The Forecasting Operations tutorial focuses on customizing your models and forecasts.
Using Forecast Modifiers teaches you how to use forecast modifiers to dictate model selection.
Building Event Models teaches you how to build event models to capture promotional and seasonal effects.
Detecting and Correcting Outliers teaches you how to use Forecast Pro’s outlier detection and correction functionality.
Machine Learning Overview (video) walks you through some machine learning basics and shows you how to build custom and automatic machine learning models in Forecast Pro. What is Machine Learning – and Will It Improve My Forecasts (video- coming soon) gives a more in-depth description of how machine learning is implemented in Forecast Pro and when to use it to improve your forecasts.
Building Multiple-Level Models teaches you how to set up and forecast a multiple-level hierarchy.
Building Custom Component Models teaches you how to prepare forecasts using the custom component model Custom component models are useful in a variety of situations including (1) customizing the trend for longer-term forecasts, (2) customizing the seasonal pattern for new products or short data sets and (3) defining the impact of future events that have not occurred historically.
New Product Forecasting teaches you how to forecast new products prior to historic data being available, how to use forecast by analogy to forecast new products based on similar products, how to use the custom component model for new products, how to manage new products in your forecasting process and how to use the Bass model.
Building Dynamic Regression Models teaches you how to build and evaluate dynamic regression models.
Using Weighting Transformations teaches you how to use weights to adjust for trading day impacts and how to account for a 4-4-5 calendar.
Out-of-sample Testing teaches you how to assess forecasting performance using a holdout sample approach.
All lessons use sample data provided with the software.