Evaluating demand planning strategy in the retail channel
Name
810135786-MIT.pdf
Description
Full printable version
Size
12.76 MB
Format
Adobe PDF
Checksum (MD5)
6c6f78aad463eac7e5043b7943db4da8
Author(s)
Zehavi, Limor (Limor Hadas)
Advisor(s)
David Simchi-Levi and Roy Welsch.
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
In 2007 Dell began selling through the retail channel. Five years later, the retail channel is still in the early stages relative to competitors and is growing rapidly. Short product lifecycles, long lead times and a high mix of configurations create a complex supply chain. Dell had decided to introduce a Build to Plan fulfillment strategy. Dell has been known for its direct consumer strategy and the retail channel adds an additional stage in the supply chain between Dell and the end consumer. This change impacts the visibility of true demand, resulting in the bullwhip effect. Better collaborative processes such as S&OP and CPFR can improve the channel forecast accuracy, inventory levels, on time delivery, and sales revenue. The personal computer industry has become commoditized; promotions and price have a high impact on the end consumer's purchase decision. Long lead times and high price fluctuation increase uncertainty. Forecasting at a SKU level is challenging and inaccurate. An aggregated approach can reduce the variability and postpone the customization. Forecast accuracy is a key metric that can be used to improve the supply chain. To improve that metric, the appropriate forecast must be tracked and compared to the actual sales. A significant portion of any new planning process will need to account for updated software tools. These tools can help Dell's demand planners facilitate weekly conversations with retailers and ensure more accurate tracking of appropriate demand signals for forecasting. The current product portfolio that allows high flexibility to retailers does not fit the low margins of the product. Demand segmentation can identify which SKU have high volatility and offer a different supply chain strategy for those with low volumes, or spotlight high costs in offering those SKU.
Description
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 77-78).
Subjects
Sloan School of Management.
Engineering Systems Division.
Leaders for Global Operations Program.
MIT Department
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Engineering Systems Division
Sloan School of Management
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