Procter and Gamble Tries to Optimize Inventory

Topics: Supply chain management, Supply chain, Inventory Pages: 13 (2629 words) Published: November 22, 2011
Chapter 8: Achieving Operational Excellence and Customer Intimacy: Enterprise Applications

The shampoo and lipstick aisles at Target


actually sites for an unending struggle among consumer products companies for retail shelf space. No company knows this better than Procter & Gamble (P&G), one of the world's largest consumer goods companies, with annual revenue surpassing $76 billion and 138,000 employees in 80 countries. The company sells more than 300 brands worldwide, including Cover Girl cosmetics, Olay skin care, Crest, Charmin, Tide, Pringles, and Pampers.

Wal-Mart hardly seem like battlegrounds, but they are

changes in inventory made by one echelon may have unpredictable consequences on the others.

Multi-echelon inventory optimization seeks to minimize the total inventory in all of the echelons of a company's supply chain. This is more complicated than traditional inventory optimization because of the additional lead times between each echelon, the bullwhip effect, and the need to synchronize orders and control costs between echelons. Companies with this level of complexity in their supply chains musr replenish and divide their inventories at each distribu_ tion point along the supply chain, as opposed to just one distribution point or even just the inventory of the initial supplier. Each point in rhe supply chain is also unaware of the inventory levels of points beyond those that they have immediate contact with, which creates a lack of visibility up and down the supply chain.

Demand variability for P&G's products from its Beauty division is very high. A popular eye shadow or lipstick color may quickly fall out of favor, while fashion trends call for new products continually to come on-stream. Major retail outlets such as Wal-Mart and Target compete by offering brand-name products at the lowest price possible.

In response to these pressures, P&G is constantly searching for ways to reduce supply chain costs and improve efficiency throughout its entire manufacturing and distribution network. It recently implemented a multi-echelon inventory optimization system to manage its supply chain more effrciently. The supply chains of a company as large as p&G are extremely complicated, featuring thousands of suppliers, manufacturing facilities, and markets. Even the slightest of changes at any part of the supply chain has significant effects on all of the other participants. What's more, because P&G's supply chains are so extensive, the chance for any effors or inefficiencies to occur are greater than with smaller, more compact supply chains. Inventory optimization for a company as large as P&G is therefore critical to cutting costs and increasing revenues. P&G was already renowned for its supply chain management, successfully reductng its surplus inventory with sales and operations planning, better forecasting, just-in-time delivery strategies, and vendor-managed inventory activity. But multi-echelon inventory optimization has provided the company with a new means to achieve even hisher levels ol efficiency. Multi-echelon networks are networks in which products are located in a variety of locations along their path to distribution, some of which are in different "echelons", or tiers, of the enterprise's distribution network. For example, large retailers' distribution networks often consist of a regional distribution center and a larger number of forward distribution centers. The presence of multiple echelons in a distribution network makes inventory management more difhcult because each echelon is isolated from other echelons. so

The multi-echelon approach to inventory manage-

ment consists of the following factors: multiple independent forecast updates in each echelon; accounting for all lead times and variations in lead times; management of the bullwhip effect; creation of visibility up and down the demand chain; synchronized order strategies; and appropriate modeling of the

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