Development of a total landed cost and risk analysis model for global strategic sourcing

Total landed cost and supply chain risk analysis are methods that many companies use to assess strategic sourcing decisions. For this project, landed cost is defined as those costs associated with material movement from a supplier to a designated PerkinElmer, Inc. (PKI) manufacturing site. Tools or models that are available in the technology marketplace are often too cumbersome to incorporate with a company's existing technology architecture or are too simplistic to compute an accurate landed cost. For PerkinElmer, as their Analytical Sciences business continues to grow globally, they are continuously reviewing their supplier portfolio and assessing their procurement strategy. The landed cost and risk analysis tool consists of two components, a cost model and a risk analysis model. Both models were developed to allow PKI to better understand the savings opportunities associated with a supplier selection. When performing supply chain modeling and cost optimization, it was necessary to be able to evaluate multiple scenarios that can influence a sourcing decision. Therefore, by changing parameters such as transportation mode, lead time, inventory carrying cost, freight cost, order frequency, and order quantities in the dynamic cost model, PKI is able to understand supply chain cost trade-offs. The model developed for this project is dynamic to allow multi-variable scenarios to be assessed simultaneously, thus increasing the overall analysis efficiency. For the risk analysis model, approximately 20 different factors were considered as a part of a risk portfolio. This concept adapts traditional financial investment portfolio management theory by considering how much operational impact one factor may have on PKI.

Department dc:contributor.department

Leaders for Manufacturing Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2008

Author dc:creator

• Feller, Brian (Brian C.)

Advisor dc:contributor.advisor

• Donald Rosenfield and David Simchi-Levi.

• Sloan School of Management.
• Engineering Systems Division.
• Leaders for Manufacturing Program.

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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/43828

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/43828