Forecasting Features and Functions

• Expected consumption based on external market conditions (weather, customer retention/growth)


• Predicted spare parts inventory replenishment based on maintenenance updates


• Expect consumption rates based on current customer profiles


• User defineable next day min & max load generation


• Conducts simulation to test policies


• Uses beta factor to resolve forecasting errors


• Compares actual service levels to service levels specified in policies


• Generates initialization and control reports to create and evaluate forecasts


• Measures accuracy of forecasts (adjusted or unadjusted)


• Analyzes performance by comparing forecasted demand to actual demand by period or product aggregate specified by user


• Imports forecast data from spreadsheet


• Forecast is adjusted automatically according to information on selling patterns, which is received by electronic transmissions


• User-defined analysis periods


• Demand forecast breaks down according to discrete profiles


• Creates demand forecasting units for a product line or a group of product lines that may not correspond to physical stocking locations


• Various algorithms are available for generating forecast summaries at aggregate level, as well as forecasts at the product family or item level


• Multilevel aggregating or disaggregating


• Matches forecast model to selected historical data


• Uses forecasting algorithms to generate several forecasts for an item, to generate the ideal forecast according to historical data


• Creates "what-if" scenarios for a product to test alternate scenarios or models


• Displays actual and forecast demand by customizable period


• Customizable forecast periods, ranges of tolerance, data points, and data presentation


• Evaluates forecast models for accuracy based on historical data


• Generates different forecasts according to various demand hypotheses


• Confidence factors incorporated into forecasting model


• Model takes demand anomalies into consideration


• Tracks accuracy of forecasted quantities by comparing planned and actual data


• Monitors high quantity demand signals


• Sends signals to users when forecast has errors or an activity is not within threshold levels


• Tracks demand fluctuations caused by extraneous events


• User-defined normal, seasonal, and promotional demand


• Permits variable length periods for demand data


• Overwrites or consolidates forecasts at item level


• Accumulation of old forecasts into future periods


• Generates statistical or focus forecasts automatically to update inventory


• Generates demand forecasts


• Users can create forecasts for each item included in a multi-level bill of materials


• Estimates percentage of future demand based on existing data for item-level components


• Forecast percentage included in forecast calculation


• User-defined component level forecast


• Open forecast sceduling based on user defined parameters


• Forecasting based on assigned holidays


• Hourly energy consumption forecasting


• Forecasting based on events


• Forecasting based on weather


• Forecasting based on season


• Forecasting based on generated and consumed power by plants