A Framework for Achieving Supply Chain Resilience in 2022
on Jan 6, 2022
The past two years have brought nearly uninterrupted volatility, disruption, and uncertainty, which we expect to continue for the foreseeable future. How individuals and companies deal with this ongoing unpredictability will determine their mental, physical, and financial health in 2022 and beyond. Here we provide a framework for companies to thrive in this new age of uncertainty.
Full Article Below -
Usually for our first issue of the year, we make our predictions for the upcoming year. For 2022, that is looking more and more like a fool’s errand.1 Instead, here we look at the ongoing uncertainty and volatility we are living through, potential trajectories for the pandemic, and how to build and maintain supply chain resilience. This is Part One of a three-part article, organized as follows:
Part One (This Article): A Framework for Achieving Supply Chain Resilience in 2022
The Current Period of Ongoing Uncertainty and Volatility
The Economist contends that “the era of predictable unpredictability is not going away.” That certainly seems to be the case as we enter 2022. Supply chain practitioners are painfully aware of how difficult it has always been to predict future demand/consumption and anticipate supply disruptions. Usually, however, we go through discrete periods of volatility followed by longer periods of relatively stability. Hence, while we have tried (to varying extents) to design our supply chain processes to be adaptable and prepared to deal with demand and supply volatility, more investment has been made in making supply chains that run economically in times of stability, sometimes at the cost of resilience.
It seems the past two years have been a period of almost uninterrupted volatility with huge swings in employment and labor supply, demand for different products and services, supply chain disruptions, and continuous uncertainty over what COVID-19 will do next. The current explosion of omicron infections, and uncertainty about what that means for supply and demand and the future of the pandemic, is just the latest episode. Will omicron finally cause the virus to burn through the population with one final wave, bringing enough immunity that it can settle into an endemic state, something more like the flu? Or will yet other variants emerge that perhaps evades vaccines, to cause yet more disruptions.
Indicators of Continuous Elevated Volatility
Stock market volatility, as measured by the CBOE Volatility Index (VIX),2 has been at about twice normal levels during the pandemic (see highlighted portion of Figure 1), peaking at about 5X normal levels in early 2020 when the pandemic first hit. Furthermore, by almost all measures, commodity prices have risen dramatically during the pandemic.
Figure 1 – CBOE Volatility Index (VIX) Has Remained Elevated Throughout 2020-2021
Extreme volatility over the past two years (highlighted below) is also evident in GDP, unemployment, CPI,
and retail sales numbers.
Figure 2 – Extreme Volatility in GDP, Unemployment, CPI, Retail Sales during 2020-2021 Source: NFIB Dec. 2021 Report
The World Uncertainty Index hit all time highs during the pandemic (Figure 3) before easing back somewhat last summer. It has since rebounded, and we expect WUI will continue its resurgence this year.
How each of us views 2022 may be a kind of Rorschach test. The 2022 outlook for supply chains, inflation, labor, GDP, and most other types of global volatility depends heavily on what course the pandemic takes in 2022 and beyond. That is one of the hardest things to predict, even for the experts.
Let’s consider the optimistic and pessimistic scenarios. Even the optimist scenario is pretty bleak for the next couple months. There is consensus that the giant wave of omicron is going to continuing crashing over us, seemingly with the delta wave going on in parallel. Predictions of the exact number of infections vary with IHME predicting a peak around the end of January, with over three billion people getting infected globally in the first three months of 2022. Columbia University is somewhat more optimistic, predicting an early January peak. Both of them think the true number of infections in the U.S. at this point is about 5 to 6 times the reported number of infections.
What is not known is what happens after the omicron surge subsides, whether that is in January, February, March, or later. The optimistic scenario is that we finally enter into more of an endemic state where future variants are milder in their impact and life steadily gets back to normal. A recent study by the Africa Health Research Institute in Durban, South Africa found that “People who have recovered from an infection with the new Omicron coronavirus variant may be able to fend off later infections from the Delta variant. In the short term, Omicron is expected to create a surge of cases that will put a massive strain on economies and health care systems around the world. But in the longer term, the new research suggests that an Omicron-dominated world might experience fewer hospitalizations and deaths than one in which Delta continues to rage.”
But it is far too early to be sure about the optimistic scenario.3 Most prognosticators (e.g., McKinsey) are hedging their bets. In pessimistic scenarios, even more virulent strains emerge, putting a continued strain on supply chains, health care systems, labor markets, and inflation. Paradoxically, there are many manufacturing industries that may not see much of a boost in the optimistic scenarios, especially those that enjoyed a big jump in sales when people started staying at home.
Supply Chain Resilience in the Age of Uncertainty
A Framework for Mitigating Risk in High-Uncertainty Scenarios
What options do supply chain practitioners have to deal with all of this uncertainty? The Risk Mitigation Framework for High-Uncertainty Scenarios offers one approach for dealing with these new realities. ChainLink developed this framework in anticipation of continued sustained volatility and uncertainty. This framework builds on traditional scenario planning for high-uncertainty scenarios.
Scenario planning for low-uncertainty scenarios tends to be more mechanistic. For example, mosquito repellent manufacturers have learned how to use weather forecasts to predict how much standing water will be generated and how long those puddles will remain. Since mosquitoes breed in standing water, the company can make reliable predictions about mosquito populations in the future weeks, based on the weather forecast. Thus, the weather forecast is a key driver of the demand forecast for their mosquito repellant.
In contrast, scenario planning for high-uncertainty scenarios is usually harder to automate, requiring more bespoke research and judgement calls. For example, large semiconductor manufacturers use scenario planning for major product launches, in which a billion dollars or more are at stake and so many things can go wrong. They plan out different plausible scenarios based on things like various factors that could cause development schedules to slip, the range of potential yield ramps their fabs might have, possible moves by competitors, and a range of different demand scenarios. They work through the pros and cons of different potential responses and decide the best course of action for each scenario. They identify key indicators that might provide early warning that a particular scenario may be occurring or is occurring. A dashboard and war room are set up to monitor those indicators, so they can spring into action and take mitigating actions early, reducing the need to figure things out on the fly, ad-lib, in the heat of the battle.
The Risk Mitigation Framework for High-Uncertainty Scenarios builds on these approaches to create a generalized methodology. It starts with identifying potential scenarios by analyzing 1) the underlying driving causes of uncertainty, 2) potential responses of key players to different trajectories of the underlying causes, and 3) potential impacts on demand and the supply chain (supply and logistics constraints). Once a range of plausible scenarios has been identified, early warning indicators and mitigating actions are identified.
Figure 4 - Risk Mitigation Framework for High-Uncertainty Scenarios
Assessing the Pandemic’s Possible Trajectories and Potential Responses
The emergence of the omicron variant has shown just how difficult it is to know the future of the pandemic. However, we now have enough history with the pandemic to map out different possible scenarios. We can create scenarios for how omicron might play out and how governments and individuals might respond. We can develop the indicators to monitor. All of this requires roll-up-your-sleeves self-education and research. For example, there have been discussion and reports on whether omicron is spreading due to superior transmissibility or due to immune evasion.4 There is also debate over whether omicron is supplanting or growing in parallel with Delta, though some signs indicate the latter seems to be the case.
While these may sound like epidemiological arcana, these will affect the outcome of the omicron surge and its impact on different populations and regions (e.g., areas with low vs. high vaccination rates). Therefore, it is critical to understand that level of detail in developing scenarios. Another example is understanding which states and countries are more likely to impose restrictions, what those restrictions might look like, and how fiscal responses might vary. In the U.S., the omicron surge has prompted congress to discuss yet another potential round of stimulus for businesses … and this is at the same time the Fed is raising interest rates to try and cool down inflation!
To understand the responses to the pandemic and the impact on the economy and specific sectors and businesses, we need to look at two interrelated pandemic-induced phenomena: 1) activity restriction/relaxation, and 2) economic constriction/loosening.
Activity Restriction and Relaxation
In the pandemic, people’s activities have been restricted and altered by both government-imposed mandates and individuals’ freewill behavior changes. In mandating restrictions, governments try to balance individual freedom/economic considerations vs. public safety/saving lives. Government-imposed restrictions come in many different forms and degrees of encumbrance, varying widely between governments and over time. A few countries—primarily eastern and/or authoritarian countries and island nations5—have tried to implement a ‘zero COVID’ policy, where detection of any cases of COVID are met with strict quarantines, contact tracing and lockdowns. As the virus mutates, with each increase in transmissibility, a zero COVID policy has become increasingly less tenable.
Even “lock down” means different things in different places and times. In some countries, like China, it means you are breaking the law if you leave your house even to get necessities, and if you want to leave the locked down area, it requires a special permit from the government, which may be denied.6 In other countries, a lock down may not be strictly enforced and is more of a guidance about what ‘essential activities’ are allowed, such as grocery shopping or doctors appointments. The definition of which types of gatherings, facilities and businesses are forced to close differs as well. In the early pandemic, shutdowns were enforced on non-essential manufacturing plants, construction sites, and places of worship. These were eased up while bars, restaurants, and large gatherings (sporting events, concerts, etc.) remained shut down longer. Different states in the U.S. took widely different strategies.
The nature and extent of activity restrictions has been and will be in constant flux throughout the pandemic, based on changing conditions on the ground, such as changing infection levels, surges and pullbacks in hospitalization and deaths, and vaccination levels across populations, as well as changing political fortunes, restriction fatigue among the public, and other forces. All of these decisions, both by individuals and governments, have an enormous impact on individual businesses and the economy as a whole. Below we discuss further how these restrictions impact different businesses and industries.
Economic Constriction and Loosening
The pandemic also creates economic constrictions. With each shutdown or set of activity restriction, specific businesses are affected. They and their employees may lose income. To compensate for this constriction and prevent economic collapse, richer nations have the capacity to enact monetary policies and fiscal stimulus. The U.S. in particular, having learned lessons from the Great Recession, went early and big (really big) handing out stimulus money, lowering interest rates, implementing quantitative easing, lending to banks and businesses and local governments, backstopping money market funds, ramping up repo operations, buying commercial paper … they threw the kitchen sink at the problem to prevent an economic melt-down. This worked … some might say too well.
Figure 5 – Contrast in US vs. Africa GDP Growth/Recovery During Pandemic
(Notes: Vertical scales were resized to align GDP % change scales in both charts to same size and position) Red line on left chart is YoY GDP change.Green line on right chart is Purchasing Managers Index)
Poorer countries have done what they can but have much fewer resources to draw on to provide this kind of stimulus. Figure 5 shows how the U.S. economy took a similar hit as Africa in Q2 of 2020, but came roaring back immediately after, propelled by the massive monetary intervention and fiscal stimulus, whereas Sub-Saharan Africa has stalled and crawled its way back, taking a year to get back to positive growth and still a long way from getting back to pre-pandemic GDP levels.
Looking forward, we also see vastly different levels of stimulus and monetary policy responses, based on many factors such as each countries’ level of inflation, debt levels, etc. A recent Bloomberg survey of forecasts for central bank interest rates for major economies by the end of 2022 ranged from -0.75% for Sweden to +43% for Argentina. This kind of detailed country-by-country information is available for those who choose to go looking.
Figure 6 – Anticipated Central Bank Interest Rate Changes for 2022 Varies by Country
Figure 7 shows an example of an analysis of key factors that have driven looser or tighter monetary policy and the monthly progression throughout the pandemic. This type of analysis can help in understanding current and projected monetary and fiscal policies.
Figure 7 – Example Analysis of Key Drivers of Monetary Policy, Monthly Throughout the Pandemic
Impact of Activity Restriction and Economic Constriction on Individual Industries and Businesses
Different industries and individual businesses have been affected dramatically differently by the pandemic. There were some obvious winners, such as PPE manufacturers and grocery delivery services, and obvious losers, such as restaurants, airlines, and cruise ships. However, there were other winners that, while seemingly obvious in hindsight, were not so obvious at the time the first major lockdowns happened. One of my favorites examples is sales of backyard trampolines, which went through the roof in 2020. This dramatic boost in demand was due to the confluence of activity restriction (people stuck at home with restless kids that needed to be kept occupied) and fiscal policy (stimulus checks for everyone). I wonder if any of the backyard trampoline manufacturers started ramping up production the moment lockdowns were announced … or (more likely) did not see it coming and did not respond until orders started flooding in, perhaps even cutting back production before then.
Another interesting example is Lamb Weston’s ‘Crispy on Delivery’ product, which they introduced in 2018 because home delivery of fast foods had been on the rise. This product helps ensure that French fries are crisp when delivered, as they tend to become soggy in the time it takes to deliver them. We assume that Lamb Weston expected home delivery growth to continue at a similar pace. However, starting around March and April 2020, demand for that product exploded as restaurants en masse pivoted from in person dining to home delivery. We can only speculate as to whether Lamb Weston anticipated this pivot ahead of time and started ramping up procurement of materials, production, labor, and perhaps even planning for new equipment. It is much more likely that they were caught flat-footed and took time to ramp up, missing revenue opportunities in the process.
A broader example is semiconductors. Early on in the pandemic, automakers, computer manufacturers, and electronic device makers pulled back on and/or put on hold existing orders. Within a short period of time, they all experienced a surge in demand. Stuck at home, people were buying more computers, digital home, and entertainment devices. And more people preferred the safety of cars over public transportation. If any of these manufacturers had done good scenario planning, they might have made very different decisions, placing big orders with semiconductor suppliers while capacity was sitting idle. They would have been way ahead of competitors when the demand flood gates opened. This move would have been a bold, calculated risk, where there was a chance that they would end up sitting on a pile of unsold inventory. But doing a proper analysis, they may have decided it was a very good bet to make … which brings us to probability forecasting, structured contracts, real options, and other tools for dealing with uncertainty.
In Part Two of this series, we examine key tools and techniques for dealing with uncertainty, including probability forecasting, structured contracts, real options as risk mitigation strategies, manufacturing flexibility, hedging strategies, mapping and monitoring, and the role of supply chain finance in supply chain resilience.