Einleitung
Für eine optimale Bewertung und Messung der Datenqualität sowie der Ableitung gezielter Verbesserungsmaßnahmen, müssen im Vorfeld entsprechende Datenqualitätskriterien definiert werden.
In-depth data analyses often reveal significant discrepancies between the assumption of linear business processes and the operational data reality. Where strategic homogeneity is assumed, structural heterogeneity often prevails at the data level. Ignoring this complexity is not a technical oversight, but a fundamental threat to AI strategies and digital transformations.
When a C-level decision-maker looks at their company's process landscape, it usually presents itself in reassuring linearity. Take a standard process such as ‘order processing’ as an example: from a business perspective, this appears to be a monolithic block. It suggests uniformity, complete controllability and clearly defined responsibilities.
