The IBP for Inventory module of the SAP Integrated Business Planning supply chain planning solution promises to reliably handle this extensive task. But why is the optimization of inventories so difficult that a planning tool is needed for it?
Basically, the complexity of optimization is due to causes that have both an internal and external origin:
- Uncertainties in the network and in planning: occurring forecast errors in demand planning, demand fluctuations at the customer and procurement uncertainties in the own logistics chain make accurate demand planning difficult.
- Challenging conditions such as complex supply chains, comprehensive and variable bills of materials, fixed lot sizes, multi-sourcing, fixed time windows, and customers with different levels of customer service require a dynamic solution for inventory planning.
IBP - Inventories always precisely planned
SAP IBP is a cloud-based solution that maps real-time planning of processes along the entire supply chain. Different modules of SAP IBP support planning processes in all business areas with innovative planning algorithms and an intuitive user interface. Modules can be implemented and used individually. The planning of target and safety stocks falls within the scope of IBP for Inventory.
IBP for Inventory calculates safety stock levels and overall inventory targets based on multi-level inventory optimization across the entire network and all BOM levels. This is especially relevant for those companies that have a complex network and want to optimize inventory not only locally, but across the entire network and reduce inventory costs. Planning with IBP for Inventory uses a dynamic, statistical approach coupled with scenario analysis to build an optimal supply chain network and inventory planning. This approach allows multistage inventory optimization across all areas of the supply chain, improving service levels and delivery performance. What-if analyses are also used, where effects of changed sales volumes and service levels can be compared.
As a result, the uncertainties at the optimal location are compensated by stocks and the bull-whip effect or whip effect* is reduced.
Here's how it works:
- Based on historical sales figures and demand forecasts, demand uncertainties at all customer demand locations are calculated, and coefficients of variation are determined as a result of the calculation.
- The actual inventory optimization is calculated on the basis of the determined values by the optimization algorithm, but also on the basis of other parameters such as the degree of readiness to deliver, replenishment time, current consensus demand and others.
- In the final step, IBP for Inventory uses the recommended safety stock level as well as information on the minimum inventory level, cost per inventory unit, etc. to calculate further inventory key figures such as reorder level, stock range, monetary key figures, etc.
Key figures illustrated
All key figures and data, as well as the aforementioned demand history as the basis for inventory calculation, can be displayed and flexibly analyzed both in the browser-based FIORI user interface and in the IBP Excel add-in.
Input parameters can also be displayed in Excel + Add-In for IBP. Here the display is not only graphical, but detailed output to predefined values.
The calculation is performed by job, individual jobs can be started either from FIORI or directly from Excel with Add-In for IBP. After the calculation has been completed, Excel flexibly displays the result key figures in individual Excel sheets. An example: Demand forecast (tab Global IO Input & Output Parameters):
The optimization algorithm determines key figures such as a recommended safety stock per distribution center and week, the average service level, etc. The user can display the results graphically and make manual adjustments in the next step. The user can display the results graphically and make manual adjustments in the next step. Planners can flexibly compile the planning views themselves and aggregate and disaggregate the data as required.
A detailed display of input and output parameters shows an inventory plan that takes into account potential risks, allows detailed and accurate analysis, and thus enables network-wide inventory reduction. The automated calculation allows manual intervention and contributes to a high flexibility of inventory optimization. The individually adjustable calculation parameters make IBP for Inventory a tool that is tailored to the company - without the need for in-house developments.
*In supply chain management, the bullwhip effect is the phenomenon that fluctuations in demand affect the entire supply chain and become stronger the further you are in the supply chain from the end customer. By the way, you can learn how to deal with the bullwhip effect in a game here.
A detailed display of the freely definable parameters shows an inventory plan that takes into account possible risks, allows a detailed and accurate analysis and thus enables a network-wide inventory reduction.
