Forecasting Features and Functions

• Uses beta factor to resolve forecasting errors


• Compares actual service levels to service levels specified in policies


• Generates initialization or simulation reports for safety stock


• 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


• Users specify stock-keeping units (SKU) and demand forecasting units (DFU) to use in demand forecasting


• User-defined analysis periods


• Demand forecast breaks down according to discrete profiles


• Classifies and orders demand structure from product family level to product unit detail


• User-defined data aggregation, grouping by sales region, product line, or customer


• 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


• Multi-level 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


• Compares forecast demand performance to historical sales data


• 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


• Aggregate forecasts break down into specific forecasts at unit level


• Provides details of items in product group forecasts to create more detailed forecasts


• Generates product family forecasts by rolling up detailed forecasts for items that are related


• Uses statistics to forecast trended demand, seasonal demand changes, and increase in demand during promotions


• Adjusts forecasts according to fluctuating demand using adaptive or exponential smoothing, moving average, and weighted moving average


• Model takes demand anomalies into consideration


• Flags violations of demand thresholds at product unit level


• 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


• Provides mean absolute deviation (MAD) to use when calculating safety stock


• Generates consolidated forecasts by part number and covering all facilities


• Uses sales history or demand pattern data of existing products to create forecast for new similar items


• Generates detailed forecasts by item number or SKU, that can be aggregated


• 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


• Users can create forecasts by demand class, by item, by customer, by product family, by model, and by option classes


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


• Forecast percentage included in forecast calculation