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Deere Company

University/College: University of Arkansas System
Date: January 10, 2018
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Deere Company

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 cosmologies, holidays and schedule shutdowns make setting the reliable inventory targets difficult. In August 2001 , C 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 plants and 25 dealers in Smart-ops MIPS application and calculate optimal inventory targets. They computed recommended stocking levels (Errs) using MIPS, 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, capacitate multistage model. The MIPS represents the flow of the material in the supply chain as an acyclic directed graph.

In the second phase, they put the results of the analysis Into dally operator and conducted a simulation of a pull based order fulfillment system with 25 dealers. The success of this two phases convinced Deere that it could reduce inventories if it used scientific methods or techniques to calculate inventory targets. The model can also accommodate additional constraints on time varying minimum inventory level by item and location. The objective is to satisfy deferent customer segments with the lowest total Investment In Inventory.

MIPS uses a fast algorithm that combines the recent stochastic analysis results and permits ongoing use. In other words it determines an ordering of stocking locations to facilitate demand propagation. Secondly, the internal service level (ISLE) module calculates the candidate service levels at warehouse stocking locations to satisfy the constraint on minimum service level. Next, the safety stock (AS) module uses this ISLE to compute AS requirements at all ticking locations In the supply chain.

The RSI for each stocking location and period algorithm transfers the target for safety stocks to the capacitate materials and distribution requirements planning (MR./DRP) module, which follows the logic and translates an input statement of demands into production quantities throughout the supply chain. The algorithm also produces various inventory components such as cycle stock, safety stock, merchandise stock, overbuild stock, physical pipeline stock and total pipeline stock.

In the order fulfillment process, the C determines the weekly Re’s over a 26- eek horizon to support the weekly order fulfillment process, thus computing over 6. 5 million Errs. Dealers review and update their records on inventory two days prior to receipt of their weekly shipments. If the inventory are not at or above the Errs, the order fulfillment system automatically generates orders to replenish their inventories by the next shipment. Dealers can add orders and manually for particular type of customers and can reroute orders to different dealer locations.

Every day Deer’s ERP system generates a delivery due list for orders to be shipped from the warehouse, allocating on-hand inventory to orders at that time. When order leaves the warehouse, the system generates invoices against the dealers, decreases inventory on hand at the warehouse and increases inventory on hand at the dealers. To determine the weekly Re’s at the warehouses, MIPS requires data on forecast, forecast error, capacity and minimum stock requirement because Deere maintains a corporate forecast by month and region only.

TO support the creation of the Errs, MIPS uses a batch process that executes the six steps. They compared C&CE’s 2003 performance to its expected performance in 2003 based on 2001 metrics and found that the inventory is reduced by $890 million. Most of the inventory reduction is measured by averaging the end of month levels, occurred at the independent dealers. While C records sales revenue when it ships inventory to the dealers, it bears the burden of financing the dealers inventory and thus reduction in inventory occurs.

The $550 million inventory breaks down into $500 million at the dealers and $50 million at the warehouses. The Deere and Company wanted to maintain warehouse inventories at their previous levels to take the advantage of pooling effects and other benefits of flexible inventory. Due to this decrease in inventory the venue bookings dropped, however Deere still received cash for these sales. Optimizing inventory reduced working capital and increased dealer service levels.

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