Why operational context matters: Realizing the full potential of supply chain resilience surveys

Editor’s Note: The following article is the unedited verion of “Realizing the full potential of supply chain resilience surveys,” a feature from the November 2022 issue of Supply Chain Management Review. The original version contains more of the authors’ research.

Abstract
At a time when massive shocks such as the COVID pandemic and semiconductor chip shortages continue to disrupt supply chains around the world, multiple market research and consulting surveys have been conducted to identify supply chain resilience strategies. However, it is difficult for managers to develop actionable strategies based on findings from such surveys, because of a lack of context of the reported decisions and because the results are aggregated over multiple levels. In this article, we analyze how such surveys can be adjusted to reveal more differentiated findings. Two recommendations have been identified: Using the supply chain as the unit of observation and adding questions to understand the operational context of the supply chain. We then illustrate the recommended methodology with three company examples.

Key words: supply chain resilience, consulting surveys, supply chain archetypes, operational characteristics

Business resilience in the context of supply chain management has become a top priority for most companies in response to the massive disruptions caused by the COVID pandemic and subsequent developments such as the chip shortage and bottlenecks in global logistics systems. Many supply chain executives are looking to develop a long-term strategy to increase their supply chain resilience since new uncertainties and major disruptions, such as the Russian invasion of the Ukraine, continue to arise.

This has led many market research and consulting companies to investigate the impact of such disruptions and to explore potential strategies to cope with them. Over the last two years multiple supply chain management surveys have been launched to discover supply chain resilience strategies. However, it has been difficult to develop actionable strategies based on insights from such surveys. This suggests that there is a need to deepen our understanding of how to interpret survey results as well as how to re-design them in order to explore supply chain resiliency.

Surveys on supply chain resilience typically use the totality of all companies in their sample as their unit of analysis, i.e., a typical result would be “x% of all companies regionalize their supply chain”. In some survey reports industry specific differences are analyzed. This can lead to interesting insights for managers and scholars. However, companies operate within idiosyncratic environments and thus there is a need for more differentiated guidance. Executives need to define strategy decisions to achieve resilience at the individual supply chain level, taking the specific challenges and constraints of their company environments into account. Thus, there is a gap between the level of analysis that is needed for decision making to support resiliency and the level of analysis that is typically provided. We call it the “unit of analysis gap”.

In this article, we want to show how this unit of analysis gap can be bridged with two steps, so that executives can benefit most effectively from survey-based insights. The first step does not require any change to the current format of the surveys since it is based on breaking down existing survey insights to the industry level. The second step requires asking additional questions in order to uncover insights at the supply chain level.

We were given the opportunity to collaborate with Gartner, one of the leading supply chain research and consulting companies, on the development of their 2020 global supply chain agility1 and resilience survey. Their report, “Future of Supply Chain: Crisis Shapes the Profession”2, is based on the results of that survey. We used the published report and additional access to some of the survey data3 to illustrate how survey results can be enhanced through the two steps noted above, leading to more differentiated and relevant insights.

We have grouped our findings into three parts. The first part documents the advantages of this type of survey and why researchers and managers should see them as an important source of valuable information that is relevant to mitigating the risks present in the current supply chain environment. In this section, we outline the conclusions drawn from reviewing the survey data and comparing the results to other survey-based reports.

The second part shows how survey data can be broken down and further analyzed at the industry level. We used additional data, based on the survey responses, that we received from Gartner, to show how further analysis can lead to additional industry-specific insights.

In the third section, we explain our recommendations for how to conduct future supply chain resilience surveys in order to generate supply-chain specific insights. We provide three company examples, whom we interviewed, that illustrate our methodology and our conclusions. The Henkel supply chain example illustrates the value of having a supply chain as the unit of analysis. The two Nike supply chains show that two different supply chain archetypes can exist within one company. Finally, the Infineon supply chain example shows that the operational context of the supply chain in certain industries can limit the option space to such an extent that only one feasible supply chain configuration remains.

Advantages of supply chain surveys
In this section, we discuss how surveys on resilience can support both supply chain practice and research. In particular, we discuss what can be learned from them with regards to resiliency. Consulting surveys and reports are a valuable means for discovering the perspective of practitioners concerning timely topics. Their value is based on the ability of consulting companies to reach a wide pool of respondents and their resources to conduct such surveys in a timely manner. This allows them to quickly generate large data sets that make drawing general conclusions derived from current practice feasible.

We have compared the results of 12 consulting surveys on supply chain resilience from May 2020 to July 2021 (see Appendix A for a summary of survey details) and found that there are some recurring messages in the survey reports. In Figure 2 we have summarized ten insights related to supply chain resilience that we found in multiple independent surveys. For example, all reports mention that a digital transformation through investments in IT infrastructure is a key enabler for becoming resilient. A Deloitte survey4 found that 78% of respondents view enhancing IT infrastructure to be a top operating model priority. In another survey5, 91% of the 715 managers responding strongly agree or agreed to “Effective investments in digital technologies and analytics will help companies recover faster from the impacts of COVID-19”. Moreover, a survey from Allianz6 showed that highly digitized companies took significantly more actions to mitigate disruptions compared to less digitized ones.

We note that 11 out of 12 survey reports conclude that changes to the current supply chain setup are needed for most companies. According to Gartner2, 40% of executives believe that their current supply chain is not able to cope effectively with short- to medium term challenges. Other surveys from our sample found that 65% of respondents7 said that they actively invest in regionalizing and localizing their manufacturing base or that 82% agree with the statement “Our supply chain footprint has shifted notably because of COVID-19”.

Thus, these consulting reports document similar developments when it comes to beliefs and actions of global supply chain managers8. The findings are interesting and relevant as they give an overview and cross-check of how managers think. Moreover, due to the large sample size, the survey results support making general statements about current management thinking. The insights also can be used as a starting point for scholars to examine resiliency in more detail and to develop analytical resilience models.

Generate industry insights through further analysis
In this section, we show how breaking down results to the industry level reveals interesting insights. Being resilient indeed does mean something different for each supply chain, as each company needs to balance different types of risks while minimizing overall costs. The “right” trade-off depends on individual circumstances such as regulatory requirements, geographic supply constraints, partner ecosystems, or risk appetite.

However, this is the first of two steps to bridge the gap between the general conclusions which are oftentimes found in consulting reports and supply chain-specific insights that managers require. Through this first step some questions can be answered. For example, are most companies in my industry implementing the same set of strategies? Do other executives in my industry share my beliefs regarding resilience? Why are some companies not investing in resilience?

Generating industry level insights can be done without any changes to the current format of most surveys, as usually the respondents are asked to specify the industry their company is competing in. We use the Gartner report as an example of how to conduct further analysis that can lead to additional industry-specific insights.

Example: Gartner survey
The annual Gartner survey, which is the survey we analyzed in this paper, is one of the leading and most relevant supply chain surveys, because of its global reach, large sample size, and the quality of its respondents. We observed that 1049 from a total of 1346 respondents work in operations and are a board member, director, vice president, or manager. Moreover, the respondents came from 18 different industries, which represents a good cross-section of all companies, while excluding industries such as Services, Software, and Finance. Thus, the survey is well suited for examining supply chain related topics at a general level.

To identify additional insights, we conducted further analysis through three cross-tabulations of the reported survey questions responses that Gartner provided for us, and which were not included in the survey findings report. All three cross-tabulations can be found in Appendix B9.

Resilience strategy deployment by industry
The first cross-tabulation analyzes industry-specific differences in investment decisions that have already been implemented and are not just intended. The table shows the total number of respondents per industry and how many of them indicated that they were currently investing in one of the sixteen agility and resilience strategies identified in the survey. Respondents that only intend to invest in the next two years were excluded, as intension does not necessarily translate into real action, which is what we want to focus on.

The results of this cross tabulation show that there are significant differences in supply chain resilience strategies that were implemented across industries. For example, only 30% of managers from automotive companies reported that they shifted manufacturing from one region to another, while 61% of high-tech executives reported that they have done so. Moreover, the results show that chemical companies and automotive companies have implemented significantly less in resilience strategies than the other industries.

Chemical companies reported that they have diversified their supply base (-20%points compared to average), increased inventory (-22%pts.), or outsourced (-17%pts.) far less than all other industries to become more resilient. These results can be explained by the particular setup of many chemical supply chains being asset-intensive and continuously flowing. Automotive companies seem to shift manufacturing capacities (-18%pts.), deepen collaborations with key suppliers (-16%pts.), and use demand sensing technology (-18%pts.) far less than other companies.

Their asset intensive production explains the lacking flexibility of production capacities. Having more purely transactional relationships with suppliers might explain why it is especially challenging for the automotive industry to secure enough of the supply-constrained semiconductor chips. We only mentioned some examples as this is not the focus of this article, however, more interesting insights can be found in the data.

Supply chain beliefs by industry
The second cross-tabulation looks at how managers’ beliefs or perspectives concerning factors or trends that can impact supply chain agility and resilience strategies vary by industry. The table is based on fourteen different belief statements and asks managers to agree, disagree or be neutral with respect to each statement.
Over 90% of the High-tech, Logistics & Distribution, CPG, Retail, and Industrial companies have indicated that they will invest in resilience and agility. These are industries where management generally understands and accepts the investments required to be more resilient and agile (see 2.5).

For CPG companies, one reason for investing more might be that they lag behind other industries in terms of agility, as their supply chains have been designed primarily for cost efficiency rather than resiliency or agility in the past (see 2.3). The industries that are doing less to make their supply chains resilient include Aerospace & Defense because national interests and regulation hamper supply chain restructuring (see 2.8, 2.7) or Food and Beverage because customers want local sourcing (see 2.9). However, further automation is needed to facilitate onshore manufacturing to make supply more agile and resilient (see 2.14). Moreover, investments in agility and resilience are simply too costly for Automotive companies and their leadership did not see the need for action at the time of the survey (see 2.4, 2.5).

For Medical Equipment & Devices companies the industry’s current low-cost outsourcing strategy is still largely sustainable and does not require them to act quickly (see 2.9, 2.10, 2.11, 2.13). Chemical companies already are very lean, based on continuous flow operations, and do not see the need to change their supply chain setup (see 2.6).

Overall, it can be observed that there are significant differences in answer patterns depending on the industry. For example, affirmative answers regarding a previous focus on cost efficiency (see 2.3) vary by up to 32%-points, depending on the industry. The same is true for customer preferences for local sourcing (up to 43%pt. difference; see 2.9) or whether the leadership accepts the need for investments in resilience (up to 36%pts.; see 2.5). Thus, it can be concluded that even though basically every respondent (90%) indicated that they will invest in agility and resilience, the underlying motivations and reasons for doing so vary significantly.

Beliefs versus decisions
The third cross-tabulation analyzes how the companies’ supply chain investment decisions are linked to their beliefs or perspectives on supply chain factors and trends. The table combines the answers from the investment decisions and the beliefs to show the split of agreeing and disagreeing to the fourteen statements by investment decision instead of by industry. Our hypothesis was that the actual decisions (i.e., the strategies implemented) tells us something about the underlying beliefs. For example, we expected companies that increased their safety stock levels or reduced their capacity utilization would agree to a greater extent that “our supply chains in the past have been designed primarily for cost efficiency rather than resiliency or agility”.

Surprisingly, the results (see cross-tabulation 3 in Appendix B) do not show that the beliefs are linked to the ultimate investment decisions/actions. For all beliefs, the percentage of respondents agreeing and disagreeing is basically constant across all resilience strategies (standard deviation of 1.5% across all responses). Thus, companies implement different supply chain resilience strategies, but on average have similar beliefs regarding the resilience vs. cost-efficiency trade-off, regionalization, and customer preferences.

This observation indicates that the implementation of a particular resilience investment can have multiple different reasons. For example, regionalization of the supply chain might implicate for a supply chain that previously operated a very lean global setup, the possibility to have more redundancies and diversified location risk. However, another company might want to regionalize its supply chain to reduce the time-to-market or relocate decision making to jurisdictions that are able to better serve the local customers. This suggests that further analysis is needed to understand how beliefs impact supply chain decision making.

The additional insights generated through the three cross-tabulations revealed that more can be learned, even without having full access to the raw data. However, it also showed that some patterns can only be explained through a more granular analysis. Staying at an industry level is not sufficient to understand how decision making for resilience is conducted in practice.

How surveys can provide differentiated answers to managers
In this section, the second step for bridging the unit of analysis gap is described. Based on our collaboration with Gartner, our analysis of the survey data, and our review of current supply chain resilience research literature, we have developed two recommendations for future surveys that can lead to supply chain-specific results. To illustrate our reasoning, we give three real-life company examples based on in-depth interviews with senior supply chain executives.

1. Use supply chain as the unit of observation (instead of company)
We believe that future supply chain surveys will benefit most from using a more detailed unit of observation which allows for a more differentiated analysis of the results (i.e., the unit of analysis is the organization entity that you wish to say something about). However, consulting surveys usually ask respondents to answer the survey questions from the perspective of their company (see Appendix A).

Thus, managers are forced to decide whether they are answering based on an average across all supply chains that are used by their company, which can be very misleading for conglomerates or companies with a wide product portfolio, or whether they are answering from the perspective of one specific supply chain without being able to document which one they are answering for. Both options can distort the results and complicate our understanding of the underlying drivers of resilience (see further details in Cohen et al.10).

Changing the unit of observation to be the supply chain will require clarification at the beginning of the survey, so that respondents do not answer from the perspective of the entire company, but rather do so for a particular, specified supply chain. Ideally, the survey asks the respondents to name the product (group) they are referring to at the beginning of the survey. This will lead to a respondent’s commitment to only one supply chain, for that product (group), and enable more detailed understanding of the results.

Company example: Henkel
Henkel is a global manufacturer of consumer-packaged goods with 20 billion revenue and 179 production facilities in 79 countries. The company is divided into three different business units, each with its own supply chain setup. Due to different setups, each supply chain has its own “point of differentiation” along the value chain (see Figure 3).

The laundry and home care products share the same footprint in terms of sourcing and production locations for scale efficiency reasons and use the same distribution network as all products are sold via retailers and distributors. However, the supply chains are differentiated based on a customer segmentation, resulting in different lead times and service levels.

The beauty care products also share the same production footprint due to similar technology and the resulting economies of scale, but the supply chains are differentiated by distribution channel into retail and direct-to-consumer (DTC) businesses, because personalized products which are directly shipped to the consumer require a different setup. And lastly, the adhesives business unit differentiates its supply chains based on production technology, ranging from local production facilities for construction business customers to a global center of production excellence structure for electronics customers.

This company example shows that a company might have very different supply chain setups across and even within a business unit. As these different setups need different approaches to becoming more resilient it is crucial to use a specific supply chain as the unit of analysis. Otherwise, a manager from this company could have answered the survey in many ways. Only with a survey based on a supply chain, can it be ensured that these overlapping factors are not aggregated into one response.

2. Understand the context
Choosing a more detailed unit of observation can remove some of the “noise” from the data since answers will be specific to one supply chain structure. Moreover, more can be gained by understanding the context associated with the responding managers answer.

There is a general belief that companies in the same industry tend to share the same supply chain resilience strategies. But that is not necessarily true. To understand why that is the case, it is important to realize that in general, industries are mainly defined by the primary product produced or sold. Other characteristics such as the production process or supply-side characteristics typically play a lesser role. Current research, however, suggests that grouping supply chains with regards to supply chain resilience requires similar operational product, process, and market characteristics11. Companies within the same industry can have different supply chain attributes due to factors such as company location, size, age, or number of product groups being offered.

One way to extract this information in a survey would be to ask detailed questions that reveal the operating characteristics of the product (group) with regards to the supply chain setup, market conditions, and product attributes. This approach will lead to more insights. However, this requires the addition of several “setup” questions, which already take up a significant portion of the total response time.

Instead of asking respondents to answer a lot of detailed questions about the operational attributes of their company, we recommend letting managers self-assess and classify their supply chain based on a resilience framework that associates a supply chain into a supply chain archetype which is defined by operational features of the company supply chain. Such self-classification captures the type of supply chain and the corresponding supply chain context for analyzing factors and attributes that influence current supply chain resiliency. This will put the managers’ answers into perspective and enable derivation of more detailed insights, which help companies to understand how to actually achieve resilience. This way, only one or two questions need to be added at the beginning of a survey.

The framework should be simple and easy to understand, so that it allows all respondents to select an appropriate archetype. We suggest using the “Triple-P” supply chain resilience framework12 which matches resilience strategies to supply chain archetypes. This framework requires responding to two questions13:

(1) about how the company’s supply chain(s) are organized and coordinate decision making, (homogeneity of internal supply-chain processes) with answer options “multiple independent supply chains”, “shared services”, “central guidance”; and “one-size-fits-all” and

(2) about how the company’s supply chain(s) coordinate decision making and information exchange with external partners and stakeholders (inter-company integration with other supply-chain actors), with answer options “less dependency/ engagement”, “coordination with key partners”, integrated systems”, collaboration”, and “vertical integration”.

Based on this classification into these two dimensions, three supply chain archetypes can be identified to group supply chains across industries based on their common barriers to achieving resilience and other operational features. Figure 4 summarizes the main results of the framework, adopted from Cohen et al.11. We note that other possible frameworks could be used to classify a supply chain.

Company example: Nike
Nike is a global apparel company focusing on sports and lifestyle clothes that sells $37 billion worth of products, which are produced in more than 600 factories in 54 different countries. The company is operating with essentially two different supply chain structures: a footwear and equipment supply chain and an apparel supply chain. Based on the “Triple-P” framework, the two supply chains belong to different archetypes (type 2 and 3) even though they are both within the same company. We illustrate the importance of understanding the supply chain context by considering how answers would be analyzed in typical consulting surveys versus how they can be interpreted when using the “Triple-P” framework instead.

Consolidated footwear supply chain
The footwear supply chain belongs to archetype 2, partner complexity. It is structured around a consolidated supply base with only a few contract manufacturers that can produce almost the full product portfolio with a limited number of large-scale factories in low-wage countries. Moreover, demand is rather predictable, and the technology is simple. This makes it easy to move production around in case of local disruptions or tariffs. Thus, the focal company collaborates with a dozen key partners after multiple decades of investing heavily in these key relationships to geographically diversify their manufacturing footprint.

Nike decided that further geographical diversification out of South-East Asia would make the footwear supply chain more resilient. Ultimately, the company wants to have production close to all demand hubs, in high-wage countries such as the US or central Europe.

Diversified apparel supply chain
The apparel supply chain belongs to archetype 3, process complexity. It differs with regards to technology, process, supplier relations and market dynamics. Nike is faced with a fragmented supplier market consisting of many specialized plants due to the great variety of materials and the complexity of material processing. Moreover, quickly changing customer preferences (fashion trends, seasonality) hamper long-term partnerships with suppliers.

To make the apparel supply chain more resilient, the company decided to focus on a smaller number of strategic partners with which they try to establish long-term relationships by helping them in the short term with preferred orders and financial aid and in the long run to diversify their product offerings. Geographical diversification is less of a concern as the fragmented market allows the company to easily do business with new production partners in new countries.

Analysis with and without context
Even though the supply chains are set up in different ways, managers from both business units could have selected, for example, the response to invest in “Shifting manufacturing from one country/region to another (including reshoring or nearshoring)” in the Gartner survey, for different reasons.

With the context given above for the two supply chains, it is understandable that a footwear manager would choose this strategy as the business unit tried to geographically diversify their manufacturing base to be in close proximity to final demand. In contrast, a manager from the apparel business unit has the streamlining of supply base activities in mind when indicating, that he/she is investing in shifting manufacturing. Bundling manufacturing capacities at a smaller number of contract manufacturer sites also involves shifting manufacturing capacities across countries.

However, usually the context is missing and therefore the underlying reasons for selecting a strategy remain unknown, as shown in Figure 5. If the respondents would have self-classified their supply chain beforehand, some of that context could have been understood (see Figure 6). In contrast to Partnership complexity, supply chains belonging to the Process complexity archetype usually have regional or even local setups.

Shifting manufacturing for them therefore does not involve re-shoring or diversification reasons. Thus, both business units could have chosen the same investment strategy for different reasons and this example shows that prior classification of the supply chain context could help to learn more about the reasoning behind the selected supply chain strategy.

Thus, using a framework, such as the suggested one, will enable surveys to mitigate the lack of crucial information to understand the underlying reasons for resilience strategy decision making and to compare supply chain setups based on similar operational attributes instead of using industry classifications.

Company example: Infineon
Infineon’s automotive supply chain is an example of the third archetype (type 1, product complexity). Infineon is a large player with $10 billion in revenues and 21 manufacturing sites distributed around the world. The company has basically one supply chain for its roughly 15,000 stock keeping units even though the product and demand characteristics differ.

The existing structure of Infineon due to its high-tech environment, volatile demand, and capital-intensive production, has built-in mechanisms to mitigate risk and resolve supply and demand disruptions as unexpected events occur on a regular basis. One example would be the investments in creating inhouse redundancies for the center of excellence production structure. These limiting factors are faced by all companies in the semiconductor industry which results in having basically one supply chain setup for this industry.

In contrast to the Nike footwear supply chain, Infineon is not about partnering with your core suppliers and contract manufacturers to get closer to the main demand hubs. Instead, strategies for becoming more resilient focus on logistics and distribution rather than production location or capacity. Thus, the company expanded the reach of its regional distribution centers to be able to supply not only their respective region but also the entire world. Moreover, actions such as preparation of master data were taken to enable fast stock transfers between distribution centers.

The Infineon supply chain example shows that the operational context of the supply chain in certain industries can limit the option space to such an extent that only one feasible supply chain configuration remains. For these cases, an analysis on industry level would be sufficient.

Conclusion
We identified some clear messages regarding the treatment of supply chain resilience in consulting survey-based reports and explained why such supply chain surveys are valuable for gaining an understanding about context and common approaches for new and upcoming topics such as the achievement of resiliency.

However, this article also showed that there is a mismatch between what can be inferred from these consulting surveys and what supply chain executives need to know to steer their supply chains effectively. We propose that this “unit of analysis gap” can be closed with two steps. The first step does not require any change to the current format of the surveys, as it breaks down the insights to the industry level based on further analysis of the raw data. An example is given in form of three cross tabulations drawn from a recent Gartner survey on supply chain resilience.

We noted that an industry level analysis alone, will not lead to supply chain-specific insights, which are required to develop a strategy such as resilience. We therefore introduce a second step that requires changing the unit of observation to the supply chain instead of the company. Asking additional questions to understand the context in which supply chain setup decisions are made supports overall understanding and enables differentiated statements to be made at the supply chain level. We propose letting respondents self-classify their supply chain according to the “Triple-P” framework.

This classification provides the necessary context and allows for a more nuanced understanding of why companies have implemented their current supply chain structure and strategy and provides concrete guidance for how to adopt a strategy that promotes resilience.

Three company examples are given to illustrate the three different archetypes. The company examples show how contextual factors, i.e., operational characteristics, determine the supply chain archetype and impact the implemented supply chain resilience strategy. Based on what is known about the barriers for each archetype, this context gives guidance for managers on what to do14. The Nike example illustrates the methodology by contrasting the information with and without using the Triple-P framework.

Thus, the results of this article suggest that the company-based format which is good for general management surveys is not a good fit for generating the insights necessary for a company to develop an effective resiliency strategy. Such surveys would benefit from more granular data. Questionnaire-based surveys that require the respondent to speak for a monolithic company-wide supply chain cannot effectively link operational characteristics to a supply chain-specific strategy. When applying these strategies in practice, managers necessarily run into company or supply chain setup-specific challenges and therefore they need more customized insights in order to develop resiliency strategies that will be successful.

Acknowledgement
The authors want to deeply thank Gartner and especially Geraint John and Kamala Raman for the collaboration on the survey questions of the “Future of Supply Chain: Crisis Shapes the Profession” report from December 2020. Moreover, we appreciate their help and the sharing of results and the aggregated data.
 

Notes
1. In the survey Gartner distinguishes between agility as “the ability to respond rapidly and cost-effectively to short-term changes in demand or supply disruptions” and resilience, “the ability to adapt to structural changes by modifying supply chain, products and technologies strategies”.
2. G. John, P. Manenti, S. Watt, and K. Raman: ‘Future of Supply Chain: Crisis Shapes the Profession: Supply Chain Executive Report’, Gartner,12/2020; available at https://www.gartner.com/en/documents/3994949/supply-chain-executive-report-future-of-supply-chain-cri.
3. The dataset includes the first five questions of the survey regarding supply chain resilience and agility (figure 20-24 in Gartner report). From the 1346 responses, only operations related job functions with a board level, VP/director, or manager/head role were included which resulted in 1049 responses.
4. Omar Arguilar, ‘Save-to-thrive - Enterprise transformation and performance improvement strategies during the COVID-19 pandemic’, Deloitte, 08/2020, available at https://www2.deloitte.com/content/dam/Deloitte/us/Documents/process-and-operations/us-save-to-thrive.pdf
5. Dimensional research, ‘Supply Chain Resilience In A Post-Pandemic World: A survey of supply chain decision makers’, 09/2020; available at https://www.jabil.com/dam/jcr:fef09432-3d00-45f8-9bc3-4da2cee764b1/special-report-supply-chain-resilience-in-a-post-pandemic-world.pdf.
6. Georges Dib, ‘Global supply chain survey – in search of post-covid-19 resilience’, Allianz research and Euler Hermes, 10.12.2020, available at https://www.allianz-trade.com/content/dam/onemarketing/aztrade/allianz-trade_com/en_gl/erd/publications/pdf/2020_10_12_SupplyChainSurvey.pdf
7. R. Gya, C. Lago, M. Becker, and J. Junghanns: ‘Fast Forward - Rethinking supply chain resilience for a post-COVID-19 world’, 24.11.2020; available at https://www.capgemini.com/wp-content/uploads/2020/11/Fast-forward_Report.pdf.
8. This is why Cohen et al. (2021) concluded that the basic roadmap to resilience is understood by managers, see M. A. Cohen, S. Cui, S. Doetsch, R. Ernst, A. Huchzermeier, P. Kouvelis, H. Lee, H. Matsuo, and A. A. Tsay: ‚Putting Supply-chain resilience Theory into Practice’, 2021, Forthcoming in Management and Business Review. https://ssrn.com/abstract=3742616
9. It is worth noting that we were not given access to the raw data that generated them.
10. M. A. Cohen, S. Cui, S. Doetsch, R. Ernst, A. Huchzermeier, P. Kouvelis, H. L. Lee, H. Matsuo, and A. A. Tsay: ‘Understanding Global Supply Chain & Resilience: Theory and Practice’, in ‘Creating Value with Operations Analytics’, (ed. H. L. Lee et al.); 2022, Springer.
11. M. Christopher, H. Peck, and D. Towill: ‘A taxonomy for selecting global supply chain strategies’, The International Journal of Logistics Management, 2006, 17(2), 277–287.
12. M. A. Cohen, S. Cui, S. Doetsch, R. Ernst, A. Huchzermeier, P. Kouvelis, H. Lee, H. Matsuo, and A. A. Tsay: ‘Bespoke Supply Chain Resilience: The Gap between Theory and Practice’, forthcoming in Journal of Operations Management, 2022.
13. More information on the derivation of the framework and regarding the answer options can be found in Cohen et al. 2022
14. Further details on the archetypes, the barriers and the strategies implemented can be found in Cohen et al. 2022

About the authors:
Morris A. Cohen is the Panasonic Professor of Manufacturing and Logistics in the Operations, Information and Decisions Department of the Wharton School at the University of Pennsylvania, in Philadelphia, USA. Email: [email protected].

Shiliang Cui is an Associate Professor of Operations and Information Management in the McDonough School of Business at Georgetown University in Washington, D.C., USA. Email:[email protected].

Sebastian Doetsch is doctoral student at the Chair of Production Management of WHU’s Otto Beisheim School of Management in Vallendar, Germany. Email: [email protected].

Arnd Huchzermeier is Chaired Professor of Production Management at WHU’s Otto Beisheim School of Management in Vallendar, Germany. Email: [email protected].

Ricardo Ernst is the Baratta Chair in Global Business and Professor of Operations and Global Supply Chain Management at the McDonough School of Business, Georgetown University, in Washington, DC, USA. Email: [email protected].

Panos Kouvelis is Emerson Distinguished Professor of Operations & Manufacturing Management, and Director, The Boeing Center for Supply Chain Innovation (BCSCI), Olin Business School, Washington University in St. Louis, USA. Email: [email protected].

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