Embrace Complexity

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At the annual Gartner Supply Chain Conference (which used to be the AMR Research Supply Chain Conference) Jane Barrett introduced the term VUCAVolatility, Uncertainty, Complexity, and Ambiguity As I stated in a blog after the conference, far too much effort is spent on figuring out how to remove VUCA from supply chains, how to suppress it.  At the time I wrote that people should embrace volatility. So I was very pleased when four months later the Harvard Business Review headlined the September issue with “Embracing Complexity,” another of the elements of VUCA. While the articles were definitely interesting, there were several lively debates in the Comments section.  What struck me in the comments was the polarization between those that believe one can pull apart a system in order understand it and then use this knowledge to reduce the complexity and thereby dampen the volatility. On the other hand there are those that believe that most system are too complex to understand completely, that the whole is a lot more than the sum of the parts.  I fall more into the latter group than the former. What fascinates me is that this same duality of ‘simplicity’ and ‘complexity’ plays itself out in supply chain management between those that believe if we could only create the perfect plan all would be OK, and those, like me, who believe the perfect plan is not achievable so you had best focus on what Hau Lee calls the “Triple-A” supply chain – Agile, Aligned, Adaptable.  But I don’t fall into the group that believe planning is “useless, ” but if we accept that we all have limited budgets, too much of that budget is focused on creating the perfect plan and too little of the budget is focused on developing the skills and capabilities to respond very quickly to real demand. It is only the very rich or the very stupid that do not plan for retirement. But life has interceded to bring us not one, but two major down turns in the stock market in three years.  What do we do now?  Understanding how we recover is not a simple 1+1=2 equation.  It is a lot more complex than that. This is true too of most decisions made by companies, not only in their supply chains, but their operations as a whole.  What we need is some way to test alternatives – "what-if's" – and evaluate the best course of action based on input from multiple people that allows me to balance hard facts with subjective option. This is the essence of embracing complexity. There is no “easy” button because there is no linear relationship between action and result, cause and effect.  Before anyone discounts my views, let’s have a look at some points from the HBR articles.

  • Embracing Complexity – Interview of Michael Mauboussin
    • Consider capital markets… complexity doesn’t lend itself to tidy mathematics in the way that some traditional, linear financial models do.
    • …humans are incredibly good at linking cause and effect – sometime too good. Ten thousand years ago most cause and effect was pretty clear…but it means that when you see something occur in a complex adaptive system, your mind is going to create a narrative to explain what happened...we have a tendency to think that certain causes will lead to particular effects.
    • …we tend to listen to experts, although it’s been well documented that expert predictions are quite poor.
    • …in complex adaptive systems, a rapidly changing environment, we don’t really know how things are going to unfold…recommend creating a set of decision rules…let people decide on the fly in the field what they think makes most sense…never violate the basic rules, but they have a lot of flexibility to actually decide from moment to moment.
  • Learning to Live with Complexity – Gökce Sargut and Rita Gunther McGrath
    • Rare events can be more significant than average ones – and may occur more often than we think
    • Human beings’ cognitive limitations mean that no manager can understand all aspects of the business, but many refuse to acknowledge this limits
    • We’ve observed two problems commonly faced by managers of complex systems: unintended consequences and difficulty making sense of a situation
    • Embedded in many analytic tools are two assumptions that don’t hold for complex systems
      • The first is that observations of phenomena are truly independent
        • This is often not the case in complex systems, with their highly interconnected parts
      • The second is that it is possible to extrapolate averages or medians to entire populations
        • It shows up when we fail to consider that outliers are often more interesting than the average case.
        • In business, the problem shows up when companies try to predict customer behavior on the basis of average response.
  • Smart Rules: Six Way to Get People to Solve Problems Without You – Yves Morieux
    • CEOs commit to 25 to 40 performance imperatives today compared to 4 to 6 in 1955
    • Many of those requirements appear to be in conflict
      • Customers want to satisfy their customers who demand low prices and high quality
    • In complicated organizations, managers spend 40 percent of their time writing reports and 30 percent to 60 percent of it in meetings
      • Note to reader: Complicated and Complex are not the same thing, though often companies will try to put in place complicated processes to manage complex situations, which only compounds the issue.
    • To address each new [business] requirement, companies typically set up a dedicated function and then create systems to coordinate it with other functions.  That explains why organizational (the number of procedures, vertical layers, interface structures, coordination bodies, and decision approvals) has seen a sharp increase.  This complicatedness hurts productivity and employee engagement.

In “Learning to Live with Complexity” the authors advocate that simulating the behavior of a system is key to both understanding and the ability to respond

appropriately.  In fact they sate that Instead of extrapolating from irrelevant medians, look for modeling that will give you insight into the system and the ways in which the various elements interact. They go on to state one needs three types of predictive information in order to strike a happy medium between excessive and convoluted scenarios about what might happen and over-simplistic linear predictions that are over reliant on past knowledge:

  • Lagging: data about what has already happened.
    • Most financial metrics and key performance indicators fall into this bucket
  • Current: data about where you stand right now
    • Your pipeline of opportunities might be in this bucket
  • Leading: data about where things could go and how the system might respond to a range of possibilities

My take on all of this – and I would be very interested in your opinion – is that the three articles together are suggesting that there are some ways in which complexity can be harnessed through simplicity.  Notice that I did not use the term simplification.  All too often we fall into the trap of simplification or linearization, meaning that the model we use to understand the system does not incorporate many of the subtleties that can lead to very different behavior for similar – but not the same – inputs. Examples of simplification are “predict customer behavior on the basis of average response” and “outliers are often more interesting than the average case”. Simplicity is about developing a culture of exploration and providing a capability to evaluate alternatives in an off-line manner before executing on them.  As stated in “Smart Rules: Six Way to Get People to Solve Problems Without You”: "Companies clearly need a better way to manage complexity. In our work with clients and in our research, we believe, we’ve found a different and far more effective approach. It does not involve attempting to impose formal guidelines and processes on frontline employees; rather, it entails creating an environment in which employees can work with one another to develop creative solutions to complex challenges. This approach leads to organizations that ably address numerous fluid and contradictory requirements without structural and procedural complicatedness." Amen to that.

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