Demand Forecasting for the Net Age: From Thought to Fulfillment in One Click

Demand Forecasting for the Net Age: From Thought to Fulfillment in One Click

Edward D’Souza (eSymbiosys Inc., Canada) and Ed White (Bayer Canada Inc., Canada)
Copyright: © 2006 |Pages: 19
DOI: 10.4018/978-1-59140-611-2.ch003
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Abstract

Picture this. The year is 2025. A customer is watching a new razor blade advertisement on interactive TV. The customer clicks to approve the purchase. When the order is received by the vendor, demand forecasting systems match customer experience data and integrate parameters—frequency of usage, preference of color, style of hand grip, language spoken by the customer, font style for customer’s name to be engraved on the razor, and so forth—into the Global Integrated Supply Chain Systems (GISCS) process. The next interaction is the customer receiving the order with a six-month supply of blades in the shortest possible time at a very affordable price. This will truly represent the process of thought to fulfillment in one click. This chapter explores the role played by demand forecasting for the net age—an age where customers can be anywhere and wants to have their needs addressed the moment they think about them. The organization that can fulfill the needs of these individuals in the easiest, fastest, and most cost-effective way will win their business. Such organizations will win over their competition and, in the process, reap profits. Any error in the thought to the fulfillment of the supply chain will result in a dissatisfied customer and, in all probability, loss of future businessto the competition. Meeting the demands of an anywhere-anytime environment requires more than just-in-time Supply Chain Management (SCM). It needs to move to the next level to what we call just-in-mind SCM. Demand forecasting for just-in-mind SCM requires the organization to do global thinking and local linking. The global thinking helps to forecast the demand, and local linking helps to fulfill it. The chapter helps the reader to understand the challenges faced by organizations in forecasting demand in the net age, gives real-life examples of these challenges, provides solutions for addressing them, and takes a look into the future.

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