SAP Supply Chain Management:
With a variety of statistical models and demand planning features, SAP SCM is a powerful forecasting tool. It includes Life cycle planning, Time series profiling, Outlier Detection and Exception Management as well.
So is your company leveraging the full functionality of APO modeling and exception management?
At Valtitude, we help you develop consistent processes to leverage the modeling power of the SAP SCM engine from basic time series models to multiple regression models.
- If your planning process with SAP needs to be re-engineered, we offer Re-design and configuration. Configure and implement a brand new APO planning environment or fix challenges created by the original implementation with better performance usability.
- Our Model Tuning Consulting Service will leverage the features in the existing configuration and optimize the Statistical capabilities.
Download our brochure here:
We help you re-energize your implementation to:
Take advantage of the automated modeling strategies
- First Order Exponential Smoothing Models or Constant Model
- Moving Average Models
- Linear Regression Models and MLR Models
- Second Order Exponential Smoothing with Trend
- Holt-Winters Models
Better use of causal modeling
Set alert thresholds to enable modeling by exception
- Uni-variate forecast alerts
- User defined macro alerts
Create a more streamlined planning process and organization by asking the right questions:
- Has APO helped improve our forecast accuracy?
- Are there products and customers that are better left to APO's automated modeling strategies?
- Am I using a segmented modeling approach?
- How many customer/product segmentations are being reviewed by my demand planners each month?
- Are the statistical models tuned? How do we set the various model parameters to produce good forecasts?
- Am I using an exception-oriented process in my forecasting activity?
- How is APO helping us simplify and improve the promotional planning process? Is it integrated into the CRM system?
- Have I created the correct customer grouping for leveraging correlations across customer forecast errors?
- Has the system simplified and improved forecast reporting process?
- Are we using the system defined error metrics in APO?