The inventory application of SAP Integrated Business Planning supports end-to-end supply planning processes by enabling inventory optimization.
Inventory Optimization is the application of algorithms and scenario planning that considers demand and supply signals, handles large-scale, complex supply chains, and maximizes or minimizes the impact of the inputs on the objective function.
By contrast, inventory planning aims to project inventory requirements across the entire supply chain network and planning horizon to meet customer service-level targets.
Inventory planning and optimization fit into the inventory review process within SI&OP. The consensus demand plan is an input into the inventory review process that focuses on setting inventory targets that align with the business's inventory budget and service level constraints. The inventory targets and the consensus demand plan are key inputs to the supply review process. As demand and supply are deterministic processes, inventory planning and review is a key process that maximizes the efficiency of the working capital tied up in inventory to absorb any variability in the demand and supply processes.
SAP Integrated Business Planning for inventory recommends total inventory targets to maximize profit while buffering for uncertainty and maintaining customer service levels.
Multiple operators are available to support planning processes related to inventory optimization.
Most of these operators are in the scope of the Harmonized Planning Area 2508 shipment.
Multi-Stage Inventory Optimization in SAP IBP for Inventory is a self-developed (confidential intellectual property), stochastic, non-linear, and optimization-solved approach. It is subjected to the hard constraint of meeting desired customer service levels while calculating internal service levels as decision variables.
SAP IBP for inventory simultaneously optimizes inventory across the end-to-end supply chain, constrained by customer service requirements with the lowest inventory holding cost. Internal service levels are assumed to be decision variables.
- Coordinated planning eliminates inventory over-buffering while meeting service-level objectives.
- Demand variability propagation to upstream stages avoids the bullwhip effect.
- Internal service level optimization provides significant inventory reduction.
- Streamlines centralized inventory planning.
SAP IBP for Inventory provides breakdowns of total safety stock, including the percentages due to demand and lead time variability.
SAP IBP can also calculate demand and lead-time variability from historical data.
The supply lead time calculation process has three components (SAP IBP add-on extractor, CI-DS templates to integrate data to IBP (to be transitioned to CI integration in future releases), and Supply lead time operator in SAP IBP).
Supply lead time operator uses dynamic lead time data from a defined historical horizon to determine the average length, variability, and outliers for the following types of lead time:
- Transportation lead time, which is the time it takes to transport goods from one location to another on a transportation lane
- Production lead time, which is the time it takes for the production processes of goods
- Supplier lead time, which is the time it takes for a vendor to deliver raw goods after a purchase order has been placed
In HPA, Total Average Leadtime and Total Average Leadtime variability (required for IO) are modelled as separate attributes on the header level. Inventory optimization doesn't require modelling activities and their durations, which are inputs to the supply algorithms.
The results of supply lead time calculations are used to perform the following business processes:
- Enhancing the quality of lead time inputs for inventory optimization operators
- Enhancing the quality of lead time inputs for time-series-based supply algorithms
A single-stage inventory operator is used to determine inventory parameters, such as recommended safety stock, reorder point, and target inventory position, for corrective maintenance.