Customer Profile

Industry: Life Sciences
Employees: ca. 100.000
Revenue (2019): ca. 40 Milliarden 

Our customer has been looking for possibilities, to establish a more transparent and agile supply chain management. Together with the customer we conceptualized and implemented a smart business intelligence solution for the prediction of inventory developments. Today, the customer uses the tool in the areas of inventory management, performance management as well as for controlling purposes.


Inventories are a key component for producing industries – they can be very volatile and are dependent on a number of factors, such as the quality of forecasts, available production capacities or raw material availability. Because of their underlying optimization potential, the steering of businesses is centered around the management of inventories: Too low inventories come at the risk of supply chain interruptions, whereas too high inventory levels result in opportunity cost in the form of higher capital commitment. “Working Capital Management“ is the key word: Companies try to find the optimal balance between the two extremes. As a result, Working Capital Management is of central meaning for producing industry sectors.

Due to his fully SAP APO-based planning, our customer has already been in full possession of inventory projection on product level. The problem was that their planning tool was not allowing to aggregate data to any higher level, let’s say to a brand, product portfolio or legal entity level. Such reports had to be created manually and resulted in hours of manual efforts – each month. Even-though our customer was able to create the reports manually, it has shown that those reports have been highly prone to errors. Furthermore, the used software has been used way past its capabilities, as it resulted in frequent crashes and data loss.


Together with our customer we identified significant potential. An automated solution would come with multiple benefits:

  • Reduction of manual efforts through fully automated, monthly calculations
  • Flexible reporting of inventory development on any aggregation level – from stock keeping unit (SKU) per location up to global company level
  • Detailed authorization concept in order to make data available only to selected users
  • Solution enables users to focus on analysis and interpretation of data (instead of report creation)
  • Easy detection of bad data quality or planning errors
  • Historization / versioning of calculated inventory developments (monthly snapshots)
  • Increased transparency of their supply chain planning through monthly report of global planning data
  • Projected inventory developments available in two measures: per quantity (base unit of measure, e.g. kilograms or pieces) and per value (with any price account, e.g. standard price, or CoGS price)


To fulfill the versatile requirements of the targeted user groups (supply chain managers, inventory managers, performance managers), we had to conduct an in-depth analysis of stakeholder requirements. It could be shown early that the solution would be suitable for all user groups – however, the required granularity of calculated data needed varied and needed to be much finer than initially expected. As a rule of thumb: Operative users (e.g. production planners) need a much finer granularity than supply chain managers, which have a rather high-level view on their supply situation. The main challenge was to fulfill all these requirements with just one solution. Our mission was clear: Create a tool that is flexible enough to be used by operative, tactical, and strategical users. Another challenge turned out to be the management of insufficient data quality: How would you predict inventory developments; in case no planning data is available or in case the projected inventory development is clearly wrong? Would you just show the error, or would you have a fallback logic in place to cover this up?


It was of highest importance for this project that the customer already had all relevant data available in just few data sources and in a harmonized & standardized way. Otherwise, we would have spent much more time just retrieving and transforming the right data. Furthermore, it was essential, that almost the entire supply chain planning was based on SAP Advanced Planner & Optimizer (APO) or SAP Integrated Business Planning (IBP).

First, the requirements have been identified together with the customer. We put a strong focus on involving all user groups into the discussions as early as possible. Together with these user groups we identified and analyzed all relevant data sources. After initial data analysis we could attest that the data quality of our customer would be sufficient for the majority of its portfolio, so that we could kick-off the implementation by building a first proof of value within three weeks. Together with the customer, we brainstormed the different calculation logics that were needed regarding some specialties on how the customer counted his inventories – especially regarding goods in transit and bad data quality. As a central part of that logic, we defined a calculation that would deal with bad data quality, but at the same time show this situation so that supply chain planners could work on optimizing their planning in APO.

As described, this proof of value has been built within three weeks and has proven that the concept was mature enough for official backend and frontend implementation. Nevertheless, we identified several gaps in our logic, which we worked-out step by step during the implementation process.

Within several months the first technical version of the solution was available and could be tested by us. In parallel all developments have been documented extensively and a concept for later user training has been developed. In multiple iteration the logic of the tool has been refined, so that after one year the first fully functional version of the tool was rolled out to the users. The feedback was highly positive, so that two more iterations / versions of the inventory projection have been scheduled and implemented until now. Those versions led to an improvement of projection quality, made the solution available to new business areas and came with some functionality extensions as requested by the business.