Pyramid Forecasting

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The main aim of a project manager in a supply chain environment is to have the ability to forecast the costs and the raw materials required for their projects in a timely manner. In order to achieve this, the manager must have good input into the decision making process of their organization. The cost and material estimates provided by a project manager to their overall customer can be quite far off the mark, causing significant delays in production. As a result, the customer is put on hold, which hampers their delivery time and, consequently, the company profits. This is why cost control is so essential in a supply chain environment. Cost reduction management is carried out through material planning, stock control, and warehouse automation.

The key concept in cost and raw material forecasting, and hence in cost control forecasting, is to forecast the lowest level of inputs and the highest level of demand needed for the end product or the final deliverable. The pyramid forecasting method is a common way which the supply chain managers use to predict the supply and prices at which the different product levels will be sold. For example, if there are three levels in the supply chain, then they would have to forecast the lowest level at which the product may be sold and the highest level at which it will be bought from the customer. From this information, the managers can then determine what their production capacity needs to be, and how many units of each product they should produce in order to meet their customers' demands.

One of the best ways to create such forecasts is to apply the method of "bottoming up" which is based upon the concept that the most important thing to do when forecasting a particular product line is to perform a "top-down" search for the data necessary to make an informed forecast. Applying this method to a supply chain, the managers will find themselves well placed to make the decisions about the inventory, pricing and promotion of their products. In this manner, the product line is forecasted right down to its critical points, and thus the managers are able to make informed product pricing decisions. Another way to create such forecasts is to apply "bottom-up" search techniques, for example, by collecting the data from point of sale terminals or from the actual sales data. These data sets will allow the managers to make better product pricing decisions as well as to forecast the demand for their product line.

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