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Massachusetts Institute of Technology

Network Optimization of a D2C Supply Chain Subject to Changing Cost Conditions and Consumer Preferences

Abstract

dc:description.abstract

This thesis examines and models the fulfillment operations of a US, medium-sized, direct-to-consumer (D2C) healthcare distributor that competes with lower-priced alternatives (e.g. Amazon) through high-service and deep customer relationships. Recent inflationary trends have pushed the company to seek new ways to reduce cost. Therefore, this thesis focuses on methods to lower operational cost via network optimization. This work attempts to solve the network layout problem through two primary approaches: (1) Integer Programming using the Gurobi optimization python package and (2) Scenario Analysis modeling the cost of feasible configurations of the uncapacitated facility layout problem under the company’s existing order allocation logic. Both approaches result in similar solutions with the second deemed more interpretable by leadership and more aligned with existing IT logic in terms of order-facility allocation. Both models are successfully able to show a decrease in total landed cost of fulfillment relative to the base case. Qualitative considerations are discussed, as well as model sensitivity to changing environmental inputs (e.g. population shifts and changes in cost). A concurrent project examining the reduction of shipping expense by incentivizing subscription-based customers to order less frequently (e.g. consolidating two orders into just one shipment), thereby maintaining revenues while lowering shipping expense. Two proposed solutions are examined: (1) existing incentives and (2) new incentives. The first was tested and showed preliminary positive impact to cost. The company referenced in this work has been renamed as “DistroCo” for privacy. Sensitive figures, data, and information may be redacted or masked.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Sloan School of Management
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sarasua, Julie
Advisors dc:contributor.advisor
  • Willems, Sean
  • Simchi-Levi, David

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/152025
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/152025

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Sarasua, Julie. Network Optimization of a D2C Supply Chain Subject to Changing Cost Conditions and Consumer Preferences. Massachusetts Institute of Technology, 2023. https://hdl.handle.net/1721.1/152025