D-Stats

Reaching the next level of planning

D-Stats is a detailed, robust and automated process for simplifying demand planning. It is composed of 5 key steps:

1. Classifying demand
2. Analysing demand patterns
3. Preparing for outlier detection
4. Running outlier detection and correction
5. Running statistical forecasting

The methodology segments and classifies the demand, analyses the data patterns and ensures an easy and accurate data cleansing exercise. New customised methods for outlier detection and correction, combined with differentiated solutions for statistical forecasting, are the core innovations to tackle the Demand Forecasting headaches and guarantee a meaningful and accurate sales forecast.

D-Stats innovation

The competitive advantage provided by D-Stats comes from statistical automation:

• New customised method for demand classification and segmentation based on statistical best practices
• New ad hoc quantitative and qualitative methods for analysing demand patterns
• New numerical and visual procedures for preparing your company portfolio to run the outlier detection and correction process
• New innovative techniques for detecting and correcting outliers
• New forecasting models to cope with the more difficult forecasting challenges
• Automated algorithms assignments based on statistical best practices
• Optimized solutions for even better results in terms of forecast accuracy and bias