Do you hear lots about the VUCA environment (Volatility, uncertainty, complexity, ambiguity)? 

If you’re coaching in the real world (which is VUCA) as distinct from coaching in theory, it’s handy to be clear about those terms and consequently where you can help, and where you can’t.  Coaching practice really needs to recognise the way the world is – or coaching can turn into economics, sounding lovely in theory, but leading to financial meltdown in reality.

However, I see masses of practice based articles that mention these terms, often written by people who – sometimes in the same article – talk about how people shouldn’t be too risk averse, or should “calculate risk”.

Because I specialise in leadership around financial decisions it’s easier to demonstrate what I mean with financial examples, both because there are lots of numbers and measures of risk, and because I have lots of examples!

1. Uncertainty and risk

Consider a “gamble”, for example a casino.  You know the odds, the payoff if you win, the stakes (what you’ll lose), you know when the gamble finishes and when you’ll be paid (or have lost your stake), you know all the potential outcomes and can calculate a complete decision tree showing the odds and return of each potential series of outcomes.  And you know things won’t change in the middle (they won’t switch packs of cards or roulette wheels on you in the middle of the game).  So it’s totally calculable, we call it a gamble and “risky”, but it is (in insurance terms, because you can set a premium for it) a true risk, it’s mathematically precise.  It might be technically difficult to calculate, but it’s not complex, it’s simple. It’s also unambiguous.

Consider business, for example the investment in new plant.  You don’t know the odds of it “winning” or even what winning would look like, you don’t know what you’ll win if you do (whatever winning is), you may have no idea what the stakes are (you could have leveraged debt), you don’t “end” the bet (even with an exit strategy) or know when the payoff will come (if it does), you can’t know, let alone calculate, all the potential outcomes.  Consequently, you cannot construct a decision tree, which, even if you could, would be growing while you created it (for example, somebody comes along with new technology and puts you out of business – that wouldn’t happen in a casino).  So it’s not calculable at all, we call it a “calculated risk” but it’s not calculable and not a risk (in insurance terms, you’d call it uncertainty and refuse to insure it).  It is not just difficult, it’s impossible and it’s complex.  It’s uncertainty, not risk. The feedback you get is ambiguous, (did you go bust or make a profit because of your skill or by luck: there’s no way to tell for sure).

Implications:

I get asked about investment in those situations, to coach people about the “risks”. But they’re not risks, they’re uncertainties.  When I ask about how the client will cut through all the complexity and ambiguity of the potential future situations to try to put some numbers on potential outcomes, they start to realise that being “risk averse”, or not being mathematically savvy enough to calculate “risk” isn’t really the issue. 

What they don’t ask for help with, until I prompt them to, are decisions that look easy, but are actually difficult, such as complex situations involving uncertainty, where everything is guesswork and maths is largely useless.  That’s where I can really help, by asking the right questions.

2 . Ambiguity, chaos and complexity

I’ve already mentioned some of this, but let’s take another example.

A client is expanding into a new area, something they’ve done before (it could be a product area, a geographical area, anything, the principle is the same).  The assumption is often that a mentor is what is needed, somebody who has been there before.  So it’s simply a case of applying experience and calculating the risk.

Of course, it isn’t a risk, but how about applying experience.  The sort of extensive, high-level experience that the Boards of the Bank of England, the Treasury and the Federal Reserve had in 2007 that relaxed financial regulation and enabled the 2008 financial meltdown!

Sarcastic Kim! But there’s a point to that.  Decisions in life can be simple; kill or be killed, fight or flight etc.  On the other hand, most of life is “non-linear”, the total result can be more, less or bear no apparent resemblance to the sum of the parts.  Chaos means that the precise starting conditions may have a huge effect on the outcomes (the “butterfly effect”) so experience may be very misleading because apparently similar starting conditions lead to wildly different outcomes (the “repeat strategy” leads to massive profits first time round, bankruptcy the next).

Complexity means that there can be “emergence” – things happen as a result of interactions that you can’t predict from analysing all the parts.  Overall, human life can be seen as a complex, self-organising system on the edge of chaos – which is a fancy way of saying that it’s unpredictable and impossible to understand in detail!  Business is the result of lots of human lives and choices – it’s therefore even more complex and non-linear than any one of those lives.

Consequently, we cannot know all the options for action because we have absolutely no way to know all the potential outcomes, how all the parts would fit together in all the different combinations possible and we have no idea how they would influence one another. 

Implications:

The assumption is that experience of an industry, a process, a management level is vital.  It’s often handy, but it isn’t a guarantee.  When clients ask what experience I’ve got of CEO functioning or widget manufacture, it might be a fair point and I can’t help, maybe what they need is a guide to the way things are usually done – not how they can be done well, but how they are done conventionally.  But if they’re facing a real decision, then that sort of experience might be a disadvantage, as it could blind them to the actual ambiguity (and paucity) of data and the complexity of the situation.

Again, where the coach can help is in asking the right questions, getting the client to think about what assumptions they are making about the world being simple and predictable, the data unambiguous and the decision process one of repeating what has been done in “similar situations” in the past – chaos theory says that similarity doesn’t mean sameness, and it might mean totally different!

3. Volatility

People usually use the word volatility in the combustion sense, something that can flare up quickly, that is changeable.

And so it is. But in finance it’s got an allied meaning. A “volatile” stock is one that tends to move sharply up or down, and there are measures of the sharpness of the movement relative to the market as a whole, an index of a portion of the market, and so on.  Those measures (such as Beta, Sharpe Ratio, Smart Beta etc.) are part of the hunger for predictability an uncertain world. 

So in finance, when there’s talk about investors’ “risk appetite”, complaints that people are “risk averse” and regulations about matching investment portfolios to customer “risk profiles”, they’d love to be talking about risk – where they could apply some numbers.  Sadly, they can’t talk about risk, because it’s uncertainty.  So they call it risk, because that’s a nice fiction that makes people believe the numbers are meaningful.  Which leaves the problem of inventing some numbers to be meaningful.

You remember from your statistics homework the standard deviation. That is the square root of the deviance, which is a measure of dispersion.  In other words, it measures the amount of movement around the average, which is a fair description of the volatility.

So what financial people do is to substitute volatility for risk. They calculate, using statistics based on distributions, standard deviations etc. and look at how much the shares tend to move around compared to the “norm” within the market.  And they call that the “risk”.

Which is great.  Except:

I.   The stock market is not normally distributed (it’s platykurtic, which means fat-tailed).

II.   The data are not independent (prices one day depend on the prior days and influence the following days)

III.   The stats don’t work for the distribution we’ve got, and they only apply to independent data anyway.

The events of 2008 demonstrated that it’s actually a complex problem, it’s uncertainty, it’s not calculable, the data are ambiguous, the outcomes are not linearly dependent on the inputs and while the prices are volatile, you can’t accurately measure their volatility, certainly not by using maths that isn’t designed for the data you’ve got, that you can’t interpret unambiguously and whose volatility is complex and uncertain!

Implications:

A good coach could have asked the tough questions, like, “what are you assuming in this situation”, “how are you deriving your estimates of risk and volatility”, “given the data are ambiguous, how much of your own money have you gambled on your interpretation and only your interpretation being right”?

In conclusion

There’s a lot that a coach can do by asking questions, helping people think through the options more thoroughly, test their assumptions and recognise that living in a VUCA world isn’t just a phrase to say “yes, I know about that” and then carry on regardless.  It’s not helpful to acknowledge we live in that world and then go back to talking about risk, assuming data are reliable and unambiguous, that experience always has value, that the world is simple and interpretable in a linear fashion and that any word such as volatility always means the same thing irrespective of context and can be assigned values that are consistently meaningful.

It does mean pushing the client very hard, and a lot of clients really don’t like that.  We all tend to say, “I welcome constructive feedback”, but how many of us, hand on heart, really do like it when instead of the friend (or coach) that we’re counting on to say, “wow, you’re a genius” says, “how have you got these numbers, have you got any basis for this assumption, do you realise how many dependencies you’ve got that assume events occur in the order and for the reasons you expect?”?

So it’s tough to do, and tough to hear, but I think it’s what – at the executive level at least – coaches should be doing.

To connect with Kim: 

Kim is a former financial advisor and an Associate of the Chartered Insurance Institute (hence the interest in costs, ROI etc.) and now a Chartered Psychologist, coach and tutor/assessor in neuroscience.  He’s written two books on the psychology of personal finance and can be contacted on kim@stephenson-consulting.co.uk or via the website, www.tamingthepound.com.