Real-time predictive forecasting enables organizations to maximize operations by combining historical analysis and by identifying new trends, as they happen, to predict future performance. Rather than basing your forecast on the opinion of the person with the highest title in the room, forecast values are determined using statistical models.
In practical terms, predictive forecasting can be enabled by integrating result sets from SAP Predictive Analytics with SAP BPC or Analytics Cloud planning tools. Layering on business intelligence tools adds the 360-degree capability of visualizations for tracking and measuring results, with the capability to drill down to details for root cause analysis.
SAP’s Predictive Analytics uses data science statistical techniques include multiple regression, factor analysis, and analysis of variance to define both correlations (factors of success) as well as generation of forecast values.
- The correlation factors become the key drivers of your forecast model
- The predictive model forecast outputs become the target values for input into the forecast.
Strengths of SAP Predictive Analytics:
- Transform large volumes of Big Data into actionable insights
- Leverage data derived predictions as starting point for more accurate plans
- Optimized for calculation of voluminous and complex logic using standard, open source predictive algorithms, utilizing hundreds of open source predictive algorithms
- Can utilize structure or even unstructured data: Financial/operational/public/social
- Easy to use
- Financial Analyst doing the work of a data scientist
- Can be up and running within a couple hours of training
- Repeatable results