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18 Sep 2014

Apocalyptic Decision Making – Dealing with Volatility

Four Horsemen of Apocalyptic Decision Making

Four Horsemen of Apocalyptic Decision Making

Nathan Bennett and G. James Lemoine (“What VUCA Really Means for You” [Harvard Business Review, January 2014 edition]) superficially introduced the four horsemen of apocalyptic decision making (Volatility, Uncertainty, Complexity and Ambiguity [VUCA]). This post dives deeper into volatility, and future ones will address the others. While two or more are often at play, for my analyses only the one under discussion will be. The objective is to increase our comfort level in dealing with these four.

Frequent and extreme changes characterize volatility. If the other three are not in the picture that means our event is not overly complex, ambiguous or uncertain. Using Bennett’s and Lemoine’s example of prices fluctuating after a natural disaster, that means prices might fluctuate wildly over the short run, but we reasonably should be able to predict their long term. That means ensuring we’re in position to “ride out the storm.” Once that’s assured, short-term opportunities might avail themselves.

Other examples include:

  • Suppliers dumping product onto the market, issuing recalls or severely reducing production
  • Employers laying off or massively hiring talent we typically need
  • New competitors making a splash without sustainability
  • Legislative changes drastically altering the “rules of play”

Again, assuming the other three are not present, the long term should be reasonably simple, clear and certain. Our allies will be history and experience in finding related patterns, and statistical and data analysis in determining long-term trends. Once done, we’ll need to re-verify that current policies, processes and procedures will get us there.

Managerially, we’ll need to avert the natural reaction of responding immediately to every change or new information. Once we’ve determined the best long-term destination for riding out the storm, and once we’ve assured ourselves our infrastructure can carry us there, it’s a matter of securing the resources to do that.

 

Series Navigation<< The Four Horsemen of Apocalyptic Decision MakingApocalyptic Decision Making – Dealing with Uncertainty >>

5 Responses

  1. It would be my position that VUCA could be disrupters; but a better approach (as always) is to see them as opportunities! For example, on the price fluctuation, how about resisting the temptation to raise your prices due to demand? The margin was already determined as necessary for business viability; AND building customer loyalty by maintaining them builds longterm success.

    I’ve always suggested to my students that “the only thing certain is uncertainty.” I look forward to your thoughts.

    1. Mike Lehr

      In a broad general context, your position is an excellent one.

      Within the context of this post and series, here is the problem: since people are never taught to deal with VUCA well, they tend to ignore or discount them. Often, VUCA don’t even work themselves into decisions. With that in mind, they certainly do become disruptors if we don’t consider them. That is why I chose to characterize them that way.

      For example, I sat on the board of a non-profit which was reworking their policies. They decided to say in the preamble of a series of employee grievance policies, “We can only deal with problems if we know about them.” This is not true. It ignores preventative measures. Just because I don’t know if termites exist in my house doesn’t mean I don’t take measures to protect my house from them.

      Your solution is definitely a solution. In my post, I recommend calling on experience, history and trend analysis to see if that solution is a good one. The Harvard Business Review article did now cover how to address problems caused by volatility. It only gave a solution to its example. What I did in this post is give advice on HOW to arrive at such a solution as yours. The post is about process not outcome. Too many times we’re so busy giving people advice on solutions that we often forget to show them HOW to arrive at solutions themselves.

      Your quote is a good one, and I’ll save it for when I address uncertainty. This post is about volatility. As I mention in the post, while two or more variables of VUCA are often at play, I’m isolating each variable so I can introduce some basic problem-solving processes to deal with each. Analogously, I’m measuring the amount of salt in salt water by evaporating the water. So to explain volatility and possible steps to address, I’m isolating it for the moment by “evaporating” uncertainty, complexity and ambiguity. The problem here is a training one: how to demonstrate ways to address VUCA. My solution is to address each one and assume for the moment the others are not in play. So, for this post, volatility exists but reasonable certainty, simplicity and clarity do too. So the question becomes, “How do I deal with volatility when most other aspects of the problem are reasonably certain, simple and clear?”

      Going with your solution, certainty, simplicity and clarity would come from history or data analysis that showed going through similar volatile events resulted in a long term price of X that is best navigated to by holding our margins and building customer loyalty. While I would say that uncertainty, even to a small degree, always exists. For the moment, in order to introduce a basic process for working volatility into a larger decision, I am stating that uncertainty isn’t dramatically at play here. Later, when I do the same for all four variable of VUCA, the challenge is putting them together into a more comprehensive problem-solving process. I can’t do that though until I establish some basic processes upon which to build.

      Again, the main problem is that when something is too uncertain, too complex, too ambiguous or too volatile, people tend to say, “Well, it’s too uncertain, too complex or too ambiguous with which to deal.” The question of whether VUCA are opportunities or disruptors doesn’t even enter the picture because people have moved on to “Well, let’s see what we DO know,” or “Let’s simplify it so we can deal with it,” or “We don’t have any measurable proof to base a decision on that.” That is the critical byproduct of VUCA, and that is the problem this post and series tackle.

      Thank you as always for visiting, John.

      1. There is absolutely every reason to provide the “isolated” ones each one at a time – with the caution you give that the often occur simultaneously. Great follow-up dialogue opportunities!!!

  2. Ralph Winters

    Interesting concept. I see that VUCA has been around since the 90’s but somehow I missed this particular buzzword.

    Nowhere is this more evident than in the changes that are happening in Healthcare. The “opportunity” part is definitely evidenced by the rising of the ACO’s, however for many involved there is much risk uncertainty and ambiguity to be probabilistic confident of anything.

    Volatility is actually the one piece that can be controlled, since bounds can be defined. Since of course assumes constant volatility, all of the VUCA parts are definitely intertwined, and one level affects the other. Historical data can help define what is baseline and what is probable, and Bayesian techniques can be use to inject and subjective assumptions that one has. That fact that there are so many pieces in play also suggests that Black Swans are possible and nothing that we predict will matter anyway!

    I think hedging is always a good course of action when decisions need to be made. Of course this is to minimize risk. Not really applicable if the intent is to go for the big win.

    1. Mike Lehr

      Well, Ralph, you might have missed the buzzword, but I’m certain you’re well versed on them. As you know, there is a difference between knowing the language and knowing the idea.

      You’re right though, these four are often intertwined. Still, I found the Harvard Business Review article helpful because it was inline with my observations: when confronted by these four horsemen, deciders tend to discount or ignore them. This will either produce unwarranted inaction or dubious plans. I do believe that probabilistic decisions are possible when matched by hedges that are inline with that probability. Bets don’t have to be an “all or nothing” option. To me, that is a perfect example of the oversimplification humans tend to want in an extremely complex world. As a result, they throw up their arms and say, “Well, we really don’t know, so let’s not decide anything.” I do believe big data has the capability to help us sort through some of this. In addition to the statistical methods you mention, experience and “gaming scenarios” help here too (see Board War Games Superior to High-tech Simulations http://wp.me/p4iBnv-1qI).

      Black Swans are always possible. Predictions do matter as long as we associate them with appropriate probabilities. Take the weather for instance, too often when people read 60% chance of rain and it doesn’t rain, they cite the weather pros as wrong. Also, predictions’ value go well beyond whether they end up right or wrong. They help to prepare us and our employees mentally for the task as we (hopefully) have run through many scenarios before we deciding to hedge against a few because we can’t do all. That is where gaming different scenarios help. How these manifest themselves in the allocation of resources and various actions is where gaming scenarios help. As Eisenhower said (although I have found numerous variations of this quote), “Planning is essential to battle, but battles rarely go according to plan.” Just because we can’t quantify probabilities in our plan within the confidences we like, doesn’t mean we don’t even attempt to form a plan.

      For example, the hedging you mention is important but if our organization has problems making swift decisions once more certain information is available, swifter competitors will leave us in the dust and obsolete. Gaming will at least show where those structural weaknesses might be and help our organization decide whether it might be better off trying to make a more solid bet on one or more scenarios. Even if we don’t know the change to make, we can at least know what we need to change or modify even temporarily to prepare our organization to adapt quickly. As illustration, just take the budgeting process. That alone hinders and lengthens many organizations decision-making capabilities.

      Still, the purpose of this post and series is to provide some back-end techniques for trying to deal with each of these. Once those are set we can combine them and use them to deal with the problem more holistically. I very much see an excellent training problem here. I’m solving it by breaking the problem down, isolating each component of VUCA, training on each and then reassembling the techniques. Keep in mind that while we can accept that all four will likely be in play for any event, especially in the current healthcare environment, all four won’t be at play to the same extent on all the different aspects and sub-events of this event.

      It is possible to probabilistically assess various scenarios using the analytic tools in your profession and combining them with honest, experienced and knowledgeable professionals in a regular gaming process as long as people have the mindset and personalities to transcend the natural inclination of oversimplifying. Otherwise, they’ll just throw up their hands and say, “It can’t be done so let’s wait,” or derive preposterous scenarios that serve no value except look fantastic in presentations.

      Of course, maybe the exercise will just prove that this buzzword is over-intellectualizing what is more commonly seen as unknowable events so some experts can make money on it.

      Thank you for visiting and commenting, Ralph. I appreciate it and your continued insights on Twitter. ~Mike

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