Contents

1. Introduction: The value of supply chain resilience
2. Key tradeoffs
   1. Time to market and Cost of Goods Sold
   2. Risk management methodology, Lean and a Culture of resilience
   3. 95% confidence intervals, safety stock and strategic stock
      • Strategic Stock
      • Flexibility and Options
      • Tiered approach to Safety Stock
   4. Economies of scale and complexity
      • Complexity avoidance and common-sense vertical integration
      • Global supply chain governance
   5. Business cycles and Structural complexity: The double helix

Introduction

In January 2020, following an outbreak of a virus that came to be known as COVID-19, several suppliers of key components and products had to temporarily shut down their factories in an effort to contain the spread of the virus. Approximately a couple of months later, the automotive and consumer electronics industries started experiencing severe shortages of microchips, grocery stores across the world started running out of toilet paper, and the phrase “Supply Chain Resilience” started trending in google searches. With subsequent events such as a drought in Taiwan and the war in Ukraine further accentuating the supply shocks, the topic of resilience now occupies a disproportionate amount of the mental bandwidth of senior executives around the world.

It is said that we learn much more in bad times than in good times, and indeed, the Supply Chain troubles of the past few years have produced a lot of scholarship on the topic of Supply Chain resilience. Experts have attempted to answer questions on topics including what Supply Chain Resilience entails, what kind of investment is needed to create a resilient supply chain, and whether there is likely to be adequate return on this investment over the long term.

Supply Chain resilience is commonly defined as the capability a company has, to prevent major supply chain disruptions and to mitigate the impact of the ones that do occur. However, there’s a school of thought that argues that resilience is just a catchphrase for the ability to mop things up when “shit happens”, which is what Business continuity planning and contingency planning are all about. This approach presumes that resilience is nothing more than a reactive capability, which kicks into effect when a rare event has already happened. All that’s needed is a steering committee that creates a recovery plan, meets every morning, and sends a company-wide update every week.

And this is indeed how the vast majority of companies operate. When sourcing and supply chain decisions are initially made, the business cases are typically based exclusively on cost – cost of goods sold, manpower costs, logistics costs etc. Questions of risk and resilience are rarely taken into consideration, other than in very superficial ways.

A big reason is that most companies do not have a way to model the risk of extremely rare Black Swan events sufficiently robustly to be included in business cases. At least not in ways that would convince an executive investment approval committee. And when times are generally good, it’s also difficult to summon the motivation to create such models. So, planning executives spend their time focusing on things like improving the accuracy of demand forecasts, reducing safety stock levels and improving service levels during normal times.

And it might indeed be a waste of these executives’ time to try to create models that predict Black Swan events, since according to Nassim Nicholas Taleb, author of “The Black Swan”, Black Swan events are inherently unpredictable, so any attempt to build predictive models for them is nothing more than an exercise in self-delusion that might help pay some people’s salaries.

However, there are events, sometimes called “Grey Swan” events, that are rare and have a high impact, and can, in fact, be predicted. Examples include things like climate change, Brexit and oil spills caused by malfunctioning machines. Moreover, our inability to predict Black Swans doesn’t mean that we shouldn’t do things that help us to prepare for such events and make ourselves more robust to their occurrence regardless of when they happen.

Indeed, as a 2020 study by the Henderson Institute of the Boston Consulting Group (BCG) has uncovered, there exist companies that are inherently and systematically more resilient than their peers against all kinds of crises. Not only do they recover faster and better from an external crisis, they also suffer less initial impact than peers.

In his books, Taleb posits that the impact of Black Swan events on the world, our lives and the course of history completely dwarfs the impact of anything we do during “normal” times. And hence, the value of robustness to these events far outstrips the value of everyday operational efficiency, service levels etc. This is something that the BCG study on resilient companies appears to validate.

BCG found that during “crisis quarters”, resilient companies (identified as around 15% of the companies in the study group) financially outperformed their peers more than 80% of the time during the 25-year study period. An even more interesting finding was that these resilient companies outperformed their industry peers by an average of 5 percentage points over the course of the 25-year study. This was true even in cases (such as Berkshire Hathaway mentioned in the study) where these companies actually underperformed their peers during non-crisis quarters. Their out-performance during crisis quarters was enough to more than compensate for the underperformance during non-crisis quarters.

Clearly, on the evidence of this study, it makes sense for Supply Chain executives to put more focus on building resilience to Black Swan events than on routine cost of goods sold, operational efficiency and working capital targets. The BCG study also identifies key things that resilient companies do to build this resilience. Although there are some new insights in the study, most of these are common-sense things that most Supply Chain leaders would already know.

These include things like identifying and anticipating everything that can possibly go wrong, and building contingency plans and early warning systems for them, building redundancies such as inventory and capacity buffers, having a diverse business portfolio and a diverse supply base, near-shoring, modularity in product and organizational design, flexible operations etc.

So why do 85% of companies fail to do these largely common-sense things to build long-term Supply Chain resilience? The answers lie in the complex set of tradeoffs most companies must negotiate in their decision-making processes, to remain competitive against their peers. These include:

1. Time to market and Cost of Goods Sold

Traditionally, the Supply Chain has been thought of primarily as a source of cost, rather than a source of value. A necessary evil, so to speak. It comes as no surprise then, that cost has been the primary driver of Supply Chain decisions within most companies.

Let’s say a consumer electronics company has just finalized the engineering design of a new gadget and has started the process of creating its Supply Chain capability. One of decisions they would need to take at this stage, is from whom to source the components. The engineers are mainly interested in the question of who can build the components to the desired specifications and quality. The sourcing managers, on the other hand, are given cost targets to negotiate, and would prioritize whichever supplier can supply an acceptable part at the lowest cost.  

Now, both the engineers and the sourcing managers are performing important roles at this stage – customers want a high-quality product that does the job, but they also want to buy it at a lower cost than offered by competitors. What’s frequently missed in this tussle between engineers and sourcing managers, are considerations of risk and resilience. Time is short, the product must be launched yesterday, and managers have no patience with the guy who comes in and says, “…but supplier X source quartz crystals from an earthquake-prone area”.

Often, the suppliers eventually chosen are a subset of the ones who were involved at the prototype stage. And the decision to qualify them at the prototype stage was typically based on trivial reasons, such as pre-existing relationships, or who can build a prototype the fastest.

Later, once the product has been launched, and managers have a moment to catch their breath, they start exploring the risk scenarios and qualifying alternative suppliers. In many cases though, it’s too late to make a substantial impact. At this point, they’re already locked-in to a significant extent, and have limited ability to influence the supply chain.

For example, in the gadget we talked about earlier, it might turn out that the type of quartz crystals needed can only be sourced from an earthquake-prone area. If the sourcing team had examined this question earlier during engineering design, they might have been able to influence the engineering team to make a minor change in the design to reduce the risk. Now, when that earthquake actually happens, the company can do little more than set up a steering committee and formulate a weekly recovery plan.

So, what’s a potential solution to this problem? The solution is fairly obvious, though not easy to implement – Incorporate Supply Chain risk management into the Product Development process. Most good product development processes already use risk assessment methodologies such as FMEA (Failure Modes & Effects Analysis), sometimes called the “Risk Matrix”. This ranks different “failure modes”, i.e., ways in which the product can fail, on 3 parameters – Severity, Probability of Occurrence and Probability of failure of Detection, on a scale of 1 to 10. These ranks are then multiplied together to obtain a “risk score”. The failure modes are then prioritized in order of risk score and addressed in this prioritization sequence.

What’s needed, is to expand the definition of failure modes at the product development stage to include not just the technical failure of the product itself, but also failure to deliver the product to the customer. When we do this, the risk of failure to deliver the product due to quartz sourced from earthquake-prone areas, for example, will come up as a risk, and appropriate design changes can be made to eliminate the risk.

2. Risk management methodology, Lean and a Culture of resilience

While assessing and addressing risks as early as possible using the Risk Matrix is an important and effective first step towards building resilience, it also carries within it, a paradox – while Black Swan events, such as pandemics or wars, have a disproportionately high “impact” score, their inherently low probability of occurrence would typically tend to give them a low risk score, and hence a place very low down in the prioritization sequence.

In many cases, it might not be possible to determine a reasonable probability of occurrence at all, since these are rare events that follow a Poisson distribution rather than a Normal distribution, which essentially means that we don’t know if and when they will happen.

However, as Taleb and BCG, among others, have shown, the failure to build resilience to potential Black Swan events can result in companies financially underperforming their peers not just during the crisis, but over the long term.

The answer is what many of the 15% resilient companies in the BCG study do – they consider robustness to extreme events based on universal, common-sense principles, without reference to specific Black Swan events or their risk scores. Black Swan events, by definition, are unpredictable, but there do exist universal principles that make your supply chains more robust in general. These include building “factors of safety” into everything, including in product design, in inventory policies, in production capacity, in transportation routes, in supplier selection etc. That is, having options, and a bit more of everything than you need.

The catch? Factors of safety cost money and run counter to the “Lean” dogma that has come to dominate industry. Don’t get me wrong, Lean is a good thing, particularly at a time when you need to save every penny to remain cost-competitive vs your competitors. Saving every penny was, in fact, the primary motivation when the Japanese first came up with Lean methodology – they simply couldn’t afford waste.

The problem is not with Lean, which goes beyond merely eliminating waste and includes other valuable principles like standardization of work, continuous improvement and production leveling. The problem is with an excessive focus on waste elimination, turning it into a dogma – an end in itself, at the expense of basic common-sense principles. Yes, do eliminate waste, but modify your definition of waste to exclude factors of safety that will ensure that your company won’t collapse into a heap in case of an extreme event that causes a supply or demand shock.

The question remains – How do you convince an investment approval committee to invest in factors of safety? It can be a hard sell, particularly when it means a lower gross margin or higher cost than competitors. There are certainly ways to make a data-driven, quantitative case for investing in resilience. Real Options Analysis, for example, can provide ways to acquire the capability to rapidly expand capacity when needed or acquire additional transportation routes etc. when needed by investing a relatively small amount of money upfront. This can help address concerns about cost and gross margins. We can also build probabilistic decision models with multiple scenarios that show the expected value of investing in resilience.

However, it might be simply impossible for us to account for all scenarios that might play out and estimate their probabilities, given the inherent unpredictability of Black Swan events. Moreover, our real options analysis and decision models might still not convince senior company leaders when they’re trying to squeeze out every penny of gross margin while remaining cost-competitive against the competition.

In the end, it can boil down to company culture and management philosophy. The mindset that prioritizes robustness and resilience in everything must be driven by Senior Management. What can help convince Management to create a culture of resilience, is published data such as that used by Taleb and BCG in their analyses, that demonstrates beyond a doubt that companies that invest in resilience financially outperform their peers not just in during crises, but over the long term. MIT professor Yossi Sheffi’s books including “The Resilient Enterprise” and “The Power of Resilience” provide further examples of companies that outperformed their peers by investing in resilience, that can help convince those who remain unconvinced.

3. 95% confidence intervals, safety stock and strategic stock

Anyone familiar with statistics would know about 95% confidence intervals. For data that is normally distributed (such as the demand for consumer goods), the 95% confidence interval represents the range within which the data tends to fall 95% of the time. It’s the green area in this bell curve.

So, if this bell curve represents the weekly demand for toilet paper in a grocery store based on historical data and the vertical line in the center is the average demand, the demand will fall within the green area in 95% of weeks.

A common use of these 95% confidence intervals is in determining safety stock levels. When the grocery store orders toilet paper, it will often order enough to cover the average demand but have some extra in the warehouse to cover any unexpected demand. This extra stock is called safety stock. A popular method for determining how much safety stock to hold is called the Kings method, which uses confidence intervals. Most often, 95% confidence intervals are used, yielding a safety stock number that will prevent a stockout 95% of the time, implying a “95% Service Level”.

Why not 98%, or indeed, 100%, you might ask? The reason is the long-tail effect and the law of diminishing returns. Beyond the 95% service level mark, it becomes increasingly more expensive to hold enough safety stock to cover the higher demand levels that occur very rarely. For example, if the average weekly demand for toilet paper is a thousand rolls, the standard deviation of demand is 200 rolls and the lead time for getting more rolls is a steady 9 weeks, you’ll need to keep 1002 rolls extra as safety stock to deliver a 95% service level, but if you want to deliver a 99.9% service level to almost completely eliminate the possibility of a stock-out, you’ll need to almost double that to 1854 rolls.

Given that the average demand is only 1000 rolls, and the peak 99.9% service level demand of 2854 rolls is likely to occur very rarely, perhaps once in several years, it makes sense to have enough to keep you covered 95% of the time, risking a stock-out once in several years. The extra rolls kept in the warehouse waiting for that rare occurrence are likely to spoil or go past their expiry date. When that rare event does happen though, such as when a supply shock triggers a bullwhip effect, causing a run on toilet paper and rampant stock-outs, questions start being asked about inventory policy.

The answer is not to suddenly move to a 99.9% service level policy, keeping large amounts of extra toilet paper in the warehouse that is very unlikely to be sold. The answer is to consider the resilience question separately from the safety stock question. Safety stock is for normal events that a “Normal” distribution can predict, not for unpredictable Black Swan events.

The right question to ask is not “How much safety stock should I hold so that my business keeps running in case of a rare extreme event?”. The right question to ask is “What capabilities and options should I develop to minimize the impact on my business in case of a rare extreme event?”.

Looking at things from this perspective yields several different approaches, including:

• Strategic Stock: Strategic stock is different from safety stock, in that it considers stock not from a variability in demand or variability in lead times perspective, but from a “risk to business in case of a failure or an extreme event” perspective. For example, a machine part that fails very rarely, perhaps once a decade, but whose failure can shut down your business for months if a spare isn’t available, causing millions worth of losses. It’s clear that you need to always keep a strategic stock of this part to protect your business, but a safety stock calculation based on the normal distribution won’t tell you that.
  
  Unlike safety stock, not all items need to have a strategic stock. To determine which items to keep in strategic stock, the risk matrix discussed earlier is a good tool to use – a high risk score would usually indicate an item that must be kept in strategic inventory.
  
  The question of “how much” strategic stock to hold is answered not by looking at demand variability, but by looking at the question of how much time it would take your business to recover from a major supply shock and the amount of stock that would be needed to keep your business running at a minimum sustenance level during that time. For example, if you have a single source supplier for a strategically important item, and the supplier goes bankrupt, you will need to factor in the time it would take you to qualify an alternative supplier and resume supply.

• Flexibility and Options: Apart from maintaining a strategic stock of critical items, another way to mitigate the impact of supply or demand shocks and prevent stockouts, is to develop the capability to quickly acquire additional stock in an extreme event.
  
  This could include developing alternative suppliers in a different geographical location, developing alternative supply routes that can be quickly harnessed, and having extra production capacity that can be quickly deployed or production capacity that is flexibly designed to accommodate multiple products.
  
  For example, a car manufacturer might decide to manufacture Model A in its Asia factory and Model B in its Europe factory, but a part of the capacity in the Europe factory can be quickly converted to manufacture Model A, in case of disruption in supply from Asia.

• Tiered approach to Safety Stock: While it almost never makes sense to target a 99% service level for all items, there might be some items, such as items that are the mainstay of your business, for which it might make sense to have enough stock to cover even rare, extreme events.
  
  For example, if you run a coffee shop, then you cannot afford to run out of coffee for several weeks – it would mean shutting down your business and huge losses. However, you could probably afford to run out of stock of exotic chocolates that you also sell, since people mainly visit you for a cup of coffee.
  
  What could make sense, is a tiered approach – you target an overall service level of 95%, but within that, there are two or more tiers. So, the target service level could be 99% for coffee, but only 85% for exotic chocolates, and perhaps 90% for muffins than many people tend to buy with their coffee. This approach is similar to the ABC classification approach commonly used in inventory management, with the difference that we look at target service levels through the prism of “critical to business survival”, rather than parameters like “high value”, “fast moving” etc.

4. Economies of scale and complexity

In the early days of the industrial revolution, and even until the mid-20^th century, international trade was very limited, and usually very expensive. “Vertical integration” in Supply Chain design is when a single company operates all or most of the supply chain. The first car manufacturers operated 100% vertically integrated craft shops, individually assembling each car with parts custom-built within the workshop.

By the time Henry Ford started mass-producing the Model T in the early 20^th century, more specialization had been introduced, and the automobile Supply Chain had become less vertically integrated. However, the geographic spread of the Supply Chain continued to be very local, with most of the parts of the Model T manufactured within the Ford factory or the local area around the factory.

Mass production brought economies of scale, which meant that you could make products cheaper when you made lots of them at the same time, as Ford did. But as mass production became the norm and international trade became cheaper and faster with improvement in transportation infrastructure, even greater opportunities for economies of scale emerged through specialization. So, a company could specialize in manufacturing just car headlights instead of the whole car, and they could make headlights not just for Ford, but for multiple car manufacturers. That gave them greater expertise in headlights, leading to better headlights, but also reduced costs further, since they could divide their fixed costs between a lot more headlights.

Supply Chains today have come a long way from where they were when Ford started manufacturing the Model T. Most supply chains are now almost completely global and decentralized, with very high levels of specialization. There could, for example, be an entire region full of factories that only manufacture camera sensors, which they supply to different electronics manufacturers around the world.

To an extent, this provides some resilience to Black Swan events – if production is distributed around the world instead of being concentrated in a single location, it can mean that you could keep production running in a different location if one location is impacted. A more modular supply chain design is, in fact, one of the ways suggested by BCG in their study to mitigate risk and build resilience, and considering that a modular design greatly mitigates the risk of disruption due to “putting all your eggs in one basket”, they aren’t wrong.

However, once we’ve mitigated the basic risk of overdependence on a single factory, a single supplier, a single location etc., further complexity in the supply chain adds risk and reduces resilience, instead of increasing it. The greater the number of nodes and middlemen in the supply chain, the greater the number of things that can go wrong.

Also, a highly complex supply chain increases the number of unknowns that you only become aware of in hindsight, because of the difficulty in understanding the entirety of your supply chain. For example, a company might not even know that they use quartz crystals sourced from an earthquake-prone zone, because the quartz is sourced by a 3^rd tier supplier, and the sheer complexity of the supply chain makes it nearly impossible to do the due diligence to fully understand the supply chain beyond the 3^rd tier. The company only finds out when an earthquake happens, and a 2^nd tier supplier informs them about supply disruptions due to the 3^rd tier supplier’s inability to supply a part that contains the quartz crystals.

There are at least a couple of approaches that would mitigate the risk arising from complexity:

• Complexity avoidance and common-sense vertical integration: When designing the supply chain for a product, one way to build resilience is to take decisions that avoid complexity and choose the simpler of available options. For example, the electronics company with the quartz crystals risk we discussed above could have chosen a more vertically integrated tier 2 supplier that has greater control over its supply chain, giving the company greater visibility to, and influence over the risk. It would make sense to make this choice even if the more vertically integrated supplier is a little more expensive, with the knowledge of the trade-off between loss of resilience and long-term financial outcomes.
  
  The company could also choose to be more vertically integrated itself, bringing more of the manufacturing process in-house, giving it direct influence over where the quartz crystals are sourced from. It goes without saying, of course, that this must be balanced against the increase in risk due to concentration of production in a single location if the company becomes too vertically integrated. In most cases, the most resilient supply chain architecture will be found midway between completely integrated and completely modular.
  
  A purely mathematical decision model will typically reveal a complex, globally distributed supply chain to be the most cost-effective solution for the supply chain design of a product. But leaders who are aware of the long-term ROI of resilience demonstrated by data, will look beyond simplistic calculations and ensure that the decision criteria and quantitative models include a resilient supply chain architecture as a prerequisite.

• Global Supply Chain governance: Implementing a system of governance across your supply chain that includes considerations of resilience can also significantly mitigates risk. Most companies do have some sort of governance process in place to ensure that their suppliers remain compliant with regulatory requirements pertaining to modern slavery, bribery, GDPR etc., but questions of supply chain risk rarely feature in the supply contracts or the governance process.
  
  For example, the electronics company discussed earlier could include resilience criteria, such as having alternatives for items sourced from ecologically sensitive areas, in its supply contracts with tier 2 suppliers, mandating risk to be kept below a certain level. As part of its governance process, it could include a checklist to ensure continued compliance with the resilience criteria in its annual audit of tier 2 suppliers.

5. Business cycles and Structural complexity: The double helix

We have seen how companies can mitigate risk arising from supply chain complexity through greater vertical integration in the supply chain. However, very often, there are other drivers and market forces that determine the supply chain architecture of a company, beyond just considerations of resilience.

These factors are succinctly summarized by Prof. Charles Fine of MIT in his book “Clockspeed”, using something he calls the “Double Helix” of business cycles, which he visualizes as below.

The primary thing that drives Supply Chain architecture is Product Architecture. If the product architecture is modular, i.e., if the product has plug and play components that function independently, can be manufactured separately, and assembled into the final product later, that allows for a more modular supply chain architecture. Different parts can be manufactured in different parts of the world and shipped to a factory where they are assembled into the final product. However, if product architecture is integral, i.e., the parts of the product are tightly integrated together and cannot easily be separated out, it forces the manufacturer to have a more vertically integrated supply chain architecture.

Apple’s early Macintosh computers, for example, had a highly integrated product architecture, with components like the monitor, CPU and keyboard integrated into a single body. PCs, on the other hand, came in with a more modular architecture, allowing monitors, keyboards etc. to be manufactured separately in different locations.

Most industries start out with a highly integral product and supply chain architecture. The first automobiles, for example, were completely hand-crafted by individual craftsmen in workshops. Even the Ford Model T had a much more integral product architecture than most cars today. As companies grow in size though, they start experiencing pressure to become more modular.

For example, an auto company that manufactures all components of the car in-house might find they are unable to focus on their core competence, for example, engine technology or aerodynamics. As a result, they have less expertise in individual components, such as brakes or headlights, than others who specialize in the manufacture of just these components. They also have smaller economies of scale than manufacturers who mass-produce components for multiple auto companies. As a result, they have poorer quality and higher costs.

As they become more modular and outsource the manufacture of all or most components to external suppliers, these suppliers start to gain an unhealthy amount of power over them, particularly when they are experts in the manufacture of these components. For example, the power that Intel or other microchip manufacturers have over computer and smartphone manufacturers. Modularity also brings less control over proprietary technology, and reduced ability to distinguish yourself from competitors. These factors then impel the reverse cycle, prompting companies to move to a more integral product and supply chain design. This is the circle of life that Prof. Charles Fine describes in his book.

So how do considerations of supply chain resilience factor into this cycle? By themselves, they don’t.  When a Black Swan event strikes, there will be some companies that are lucky to be at a stage of this cycle where they have some resilience to such events, and there will be others that have less luck. And then of course there will be the 15% of companies in the BCG study that have systematically and consciously built resilience independently of this cycle, that will do better than others. However, parallel to the double helix cycle that Prof. Fine talks about, there is another dynamic that tends to operate across all companies, which is directly related to resilience to Black Swan events and goes something like below. We could call it the resilience cycle.

Every time an extreme event, such as a Tsunami, a global pandemic or a war occurs, supply chain disruptions cause executives to sit up and take notice of the vulnerabilities in their supply chain. Changes are instituted to mitigate risks, such as simplification of the supply chain, near-shoring and greater vertical integration. These changes though, usually come at a cost. Factors of Safety cost money and add to the cost of the product. Companies that perform more of the Supply Chain functions themselves instead of outsourcing them also become large and unwieldy and lose their internal agility.

As a result, they gradually find themselves losing ground against competitors who are nimbler and have lower costs. This provides an impetus to disintegrate again to lower costs and keep up with the competition. Until, that is, when another extreme event happens, and the cycle repeats.

To conquer these cycles, the first step Supply Chain leaders need to take, is become aware of them, as they pertain to their own organizations. Awareness of where you are in the cycle, and understanding of the underlying dynamics can, by themselves, provide insight into how things are likely to play out in the future, and prompt needed corrective actions. Even when building a resilient supply chain architecture comes with somewhat higher supply chain costs than competitors, leaders with vision will persist with the resilient architecture, with the knowledge that the long-term return on investment exceeds that of competitors with less resilient architecture.

Another cycle that operates alongside these business cycles and influences the fate of companies, is that of economic boom and busts. If we look back at history over the past century or more, we find periods of economic boom followed by periods of recession. In times of economic boom, many companies tend to buy up additional manufacturing capacity at a very high cost to keep up with the demand. However, when recession arrives, they are saddled with lots of excess capacity which often drives them out of business or compels them to cheaply dispose of the extra capacity.

Some industries are more vulnerable to economic cycles than others, and commodity industries such as the Steel industry are more vulnerable than most. A popular anecdote about the Steel behemoth Arcelor Mittal says that they became the largest Steel company in the world by having a better understanding of these cycles than their competitors. In times of recession, they bought up large amounts of capacity from loss-making competitors at dirt-cheap prices, which they later capitalized on during boom times to capture the market. Supply Chain leaders who understand the vertical integration and disintegration cycles can similarly use this understanding to make decisions that bring long-term value to their company.