Many problems along the EC supply chain stem from demand uncertainties and the difficulties that ensue across the supply chain in trying to meet this uncertain demand. This is where demand forecasting comes into play. The major goal of demand planning is to forecast at a very detailed level the number of product of a certain
type will be needed to meet demand at specific locations at particular points or intervals of time in the future. For instance, a virtual retailer might want to estimate the number of smart phones of a particular model that will be needed to fulfill potential orders for a particular city or area of a city during the upcoming holiday season.
Usually, demand forecasts rest on statistical (time series) estimates from historical patterns and trends in sales or order data. The estimates try to incorporate a number of factors in under- standing what produced these historical patterns and trends so these factors can be taken into account when making the estimates. Some of the factors might include economic conditions, prices, seasonal adjustments, weather conditions, estimates of consumer confidence, and the impact of promotions of various types. Obviously, any- one of these factors can change very quickly, as well as the fact that consumer tastes can change quite radically, which is why demand forecasting is as much an art as it is a science.
The problem is that demand planning is prob- ably the most critical planning process in the sup- ply chain because it determines many of the other processes in the chain. Among other things, it drives the plans of how many orders can be filled from inventory, how much a retailer will buy, how much manufacturers will need to build, what raw materials are needed, how much factory capacity is needed, how much will have to be shipped, and when and where it will have to be shipped, and so forth. Inaccurate estimates of demand ripple throughout the supply chain. This is why the demand forecast should be conducted frequently, and adjustments to plans in collabora- tion among the business partners along the sup- ply chain, in order to correctly forecast demand and make plans to meet it. Companies attempt to achieve accurate demand forecasts by methods such as information sharing using collaborative commerce.
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