Establishing and operationalizing the Data Governance department
One of our HYGHT team members has been taken over the interim manager role of Head of Data Governance in one of the leading Pharmaceutical companies. Establishing a Global Data Governance organization that will anchor Data Governance in key Line of Business across the enterprise. Additionally, the goal is to refine and operationalize the data governance framework, and drive the design of an enterprise Semantic Layer that caters to individual Line of Business needs while making data FAIR (findable, accessible, interoperable, and reusable).
at a glance
Company Size
global market leader
Location
Nordics
Period
03/23 - 10/24
Industry
Life Sciences
Main Services
Data Governance
From theory to practice to business impact
01
Challenges
- Integration of Data Governance: Despite recognizing data governance as a critical success factor, the challenge was its lack of integration into solution delivery streams. This resulted in unsuccessful initiatives and hindered the achievement of strategic objectives.
- Theoretical vs. Implementable Framework: Numerous consultants attempted to define a theoretical data governance framework, which posed a significant challenge due to its lack of implementability. The need was to translate theoretical constructs into a framework that could be practically applied within the organization.
- Practical Application of Data Governance: Data governance was initially introduced as an impractical concept, which led to a limited willingness to concentrate on this critical aspect. The challenge lay in shifting perceptions and demonstrating its practical value.
02
Procedure
- Operating Model Review: Conducted an extensive review of the existing operating model to understand how solutions are defined and shaped.
- Solutioning Approach: Developed a clear approach delineating roles and responsibilities, ensuring accountability and effective execution.
- Alignment of Data Governance Roles and Responsibilities: Aligned data governance roles, responsibilities, and interaction models with decision-making dynamics to ensure seamless integration.
- Hiring Key Personnel: Recruited data governance lead roles with a focus on implementing data governance across different business domains.
- Data Governance Rollout Methodology: Designed, tested, and validated a holistic rollout methodology to effectively deploy data governance across the organization.
Results
- Strategic Decision-making: Improved data quality leading to enhanced decision-making.
- Accountability: Clear role definitions boosting accountability and efficiency.
- Streamlined Operations: Refined processes through operating model review.
- Effective Implementation: Successful data governance execution via dedicated lead roles.
- Business Value: Increased value from accurate, compliant, and consistent data.
Project Highlights
01
Successfully formed a Center of Excellence (CoE) for data governance, and embedded it into key line of business initiatives, thereby streamlining information management and enhancing data quality.
02
Initiated a data governance pilot program in crucial commercial area affiliates, devising a mechanism for large-scale, global implementation. This strategic move enabled standardized data practices and policies globally.
03
Developed and refined a robust data governance framework, translating theoretical constructs into practical applications. This has resulted in improved data accuracy, compliance, and decision-making across the organization.