Ray Kurzweil and Peter Diamandis, Singularity University (SU) has committed itself to understanding the impact of “exponential technologies” on the world around us. We've talked extensively with SU about how exponentials have the potential to radically change the world around us.

Moore's Law and Kurzweil's Law of Accelerating Returns are both fundamental to understanding the nature of exponential change. The former is likely the better known of the two, and it stems from an observation made by Gordon Moore, the cofounder of Fairchild Semiconductor and Intel. In the mid-1960s, he famously predicted that the number of components per integrated circuit would continue to double every year for at least the next decade. History has squabbled a bit about whether 1 year, 2 years, or 18 months was Moore's predicted doubling time frame, but the reality is that, for 50 years, the prediction of exponential growth in transistor count held true.4

As we write, Ray Kurzweil is Director of Engineering for Google, although he's more frequently referred to as its “chief futurist.” Kurzweil has enjoyed a storied career as an inventor, entrepreneur, author, speaker, and prognosticator. His Law of Accelerating Returns stipulates that: “the rate of progress in any evolutionary learning environment (a system that learns via trial and error over time) increases exponentially. The more advanced a system that improves through iterative learning becomes, the faster it can progress.”5 Both laws helped provide the foundation for SU's core area of research.

Exponential technologies include – among others –augmented reality (AR), virtual reality (VR), artificial intelligence (AI), robotics, digital biology, and data science. What knits them together is that in each, their power and/or speed doubles every year, or their costs drops by half – or both. Because all are powered by an exponential increase in computing capacity, we can assume (and indeed have seen evidence that) they themselves will grow exponentially as well. Spurred in large part by the vision of cofounder Peter Diamandis – among other roles, the founder of the X Prize Foundation – SU sees the opportunity for unparalleled good and advancement to come from exponentials in addressing some of the world's most pressing challenges.

SU posits that “when two or more of these technologies are used in combination to attack a persistent challenge, the possibility of developing a sustainable solution becomes much more likely.” This has given rise to the belief in an “abundance mindset” in which no problem exists that can't be addressed by applying exponential technologies and innovation. As Elon Musk brings to the here-and-now futuristic visions of democratized space travel, hyperloops and fully autonomous vehicles, SU may be on to something, and indeed we all have ever more reason to be hopeful about the future.

We are likewise optimistic but also see the flip side: the possibility for massive disruption of all aspects of legacy business models. As SU has taught us, humans are simply not equipped to process exponential growth or to even imagine how to harness it because we have always lived in – in fact, evolved in – a linear world. One of SU's famous challenges is to imagine taking 30 steps. Thirty linear steps would take you across the room. Thirty exponential steps – in which the distance covered doubles with each step – would take you around Earth 26 times. Because we all innately assume a constant rate of change, we completely underestimate the power of exponentials: power for good but also for disruption.

THE CHANGING NATURE OF COMPETITIVE ADVANTAGE

Traditional ways of producing competitive advantage are also being overturned. Bruce Greenwald, an economist at Columbia University's Graduate School of Business, has written extensively about the nature of competitive advantage. He argues that there are three categories of advantage: supply, demand, and economies of scale. Supply advantages stem from a company's proprietary access to an input that enables its customer offer. It might be proprietary or preferred access to raw material inputs, intellectual property, technology or any other input. Demand advantage happens when a company has captive or near-captive access to a group of customers. It's stronger than a preference – which can be changed based on competitors out-differentiating a group of customers. And it's far more than “brand preference,” as history is littered with brands that are well “liked” or “admired” only to lose customers to an upstart brand. Demand advantages exist when customers are virtually locked in – typically through switching...