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Optimize the supply chain of a major office equipment

/ automation company

By: Zhimin Mao, School of Business

Introduction:

The object of this study is to optimize the supply chain of a major office equipment / automation

company. Supply chain encompasses all activities associated with the flow and transformation of goods

from the raw materials stage, through to the end user, as well as associated information flows (Handfield

and Nichols, 1999). One of the major drivers of supply chain performance is considered to be inventorymanagement. Changing inventory policies can dramatically alter the supply chains efficiency and

responsiveness (Chopra and Meindl, 2001). However, managing inventories in supply chains is typically

difficult, and may have a significant impact on customer service level and system-wide costs (Simchi-

Levi, Kaminsky and Simchi-Levi, 2003). Currently, the company considered in this study is holding

extra inventory, resulting in a significant inventory carrying costs. This project will focus on developing

different inventory management models to optimize this companys supply chain performance. The

supply chain network considered consists of:

Three manufacturing facilities in Rochester (NY), Oklahoma City, and Oakville (Ontario).

Seven major supply distribution centers (SDCs) in New York, San Francisco, Los Angeles,

Atlanta, Chicago, Dallas, and Washington D.C.

Thirteen smaller regional distribution centers (XSCs) in Salt Lake City, Seattle, St Louis,

Indianapolis, Detroit, Tampa, Denver, Kansas City, Houston, Phoenix, Puerto Rico, Minneapolis,

and Hawaii.

Methodology:

The following notation is used to describe the inventory management models utilized:

AVG: Average demand STD: Standard deviation of demand

L: Lead time STDL: Standard deviation of lead time

Z: Desired customer service level Mod Pack: Lot size

Year of 2007, E- business Supply Chain Management, Mentor: Farzad Mahmoodi, Presentation

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Three inventory management models were utilized to conduct the analysis depending on the variation in

demand and lead times at various manufacturing and distribution facilities:

Model 1: Demand Variable, Lead Time constant

Safety Stock = Z x STD x (L)0.5

Average Inventory= Safety Stock +(L x AVG)/2 + (Mod Pack-1)/2

Model 2: Demand Variable, Lead Time Variable

Safety Stock = Z x L x ( STD)2+ (AVG)2(STDL)2)0.5

Average Inventory= Safety Stock +(L x AVG)/2 + (Mod Pack-1)/2

Model 3: Demand Variable, Lead Time Variable- Multi Echelon

Safety Stock= Z x ((AVGLe)STD2+AVG2 x (STDLe)2)0.5

Average Inventory= Safety Stock +(L x AVG)/2 + (Mod Pack-1)/2

Results:

The models were used to determine each distribution centers optimal levels of safety stock and average

inventory. The results indicated that safety stocks were being held at wrong locations. For example, the

distribution center at San Francisco was holding too much safety stock while New York and Cerritos

were holding too little. Also, most of the XSCs need to carry more safety stocks due to the excessive

transportation time variance, indicating an important area for improvement.

The models also showed that wrong amount of average inventories were being carried at the wrong

location, at different times of the year. For instance, the distribution center at Chicago was holding toomuch inventory at the end of the year while too little during the rest of the months. This may be caused by

the push strategy used by the manufacturing facilities at the end of each year.

In summary, the models resulted in recommending optimal levels ofsafety stock, average inventory, and

reorder points at all 20 distribution centers for various products. Furthermore, the models optimized the

Year of 2007, E- business Supply Chain Management, Mentor: Farzad Mahmoodi, Presentation

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location and the amount of safety stocks in the manufacturing facilities by utilizing process improvement

techniques, as well as push-pull strategies. The recommendations are being implemented since they result

in significantly lower inventory costs while maintaining customer servicelevels (by having the right mix of

inventory at the right location, and at the right time).

References:

William, S. (2005) Operations Management (8th Ed). McGraw- Hill/Irwin

David, S; Philip, K; Edith, S. (2003) Designing & Managing The Supply Chain: concepts, strategies &

case studies. (2nd Ed) McGraw- Hill/Irwin

Sunil, C; Peter, M.(2001) Supply Chain Management: strategy, planning and operation. Prentice Hall

Year of 2007, E- business Supply Chain Management, Mentor: Farzad Mahmoodi, Presentation