Master Thesis Supply Chain Management
University of Groningen
SUPPLY CHAIN RESILIENCE – How partnerships help to
minimize the effects of disruptions
Sanne Schilder
S2357869
sanne-schilder@live.nl
Supervisor University of Groningen: Dr. K. Scholten
Co-assessor University of Groningen: Prof dr. J. de Vries
June 20, 2014
Word count: 10.6252
CONTENT
ABSTRACT ... 4
1.
INTRODUCTION ... 5
2.
THEORETICAL BACKGROUND ... 7
2.1 Supply chain resilience ... 7
Constructs of supply chain resilience ... 8
2.2 Collaboration... 10
Buyer-supplier relationships ... 11
Conceptual model ... 13
3.
METHODOLOGY ... 14
3.1 Introducing the focal company ... 14
3.2 Case selection... 15
3.3 Data collection ... 17
3.4 Data analysis ... 18
4.
FINDINGS ... 20
4.1 How relationship strength relates to supply chain resilience ... 20
Information sharing ... 21
Joint relationship efforts ... 22
Dedicated investments ... 23
Mutual dependency ... 24
Years experience ... 24
4.2 Stronger relations leading to more resilience ... 25
5.
DISCUSSION ... 27
6.
CONCLUSION ... 30
6.1 Managerial implications... 31
6.2 Limitations and suggestions for future research ... 32
REFERENCES ... 33
APPENDIX A: INTERVIEW PROTOCOL ... 37
Interview guide (supplier) ... 37
Interview guide (Focal company) ... 41
APPENDIX B: STUDIED DOCUMENTS ... 46
APPENDIX C: CODING TREE EXCERPT ... 47
APPENDIX D: CASE NARRATIVES ... 49
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Case B ... 50
Case C ... 51
Case D ... 52
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ABSTRACT
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1.
INTRODUCTION
An international survey conducted in 2013 shows that 75% of the companies experienced at least one disruption in 2013 (Business Continuity Institute, 2013). Examples of those disruptions include equipment malfunctions, unforeseen discontinuities in supply, employee strikes, natural hazards, terrorism and political instability (Kleindorfer & Saad, 2005). Due to more pressure for efficiency and globalization, increasing the length and complexity of the supply chain (Blackhurst, Dunn & Craighead, 2011; Christopher & Peck, 2004; Pettit, Croxton & Fiksel, 2013) companies now are more than ever vulnerable to supply chain disruptions. The consequences hereof may have a direct effect on the ability to continue operations and serve customers (Jüttner, 2005): 15% of all respondents suffered more than €1M and 7% had even more than €11M in costs per incident (Business Continuity Institute, 2013). They can even result in entities in the supply chain, or the whole supply chain, shutting down (Jüttner & Maklan, 2011). As most supply chain disruptions (58%) occur at the first tier supplier and failure of service provision by an outsourcer is among the top 5 causes for disruption (Business Continuity Institute, 2013), sourcing decisions can be of vital importance to reduce (the impact of) those disruptions. There are some indications that having stronger buyer-supplier relationships may lead to a more resilient supply chain (Blackhurst et al., 2011; Wieland & Wallenburg, 2013). However, it does not become clear from previous research how companies need to manage their supplier relations in order to reduce the impact of those disruptions (Wieland & Wallenburg, 2013).
In order to prevent disruptions, companies engage in supply chain risk management (SCRM) approaches (Jüttner, 2005), which focus on identification, quantification and management of supply chain risks. However, not all supply chain disruptions can be anticipated through SCRM (Pettit, Fiksel & Croxton, 2010), resulting in the concept of supply chain resilience currently being of upcoming interest, as this does help to deal with those disruptions (Jüttner & Maklan, 2011). Supply chain resilience helps to reduce the impact of a disruption and provides the ability to recover quickly from a disruption when it does occur (Sheffi & Rice, 2005), it can be defined as “the adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function” (Ponomarov & Holcomb, 2009: 131).
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state that increased collaboration and information sharing – which is present to a higher degree in single sourcing relations (Skjott-Larsen, Schary, Mikkola & Kotzab, 2007) – are mitigators as they help to make risk response processes faster (Ergun, Heier Stamm, Keskinocak & Swann 2010) (as was mentioned in Wieland & Wallenburg, 2013). Hence, there is a need for strong supplier relations in creating a resilient supply chain (Christopher & Peck, 2004; Christopher, Mena, Khan & Yurt, 2011; Jüttner & Maklan, 2011; Kleindorfer & Saad; Peck, 2005; Wieland & Wallenburg, 2013). A case study from Blackhurst et al. (2011: 382) indicates that companies see supplier relationship management as an important tool to create more resilient supply chains and “suppliers are the companies number one worry” in terms of risk sources. However, no in-depth empirical evidence has been provided for this so far; it remains unclear how relations with suppliers need to be strengthened in order to create a more resilient supply chain. Therefore, the aim of this study is to explore How the strength of buyer-supplier relationships influences supply chain resilience. This will be investigated by means of an explorative multiple case study among four buyer-supplier relations, that differ in relationship strength, measured by means of the degree of collaboration between buyer and supplier, e.g. the degree of information sharing, joint relationship efforts and dedicated investments (Nyaga, Whipple & Lynch, 2010).
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This report will continue with the theoretical background, describing literature related to supply chain resilience and collaboration in buyer-supplier relationships. Followed by the methodology, findings and discussion of the case study. Finally, a conclusion will be provided, along with some suggestions for future research.
2.
THEORETICAL BACKGROUND
2.1 Supply chain resilience
As it is advised to consider the effect of relations on either supply- or demand-risks specifically (Wieland & Wallenburg, 2013), this research will focus mainly on the supply side disruptions, which are related to the potential or actual disturbances to the flow of products or information resulting from the network upstream to the focal firm (Christopher & Peck, 2004). Supply chain resilience helps to deal with these (unforeseen) disruptions, through building adaptive capability to prepare for events, reducing the impact of a disruption and strengthening the ability to recover quickly from it, covering the three phases of a disruption (Sheffi & Rice, 2005): readiness, responsiveness and recovery (Jüttner & Maklan, 2011).
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Constructs of supply chain resilience
As the previous part implies, the underlying constructs that create supply chain resilience differ among the studies written about resilience. However, taking a closer look at multiple articles that form the base of this study, and comparing the constructs used, results in some overlap as shown in Table 1 below.
Construct Christopher and Peck (2004) Jüttner and Maklan (2011) Pettit et al. (2010) Sheffi and Rice (2005) Wieland and Wallenburg (2013) Anticipation Collaboration Flexibility Redundancy (or capacity) Velocity (or speed) Visibility
TABLE 1: Resilience constructs used in previous studies
The papers used in Table 1 may not cover all possible underlying constructs for resilience that are available in literature. Since the aim of this study is not to provide a full review of available resilience papers, this overview is merely provided to demonstrate the similarities and differences amongst papers that form an important grounding for the current study. Jüttner and Maklan (2011) review more literature related to resilience constructs, resulting in four underlying constructs - flexibility, velocity, visibility and collaboration - that result in resilience, all aiming at building adaptive capacity in the supply chain. Capturing the conceptual essence of the suggestions in Table 1 and therewith providing a well-grounded framework to describe resilience for the current study.
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(Daugherty et al., 2006; Paulraj, Lado & Chen, 2008; Holweg, Disney, Holmström & Smaros, 2005). Due to this complexity, the concept of collaboration will be discussed more in depth in the following section, after the other three constructs - flexibility, velocity and visibility - are discussed in more detail individually below.
Flexibility
Flexibility can be defined as “being able to bend easily without breaking” and forms the ability to encounter, resolve and when appropriate exploit unexpected disruptions through effective responses (Jüttner & Maklan, 2011: 247). Hence, it helps to sense threats and respond to them quickly, influencing the readiness and responsiveness phase of supply chain resilience (Sheffi & Rice, 2005). The operationalization of flexibility would be the ability to change the number of possible supply chain options and the degree of difference between those options in order to cope with market changes or events, when performing comparably well (Jüttner & Maklan, 2011). In short, it contributes to resilience with the ability to alter processes within the supply chain quickly in response to an (upcoming) disruption.
Velocity
Velocity is concerned with the total time it takes a product to move through the supply chain (lead time), or the speed with which a supply chain can react to market changes or events (Christopher & Peck, 2004), focusing on the efficiency within the supply chain (Jüttner & Maklan, 2011). Higher supply chain velocity in this regard leads to quicker response to a disruption and helps to recover more quickly. It supports the adaptive capacity of the supply chain in all three phases of resilience by indicating the rate at which the risk event happens, the rate at which losses happen, how fast the event is discovered and the speed of recovering from an event (Manuj & Mentzer, 2008; Jüttner & Maklan, 2011). Hence, velocity contributes to resilience, by reducing the timeframe where the disruption impacts the supply chain, determining the loss that happens per unit of time (Jüttner & Maklan, 2011).
Visibility
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contributing to resilience in effective response and recovery, but also through event readiness by having the right information available in a timely manner (Jüttner & Maklan, 2011).
2.2 Collaboration
Since collaboration is argued to be one of the four constructs of resilience (Jüttner & Maklan, 2011), but on the other hand also influences visibility, velocity and flexibility (Daugherty et al., 2006; Paulraj, Lado & Chen, 2008; Holweg, Disney, Holmström & Smaros, 2005), this construct is elaborated more in-depth in this section. Collaboration as a construct of resilience results in reduced uncertainty which improves event readiness, but also improves responsiveness, by preventing opportunistic behavior from both parties (Jüttner & Maklan, 2011). After the disruption, parties should collaborate as well, in order to share experiences, improving resilience for a next disruption (Jüttner & Maklan, 2011). Hence, collaboration is important to build resilience in all phases of a disruption. However, it is unclear how collaboration exactly influences resilience, via visibility, velocity and flexibility or more direct.
In operationalizing collaboration, previous studies use dimensions such as information sharing, dedicated investments and joint efforts, like joint strategic planning and decision making (Jagdev & Thoben, 2001; Ramanathan & Gunasekaran, 2014; Daugherty et al., 2006). We follow Nyaga et al. (2010), who created a framework for collaboration by taking into account multiple previous studies, representing the overall concept of collaboration. In this framework collaborative activities include information sharing, joint relationship effort and dedicated investments, which all together lead to trust and commitment (Nyaga et al., 2010). Therefore, the definition of collaboration that will be used is:“two or more chain members working together to create a competitive advantage through sharing information, making joint decisions, and sharing benefits which result from greater profitability of satisfying end customer needs than acting alone” (Simatupang & Sridharan, 2002: 19).
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how often there is contact between company representatives to share information and how sensitive the information shared is. Also the time from when the information was known to the supplier until it is shared to the buyer, or the other way around, is taken into account here. Secondly, joint relationship efforts include joint goal setting, planning, vendor managed inventory, performance measurement like supplier evaluation and taking responsibility by joint problem solving (Min et al., 2005; van der Vaart & van Donk, 2008). Joint relationship effort is operationalized as the joint projects set up between buyer and supplier and joint actions taken. Finally, dedicated investments are investments dedicated to-, or critical resources embedded in the relationship, such as employees, systems, capacity, production lines or other resources that are dedicated to this customer/supplier (Heide & John, 1990; Dyer & Singh, 1998). These investments are operationalized as all investments that are made specifically for the relationship between buyer and supplier and are no longer relevant or have less added value when the relationship would be dismissed.
Buyer-supplier relationships
As indicated before, the strength of relationships between buyer and supplier seems to have an impact on supply chain resilience (Blackhurst et al., 2011). These buyer-supplier relationship strengths can be classified in many ways, depending amongst others on economic factors, the character of the exchange relationship, the distance between buyer and supplier and the cooperation between buyer and supplier (Olsen & Elram, 1997). Furthermore, the strength could be measured based on commitment, trust and relationalism involved (Hausman, 2001) or via communication, collaboration and integration (Wieland & Wallenburg, 2013), where communication improves resilience, but effects of both cooperation and integration on resilience are contradicting to other studies (Paulraj & Chen, 2007; Braunscheindel & Suresh, 2009). The common part in all of these classifications is that they include a form of collaboration or concepts such as trust and commitment, that are related to collaboration (Nyaga et al., 2010). Hence, multiple papers see increasing collaboration and stronger buyer-supplier relationships as interchangeable (Paulraj et al., 2008; Nyaga et al., 2010). Therefore, the framework that is used to classify buyer-supplier relationships in this study is one from Trent (2007), determining the strength of relationships based on collaboration. The framework is adapted1 (see Figure 1) with the degree collaborative activities -
information sharing, joint relationship efforts and dedicated investments - (Nyaga et al., 2010) that take
1 Originally the four C’s from Trent (2007) had the following characteristics:
Counterproductive relations: also called antagonistic relationships; parties work actively against the needs of each other; neither party takes responsibility for what happens in the relationship; destructive conflict occurs.
Competitive: also called adversarial relationships; parties engage in struggle over fixed value; parties attempt to maximize value for their side; minimal sharing of information.
Cooperative: parties work together and share information; closer relationships are a result of mutual goals; supplier involvement increases.
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place in each type of relationship. Overall, the framework shows that the more intense the collaboration between buyer and supplier is, the stronger their relationship will be. This could also be seen as more integration between buyer and supplier, since integration is defined as “the degree to which a manufacturer strategically collaborates with its supply chain partners and collaboratively manages intra- and inter-organization processes” (Flynn, Huo & Zhao, 2010: 59), recognizing the importance of close and interactive relationships with suppliers. Increasing supplier integration in this regard, will help to improve understanding and anticipation of the focal company’s needs through more mutual information exchange and in that way makes the supplier respond better to changing needs (Flynn et al., 2010).
FIGURE 1: The four Cs of supply relationships adapted from Trent (2007)
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Wieland and Wallenburg (2013) were first, however, next to finding some evidence for the positive effects of communication on resilience, their study also results in some contradictions with existing literature as mentioned before.
Since the main determinant for relationship strength in literature is collaboration, the way collaboration between one buyer and its suppliers influences the resilience of their supply chain towards supply side disruptions is investigated in this study, as explained more in-depth below.
Conceptual model
As described throughout the theoretical background, collaboration, flexibility, velocity and visibility, are the constructs that form a more resilient supply chain. Besides, it is indicated that collaborative relations result in higher visibility, flexibility and reduced lead times (Daugherty et al., 2006; Paulraj et al., 2008; Holweg et al., 2005). Hence, collaboration next to directly leading to resilience, also influences the other three capabilities - flexibility, velocity and visibility - resulting in resilience. Building on this, the need arises to understand how exactly collaboration relates to resilience; directly or through visibility, velocity and flexibility. Therefore, in order to investigate how the strength of buyer-supplier relations, operationalized as collaboration, influences supply chain resilience, this study explores collaboration as a antecedent for velocity, visibility and flexibility as shown in the conceptual framework, Figure 2 below.
FIGURE 2: Conceptual model
Collaboration determines the strength of buyer-supplier relations based on the degree of information sharing, joint relationship efforts and dedicated investments (Nyaga et al., 2010; Trent, 2007). Relations between those collaborative activities and (the constructs of) resilience will be explored in depth by collecting data related to supply risks from both suppliers and buyers within multiple supply chains. It has
Collaboration
Information sharing Joint relationship efforts Dedicated investments
Velocity Flexibility Visibility
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been found before that information sharing, or communication, leads to increased visibility across the supply chain (Faisal et al., 2006), which reduces uncertainty (Holweg et al., 2005), making the (possible) disruption visible in an early stage. Next to that, it helps to reduce lead times (Paulraj et al., 2008; Daugherty et al., 2006), leading to improved velocity. While lack of information sharing results in problems with creating a flexible supply chain (Chan, Wang, Luong & Chan, 2009). Supply chain resilience will increase with dedicated investments, since this leads to more willingness between parties to invest in helping each other when a disruption occurs (Wieland & Wallenburg, 2013). Furthermore, decision synchronization is necessary for effective disruption responses (Simatupang & Sridharan, 2008), indicating the impact of joint efforts on flexibility. Overall, collaboration helps to increase visibility, flexibility and responsiveness (Faisal et al., 2006; Daugherty et al., 2006).
3.
METHODOLOGY
In order to empirically investigate the effect of buyer-supplier relationship strength on supply chain resilience, a multiple-case study was executed, since this method is most appropriate to explore a real-life phenomenon in depth (Yin, 2009). Multiple cases were included because this provides a more objective dataset, with which a cross-case analysis can be done (Yin, 2009), increasing analytical generalization of the study (Voss, 2009). A number of four cases were studied, because time to gather and analyze data was limited. Besides, a minimum of four cases is suggested by Eisenhardt (1989) in order to have some convincing and robust theory as it is grounded in more varied empirical evidence (Eisenhardt & Graebner, 2007). Since literature related to supply chain resilience asks for a holistic view (Pettit et al., 2013; Jüttner, 2005) and it is suggested to focus on one type of risk, either demand- or supply risks (Wieland & Wallenburg, 2013), the unit of analysis for this study was the relation between the first tier supplier and the focal company within the supply chain, focusing on supply side disruptions. The four cases that were used include relations with four different suppliers from one focal company.
3.1 Introducing the focal company
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located in the west of Europe. It is essential that all of the raw materials are in place in order to be able to produce and deliver a product to the highly demanding customers. Therefore, a disruption in the supply side of the supply chain can cause serious trouble for this company. In the past year, supply disruptions at X have caused damage for over €1.000.000,- in terms of lost customer revenues, destroyed raw materials and additional costs made in order to process lower quality products.
3.2 Case selection
In line with the aim of this study to investigate the effect that the relationship strength has on resilience, four cases were selected based on the adapted classification of Trent (2007), assuming the more collaboration takes place between the focal company and the first tier supplier, the stronger their relationship will be. Figure 3 shows the characteristics per case, based on which the cases were selected. Through applying theoretical replication (Voss, 2009), by choosing cases with different positions on the four C’s continuum, we expect to see differences in the degree of supply chain resilience between cases.
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A broad amount of cases was preselected through analysis of documents related to the supply base (Appendix B) for background information, picking suppliers that are of significant financial and strategic importance to the focal company. Selection criteria were that suppliers should be in the top 40 raw material suppliers when it comes to yearly financial spend and supplying at least some key products to the focal company, which are mostly single sourced and in some way specific to the focal company. The suppliers had no or short-term (1 year) written contracts with the focal company, but there is some bonding due to the long-term relationships with some of those suppliers as well (as shown in Figure 3) and due to the common customer in case C which results in unwritten commitments. Those criteria were applied to keep the supplier importance relatively equal amongst the cases. Besides, a conversation with the purchasing manager and senior purchaser of the focal company helped in understanding the importance and relationship with several suppliers and led to a final selection of four cases that differ in relational strength but which all are of significant financial and strategic importance to the focal company. Due to anonymity issues, those suppliers are named A, B, C and D. The relationship characteristics of each case, as mentioned by the purchasing manager and found in documentation based on which the cases were initially selected, are shown in Figure 3. Supplier A here is the supplier that has the weakest relationship with the focal company and supplier D has the strongest relationship, based on the degree of collaborative activities. After analyzing the interviews, it turned out that the initial estimation of the relationship strength is in line with the actual degree of collaborative activities as perceived by the representatives of both buyer and supplier and as shown in figure 4 below.
FIGURE 4: Relationship strength cases 0 1 2 3 4 5 Information sharing Joint relationship efforts Dedicated investments Case A Case B Case C Case D
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3.3 Data collection
In each case, interviews were taken from one representative from the first-tier supplier and one representative that is related to that supplier within the focal company. The interviewee was chosen as the person in the organization that knows most about interactions with and historical disruptions related to the other party. The functions and additional information related to each interview is shown in Table 2. A number of two interviews per case was chosen in order to reduce respondent bias, so increase reliability and to view the case from both the supplier and focal company perspective, increasing the richness of the data (Voss, 2009). These interviews help to provide insightful data on the specific case study targets (Yin, 2009). Additional background information was derived from reviewing company documents (see appendix B for a list of documents that were reviewed) and informal conversations with people from the focal company. These additional data sources are used to achieve reliable historical data and will enhance data triangulation, which helps to improve the content validity of this study (Voss, 2009).
Supplier case A Focal company case A Supplier case B Focal company case B Supplier case C Focal company case C Supplier case D Focal company case D Interviewee(s) position(s) Account manager Buyer SC analyst + planner Buyer Account manager Buyer Commercial director Buyer Location X X B X X X X X Total time recorded
71 min 62 min 48 min 63 min 73 min 50 min 51 min 49 min TABLE 2: Interview details
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3.4 Data analysis
The interviews were analyzed by following the three steps suggested by Miles and Huberman (1994), data reduction, data display and conclusion. Reducing the data was done firstly by means of transcribing the interview in terms of quotes that may be of relevance for this study. Then, those quotes were coded, labeling parts of the interview into categories and subcategories (Miles & Huberman, 1994). Definitions used for the (sub)categories are displayed in Table 3 and are deductively derived from the theory as discussed in the theoretical background wherever this was possible. However, some new variables that were indicated to influence behavior that results in resilience were inductively derived form the interviews. First of all, mutual dependency was mentioned now and then and is indicated to lead to a more collaborative attitude. Additionally, years experience turns out to improve visibility, because both companies get to know the (processes of the) other company better over the years, which makes it possible to respond faster to disruptions and recognize it early on when a certain disruption is coming and what influence it may have. Therefore, those inductive variables were added to the deductive variables in Table 3.
Categories and subcategories Collaboration
Information sharing The amount of relevant information shared, the quality or usefulness of the information, how often there is contact between company representatives to share information and how sensitive the information shared is. This includes visiting the other company and generating insights in their production processes.
Joint activities The joint projects set up between buyer and supplier and joint actions taken.
Dedicated investments Investments that are made specifically for the relationship between buyer and supplier and are no longer relevant of have less added value when the relationship would be dismissed.
Phases of disruption
Readiness The time to prepare until the disruption strikes at the focal company, so when it is clear that a disruption is coming.
Responsiveness Includes the reaction from both companies to the disruption, form the first response to the disruption, until recovery starts.
Recovery The process of returning to the original state of the supply chain, or even better than original.
Supply Chain Resilience
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Velocity The speed with which a supply chain can react to and recover from a disruption, so the overall timeframe where the disruption impacts the supply chain.
Flexibility The ability to sense threats and respond to them quickly by altering processes within the supply chain.
New categories derived from the interviews:
Mutual dependency The importance of the customer to the supplier, or the other way around and dependency on the other company.
Years experience The amount of years companies have been working together and visiting each other.
TABLE 3: Category definitions
Starting with coding, the code was first related to a subcategory of collaboration, or directly to the category “mutual dependency”, which was then related to subcategories of collaboration as well, since mutual dependency improves (parts of) collaboration. Besides, some quotes were linked directly to the new category “years experience”. From each quote it could be derived to which phase(s) of a disruption it was related and which construct(s) of resilience were influenced. Therefore, the codes were related not only to the different subcategories of collaboration, but also to the subcategories of supply chain resilience and phases of disruption. In this way it becomes clear how collaboration influences resilience and in which phase of a disruption a specific collaborative activity is
important
. An excerpt of such a coding tree can be found in Appendix C, showing how different aspects of collaboration lead to resilience and to which degree the collaborative activities are present in each phase of a disruption. For this, a database was set up, keeping track of each data reduction step from scratch. When anything in the interview data was unclear or missing, the gap was filled by asking the respondent afterwards to provide some more clarity on that specific issue, in order to increase reliability of the data.20
the different aspects of collaboration influence supply chain resilience and in which phases of a disruption it is most applicable. This was done by combining all coding trees into one large coding tree and analyzing in which way the characteristics of collaboration are related to resilience and what are important underlying aspects. Those characteristics and the degree of presence per case are displayed in Table E1 in Appendix E.
This methodology does have some limitations even though we made several choices that enhance the reliability and validity of the data. First of all, the results do not have a high practical generalizability, in contrast to the analytical generalizability that is achieved. This is due to the trade-off that had to be made between more rich data collection, or using more similar cases to be able to generalize results. However, this low amount of cases was needed in order to be able to generate more in-depth insights. Secondly, the interviews with the suppliers mostly took place at the location of their customer (the focal company). Even though we made sure that there were no interferences and a private room was used, this may have led to respondents being less open, since they were not in their own environment.
4.
FINDINGS
4.1 How relationship strength relates to supply chain resilience
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FIGURE 5: Relationship strength, mutual dependency and years experienceInformation sharing
The most mentioned collaborative activity that improves resilience is information sharing, this helps mainly to create visibility in the supply chain. It was stated in the interviews that visiting the other company helps to generate insights in the processes of the other company and gives the ability to recognize possible disruptions early on, especially the buyer, account manager and quality employees are involved in this. In case D this activity was mentioned to be highly important in order to recognize (possible) disruptions early on as stated by the commercial director of supplier D “The buyer of X visits us once a week, then we have a look at the products that we are about to deliver to X in a while. In that way we can make sure that we can anticipate on possible quality or quantity issues early on”. Besides, face-to-face contact and after that phone contact were mentioned to be the best ways to communicate about disruptions in order to solve and anticipate them quickly, as the account manager of A for example says “Because I went to visit the production location of X immediately and actually could see what was happening over there, I was able to respond to this issue in a quick manner and better explain to people from A what was happening as well. This works better for me than when I would have done this from a distance”. Companies also tend to have more intensive contact during disruptions and most do evaluate disruptions in order to be able to learn from it for the future, so improve resilience of the supply chain, as emphasized by the buyer of case D “I do evaluate everything with D, every disruption, in order to learn for the future, to prevent things like this and to be able to respond even better with future disruptions”. Next to that, it is important that information is shared early on and is detailed, reliable, complete and of good quality. Types of information mentioned to
0 1 2 3 4 5 Information sharing Joint relationship efforts Dedicated investments Dependency Supplier on X Dependency X on Supplier Years experience Case A Case B Case C Case D
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have an impact on visibility are amongst others orders, forecasts, upcoming disruptions, market trends and maintenance schedules.
However, next to visibility, it became clear that information sharing also improves velocity. Having information available in time and knowing the processes of the other company, helps to quickly anticipate and respond to or better recover from a disruption. In case C, information related to one disruption was not shared which actually resulted in a long-lasting disruption, as their account manager says “They [the supplier of C] did not inform us or X about this and did not specify this with their product either. So they actually did not provide us with the time to anticipate on the fact that something like this might happen”. This in contrast to one disruption in for example case D, where things are anticipated as soon as possible, due to the high amount of visits from buyer to supplier. Hence, it might be that visibility in some cases actually leads to velocity, leading to a surprising new insight. In some cases, information sharing also helps to improve flexibility. As for example in case D, where the production process is fixed from a certain moment, but could be quite flexible when information about future demand is known in advance as the commercial director of D says “When we would have been informed [about the planned maintenance] in time, I could have planned not to produce those products and then this would have had much less impact”.
Overall, it becomes clear that more and early sharing of detailed, reliable, complete and good quality information related to disruptions, but also in general, leads to more visibility, velocity and flexibility and in that way improves supply chain resilience. The fact that information sources like forecasts and maintenance schedules and also company visits in daily life – not related directly to disruptions – is indicated to lead to more resilience, implies that stronger relationships (where more information is shared) help to improve resilience.
Joint relationship efforts
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product, or we can look for alternatives at other suppliers”. Hence, joint solution seeking improves flexibility and velocity.Joint relationship efforts not directly related to disruptions, e.g. product development, help to improve visibility and through that velocity as well, because companies get insights in each others processes, as explained by the account manager of C “I am involved in a lot of activities like the joint product development (…) this really helps me to get insights in what is needed at X and to respond to complaints or disruptions effective and quick”. Those insights are derived through joint solution seeking as well, leading to more visibility in what is happening in the other company and with that coming out stronger from a disruption. Next to that, joint solution seeking in terms of changing processes in both companies, or adapt the way a product is treated, may result in some flexibility in both companies.
Hence, joint relationship efforts in general lead to improved visibility, since companies get to know each other better, as case C demonstrates. This also makes it possible to have quick readiness and responsiveness for disruptions, improving velocity. Indicting a positive effect of stronger relationships, through more joint relationship activities, on resilience. Besides, joint solution seeking helps to improve velocity as it helps to improve fast response and improves flexibility in some cases where adapting processes (in both companies) help to respond better to disruptions.
Dedicated investments
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Mutual dependency
The new variable mutual dependency indicates that when companies depend more on each other, they will be more collaborative to reduce the overall impact of a disruption. The underlying reasons for this could be a common customer which is important to both buyer and supplier, supplier depending on buyer or the other way around and importance of one company to the other company. As was stated by the buyer of case D “I would communicate this directly to D, because they are highly dependent on X and in the end this will cost X a lot of money” and “They are doing this [Informing me right away], because they know how important this product is for X”. The effect of dependency is further emphasized by the account manager of C stating “Overall, this communication always is very fast and collaborative, because we together do everything to make sure that we can deliver to our common customer quickly“. Hence,
mutual dependency
is indicated to improve the degree of collaborative activities.
Years experience
The amount of years that both companies have been working together is indicated to have an impact as well. In both cases B and D, which have been working with X for 25 years already, it was stated that the suppliers know what X needs and know their processes due to the long time they are working with each other,
as mentioned by the buyer of case B “
They know from experience what X wants and helps us to develop new ideas”.
This creates more visibility in the chain as companies have more insight in each others processes, making it easy to “solve disruptions more quickly and also to see some disruptions coming in an early stage” as the supply chain analyst of B states it, so leading to improved velocity. Indicating that the longer companies are working together, the better they get to know each other and the more visibility and velocity there is, helping to create more resilience.25
4.2 Stronger relations leading to more resilience
Although the previous paragraph shows there are some clear differences across the cases in the degree of collaboration related to disruptions, both buyer and supplier in all cases emphasized that sharing complete information early on in order to generate insights in the other company’s situation and where possible working together to solve a certain problem, will help to reduce the overall impact of a disruption. When companies from this study had a stronger relationship, it turns out they have more intensive contact during disruptions and share information more timely, leading to improved velocity, flexibility and visibility, as summarized in Table 4 below (derived from Appendix E). Besides, they are more willing to engage in joint solution seeking and do more effort to reduce the overall impact of a disruption as was emphasized by the account manager of C: “when needed we may be able to take back some of the products of X, which they are not able to use anymore because of the limited shelf life and still make some money out of that for them, to limit the total impact”. While actions like this did not really come up in the interviews in case A, showing less willingness for joint solution seeking than case C. Finally, when companies have a strong relationship, they tend to engage in dedicated investments that help to increase flexibility, as the commercial director of D says “We need to be 100% reliable, therefore we did some specific investments in our machines, to make sure we can deliver at any time”. However, this last finding is demonstrated in one case only, so it is hard to say whether this goes for all companies that have very strong relationships.
Case A Case B Case C Case D
Information sharing
Not all information is shared, only what is really needed. Not proactively shared, only when issue is not solved before it starts to affect X.
Detailed information, however not all is shared and not highly proactive. Not directly shared when may be solved internally first. Directly when X needs to help in solving it. X does inform supplier fast.
Usually good quality information. However, one supplier from C did not provide complete information. Some proactive information sharing. X informs supplier quickly, supplier waits at most 24 hours. Good information from supplier, sometimes information from X is less reliable. Information is shared immediately between parties and also proactively about any possible (upcoming) disruption.
Joint relationship efforts
Not much joint solution seeking, slow handling of claim, not collaborative. Some product improvements for X.
Some joint solution seeking, when possible. Some joint product development.
Joint solution seeking done when it could be done and relatively quick handling of claims. Much joint product development.
Always try to look for solutions together. No claims due to mutual dependency. Some joint raw material decisions made.
Dedicated investments
No Not really Some, but not to
improve resilience
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Resilience per case as demonstrated in Figure 6, is based on the degree of collaboration, visibility, velocity and flexibility related to disruptions, to show which cases are overall more resilient. As this Figure shows, generally speaking the stronger the relationship between buyer and supplier, the more resilient their supply chain is. This increased resilience results from more collaboration between buyer and supplier, when there is a stronger relationship, as became clear above.
FIGURE 6: Supply chain resilience versus relationship strength
To demonstrate the effect of stronger relationships a little further, supplier A takes some time to try to solve the issue individually before informing X "(…) but when it escalates we do need to involve X in this", while supplier D informs X as soon as they see something that might lead to a disruption and tries to look for solutions together with X, in order to be able to quickly respond to and be ready for disruptions "I would inform the buyer of X right away to ensure that he has time to anticipate to this. Then we can look for possibilities to deal with this issue together with X". Those quotes demonstrate that there is more collaboration related to disruptions in case D than in case A and with that also more visibility and velocity because information is shared early on and parties are willing to solve the issue together. The same implication can be derived from comparing case B and case D. Where the supply chain analyst of B does recognize the importance of collaborating related to a disruption: “when we would contact X immediately, we could together look for a solution and X may tell us that they do not specifically need that product on short notice. (…) then we have more flexibility and more time to solve the problem internally”, they do not actually directly look for possibilities together when a disruption occurs, while in case D they do
27
immediately collaborate, leading to more visibility, velocity and flexibility. Furthermore, the account manager of C explains well how their strong relationship with X helps them to become more resilient: “I was able to find out a lot about the way X works and their production processes, because I am involved in a lot of activities like the joint product development and visit X often. This really helps me to get insights in what is needed at X and to respond to complaints or disruptions effective and quick”. Since these companies only have a 3 year relationship so far, this increased visibility and velocity really seems to result from their strong relationship or collaboration in daily life which provides some valuable new insights, indicating that stronger overall relationships do help to become more resilient.
5.
DISCUSSION
Overall, as became clear from the previous part, it turns out that stronger relationships or more collaboration related to disruptions, (indirectly) leads to a more resilient supply chain by improving visibility, velocity and flexibility. Besides, when we compare across the four cases, it becomes evident that when buyer and supplier have a stronger relationship in general, they will collaborate more in order to reduce the impact of a certain disruption as summarized in Figure 6 and Table 4 (and more detailed in Appendix E). Hence, companies engage more in information sharing, joint relationship efforts and dedicated investments when there is a stronger general relationship, resulting in more visibility, velocity and flexibility and in that way leading to more resilience. As explained in the theoretical background, this stronger relationship might be seen as similar to more buyer-supplier integration (Flynn, Huo & Zhao, 2010). The underlying mechanism, explaining how stronger relationships in the end lead to more resilience, is explained and linked to theory in more detail below.
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Daugherty et al. (2006) who state that information sharing improves velocity through reduced cycle times. However, going more in-depth we found that velocity resulting from information sharing results mainly from early sharing of good quality, complete and reliable information and having insights in the processes at the other company, leading to quick anticipation, readiness and responsiveness to disruptions. This might indicate a new interesting relationship that we did not found in literature before, namely that visibility may lead to velocity related to disruptions. This also implies some important insights in the interrelation of velocity and visibility as the underlying constructs of agility which is used as a construct of resilience in multiple studies (Christopher & Peck, 2004; Wieland & Wallenburg, 2013).
Furthermore, linking to the second collaborative activity, joint relationship efforts, Simatupang and Sridharan, (2008) found that decision synchronization improves flexibility through effective disruption responses, providing an indication that joint relationship efforts help to improve resilience. This finding was confirmed by findings from our study, where joint solution seeking leads to improved flexibility through adapting processes in (both) companies in order to respond to disruptions. Going more in-depth, joint solution seeking as well turns out to improve velocity by reducing the overall time a disruption impacts the supply chain. This is not surprising, as it seems logical that looking for a solution together overall tends to work faster than doing this on your own and in the end both companies could profit from this. As one of the main principles of supply chain management is sharing risks and rewards and trying to lower costs in the supply chain as a whole (Anderson, Britt & Favre, 2007). Adding to this, our study indicates that joint relationship efforts in general help to increase visibility and because of this increased knowledge of each others processes also help to responding faster, improving velocity.
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customer or the other way around and leads to more collaborative activities. Hence, implying a new variable that may help to improve supply chain resilience indirectly.
Another initial conclusion is that the longer companies are working together, the more visibility and velocity there is when a disruption occurs. This was not explicitly found in literature as far as we know, however it does seem a natural effect resulting from a long-term relationship. The velocity in this case again results from more visibility, as companies over the years get to know the processes of the other company and with that have the visibility in the other company that is needed in order to anticipate a disruption early on and respond to and recover from a disruption quickly.
Overall this study adds more in-depth insights on how collaboration in the form of information sharing, joint relationship efforts and dedicated investments improves resilience through visibility, velocity and flexibility, as was partly indicated in literature (Faisal et al., 2006; Daugherty et al., 2006; Wieland and Wallenburg, 2013; Chan et al., 2009). Next to this effect, the effect of buyer-supplier relationship strength on supply chain resilience became more clear, indicating that companies with stronger relations are first of all engaging more in joint solution seeking, leading to more velocity, visibility and flexibility and do more effort to reduce the overall impact of a disruption. This relation was not directly found in literature, however, it seems a logical consequence from a strong relationship. Since parties with a stronger relationship were defined to collaborate more in general, resulting from that it seems logical that they are looking for joint solutions sooner than parties with a weak relationship. Secondly, stronger relationships result in early sharing of information related to disruptions and overall more sharing of information, leading to improved visibility, velocity and flexibility. Finally, the stronger the relationship, the more dedicated investments. However, the effect of those dedicated investments is not directly clear from this study, only when the investments improve flexibility they may help to improve resilience. Besides, they may increase mutual dependency, leading to more willingness to collaborate related to disruptions.
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are positive, so for example more information sharing leads to more visibility which leads to more supply chain resilience.
FIGURE 7: Research model
6.
CONCLUSION
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resilience is build up and what the underlying constructs are, indicating that collaboration is not just a construct of resilience, but actually is an antecedent of resilience and in that way stronger relations do lead to more resilience through more collaboration.
One of the surprising findings was that the longer companies have been working together, the more resilient they become. The underlying mechanism here is that more experience with the other company improves visibility and improves velocity. Hence, for future research it is important to take into account the possible effects of this variable on resilience. Another surprising indication related to this is that velocity in a lot of cases seemed to be resulting from visibility which was based on collaboration again. Hence, a relationship between visibility and velocity may be present where more visibility in the supply chain leads to more velocity. Overall, this study implies some new and interesting insights related to the concept of supply chain resilience and the possible interrelations between its underlying constructs that should be investigated more in-depth in order to clarify the exact underlying mechanism of supply chain resilience.
Besides, this study took a broader view by investigating the effects on resilience of the supply chain between buyer and supplier and not just a single company perspective. This broader perspective helped to oversee the impact of disruptions on both buyer and supplier and how collaboration could reduce the overall impact on both companies by improving the supply chain resilience.
6.1 Managerial implications
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One implication that is important for managers as well as for theory, is that the longer companies have been working together, the more resilient they become due to increased visibility. This is especially important to consider when looking for alternative suppliers, since having the same relationship strength, but less experience with a new supplier, may lead to reduced resilience compared to a supplier which is delivering for a lot of years already.
Finally, dependency of buyer on supplier and the other way around, so mutual dependency, is indicated to improve collaboration related to disruption. So the more dependency there is, the more both parties are willing to work together to for example solve disruptions and share information in time, in that way improving visibility, velocity and flexibility, leading to a more resilient supply chain. Hence, managers should take into account the mutual dependency when building supply chain resilience.
6.2 Limitations and suggestions for future research
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