- SAP Managed Tags
MANAGEMENT SUMMARY
This blog demonstrates how SAP Business Data Cloud (BDC) can be used to implement a contribution margin forecast, which serves companies as a substantial controlling tool to steer financial results in the short- and medium-term. Combining SAC Planning with Datasphere (“Seamless Planning”) allows for (near) real-time usage of actual data from SAP BW to extrapolate the variable cost component of the contribution margin, while SAC Planning is used to forecast the revenue component and report on the resulting KPIs. The combination of the actual and planning data happens without the need for redundant data replication. Furthermore, this blog will briefly touch on how BDC can be leveraged to enhance this use case through a comprehensive path for BW modernization, the re-use of SAP-managed data products, and the application of advanced machine learning methods for forecasting.
RECAP
Before continue reading it is recommended to familiarize with the following preceding blog posts to properly understand the fundamentals:
- The Value of SAP Business Data Cloud (BDC) in The Context of Business Steering puts this blog post into perspective of a comprehensive blog series that aims to demonstrate the business value add of SAP BDC.
- Real-time steering with LIVE planning uncovers the "Seamless Planning" paradigm (which is the key enabler for below-described use case) and illustrates a practical end-to-end use case that leverages External Live Versions, our latest innovation in context of Seamless Planning.
MOTIVATION AND USE CASE
The motivation of this blog is to demonstrate a tangible implementation example for how BDC can be leveraged to enable effective and efficient business steering. The demonstrated use case is a contribution margin forecast which estimates future revenues and variable costs, calculating expected contribution margins over time. The contribution margin is particularly relevant for financial steering because fixed costs are, by definition, largely unchangeable in the short- and medium-term. Therefore, if a company aspires to impact financial results, management’s primary focus and opportunity for action resides in maximizing the contribution margin. In essence, the contribution margin is calculated by subtracting variable costs from revenues, with the remainder – that is, the contribution margin – available to cover fixed costs. The levers that management can actively influence on a regular basis are:
Such a contribution margin forecast can be implemented in an innovative fashion leveraging the Seamless Planning capability within BDC as explained in the following paragraph.
IMPLEMENTATION
Considering the above-described contribution margin levers, we are using the following BDC components for the corresponding implementation.
A SAC Story on top of a SAC Planning model is used to enter sales volume forecast and pricing assumptions (1). Upon publishing (2) the forecasted values (volumes, prices) are directly persisted within Datasphere (“Seamless Planning”).
In an Analytic Model (5) on top of the union view the relevant KPIs consisting of both forecast and actual data are calculated:
Forecasted revenues: Restricted measures filter on forecasted volumes and prices originating from the SAC planning model. A calculated measure multiplies these two measures to derive the forecasted revenue [forecasted revenues = forecasted sales volumes * price assumption].
Extrapolated variable costs: Restricted measures filter on actual volumes and total manufacturing costs originating from SAP BW. These measures are cumulated over the actual time horizon as selected per prompt (6). A calculated measure divides cumulated costs by cumulated volumes to derive the volume-weighted average costs per unit [weighted-average costs per unit = cumulated actual costs/cumulated actual sales volumes]. Note that this measure is kept constant over the time dimension to allow applicability to any forecast months (see below).
Expected contribution margin: A calculated measure extrapolates the actual variable costs by multiplying the volume-weighted actuals costs per unit (see above) with the forecasted sales volumes [extrapolated variable costs = weighted-average actuals costs per unit * forecasted sales volumes]. A calculated measure subtracts extrapolated variable costs from forecasted revenues to finally derive the contribution margin [contribution margin forecast = forecasted revenues - extrapolated variable costs].
It is now worthwhile looking at the unique highlights of the above-described setup. First, Seamless Planning within BDC combines "best of both worlds": SAC planning and reporting capabilities with Datasphere ETL and modeling capabilities. Second, SAC planning model entries are directly exposed within Datasphere upon publishing without the need for redundant data replication. Third, it would be generally feasible to access the actual variable costs virtually (as opposed to replicated), thus combining planning with actual data in real-time. However, note that regular snapshots (near real-time) of the actual data can be required for high-performant dashboards. Forth, the prompt to dynamically steer the time range for the weighted-average actual variable costs allows end users to sort of “smoothen” the data over time (when choosing a longer range) versus emphasizing more recent months to reflect latest changes in cost structures etc. Lastly, given the completely automated retrieval of the variable costs part of the calculation, end users only need to manually update the expected sales volumes and price assumptions. This allows for a fast forecast process with a high frequency (e.g., monthly rolling forecast) which is highly relevant in today’s dynamic market environment.
POSSIBLE ENHANCEMENTS
In the above-described implementation setup actual data is being acquired from an SAP BW system via standard data acquisition means in Datasphere (remote tables, real-time replication, etc.). However, for SAP BW systems (both BW/4 and on HANA) BDC opens up the path for comprehensive BW modernization through means of the Data Product Generator (please see this blog for further details).
Furthermore, the use case could be enriched with SAP-managed data products derived from an S/4 PCE system as part of a BDC formation. For instance, if the contribution margin forecast should be integrated into a broader plan/actual reporting solution, the relevant actuals could be built upon SAP-managed data products serving as significant accelerators given that the complete data orchestration is handled by SAP. You could directly start modeling within Datasphere and combine the forecast data with the actual data based on the SAP-managed data products. A detailed blog discussing how you can leverage data products in the context of planning will follow.
Finally, for more advanced forecasting techniques you could leverage SAP Databricks as part of the BDC formation. Imagine that instead of the manually provided sales volume forecast as in the above example you would generate such a forecast by means of statistical methods such as time series forecasting.
SUMMARY AND CALL TO ACTION
A contribution margin forecast allows companies to proactively steer financial results and can therefore be considered a crucial controlling instrument. SAP BDC enables an innovative implementation approach with clear benefits such as rapid, high-frequency forecasts through automated calculation of variable costs and replication-free, (near) real time combination of actual and planning data. Besides that, SAP BDC opens up the path for comprehensive BW modernization, thus allowing you to follow parallel streams: Implementation of innovative use cases while modernizing your SAP BW. Sounds like a plan to you? Please reach out to your SAP representative and register for your SAP BDC Discovery Workshop!
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