A research-based biopharmaceutical company adopted cross-domain data governance policies, procedures and processes to support its ERP migration.
About
Our client has contributed significantly to oncology research and development as a pioneer in virology medicine research and development. In addition to developing life-changing medicines, they partner with global health groups to treat, prevent and cure life-threatening diseases.
Industry: Biopharmaceutical
Background: An ERP migration from Oracle to SAP has been underway for three years. As part of this initiative, the FSFP team assisted in developing a formal data governance program.
Engagement Type
Principles, policies and processes for cross-domain data governance and domain-specific artifacts such as the data dictionary and data quality rules and standards.
Engagement Snapshot
- Cross-Domain Data Governance Artifacts – developed guiding principles, policies and procedures to establish a cohesive “North Star” for data governance.
- Domain Specific Artifacts – created a data dictionary, policies, standards and data quality rules for business partners (vendors and customers) and finance.
- Workflows – developed processes for modern data governance workflows and interim state deeds to ensure alignment across Oracle and SAP in releases 2 and 3.
- Data Quality Scorecard – analyzed information steward scorecards to identify data quality issues and worked with data owners to resolve them.
- Business Process Data Mapping – conducted data mapping of business processes to ensure all objects, datasets and attributes were considered for lineage analysis.
Opportunity Areas
Due to the limited capacity of data councils and owners, our client needed data governance expertise.
Impact
- Cross-domain consistency is embedded throughout the data governance organization based on the templates, principles, policies and standards instituted.
- As the data organization engaged with business areas and stakeholders, a common language helped create a cohesive message.
- Using both ERP systems simultaneously, a proactive data quality system within SAP is guided by modern data governance workflows, approval processes and data integrity considerations.
- FSFP implemented scorecards and procedures for reviewing and resolving issues.
- The client reduces downstream risks by understanding the impacts of data lineage changes.
