Case Article—ReCellular Inc: Managing Demand Uncertainty in Closed-Loop Remanufacturing

1. Introduction

This case study is based on a five-year-long collaboration with ReCellular, a third-party remanufacturer (3PR) in the closed-loop supply chain industry, and the challenges that small to midsized firms face to be successful in this industry. Specifically, this case study focuses on cellphone remanufacturing. New phones are manufactured by original equipment manufacturers (OEMs) such as Apple and Samsung for carriers such as Verizon and AT&T. The carriers sell these phones to end users. These two transactions constitute the forward supply chain. The reverse supply chain starts when the end user decides to replace his or her existing phone. Typically, the end user will visit his or her carrier who will make a trade-in offer in which the customer will obtain a new phone when he or she returns the old phone plus some credit toward the cost of the new phone. The carriers sell these returned (used) phones to consolidators or brokers such as Gazelle. Consolidators collect used phones from multiple streams (e.g., carriers) and then sell them to 3PRs such as ReCellular. The third-party remanufacturers are named thus, because they are neither the OEM nor the carrier. The 3PRs remanufacture the used phones and then sell them in the marketplace. In many cases, their customers are firms that buy remanufactured phones to equip their workforce. In some other instances, their customers are internet-based sellers that sell individual phones to end users. Figure 1 shows these forward and reverse supply chains of cellphones (adapted from Mutha et al. 2016, 2019).

The business model of 3PRs is of interest for several reasons. There are more than 10,000 remanufacturing firms in the United States with a total annual turnover of $5 billion and employing more than 25,000 workers. Second, 3PRs are an essential part of the closed-loop supply chain business model. Without their presence, there is no clear path for used devices to find a second use cycle on a wide scale, especially for products that are not collected back and remanufactured by OEMs. Third, from a pedagogical perspective, their business model is uniquely complex. The 3PRs face the dual challenge of matching supply with demand under thin margins. Unlike OEMs, 3PRs depend on end users for the supply of used products and on large business customers for the demand of remanufactured products. The supply of used cellphones for the consolidators, and from them to the 3PRs, tends to wax and wane depending on the release of new phone models. The demand for remanufactured phones tends to be episodic, because large customer-firms purchase phones for their workforce only periodically. The 3PRs need to be in tune with both their customers who place a large order but for specific types of remanufactured phones as well as the market to understand the available and potential supply of used phones by consolidators. In many other domains, one way in which firms are able to match supply with demand is by maintaining a healthy inventory. Unfortunately, this strategy is not always feasible for a 3PR in closed-loop supply chains. Used consumer electronic products such as cellphones lose their value quickly, by some estimates by as much as 15% per month. When compared with the prevalent profit margin in the remanufacturing industry (∼20%), this loss of value is significant. As a result, acquisition of used products for remanufacturing is an important decision for 3PRs.

One of the ways in which the remanufacturing industry has evolved to assist 3PRs is that the consolidators collect used products from end users, sort them into different grades based on their quality condition, and offer these grades to the 3PRs. Figure 1 shows these grades as “High,” “Medium,” and “Low” for ReCellular. High grade means that the phone was used gently by its owner and the 3PR will only need to do minimal amount of work on the phone to bring it to a like-new condition before sale. The low grade means that the phone has undergone rough usage and may have some broken parts that need to be replaced before its sale. The medium-condition phones require an intermediate level of remanufacturing work. High-grade phones are the costliest to acquire for the 3PR, followed by medium and low (see Table 1 for a numerical illustration that we revisit in detail later). The 3PR restores all phones to the same like-new standard during remanufacturing. The 3PRs in this industry are able to optimize their operations by buying used products in specific grade(s) in specific number(s) before observing the demand and then remanufacturing them after receiving a firm order from the customer, consistent with a make-to-order regime. Essentially, a 3PR must order the inventory of used phones in anticipation of demand from a large customer (with a range of possible order quantities available from the customer with prior experience) and will remanufacture this inventory after observing the demand.

Table 1. Cost Parameters for Each Grade

Because of these unique features, the analytical tools developed to manage traditional manufacturing operations need to be customized to the remanufacturing business. Industry evidence shows that ignoring these contextual details and simply adopting solutions from other domains for similar problems can be catastrophic (Ferguson 2010). ReCellular was a profitable 3PR until 2002 when it was acquired by a business consortium. The consortium replaced several personnel with experienced managers from the retail industry. Nevertheless, within six months, the firm was in a loss and was shut down two years later. A business-biopsy since then has revealed that a major reason for this failure was that the inventory solutions adopted in the retail industry based on relatively low decline in good’s value are not directly applicable to the remanufacturing of consumer electronic devices that have a high rate of obsolescence, as noted earlier Ferguson (2010).

The case focuses on the development of a decision support tool to help the 3PR determine the best inventory decision under uncertain demand, in anticipation of a one-time order. The remanufacturing is carried out after receiving the order. As shown in Table 1, on one hand, buying used products in the high grade maximizes the per-unit profit for the 3PR. On the other hand, the used products in the low grade require the lowest up-front investment in inventory. The medium-grade products have an intermediate up-front cost as well as margin when sold. The case requires a careful analysis of these trade-offs for the three grades. The rest of the article is organized as follows. Section 2 contains a review of related prior academic literature. In Section 3, we discuss the teaching plan for the case. In Section 4, we discuss classroom experience and conclude in Section 5.

2. Literature

The challenges introduced by the variation in the quality of used products for closed-loop supply chains are well known. A number of academic articles have studied various aspects of managing this variation, and this area of research has evolved with industry practices. Galbreth and Blackburn (2006, 2010) and Guide et al. (2003) study a setting in which a 3PR buys used products with a known variation in their quality. The 3PR first determines the lowest quality of used products that it intends to remanufacture. In sight of this decision, the 3PR seeks to determine the optimal quantity of used products to purchase from a consolidator. Guide et al. (2003) study a slightly different setting in which the consolidator classifies the used products in multiple quality buckets or grades and then sell these grades to remanufacturers. Ferguson et al. (2009) find that for most practical settings, used products should be sorted into four to six grades. Drake et al. (2012) discuss the remanufacturing problem in a newsvendor setting. Mutha et al. (2016) consider a setting where the 3PR acquires used products in different grades and study the optimal acquisition decision for the 3PR for these grades. This focus is consistent with the case study.

On the solution aspect, Mutha et al. (2016) note that the presence of multiple grades adds managerial complexity to decision making. At first glance, the problem is similar to the newsvendor problem in which a firm orders inventory under uncertain demand. However, many differences in the two settings are also salient. In the newsvendor context, a firm considers only one type of inventory, whereas in the remanufacturing context, the 3PR has the option of ordering inventory in different grades, each with a different profit margin. Furthermore, in the traditional newsvendor model, the per-unit cost incurred by the firm at the time of acquisition is the only cost incurred by the firm. Whereas, in the closed-loop context, the 3PR first incurs the acquisition cost at the time of acquiring inventory and then a subsequent remanufacturing cost if he or she chooses to remanufacture a specific unit. Because of these intricacies, it is not clear whether the newsvendor solution can be directly applied (and how) to the remanufacturing domain. Mutha et al. (2016) use marginal analysis to inform the 3PR’s decision. They use the intuition that the 3PR should choose a unit in the grade that provides the highest marginal benefit.

Although this body of work provides an academic analysis of the problem, our focus via the case is to present the problem in a more accessible fashion in order to train practitioners. The case also focuses on the importance of contextual details, such as the timing of acquisition and remanufacturing costs in closed-loop supply chains, in solving industry problems. The academic solution based on marginal analysis can be somewhat challenging; to that end, the case is also a vehicle to show how scenario-based numerical optimization (stochastic programming) can be used by managers within a spreadsheet environment for decision making. In advanced classes, both methods can be discussed as well.

3. Teaching Plan

3.1. Salient Features and Questions

The intended audience for this case comprises MBA and undergraduate students enrolled in modeling-focused courses. The case addresses production planning under demand uncertainty and is therefore suited to students majoring in supply chain or operations management. The remanufacturing context also makes this case study useful for courses focused on sustainability. A knowledge of Excel Solver is necessary to solve the case.

The case has two salient features of the remanufacturing industry: (i) the focus on availability of multiple grades of used phones and (ii) the role of two costs—acquisition and remanufacturing cost and their timing—on a 3PR’s operations. The case questions focus on these two features. The questions are as follows:

1. Draw a timeline for the decisions to be made by ReCellular and the cash flows associated with these decisions. Which grade is most profitable? Which is least profitable?

2. For the data provided in Table 1, what inventory positions would you recommend for ReCellular? Why? What is the corresponding expected profit? Consider that demand for remanufactured cellphones follows a normal distribution with a mean of 1,000 and standard deviation of 250 units.

The second question can be framed in other ways as well, as discussed in the teaching note.

3.2. Teaching Plan

We typically ask students to read the case before class and come to the class prepared with two items: (i) a timeline for the decisions and cash flows and (ii) a recommendation for which grade(s) of used phones to buy and the quantity (or quantities) to purchase along with an explanation for their recommendation.

In our experience, this preclass preparation is helpful in several ways. Some students recognize the similarity of the problem to the classical newsvendor problem. If they recall the critical fractile formula for the newsvendor problem, they try to use the formula in order to come up with a recommendation. But almost in all cases, students recognize that the presence of multiple grades leads to no direct way to apply the newsvendor formula. This recognition is important, both from a modeling perspective as well as for a domain-driven understanding of closed-loop supply chain problems. On the modeling side, this hurdle conveys the message that many business situations may require development of a new mathematical model. On the context side, this hurdle underscores that the need for new models is sometimes driven by industry-specific factors and that, as prospective managers, they should ensure that the model is a faithful representation (though with limitations) of the business situation. In most cases, students arrive with a numerical recommendation for the grade and quantity of used phones to buy, along with some justification.

We start the classroom discussion by asking students to share their recommendations. These recommendations differ, with some students recommending that the 3PR buy inventory in only one grade, whereas some others suggest that it would be prudent to buy inventory in multiple grades. This tension in opinions and the rationales provided by the students brings to fore the value of drawing the timeline for the decisions and cash flows for the business situation. Individual students typically suggest the following two timelines. In the first suggested timeline, the two costs are staggered in time. The acquisition cost is incurred before seeing the demand; the remanufacturing cost is incurred after observing the demand, coinciding with revenue collection. In the second suggested timeline, both costs are lumped together and separate from the revenue realization to determine the margin on the product. Figure 2 shows these two timelines. The differences in these two timelines help underscore the importance of using figures such as a decision timeline to improve the understanding of the business problem at hand as well as a useful peg for brainstorming and reaching consensus on assumptions of business processes that a subsequent model should capture.

After this discussion, we set up a model in Excel with three decision variables that correspond to the quantities of used products in the three grades and a number of scenarios of demand. For standard demand distributions such as the Normal distribution, these scenarios can be generated in Excel. For each scenario, we determine the remanufacturing cost based on the demand and the inventory of the three grades. Subsequently, the average profit from all scenarios can be optimized using Excel Solver. Although the formulation does have kinks in the expected value calculation, the nonlinear optimization routine is usually able to navigate to the optimal solution for the three-variable problem. One can also use Excel add-ins such as @RISK for this optimization. This setup also provides a distribution of the profit, which can be used to analyze the trade-offs between the expected profit with a set of inventory levels and risk measures, such as standard deviation of profit, probability of loss, or others.

The discussion usually concludes with three items. First, we revisit the recommendations provided by the students in the beginning of the session. We input these values in the model developed in the class to see how they would perform in comparison with the optimal solution. Interestingly, the improvement provided by the model stems from two sources: from using different grade(s) than they selected and buying inventory in a different quantity than recommended initially. Second, we discuss the practices at ReCellular that enabled it to operate near the solution provided by the model, as reported in Ferguson (2010) and Guide et al. (2003). Finally, we encourage students to identify other business situations that face a similar procurement problem involving raw material in different quality grades. Students identify many industry sectors where semifinished inventories are bought by firms with the intention of finishing them after observing the demand. We also use this opportunity to discuss differences between make-to-order and make-to-stock systems and backup orders.

4. Classroom Experience and Observations

We have used the case for over three years in an MBA classroom and an executive program. As discussed above, we ask students to study the case before the class and then come to class ready with a recommendation and its justification. Two themes were salient in these initial responses. First, nearly 65% of students consistently choose to order inventory in the high grade only. The most common rationale for this choice is, “High grade has the highest margin of $40, so that’s what we should do.” Some other students noted that the low grade reduces risk and that high grade is most profitable; but in the absence of a clear idea about how to split their order, they preferred to order units only from the high grade. A representative comment for this thought process is, “I know I should diversify, but how? The newsvendor formula doesn’t quite apply. I think I will just take my chances with the high grade.”

Approximately 20% of the students choose to acquire units only in the low grade, citing risk concerns. About 15% of the students choose to diversify their portfolio and order inventory in more than one grade. The combination of high and low is the most popular combination, with the rationale that “it helps me balance the high margin on high with the low risk of low.” These observations in the classroom are consistent with the observations made in Sabbaghi et al. (2020) using data obtained from managers in the remanufacturing industry. These differences in responses lead to robust discussions in the classroom.

Second, by mapping the recommendations into the time lines provided by the students, we found that students who provided the Net Margin¹ approach to decision making almost always chose to acquire used products only in the high grade. In contrast, more than half of the students who provided the staggered approach to decision making suggested to buy used products in high and low grades. This difference suggests that in business situations where contextual details are central to cash flows, drawing figures to represent business processes with associated cash flows can be a powerful tool for improving decision making, especially in group decision-making settings.

5. Concluding Remarks

This case introduces students to some unique issues in closed-loop supply chains, with a focus on the variability in the condition of used products and their classification into various quality grades that serve as the input material for the remanufacturing process. The mathematical modeling focus is on appreciating the importance of developing a mathematical model that incorporates the availability of different grades of used products at different prices. Overall, the case works well as a teaching instrument in mathematical modeling classes. For supply chain majors, the case provides a natural extension of the classical newsvendor problem; yet it also acts as a caution against trying to use the newsvendor model (or any other off-the-shelf model) in a business context without validating its fit to the context at hand.