SAP Integrated Business Planning for Supply Chain is a solution that synchronizes supply chain planning processes in real time, ensuring the continuity of all business processes even in the face of unforeseen disruptions.
SAP IBP is:
- SAP HANA-based cloud solution that integrates sales and production planning, forecasting and demand, response and supply, replenishment based on demand, inventory planning;
- Automated, closely coordinated supply chain planning processes;
- Advanced machine learning algorithms and scheduling capabilities;
- Built-in integration with SAP Supply Chain Control Tower and other solutions.
SAP IBP functionality
SAP Integrated Business Planning for Supply Chain (SAP IBP) enables you to effectively meet future demand by offering analytics across the supply chain, simulation of possible options, warning and many other features that allow you to predict changes and respond to them faster.
Sales and Operations Planning (S&OP)
- Real-time planning. Balancing supply and demand, integrating financial and operational planning and linking high-level strategic plans with medium- and long-term business plans;
- Modeling and comparison of scenarios. Modeling changes in needs or supplies to analyze “what ifs” and comparing scenarios to make effective and informed decisions quickly;
- Interactions. Eliminate fragmentation of operations and planning, improve teamwork and the effectiveness of the planning process.
- Performance monitoring. Analysis of actual performance on plans and monitoring of future discrepancies between operational and strategic plans.
Demand forecasting and management
- Planning of demand. Combination of several demand indicators with statistical forecasts, formation of accurate demand plans;
- Expanded needs assessment. Refining short-term forecasts to optimize order fulfillment and reduce inventory;
- Reliable statistical models. Using sophisticated prediction algorithms combined with machine learning, preprocessing, and postprocessing algorithms;
- Time series analysis. Classification of products based on historical data and selection of algorithms based on this classification.
Inventory planning and optimization
- Multi-stage optimization of stocks. Reduces the amount of inventory needed to minimize risks and reduce the impact of uncertainties;
- Reliable statistical models. Provide significant improvements in comparison with calculations performed manually;
- Managing forecast errors. Protection against forecast errors and demand uncertainty factors, support of the supply chain based on need;
- Embedded analytics. Visualization of the logistics chain, timely and accurate analytics.
Demand-driven supply planning
- Multi-level planning. Location modeling and multilevel specifications to cover the entire supply chain network;
- Supply planning. Using analytics and optimization tools to develop a supply schedule;
- Enlarged planning. Development of a tactical enlarged plan for the use of resources while taking into account existing restrictions;
- Response management. Provide an operational or order-based delivery plan with order rescheduling, using priority rules.
Replenishment based on need
- Continuous material and information flow. Eliminating the Forrester effect (stick effect) in the supply chain, ensuring the consistency of the supply chain;
- Replenishment based on actual need. Minimizing the impact of incorrect forecasts on the replenishment strategy;
- Calculation of the safety stock. Using analytical and statistical data, as well as forecasts and plans to determine the optimal amount of safety stock;
- Sustainability of the entire supply chain.
