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- April 20, 2012 -

 
     
 

Supply Chain Graphic of the Week: Supply Chain Segmentation by Inventory Characteristics

 

Analysis by Sales Volume and Variability Leads to Three SKU Metatypes and Resulting Stocking and Distribution Policies, Driving Big Savings

 
     
 

By SCDigest Editorial Staff

 
 

 

We featured once again our good friend Dr. David Simchi-Levi of MIT on a Vidocast this week on the Supply Chain Television Channel, based on his best-selling book Operations Rules: Driving Customer Value Through Flexible Operations.

This time, the focus was on the very hot topic of supply chain segmentation, a strategy for which Simchi-Levi has been at the forefront of industry thinking. The basic idea: almost every company should operate multiple supply chains, based on such variables as the customer value proposition, product characteristics, or channels to market. Each supply chain will have its own needs for overall design, capabilities, metrics for success, and more.

 

Fortunately, companies can look for potential synergies across these different supply chains and share physical assets to keep costs low while managing their different logical supply chains in a way that optimizes their performance.

 

The graphic below illustrates the results of one consumer packaged goods company Simchi-Levi recently worked with that looked across its large SKU base in terms of overall sales volume and how dynamic (variable) demand was over short periods of time.

 

 

 

 

Source: Dr. David Simchi-Levi, MIT

 

 

This analysis led to segmenting the product base into three categories, as shown in the horizontal T figure overlaying the data. Those are: high volume, low variability SKUs; low volume, low variability; and low volume, high variability.

 

This segmentation analysis was used to significantly adjust distribution and stocking strategies, relative to what products are stored at central or local distribution centers.

 

The result was substantial overall reductions in inventory and transportation costs.

 

Perhaps your SKU base could use a similar analysis.

 

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