Volatile, Uncertain, Complex, and Accelerating (VUCA): A Defensive View of Change
The acronym VUCA was developed in 2002 by defense scholars Judith Stiehm and Nicholas Townsend at the US Army War College to describe the new more complex and dangerous military environment we now lived in post-9/11/2001. After the collapse of the USSR in 1991, we had a “golden period” of roughly ten years of sole superpower status, partly reminiscent of America’s privileged position after World War II. We even had a federal surplus, from 1998-2001 (though the national debt did not go down), and the last time that happened was 1969. Post 9/11, we all recognized we were in a world with radically empowered small asymmetric actors, and had to do something about it.
After a decade of status quo, it was now substantially less clear what kind of geosecurity was coming next. Would we see a resurgent Russia, and a new phase of Cold War struggle in Eastern Europe? More autocracy or democracy? Increasingly superempowered small political, terror, and criminal groups? A near-peer China? All of these? Suddenly our geostrategic future wasn’t clear. It had become harder to predict, in ways it hadn’t been over the entire Cold War, and for roughly a decade afterward.
The original VUCA acronym stands for Volatile, Uncertain, Complex, and Ambiguous. As the Google Trend below shows, its use has become increasingly popular since 2012, as we see in the Google Trend below. One analysis of why this has happened is that we’ve seen more plutocracy, nationalism, extremism, a resurgence of autocracy, new conflict in the Middle East and Africa, and more obvious polarization and political dysfunction. That’s all true, but it’s an incomplete analysis, in my view.
The most fundamental driver of the new use of the VUCA term, in my estimation, has been the accelerating disruption we’ve seen in the marketplace, from big players like the FANG group (Facebook, Amazon, Netflix, Google) and the hundreds of new billion dollar startups, and the vast new venture capital funds driving them, all enabled by new intelligent technology and automation. Note that VUCA didn’t really blow up in use during the Great Financial Crisis in 2008-11, as global quantitative easing did much keep disruptiveness at bay.
But all that new money had to go somewhere, and it rapidly flowed to the top. That new money, along with a series of powerful accelerations in technological capabilities. investment, and entrepreneurship, has created new financial volatility and more rapidly-changing competitive conditions for both companies and workers. What’s more, when we look to the future of technologies like deep learning, and the rise of crowd-based economics around bitcoins and blockchain, both of which began their public ascent in 2012, it’s obvious that this disruptive technological acceleration is going to continue for the foreseeable future.
Leading capitalists have amassed astonishing sums for entrepreneurial investment, and they are using those sums to massively disrupt industries and consolidate power. For example, Softbank’s Masayoshi Son has used his massive $100B Vision Fund to force his way into owning major stakes in the leading disruptors like Uber, Nvidia, ARM, and many other tech companies, simply by threatening to give billions to their closest competitors instead. These rapidly growing companies usually don’t need or want the money, but they have to take it, and give up minority stakes, as a strategic defense. There is now so much money running around at the top, it is causing consolidation and disruption like never before.
VUCA (2004-2018). The uptick coincides directly with all the crazy new technology and investment money we’ve seen.
These technological and economic accelerations have been the central contributors to the growth of both wealth and plutocracy, and the increasing polarization, nationalism, and political dysfunction that plutocracy unfortunately breeds. We need an acceleration-aware perspective to understand VUCA conditions. Because better technology, globally applied, has such strong “winner-take-most” effects, wealth and power are increasingly racing to the few, and as they free themselves from the many, the conditions for the many are more unstable and uncertain than ever before. In A Future That Works (2017) James Manyika and colleagues at McKinsey Global argue that about half of the tasks that people currently do in their jobs could be automated by presently demonstrated technologies. Most folks are more uncertain with respect to their future incomes than ever before. Meanwhile, average wages have declined as a share of GDP in all our most technologically developed countries, and real wages for the bottom 50% of citizens in those countries are lower today than they were at the end of the 20th century. For most citizens of most democracies, things are presently going the wrong direction.
Given this analysis, I think we can improve the VUCA acronym in two ways.
First, we can recognize that Uncertain and Ambiguous are so similar, by definition, that they deserve to be grouped together. Uncertain typically means the causal structure and inputs to any complex system, as well as its outputs, are unclear, conflicting, or unknown. Ambiguous typically means a system has many possible outcomes (it is dynamically complex). Uncertain is thus a more encompassing and useful term for both of these conditions.
Second, we can recognizing that a missing fourth factor, Accelerating, is the one that has made VUCA conditions so prevalent today. While acceleration may be predictable in a variety of general ways, as we’ll see in this chapter, many of its specific consequences on individuals, organizations, and societies are far harder to predict, and we have a lot less time to try to anticipate and adapt to that change. It is accelerating change that has made VUCA such a useful acronym, and that scientific, technical, and economic acceleration is going to continue to drive change faster than many individuals and institutions can adapt, for the rest of of our careers. We need to recognize that, and get better at anticipating and managing the downsides of acceleration.
Our updated VUCA acronym stands for Volatile, Uncertain, Complex, and Accelerating., and we recommend you use that as a good summary of a defensive view of change. Let’s briefly look at some useful definitions of these four concepts in turn:
- Volatile. Conditions are nonlinear, with sensitive dependence on inputs and nonintuitive, disproportionate outputs, including exponential and superexponential outputs. Fluctuations can be increasingly rapid, chaotic, or extreme, increasing risk and limiting understanding and predictability, until we have sufficiently accurate nonlinear models and sensitive sensors.
- Uncertain. Causal structure and inputs are unclear, conflicting, or unknown. There are many possible outputs depending on assumptions and inputs, increasing risk and limiting understanding and predictability, until we’ve understood the conditions that determine which of many assumptions and potential causal factors are the most important in various contexts.
- Complex. There are many actors, variables, and degrees of freedom in structure and function, increasing risk and limiting understanding and predictability, until we have developed sufficiently complex models and input sensors.
- Accelerating. Outputs and dynamics are speeding up, increasing risk and limiting understanding and predictability, until the speed of our technology- and community-aided modeling, learning, experimentation, and leadership have increased to match, or exceed, the speed of change.
Again, VUCA is often used as a general stand-in for concept that a given process or environment has become increasingly dangerous, poorly understood, and poorly predictable. As Bennett and Lemoine argue in What VUCA Really Means for You, HBR Jan-Feb 2014, reducing danger and increasing understanding and predictability requires different strategies, depending on which of the VUCA conditions are most important for the problem you face. They didn’t include accelerating change in their analysis, but it a central driver of disruption, and so we are updating the term.
Human individuals, of course, only accelerate for a short time in our lives. We’re all individually on life cycle curves, which look like S-curves, with a declining and recycling phase at the end. But our interdependent society, by contrast to individuals, continually accelerates in certain special ways. As we’ll see in this chapter, some of these accelerating processes must be not only evolutionary (creative, unpredictable) but developmental (conservative, predictable) in a general, statistical way. Some of these accelerations are too smooth, too ubiquitous, and have been going on for too long (even longer than human civilization, as we’ll see) to be only a random, experimental, evolutionary process. If they were evolutionary, their signature would be variable, on a big picture scale. As we’ll see, some forms of acceleration appear to be baked into the “genes” of our particular universe, and thus we can expect there are developmental processes we will discover that protect this accelerating complexification, processes that continually increase adaptiveness, at the leading edge of change.
Defensive thinkers know that VUCA conditions are all around us, continually creating risk and danger, particularly to less adapted actors, who must increasingly be protected from the disruption that volatility creates, and empowered to become more adaptive. VUCA conditions also tell us that our defensive foresight, especially with regard to protecting any particular actor, is going to get increasingly challenging in some environments. DARPA was created with the mission to “prevent technological surprise”, but the reality is that such surprise (Uncertainty) is going to continue to hit us, in a world that is continually more Complex, Accelerating, and Volatile, particularly to less adapted individuals and institutions. When we look carefully for VUCA conditions, and ask what drives them, we can more strategically respond to the new danger, risk, ignorance, and unpredictability that those conditions bring. When we do so effectively we can be defensively proactive, and prevent a lot of unfortunate outcomes.
I began writing publicly about accelerating change at AccelerationWatch in 1999. When I first heard the VUCA term in the early 2000’s, I realized it was an incomplete acronym, because it left out acceleration, and the need to respond to it if we are to stay adaptive. General Electric CEO Jack Welch also saw this when he famously said “If the rate of change on the outside exceeds the rate of change on the inside, then the end is near.” This new VUCA acronym is a good reminder of the defensive challenges of change. We need fast strategy and fast foresight, in an increasingly fast and complex world
The Value and Limits of VUCA as Defensive Pessimism
As we learned in Chapters 1 and 2, psychiatrist and neuroscientist Dilip Jeste proposes that people view the world from two primary perspectives: as defensive pessimists, looking for problems to manage and respond to, or as strategic optimists, looking at the opportunities ahead. The VUCA perspective is the most adaptive summary I know of of the defensive pessimist’s world view, and we will treat VUCA and defensive pessimism as the same concepts in the Guide.
We observed that human beings have an evolutionary bias to defensive pessimism first and strongest, and that there is a pervasive mass media bias towards pessimism as well. We mentioned that defensive pessimists live 10% longer, on average, perhaps because they tend to better anticipate and avoid unnecessary risks, manage their resources better, and engage in more healthy behaviors. We said that in respect to security, politics, and competition, being a defensive pessimist can be highly adaptive. Let’s say more about the value of this perspective now.
Defensive pessimists are better than optimists at seeing and managing the saturation phase in every S-curve, when limits and discipline are the rule. They also are very good at identifying and avoiding Hype cycles, and at managing the first stages of Kuznets curves. As we saw in Chapter 4 (Models), Kuznets curves tell us that change often makes things worse before they get better, so the better we learn to anticipate potential downsides, and try to design against them, and respond to minimize them, the faster we can climb out of the Kuznets valley of dehumanizing impacts, and onto a Kuznets peak of even higher benefits than we had before the change began.
But as we’ll see in our next section, is not adaptive when we dwell on VUCA too long, too strongly, or out of balance with our strategic optimism. We live in a much safer, and far faster-improving world than it was when our defensive pessimism genes were selected. There are far more positive changes happening all around us, now on a daily basis. Lots of things really are getting better, much faster than defensive pessimists recognize. Being too pessimistic can blind us to both the reality and the controllable dynamics of accelerating progress. We will see and sieze far fewer of the opportunities we should over our lifetimes. So we must recognize its limits.
Even for security, defensive pessimists don’t always make the best leaders. Strategic optimists cause us to stretch just a bit beyond our reach, and they typically make the best CEOs, managers, and leaders. They motivate us to achieve more, and they more easily see exponential trends and opportunities. Defensive pessimists are often the best deputies, detectives, evaluators, critics, and advisors. They help us see things as they are, not as they could be. VUCA is a necessary world view, but it is not a sufficient. We need an additional perspective.
Let’s look now at CIBA, a strategically optimistic view of change.
