Deere Company

Topics: Inventory, Supply chain management, Distribution, retailing, and wholesaling Pages: 2 (942 words) Published: December 2, 2014
Improving Asset Management and Order Fulfillment at Deere & Company’s C&CE Division

Deere & Company founded in 1837 and headquartered in Moline, Illinois is a leading production company of agriculture equipment, forestry and consumer use. The $15.5 billion company employs 43,000 people. The Commercial and Consumer Equipment (C&CE) Division reported over $3 billion revenues in 2003. In 2001 C&CE leaders committed to reducing total inventory by $500 Million and as sales increased, to holding inventory dollars constant. C&CE’s Leaders committed to delivering products to dealers by the dates requested at least 90% of the time by 2005.

Optimizing inventory in complex supply chain is challenging. Due to this increase in competition the profit margin of the companies are goes on decreasing as a result of which every company now a days focusing on reducing inventory by investing in enterprise planning and execution system but continue to face inventory problems. Establishing a sustainable inventory optimization system is not simple. In addition to that, time-varying demands caused by seasonality, product life cycles and time-varying capacities caused by expanding plants, introducing new processes and technologies, holidays and schedule shutdowns make setting the reliable inventory targets difficult.

In August 2001, C&CE order fulfillment group contacted the Smart-Ops and formed a team to tackle the challenge in a sequential, multiphase approach. The team conducted an analysis to determine how much to cut inventory levels using a more sophisticated approach. They loaded a data from three C&CE plants and 25 dealers in Smart-Ops MIPO application and calculate optimal inventory targets. They computed recommended stocking levels (RSLs) using MIPO, an enterprise-strength application that solves complex stochastic inventory-optimization problems efficiently. It views a supply chain as a discrete-time, stochastic finite-horizon, time-varying, capacitated multistage...
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