Failures in operating and business models during the COVID-19 crisis
Operating models and business models may have many components (e.g. a business model such as one-time sale may be enabled by job-shop production based on the reconfiguration of 3D-printing line).
For high performance, these components must work together in a cohesive way. A crisis such as COVID-19 shocks all the components of operating and business models, and such shocks typically create extreme conditions and reveal whether underlying business and operating models are either robust or whether they fail under such stress.
The four modes of failure
Even if there is still a lot of uncertainty and lack of reliable information on how the current crisis will evolve, we categorized observed failures under four modes of unanticipated outcomes:
- Demand and supply imbalance
- Inflexible human resources and organizational processes
- Constrained capital and venture capital
- Rigid integrative systems
Underlying driving factors are described below in isolation for ease of explication. We note that systemic failures have typically cascaded across these modes rapidly. Our assessment explores whether observed failures can be ascribed to shortcomings either in the business model, or with the operating model.
1. Demand and supply imbalance
It is not useful to think about demand and supply in isolation. That is, a business, even if it experienced a demand surge owing to COVID-19, might fail if it cannot scale and satisfy demand. We characterize the demand and supply imbalance in terms of three separate, but related, drivers: significant supply chain delays; stockouts and hoarding; and shifts in consumption.
Significant supply chain delays
A number of our industrial partners have reported COVID-19-driven supply delays ranging from 1.5X to 5X normal lead times to get the supplies. In general, global supply chains, especially those involving maritime logistics, displayed the largest delays. Much of this delay is because the volume of air shipments has been reduced and even when goods are available (e.g., from factories in mainland China), ports have been clogged and bulk and container shipping routes have been delayed as crew and support systems have been exposed to COVID-19 and cannot get the personnel replacements and provisions needed for rapid turnarounds.
Stockouts and hoarding
Independent of shipping delays, the demand for select items (like toilet paper) has been subject to hoarding and panic. Hoarding creates shortages and swings in demand and demand-supply mismatch at each stage of the supply chain because of the bullwhip effect. Some retailers have resorted to rationing, but with long lead times at each stage of the supply chain, such rationing has not always worked as evidenced by reported shortages. In addition, solutions, such as rationing, may not fit all business models: some of the higher-end retailers in the United States, for instance, have discontinued price discounting when faced with shortages, while lower-end retailers have accessed local suppliers and cooperatives to manage their demand and supply mismatch.
Shifts in consumption
A third leading factor driving the imbalance is a shift in consumption. For instance, social distancing has shut down the demand for restaurants (except for takeout orders) while creating additional demand for items such as baking goods for home use, and for vegetable seeds for home gardens, which have also resulted in stockouts and long waits.
In our interviews, the origins of both hoarding and shifts in demands were attributed to consumer behaviour (e.g., panic) and related actions. These consumer actions and resulting shortages were compounded by long delays. Long delays are largely caused by decisions associated with operating models, such single as sourcing, during configuration of supply chains for items such as personal protective equipment (PPE) and masks.
These delays are likely to either persist for months or rear their head periodically. Such phenomena are exacerbated by both the rigidity in the operating models (e.g., inability to find second sources rapidly) and the inability to adjust the business model (e.g., systematic and rapid changes in prices in face of a shortage).
2. Inflexible human resources and organizational processes
A second major source of failures during COVID-19 has been associated with HR and organizational processes. We characterize these types of failures in terms of three separate but related drivers: lack of collaboration and leadership; widespread infections leading to sickness and absence; and overwork and furloughs.
Lack of collaboration and leadership
A key reason for lack of collaboration has been interorganizational processes that involve coordination across boundaries. Examples included supplies for PPEs being directed towards a single country instead of sharing proportionally across multiple affected countries. Bidding for items such as test kits has created infighting and finger pointing between the federal government and states in the US. Often there is an element of incentive incompatibility in the underlying business models, whereby individual actors deem interorganizational collaboration as a zero-sum game.
Such problems highlight the clear need for higher level coordination (federal and global). Lack of leadership is also evident in continued reliance on existing information systems, such as data for ordering processes and oversight of workforce health, while it is apparent that systems have been hardwired for maintaining the status quo rather than for the needed responses.
Widespread infections leading to sickness and absence
A second source of failure is the possibility of infections in each link of the manufacturing and supply chain infrastructure simultaneously. We have seen large-scale meat production capacity – e.g., at firms like Tyson foods – and distribution being compromised simultaneously because production processes could not ensure distancing, and frontline workers in grocery store have faced infection possibilities because of frequent interactions with fellow workers and customers.
Overwork and furloughs
Sickness and the resulting loss of capacity usually lead to overwork. This has been especially acute in sectors such as healthcare but is also seen in some sectors of the logistics system, especially those parts that are providing critical supplies. Both the healthcare and the retail sectors have also been forced to furlough some of their workforce (such as the personnel who do elective surgeries).
In our interviews, failures in HR practices (e.g., furloughs) were typically associated with business models that promoted the hiring of specialized labour. Similarly, a lack of collaboration was often associated with the set-up of the business model incentives rather than the way the operating model was executed. Sickness and loss of capacity could be countered with buffers, but only if the operating model had built-in slack and flexibility. In the reported failures we have seen, the operating system lacked such buffers.
3. Constrained capital and venture capital
We have identified three drivers of capital-related failures: lack of liquidity; inflexible healthcare technologies; and leaning of shop-floor/supply-chain technologies. It is worth noting that manufacturing infrastructure has only accounted for approximately a third of the entire capital stock (even in the US, the remaining investment has gone to sectors such as services).
This underinvestment is because manufacturing and supply chains are not seen as key drivers of innovation. The flow of venture capital into the sector has also been relatively weak as compared to other digital infrastructures.
Lack of liquidity
COVID-19 shortages and shifts in demands have reduced revenues. This has affected low-margin business models, such as the retail sector, immediately, especially for small and medium-size enterprises. This lack of liquidity has in turn created pressure to reduce fixed costs (see furloughs, discussed above) and to reduce variable costs by reducing orders, which have created liquidity pressure on upstream manufacturing firms.
Inflexible healthcare technologies
Independent of the liquidity crisis, a second source of failure is the lack of investment in flexible service technologies, particularly in the healthcare sector. Business models in this sector have been myopic, resulting in a lack of buffers for PPE. Such business models, both at individual firms and at national levels, have underinvested in R&D and it will take a very long time for their innovation and production systems to invent, produce and distribute critical supplies such as suitable vaccines, when demand goes into billions, for COVID-19 prevention and cure.
Leaning of shop-floor/supply-chain technologies
A third dimension of capital-driven failure has been operating models that shape investments in production shop-floor and supply-chain technologies. Implementation of these technologies, such as factory robots at automotive and pharmaceutical firms, has been based on lean production principles that are designed to optimize “just in time” inventories and to reduce variable costs. In doing so, these operating models may have over-emphasized “just in time” while underinvesting in “just in case” and the flexible production capacity that is so clearly needed during the COVID-19 crisis and which would be of tremendous benefit in future disruptions that are nearly certain to take place because of megatrends such as climate change.
4. Rigid integrative systems
In addition to components such as HR and capital, large systems draw on integrative systems to ensure these functions work cohesively as a system. Drivers for a final set of failures, which we label as integrative failures, may be grouped into: knowledge gaps, inflexible platforms and hierarchies; restrictive legal regimens; and unreliable information systems.
Knowledge gaps, inflexible platforms and hierarchies
We have witnessed systemic failures in platforms that have the governing rights and an implicit responsibility to protect the interests of their supply and consumption networks. Some platforms (such as Alibaba) have helped their suppliers that faced liquidity issues. Others, including firms such as Amazon, have elected not to do so.
Organizations with flat structures, such as some big box retailers in the UK, have also been slow to pick up trends in demands and have faced stock-outs. Many multi-layered entities have faced distortions in demand-and-supply signals that are amplified by knowledge uncertainties, wherein manufacturers and suppliers either do not have access to real-time data or lack the knowledge to ask the right questions.
Tighter hierarchies, such as Asian grocery chains in the UK, have leveraged formal and informal networks at multiple levels to detect trends early and have been able to address knowledge gaps at multiple levels (retail, distributor and shipping) through rapid cycles of informal feedback on the demand, pricing and lead times. This speaks to need for resilience multiple levels in business and operating models.
Restrictive legal regimens
Legal regimens affect the manner in which operating and business models get set up. The COVID-19 crisis has created needs that have changed some regulations. For instance, trucking laws in the US have been relaxed to remove restrictions on contiguous hours worked. Although this increases capacity in the near term, the relaxation has also resulted in increased workload and mounting safety concerns, with the possibility of a loss of capacity in the mid and long term.
Similarly, there are restrictions in several countries on specific trades such as construction work and seasonal fertilization of gardens because they are deemed as “non-essential work” based on distancing requirements. This creates production failures that will last for months or for an entire year’s work cycle. It has also fostered a sense of inequity and new legal regimens may have to evolve to assess which work is deemed essential in a fair and consistent manner.
Unreliable information systems
In many instances, individual firms have rapidly flipped their operating models and have implemented Buy Online Pickup In Store (BOPIS) practices. In our interviews, we have been told about shifts in the demand from conventional retail to BOPIS by a factor of five or more.
The lack of reliable information and continued uncertainties are the key issues here. Many of these firms had to take on the herculean task of dismantling their existing operating models, such as bypassing ordering heuristics that are hardwired into their information systems. For example, instead of making decisions based on orders seen at the store level, these firms had to switch decisions based on online orders. Whether this shift will lead to permanent changes in consumer preferences and in turn require a change in underlying business models is an open question.