Sales planning and forecasting tool GIB Dispo-Cockpit Forecast is fast and easy to use. Reliable forecast procedures facilitate rolling sales planning, allowing you to focus on materials and product groups that can hardly be forecasted. This helps you optimize your planning for the long term.
It also gives you the possibility of implementing your forecast procedures promptly, thus increasing your readiness for delivery and optimizing your inventory.
- Advanced forecast models
- Data basis: SAP and alternative subsystems
- If required, creation of nodes which are independent of SAP
- Consolidation of decentralized planning into one planning monitor
- Mapping of organizational structures which are independent of SAP
- Forecasting and monitoring via workflow, traffic light, and alert features.
- Dependable requirements planning thanks to a comprehensive data basis
- Ability to check forecast quality through ex-post analysis
- Constant optimization of production plans using rolling sales planning
- Inventory optimization, precise planning, and reliable forecasts
- Simulation of the impact of planning, e.g. on work center capacities
- Sales, supply chain management and other specialized departments
GIB Dispo-Cockpit Forecast provides support for decentralized planning through automated forecast procedures. Thus, data from many different sources can be included. The result: optimized inventories, improvement of delivery readiness, and reliable capacity planning.
Forecast procedures with GIB Dispo-Cockpit Forecast facilitate precise forecasting and reliable planning accuracy.
In the standard, the planning hierarchy can take the form of sales or plant planning (plant planning: up to three aggregation levels of an S structure, e.g. S001 - VKORG, VTWEG, customer/plant planning: material consumptions from DCC or MVER) or else be tailored to the customer. This makes it extremely versatile in terms of its characteristics.
Simple, intuitive planning interface in the Excel-like ALV Grid format.
Automatic forecast selection through monitoring various tracking signals while taking into account XYZ consumption constancy, making the responsible planner’s work easier, especially for materials that are easily forecasted.