Advancing Replenishment Efficiency Utilizing Unit of Measure and Planogram Settings

Throughout the pandemic, Target has experienced many changes in the retail landscape. The rapid sales growth and significant transition to online shopping has stressed the limits of their distribution network, exposing some of the weaknesses of the existing supply chain. Despite the industry changes, Target remains true to improving the guest experience through product availability and customer interaction. The overload in sales has lead to large swings in inventory throughout the network. Their adoption of an omnichannel distribution network provides the flexibility to succeed in this environment, but the distribution network is extremely complex, Utilizing a variety of stores, distribution centers, and suppliers. Excess inventory at the store creates unnecessary burden of storage and shelf refills, reducing time for customer engagement. With Target’s customer focus at the heart of their continuous improvement efforts, they are examining the levers at their disposal throughout the supply chain to reduce inventory spillover, such as POG Design and Unit of Measure. To help deepen the understanding of how the supply chain settings can be manipulated to unlock better performance, this paper examines product characteristics at a more granular level to identify when and where Target can take action. A categorization technique is utilized to identify which setting is creating the risk of systematic spillover. This technique is then applied to historic data to understand trends and identify opportunities. The paper then defines a method of identifying demand variability and proposes a shelf optimization technique for the stable demand items. The intent of this research is to reduce the systematic risk of inventory spillover, thus enhancing store performance for the guest.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Sidell, Ben

Advisors dc:contributor.advisor

• Anthony, Brian
• Levi, Retsef

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/146683

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/146683