Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 191-194). / The problem of optimally distributing new products is common to many companies and industries. This thesis describes how this challenge was addressed at Zara, a leading retailer in the "fast fashion" industry. The thesis discusses the development and evaluation of a modular system including distributional demand forecasting and dynamic programming distribution optimization. The demand forecasting module combined the practice of using similar products to predict the demand of a new product with a new store or customer cluster data aggregation scheme. Moreover, distributional forecasts were generated using a generic distribution of the expected relative forecast error constructed based on historical forecast performance. Finally, an empirical study of expert or qualitative forecasting within Zara was performed to evaluate the potential for forecast improvement. The distribution optimization module leveraged the distributional forecasts and dynamic programming to determine the optimal initial shipment quantities. The dynamic program directly accounted for the inventory constraints as well as the information dynamics that result from the improvement in forecast accuracy after initial sales are observed. The complete system was validated using extensive simulation. Overall, the new demand forecast reduced forecasting error by over 30% and the final simulation results showed that the overall system would be expected to improve initial sales by over 12%. Given Zara's scale, these results would translate to hundreds of millions in additional profit. Thus, a live pilot was approved and initiated by Zara with the goal of confirming the simulated impact of the system under real conditions. Assuming a successful pilot, full system implementation is expected in 2011. / by Andres Garro. / S.M. / M.B.A.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2010. / Title-page reads "Master of Science in Management."-- Student received an M.B.A per June 2010 Degree List, Office of the Registrar, MIT. Cataloged from PDF version of thesis. / Includes bibliographical references (p. 87-89). / Acquisitions are costly, even the ones that never happen. They require a significant commitment of resources involving multi-disciplinary teams examining all aspects of a business. This can come at a significant cost if either the acquisition does not produce the value that was originally expected or if the acquisition process is aborted all together. Clearly, it is critical to be confident in the initial selection, when investing capital and resources to carry out the lengthy investigation process. However, while there is exhaustive research on the detailed evaluation of a target, there is very little published about the preliminary selection process. In this thesis, we demonstrate a methodology for acquisition target selection. We propose a method of metric-based ranking of targets for criteria defined in 3 dimensions. The first is a measure of how a target meets the Strategic Goals of the acquiring company. This is critical not only to measure a target, but to clarify and create alignment among the leadership of the company for the purpose of the acquisition. The second dimension is a measure of Acquisition Fit. This represents a rough measure of likelihood of integration success of a target. The metrics in this dimension are based on research into attributes of acquisition failures. The final dimension is a Financial Impact measure, which represents a rough business case for the acquisition. In the second half of this thesis, we introduce a case study of this methodology being applied in the large commercial aircraft (LCA) industry at Spirit AeroSystems, Inc. This case study demonstrates the application of this methodology with the necessary industry analysis, internal and external technology evaluation and implementation challenges. During this case study, the LCA industry is undergoing a period of technological disruption and re-distribution of engineering responsibilities. These shifts in the industry structure require additional rigor in evaluation of technological and engineering needs and capabilities. Experience is statistically a strong indicator of success in M&A. We hope to lower the learning curve costs and associated risk by capturing research of best practices in a manageable process for M&A target selection. / by Michael Tajima. / M.B.A. / S.M.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 75-78). / Strategic Managed Inventory (SMI) is an inventory replenishment process deployed by Caterpillar that blends elements of Vendor Managed Inventory (VMI) and Collaborative Planning, Forecasting, and Replenishment (CPFR). The SMI process calls for Caterpillar's suppliers to control the material replenishment process and hold inventory in strategic locations. SMI is designed such that Caterpillar and the supplier collaborate on replenishment plans and forecasts to ensure that material moves efficiently through the supply chain. The process is aimed at increasing supply chain flexibility, responsiveness and performance. This paper examines the current deployment of the SMI process in Caterpillar's supply chain in an effort to determine how the company can go about better leveraging this capability. It proposes potential frameworks for the identification of future SMI opportunities and part suitability. It also looks at the drivers behind SMI in cost evaluation. While there are some challenges identified with the process by the study, the study concludes that the SMI process does lead to benefits for Caterpillar and its suppliers. It suggests that these benefits could be better leveraged by growing the capability slowly using the most proficient suppliers, establishing oversight for the SMI process, increasing supplier vetting, and crafting a way to gain visibility into current SMI usage. / by Brandon Rowan. / S.M. / M.B.A.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 79-80). / The problem of optimally purchasing new products is common to many companies and industries. This thesis describes how this challenge was addressed at Zara, a leading retailer in the "fast fashion" industry. This thesis discusses the development of a methodology to optimize the purchasing process for seasonal, short life-cycle articles. The methodology includes a process to develop a point forecast of demand of new articles, the top-down forecast at the color and size level and an optimization module to produce recommendations to define the optimal quantity to purchase and the optimal origin to source from. This thesis is the first phase of a two phases purchasing optimization process. The focus of this thesis is: a) the outline of an enhanced purchasing methodology b) the development of the most important input in the system: a point forecast of demand at the article, color, and size level, and c) the development of an IT prototype to automatically manage the purchasing methodology. The second phase of the purchasing optimization process focuses on the optimization module. The optimization module is beyond the reach of this thesis. / by Tatiana Bonnefoi. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / 8 / Cataloged from PDF version of thesis. / Includes bibliographical references (page 69). / The mission of the Always Available retail replenishment business at NIKE is to ensure consumer-essential products are in-stock at retailers at all times. To achieve this goal, NIKE has developed a forecast-driven, make-to-stock supply chain model which allows retailers to place weekly orders to an on-hand inventory position in a distribution center. The challenge facing the business is how to design an inventory strategy that achieves a high level of service to its customers while minimizing inventory holding cost. Specifically, safety stock holding cost is targeted as it accounts for the majority of on-hand inventory and can be reduced without significantly impacting the underlying supply chain architecture. This thesis outlines the application of multi-echelon inventory optimization in a retail replenishment business model. This technique is used to determine where and how much safety stock should be staged throughout the supply chain in order to minimize safety stock holding cost for a fixed service level. Provided a static supply chain network, the ideal safety stock locations and quantities which result in minimal total safety stock holding cost is determined. For this business, the optimal solution is to stage lower-cost component materials with long supplier lead times and high commonality across multiple finished goods at the manufacturer in addition to finished goods at the distribution centers. Safety stock holding cost reduction from component staging increases significantly when the distance between manufacturers and the distribution center decreases and for those factories producing a variety of finished goods made from the same component materials due to inventory pooling. Forecast accuracy drives the quantity of safety stock in the network. The removal of low volume, highly unpredictable products from the portfolio yields significant inventory holding cost savings without a detrimental impact to revenue. By deploying the optimal safety stock staging solution and by removing unpredictable products, this analysis shows that finish goods safety stock inventory would be reduced by 35% for the modeling period (calendar year 2012) while only decreasing topline revenue by 5%. / by Benjamin M. Polak. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 72). / Amazon is one of the world's largest retailers with revenues of $74.5 billion in 2013 and 22% growth over 2012. As Amazon continues to grow and offer greater selection, more products are flowing through an expanding inbound network. While this growth has added complexity for the inbound transportation organization, it has also created opportunities to reduce transportation cost and improve performance. Inbound transportation managed by Amazon currently represents 60% of the company's inbound freight. For this freight, Amazon uses automated shipment-planning systems to select a carrier for all shipments. The systems run once per day, selecting carriers for a set of shipment requests where each vendor has specified a freight ready date of tomorrow. Several inputs are included to achieve a low transportation cost for the network, but the systems are constrained by the vendor's freight ready date. By introducing dynamic pickup windows based on when the freight is needed in the fulfillment centers (FCs), Amazon has the opportunity to reduce transportation cost and mitigate out-of-stock occurrences. A current state analysis revealed that approximately 70% of Amazon's freight was shipped through expensive less-than-truckload and small-parcel methods. While truckload shipments are ideal in transportation, ordering smaller lots more frequently is preferable to maintain high in-stock levels in the FCs while keeping inventory holding costs low. Therefore, Amazon's shipment-planning systems minimize transportation cost by building multi-stop routes to pick up smaller shipments from several vendors before delivering to the FC. The dynamic pickup window solution changes the planning process by relaxing the constraint of tendering a shipment today to a high cost transportation mode if that freight does not need to ship today. If shipment requests are not tendered today and instead sent to tomorrow's pool of requests, two types of consolidation can occur: (1) a single-vendor consolidation and (2) a multi-vendor consolidation. A model was developed to simulate shipment planning on the entire network for one week, resulting in a 2% transportation cost reduction and 4% fewer shipments while protecting in-stock levels. Amazon piloted in late 2013 with success and plans to implement throughout the network in early 2014. While the dynamic pickup window solution is presented with Amazon as the case study, the solution is applicable to any business with stochastic demand and lead time, a large vendor base, and control of managing its inbound transportation. / by Charles R Cummings, III. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 68-69). / Effective execution and alignment of data management across development and manufacturing teams is essential for Amgen's Drug Product Technology group to realize its main goals of shortening the development timeline and ensuring robust commercial manufacturing. The right data management strategy can help address these goals by accelerating development work and regulatory filing as well as improving commercial manufacturing efficiency. In the face of challenges associated with rapid growth and an expanding product pipeline, Amgen's commitment to standardizing development work and digitizing both clinical and commercial manufacturing has introduced many opportunities for new data management initiatives, improvements, and a revamped overall data management strategy. We identify a framework for the development of a data management strategy for the Drug Product Technology group to enable greater efficiency and alignment across development and manufacturing teams. The primary steps in data management and objectives at each step were determined. While a full data management strategy has been recommended to the Drug Product Technology group as a set of current and future projects, this thesis focuses on three specific case study projects within the overall strategy: (1) data generation and collection in drug product manufacturing, (2) real-time multivariate statistical process monitoring of lyophilization in clinical manufacturing, and (3) integration of development study data through electronic lab notebook software. Based on insights from these case studies, we make specific recommendations for further improvements in data management. / by Spencer C. Anderson. / M.B.A. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / "June 2014." Cataloged from PDF version of thesis. / Includes bibliographical references (pages 46-47). / The Amgen Manufacturing Ltd. facility in Juncos, Puerto Rico faces a challenge encountered by manufacturers across industries: How can they make the best use of their existing resources? As production volume and product mix increase, how are costs kept from increasing as well? This LGO internship looked to answer those questions in the context of raw material receiving for biopharmaceutical manufacturing. Over the course of the seven month project, an analytical planning tool centered on scheduling optimization and priority queuing was developed, highlighting areas for improvement. Based on insight gained from the tool, a plan was established which can reduce turnaround time (TAT) by 50% and work in process (WIP) by 45% in the raw material sampling area. The improvements will not only provide financial and operational benefits to the organization, but serve as a foundation for continuous improvement as the findings from this project are applied elsewhere. This project highlights the importance of understanding how process inputs affect process output. In the case of raw material sampling, the variable mix of incoming materials exceeded the capacity for processing, particularly for solid materials, elevating the average TAT and WIP. Aligning sampling's capabilities to the input work makes it more flexible and better able to handle future demand. However, the ideal state for the area involves working with the upstream group, supply chain, to level-load arrivals. In this case, WIP can be reduced over 60% from its current level while maintaining TAT adherence at the 50% improved rate. Further utilization gains are possible, but only through value stream analysis and enhanced collaboration between functional groups. / by Andrew D. Bower. / S.M. / M.B.A.

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 57-58). / During manufacturing scale-up of a new product, new failure modes often surface which require corrective action. However, as production numbers of an insulin injection device pass 200 million per year, testing continues to find sub-assemblies with too-high injection forces, seemingly at random. Up until now, no corrective action has been effective in preventing these problems. These non-conforming sub-assemblies cause batches to be rejected, reducing the production yield at Sanofi's Site Frankfurt Devices (SFD) production facility. This thesis describes the current state of rejected batch problem solving and explores the application of new methods to better understand the root problems and improve the process. Frequency spectra analysis of testing data using the Fast Fourier Transform (FFT), combined with device physics, identified the key interaction points within the sub-assemblies. This model of part interactions has been verified through testing of purpose-built defective pieces and examination of defective parts. The verified model was then used to identify which components within sub-assemblies cause non-conformances. The root causes of several failure codes were determined, and results were further confirmed by rebuilding and retesting subassemblies with the identified problem components. These results confirm the usefulness of this novel application of frequency analysis to a new field of industrial troubleshooting. Various improvement and control methods are explored and next steps recommended for Sanofi to further improve quality control processes and thereby the production yield. The opinions expressed herein are solely those of the author and do not necessarily reflect those of Sanofi S.A. / by William D. Bellows. / S.M. / M.B.A.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 61-62). / This thesis focuses on a medical device manufacturer, Company X, using a razor-and-blades business strategy, in which surgical instruments are offered to customers at little or no cost in order to facilitate the sale of certain implantable products that require the use of such instruments. It faces considerable challenges in managing the instrument supply chain. Company X is interested in better understanding its instrument portfolio through segmentation so that it can efficiently manage its supply chain with an appropriate supply chain strategy for each segment. This thesis deals with the development of a segmentation methodology that can be used to objectively rank and segment medical device products that do not directly generate sales revenues, but contribute to the revenues generated by a dependent class of products. A methodology was developed to rank and segment the instruments within Company X's instrument portfolio using criticality heuristics. The segments were then evaluated for opportunities for inventory reduction without harming service levels. In addition, a cost minimization decision tool was developed to determine the optimal amount of excess inventory that should be discarded when items subject to minimum order quantities. Using the segmentation methodology and the minimum order quantity decision tool, Company X can potentially reduce its inventory value by over 60%. / by Todd A. Rosenfield. / M.B.A. / S.M.