All plants require sales forecasts to plan production, material batching, deployments to warehouses, work force requirements and raw material purchases. It is critical that a plant neither under-produce (risking stock-outs) nor over-produce (risking product dumpage). Many plants use Production Systems, such as Avail 6.0, as a tool to create production and deployment schedules, as well as to plan material requirements for scheduling raw materials. Clearly, the effectiveness of the schedules is directly related to the quality of the sales forecasts that drive them.

Prevail 6.0 is a statistical program that generates sales forecasts based on trend, seasonality, net wholesale and retail pricing, along with ad and display activity. The data required to develop the forecasts are merged, entered and generated by the demand planner, who ensures that the raw data is correct and that the forecasts are available to the production and other operational schedulers in a timely fashion.

Prevail 7.0 is a program specifically developed to assist with a collaborative forecasting process.

A typical Prevail installation forecasts all sales for 5 to 20 locations (plants and warehouses) at one time. Forecasts can be reviewed, revised and approved by the demand planners. Prevail offers scores of forecasting process metrics. Planners can instantly create reports that include sales, forecasting accuracy, and error dispersion grouped by category, location, and timeframe.

Forecasting Methodology
With Prevail, Areté has developed a detailed methodology to automatically generate demand plans based upon our years of experience assessing and solving this type of business problem. We began by understanding what primarily drives variations in sales volume in your markets. We then developed specific types of forecast models used to predict sales volume drivers accurately, and algorithms to blend the model values into an aggregate forecast value in a way that makes sense for your markets. Finally, we incorporated various levels of demand resolution into the process to address the different ways in which history is held and how sales and manufacturing desire to view the results of the demand planning process.