History of Dell, Inc.
Formed by Michael Dell, Dell is a computer hardware company in the USA headquartered in Texas. According to Pichetpongsa and Campeanu (2011), Dell ventured into the computer-selling business in 1996 via its website. The company overtook Hewlett Packard (HP) in 1999 to become the biggest company selling desktop computers and ran the business by the name PCs limited. However, the company’s name was later changed to Dell, Inc. through the approval of stakeholders in the company’s annual meeting in 2003.
Dell’s core business is to manufacture, hold and sell mobile phones, networks switches, laptops, servers, PDAs, data storage devices, desktop computers, and more technology-related products. However, the company’s core objective is in the manufacturing of low-cost personal computers and has an excellent after sales customer service and a solid system of distribution. As a result of the evolving of personal computers from mere machines to gadgets which are essential in life, Dell has ensured that it offers computers with exceptional computational power (Niosi, Athreye & Tschang, 2012). The key role of inventory management in the company is to enhance customer satisfaction through the provision of quality services thus generating more revenue for the company. In addition, the company has highly personalized Inspiron and Studio laptops, netbooks (Dell mini), and desktops. Furthermore, Dell has invented high performing gaming desktops and laptops like the new line of XPS products. In response to HP Voodoo Envy and MacBook Air, Dell created Adamo which was the company’s foray into the luxury market.
Dell realizes that creating and maintaining quality and high-performance inventory and ensuring the satisfaction of customers plays a critical role in the success of the organization. As a result, seventy percent of the company’s customers comprise of corporate companies, governmental institutions, and large educational institutions (Pichetpongsa & Campeanu, 2011). The company reduces the risk of competition through the management of the inventory of its big customers and has continued to target large institutions so as to increase the profitability of its scalable business. Through the maintenance of the large customer’s key inventory both globally and nationally, Dell has been successful in increasing its profits and suppressing on its expenditures. The company has partnered with few suppliers to secure the information shared with other companies and ensure that the inventory relayed from the organization moves quickly through the virtual supply chain. Moreover, Dell makes orders through a networked computer system to enhance efficiency and improve the supplier trust relationship.
Dell, Inc. uses the Just In Time (JIT) manufacturing strategy which is a specific strategy and technique for the production of inventory used in the improvement of an organization’s Return On Investment (ROI) through cutting back on the levels of stock held. JIT’s major goal is to enable organizations to achieve zero inventory level, not within one organization, but entirely throughout the supply chain. Many companies have transitioned to the adoption of JIT manufacturing, although the automotive industry was responsible for pioneering of the principle. Currently, organizations’ inventories have shrunk to the minimum due to the high adoption of the JIT manufacturing strategy. However, Dell, Inc. has been the most well-known organization which has successfully implemented lean manufacturing and integrated it within its processes.
Core Business and Target Market
Dell’s Just In Time (JIT) inventory strategy is believed to be building and enhancing a leaner manufacturing system for minimizing inventories within the organization. Just In Time has made the company’s operations production more efficient in comparison to other production methods due to its cost efficiency. Dell, Inc. realized that using the Just In Time inventory strategy and technique would be the best strategy for the processes of the organization before other computer companies did. As a result, the organization has cut its inventory from their earlier ‘twenty to twenty-five days of inventory’ to having ‘no warehouses’ and a maximum of two hours in the company’s factories.
Furthermore, Dell, Inc. has attained one of its major goals of constant improvement of the organization’s performance. Moreover, the company has realized it could achieve a reduction of its expenditure through integration and optimization of its computer manufacturing system. The system has built a leaner supply chain for Dell, Inc. to achieve minimal inventories. In addition, the strategy has also reduced the company’s lead time in the service of customer orders for laptops and computers. As a result, Dell, Inc. has gained a very successful improvement of its processes within the company.
The best inventory system in this situation will be the Economic Order Quantity (EOQ) model that involves a fixed time period model (FTPM) and fixed order quantity (FOQ). According to Lee and Yu (2010) the fixed-time period model refers to many household commodities or items that have a consumption of either monthly, weekly or annually. Furthermore, fresh food for the kitchen can be purchased on the fixed-order quality model. The order quality model will generate pickup commodities when needed after the supply runs low. Order quality model considers ordering costs and storage costs when choosing the best kitchen food quantities. The order costs that might occur in this case include transportation costs and communication costs when communicating about food delivery for supplying the kitchens. The model will be advantageous when supplying large-quantities of food to the kitchen as it will reduce frequent ordering. When the model is used to supply food for few kitchens, it will require frequent ordering thus it will incur high monthly costs since it will lose the bulk order discount.
The period model will be the suitable inventory system for obtaining a daily newspaper, as readers tend to buy new newspapers before completing reading the previous one. Furthermore, the newspapers are not purchased on a single order basis placed by one customer. When obtaining a daily newspaper there is only one chance of the right quantity after placing a single order, as the newspaper will have no value after the time needed has elapsed. However, ordering one newspaper must incur additional costs like transportation costs. Therefore, the order for the newspaper must be right the first time in order to minimize chance losses. In the modern world, the majority of customers prefer to subscribe to weekly, monthly or yearly memberships whereby the services are paid for a specific fixed time (Cestino & Berndt, 2017). The monthly and weekly subscription will attract discounts and newspapers will be obtained at relatively cheap prices.
Fixed Order Quantity Model (FOQM) and the hybrid model will be the suitable inventory systems for buying gas for the car. Once there is a signal at re-order point, the fuel is refilled. This means that once the level of consumption goes to zero, the gas is refilled. However, many people tend to have fixed-quantity purchase after the gas has reached recorder point (Su, 2009). For example, “put 30 gallons worthy $30.00.” Others also draw their estimation upon experience by using a periodic ordering system. For example, taking their cars for filling after church or a football match. Therefore, the car is not refilled on a daily basis but on specific time intervals when the gas exhausts. Furthermore, the Fixed Order Quantity Model (FOQM) is advantageous to the car owner because the inventory level can be continuously monitored and the stock that has already depleted can be ordered using previously fixed quantities. The stock can be ordered under the circumstance of the stock falling to establish the re-order point.
Buying gas for the car has the highest stock out cost for most of the well-read and well-fed individuals because the gas will not be everywhere. Furthermore, in a situation where a car runs out of gas in front of the gas station as a result of an accident on the highway, the cost could range practically from zero.
References
Cestino, J., & Berndt, A. (2017). Institutional limits to service dominant logic and servitization in innovation efforts in newspapers. Journal of Media Business Studies, 14(3), 188-216.
Kshetri, N. (2010). Cloud computing in developing economies. Computer, 43(10), 47-55.
Lee, L.F. and Yu, J., 2010. A spatial dynamic panel data model with both time and individual fixed effects. Econometric Theory, 26(2), pp.564-597.
Niosi, J., Athreye, S., & Tschang, T. (2012). The global computer software sector. Economic Development As a Learning Process: Variation Across Sectoral Systems.
Pichetpongsa, N., & Campeanu, G. (2011). Analysis of green information technology in Dell and Toshiba companies. IDT: Malardalen University, Västerås, 1-7.
Su, X. (2009). A model of consumer inertia with applications to dynamic pricing. Production and Operations Management, 18(4), 365-380.
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