148
Chapter Six
Quantity and
Inventory
Chapter Outline Inventory ManagementFunctions and Forms of Inventories
The Functions of Inventory The Forms of Inventory
Inventory Function and Form Framework Managing Supply Chain Inventories
ABC Classification Costs of Inventories Forecasting
Forecasting Techniques
Determining Order Quantities and Inventory Levels
Fixed-Quantity Models Fixed-Period Models
Probabilistic Models and Service Coverage Buffer or Safety Stocks and Service Levels
Material Requirements Planning (MRP)
MRP Inputs MRP Lot Sizing Modern MRP Systems Supply Implications of MRP
Lean Supply and JIT
Kanban Systems
JIT and Inventory Management
JIT Implications for Supply Management
Conclusion
Questions for Review and Discussion References
Cases
6–1 Connecticut Circuit Manufacturers 6–2 Abbey Paquette
Key Questions for the Supply Manager Should we
• Change the way we forecast? • Use vendor-managed inventories? • Purchase our A items differently? How can we
• Reduce our investment in supply chain inventories? • Improve our inventory management?
• Obtain supplier cooperation for JIT?
Continuous improvement; speed to market; customer, employee, and supplier satisfaction; and global competitiveness require dedication to productivity and value-adding activities. These organizational goals drive management attitudes to quality, quantity, and delivery, with profound impact on the acquisition process. With respect to quantity and delivery considerations, the most telling evidence comes from inventory reduction and shortened lead times. Both can be accomplished by increasing frequency of deliveries, while decreas-ing the amount delivered at one time. Accompanydecreas-ing efforts in setup time reduction, just-in-time (JIT) systems, vendor-managed inventory systems, order cost reduction, EDI, and e-commerce are all part of the same drive.
The decisions of how much to acquire and when logically follow clarification of what is required. The natural response is to say, “buy as much as you need when you need it.” Such a simple answer is not sufficient, however. Many factors significantly complicate these decisions. First, managers must make purchase decisions before, often a long time before, actual requirements are known. Therefore, they must rely on forecasts, not only of future demand but also of lead times, prices, and other costs. Such forecasts are rarely, if ever, perfect. Second, there are costs associated with placing orders, holding inventory, and running out of materials and goods. Third, materials may not be available in the desired quantities without paying a higher price or delivery charge. Fourth, suppliers may offer reduced prices for buying larger quantities. Fifth, shortages may cause serious disruptions. In many organizations, the decision of how much to purchase and when is made more important by the close relationship between purchase quantity and scheduled use. It is nec-essary to distinguish between how much to buy in an individual purchase or release and what portion of total requirements to buy from an individual supplier. This chapter deals only with individual order quantities and inventory management; the allotment to suppli-ers is discussed in Chaptsuppli-ers 10, 18, and 19.
INVENTORY MANAGEMENT
Quantity and delivery go hand in hand. Order less, deliver more frequently; order more, deliver less frequently. Every supplier performance evaluation scheme includes quantity and
delivery as standard evaluation criteria. To ensure timely delivery, recognition needs to be given to the times required to complete each of the steps in the acquisition process discussed in Chapter 3. The ability to compress these times by doing them in parallel, by eliminating time-consuming and non-value-adding activities, by doing steps faster, and by eliminating delays can provide significant benefits. Much of the reengineering work in the supply area has focused on the acquisition process to make it more responsive and to reduce cycle time. For the supply management function, the time-based strategies that are of importance in the quantity decision are ones that relate directly to the flow of materials, inventories (raw material, work-in-process, and finished goods), and related information and deci-sions. Competitive advantage accrues to organizations that can (1) successfully reduce the time it takes to perform activities in a process (reduce setup and cycle time) and (2) coor-dinate the flow of resources to eliminate waste in the system and ensure that materials and equipment arrive on time or just-in-time in economically sized batches.
Long lead times can occur in the design and development process, in the material acqui-sition to distribution of finished goods process, and in administrative support cycles (e.g., accounts payable, purchase order development/release cycle). Some of the causes of long lead times are waiting and procrastination, poorly engineered designs, the accumulation of batches prior to movement, inefficient and long physical flows with backtracking, and poor communication. Long lead times can impact decisions about how much to buy. Compressed cycle times and coordination of material and information flows can result in materials arriving just-on-time (e.g., when they were scheduled to arrive) or just-in-time (just prior to actual use or need). Material requirements planning–type (MRP) programs or kanban (pull systems) can be used to plan the timing and quantity of purchased materials and internally manufactured materials.
There are many causes for poor material flow coordination, including late, early, or no deliveries; low fill rate; material defects; scrap; uneven batch sizes; long lead times; production schedule changes; downtime; long setup/changeover times; infrequent updates of MRP systems; forecasts; and on-hand inventory accounting systems. Greater coordination of material and information flows both within the buying firm and its cus-tomers and between the buying firm and its suppliers (and their suppliers) can result in lower inventories and improvements in return on assets in the supply chain (see example in Chapter 1).
FUNCTIONS AND FORMS OF INVENTORIES
Understanding where (and why) inventory should be positioned in the supply chain can improve customer service, lower total costs, or increase flexibility. Proper inventory manage-ment requires a thorough understanding of both the functions and the forms of inventory.
The Functions of Inventory
Many purchases cover repetitive items often held in inventory. Thus, inventory policy has a great influence on purchase quantity decisions. The questions of how much to order, when, and how much to carry in stock are key decisions subject to continuous improve-ment examination along with the focus on quality and customer, employee, and supplier satisfaction. It is important in making delivery, inventory, or purchase order size decisions
to understand why inventories exist and what the relevant trade-offs are. Inventories exist for many purposes, including:
• To provide and maintain good customer service.
• To smooth the flow of goods through the productive process.
• To provide protection against the uncertainties of supply and demand. • To obtain a reasonable utilization of people and equipment.
The following classification of inventory functions reveals the multipurpose roles played by inventories.
Transit or pipeline inventories are used to stock the supply and distribution pipelines
linking an organization to its suppliers and customers as well as internal transportation points. They exist because of the need to move material from one point to another. Obviously, transit inventories are dependent on location and mode of transportation. A decision to use a distant supplier with rail transport will probably create a far larger raw materials transit inventory than a decision to use a local supplier with truck delivery.
In just-in-time (JIT) production, a variety of means are used to reduce transit invento-ries, including the use of local suppliers, small batches in special containers, and trucks specifically designed for side loading in small quantities.
Cycle inventories arise because of management’s decision to purchase, produce, or sell
in lots rather than individual units or continuously. Cycle inventories accumulate at vari-ous points in operating systems. The size of the lot is a trade-off between the cost of hold-ing inventory and the cost of makhold-ing more frequent orders and/or setups. A mathematical description of this relationship, the economic order quantity, will be discussed later. In JIT, the need for cycle inventories is reduced by setup cost and time reduction.
Buffer or uncertainty inventories or safety stocks exist as a result of variability in demand
or supply. Raw material, purchased parts, or MRO buffer stocks give some protection against the variability of supplier performance due to shutdowns, strikes, lead-time variations, late deliveries to and from the supplier, poor-quality units that cannot be accepted, and so on. Work-in-process buffer inventories protect against machine breakdown, employee illness, and so on. Finished goods buffers protect against unforeseen demand or production failures. Management efforts to reduce supply variability may have substantial payoffs in reduced inventories. Options may include increasing supply alternatives, using local sources, reduc-ing demand uncertainty, reducreduc-ing lead time, or havreduc-ing excess capacity. Buffer inventory levels should be determined by balancing carrying cost against stockout cost.
Buying in expectation of major market shortages is a longer time-frame variation of buffer inventory. It may require large sums and top management strategic review. Chapter 8 discusses forward buying more fully.
Another class of buffer stock is that purchased in anticipation, but not certainty, of a price increase. In this case, the trade-off is between extra carrying costs and avoidance of higher purchase cost. This trade-off can be structured as shown in Figure 6–1. Obviously, intermediate levels of price increase and the timing of increases also will be identified. Other buffer stock trade-offs can be structured similarly.
Anticipation or certainty inventories are accumulated for a well-defined future need.
They differ from buffer stocks in that they are committed in the face of certainty and therefore have less risk attached to them. Seasonal inventories are an excellent example.
FIGURE 6–1 Decision to Inventory in Anticipation of a Possible Price Increase DECISION ALTERNATIVES DECISION VARIABLES OUTCOMES
Price increase avoided Carrying cost incurred
Carrying cost incurred Carrying cost avoided Price increase incurred Purch ase addition al inventory Price increases Price increases Price does n ot increase Price does not
increase No additional inventory 1 – P 1 – P P P
The stocking of commodities at harvest time for further processing during the year is a typical example. Reasons for anticipation stocks may include strikes, weather, shortages, or announced price increases.
The managerial decision is considerably easier than with buffer stocks because the cer-tainty of events makes probability estimates unnecessary. Unfortunately, in times of short-ages and rapid price increases, organizations may not be able to commit enough funds to meet the clear need for more anticipation stocks. Public organizations working under preestablished budgets may not be able to obtain authorization and funds. Many organiza-tions that are short of working capital may be similarly frustrated.
Decoupling inventories make it possible to carry on activities on each side of a major
process linkage point independently of each other. The amounts and locations of raw mate-rial, work-in-process, and finished goods decoupling inventories depend on the costs and increased operating flexibility benefits of having them.
All inventories perform a decoupling function, whether they be transit, cycle, buffer, or certainty inventories. When the prime purpose is to decouple, and space and time have been designed into the process to accommodate them, it is appropriate to recognize decoupling inventory as a unique category of its own. It gives flexibility and independence to both par-ties and is an excellent area for negotiations. Many contracts specify that a supplier main-tain a cermain-tain finished goods inventory. A finished goods inventory performs a decoupling function between the supplier’s manufacturing process and the customers’ process.
By examining the functions of inventory, it is clear that they are the result of many inter-related decisions and policies within an organization. At any time, any of the inventory func-tional types will be physically indistinguishable from the others. Frequently, a particular item
may serve many of the functions simultaneously. Why, then, classify inventories by func-tion? The answer lies in the degree of controllability of each class. Some inventories are essentially fixed and uncontrollable, whereas others are controllable. A management direc-tive to reduce total inventories by 20 percent, because of supply and marketing policies and prior commitments on cycle and seasonal inventories, could reduce decoupling and buffer inventories to nearly zero with potentially disastrous results.
The Forms of Inventory
Inventories may be classified by form as well as function; indeed, this classification is much more common. The five commonly recognized forms are (1) raw materials, pur-chased parts, and packaging; (2) work-in-process; (3) finished goods; (4) MRO items; and (5) resale items. Scrap or obsolete materials, although technically regarded as inventory, will not be considered here (see Chapter 11 dealing with investment recovery).
Raw materials, purchased parts, and packaging for manufacturers are stocks of the basic material inputs into the organization’s manufacturing process. As labor and other materials are added to these inputs, they are transformed into work-in-process invento-ries. When production is completed, they become finished goods. In general, the forms are distinguished by the amount of labor and materials added by the organization. The classification is relative in that a supplier’s finished goods may become a purchaser’s raw materials.
For resource industries, service organizations, and public organizations, MRO inventories may be substantial. In resource industries, a significant portion of such inventory may be maintenance or repair parts to support the heavy capital investment base. In resale organiza-tions, the main categories are goods for resale and inventories to maintain building and equipment. For many consumer goods industries, such as food and beverage, packaging rep-resents a major purchase inventory category with substantial environmental implications.
Inventory Function and Form Framework
Combining the five forms and five functions of manufacturing inventory gives the 25 types of inventory that make up the inventory profile of an organization. They are pre-sented in Figure 6–2 along with some of the managerial decision variables affecting each type. Not all inventory types will be present to the same extent in each organization; indeed, some may be completely absent. The 25 types make inventory control a more com-plex but a more easily focused task.
The behavior of inventories is a direct result of diverse policies and decisions within an organization. User, finance, production, marketing, and supply decisions can all have crucial influences on stock levels. Long-term fixed marketing or supply policies may render finished goods transit, raw materials transit, and cycle inventories quite inflexible, whereas short-term production scheduling may provide a great amount of flexibility of work-in-process invento-ries. Long-term supply contracts coupled with falling demand may lead to raw materials accumulation. Effective supply managers must recognize the behavior and controllability of each type of inventory in both the short and long terms. For effective supply management, they must also coordinate the policies and decisions of all functional areas.
Often managers use various informal rules of thumb in their decision making. A com-mon one is turnover in number of times per year. The rule of thumb would dictate that as
Raw Materials, Purchased Parts, and
Packaging Work-in-Process Finished Goods MRO Resale
1 2 3 4 5
Logistics Decisions
Design of supply Design of layout Design of Supplier location, Warehouse location, system, and materials plant transportation distribution, supplier handling location and mode, small transportation
location, system product shipments mode
transportation distribution
mode system
Product/Process Design Decisions
Order size, order Lot size, setup Distribution OEM or not and Order size
cost costs, lot order size and order cost
sizes
Management Risk Level Decisions and Uncertainty
Probability Probability Probability Probability Probability distributions of distributions distributions distributions of distributions of price, supply of machine of demand breakdowns demand associated and stockout, and product and during use with carrying and and carrying capabilities associated stockout costs
costs carrying and
stockout cost
Price/Availability/Decisions and Uncertainty, Seasonality, Capacity
Know future Capacity, Demand Maintenance Supply and demand supply and production patterns planning patterns and price demand price costs of hire, (seasonal) projects levels
levels fire, transfer, overtime, idle time, etc.
Production Control Decisions
Dependence/ Dependence/ Dependence/ Stock at vendor Stock at vendor independence independence independence or at user or buyer stock from supplier of successive from market
behavior production behavior operations 1 Transit (pipeline) 2 Cycle (EOQ, lots) 3 Buffer (uncertainty) 4 Anticipation (price) (shortage) 5 Decoupling (interdepen-dence) Inventory Function FIGURE 6–2
the use doubles, inventories should also double. However, a closer look must be taken at the components of that inventory.
Cycle inventories, produced in economic order lots (see the next section), increase pro-portionally to the square root of demand so, as demand doubles, cycle inventories should rise by a factor of only about 1.4. Ordering raw materials or storing them may have quite different cost structures from setting up machines, issuing production orders, or storing finished goods.
Transit inventories depend on supply and distribution networks. A change in the distri-bution system to accommodate extra volume could more than double or even reduce fin-ished goods transit inventory. Anticipation stocks vary with the pattern of demand, not demand itself. Decoupling inventories may remain unchanged. Buffer inventories may increase or decrease in response to demand and supply instabilities. Many of these effects will balance each other out, but the point remains: Rules of thumb are crude ways of con-trolling inventory levels. Even if they seem to work, managers never know if they are the best available. Any set of rules must be interpreted intelligently and reevaluated and tested periodically.
Companies that have adopted lean supply practices achieve inventory reductions by eliminating the root cause for the purpose of holding the inventory. For example, cycle inventories are brought down by reducing setup times; decoupling inventories are reduced by better planning and better quality; and safety stocks are lowered because of lower sup-ply and/or demand variability, reduced quality problems, or better on-time delivery per-formance. It is a continuing challenge to search for better ways to control inventories.
Managing Supply Chain Inventories
Decisions regarding what inventory to have in the supply chain and where to have it have important implications for customer service, working capital commitments, and ultimately profitability. Companies such as Dell, Wal-Mart, and Hewlett-Packard have demonstrated the opportunities to combine lean supply chains with high levels of customer service.
Supply chain inventory management involves managing information flows and estab-lishing operational design of the physical flow of the goods and services. Managing infor-mation flows with supply chain partners is not an easy task. While inforinfor-mation technology can be used to link customers quickly and efficiently, firms are frequently required to make major investments in new systems to ensure compatibility. (See Chapter 4 for a more detailed examination of information systems and information technology issues in supply chain management.)
However, coordinating information technology standards and software compatibility is just part of the challenge. Because most suppliers frequently deal with multiple customers, as opposed to focusing on a dominant downstream supply chain partner, issues relating to confidentiality must be addressed, affecting what information should be shared and when it should be communicated.
Operational design issues relate to production and fulfillment activities and can affect performance factors such as lead times, quality, and lot sizes. For example, flexible man-ufacturing processes that can respond quickly to customer orders may allow reductions in safety stock. Identifying appropriate modes of transportation is also important. Rail may
provide the lowest cost, but trucking provides faster door-to-door service and opportuni-ties to reduce transit inventories.
Finally, inventory fulfillment policies should take into account market conditions and the impact on supplier operations. Broad policies such as “we keep four weeks of inven-tory for all A items” ignores variability of demand or supply for product groups or fami-lies. It may be necessary to develop inventory level decision rules within group classifica-tions to ensure that appropriate stocks are maintained.
Order policies based on percentage of total demand can lead to large fluctuations in demand at the supplier level, known as the “bullwhip effect.” It can be addressed by shar-ing forecasts with suppliers so that they can plan production and have appropriate inven-tory available while keeping their costs low.
ABC CLASSIFICATION
A widely used classification of both purchases and inventories is based on monetary value. In the 19th century, the Italian Vilfredo Pareto observed that, regardless of the country studied, a small portion of the population controlled most of the wealth. This observation led to the Pareto curve, whose general principles hold in a wide range of situations. In materials management, for example, the Pareto curve usually holds for items purchased, number of suppliers, items held in inventory, and many other aspects. The Pareto curve is often called the 80-20 rule or, more usefully, ABC analysis, which results in three classes, A, B, and C, as follows when applied to inventory:
Class Percentage of Total Percentage of Total Dollars
Items in Inventory Tied up in Inventory
A 10 70–80
B 10–20 10–15
C 70–80 10–20
These percentages may vary somewhat from organization to organization, and some organizations may use more classes. The principle of separation is very powerful in mate-rials management because it allows concentration of management efforts in the areas of highest payoff. For example, a manufacturer with total annual purchases of $30.4 million had the following breakdown:
Number of Percentage of Annual Purchase Percentage Annual Class
Items Items Value Purchase Volume
1,095 10.0% $21,600,000 71.1% A
2,168 19.9 5,900,000 19.4 B
7,660 70.1 2,900,000 9.5 C
Total dollar investment (percent) Number of items (percent) 100 90 75 20 50 100 Intermediate dollar investment “B” items Low dollar investment “C” items High dollar investment “A” items FIGURE 6–3 ABC Classification of Inventory
A similar analysis of the organization’s inventories would be expected to show a simi-larly high portion of total value from a relatively small number of items.
Purchase value is a combination of unit price and number of units, so it is not sufficient to classify either high-priced or high-unit-volume items as A’s on that basis alone. Annual value (e.g., Unit value ⫻ Annual value ⫽ Total annual value) must be calculated and a classification into three groups on this basis is a good starting point (see Figure 6–3).
How can a supply manager use such a classification? It pays to spend far more mana-gerial time and effort on A and B items than on C items. Because supply assurance and availability are usually equally important for all items, it is common to manage C items by carrying inventories, by concentrating a wide variety of requirements with one or a few suppliers, by arranging stockless buying agreements or systems contracting, by using pro-curement cards, by exploiting e-catalogues, and by reviewing the items infrequently. These techniques reduce documentation and managerial effort (for most items) but maintain high service coverage.
A items are particularly critical in financial terms and are, therefore, barring other considerations, normally carried in small quantities and ordered and reviewed fre-quently. B items fall between the A and C categories and are well suited to a systematic approach with less frequent reviews than A items. It should be noted that some B or C items may require A care because of their special nature, supply risk, or other considerations.
COSTS OF INVENTORIES
Because of the high cost of carrying inventory, many systems have been developed to reduce stocks. Japanese manufacturers have spearheaded lean supply chain practices, including just-in-time systems. Nevertheless, it is useful to understand the nature and costs of inventories so that appropriate policies and procedures can be developed for specific organizational needs. North American organizations have begun to rely heavily on material requirements planning systems that have similar goals of reducing inventories wherever possible by having accurate, timely information on all aspects of the users’ requirements, thorough coordination of all departments, and rigorous adherence to the system.
For every item carried in inventory, the costs of having it must be less than the costs of not having it. Inventory exists for this reason alone. Inventory costs are real but are not easy to quantify accurately. The relevance of cost elements in a given situation depends on the decisions to be made. Many costs remain fixed when the order size of only one item is doubled, but the same costs may well become variable when 5,000 items are under con-sideration. The main types of inventory costs are described below.
Carrying, holding, or possession costs include handling charges; the cost of storage
facilities or warehouse rentals; the cost of equipment to handle inventory; storage, labor, and operating costs; insurance premiums; breakage; pilferage; obsolescence; taxes; and investment or opportunity costs. In short, any cost associated with having, as opposed to not having, inventory is included.
The cost to carry inventory can be very high. For example, recent estimates of the annual cost to carry production inventory ranged from 25 to 50 percent of the value of the inventory. Many firms do not do a very good job of estimating carrying costs. While there are several methods for calculating inventory carrying costs, the basic elements are (1) capital costs, (2) inventory service costs, (3) storage space costs, and (4) inventory risk costs.1
Once the firm has estimated its carrying costs as a percentage of inventory value, annual inventory carrying costs can be calculated as follows:
(Carrying cost per year) ⫽ (Average inventory value)
⫻ (Inventory carrying cost as a % of inventory value) Average inventory value ⫽ (Average inventory in units) ⫻ (Material unit cost)
CC⫽ Q/2 ⫻ C ⫻ I
where CC ⫽ Carrying cost per year
Q ⫽ Order or delivery quantity for the material, in units C ⫽ Delivered unit cost of the material
I ⫽ Inventory carrying cost for the material, as a percentage
of inventory value
1Doug M. Lambert, James R Stock, and Lisa M. Ellram, Fundamentals of Logistics Management,
Ordering or purchase costs include the managerial, clerical, material, telephone,
mail-ing, fax, e-mail, accountmail-ing, transportation, inspection, and receiving costs associated with a purchase or production order. What costs would be saved by not ordering or by combin-ing two orders? Header costs are those incurred by identifycombin-ing and placcombin-ing an order with a supplier. Line item costs refer to the cost of adding a line to a purchase order. Most orders will involve one header and several line item costs. Electronic data interchange (EDI) and Internet-based ordering systems try to reduce ordering or purchase costs significantly as well as reduce lead time at the same time.
Setup costs refer to all the costs of setting up a production run. Setup costs may be
sub-stantial. They include such learning-related factors as early spoilage and low production output until standard rates are achieved as well as the more common considerations, such as setup, employees’ wages and other costs, machine downtime, extra tool wear, parts (and equipment) damaged during setup, and so on. Both the purchaser’s and vendors’ setup costs are relevant. It should be pointed out that the reduction of setup costs and times per-mits smaller production runs and hence smaller purchaser order quantities and more fre-quent deliveries.
Stockout costs are the costs of not having the required parts or materials on hand when
and where they are needed. They include lost contribution on lost sales (both present and future), changeover costs necessitated by the shortage, substitution of less suitable or more expensive parts or materials, rescheduling and expediting costs, labor and machine idle time, and so on. Often, customer and user goodwill may be affected, and occasionally penalties must be paid. The impact of stockouts on customers will vary. In a seller’s mar-ket, an unsatisfied customer may not be lost as easily as in a buyer’s market. In addition, each individual customer will react differently to a shortage.
In many organizations, stockout costs are very difficult to assess accurately. The gener-al perception, however, is that stockout costs are substantigener-al and much larger than carrying costs. Stockout costs, here discussed as they relate to inventory, are similar for late deliv-ery or quantity shortfalls.
Variations in delivered costs are costs associated with purchasing in quantities or at
times when prices or delivery costs are higher than at other quantities or times. Suppliers often offer items in larger quantities or at certain times of the year at price and transportation discounts. Purchases in small quantities or at other times may result in higher purchase and transportation costs, but buying in larger quantities may result in significantly higher holding costs. The quantity discount problem will be discussed in Chapter 9.
Many inventory costs may be hard to identify, collect, and measure. One can try to trace the individual costs attributable to individual items and use them in decision mak-ing. Usually such costs will be applicable to a broader class of items. A second approach is to forecast the impact of a major change in inventory systems on various cost cen-ters. For example, what will be the impact on stores of a switch to systems contracting or vendor-managed inventories for some low-value items? Or what would be the impact of a just-in-time system on price, carrying, ordering, and stockout costs? Because most inventory models are based on balancing carrying, order, and stockout costs to obtain an optimal order and inventory size, the quality and availability of cost data are important considerations.
FORECASTING
Inventory management is complicated by the rapidly changing environment within which inventory and supply planning is carried out. Inventories always seem to be too big, too small, of the wrong type, or in the wrong place. With changing economic conditions, what is too little in one period may easily become too much in the next.
Forecasting is very much a part of the supply management picture and directly affects both quantity and delivery. Forecasts of usage, supply, market conditions, technology, price, and so on, are always necessary to make good decisions. The problem is how to plan to meet the needs of the future, which requires answers to questions such as Where should the responsibility for forecasting future usage lie? Should the supply management group be allowed to second-guess sales, production, or user forecasts? Should suppliers be held responsible for meeting forecasts or actual requirements? Should the supply manager be held responsible for meeting actual needs or forecasts?
In many organizations, the need for raw materials, services, parts, and subassemblies is usually derived from a sales forecast, which is the responsibility of marketing. In some service organizations and public agencies, the supply function often must both make fore-casts and acquire items. In resale, the buyer may have to assess the expected sales volume (including volumes at reduced prices for seasonal goods), as well as make purchase com-mitments recognizing seasons. Whatever the situation, missed forecasts are quickly for-gotten but substantial overages or shortages are long remembered. Supply managers are often blamed for overages or shortages no matter who made the original forecast or how bad the forecast was.
The real problem with forecasts is their unreliability. Forecasts will usually be wrong, but will they exceed or fall short of actual requirements and by how much? Continuous improvement methods can be applied to forecasting by tracking forecast accuracy and tak-ing steps to eliminate root causes of forecast error.
To a supplier, a substantial variation from forecast may appear as a procurement ploy. If demand falls below forecast, the supplier may suspect that the original forecast was an attempt to obtain a favorable price or other concessions. Should demand exceed forecast, supplier costs may well increase because of overtime, rush buying, and changed produc-tion schedules. Purchasers need to share forecast uncertainty regularly with suppliers so that their quotations may take uncertainty into account. Such sharing is obviously impos-sible if buyers themselves are not aware of the uncertainty and its potential impact on the supplier. Forecasts also should be updated regularly.
Forecasting Techniques
There are many forecasting techniques that have been developed and an extensive litera-ture that describes them. This section will review some briefly but will not describe any technique in detail.
Quantitative forecasting attempts to use past data to predict the future. One class of quantitative forecasting techniques, causal models, tries to identify leading indicators, from which linear or multiple regression models are developed. A carpet manufacturer might use building permits issued, mortgage rates, apartment vacancy rates, and so on, to predict carpet sales. Standard computer programs are used to develop and test such mod-els. Chosen indicators are usually believed to cause changes in sales, although even good
models do not prove a cause-and-effect relationship. Indicator figures must be available far enough ahead to give a forecast that allows sufficient time for managerial decisions.
A second quantitative forecasting class assumes that sales (or other items to be forecast) follow a repetitive pattern over time. The analyst’s job in such time series forecasting is to identify the pattern and develop a forecast. The six basic aspects of the pattern are constant value (the fluctuation of data around a constant mean), trend (systematic increase or decrease in the mean over time), seasonal variations, cyclical variations, random varia-tions, and turning points. Time series forecasting techniques include simple moving aver-ages, weighted moving averaver-ages, and exponential smoothing.
One of the most common classes is the qualitative approach of gathering opinions from a number of people and using these opinions with a degree of judgment to give a forecast. Market forecasts developed from the estimates of sales staff, district sales managers, and so on, are an example. Such forecasts may also flow from the top down. The Delphi tech-nique is a formal approach to such forecasting. Collective opinion forecasts lack the rigor of more quantitative techniques but are not necessarily any less accurate. Often, knowl-edgeable people with intimate market knowledge have a “feel” that is hard to define but that gives good forecasting results.
DETERMINING ORDER QUANTITIES AND INVENTORY LEVELS
In the following sections, some relatively simple theoretical models used to determine order quantities and inventory levels are discussed. The application of these models depends on whether the demand or usage of the inventory is dependent or independent. Dependent demand means the item is part of a larger component or product, and its use is dependent on the production schedule for the larger component. Hence, dependent demand items have a derived demand. Independent demand means the usage of the inventory item is not driven by the production schedule and is determined directly by customer orders, the arrival of which is independent of production scheduling decisions.
Fixed-Quantity Models
The classic trade-off in determining the lot sizes in which to make or buy cycle invento-ries is between the costs of carrying extra inventory and the costs of purchasing or making more frequently. The objective of the model is to minimize the total annual costs. In the very simplest form of this model, annual demand (R), lead time (L), price (C), variable order or setup cost (S), and holding cost percentage (K) are all constant now and in the future. When inventory drops to the reorder point (P), a fixed economic order quantity (Q) is ordered. Back orders and stockouts are not allowed.
Total cost is given as purchase cost, plus setup or order cost, plus holding cost, or
Using differential calculus, the minimum value of Q (also known as the EOQ) is found at
Qopt⫽
冑
2RS KC TC⫽ RC ⫹RS Q ⫹ QKC 2Cost
EOQ Order Size
Total ca rrying and ord er cost Carrying cost Ordering cost FIGURE 6–4 Material Carrying and Order Costs Inventory (units) Time L = Lead time
EOQ = Order quantity • = Reorder point, P P EOQ L FIGURE 6–5 Simple Fixed Quantity Model
This is the value at which order cost and carrying cost are equal. Figures 6–4 and 6–5 show how costs vary with changes in order size and how inventory levels change over time using this model. As an example of the use of the model, consider the following:
R⫽ Annual demand ⫽ 900 units C⫽ Delivered purchase cost ⫽ $45/unit K⫽ Annual carrying cost percentage ⫽ 25 percent
S ⫽ Order cost ⫽ $50/order
Qopt ⫽ A 2RS KC ⫽ A 2 ⫻ 900 ⫻ $50 .25 ⫻ $45 ⫽ 89 units
To determine the reorder point P, it is necessary to know the lead time L, which is 10 work-ing days. Assumwork-ing 250 workwork-ing days per year, the reorder point can be calculated as:
This model suggests an order of 89 units whenever the inventory drops to 36 units. The last unit will be used just as the next order arrives. Average inventory will be 89/2 ⫽ 44.5 units. In practice, it might be advisable to keep some safety stock that must be added to the average inventory. Also, the bottom of the cost curve (see Figure 6–4) is relatively flat (and asymmetric) so that there might be advantages in ordering 96 (eight dozen) or 100 units instead. In this case, these quantities would cost approximately an additional $2.50 and $6.25, respectively, out of a total annual cost of about $41,500. These costs are the addi-tional ordering and carrying costs resulting from the addiaddi-tional units ordered.
The assumptions behind the EOQ model place some rather severe restrictions on its general applicability. Numerous other models have been developed that take into account relaxation of one or more of the assumptions. The reader may wish to refer to books on inventory management for a more extensive discussion.
Fixed-Period Models
In many situations, ordering every so often rather than whenever the stock reaches a cer-tain level is desirable from an operations viewpoint. The scheduling of workload is easier when employees can be assigned to check certain classes of inventory every day, week, month, and so on.
In fixed-quantity models, orders are placed when the reorder point is reached, but in fixed-period models, orders are placed only at review time. The inventory level, therefore, must be adjusted to prevent stockouts during the review period and lead time.
Fixed-period models attempt to determine the optimal order period (O). The minimum cost period can be determined as follows. There are R/O cycles per year and, therefore, T (the frac-tion of the year) is O/R. This value of O can then be substituted in the EOQ formula to give:
Using the values given for the previous example:
For a year of 250 working days, this is 25 working days, or once every five weeks. The optimum order quantity, EOQ, is RTopt or 90 units. This is the same result as before. Organizational procedures may make a review every four weeks or monthly more attrac-tive. In this case, T would change to 0.08 and O to 72 at an additional cost of $23.77 per year over the optimum value.
Probabilistic Models and Service Coverage
The aforementioned models assume that all parameters are known absolutely and do not change over time. It is far more common to have some variability in demand, lead times,
Topt ⫽
A
2 ⫻ 50
900 ⫻ 0.25 ⫻ 45 ⫽ 0.1 or 10 times per year
ToptR ⫽ A 2RS KC or Topt ⫽ A 2S RKC P ⫽ L ⫻ Daily demand ⫽ L ⫻ R 250 ⫽ 10 ⫻ 900 250 ⫽ 36 units
supply, and so on. Probabilistic lot size models take these variations into account. The models are more complex than the deterministic ones above, but the probabilistic approach gives more information on likely outcomes.
Buffer or Safety Stocks and Service Levels
For buffer or safety stocks, the major decision variable is how much buffer inventory to carry to give the desired service coverage. The service coverage can be defined as the por-tion of user requests served. If there are 400 requests for a particular item in a year and 372 were immediately satisfied, the service coverage would be 372/400 ⫽ 93 percent.
Service coverage also can be defined as the portion of demand serviced immediately. If the 372 orders in the above example were for one unit each and the 28 other, unserviced ones, for five units each, the total yearly demand would be for 372 ⫹ 140 ⫽ 512 units. The service coverage would be 372/512, or 73 percent. It is obviously important to understand exactly what is meant by service coverage in an organization.
Holding a large inventory to prevent stockouts, and thus to maintain a high service cov-erage, is expensive. Similarly, a high number of stockouts are costly. Stockout costs are often difficult and expensive to determine but nevertheless real. Setting service coverage requires managers to make explicit evaluations of these costs so that the appropriate bal-ance between carrying and stockout can be achieved.
Trade-offs between holding inventory and stocking out can be assessed quantitatively if accurate data are available, such as inventory holding costs, stockout costs, and demand or supply variability. However, because of the expense and difficulty of obtaining such costs and probability estimates for individual items, managers often set service coverage arbi-trarily, typically about 95 percent, implying a ratio of stockout to holding costs of about 19 to 1. In practice, setting and managing service coverage is difficult because of the com-plexity of item classification, function, and interdependence. Service coverage need not be as high on some items as on others, but an item that may be relatively unimportant to one customer may be crucial to another. If the customer is an assembly line, low service cov-erage on one component makes higher service covcov-erage on others unnecessary. Also, some customers will tolerate much lower service coverage than will others. Within an organiza-tion, internal departments are sometimes regarded as customers, and service coverage attained is one measure of supply management’s effectiveness. It is useful to stress that service coverage and inventory investment are closely related. It becomes expensive to achieve high service coverage, and a high service coverage expectation without the neces-sary financial backup can lead only to frustration. Supply is, of course, also interested in service coverage as it pertains to supplier performance.
Service coverage can be used to determine the appropriate level of buffer inventory. The situation is shown in Figures 6–6 and 6–7. Four situations can arise as shown from left to right in Figure 6–6.
1. Only some of the buffer inventory was used.
2. No buffer inventory remained, but there was no stockout. 3. There was a stockout.
4. All the buffer inventory remained.
Figure 6–7 starts with an EOQ model except that it is not certain how many units will be used between placing and receipt of an order. Figure 6–7 targets desired service coverage
Inventory (units) Buffer inventory L Time 3 1 2 4 Q P B 0 Expected distribution of usage during lead time
Most likely usage level Service coverage level— 95 percent of area under distribution curve above this point Time L P B 0 Inventory (units) FIGURE 6–6 Fixed-Order-Quantity Model with Buffer Inventory and Variation in Demand FIGURE 6–7 Determination of Buffer Inventory to Achieve Desired Coverage
at 95 percent, given the standard deviation of average daily demand, an assumption of a normal demand distribution, and a most-likely usage level.
The complexity of probabilistic models increases greatly when lead times, usable quan-tities received, inventory shrinkage rates, and so on, also vary under conditions of uncer-tainty, when nonnormal distributions are observed, and when the variations change with
time. Simulation models and other more advanced statistical techniques can be used to solve these complex situations.
MATERIAL REQUIREMENTS PLANNING (MRP)
One of the assumptions behind the lot-sizing models just described is that demand for the item being purchased or made is independent of all other demands. This situation is true for most manufacturers’ finished goods. However, subassemblies, raw materials, and parts do not exhibit this independence. Demand for these items is dependent on the assembly schedule for finished goods. For example, each car assembled needs one windshield, one steering wheel, but four tires plus a spare. Similarly, many MRO items depend on mainte-nance schedules. Recognition of the existence of demand dependence lies behind the tech-nique known as material requirements planning (MRP).
MRP systems attempt to support the activities of manufacturing, maintenance, or use by meeting the needs of the master schedule. In order to determine needs, MRP systems need an accurate bill of materials for each final product or project. These bills can take many forms, but it is conceptually advantageous to view them as structural trees.
Not all organizations have been successful in implementing MRP systems. Implementation may take years and involve major investments in training, data prepara-tion, and organizational adjustments as well as in computer software and hardware. However, most organizations with successfully implemented systems feel that the reduced inventory, lead times, split orders and expediting, increased delivery promises met, and discipline resulting from MRP make the investment worthwhile. MRP systems allow rapid replanning and rescheduling in response to the changes of a dynamic environment.
MRP Inputs
There are three basic MRP inputs. The whole system is driven by the requirements fore-cast by time period (the master production schedule), which details how many end items are to be produced during a specified time period. The structured bill of materials (BOM) is the second input. The BOM uses information from the engineering and/or process records to detail the subcomponents necessary to manufacture a finished item. The third input is the inventory record, which contains information such as open orders, lead times, and lot-size policy so that the quantity and timing of orders can be calculated.
The logic of MRP allows simultaneous determination of how much and when to order. The calculations hinge on the assumptions that all information is accurate and known with certainty and that material will be ordered as required. MRP systems can help production meet schedules, avoid equipment downtime, adjust to order quantity changes, and identify the need to expedite late orders.
MRP Lot Sizing
Lot-sizing rules must be assigned to each item before the MRP plan can be computed. The selection of a lot-sizing rule is important because it affects inventory holding costs and operations costs, such as setup costs.
The four basic lot-sizing rules are lot-for-lot (L4L), economic order quantity (EOQ), least total cost (LTC), and least unit cost (LUC).
Lot-for-lot is the most common technique. It does not take into account setup costs, car-rying costs, or capacity limitations. Lot sizing is based on producing net requirements for each period.
The EOQ lot-sizing technique balances inventory holding and setup (or order) costs. It uses the EOQ formula to set lot sizes, which requires estimates for annual demand, inven-tory holding costs, and setup (or order) costs.
The least-total-cost method compares the cost implications of various lot-sizing alter-natives and selects the lot size that provides the least total cost. The LTC method is a dynamic lot-sizing technique.
The least-unit-cost method is also a dynamic lot-sizing method. It factors inventory holding and setup (or order) costs into the unit cost.
Lot sizing is a difficult issue when using MRP. Because most lost-sizing techniques require cost and annual demand information, accuracy of the data used will determine the effectiveness of the decisions made.
Modern MRP Systems
With advances in information systems technology, a number of improvements have been made to MRP systems that can help managers with planning and coordinating production and supply. One significant advance in MRP systems has been the addition of capacity requirements planning (CRP). CRP performs a similar function for manufacturing resources that MRP performs for materials. When the MRP system has developed a mate-rials plan, CRP translates the plan into the required human and machine resources by workstation and time bucket. It then compares the required resources against a file of avail-able resources. If insufficient capacity exists, the manager must adjust either the capacity or the master production schedule. This feedback loop to the master production schedule results in the term closed-loop MRP to describe this development.
The CRP module is often linked to a module that controls the manufacturing plan on the shop floor. The goal is to measure output by work center against the previously deter-mined plan. This information allows identification of trouble spots and is necessary on an ongoing basis for capacity planning.
Manufacturing resource planning systems (MRP II) links the firm’s planning processes with the financial system. MRP II systems combine the capability of “what if ” production scenario testing with financial and cash flow projections to help achieve the sales and prof-itability objectives of the firm.
Many companies use enterprise resource planning systems (ERP), which include MRP modules, to integrate business systems and processes. ERP systems are software that allows all areas of the company—manufacturing, finance, sales, marketing, human resources, and supply—to combine and analyze information. ERP can provide a link from customer orders through the fulfillment processes. Therefore, fully implemented ERP systems allow supply to be aware of orders received by sales, manufacturing to be aware of raw material delivery status, sales to understand product or service lead times and availability, and financial trans-actions and commitments to be communicated directly into the financial accounting sys-tem. A thorough discussion of e-supply applications is provided in Chapter 4.
Consequently, a modern MRP system is thus a lot more than simply a device to calculate how much material to obtain and when to do so. It is an information and communication sys-tem that encompasses all facets of the organization. It provides managers with performance
measures, planned order releases (purchase orders, shop orders, and rescheduling notices), and the ability to simulate a master production schedule in response to proposed changes in production loading (by, for example, a new order, delayed materials, a broken machine, or an ill worker). The integration required of such systems forces organizations to maintain highly accurate information, abandon rules of thumb, and use common data in all departments. The results are reduced inventory levels, higher service coverage, ready access to high-quality information, and, most importantly, the ability to replan quickly in response to unforeseen problems.
Supply Implications of MRP
The tight control required by MRP means that supply records regarding quantities, lead times, bills of material, and specifications must be totally accurate and tightly controlled. The on-time delivery required of MRP needs cooperation from suppliers. Purchasers there-fore, must educate their suppliers to the importance of quantity, quality, and delivery prom-ises to the purchaser. Such education should enable purchasers to reduce their safety stock.
Many MRP systems have purchasing modules that perform many of the routine cleri-cal supply tasks, making supply’s job more analyticleri-cal and strategic. The long-term nature of the MRP planning horizon, typically a year, means longer-term planning for supply and the negotiation of more long-term contracts with annual volume-based discounts. These contracts have more frequent order release and delivery, often in nonstandard lot sizes. Quantity discounts on individual orders become less relevant in favor of on-time delivery of high-quality product.
Purchasers must understand the production processes both of their own organizations and of their suppliers. The tighter nature of MRP-using organizations increases the respon-sibility on supply to be creative and flexible in providing assistance to minimize the inevitable problems that will occur in supply lines. The MRP system provides purchasers with an information window to production scheduling so they are better able to use judg-ment in dealing with suppliers. Because of the reduced resource slack that results from MRP, purchasers must incorporate de-expediting into their activities as well as the more usual expediting role. The integrating and forward-looking nature of MRP means an increase in specialization in the supply department. For example, the buyer-planner is a person who uses MRP to assure smooth functioning of the interface between the purchas-er’s and supplipurchas-er’s processes. Also, specialization will be based on finished product line outputs rather than on raw material inputs.
In contrast to MRP, just-in-time production methods can achieve many of the goals of MRP in conjunction with MRP or on a stand-alone basis.
LEAN SUPPLY AND JIT
Lean supply is an approach where relationships with suppliers are managed based on a long-term perspective so as to eliminate waste and add value. It is based on Japanese manufactur-ing concepts pioneered by Toyota. Lean systems have been adopted in many organizations, under a variety of names, such as the Delphi Manufacturing System at the automotive parts maker Delphi Corporation. However, the Toyota production system is generally recognized as the best model of lean operations.
The most popular system that incorporates the lean philosophy is just-in-time (JIT). Under a JIT system, components, raw materials, and services arrive at work centers exactly as they are needed. This feature greatly reduces queues of work-in-process inventory. The goals of JIT production are similar to those of MRP—providing the right part at the right place at the right time—but the ways of achieving these goals are radically different and the results impressive. Whereas MRP is computer based, JIT is industrial engineering based. JIT focuses on waste elimination in the supply chain, and there are many JIT features that are good practice in any operation, public or private, manufacturing or nonmanufacturing.
In JIT, product design begins with two key questions: Will it sell? and Can it be made easily? These questions imply cooperation between marketing and operations. Once these questions have been answered positively, attention turns to design of the process itself. The emphasis is on laying out the machines so that production will follow a smooth flow. Automation (often simple) of both production and materials handling is incorporated wherever possible. Frequently, U-shaped lines are used, which facilitate teamwork, worker flexibility, rework, passage through the plant, and material and tool handling. In process design, designers strive to standardize cycle times and to run a constant product mix, based on the monthly production plan, through the system. This practice makes the production process repetitive for at least a month.
The ability to smooth production implies very low setup and order costs to allow the very small lot sizes, ideally one. JIT treats setup and order costs as variable rather than as the fixed costs implied by the EOQ equation. By continuously seeking ways to reduce setup times, the Japanese were the first to have managed impressive gains. Setups, which traditionally required three to four hours, have been reduced to less than a minute in some JIT facilities. These dramatic improvements have been achieved by managerial attention to detail on the shop floor; the development and modification of special jigs, fixtures, tools, and machines; and thorough methods training. Setup simplification is aided by their will-ingness to modify purchased machines, their acquisition of machines from only a few sources, and their frequent manufacture of machines in-house—often special purpose, light, simple, and inexpensive enough to become a dedicated part of the process. Order costs, conceptually similar to setup costs, have similarly been reduced.
One of the necessary corollaries of having components and materials arrive just as they are needed is that the arriving items must be perfect. In JIT, a number of interrelated prin-ciples are used to ensure high-quality output from each step in the production process.
First, responsibility for quality rests with the maker of a part, not with the quality con-trol department. In addition, workers and managers habitually seek improvement of the status quo, striving for perfection. Quality improvements are often obtained from special projects with defined goals, measures of achievement, and endings. Also, workers are responsible for correcting their own errors, doing rework, and so on.
Second, the use of production workers instead of quality control inspectors builds qual-ity in rather than inspecting it in. This feature and the small lot sizes allow every process to be controlled closely and permit inspection of every piece of output. Workers have authority to stop the production line when quality problems arise. This aspect signifies that quality is a more important goal of the production system than is output.
Third, JIT insists on compliance to quality standards. Purchasers reject marginally unacceptable items and visit supplier plants to check quality on the shop floor for them-selves. Because such visits are frequent, JIT manufacturers document their quality in
easily understood terms and post the results in prominent places. This process forces the manufacturer to define quality precisely.
JIT control of quality is helped by the small lot sizes that prevent the buildup of large lots of bad items. JIT tends to have excess production capacity so that the plants are not stressed to produce the required quantities. In the same vein, machines are maintained and checked regularly and run no faster than the recommended rates. Plant housekeeping is generally good. The quality control department acts as a quality facilitator for production personnel and suppliers, giving advice in problem solving. This department also does some testing, but the tests tend to be on final products not easily assignable to a single produc-tion worker, or special tests requiring special equipment, facilities, knowledge, or long times not available to personnel on the shop floor. Automatic checking devices are used wherever possible. Where necessary, sample lots are chosen to consist of the first and last units produced rather than a larger, random sample. Analytical tools include the standard statistical techniques, often known by workers, and cause-and-effect diagrams to help solve problems.
JIT requires great dedication by both workers and managers to hard work and helping the organization. JIT workers must be flexible. They are trained to do several different jobs and are moved around frequently. The workers are responsible for quality and output. Workers continuously seek ways to improve all facets of operations and are rewarded for finding problems that can then be solved.
In summary, JIT is a mixture of a high-quality working environment, excellent indus-trial engineering practice, and a healthy focused factory attitude that operations are strate-gically important. The order and discipline are achieved through management effort to develop streamlined plant configurations that remove variability. The JIT system has often been described as one that “pulls” material through the factory rather than pushing it through. The use of a kanban system as a control device illustrates this point well.
Kanban Systems
Kanban is a simple but effective control system that helps make JIT production work. Kanban is not synonymous with JIT, although the term is often incorrectly so used and the two are closely related. Kanban is Japanese for “card”; the use of cards is central to many Japanese control systems, including the one at Toyota, whose kanban system has received much attention.
Kanban systems require the small lot size features of JIT and discrete production units. The systems are most useful for high-volume parts used on a regular basis. They are much less useful for expensive or large items that cost a lot to store or carry, for infrequently or irregularly used items, or for process industries that don’t produce in discrete units.
Two types of kanban systems exist: single card and double card. In double-card systems, two types of cards (kanban) exist: conveyance (C-kanban) and production (P-kanban). Single-card systems use only the C-kanban. The two-card system’s operation uses the following rules.
1. No parts may be made unless there is a P-kanban authorizing production. Workers may do maintenance, cleaning, or work on improvement projects until a P-kanban arrives rather than making parts not yet asked for. Similarly, C-kanban controls the transport of parts between departments.
2. Only standard containers may be used, and they are always filled with the prescribed small quantity.
3. There is precisely one C-kanban and one P-kanban per container.
The system is driven by the user department pulling material through the system by the use of kanban. The main managerial tools in this system are the container size and the num-ber of containers (and therefore kanban) in the system. The control is very precise, flexible, and responsive. It prevents an unwanted buildup of inventory. For example, the actual assembly of parts into a complete finished product provides the “pull” for more parts to be produced.
JIT and Inventory Management
Inventories often exist to cover up problems in supply or inside the organization. For exam-ple, a buffer inventory can protect a user from poor quality or unreliable delivery from a marginal supplier. In JIT, the deliberate lowering of inventory levels to uncover such mal-practices forces an organization to identify and solve the underlying problems or causes for high and undesirable inventories. This deliberate inventory reduction is often seen by some managers as a form of organizational suicide, a willingness to put continuity of sup-ply, service, or operation at risk. However, enough organizations have experimented with this concept (and survived) to show the merits of this practice. Diagrammatically, this low-ering of inventory levels is frequently shown as a seascape of inventory with sharp rocks of different heights underneath, representing the problems or malpractices that need to be exposed sequentially.
JIT Implications for Supply Management
JIT has become sufficiently entrenched as a concept that its applicability is not in ques-tion, only the extent to which it should be applied. Many companies are working closely with their suppliers to implement JIT.
There are a number of implications of JIT for supply management. One of the obvious includes the necessity to deal with suppliers of high and consistent quality and with reli-able delivery. This implies that concentrating purchases with fewer nearby suppliers may be necessary. The frequent delivery of small orders may require a rethinking of the inbound transportation mode. For example, it is normal to have a trucker follow a standard route daily to pick up, from 6 to 20 different suppliers, small lots in a specially designed side-loading vehicle. Having delivery arranged directly to the place of use eliminates double handling. Special moving racks designed for proper protection, ease of counting, insertion, and removal also help improve material handling. A lot of supplier training and coopera-tion is required to assist in the design and operacoopera-tion of an effective JIT system.
In the minimum sense, JIT can refer to arranging for delivery just before a requirement is needed. In this context, JIT has wide applicability beyond manufacturing—in public, service, and other nonmanufacturing organizations. Reliability of delivery reduces the need for buffer or safety stock, with the benefits that arise out of such inventory reduction. In JIT there is a close cooperation between supplier and purchaser to solve problems, and suppliers and customers have stable, long-term relationships. In keeping with the JIT philosophy, suppliers, usually few in number, are often located close to their customers to facilitate communication, on-time delivery of small lots of parts, low pipeline and safety
stocks, and low supply costs. The situation in many JIT companies is much like extensive backward vertical integration. The organizations have close coordination and systems inte-gration that smooth operations. The job of a purchaser in the JIT environment is that of a facilitator, negotiator, communicator, and innovator.
Conclusion
Supply chain effectiveness is totally dependent on the assurance that quality, quantity, and delivery are consistently perfect. Both quantity and delivery involve lot-sizing and inven-tory decisions that, in turn, affect costs, productivity, flexibility, and customer satisfaction. To complicate matters even further, uncertainty rears its ugly head and forecasts are unre-liable. Despite major advances such as MRP and JIT, the challenges of quantity and deliv-ery continue to occupy supply managers all over the world.1. Of what interest is ABC analysis?
2. What is a master production schedule and what role does it perform? 3. Why is it expensive to carry inventories?
4. In a typical fast-food operation, identify various forms and functions of inventory. How could total investment in inventories be lowered? What might be the potential conse-quences?
5. What are transit inventories?
6. What is a kanban and why is it used?
7. What problems do inaccurate usage forecasts create for buyers? For suppliers? 8. What is the difference between JIT and MRP?
9. Why would anyone prefer to use a fixed-period reordering model over a fixed-quantity one? 10. Describe sources of variability in the supply chain. How does variability increase supply
chain costs?
Questions
for
Review
and
Discussion
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