Use cases
Master data and AI?
Efficient master data management (MDM) is essential in order to remain competitive in times of increasing data diversity and digitalization. Up-to-date, correct and complete master data is essential in order to design processes efficiently, reduce costs and minimize risks.
With artificial intelligence (AI), master data can be permanently and automatically cleansed, enriched and optimized – for data quality by design.
- Permanently high data quality
- Basis for efficient process automation
- Relief from experts
- Error and risk minimization
- Minimization of expenses in the context of IT migrations, mergers and acquisitions (M&As) and consolidations
AI use cases master data optimization
Problem: 20-30% of products and materials are often not or not correctly assigned to material groups, customs tariff numbers and other classes. Inefficient processes and manual rework unnecessarily burden experts.
Solution: AI analyzes product data and automatically classifies it according to standards such as ECLASS and other hierarchies.
Advantages: Reduced manual effort, consistent data quality and efficient processes.
Problem: Duplicates within your master data, such as duplicate supplier or material entries, lead to errors and inefficiencies.
Solution: AI recognises and consolidates duplicates and suggests solutions for merging information and golden records – for existing data and new master data.
Benefits: Less effort for migrations and master data maintenance, reduced error rate and smooth business processes.
Problem: Incomplete master data makes decision-making difficult and hinders process automation.
Solution: AI automatically fills in missing information, e.g. by comparing it with external and internal data sources, images, invoice documents or the forecast of missing information, such as weight.
Advantages: Optimal basis for process automation, more informed decisions and less manual post-processing.
Extraction of product features from product descriptions
Problem: Product information is often in an unstructured form, e.g. in PDF or Office documents or images. The manual transfer and assignment to the fields in your PIM or ERP system sometimes requires expertise and manual effort.
Solution: AI extracts relevant properties from texts and images and assigns this information to your structures and fields in the target systems.
Advantages: Always up-to-date and complete database, simple search via product properties, better database for forecasts and well-founded decisions.
Problem: Traditional customer segments such as “gold, silver, bronze customers” are often too coarse and insufficiently differentiating.
Solution: AI analyzes customer data and recommends meaningful segments based on a variety of parameters. New and existing customers are automatically assigned to the appropriate segments.
Advantages: More precise customer approach, targeted marketing and sales measures and an optimal basis for sales reporting.
Further use cases
Discover exciting use cases from different areas of the company and be inspired by how other teams find and implement innovative solutions. This exchange opens up new perspectives and creates valuable synergies for joint growth.
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