Driver-based planning: Quality through transparency and scenarios

Today’s companies face enormous pressure to change: volatile markets, geopolitical uncertainties, digital transformation, and regulatory requirements are shaping the business environment. Under these conditions, traditional planning approaches based on detailed figures and linear planning cycles quickly reach their limits. Although they provide a high level of detail, they often leave one crucial question unanswered: Which factors actually determine the development of sales, costs, and earnings? This is precisely where our webinar comes in. It highlights the need for driver-based planning and shows how controllers can enhance the quality and relevance of their planning processes – quickly and effectively.

Driver-based planning focuses on causal relationships. Instead of laboriously consolidating target figures in time-consuming coordination rounds, it systematically identifies which value and cost drivers significantly impact business performance and how changes in these drivers affect financial results. The outcome is models that are not only grounded in historical data but also reflect the company’s future viability.

The relevance of this approach becomes particularly clear in light of the Principles of Proper Planning (GoP). These require completeness, traceability, and transparency  with regard to assumptions, risks, and opportunities. While traditional planning often relies on rigid point estimates, the GoP call for a range of plausible scenarios. This is where driver-based planning offers a methodological advantage: it enables the simulation of different developments, the modeling of ranges, and the visualization of interactions between drivers. The result is a planning processt hat is not only formally compliant but also realistic and meaningful for management.

Another key aspect is the close linkage between operational and financial variables. Driver models connect key indicators such as sales volumes, productivity, or capacity utilization directly to earnings, balance sheet, and liquidity variables. This consistency satisfies the GoP requirement for a logical and coherent planning structure. At the same time, the documentation of driver models facilitates validation by internal and external auditors.

Finally, driver-based planning supports the cultural shift required in controlling. Planning is understood less as a static set of numbers and more as a management tool that provides orientation, exposes uncertainties, and opens up strategic options. This marks a decisive step toward transforming planning from a pure control mechanism into an agile, forward-looking instrument.