Kamalini Ramdas

Chain or Shackles: Understanding What Drives Supply-Chain Performance

We relate an array of factors that embody current practice and thinking in supply-chain management with supply-chain performance. We measured supply-chain performance using a set of variables that capture the impact of supply-chain management on systemwide revenues and costs. We classified supply chains based on the products they support as inherently functional or inherently innovative. They differ in practices used and thinking. High performers among innovative-product supply chains use practices that enhance revenues more than high performers among functional product supply chains. They are more likely to engage in supply-chain management to enhance revenues. Finally, we found that the practices and reasons for engaging in supply-chain management that distinguish high performers from low performers are different for functional-and innovative-product supply chains.

A Cross-Functional Approach to Evaluating Multiple Line Extensions for Assembled Products

Assembled product manufacturers often introduce line extensions that share components with existing products, or among themselves, resulting in cost interactions among products because of shared costs, and revenue interactions because of cannibalization. We present a cross-functional approach to evaluating multiple line extensions that simultaneously considers revenue implications of component sharing at the product level and cost implications at the component level. We develop a source-of-volume model and a measurement procedure to decompose the life-cycle sales volume from a line extension into sales from cannibalization, competitive draw, and demand expansion. We develop an activity-based costing procedure for estimating the life-cycle costs of line extensions that share components. We develop an optimization model that uses these revenue and cost estimates to identify a subset of line extensions that maximizes incremental profits. We implement our approach at a quartz wristwatch manufacturer. Results suggest that our approach would have improved profits for the firm by over 5%, while actually launching fewer line extensions. We also find that the drivers of cannibalization are counterintuitive. In simulation studies, our approach outperforms three managerial heuristics. We demonstrate that this approach is most valuable when cannibalization dominates competitive draw as a source of volume, and discuss its relative merits under low and high parts-sharing.

Ending Inventory Valuation in Multiperiod Production Scheduling

When making lot-sizing decisions, managers often use a model horizon T that is much smaller than any reasonable estimate of the firms future horizon. This is done because forecast accuracy deteriorates rapidly for longer horizons, while computational burden increases. However, what is optimal over the short horizon may be suboptimal over the long run, resulting in errors known as end-effects. A common end-effect in lot-sizing models is to set end-of-horizon inventory to zero. This policy can result in excessive setup costs or stock-outs in the long run. We present a method to mitigate end-effects in lot sizing by including a valuation term VIT for end-of-horizon inventory IT, in the objective function of the short-horizon model. We develop this concept within the classical EOQ modeling framework, and then apply it to the dynamic lot-sizing problem DLSP. If demand in each period of the DLSP equals the long-run average demand rate, then our procedure induces an optimal ordering policy over the short horizon that coincides with the long-run optimal ordering policy. We test our procedure empirically against the Wagner-Whitin algorithm and the Silver Meal heuristic, under several demand patterns, within a rolling horizon framework. With few exceptions, our approach significantly outperforms the other approaches tested, for modest to long model horizons. We discuss applicability to more general lot-sizing problems.

Does Component Sharing Help or Hurt Reliability? An Empirical Study in the Automotive Industry

Component sharing---the use of a component on multiple products within a firms product line---is widely practiced as a means of offering high variety at low cost. Although many researchers have examined trade-offs involved in component sharing, little research has focused on the impact of component sharing on quality. In this paper, we examine how component sharing impacts one dimension of quality---reliability---defined as mean time to failure. Design considerations suggest that a component designed uniquely for a product will result in higher reliability due to the better fit of the component within the architecture of the product. On the other hand, the learning curve literature suggests that greater experience with a component can improve conformance quality, and can increase reliability via learning from end-user feedback. The engineering literature suggests that improved conformance in turn increases reliability. Sharing a component across multiple products increases experience, and hence, should increase reliability. Using data from the automotive industry, we find support for the hypothesis that higher component reliability is associated with higher cumulative experience with a component. Further, we find support for the hypothesis that higher component reliability is associated with a component that has been designed uniquely for a product. This finding suggests that the popular design strategy of component sharing can in some cases compromise product quality, via reduced reliability.

Can Financial Markets Inform Operational Improvement Efforts? Evidence from the Airline Industry

We investigate whether stock price movements can inform operations managers as to where they should focus improvement efforts. We examine how unexpected performance along several dimensions of service quality---on-time performance, long delays and cancellations, lost bags, and denied boardings---impacts contemporaneous stock returns. Prior research suggests that airlines buffer their flight schedules and engage in expensive employee incentive programs to increase the likelihood of on-time arrival. We find that only long delays are penalized by the market, and we identify a number of carrier-specific factors that alter the financial impact of long delays. We find that the penalty a carrier faces for long delays is significantly higher if it operates a high percentage of short-haul or connecting flights, or if its competitors incur fewer long delays in the same time period. Our findings suggest that developing ways to curtail long delays is a useful future research area.

Is IT enough? Evidence from a natural experiment in India's agriculture markets

Access to information and communication technologies (ICTs) such as mobile phone networks is widely known to improve market efficiency. In this paper, we examine whether access to timely and accurate information provided through ICT applications has any additional impact. Using a detailed data set from Reuters Market Light (RML), a text message service in India that provides daily price information to market participants, we find that this information reduces the geographic price dispersion of crops in rural communities by an average of 12%, over and above access to mobile phone technology and other means of communication. To identify the effect of information on price dispersion, we exploit a natural experiment where bulk text messages were banned unexpectedly across India for 12 days in 2010. We find that besides reducing geographic price dispersion, RML also increases the rate at which prices converge across India over time. We discuss the implications of this for development organizations and information providers. This paper was accepted by Lorin Hitt, information systems .

Adopting innovations in care delivery - the case of shared medical appointments

Shared medical appointments can improve outcomes and patient satisfaction while dramatically reducing waiting times and costs. Accelerating their adoption will require experimenting with delivery models and finding strategies for getting patients and providers on board.

Robust Scheduling Practices in the U.S. Airline Industry: Costs, Returns, and Inefficiencies.

Airlines use robust scheduling to mitigate the impact of unforeseeable disruptions on profits. We examine how effectively three common practices—flexibility to swap aircraft, flexibility to reassign gates, and scheduled aircraft downtime—accomplish this goal. We first estimate a multiple-input, multiple-outcome production frontier, which defines the attainable set of outcomes from given inputs. We then recover unobserved input costs and calculate how expenditure on inputs affects outcomes and revenues. We find that the per-dollar return from expenditure on gates, or more effective management of existing gate capacity, is three times larger than the per-dollar returns from other inputs. Next, we use the estimated trade-offs faced by carriers along the frontier to measure the value to carriers of reducing delays. Finally, we calculate the improvement in carriers’ outcomes and profits if their operational inefficiencies are eliminated. On average, we estimate that operational inefficiencies cost carriers about

A Methodology to Support Product-Differentiation Decisions

1.7 billion in revenue annually. This paper was accepted by Serguei Netessine, operations management .

Learning from Many: Partner Diversity and Team Familiarity in Fluid Teams

Choosing the right set of new products to offer is a key driver of profitability. New products often share some design attributes with existing products, thus, firms need to decide which attributes to keep common and which to differentiate. We propose and empirically implement a new methodology that can help managers to navigate the complex decision of where to focus differentiation, using “looks-like” prototypes that typically become available in the later stages of the product-development process. Our methodology complements early stage product-positioning methods, such as conjoint analysis and perceptual mapping. It also offers a way to estimate the impact of context dependence on choice. Finally, our methodology provides a way to test empirically whether perceptual mapping based on pairwise similarity judgments is appropriate for a product category. Using data obtained from a major wristwatch manufacturer, we are able to suggest guidelines on how to differentiate the firms offerings and estimate the magnitude of context dependent effects. We also find that for wristwatches, attributes that drive perceptions differ from those that drive choice. Overall, our approach can help avoid falling into the trap of focusing variety on attributes that are costly to differentiate and have little impact on choice.