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Massachusetts Institute of Technology

Statistical and causal analysis of inbound supply chain inefficiencies

Abstract

dc:description.abstract

Given the importance of operational inefficiencies and their negative impact on the bottom line in today's competitive economy, CVS/pharmacy is very interested in implementing operational improvement initiatives across its inbound supply chain to minimize the number of non-value-added activities. Undertaking such efforts requires collaboration amongst all trade partners and a systematic approach in measuring the important performance metrics. Currently there is not a single procedure that defines the necessary metrics and the analytical tools necessary for identifying improvement opportunities. Leveraging research from the manufacturing industry, specifically supplier certification and statistical process control, this thesis aims to develop a comprehensive methodology for analyzing, monitoring and improving the operational performance of the retail industry supply chain. In this thesis, through an innovative approach to perfect order performance measurement combined with the practical application of statistical analysis methods, a complete supplier evaluation process is established. Further, by utilizing statistical sampling and based on the evaluation results, an inspection plan is provided that allows for accurate monitoring of ongoing processes with a reduction in inspection efforts. Finally through introduction of statistical process control models and root cause analysis, a complete procedure is developed for continuous evaluation and improvement, leading to efficiency gains and cost savings across the entire inbound supply chain.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Engineering Systems Division.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Authors dc:creator
  • Haley, Tyler, 1983-
  • Nasseri, Hossein
Advisor dc:contributor.advisor
  • Tony Craig.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/92117
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/92117

Chain of custody

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

Haley, Tyler, 1983-; Nasseri, Hossein. Statistical and causal analysis of inbound supply chain inefficiencies. Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92117