Global supply chains and distribution new competitive strategies project peropt
- 1. MIE 697Q: Logistics Global Supply Chains and Distribution Hewlett-Packard : DeskJet Printer Supply Chain TERM PROJECT Submitted by: Hasmik Mehranian
- 2. Table of Contents Page I. Abstract 3 II. Introduction 3 III. Project Definition 4 IV. Background_______ _6 V. Model Definition__ 6 VI. Model Formulation 7 VII. Cost Analysis 9 VIII Conclusion 11 IX. References 11 2
- 3. I. Abstract On average, a firm loses anywhere between 9 and 20 percent of its value over a six-month period due to supply chain problems, according to a Georgia Technical University study. That gives a lot of room for improvement of the Supply Chain performance in general and for cutting losses of companies of the system. Understanding mechanisms of relations in the global network of suppliers, manufacturers and distributors might help to rich the goal of the system: the merchandise is produced and distributed at the right quantities, to the right locations, and at the right time, in order to minimize system wide costs while satisfying service level requests. Supply Chains are very complex system and realization of what can go wrong and why, could be the first step in the process of its optimization. II. Introduction In a supply chain for a typical consumer product, even when consumer sales do not seem to varying much, there is pronounced variability in the retailers’ orders to the wholesalers. Orders to the manufacturer and to the manufacturers’ supplier spike even more. To solve the problem of distorted information, companies need to first understand what creates the bullwhip effect so they can counteract it. There are four major causes of the bullwhip effect: ·demand forecast updating ·order batching ·price fluctuation ·rationing and shortage gaming. Lets’ look closer at the impact of the demand forecast updating on creating a bullwhip effect. When a downstream operation places and order, the upstream manager processes that piece of information as a signal about future product demand. Based on this signal, the upstream manager readjusts his or her demand forecast and, the orders placed with the suppliers of the upstream operation. This demand signal processing procedure is the major contributor to the bullwhip effect. For example, if you are a manager who has to determine how much to order from a supplier, you use a simple method to do demand for testing. The order you sent to the supplier reflects the amount you need to replenish the stocks to meet the requirements of future demand, as well as the necessary safety stock. The future demands and the associated safety stocks are updated every revision period. With long lead times you usually have weeks of safety stocks. The result is that the fluctuations in the order quantities over time can be much greater than those in the demand data. Innovative companies in different industries have founded that they can control the bullwhip effect and improve the supply chain performance by coordinating information and planning along the supply chain. One of such companies is Hewlett-Packard. 3
- 4. HP produces computational and measurement products whose supply chain includes manufacturing integrated circuits, board assembly, final assembly, and delivery to customers. Of HP’s product groupings, computers and peripherals provide the largest percentage of net revenue. 77.00% 3.00%3.00% 6.00% 11.00% computers and peripherals test and measurement medical components analytical Figure 1. Hewlett Packard’s new revenues by product groups. In the late 1080s’ Hewlett-Packard faced inventories counting in to the billions of dollars and alarming customer dissatisfaction with ifs order fulfillment process. III. Project Definition For the purposes of this project we’ll use term Supply Chain to describe the network of manufacturing (HP’s Vancouver plant) and distribution center (HP’s European Distribution Center). The DeskJet Plus is one of most successful printers manufactured by the Vancouver Division of HP. The final stage of manufacturing process is the final assembly and test. To localize the DeskJet Printers for different countries, HP packages the appropriate power supply module (with the correct voltage and plugs) and the appropriate manual with the printer. We will refer to this design of the process as factory-localization. Since the factory produces finished printers for all DeskJet Printer modifications, DCs became an inventory stocking points with large safety stocks to meet a target off-the –shelf fill rate, where the replenishment of the product came from manufacturing. Under this Supply Chain design, HP ships the finished goods to the European distribution center by sea, with a transit time of about a month. Because of this long lead time, the DC should maintain high level of safety stocks, to ensure high level of service for the customers and respond to the fluctuations of the demand for different versions of the DeskJet Printers. Two major sources of uncertainty can affect such a Supply Chain: 1. Internal process; 4
- 5. 2. Demand. Internal process variability can cause delays in replenishing stocks at the DC. The second one, the uncertainties of demand in conjunction with the long lead times can cause a “bullwhip” effect. From the analysis of Common Pitfalls of Global Supply Chains we can outline three main arias which can effect the performance of the system: · inefficient information systems – forecasting errors; · operational problems – incomplete shipment method analysis; · strategic and design related – product/process design without consideration of the Supply Chain. First we are going to explore the possibilities of the alternative shipping method, to reduce the shipment lead times between manufacturer and the DC. The air shipment is costly, but it may be worth considering, since by drastically reducing the lead times it will reduce the safety stock inventory at the DC, and increase the flexibility of the manufacturing to respond to the fluctuations of the demand for different modifications of the product. Second we will consider new product localization design, which can take advantage of the “risk pulling” effect to buffer against uncertainty and impact of poor forecast. Board Euro DC US Version European Version Far East Version Unlocalized Printer US Version Localization Materials Motors Flex cables Key pad board Plastic mechanics Plastic skin Carriage motor Plastic gears Head Driver Logic Board to the US Distribution Center localization performed at the European DC to the European DC assembly performed at the factory. Figure 2. The manufacturing process and the localization strategies for the DeskJet printers. 5
- 6. IV. Background Eppen (1979) studied the so-called “risk pooling effects”, namely the effects of inventory-costs savings achieved by grouping retailers, or demand. Assume customer demands are normally distributed with mean µi and a standard deviation σi for customer i. Then the expected total inventory cost under the decentralized mode for n retailers is K σ∑= n i 1 i. If the demands of the n retailers independent, the optimal cost under a centralized mode can be express by K ∑= n i 1 σi 2 , which is less than K σ∑= n i 1 i, where K is a constant depending on the holding and penalty costs and the standard normal loss function. V. Model Definition There are two alternatives to consider for the manufacturing and distribution of the DeskJet Printer: 1. fully localized at factory US and European standard printers; 2. a fully localized US version and a generic product without the power supply and manuals, to be shipped to Europe to be localized there. Factory Localization System DC Localization System • • • • • • • • • • • • • • • • S S21 DC 1 2 Supplier DC il + C Localization Sl C2l1l S21 Supplier Figure 3. Two alternatives for HP DeskJet Printers. 6
- 7. VI. Model Formulation We consider two systems: Factory Localization and DC Localization systems. We’ll consider both of them to be standard periodic review, order up to systems. We’ll also assume that the demand per review period is stationary and normally distributed; demands in different time periods are independent; demands for different product versions of the printer are statistically independent; locations of the supplier and the retailers are known; the suppliers have infinite capacity. Factory Localization system consists of one supplier, the factory, where different variations of the printer are made, and one distribution center, which is facing demands for S different types of printers. DC Localization system consists of one supplier, which produces components for the modifications of the basic printer and one distribution center, which have the capacity of final assembly for S variations of the same printer. The problem is to determine the optimal ordering and inventory policy: reorder size, safety stock, and transportation. Let’s define variables: i : ith model of the printer; i = {1,2,…S}; µi : weekly mean of demand for product i; σi : standard deviation of demand for product i; L : lead time in weeks; R : review period in weeks; κ : safety factor to fulfill the K% of customer demand; h : holding cost per unit per week; Ci F : factory localized product cost per unit; Ci DC : DC localized product cost per unit; Note: Ci DC > Ci F , since final assembly at the DC will require new investment, training, and management. Ci F = Cc + Ci m Ci DC = Cc + Ci m + ∇C Where Cc is the cost per unit of common component; Ci m is the cost per unit of modification component; ∇C is the cost difference per unit in the final localization assembly. Calculation of the costs, tied-up in Safety Stock: Factory localization : safety stock for exposure period (lead time L plus review period R) κ R)(L + ∑= S i i 1 σ 7
- 8. Costs, associated with this safety stock κ R)(L + C∑= S i i 1 σ i F = κ R)(L + (C∑= S i i 1 σ c + Ci m ) = = Cc κ R)(L + + κ∑= S i i 1 σ R)(L + C∑= S i i 1 σ i m DC Localization: costs associated with safety stock for exposure period (risk pulling effect) κ Cc R)(L + ∑= S i i 1 2 σ + κ R)(L + C∑= S i i 1 σ i m The holding costs for both systems are going to be the same, and depend only on the mean demand, 2 1 h(L+R)∑= S i i 1 µ Transportation costs would depend on the size of the shipment, and we will assume that what ever is ordered from the manufacturing site will be shipped by one shipment, t (L+R)∑= S i i 1 µ where t is a transportation cost per unit. Overall cost is the Factory localization will be the sum of safety stock cost, holding cost, and transportation cost. Cc κ R)(L + ∑ + κ = S i i 1 σ R)(L + C∑= S i i 1 σ i m + 2 1 h(L+R) + t (L+R)∑= S i i 1 µ ∑= S i i 1 µ For the DC localization modes overall cost will have an additional cost – the difference in final assembly costs times the average number of assembled printers over the exposure period κ Cc R)(L + ∑= S i i 1 2 σ + κ R)(L + C∑= S i i 1 σ i m + 2 1 h(L+R) + t (L+R) + ∇C (L+R) ∑= S i i 1 µ ∑= S i i 1 µ ∑= S i i 1 µ It is easy to see that three entries in the cost functions are the same for both models, and that for application of the DC localization system, the savings accumulated 8
- 9. by the “risk pulling effect” should be grater then additional costs associated with DC localizing final assembly, i.e. Cc κ R)(L + (∑ - = S i i 1 σ ∑= S i i 1 2 σ ) > ∇C (L+R)∑= S i i 1 µ ∑= S i i 1 σ - ∑= S i i 1 2 σ > R)(L + ∑= S i i 1 µ (∇C/ Cc κ) And if two sides of the equation are equal, there is no cost savings associated with the new system (“break even point”), which will happen if the ratio of “the additional cost of the filial assembly at the DC” to “the cost of the common component” is: ∇C/ Cc = (∑ - = S i i 1 σ ∑= S i i 1 2 σ ) / (κ R)(L + ∑= S i i 1 µ ) VII. Cost Analysis Let’s consider a real life example for the DeskJet printers. Monthly data for European Distribution Center Options Nov Dec Jan Feb Mar Apr May June July Aug Sept Oct Mean Std Dev A 80 0 60 90 21 48 0 9 20 54 84 42 42.3 32.4 AA 400 255 408 645 210 87 432 816 430 630 46 273 420.2 203.9 AB 20572 20895 19252 11052 19864 20316 13336 10578 6096 14496 23712 9792 15830 5624.6 AQ 4008 2196 4761 1953 1008 2358 1676 540 2310 2046 1797 2961 420.8 1168.5 AU 4564 3207 7485 4908 5295 90 0 5004 4385 5103 4302 6153 4208 2204.6 AY 248 450 378 306 219 204 248 484 164 363 384 234 306.8 103.1 Total 29872 27003 32344 18954 26617 23103 15692 17431 13405 22692 30735 19455 23109 6244 Mean weekly demand = mean monthly demand / 4.33 weeks; SD of weekly demand = SD of monthly demand / (4.33)1/2 ; κ = 1.9 for Target Line Item Fill Rate of 98%. Lead time: 5weeks for sea shipment, 1 week for air shipment Mean Std Dev 9.769053 15.57045 97.04388 97.98809 3655.889 2703.01 9
- 10. 97.18245 561.5453 971.8245 1059.463 70.8545 49.5467 5336.952 3000.675 ∇C/ Cc = (∑ - = S i i 1 σ ∑= S i i 1 2 σ ) / (κ R)(L + ∑= S i i 1 µ ) For shipment by sea ∇C/ Cc = (3000.675 – (3000.675)1/2 / ( 5336.952*5*1.9) ∇C/ Cc = 0.058 For shipment by air ∇C/ Cc = (3000.675 – (3000.675)1/2 / ( 5336.952*2*1.9) ∇C/ Cc = 0.145 From the results above, we can conclude, that shipment by air gives more flexibility in terms of redesigning of the product and production process: for shipment by sea choice the additional cost of final assembly can not exceed 5% of the cost of common component; for the shipment by air that cost can be up to 14%. Calculation of safety stock required to achieve a given Fill Rate: Exposure period = Lead time + Review period; SD of demand over Exposure Period = SD of weekly demand*(Exposure period)1/2 ; Safety Stock = Safety factor * SD of demand over Exposure Period; Safety Stock in weeks of Supply = Safety Stock/ Mean weekly demand; Holding cost: 0.12; Review period: 1 week; Factory Localization DC Localization By Air By Sea By Air By Sea Holding cost of safety stock $529,784.00 $1,031,007.00 $324,955.79 $632,393.00 Holding cost of cycle stock $127,986.00 $127,986.00 $127,986.00 $127,986.00 Holding cost of pipeline inventory $255,972.00 $1,279,860.00 $255,972.00 $1,279,860.00 Total supply chain holding cost $913,742.00 $2,438,853.00 $708,913.79 $2,040,239.00 Per unit holding cost $3.30 $8.79 $2.56 $7.36 Common component 10
- 11. Results show that most economic inventory is achieved for DC Localization , air transportation model. But for decision about the model of design and transportation one should calculate all the costs: final assembly and transportation, batching of components, taxes for import of the finished goods or components, and so on. VIII Conclusion Supply Chains are very complex systems with following main characteristics: · dynamic system (real-time response to changing market demand); · decision support system (planning, forecasting, and decision-making) · hierarchical system (hierarchical relationships determined by business nature) · complexity (numerous factors and complex relationships); · indeterministic (unpredictable factors) Variability and uncertainties can occur at any point along the chain, and impact performance of the system. Supply Chain performance can be greatly improved by redesigning a product and its production process for Supply Chain Management. IX. References Baker, K. R., Magazine M. J., Nuttle H. L. W., “The Effect of Commonality of Safety Stock in a Simple Inventory Model”, Management Science, Vol. 32, No 8, November 1986. Cheng, F., Ettl, M., Lin, G., Yao, D. D., “Inventory –Service Optimization in Configure- to-Order Systems”, Oper. Management ( to appear ). Daskin, M. S., Coullard, C. R., Shen, M.Z.J., “An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results”, http://www.optimization- online.org, February 2001. Eppen, G., Schrage. L., “Centralized Ordering Policies in a Multi-Warehouse System with Lead Times and Random Demand”, TIMS Studies in Management Sciences, 16 (1981) 51-67. Kalakota, R., Stallaert, J., Whinston, A. B., “Implementing Real-time Supply Chain Optimization Systems”, http://www.optimization-online.org, 2001. 11
- 12. Lee, H. L., Padamanabhan, V., Whang, S., “The Bullwhip Effect in Supply Chains”, Sloan Management Review, Vol. 38, No 3, Spring 1997. Lee, H. L., Billington, C., ”Managing Supply Chain Inventory: Pitfalls and Opportunities” Sloan Management Review, Spring 1992. Lee, H. L., Billington, C., Carter, B., “Hewlett-Packard Gains Control of Inventory and Service through Design for Localization”, Interfaces, Vol. 23, No 4, July-August 1993 (pp. 1-11). Lee, H. L., Billington, C., “The Evolution of Supply-Chain-Management Models and Practice at Hewlett-Packard”, Interfaces, Vol. 25, No 5, September-October 1995 (pp. 42-63). 12