Journal of Business Logistics, 2013, 34(4): 270–288 © Council of Supply Chain Management Professionals
Supply Chain Disruption Management: Severe Events, Recovery, and Performance John R. Macdonald1 and Thomas M. Corsi2 1 2
Michigan State University University of Maryland
iven their proclivity to occur despite managers’ best efforts, disruptions often result in lost sales, lead to large financial losses, and have a negative impact on shareholder wealth and operating performance. Less attention, however, has been paid to improving the process of managing a disruption from its discovery through to complete recovery. This entire process is not, in fact, fully understood. Clearer insights are needed surrounding the following issues: factors influencing the recovery process, how those factors interact to play a role in managerial decision making, and the company’s actual ability to recover. While it is possible to determine basic recovery process factors, a more complete picture of disruption management can be built from analysis of data collected through qualitative in-depth interviews. This research delivers insights around the interactions and relationships among factors, providing the foundation for a set of propositions useful for further investigation in the following areas: discovery of the disruption event, causes of the event, and recovery performance. One finding indicates that while internal disruptions are faster to recover from, they more likely lead to negative perceptions about the recovery performance outcome.
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Keywords: disruption management; recovery; risk management; supply chain
INTRODUCTION Supply chain disruptions have been defined as “unplanned and unanticipated events that disrupt the normal flow of goods and materials within a supply chain” (Craighead et al. 2007, 132). Much research has focused on preventing disruptions before they occur by minimizing the risk of their occurrence (see, e.g., Tomlin 2006; Ritchie and Brindley 2007; Zwikael and Sadeh 2007; Manuj and Mentzer 2008a; Wagner and Bode 2008; Fragniére et al. 2010; Wang et al. 2010; Yang and Yang 2010). However, a series of recent disruptions caused by events such as Hurricane Katrina (2005), the Eyjafjallaj€ okull volcano (2010), the Japanese earthquake/tsunami (2011), and the Evonik chemical plant fire in Germany (2012) provide unmistakable evidence that managers do not have the ability to prevent all disruptions. Certain events having a significant disruptive impact on supply chains will, in fact, occur regardless of risk planning. As a result, managers will continue to face the critical challenge of recovering from supply chain disruptions and attempting to minimize their impact. Thus, beyond understanding how managers might work to prevent disruptions through risk planning, it must be better understood how managers respond to and recover from the supply chain disruptions they experience. Indeed, managers face disruptions to their supply chains resulting from a variety of causes including: poor communication between suppliers and manufacturers, opportunism by suppliers, strikes by truck drivers or port workers, acts of terrorism, information technology (IT) malfunctions, industrial accidents, quality problems, operational problems, natural disasters, and government regulations (Sheffi 2001; Chapman et al. 2002; Cooke 2002; Machalaba and Kim 2002; Mitroff and Alpaslan 2003;
Corresponding author: John R. Macdonald, Department of Supply Chain Management, Michigan State University, 632 Bogue St., Room N370, East Lansing, MI 48824, USA; E-mail:
[email protected]
Blackhurst et al. 2005; McKinnon 2006). These disruptions often lead to large financial losses, lost sales, and have a negative impact on shareholder wealth and operating performance (Hendricks and Singhal 2003, 2005). After a disruptive event has impacted the supply chain, the goal of the affected company is to recover from the event and minimize its effects as quickly as possible. Clearly, the speed and success with which an organization recovers from disruptions depends in large part on the choices its supply chain managers make. As an example, the well-known example of Nokia and Ericsson (Sheffi 2005) can be called to mind to understand the difference managerial decisions can make on the recovery process. Nokia took a series of immediate, proactive interventions to recover from a supply chain disruption caused by a fire in one of its core suppliers of a critical cell phone component. As a result of these actions, Nokia arguably recovered more quickly and effectively than did Ericsson, which initially adopted a “wait and see” approach to handling the event. For organizations to effectively respond and recover when disruptions occur, managers should be aware of the internal and external factors that may affect the overall disruption management process. To date, however, the literature has only begun to define exactly what these specific factors are or how they are linked together in an overall process. Frameworks to date have focused primarily on steps to be taken (see, e.g., Helferich and Cook 2002) in recovering from the disruption. There has been far less attention, however, devoted to understanding the overall disruption management process (Bode et al. 2011). Blackhurst et al. (2005) describe three key process-level categories that are part of the overall postevent disruption management process; namely, discovery (of the disruption event), recovery (from the event), and redesign (of the system after recovery). Bode et al. (2011) began an exploration of factors by focusing on the buffering or bridging decisions managers make based on the disruption’s impact as well as the predisruption factors of trust, dependence, prior experience, and supply chain disruption orientation. A buffering decision will lead to reduction of a
Managing a Supply Chain Disruption
firm’s exposure to breakdowns in their partners’ supply chains through mechanisms such as added inventory. A bridging decision will lead to enhancing the relationship with supply chain partners through mechanisms such as increased communication and information exchange. Figure 1 puts these concepts in a time-series profile. Continuing in this line of research, the factors that influence, and contribute to, the process of disruption management need to be better understood. Insights into the manner in which the factors interact with one another and impact recovery performance are important. Toward that end, this exploratory paper works to build on previous research by: (1) identifying important factors involved in the recovery process that can expand on previous frameworks and (2) use experiences from decision makers who handle disruptions for their companies to provide understanding of how these factors tie together in a directional process, influencing and relating both to one another and how they may preliminarily affect ultimate recovery performance. A review of disruption-related research allowed development of an initial set of disruption factors relating to the categories of the event, discovery, readiness, recovery, and performance. To enhance these categories, and, borrowing heavily from a grounded theory approach, qualitative data were collected through interviews with high-level supply chain managers. Analysis of the data allowed identification of new factors to be incorporated into a more complete recovery framework of the disruption management process as well as investigate the concept of recovery performance, both of which are discussed in the results section. This does not seem to appear in previous research, especially given that less attention has been given to this research stream (Bode et al. 2011). Finally, a series of propositions are developed which are testable with a representative sample of supply chain managers in future research.
DISRUPTION MANAGEMENT The disruption management process makes an important contribution to a company’s overall resiliency (Bhamra et al. 2011). Resilience has been articulated in Sheffi (2005) as a business having the ability to recover quickly. Other definitions have appeared in more recent supply chain literature; one useful example is Fiksel’s (2006) definition: “the capacity for an enterprise Figure 1: Time-series profile of concepts.
Sources: Adapted from Sheffi (2005) and Zobel et al. (2012). Includes descriptions from Blackhurst et al. (2005)
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to survive, adapt, and grow in the face of turbulent change” (p. 16). Using similar words with alternate definitional scopes, Ponomarov and Holcomb (2009) include the terms of response and recovery as the latter parts of supply chain resilience that take place after the disruption has occurred. Turbulent change can refer to a disruption event, and how well the company performs in the recovery effort affects its ability to be resilient. It is vital, then, to know how to manage, and recover from, a disruption. Building on Figure 1, a set of previous research findings is reviewed to present a set of steps and factors important for understanding the overall disruption management process. These steps will begin with the event description and discovery, move through key aspects recovery process, and end with full recovery and the performance assessment of the company during the recovery effort. Event attributes Researchers have used a number of different attributes to define and categorize disruptive supply chain events. One example attribute is the impact (or severity) factor of the disruption, as evidenced in preevent likelihood versus impact matrices (Sheffi 2005). This matrix examines potential events that could affect a company and assigns a probability of occurrence (from low to high) and a consequence level (from light to severe) (Sheffi 2005, 32), mapping them altogether in a visual format to help managers make decisions about which potential events to use resources to mitigate against. Ogden et al. (2005) suggest using low-, medium-, and high-impact ranges for supply chain disruptions with no fixed cost points. “Impact” effectively serves as a higher-order factor that is made up of other factors, including event-specific and probable performance results. The term “severity” is conceptually similar to “impact” and has been either left out or proven difficult for researchers to define. The frameworks and constructs that exist to date presume that the disruption is serious and requires the steps or factors outlined by that framework. Some researchers have focused on circumstances that lead to severe disruptions, such as unreliable information (Loch and Terwiesch 2005). Others appropriately define it as a continuum, with severity denoted by the number of nodes within a supply network “whose ability to ship and/or receive goods and materials … has been hampered” by the disruption (Craighead et al. 2007, 134). Helferich and Cook (2002) use a subjective scale of minor (score of 1) to massive (score of 5) measured with lives, injuries, and dollars in their handling of the term in a Federal Emergency Management Agency (FEMA) context. Boin (2004) points out that the similar term “crisis” is subject to “the perceptions of decision makers, rather than some set of predefined conditions” (p. 171). Many studies that focused on other topics mention “severe disruption” without defining it (e.g., Heese 2007; Wagner and Bode 2008; Skipper and Hanna 2009). There are similar examples of categorizing disruption events. The cause of the disruption is an initial method, with Kleindorfer and Van Wassenhove (2004) using the concepts of “purposeful” and “accidental” disruptions. Similarly, “natural,” “intentional,” and “accidental” are used by Helferich and Cook (2002) and Ritter et al. (2007). Chopra and Sodhi (2004) use location as an identifier instead, with their categories of “supplier,” “internal,” and “customer” referring to the part of the supply chain that was
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affected. Murphy (2006) merges both categories into three groups: “natural events,” “external—man-made events,” and “internal—man-made events.” Disruption events can be of a short duration, such as a fire that is put out within 10 min at the Philips semiconductor plant (Sheffi 2005), while others, such as a port strike, can last much longer. It is important to note that the effects of even a shortlived event can last for months and perhaps years, as in the case of the Philips plant fire. Though the fire itself only lasted for mere minutes, the effect and recovery effort from that event lasted many months for both Nokia and Ericsson. Table 1 summarizes the key factors that have been discussed to this point, as well as those discussed in the remainder of this section.
of individuals representing various parties in the supply chain or various roles within the focal organization who will make decisions regarding the recovery process. The final structural attribute is what the actual available options for recovery are. There are also behavioral attributes of the people involved that apply to the recovery process. Perhaps the first factor, reflected earlier, is whether the risk plan is even referred to, if it exists. This action is likely based on two additional factors of the experience of the decision maker(s) (how many times they have faced similar situations) and the training that they have received (Sjoberg et al. 2006). Finally, recovery efforts can include the time pressure and intensity of the emotions felt by the decision maker, which corresponds to the severity of the disruption), among others (Hastie and Dawes 2001).
Managing the disruption
Performance
Two key phases of disruption management have been described as “discovery” (of the event) and “recovery” (from the event) (Blackhurst et al. 2005). Discovery refers to the point in time when people become aware of the event or supply chain disruption. After discovery, managers then begin to either quell the event and/or begin the recovery process. How quickly managers recognize that the event or disruption is occurring is vital. Only then can recovery, fully realized upon the return of the supply chain to its previous state, begin. After the disruption is discovered, supply chain managers often first assess any previous plans that have been developed as part of their risk management planning process. This is the concept of readiness, a plan of action that is standing by for implementation should certain events (or types of events) occur, and aid managers in determining what immediate actions to take in response to the effects of the event that has occurred. Helferich and Cook (2002) assume implementation as part of the first recovery step, while Ritter et al. (2007) allow for plans to not be applicable once the event has occurred. According to Morton (2002), companies should document and test their plans, train their employees in how to carry them out, and then maintain them. The importance of training is echoed by Ritter et al. (2007), who describe levels of scenario training that are valuable for readiness. There are both structural and behavioral factors that apply to the recovery process. Starting with structural, generally, the beginning of the recovery phase includes formal or informal designation of the decision maker(s) who will lead the recovery effort. Companies may centralize decision-making authority in one primary leader (Dubrovski 2004), in a team that has been created to make recovery decisions, or in a hybrid of the two approaches. Some companies establish war rooms, or meetings
As discussed in supply chain disruption literature, disruptions can affect companies in two primary ways: financial and service impacts. Financial impact refers to the monetary cost incurred as a consequence of the disruption. Service failures tend to occur during disruptions because companies cannot devote as much attention to meeting customer demand as they can in a normal operating environment (Melnyk et al. 2005). The goal of the recovery process is to minimize these impacts and their respective costs. A measure of a company’s recovery performance is the speed with which the recovery is completed. Speed has an effect on the cost and service impacts as well. The longer it takes to fully recover, the more expensive the entire recovery process is likely to be. What is missing, however, is how companies themselves view performance of the recovery effort. For example, the resumption of operations is the final step (that relates to performance) in the FEMA guide presented by Helferich and Cook (2002). As noted earlier, previous research efforts have not focused on explaining the entire disruption management process, from beginning to complete recovery. Efforts have begun, but additional questions remain. An effective way to answer them is with an inductive means of research. Some factors are known and developed, others are known but lack development, and still others require initial identification and insight.
METHOD A series of in-depth interviews with managers were conducted with a variety of companies who have experienced and
Table 1: Disruption management factors derived from literature review Framework category
Specific factors
Event Discovery and recovery
Severity, cause, duration Discovery: speed Recovery structure: Quantity (one or team), roles represented, options available Recovery behavior: Experience, training, refer to risk plan (if applicable), emotions, time pressure Speed of recovery, financial cost, customer impact
Performance
Managing a Supply Chain Disruption
“managed” their way through supply chain disruptions. Their experiences, relative to the disruption event and postevent internal management procedures, provide the basis for framing the factors that individually and interactively contribute to the overall disruption management process. These interviews are a fieldbased means of qualitative research. Other researchers (Flynn et al. 1990; Stuart et al. 2002; Mello and Flint 2009) have recommended or encouraged greater use of this method in supply chain research as resulting models are more comprehensive and —once subjected to quantitative, empirical testing—more robust. The scope of this investigation is limited to the period encompassing the beginning of the disruption event through to its effective end, defined as a full recovery from the disruption event. This scope does not minimize the importance of risk management or its many frameworks dealing with efforts prior to the disruptive event (see, e.g., Manuj and Mentzer 2008b), or any corporate learning effects and system redesign, which can occur during or after the event is recovered from (see, e.g., Blackhurst et al. 2005). Qualitative research principles are followed in the sample selection, data collection, and data analysis research phases. These principles stem from the Grounded Theory tradition of Corbin and Strauss (2008) as well as general case study methods from Yin (2003). In addition, Flint et al. (2002) provide an appropriate example of the proper application of data collection rigor. Sample selection An essential aspect of the field-based research method is the selection of companies and participants for interviews. Glaser and Strauss (1967) state that a purposive method of sampling works well in conjunction with in-depth interviews, as it facilitates adding companies or industries of interest. The corporate contacts were generated both from a convenience sample of relationships the authors had as well as a set of contacts provided through a third-party logistics company. This type of service provider often assists customers in recovering from supply chain disruptions. The interview sample is chosen by applying the principle of theoretical sampling (Glaser and Strauss 1967). This principle states that the first few interviews reveal relationships between concepts, terms, and their dimensions, as well as important variations (Corbin and Strauss 2008). The way to add knowledge about a specific area is to find additional observations (samples) based on theoretical, relational, and discriminative reasons (Flint et al. 2002). For example, when one participant noted the difference in supply chain “speed” between his industry and the hightech sector, two companies from the high-tech industry were added to the data set. The final sample is diverse in terms of company size and product/industry. After the contacts are initiated, participant appropriateness determinations are made by forwarding example questions and confirming their experience with disruption management through emails and phone calls. Reliability of the data is confirmed through job scopes and positions within the company. Data are collected to a point of theoretical saturation (Flint et al. 2002), rather than predetermining the number of interviews. In this data collection, saturation was indicated by the repetitiveness of the
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information being provided (Flint et al. 2002). The final set includes interview data from 17 participants at 17 different companies. Table 2 displays demographic information about the participants and their companies. Data collection: protocol and validation An interview protocol was developed from factors included in the reviewed literature. Through an iterative process, the two primary researchers refined the protocol. Four researchers familiar with the key components of supply chain disruptions and qualitative research were asked to review the protocol. However, in keeping with the principles of theoretical sampling, each interview was treated as a replication of a process following the pattern of Pagell (2004). This allowed for the original set of questions to be updated with additional questions after each interview as needed. Especially during the first few interviews, questions and issues can be realized that should be investigated in subsequent interviews. An example of this is the question of how a manager’s postdisruption performance is evaluated. More importantly, at the end of the interview process, any questions that were asked of later respondents, but not of early respondents, were sent to those who had not had the opportunity to answer them. In this manner, reliability and rigor are ensured. The interview protocol is provided in the Appendix. An alternative perspective states that this type of revision (theoretical sampling) introduces bias to the interview protocol (Miles and Huberman 1994). While this view is understood, it is argued that the validity of the chosen procedure depends on the final goal of a research effort. The goal of this research is to develop the disruption management process; any additional questions developed as a result of information obtained in the early interviews will reveal factors that otherwise might not have been determined prior to the development of the interview protocol. The interview protocol employs the critical incident technique (Flanagan 1954) to ask questions related to the direct observations of the participants about the specific disruptions in order to understand the event and aid recall details. The participants are asked to identify two severe supply chain disruptions, a wellmanaged disruption and a disruption that had the opportunity to be better managed. This same method of identifying two types of disruptions of varied perceived performance has been successfully used by other researchers (see, e.g., Craighead et al. 2007). All of the interviews were recorded and last between 45 and 135 min. The average length was 75 min. Although past research demonstrates that conducting interviews via telephone does not lead to differences in the results (Blackhurst et al. 2005; Craighead et al. 2007), the interviews were conducted in person whenever possible. Ten of the interviews were conducted face-to-face. Flint et al. (2002) bring together nine criteria from previous interpretive and grounded theory streams of research to help ensure the trustworthiness of the research findings. Strauss and Corbin (1990) represent grounded theory by incorporating control, fit, generality, and understanding. From multiple authors in interpretive research, confirmabilty, credibility, dependability, generality, and transferability were included (Lincoln and Guba 1985; Hirschman 1986; Wallendorf and Belk 1989). All nine criteria are adhered to and met in this research. Multiple researchers
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Table 2: Participant and company demographics
Participant†
Gender
Adam
Male
Bob
Male
Doug
Male
Fred
Male
Greg
Male
Hal
Male
Manager of Worldwide Logistics Quality Director Current Material Availability, Mfg. Supply Operations Executive Director for Global Logistics Warehouse Lead North America Director of Global Transportation Logistics and Warehousing VP of Global Supply Chain
Ivan
Male
Global Purchasing Manager
John
Male
Kevin
Male
Larry
Male
Matthew Nick
Male Male
Oliver
Male
Paul
Male
Executive Director for Global Inbound Logistics Vice President of Supply Planning Senior Manager of Operations Planning Supply Chain Manager Senior Manager for Global Transportation Logistics Manager for the Americas Director of Transportation
Randy Steve
Male Male
Teresa
Female
Title
Supply Chain Manager Leader—Global Transportation Organization Manager of International Logistics
Current position exp.
Supply chain exp.
Comp. size (Ann. sales, in $B)
Comp. no. of employees
Agricultural equipment Automotive
4 years*
34 years
$10+
25,000+
3 years
31 years
$10+
25,000+
Chemical
3 years
20 years*
$10+
