Pre- and In-season Stock Allocation at H&M Online

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dc.contributor.authorAdlarson, Carl
dc.contributor.authorHolgersson, Marcus
dc.contributor.departmentChalmers tekniska högskola / Institutionen för teknikens ekonomi och organisationsv
dc.contributor.departmentChalmers University of Technology / Department of Technology Management and Economicsen
dc.date.accessioned2019-07-03T14:16:12Z
dc.date.available2019-07-03T14:16:12Z
dc.date.issued2016
dc.description.abstractToday the Swedish multinational retail-clothing company H&M mainly source products from production suppliers in Asia, resulting in extensive lead times. The time-consuming transportation and short fashion seasons and trends require H&M to produce to stock based on forecasts. H&M Online, which is the e-commerce company within the H&M group, are currently planning to source their largest online market Germany from two warehouses instead of only using one warehouse as of today. This will in theory shorten the critical lead time from 3-5 days to 1-2 days to all German e-commerce customers. The more decentralized logistics setup will on the other hand bring challenges when it comes to the allocation of stock between the two warehouses both before a season starts but also during an ongoing season. The purpose of the thesis is consequently to develop a preseason stock allocation model and to come up with strategies for how to optimize the stock allocation during an ongoing season for the hypothetical warehouse network. The pre-season allocation model and in-season allocation strategies are developed by combining theoretical insights from e-commerce, fashion forecasting and stock allocation literature with qualitative and quantitative findings from the case study at H&M Online. The developed model is mainly based on a statistical forecasting method, which estimates a future allocation split based on previously observed demand data last comparable season from the market that the warehouses supply, together with future sales targets for the upcoming season set by H&M’s market experts. By testing and simulating the developed pre-season stock allocation model using historical demand data from the spring season of 2014 to estimate suitable stock allocation splits for the spring season of 2015, a total miss in sales of 7.4 percent at an aggregated level for all H&M Online’s departments is achieved. Potential improvement areas for the model are identified. Due to the fashion e-commerce industry’s many sources of future demand uncertainty and to shortcomings of the developed allocation model, stock allocation during ongoing season can and should be used. In-season stock allocation strategies suitable for H&M Online are usage of real-time demand data during season to update the stock allocation split between the warehouses but also different stock postponement and quick response strategies.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/238920
dc.language.isoeng
dc.relation.ispartofseriesMaster thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden : E2016:042
dc.setspec.uppsokTechnology
dc.subjectTransport
dc.subjectÖvrig industriell teknik och ekonomi
dc.subjectTransport
dc.subjectOther industrial engineering and economics
dc.titlePre- and In-season Stock Allocation at H&M Online
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeManagement and economics of innovation (MPMEI), MSc
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