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dc.contributor.advisorJames B. Rice, Jr.en_US
dc.contributor.authorBotero Aristizabal, Melissaen_US
dc.contributor.authorBrenninkmeijer, Fabianen_US
dc.contributor.otherMassachusetts Institute of Technology. Supply Chain Management Program.en_US
dc.date.accessioned2017-12-20T18:15:37Z
dc.date.available2017-12-20T18:15:37Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/112873
dc.descriptionThesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 51-52).en_US
dc.description.abstractHigh volatility in order patterns leads to supply chain wide inefficiencies and high operational costs. This issue is particularly common in the consumer goods industry due to large numbers of SKUs under management and frequent promotions. By leveling out the number of weekly shipments (containing constant quantitates of top selling SKUs), a company can potentially boost operational performance while reducing costs. The research question of this thesis was therefore "Will a consistent, pre-determined customer shipment profile based on the lean leveling principle reduce variability and enable improvements in transportation cost, service level and cash (i.e. reduce working capital tied up in inventory)?" In academic literature, lean principles have been applied extensively in manufacturing settings, while the logistics domain remains a relatively unexplored lean frontier. In this thesis the team sought to realize lean-based gains by replacing large, infrequent batch deliveries with frequent small shipments, as derived from lean theory. The team created a customer shipment profile based on historical shipping data, consumption data and forecast information. The top selling items, which were the core products of subsequent analysis, were derived from a SKU segmentation. The number of required units was calculated based on the service promise. The team simulated two inventory policies: a Fixed scenario (orders are derived from historical averages) and a hybrid scenario (a fixed component based on a percentage of the historical average and a variable component). The model was validated by comparing calculated transportation cost, service level and cash with the values derived from the actual company records. The study suggests that applying the lean leveling concept may lead to reduced shipment variability. Placing orders on a fixed shipment schedule can lead to lower transportation costs and higher service levels. Cash requirements for inventory may be higher with increasing implementation of lean leveling. The optimal result for buyer and seller could be obtained with the hybrid model: At 75% fixed orders, the benefits of transportation cost, cash and service level were equally balanced. Other companies across different industries may find the thesis model useful to possibly improve operational performance while reducing costs through lean leveling.en_US
dc.description.statementofresponsibilityby Melissa Botero Aristizabal and Fabian Brenninkmeijer.en_US
dc.format.extent52 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSupply Chain Management Program.en_US
dc.titleReducing shipment variability through lean levelingen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Supply Chain Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Supply Chain Management Program
dc.identifier.oclc1014340138en_US


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