Anaplan's Generic Monthly Statistical Forecasting App for multiple use cases allows you to upload a customized product and location hierarchies from flat CSV files, load historical data, and generate forecasts using various statistical algorithms. The app includes 30 of these algorithms across 4 different overarching forecasting methods: Basic and Intermittent Demand, Curve Fit, Smoothing, and Seasonal Smoothing.
Not only does this model generate statistical forecasts based on historical data but it also analyzes which algorithm would best fit that data. This approach provides you with a suggestion of which method may be the most accurate to use for future periods.
Brief Intro and Overview of new statistical forecasting calculation engine model
Clear sample hierarchy and historical data, download templates to enter your data, then upload those files as CSVs to statistically forecast.
View each item's history and suggested, best-fit forecast.
Analyze the forecast and historical forecast accuracy for multiple statistical algorithms against each lowest level item.
View upper and lower bounds by standard deviation or inter-quartile range and the resulting outlier values.