Decision Making and Global SCM
Introduction:
In this exercise, the student will analyze decision making as it applies to SCM.
Tasks:
Read case study “What Decision Making Structure is Better for the Supply Chain as a Whole” in Bowon Kim: Supply Chain Management. Answer the following questions:
2-3 pages. APA citations.
CASE STUDY: What Decision-Making Structure Is Better for the Supply Chain As a Whole?12
The impact of sharing the decision-making between a manufacturer and its supplier on their collaborative performance
Consider manufacturers and suppliers who engage in strategic relationships for quality improvement and new product development. Depending on the balance of bargaining power in the relationship, each partner’s resource commitment to activities such as quality improvement and new product development may vary. This has implications for both manufacturer and supplier profitability, shedding light on how variations in the structure of the decision-making process affect the performance of each partner in a strategic collaborative relationship. We have found that sharing the decision-making process has indeed a significant impact on the collaboration performance: an optimal outcome would have been achieved should the decision-makers have tried to maximize both partners’ profits simultaneously.
Introduction
Coordination between companies in a supply chain is regarded as vital (Stock et al. 2000, Morash and Clinton 1998).13 In fact, such coordination contributes significantly to enhancing profitability for the supply chain participants (Dyer 1997, Cachon and Lariviere 2001, Primo and Amundson 2002).14 Consider a relationship between a manufacturer and its supplier in a supply chain, which is strategic and long-term (Clark 1989, Sobrero and Roberts 2001, Ring and Van de Ven 1994).15 Then, the two supply chain partners cooperate with each other on multiple operations activities (More 1986, Maffin and Braiden 2001).16 Here we focus on coordination between a manufacturing company and its supplier on both current product’s quality improvement and new product development. By enhancing the product quality, the manufacturer will be able to sell more of the existing product on the market and thus earn more profit. In turn, the supplier can expect to become profitable as well since the manufacturer should buy more from the supplier. This is the primary motivation on the supplier’s part to coordinate with the manufacturer for quality improvement. Assuming that the relationship between the two will last for a long time, the supplier and the manufacturer would find it necessary to collaborate on developing new products for future profit generation (Clark 1989, Clark and Fujimoto 1991, Eisenhardt and Tabrizi 1994).17 An issue faced by the supplier is how to allocate its resources, available for such collaboration, between improving current operations (for quality improvement) and developing a new product in collaboration with the manufacturer. The manufacturer, likewise, will face the same question, albeit with different decision factors. Since they have to allocate their present resources between current operations and future possibility, they are facing a tradeoff decision (Sobrero and Roberts 2001).18
Figure 5.16 describes this situation. In short, the question is how to coordinate how much to spend on each of the activities over time. One would be able to answer the question by comparing the “relative profitability” of the activities, which must take into account future as well as present profit streams, uncertainty involved in the new product development, and the characteristics of the market demand.
Coordination requires joint decision-making, either explicit or implicit, between partners: the manufacturer and the supplier. As a result, the balance of bargaining power between the two decision-makers becomes an important issue (Lim 2001, Harrigan and Newman 1990, Yan and Gray 1994).19 Here sharing the decision-making process between manufacturer and supplier or setting a performance goal aligned for both partners is compatible with such an issue. For instance, should the manufacturing company dominate the coordination process, exerting stronger bargaining power vis-à-vis the supplier’s? Or should the supplier take the leading role?
“Coordination requires joint decision-making, either explicit or implicit, between partners: the manufacturer and the supplier. As a result, the balance of bargaining power between the two decision-makers becomes an important issue.”
In essence, our primary question is “How does the structure of the decision-making process (as a coordination process) affect each supply chain partner’s profitability, and thus the sustainability of the strategic supply chain relationship itself?” In this section, we consider three different types of the decision-making process structure: manufacturer-dominated, supplier-dominated, and balanced. Under the manufacturer-dominated decision-making structure, the manufacturer has complete control over the supply chain relationship. On the contrary, the supplier-dominated decision-making process sets up an objective function to take into account the supplier’s profitability only. Finally, the balanced decision-making process takes into account both supplier’s and manufacturer’s profit optimization. Which decision-making process enables the supply chain partners to achieve the best outcome? In order to answer the question, we have to look into the detailed dynamics of resource allocation by both the supplier and the manufacturer.
Figure 5.16 Influence diagram
Case company
The case company in this study is a major telecommunications company in Korea, Company S. The company has been dominating the Korean telecommunications industry. As of 2003, its market share of the Korean mobile telecom market is over 50%. Although it has been the largest player in the market, it has been also one of the most active contributors to technological innovation in the industry. For instance, it has helped the entire industry to move from analog to digital technology.
Among its many suppliers, Company S has enjoyed a strategic partnership with one major supplier for a long time. The supplier has not only been supplying key parts to the company, but also helping it to improve the quality of its product based on analog technology on the market. While Company S had been the dominant player in the analog-based telecom market, it also recognized that the dominant design in the future would be based on digital technology. Thus, when the company started developing a new product using digital technology, it realized that coordination with its major supplier was critical, particularly during the transition from analog to digital. The company needed prototype parts and materials for the new product development from the supplier. Thus, the relationship between the company and its key supplier has developed into a strategic one.
During such collaboration on both quality improvement and new product development, the company has allowed the supplier’s voice to be heard to a certain extent. The supplier was not just a passive “supplier” of parts/materials, but was allowed an active role in operations and designing activities, albeit not to a full extent. Such cooperative decision-making between the two partners has resulted in some managers in the company becoming concerned about inefficiencies in the process: they implied that excessive supplier interference with the decision-making would result in suboptimal resource allocation and lower performance. It was not an easy question, whether it is better to have the supplier participate in the decision-making process or whether such balanced decision-making would lead to better financial performance. Allowing the supplier to participate in the decision-making process is related to the balance of bargaining power between the manufacturer and the supplier in supply chain collaboration. For instance, if Company S accommodates more feedback as well as input from its supplier into its decision-making on quality improvement and new product development, the supplier’s bargaining power will increase and vice versa.
Focusing on the period of technology transition, we have developed a system dynamics simulation model that describes the dynamic interaction between the company and its supplier as accurately as possible. To develop a realistic model, we have interviewed key managers at both Company S and its supplier, and also observed their actual decision-making processes.
Technical note: Simulation rules
Resource pooling–Part of each company’s sales revenue is earmarked for quality improvement and new product development. We use 30% in our model, based on our observation that each company has earmarked 25–30% of its sales for the two activities.
Resource allocation rules–When each company allocates its earmarked resources between quality improvement and new product development, it compares the potential benefits of the two activities (Sterman 2000).20 When it makes a resource allocation decision, it estimates the marginal value of improving quality and also the marginal value of new product development effort, and compares these two values. The resources are allocated to each activity proportionally.
Quality improvement dynamics–The quality of the existing product is improved by the efforts of the manufacturer and/or the supplier. In addition, a decreasing rate of return is adopted–the quality improvement dynamic is concave.
NPD dynamics–We employ a project management routine, which is widely used in the literature (Vensim4 1999).21 The routine encompasses such dynamic equations as workflow, rework, rework discovery rate, and fraction of completion.
Market demand dynamics–Before the new product is completed, the market demand for the existing product is determined by the overall attractiveness of the existing product (Bass 1969).22 However, once the new product development is finished, the company estimates the attractiveness of the new product along with that of the existing product, and compares them to determine the relative attractiveness in order to calculate the relative demand for the two products. The attractiveness of each product is determined by two factors: quality and price (Sterman 2000).23
Pricing policy–After observing the actual data, we decided to use a decreasing pattern of price over time (Krishnan et al. 1999).24 During the early period of the PLC, the price is relatively high, but it decreases over time in order to attract more customers in the market.
Learning effects and production cost dynamics–The variable cost to produce the new product, as well as the existing one, is affected by the learning curve effect. We use a 5% learning rate for both the companies.
Model verification and simulation
The first step in our simulation is to calibrate, or verify, our model against the real-world data in order to see whether our model is realistic in the sense that it is capable of replicating what happened in the market reasonably well. Figure 5.17 shows the result of such calibration, using the actual sales data from the company. It shows that our simulation model is good enough to describe what actually has happened in the market.
Figure 5.17 Model verification
Note: “Actual–current product” is plotting actual sales data for the existing product, and “Actual–new product” is actual sales data for the new product. The other two curves result from the calibration. We calibrated our simulation model against the actual data points and plotted the endogenously generated sales figures for the two products. These “endogenously generated” sales are plotted alongside the actual data. “Calibrated–current product” is the plot of “endogenously generated sales for the existing product,” while “Calibrated–new product” is plotting “endogenously generated sales for the new product.” The fit between the actual sales data and the calibrated data, i.e., R2, is about 0.97, which indicates that the simulation model does describe the real case quite accurately–realistically enough to conduct the next step analysis, or what-if analysis.
Before proceeding to the what-if analysis, we discuss some of the key outcomes from the calibration. Figure 5.18 shows the profits of the calibrated dynamics: the manufacturer enjoys more cumulative profit than the supplier does. In fact, the supplier’s cumulative profit picks up only after the new product was successfully developed in the 97th month. On the contrary, the manufacturer (Company S) has enjoyed a significant level (vis-à-vis the supplier) of cumulative profit from the very beginning. We contend that given the case setting, the manufacturer was able to earn a significant portion of profit from quality improvement of the existing product early on and also from the new product as well, whereas the supplier was getting more profit from the new product development rather than the quality improvement activity.
Figure 5.18 Cumulative profits–Calibrated estimates
The what-if analysis
Our primary objective is to determine how variations in the structure of the decision-making process affect the collaborative performance. Three types of decision-making process structures are considered: manufacturer-dominated, supplier-dominated, and balanced. We have varied the weight structure of the objective function to represent the three types and estimated the profits by utilizing the optimization function in the system dynamics simulation; that is, (1) for the manufacturer-dominated case, we use an objective function to maximize only the manufacturer’s cumulative profit at the end of the decision time horizon (denoted as 1:0); (2) the supplier-dominated case, denoted as 0:1, where the objective function is to maximize the supplier’s profit only; and (3) for the balanced case, denoted as 1:1, the objective function is to maximize the sum of the profits for both the supplier and the manufacturer at the same time.
Figure 5.19 shows the manufacturer’s cumulative profits for the three different scenarios: the cumulative profit is maximal when the objective function is to optimize the manufacturer’s profit only. The cumulative profit is minimal when the objective function takes into account the supplier’s objective function only. We can make similar arguments from the supplier’s perspective in Figure 5.20. One striking observation is that the supplier’s cumulative profit becomes increasingly negative when its profit objective is not reflected in the decision-making process at all–when the manufacturer makes the decision to its own advantage at the expense of the supplier’s.
Figure 5.19 Manufacturer’s profits as decision-making sharing changes
Figure 5.20 Supplier’s profits as decision-making sharing changes
Figure 5.21 shows the total profit dynamics for the three decision-sharing scenarios. Possibly except for a very short period of time, throughout the decision time horizon, the balanced decision-making process (or 1:1 arrangement) produces the largest total profit.
We summarize the results in Table 5.11. From the manufacturer’s own profit perspective, the best is the “manufacturer-dominated decision process,” whereas the best is the “supplier-dominated decision process” from the supplier’s perspective. The critical question is if either of the dominated cases would be sustainable in the long run. A short answer to the question is “no.” The second column (“estimated actual”) of Table 5.11 represents the actual profits they would have earned, given the present market conditions–the calibrated profits that are the profits the supply chain partners are supposed to earn without deliberately influencing the decision-making balance.
Figure 5.21 Total profits as decision-making sharing changes
Table 5.11 Summary of changes in profits
* DMS–Decision-making sharing.
**MM–million in relative scale.
To the manufacturer, the best is to make a decision on its own, wielding 100% of bargaining power during the decision-making process; that is, the manufacturer-dominated case. But, this is not acceptable to the supplier: should the supplier accept the deal, its cumulative profit would have changed from 119 million to–58 million in relative scale. Should the supplier wield 100% bargaining power during the decision-making process, the manufacturer’s profit would have changed from 210 million to 37 million. Again, it is not an acceptable deal to the manufacturer.
Finally, the only alternative to the “estimated actual” case is the balanced decision process. Not only is the total profit the largest among the four scenarios, but also the individual player’s profit becomes larger. The manufacturer’s profit increases from 210 MM to 233 MM, while the supplier’s from 119 MM to 121 MM. Thus, the balanced decision process satisfies two fundamental conditions for sustainable coordination in SCM: (1) system-level optimization–the total profit after coordination should be larger than that before such coordination, and (2) distributive justice at the individual level–each participant’s profit should be larger than or at least equal to that before such coordination (Kim 2000).25
We can apply the concept of “bargaining zone” to the period after about the 110th month in Figure 5.21. After this month, the profitability of the balanced decision process surpasses the others’. Should the decision time horizon be longer than 110 months, the manufacturer and the supplier could find the balanced decision process more attractive than when either one dominates the decision process completely. Therefore, there is room for them to bargain with each other to strike a mutually beneficial and acceptable arrangement in sharing the decision-making process.
Conclusions
In effect, the result indicates that the balanced decision-making process engenders the best outcome, which is sustainable and acceptable to both players in the supply chain. It implies that a decision-making process dominated by one party in the supply chain couldn’t be sustainable–such an arrangement can’t be acceptable to other parties in the long run. In a more practical sense, for example, a decision process dominated by the manufacturer (supplier) without taking into account the supplier’s (manufacturer’s) profitability might eventually cause the manufacturer’s (supplier’s) own profitability to be reduced significantly. It is based on our observation that when the manufacturer has full power to make resource allocation decisions over not only its own resources, but also the supplier’s, it would usually use supplier’s resources first before using its own resources, and thus either waste some of the supplier’s resources or use them for non-value-creating activities. All these combined would cause inefficiency to the supply chain as a whole. Our conclusion is that collaborated decision-making in the supply chain creates more value at the system level–from the entire supply chain’s perspective. How to share the additional value created through such collaboration remains a very important research issue, which deserves further empirical, as well as theoretical, research in the future.
Reference:
(Kim 271)
Kim, Bowon. Supply Chain Management in the Mastering Business in Asia series. John Wiley & Sons (P&T), 10/21/05.
