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Developing A Manufacturing Cost Of Ownership Algorithm For Comparing Goods From Traditional Suppliers To Vendor Management

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Conference

2009 Annual Conference & Exposition

Location

Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009

ISSN

2153-5965

Conference Session

Research and Project Initiatives in IT and IET

Tagged Division

Engineering Technology

Page Count

11

Page Numbers

14.442.1 - 14.442.11

Permanent URL

https://peer.asee.org/5539

Download Count

77

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Paper Authors

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Jonathan Davis Purdue University

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Edie Schmidt Purdue University

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Sorraya Khiewnavawongsa Purdue University

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Regena Scott Purdue University

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Comparing the total cost of goods from traditional distributors to total costs under vendor management Abstract

Vendor-managed inventories (VMI) are a great boon for manufacturers—when skillfully implemented—because they provide for lower inventories, lower overall costs, a multitude of risk management advantages, and improved service levels. Far-sighted manufacturers who have adopted VMI see cost savings and service improvements that belie the larger dollar figure shown on each product invoice.

As is usual in education, it is quite simple to issue this statement in a classroom and receive nodding heads in response, but it is quite a different situation when those students become purchasing managers themselves and are faced with the choice of paying more money up front under VMI or picking the lowest bid from any competitive supplier of reasonable quality and reputation. Typical business measures put in place to influence purchasing employees’ behavior create negative incentives for employing VMI, since paying more money for supplies yields concrete negative numbers, even if the organization as a whole sees a cost reduction that is hidden in other areas of the organization. Conversely, measurements usually create incentives for purchasing managers to pick the lowest bid, even if the company as a whole loses.

This project, based on an ongoing study of the electric-utility industry, seeks to construct a solution for communicating the economic realities of separately sourcing materials for manufacturing versus creating a lasting relationship with one primary supplier through VMI. Moreover, the project will attempt to create an “argument” that arms students with knowledge of “total cost of ownership” philosophies, so that they can approach future manufacturing sourcing decisions with clear and convincing “experiential” knowledge. The result will be a clearly- defined economic difference between sourcing methodologies, complete with specific methods of quantifying (in terms of money) many of the benefits of VMI that impact the bottom line, but are not easily converted to a dollar figure.

Introduction

Vendor management of inventory (VMI) has a distinguished recent history of progress and success at the highest levels of industry.[1] From Procter and Gamble’s 24-year-old partnership with Wal-Mart to the current environment of widespread big-box retailer adoption, VMI has grown up from its roots as a wishful thinking plan to combat the bullwhip effect to a legitimate and even dominant idea for optimization of a retail supply chain.[2]

Even so, VMI remains difficult to sell to some industries, and difficult to implement even if sold.[3] This is especially true when the nature of the industry means that freely sharing information is risky, or when operational compliance to regulation is enforced by means of a government order, subpoena, or criminal charge.

One such industry is the electric utilities industry, where a small handful of large national distributors compete with seemingly innumerable small regional distributors to serve hundreds of

Davis, J., & Schmidt, E., & Khiewnavawongsa, S., & Scott, R. (2009, June), Developing A Manufacturing Cost Of Ownership Algorithm For Comparing Goods From Traditional Suppliers To Vendor Management Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. https://peer.asee.org/5539

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