Patterns over Averages

From Averages to Reliable Ranges in Liquidity Planning. Companies often still manage their liquidity based on averages, thereby systematically underestimating the uncertainty in cash flow. However, actual payment behavior often deviates significantly from contractual assumptions and is a key driver of forecasting errors.

This whitepaper shows how process mining and AI close this gap: By analyzing real transaction data, reliable payment profiles and forecast ranges are generated instead of static point values. This enables companies to manage their liquidity in a significantly more transparent, precise, and risk-adjusted manner while simultaneously gaining new insights for optimizing their working capital.