Statistical forecasting methods and features
Several statistical forecast methodologies can be implemented in SAP IBP/ Power BI and are currently available in the application. Each forecast methodology contains at least two of the listed features below:
- Baseline
- Irregular fluctuations
- Trend
- Cyclicity
- Seasonality
Statistical forecast methodologies:
- Regression (linear, logarithmic, exponential, power)
- Historical average/moving average (single, double)
- Driver-based forecast
- Exponential smoothing (simple, double, triple)
- Holt’s linear trend
- Decomposition (additive, multiplicative/linear/logarithmic, exponential, power)
- Winter’s additive/mulitplicative
Solution features
- Features of the automated statistical forecast application
- Forecast methodologies with associated parameters.
- Forecast scenarios for comparison.
- Forecast features adapt to forecast needs.
- Selecting forecast methods based on maximizing performance and minimizing variance.
- Visualization of all forecasting techniques with the possible parameters.
- Visualization of the optimal parameters vs. the actuals.
- Comparison of loaded actuals vs. previous forecast scenarios (margin %) to anticipate GAPs that can be explained.
