TY - JOUR
T1 - Total Hockey Optimizes Omnichannel Facility Locations
AU - Millstein, Mitch
AU - Campbell, James F.
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PY - 2018/7/31
Y1 - 2018/7/31
N2 - Omnichannel distribution, which blends brick-and-mortar retailing and e-commerce, is a key challenge for today’s supply chains. In this paper, we report on a study to design an omnichannel distribution system for Total Hockey, a growing U.S. sporting goods retailer in a competitive environment. Management strongly believes that e-commerce success will depend on high service levels characterized by one- or twoday delivery and initially thought that a new omnichannel warehouse located on the East Coast could support its expansion plans. To study the situation, we developed a profit-maximizing optimization model for locating omnichannel warehouses that supports both e-commerce and store shipments. The model uses estimates of e-commerce demand by metropolitan statistical area (MSA) across the United States, while incorporating management’s sales expectations regarding the value of high service levels, e-commerce sales lost to competitors’ stores, and reverse cannibalism from Total Hockey’s own retail stores. Multiple warehouse sizes allow modeling of nonlinear inventory costs. The facility-location optimization model allows exploration of multiple solutions and an assessment of the impact of higher service levels. The results of the study were contrary to management expectations and suggested a significant redesign of the distribution system. We report results for several analyses, implementation details, and managerial insights for omnichannel distribution.
AB - Omnichannel distribution, which blends brick-and-mortar retailing and e-commerce, is a key challenge for today’s supply chains. In this paper, we report on a study to design an omnichannel distribution system for Total Hockey, a growing U.S. sporting goods retailer in a competitive environment. Management strongly believes that e-commerce success will depend on high service levels characterized by one- or twoday delivery and initially thought that a new omnichannel warehouse located on the East Coast could support its expansion plans. To study the situation, we developed a profit-maximizing optimization model for locating omnichannel warehouses that supports both e-commerce and store shipments. The model uses estimates of e-commerce demand by metropolitan statistical area (MSA) across the United States, while incorporating management’s sales expectations regarding the value of high service levels, e-commerce sales lost to competitors’ stores, and reverse cannibalism from Total Hockey’s own retail stores. Multiple warehouse sizes allow modeling of nonlinear inventory costs. The facility-location optimization model allows exploration of multiple solutions and an assessment of the impact of higher service levels. The results of the study were contrary to management expectations and suggested a significant redesign of the distribution system. We report results for several analyses, implementation details, and managerial insights for omnichannel distribution.
UR - https://sites.math.washington.edu/~stgriff/Interfaces/Interfaces_Hockey_Location.pdf
UR - https://pubsonline.informs.org/doi/10.1287/inte.2018.0942
U2 - 10.1287/inte.2018.0942
DO - 10.1287/inte.2018.0942
M3 - Article
JO - Articles in Advance
JF - Articles in Advance
ER -