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About the Author

Cliff Holste is Supply Chain Digest's Material Handling Editor. With more than 30 years experience in designing and implementing material handling and order picking systems in distribution, Holste has worked with dozens of large and smaller companies to improve distribution performance.

Logistics News

By Cliff Holste

November 5, 2014



Fine Tuning Inventory Levels is Key to Improving the Bottom-line

Innovations in Inventory Optimization – What's Old is New Again



Holste Says:

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Buyers, working in the cross-fire of sales and financial administration, must have full confidence in the purchase proposals produced by a system or calculation model.
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Previous Columns by Cliff Holste

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Sorting It Out: For Shippers - Benefits Of Real-Time Control In The DC Are Huge!

Sorting It Out: Shippers Looking to Improve Operations Choose Customer Centric Approach

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Sorting It Out: Packaging Construction Impacts on Logistics Operations

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For consumer goods retailers, product inventory and purchases play a significant part in the bottom line results of the company. A loss in sales caused by an out-of-stock condition not only has an impact on net sales and operating profit, but also on customer satisfaction and image. However, the capital tied to excessive inventory levels decreases funds otherwise available for improvement projects. In addition, there is always risk of products turning obsolete prematurely. The impact of the undervaluation of slow-moving products can be seen directly in the bottom line of the income statement.

 

Challenges for the Buyer

The ungrateful task of the Buyer is to be able to purchase a sufficient quantity of the correct products so that the sales unit has items to sell but, at the same time, not too many products so that the total inventory value will not rise too high. Therefore, the essential question is “How much?”

According to textbooks, the calculation of the Economic Order Quantity (EOQ), known as the Wilson Formula, is based on the optimization of holding costs and ordering costs. The formula works in theory and, with specific restrictions, also in practice. The basics is that the demand for products remains fairly stable, ordering costs are independent of the batch size, and the lead time remains unchanged. In which case, ordering and holding costs should be allocated to each product with sufficient accuracy. However, this presents challenges, because even in a small company there may be several thousand different products. Some products are easy to order and store, whereas, others require a more complicated ordering process that takes into consideration safety stock levels.

Buyers, working in the cross-fire of sales and financial administration, must have full confidence in the purchase proposals produced by a system or calculation model. The calculation of EOQ and, as a result, the allocation of costs to products, must be revisited frequently because the company’s operating environment is constantly changing (i.e. new products are launched, old ones are removed, demand for products varies and there are changes in the company’s cost structure). In most businesses, the company’s purchase process is based on purchase proposals generated by an Enterprise Resource Planning (ERP) system.

With ERP the calculation of purchase proposals uses item-specific control parameters (e.g. order point). The order point can be calculated by adding consumption over the delivery time to the safety stock. While the Wilson Formula pays no attention to the safety stock, it can be calculated through the mean deviation in deliveries using statistical methods. However, confidence presents yet again a problem. Does the Buyer understand the principle for calculating the safety stock and does the principle produce sufficiently correct results?

 

Life cycle-based ABC+ categorization

Current sales & marketing trends appear to be shorting the life cycle of products. This applies not only to the latest mobile phones and digital cameras, but also to nearly all traditional consumer goods categories.

With this in mind, when considering the EOQ, the safety stock of “rising trend products” (that might be at the introduction stage or growth stage of their life cycle) could be over-stated, whereas the safety stock of products that are approaching the end of their life cycle could be kept at minimum. The question is then - how can this be carried out in practice? One possibility is product categorization.

In a traditional ABC categorization, products are divided into A, B or C categories on the basis of sales volume. This product method however, does not indicate whether a specific product is at the initial or final stages of its life cycle. For this purpose, a product life cycle-based ABC+ categorization method has been developed. New and EOS (end of sales) products require separate categories. A rising trend, stable demand and decreasing trend can be represented using symbols '+', '=' and '-'. As a result, the ABC category of a volume product with a rising trend is ‘A+’. The category of a volume product with decreasing sales is ‘A-‘and, that of a volume product with stable demand is ‘A=’.

A Min–Max range is specified for each ABC category within which the product’s stock balance must be kept. For example, the minimum level (i.e. safety stock) of an A+ product can be a quantity corresponding to the consumption of one month and the maximum level can be a quantity corresponding to the consumption of three months. This method is not aimed at optimising costs related to the ordering process, but it can significantly reduce costs arising from the undervaluation of obsolete products because the stock levels can be reduced in a controlled manner following the product’s life cycle. At the same time, the capital tied to the inventory can be reduced and product availability can be improved.


Final Thoughts

 

The above described inventory optimization method takes the well established ABC method and enhances it to better serve today’s rapidly changing "fashion-driven" marketplace.

 

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