The Hazards of Forecasting and the Incontrovertibility of Resilience
The age of unpredictability requires new notions of strategy.
Two months away to almost three years since the outbreak of the first case of the Wuhan coronavirus – it may be prudent to take stock of some of the major changes to organisational mindset we’ve seen over this period and the unequivocal importance of the virtue of resilience.
So far, the advent of the 2020s has seen upheaval unlike most other decades; and while forecasting future market movements, competitor responses and consumer behaviour is central to most businesses today – particularly relevant since the advent of the COVID-19 pandemic – attempting to develop precise forecasts often turns out to be ‘a fool’s errand’.
In this regard, Michael Mankins, partner at consulting giants Bain & Company, opines for the Harvard Business Review:
“Meteorologist Edward Lorenz proved this nearly 60 years ago when he popularised “the butterfly effect.” He suggested: “A butterfly flaps its wings in the Amazonian jungle and subsequently a storm ravages half of Europe.” While this statement is often interpreted as meaning “small things can have big impacts,” Lorenz’s insight was actually far more profound:
In complex systems, small changes in one variable may have no effect or massive ones, and it is virtually impossible to predict which will turn out to be the case.”
‘In uncertain times, the best strategy Is adaptability’
Prior to Lorenz’s work on the butterfly effect, forecasters naturally assumed that an approximation of the specific initial conditions of a system would lead to an approximate prediction of future outcomes. This was, however, proved almost entirely redundant with Lorenz concluding that only a perfect delineation of initial conditions could provide accurate predictions.
This becomes especially relevant in a highly globalised interconnected system fraught with unknowns such as telecommunication and technological advancements, consumer preference shifts, instability in geopolitical systems and several others by and large even beyond the comprehension of a forecaster building a model.
While this doesn’t necessarily discount entirely the process of forecasting or scenario analysis, what it does is to genuinely underline the importance that executives must place on being nimble – i.e. designing an organisational structure characterised by inbuilt flexibility, dynamic planning and a willingness to adapt.
A willingness to adapt
“The Covid-19 pandemic serves as testimony to the importance of adaptability. In early 2020, almost no company’s strategic plan forecast the impact that the global pandemic would have on business.”
Yet, the companies that really blossomed through the pandemic – think Zoom, Disney, Amazon etc. — are the ones who could quickly adapt their business models to deal with dynamic demand changes owing to restrictions placed on consumers and workers and the growth of work-from-home culture. While some firms extended inventory and capacity in response to sudden demand surges, others changed delivery models to serve customers in new and innovative ways.
Enterprises which could not – or maybe did not – adapt as well, such as hotel operators or commercial airlines, saw their profits and revenues plummet, many even turning insolvent. If nothing else, the pandemic has taught us that the ability to pivot quickly in response to exogenous shocks is perhaps the most primary.
Inbuilt flexibility
In periods of high volatility, flexibility proves to have immense value – consider aluminium production as an example.
Future returns on capital-heavy projects, such as investing in a new smelter oven, depend heavily on the highly volatile prices attached to aluminium and electricity (i.e. energy prices). Price uncertainties, however, entail that there may indeed be times when cash inflows from aluminium sales fall short of the costs of production or are lower than the revenues that could be generated from the sale of contracted or co-generated power.
In such a scenario, altering strategy to temporarily stall production during periods of exorbitantly high energy prices and sell available power back to the grid has proved to be rather beneficial to the producers who have opted for it. “The few aluminium producers that have stuck with rigid, production-only plans have experienced dramatically lower returns than those opting for more flexible strategies,” reports the HBR.
Consider another example: of sourcing strategy.
The list of exogenous factors affecting ailing supply chains today – Russia’s invasion of Ukraine, or China’s zero-Covid policy, for instance – have almost completely cut off the flow of raw materials such as nickel, titanium, palladium and neon; or in the latter case, halted global manufacturing processes affecting everything from smartphones to automobiles.
In such a scenario, companies with flexible supply networks, capable of sourcing from other regions have found it much easier to cope with these disruptions, while those with rigid supply chains continue to suffer in tumult as we speak.
Dynamic planning
“In an unpredictable world, it might be tempting to throw up your hands and give up on planning altogether. But great performance is rarely the result of happenstance. It requires a direction, even if it isn’t possible to define the exact path.”
In a dynamic world of extreme volatility, it is especially important for organisations to change the approach to strategic planning. An evolution from a static, plan-then-do model to a dynamic and continuous approach to strategic decision-making needs to be adopted instead. US tech giant Dell Technologies was one of the first to adopt this new model in 2013 after Michael Dell took the company private.
“The company shifted from a traditional planning model — where managers developed a fixed strategic plan each year — to an approach focused on continuously identifying and making critical decisions. This new model — combined with new techniques for making strategic decisions under uncertainty — has enabled Dell Technologies to increase its operating profits by more than four-fold since 2013.”
We have almost certainly reached a point where a deterministic and rigid forecasting approach needs to be foregone – and instead, replaced with a more dynamic, decision-focused approach. Flexibility and adaptability need to come to the fore, and stay there.
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