- Not easy to acquire data, with long lead time for data creation and mass data changes
- Handling project-related master data, e.g., asset capitalisation and related issues
- Handling consumer data in the retail segment, e.g., privacy and data security
Spare Parts Data Management to reduce inventory costs
- Handling asset data, e.g., GIS information, data collection from the field, serialized assets
- Outdated or incorrect characteristics, hence the need to incorporate industry standards
- Data integrity issues—no validation mechanism across different datasets
- No governance around supplier integrity and procurement, hence increasing risk, compliance, and sustainability issues