Managing duplicates across multiple teams or departments refers to the process of identifying and resolving redundant or conflicting data entries (like customer records, product IDs, or project files) created independently by different groups within an organization. This happens because teams often operate in silos using separate systems. It differs from simple duplication removal within one system by requiring cross-team coordination and agreement on data ownership and standardization rules.

For example, sales and billing departments might both maintain customer contact lists in different CRMs, leading to duplicate profiles when the same customer interacts with both teams. Similarly, engineering and procurement might assign different part numbers to the same physical component in their separate PLM and ERP systems, causing inventory errors. Central platforms like MDM (Master Data Management) systems or collaborative tools like SharePoint with strict metadata rules help enforce consistency.

Key advantages are improved data accuracy, operational efficiency (less rework), and better decision-making with single sources of truth. The main limitation is the significant effort required for initial cleanup, ongoing governance, and fostering cross-departmental collaboration to agree on data standards. Future developments involve AI-powered data quality tools to automate identification and cleansing. Without broad organizational buy-in and clear governance policies, successful adoption remains difficult despite the clear benefits.