Abstract
Sales forecasts are essential for a smooth workflow and cost optimization. Usually, they are assessed using statistical error measures, which might be misleading in a business context. This paper proposes a new dynamic systems model for an economic evaluation of sales forecasts. The model describes the development of the inventory level over time and derives the resulting overstock and shortage costs. It is tested on roughly 3,000 real-world time series and compared with the commonly used approach based on statistical measures. The experiments show that different statistical measures have no coherent evaluation, making their usage even less suitable for a practical economic application.
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