Inventory McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.

Overview of inventory Inventory functionality and definitions Inventory carrying cost Planning inventory Managing uncertainty Inventory management policies Inventory management practices

Why do we have inventories? Because the customer usually isn’t sitting at the plant exit! Queen Elizabeth research station in Antarctica

Risks associated with holding inventory Time duration Depth of commitment Width of commitment Typical measures of exposure to investments in inventory Manufacturer’s exposure is typically narrow, but deep and of long duration Wholesaler’s exposure is wider than manufacturers and somewhat deep Duration is medium Retailer’s exposure is wide, but not very deep Duration is usually short except for specialty retailers Supply chain exposure based on location

Functions of Inventory Geographical specialization allows us to specialize production across different locations Decoupling allows us to run processes for maximum economic lot sizes within a single facility Supply/Demand balancing accommodates the elapsed time between inventory availability and consumption Buffering uncertainty accommodates uncertainty related to: Demand in excess of forecast or Unexpected delays in delivery (aka safety stock)

Inventory policy Inventory policy is a firm’s guidelines concerning What to purchase or manufacture When to take action In what quantity should action be taken Where products should be located geographically Firm’s policy also includes decisions about which inventory management practices to adopt

Service level Service level is a performance target specified by management and defines inventory performance objectives Common measures of service level include Performance cycle is the elapsed time between release of a purchase order by the buyer to the receipt of shipment Case fill rate is the percent of cases ordered that are shipped as requested Line fill rate is the percent of order lines (items) that were filled completely Order fill is the percent of customer orders filled completely

Inventory definitions Inventory includes materials, components, work-in-process, and finished goods that are stocked in the company’s logistical system The cycle inventory (base stock) is the portion of average inventory that results from replenishment Order quantity is the amount ordered for replenishment Transit inventory represents the amount typically in transit between facilities or on order but not received Obsolete inventory is stock that is out-of-date or is not in recent demand Speculative inventory is bought to hedge a currency exchange or to take advantage of a discount Safety stock is the remainder of inventory in the logistics system

Average inventory is the typical amount stocked over time Average inventory equals the maximum inventory plus the minimum inventory divided by two Typically equal to ½ order quantity + safety stock + in-transit stock Figure 7.1 Inventory Cycle for Typical Product

Figure 7.3 Alternative Order Quantity and Average Inventory Smaller replenishment order quantities results in lower average inventory Policy must decide how much inventory to order at a specified time Reorder point defines when a replenishment order is initiated However, other factors are important like performance cycle uncertainty, purchasing discounts, and transportation economies Figure 7.3 Alternative Order Quantity and Average Inventory

Inventory expense is: Cost components: Inventory carrying cost is the expense associated with maintaining inventory Annual inventory carrying cost percent times average inventory value Inventory expense is: Cost of capital is specified by senior management Taxes on inventory held in warehouses Insurance is based on estimated risk or loss over time and facility characteristics Obsolescence results from deterioration of product during storage E.g. food and pharmaceutical sell-by dates Storage is facility expense related to product holding rather than product handling Cost components:

Final carrying cost percent used by a firm is a managerial policy Table 7.2 Inventory Carrying Cost Components

Inventory ordering cost components Order preparation costs Order transportation costs Order receipt and processing costs Material handling costs Total cost is driven by inventory planning decisions which establish when and how much to order

When to order × = T R D + SS × = T R D Basic reorder formula if demand and performance are certain R = Reorder point in units D = Average daily demand in units T = Average performance cycle length in days If safety stock is needed to accommodate uncertainty the formula is SS = Safety stock in units × = T R D + SS × = T R D

Figure 7.4 Economic Order Quantity How much to order Economic order quantity is the amount that balances the cost of ordering with the cost of maintaining average inventory Assumes demand and costs are relatively stable for the year Does not consider impact of joint ordering of multiple products Figure 7.4 Economic Order Quantity

Standard mathematical solution for EOQ

Example EOQ solution using Table 7.3 Total ordering cost is $152 = (2400/300 x $19.00) Inventory carrying cost is $150 = [300/2 x (5 x 0.20)]

Simple EOQ model assumptions All demand is satisfied Rate of demand is continuous, constant and known Replenishment performance cycle time is constant and known Constant price of product that is independent of order quantity or time An infinite planning horizon exists No interaction between multiple items of inventory No inventory is in transit No limit is placed on capital availability

Relationships useful for guiding inventory planning EOQ is found at the point where annualized order placement cost and inventory carrying cost are equal Average base inventory equal one-half order quantity Value of the inventory unit, all other things being equal, will have a direct relationship with replenishment order frequency Higher value products will be ordered more frequently

Typical adjustments to EOQ Compare total cost with each transportation rate option Volume transportation rates offer a freight-rate discount for larger shipments If discount is sufficient to offset added inventory carrying cost less the reduced cost of ordering then it is viable choice Quantity discounts offer a lower per unit cost when larger quantities are purchased Production lot size Multiple-item purchase Limited capital Dedicated trucking Unitization Other EOQ adjustments

Uncertainty in inventory management Demand uncertainty — when and how much product will our customers order? Performance cycle uncertainty — how long will it take to replenish inventory with our customers? Inventory policy must deal with uncertainty Variations must be considered in both areas to make effective inventory planning decisions

Demand uncertainty can be managed using safety stock To protect against stockout when uncertain demand exceeds forecast we add safety stock to base inventory Determine the likelihood of stockout using a probability distribution Estimate demand during a stockout period Decide on a policy concerning the desired level of stockout protection Planning safety stock requires three steps

Probability theory enables calculation of safety stock for a target service level E.g. a service level of 99% results in a stockout probability of 1% Service level is equal to 100% minus probability % of stockout From analysis of historical demand data the safety stock required to ensure a stock out only 1% of the time is possible A one-tailed normal distribution is used because only demand that is greater than the forecast can create a stockout The most common probability distribution for demand is the normal distribution

Example of historical demand analysis using a normal distribution Figure 7.6 Historical Analysis of Demand History Figure 7.7 Normal Distribution

Performance cycle uncertainty means operations cannot assume consistent delivery Table 7.10 Calculation of Standard Deviation of Replenishment Cycle Duration

Safety stock with combined uncertainty Planning for both demand and performance cycle uncertainty requires combining two independent variables The joint impact of the probability of both demand and performance cycle variation must be determined Direct method is to combine standard deviations using a convolution formula

Figure 7.8 Combined Demand and Performance Cycle Uncertainty Typical situation where both demand and performance cycle variation exists Figure 7.8 Combined Demand and Performance Cycle Uncertainty

Summary of alternative solutions to combined uncertainty Table 7.12 Average Inventory Impact Resulting from Changes in EOQ

The fill rate is the magnitude rather than the probability of a stockout Increasing the replenishment order quantity decreases the relative magnitude of potential stockouts The formula for this relationship is

Figure 7.9 Impact of Order Quantity on Stockout Magnitude Number of stockouts is reduced from two to one when order quantity is increased Figure 7.9 Impact of Order Quantity on Stockout Magnitude

Increased order size can be used to compensate for decreasing the safety stock Table 7.15 Impact of Order Quantity on Safety Stock

Dependent demand replenishment Inventory requirements are a function of known events that are not generally random No specific safety stock is needed to support time-phased procurement programs (e.g. MRP) Dependent demand does not require forecasting because there is no uncertainty Procurement replenishment is predictable and constant Vendors and suppliers maintain adequate inventories to satisfy 100% of purchase requirements No safety stock assumes:

3 approaches to introduce safety stock into dependent demand situations E.g. order a component earlier than needed to assure timely arrival Put safety time into the requirements plan E.g. assume plan error will not exceed 5 percent Over-planning top-level demand is a procedure to increase the requisition by a quantity specified by some estimate of expected plan error Utilize statistical techniques to set safety stocks directly for a component rather than to the item of top-level demand

Approaches to implementing inventory management policies Reactive (or pull) approach responds to customer demand to pull the product through the distribution channel Planning approach proactively allocates inventory on the basis of forecasted demand and product availability Hybrid approach uses a combination of push and pull

Inventory control using reactive approaches Inventory control defines how often inventory levels are reviewed to determine when and how much to order Perpetual review continuously monitors inventory levels to determine inventory replenishment needs Periodic review monitors inventory status of an item at regular intervals such as weekly or monthly

Reorder point formulas for reactive methods Perpetual Review Periodic Review

Assumptions of classical reactive inventory logic All customers, market areas, and product contribute equally to profits Infinite capacity exists at the production facility Infinite inventory availability at the supply location Performance cycle time can be predicted and that cycle lengths are independent Customer demand patterns are relatively stable and consistent Each distribution warehouse’s timing and quantity of replenishment orders are determined independently of all other sites, including the supply source Performance cycle length cannot be correlated with demand

Two planning approaches Planning approaches coordinate requirements across multiple locations in the supply chain Fair share allocation provides each distribution facility with an equitable distribution of available inventory Limited ability to manage multistage inventories Requirements planning integrates across the supply chain taking into consideration unique requirements Materials requirements planning (MRP) is driven by a production schedule Distribution requirements planning (DRP) is driven by supply chain demand Two planning approaches

Example of fair share allocation method Figure 7.11 Fair Share Allocation Example Allocation of 500 available units from plant Warehouse 1 = 47 Warehouse 2 = 383 Warehouse 3 = 70

Figure 7.12 Conceptual Design of Integrated MRP/DRP System Integrated planning approach for raw materials, work-in-process, and finished goods MRP system DRP system Figure 7.12 Conceptual Design of Integrated MRP/DRP System

Limitations to planning approaches Requires accurate and coordinated forecasts for each warehouse Requires consistent and reliable product movement between warehouse facilities Subject to frequent rescheduling (system nervousness) because of production breakdowns or delivery delays

Collaborative inventory replenishment programs Intent is to reduce reliance on forecasting and position inventory using actual demand on a just-in-time basis Replenishment programs are designed to streamline the flow of goods within the supply chain Quick response (QR) is a technology-driven cooperative effort between retailers and suppliers to improve inventory velocity while matching supply to consumer buying patterns Vendor-managed inventory (VMI) is a modified QR that eliminates the need for replenishment orders Profile replenishment (PR) extends QR and VMI by giving suppliers the right to anticipate future requirements according to their knowledge of a product category

Managerial considerations when developing an inventory policy Table 7.18 Suggested Inventory Management Logic

Inventory management practices E.g. classify by sales, profit contribution, inventory value, usage rate or item category Product/market classification groups products, markets, or customers with similar characteristics to facilitate inventory management E.g. service objectives, forecasting method, management technique, and review cycle Segment strategy definition specifies all aspects of inventory management process for each segment of inventory E.g. data requirements, software applications, performance objectives, and decision guidelines Policies and parameters must be defined at a detailed level

Example of product classification by sales Table 7.19 Product Market Classification (Sales)

Sample illustrating segment strategy definitions Table 7.20 Integrated Strategy