Challenge it addresses
5000 employees and hundreds of systems
Units and people across the enterprise were not in full agreement on the understanding of fundamental entities such as ‘Customer’
Data mastering systems/SVoTs were not consistently defined across the enterprise; integration decisions were localized rather than following a consistent framework
It was impossible to deliver predictable results in Change Management
Impact analysis
Project sizing and planning
Benefits
Enterprise Data Quality Scorecard provided MIS interfaces for insight and oversight
Causal Analysis Reports helped identify weak areas and causes of data quality issues
Financial and reputational impact due to low data quality was mitigated
Business stakeholders could be assured that data will be complete, accurate, timely, and suitable for business decision making, communications, and reporting; they were able to have a forum to report and receive service for data quality issues