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McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Inventory Management and Risk Pooling.

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Presentation on theme: "McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Inventory Management and Risk Pooling."— Presentation transcript:

1 McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Inventory Management and Risk Pooling

2 2-2 2.1 Introduction Why Is Inventory Important? Distribution and inventory (logistics) costs are quite substantial Total U.S. Manufacturing Inventories ($m): 1992-01-31: $m 808,773 1996-08-31: $m 1,000,774 2006-05-31: $m 1,324,108 Inventory-Sales Ratio (U.S. Manufacturers): 1992-01-01: 1.56 2006-05-01: 1.25

3 2-3 GM’s production and distribution network 20,000 supplier plants 133 parts plants 31 assembly plants 11,000 dealers Freight transportation costs: $4.1 billion (60% for material shipments) GM inventory valued at $7.4 billion (70%WIP; Rest Finished Vehicles) Decision tool to reduce: combined corporate cost of inventory and transportation. 26% annual cost reduction by adjusting: Shipment sizes (inventory policy) Routes (transportation strategy) Why Is Inventory Important?

4 2-4 Why Is Inventory Required? Uncertainty in customer demand Shorter product life cycles More competing products Uncertainty in supplies Quality/Quantity/Costs/Delivery Times Delivery lead times Incentives for larger shipments

5 2-5 Holding the right amount at the right time is difficult! Dell Computer’s was sharply off in its forecast of demand, resulting in inventory write-downs 1993 stock plunge Liz Claiborne’s higher-than-anticipated excess inventories 1993 unexpected earnings decline, IBM’s ineffective inventory management 1994 shortages in the ThinkPad line Cisco’s declining sales 2001 $ 2.25B excess inventory charge

6 2-6 Inventory Management-Demand Forecasts Uncertain demand makes demand forecast critical for inventory related decisions: What to order? When to order? How much is the optimal order quantity? Approach includes a set of techniques INVENTORY POLICY!!

7 2-7 Supply Chain Factors in Inventory Policy Estimation of customer demand Replenishment lead time The number of different products being considered The length of the planning horizon Costs Order cost: Product cost Transportation cost Inventory holding cost, or inventory carrying cost: State taxes, property taxes, and insurance on inventories Maintenance costs Obsolescence cost Opportunity costs Service level requirements

8 2-8 2.2 Single Stage Inventory Control Single supply chain stage Variety of techniques Economic Lot Size Model Demand Uncertainty Single Period Models Initial Inventory Multiple Order Opportunities Continuous Review Policy Variable Lead Times Periodic Review Policy Service Level Optimization

9 2-9 EOQ: Costs FIGURE 2-4: Economic lot size model: total cost per unit time

10 2-10 Demand Uncertainty The forecast is always wrong It is difficult to match supply and demand The longer the forecast horizon, the worse the forecast It is even more difficult if one needs to predict customer demand for a long period of time Aggregate forecasts are more accurate. More difficult to predict customer demand for individual SKUs Much easier to predict demand across all SKUs within one product family

11 2-11 Single Period Models Short lifecycle products One ordering opportunity only Order quantity to be decided before demand occurs Order Quantity > Demand => Dispose excess inventory Order Quantity Lose sales/profits

12 2-12 Single Period Models Using historical data identify a variety of demand scenarios determine probability each of these scenarios will occur Given a specific inventory policy determine the profit associated with a particular scenario given a specific order quantity weight each scenario’s profit by the likelihood that it will occur determine the average, or expected, profit for a particular ordering quantity. Order the quantity that maximizes the average profit.

13 2-13 Observations The optimal order quantity is not necessarily equal to forecast, or average, demand. As the order quantity increases, average profit typically increases until the production quantity reaches a certain value, after which the average profit starts decreasing. Risk/Reward trade-off: As we increase the production quantity, both risk and reward increases.

14 2-14 What If the Manufacturer Has an Initial Inventory? Trade-off between: Using on-hand inventory to meet demand and avoid paying fixed production cost: need sufficient inventory stock Paying the fixed cost of production and not have as much inventory

15 2-15 Multiple Order Opportunities REASONS To balance annual inventory holding costs and annual fixed order costs. To satisfy demand occurring during lead time. To protect against uncertainty in demand. TWO POLICIES Continuous review policy inventory is reviewed continuously an order is placed when the inventory reaches a particular level or reorder point. inventory can be continuously reviewed (computerized inventory systems are used) Periodic review policy inventory is reviewed at regular intervals appropriate quantity is ordered after each review. it is impossible or inconvenient to frequently review inventory and place orders if necessary.

16 2-16 Optimal inventory policy assumes a specific service level target. What is the appropriate level of service? May be determined by the downstream customer Retailer may require the supplier, to maintain a specific service level Supplier will use that target to manage its own inventory Facility may have the flexibility to choose the appropriate level of service Service Level Optimization

17 2-17 Trade-Offs Everything else being equal: the higher the service level, the higher the inventory level. for the same inventory level, the longer the lead time to the facility, the lower the level of service provided by the facility. the lower the inventory level, the higher the impact of a unit of inventory on service level and hence on expected profit

18 2-18 Retail Strategy Given a target service level across all products determine service level for each SKU so as to maximize expected profit. Everything else being equal, service level will be higher for products with: high profit margin high volume low variability short lead time

19 2-19 Target inventory level = 95% across all products. Service level > 99% for many products with high profit margin, high volume and low variability. Service level < 95% for products with low profit margin, low volume and high variability. Profit Optimization and Service Level

20 2-20 2.3 Risk Pooling Demand variability is reduced if one aggregates demand across locations. More likely that high demand from one customer will be offset by low demand from another. Reduction in variability allows a decrease in safety stock and therefore reduces average inventory.

21 2-21 Demand Variation Standard deviation measures how much demand tends to vary around the average Gives an absolute measure of the variability Coefficient of variation is the ratio of standard deviation to average demand Gives a relative measure of the variability, relative to the average demand

22 2-22 2.4 Centralized vs. Decentralized Systems Safety stock: lower with centralization Service level: higher service level for the same inventory investment with centralization Overhead costs: higher in decentralized system Customer lead time: response times lower in the decentralized system Transportation costs: not clear. Consider outbound and inbound costs.

23 2-23 Inventory decisions are given by a single decision maker whose objective is to minimize the system-wide cost The decision maker has access to inventory information at each of the retailers and at the warehouse Echelons and echelon inventory Echelon inventory at any stage or level of the system equals the inventory on hand at the echelon, plus all downstream inventory (downstream means closer to the customer) 2.5 Managing Inventory in the Supply Chain

24 2-24 Echelon Inventory FIGURE 2-13: A serial supply chain

25 2-25 More than One Facility at Each Stage Echelon inventory at the warehouse is the inventory at the warehouse, plus all of the inventory in transit to and in stock at each of the retailers. Similarly, the echelon inventory position at the warehouse is the echelon inventory at the warehouse, plus those items ordered by the warehouse that have not yet arrived minus all items that are backordered.

26 2-26 Warehouse Echelon Inventory FIGURE 2-14: The warehouse echelon inventory

27 2-27 2.6 Practical Issues Periodic inventory review. Tight management of usage rates, lead times, and safety stock. Reduce safety stock levels. Introduce or enhance cycle counting practice. ABC approach. Shift more inventory or inventory ownership to suppliers. Quantitative approaches. FOCUS: not reducing costs but reducing inventory levels. Significant effort in industry to increase inventory turnover

28 2-28 Inventory Turnover Ratios for Different Manufacturers IndustryUpper quartileMedianLower quartile Electronic components and accessories Electronic computers22.77.02.7 Household audio and video equipment Paper Mills11.78.05.5 Industrial chemicals14.16.44.2 Bakery products39.723.012.6 Books: Publishing and printing

29 2-29 2.7 Forecasting RULES OF FORECASTING The forecast is always wrong. The longer the forecast horizon, the worse the forecast. Aggregate forecasts are more accurate.

30 2-30 Utility of Forecasting Part of the available tools for a manager Despite difficulties with forecasts, it can be used for a variety of decisions Number of techniques allow prudent use of forecasts as needed

31 2-31 Techniques Judgment Methods Sales-force composite Experts panel Delphi method Market research/survey Time Series Moving Averages Exponential Smoothing Trends Regression Holt’s method Seasonal patterns – Seasonal decomposition Trend + Seasonality – Winter’s Method Causal Methods

32 2-32 The Most Appropriate Technique(s) Purpose of the forecast How will the forecast be used? Dynamics of system for which forecast will be made How accurate is the past history in predicting the future?

33 2-33 SUMMARY Matching supply with demand a major challenge Forecast demand is always wrong Longer the forecast horizon, less accurate the forecast Aggregate demand more accurate than disaggregated demand Need the most appropriate technique Need the most appropriate inventory policy

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