Volatile, Uncertain, Complex, and Ambiguous (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. We’d had roughly ten years of sole superpower status after the collapse of the USSR in 1991, and now, suddenly, we were in a world with radically empowered small asymmetric actors. For the first time in a decade, it was substantially less clear what kind of geosecurity world was coming next.
Would we now see a phase of globally increasing failed post-Communist states? Increasingly superempowered small political, terror, and criminal groups? A near peer China? A resurgent Russia? Suddenly our geostrategic future wasn’t clear. It had become hard to predict, in ways it hadn’t been over the entire Cold War, and for almost a decade afterward.
VUCA stands for Volatile, Uncertain, Complex, and Ambiguous. Let’s briefly look at each of these 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. There are lots of unknown unknowns, increasing risk and limiting understanding and predictability, and requiring much better empirical testing, deduction, and causal understanding.
- 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.
- Ambiguous. Causal structure is conflicting, or inputs unknown. 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 inputs are the most important in various contexts.
VUCA has become an increasingly popular acronym in the years since. Others began to adopt it to describe ever more rapidly changing financial markets, competitive conditions, and technological and social changes. It 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 these four conditions is most important for the problem you face, though I believe they define these four conditions less usefully than I have done above.
The bottom line is that VUCA conditions are all around us in a world of change. Besides viewing change from the CA3 perspective, looking for opportunities and upsides, there is great value in looking for VUCA, and strategically responding to the new danger, ignorance, and unpredictability that VUCA conditions bring. When we do so effectively we can be defensively proactive, and prevent a lot of unfortunate outcomes.
Finally, we must acknowledge a fifth actor, accelerating change, which makes VUCA conditions emerge increasingly rapidly over time, in certain contexts. We’ll explore those contexts in this chapter.
- 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.
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 not a complete acronym, because it left out acceleration, and the need to respond to it if we are to stay adaptive. General Electric CEO Jack Welch 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.” Thus VUCAA is an even better acronym for the defensive challenges of change, and the ways we must respond to an increasingly fast and complex world to improve our strategic foresight.
Like complexity then, acceleration can be viewed optimistically or defensively, depending on our perspective. The best response is to see both potential outcomes occurring at the same time, depending on our context and perspective. There are always individual winners and losers in any process of change, even if the system as a whole is continually getting smarter and more adaptive. As we’ll see in Chapter 6, Kuznets curves tell us that change often makes things worse before they get better, so the better we 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.
On the web, folks looking for simple labels will sometimes call me a “techno-utopian” thinker, as I talk about the probable, possible, and preferable nature of our increasingly intelligent technology. But that label is just libel, in my view. What I am is a protopian thinker. I think that various forms of progress are occurring in our most complex and adaptive systems, and while that progress can often be volatile, erratic, and dangerous on the individual level, with three forward steps often being followed by two backward steps, or with many Kuznets effects at first, I firmly believe that for the system as a whole, on average, we’re seeing ever more rapid movement toward measurably better states of the world.
I think history so far shows that our non-living universe, prehuman life on Earth, and now human society and its technology, have been evolving and developing more adaptive forms of complexity at steadily accelerating rates. As our complexity science grows up, I think we’ll learn how to measure those forms of progress in increasingly universal ways, making it something that everyone sees, once their own mental models have the appropriate definitions and complexity.
Let’s take a look at five primary forms of that progress now, in the third and most comprehensive view of change that I recommend for anyone seeking to improve their strategic foresight.