HP, P&G and Xilinx Supply Chains - Essay Example

? Case Analysis: HP, P&G and Xilinx Supply Chains s: CASE ANALYSIS: HP, P&G AND XILINX SUPPLY CHAINS Q To reduce the impact of the bullwhip effect, P&G took the following steps: P&G began by seeking to improve the flow of information along their chain of supply. Improving communication and forecasting the needs of the consumer will help in observing trends in the supply chain operations and better prediction of demand, which will lessen the bullwhip effect (Wang, Ma & Guo 2012, p. 119). P&G then sought to reduce supply chain delays through information systems that aid in tracking products better along the chain of supply. By reducing the order delivery time, they will decrease fluctuations as well as costs and inventory levels (Wangphanich, Kara, & Kayis, 2010: p4508). P&G then turned their attention to POS purchases at their main distributors and retailers to track ordering trends and preferences respectively. Using a point-of-sale system will allow P&G to identify trends and improve communication along the chain of supply (Wang et al. 2012, p. 120). P&G also sought to get the main retailers to reduce their order sizes relative to demand. Ordering according to the needs of the consumer, rather than to stock, will aid P&G in attenuating the impact of the bullwhip effect (Wangphanich, Kara, & Kayis, 2010: p4509). P&G then utilised the improved communication and forecasting to maintain consistency in price. This will prevent increased ordering when prices are low, lessening the bullwhip effect (Wang et al. 2012, p. 120). Other approaches that P&G could have taken include: Portfolio planning, in which they could diversify the distributor base into a group that is on long-term contract terms to meet the major demand, and others on short-term contract terms to cover any increase in demand (Gupta & Mishra 2012, p. 27). Postponement, in which they would delay delivery of the product to their distributors until they have reliable information on demand (Gupta & Mishra 2012, p. 28). Q #2 The demand–supply gap at Cisco occurred for a number of reasons: When supply is exceeded by demand, the manufacturers such as Xilinx produced more components for the consumers, who may have ordered more products than required to generate profit. After supply caters to normal demand, orders may be cancelled, which results in unwanted inventory (Thompson & Liang-Chieh 2012, p. 120). A gap between demand and forecasting may also have caused the demand–supply gap, especially if Cisco’s planning team forecasted demand through extrapolation of demand at present. Small fluctuations result from long lead-time extrapolation, which ends up having a huge impact on the demand–supply gap (Akkermans & Voss 2013, p. 770). Use of batch orders for small and frequent orders may have been made to reduce storage costs or logistics. This could result in increased demand variability compared to supply (Thompson & Liang-Chieh 2012, p. 121). Price fluctuations due to anticipation that there will be a price increase could have led to items being stocked up to capitalise on low prices. This leads to variation between supply and demand (Akkermans & Voss 2013, p. 771). These arrangements could have resulted in a pileup of Cisco’s inventory, as forecasters did not notice artificial inflation within their projections. Since many of the company’s clients ordered similar products from competitors so as to close the deal with the company that delivered on their orders first, Cisco’s demand forecasts were inflated by triple and double orders (Thompson & Liang-Chieh 2012, p. 121). Their supply chain management system was unable to indicate the increased demand. This was representative of overlapping orders, leading to a vicious cycle of demand that was inflated artificially, increased costs, and poor communication along their chain of supply (Akkermans & Voss 2013, p. 771). For these reasons, it is clear that the biggest problem had to do with poor communication across the chain of supply. To counter this, Cisco integrated an Enterprise Resource Planning system into its supply chain to improve the information flow in the supply chain. (Zhang & Burke 2011, p. 519) The information flow is enabled through integration of the Enterprise Resource Planning system and supply chain management. (Zhang & Burke 2011, p. 520) This integration of the supply chain with the enterprise’s resource management system has several advantages including: Complete visibility of the vital processes across departments that are crucial in forecasting demand (Zhang & Burke 2011, p. 519). Coherent and automatic workflow across departments at Cisco and suppliers, ensuring smooth process completion. The single unified system of reporting afforded by ERP integration enables analysis of statistics across all functions of the supply chain and departments at Cisco in real time, enhancing the forecasting ability. The ERP system can also be extended to provide Cisco with functionalities of Business Intelligence (Zhang & Burke 2011, p. 520). Integration with e-commerce is also enabled by the ERP system, which will allow Cisco to track ordering and processing of orders. Implementing a single database at the back end for storage of information for use by the ERP system will enable to centralise data storage and back up all data for Cisco (Zhang & Burke 2011, p. 520). There is added security since Cisco can apply centralised security policies, which will enable them to track all transactions occurring across the ERP system (Ouyang & Li 2010, p. 801). The system eases inventory tracking, order tracking, sales forecasting and revenue tracking (Ouyang & Li 2010, p. 801). However, integrating an ERP system into the supply chain will also have several disadvantages: The costs of planning, configuration, customisation, implementation and testing of the ERP system are high, as are indirect costs such as upgrading of WAN links and new IT infrastructure (Zhang & Burke 2011, p. 521). Deployment of ERP in the supply chain will take approximately two years in order to be fully functional. Undercustomisation may fail to integrate the system with important processes, while overcustomisation may slow the project down and increase difficulties in upgrading it in case the company contracts another supplier (Zhang & Burke 2011, p. 521). Because the ERP system is generally hard to learn and use, participation of all users may not be desirable, which may result in biased forecasting (Salcedo et al, 2013, p. 264). Q #3 Procter & Gamble For P&G, the key order winner is quality with an emphasis on reliability, technical durability and value for money. In order to take advantage of technical durability of diapers, the best supply chain model for the company would be the integrated make-to-stock model (Shah 2009, p. 71). This model will be focused on tracking, in real time, demand by customers in order for the production process to efficiently restock finished goods. By improving the information flow across the supply chain, P&G can receive demand information to modify and develop schedules and plans of production and distribution. In this model, P&G can use several channels of distribution to sell to department stores and supermarkets, in which marketing is done through information technology and the Internet. Using the integrated MTS process, P&G will manufacture pampers based on forecasts using vendor data, preventing opportunity loss and excess inventory. In P&G’s environment of mass production and marketing, forecasting mass production requires efficient business management and standardisation (Shah 2009, p. 71). Because high quality of diapers is not affected by time owing to their durability, decreases in demand coupled with increases in inventory will not influence the supply chain as the inventory will eventually be turned into cash when demand increases again (Arlbjorn 2010, p. 51). By using demand cycles from the past, P&G can predict future demand. Specifically, an inventory management system should be used to improve efficiency by setting optimal production, safety stock and ordering points on the basis of lead times in production, procurement of materials, delivery and forecasts in demand. By making diapers to stock and relying on demand forecasts to release the stock, P&G will respond faster to replenish a retailer’s inventory and avoid opportunity cost. Since the MTS model is also used to reduce excess inventory, small batch supply should be performed by various pull-type demand aspects such as vendor managed inventory, continuous replenishment programmes, efficient consumer response, and quick response. This will accelerate product flow and will increase cash flow. By using pull type MTS models of the supply chain, such as vendor management inventory and continuous replenishment programmes while moving away from the push type MTS model, P&G can successfully leverage the durability of their product (Arlbjorn 2010, p. 52). HP The key order winner for HP is flexibility, which necessitates HP to use a build-to-order type of supply chain model. In this model, HP starts assembling the order from the customer after receiving it, requiring careful management of delivery of required components across the chain of supply, as well as of component inventories (Ivanov & Sokolov 2010, p. 59). This potential inventory issue is solved by using many common components in several locations and lines of production, leveraging the flexibility of their production and assembly. This supply chain model has the advantage of perception by the customer that they are getting customised products. In addition, it increases the speed of delivery and supports the mass customisation concept. The assembly process begins after HP receives demand or following developmental planning. Assembly or manufacturing after reception of the order refers to the beginning of a pull-type supply chain operation, in which manufacturing is pulled by demand. In the MTO model, the assembly process for HP and its partners begins after they receive orders. In addition, the process of production begins when the suppliers obtain parts and materials while, earlier on, commencing from development engineering (Ivanov & Sokolov 2010, p. 59). MTO, which is a pull type of production, is a model in which production quantity for each product specification is limited. From the supply chain management viewpoint, this model will enable HP to meet the due dates promised to customers while also reducing lead times to gain a competitive edge (Ivanov & Sokolov 2010, p. 60). Even when there is an increase in quantity produced by suppliers and quantity assembled, greater business opportunities will result from products manufactured and assembled by pull type production in the MTO model. This supply chain model can also be used as a marketing tool and in the creation of marketing models (Ivanov & Sokolov 2010, p. 61). For example, HP can market its products as computers that will be assembled and made as requested, and delivered in a week as a custom-made product. Xilinx The key order winner for Xilinx is dependability, for which Xilinx has implemented a Direct Fulfillment Programme model using a channel assembly. Engaging this model, Xilinx uses information from Cisco and other clients to integrate a demand-driven system to communicate the removal of components from the inventory by Cisco (Coyle 2009, p. 61). Parts of the model are assembled as products move along the distribution channel. Overall, Xilinx uses an assemble-to-order model, in which it can simplify the process of manufacturing goods for finishing. Based on forecasting, it manufactures subassemblies before receiving orders from its customers and, after it receives their orders, the components that have been manufactured are taken for assembly to Cisco and other partners. In this model, the final assembly is done after reception of the orders from clients. The strategy allows durable sub-components to be manufactured, but assembled only after the order is received from Cisco and other partners (Coyle 2009, p. 61). The process planning in this model anticipates demand fluctuations for internal and external components while focusing on customising products for individual clients such as Cisco. Shipping modules, order management, and WIP are also integrated into the supply chain to support the manufacture and shipping of assemble-to-order configurations. Such an item in this supply chain model is then linked to the sales order (Coyle 2009, p. 62). For example, where one of the partners, for example Cisco, is producing a computer accessory, Cisco will require various components to complete their accessories. This model will begin at the top of the hierarchy of configuration followed by the option class and, finally, the option item. References Akkermans, H & Voss, C 2013, The service bullwhip effect. International Journal of Operations & Production Management , 33 (6), 765 - 788. Arlbjorn, JS 2010, Supply chain management: sources for competitive advantages, Academica, A?rhus. Coyle, JJ 2009, Supply chain management: a logistics perspective, South-Western Cengage Learning, Mason, OH. Gupta, S & Mishra, P 2012, ‘Information technology: tool to deal with bullwhip effect in supply chain management’, International Journal of Management & Internartional Technology, vol. 1, no. 3, pp. 20–32. Ivanov, D & Sokolov, BV 2010, Adaptive supply chain management, Springer, London. Ouyang, Y & Li, X 2010, The bullwhip effect in supply chain networks. European Journal of Operational Researc , 201 (3), 799–810. Salcedo, CA Hernandez, AI Vilanova, R & Cuartas, JH 2013, Inventory control of supply chains: Mitigating the bullwhip effect by centralized and decentralized Internal Model Control approaches. European Journal of Operational Research , 224 (2), 261–272. Shah, J 2009, Supply chain management: text and cases, Pearson Education, Upper Saddle River, N.J. Thompson, B & Liang-Chieh, C 2012, ‘Bullwhip effect in contract manufacturing industry: case studies’, Journal of the Academy of Business & Economics, vol. 12, no. 3, pp. 117–124. Wang, G Ma, J & Guo, Y 2012, ‘A model study on information sharing to tame the bullwhip effect in supply chain’, Advances in Intelligent and Soft Computing, vol. 112, pp. 117–123. Wangphanich, P Kara, S & Kayis, B 2010, Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems–a simulation approach. International Journal of Production Researc , 48 (15), 4501-4517. Zhang, X & Burke, GJ 2011, ‘Analysis of compound bullwhip effect causes’, European Journal of Operational Research, vol. 210, no. 3, pp. 514–526. Read More