Automotive & Industrial Manufacturing

Failure to ensure high-quality material master data can lead to critical process disruptions - such as planning mistakes and material shortages. Proper system support is not possible, and manual intervention becomes necessary.

Data Quality Navigator's comprehensive repository of validation rules covering a wide range of material-related processes identifies potential process disruptions and enables proactive countermeasures.

Poorly managed demand and capacity planning data results in delayed supplier delivery and causes disruptions in the production schedule.

Integrating data from different source systems, the Data Quality Navigator supports the validation of the consistency between material demand requirements from program planning and the required supplier capacity.

Complex demand patterns require adequate parameter settings for digital line supply processes (e.g., number of KANBAN containers and replenishment strategy). Failure to do so may cause excessive stocks, missing parts, and eventually, line stoppages.

By combining advanced optimization algorithms with a powerful simulation engine, the Data Quality Navigator can detect critical demand patterns and identify inadequate out parameter settings. Decision-makers can directly derive optimal parameter settings to prevent overstock or line stoppages.

During a production launch, data issues often cause unstable logistics or production processes, resulting in material excess or shortages, discrepancies between system and physical inventory, and line supply delays - eventually leading to frictions during the start of production.

Data Quality Navigator’s comprehensive repository of validation rules identifies inconsistencies and enables their elimination before they can cause problems.