Governance Framework in your business
Governance Framework in your business

How to Apply This Framework: A Practical Example

By analyzing the issues within an organization, we can see that problems exist across multiple areas of data governance. The 10 governance pillars serve as a guiding framework—a compass that helps organizations identify and resolve data challenges effectively.

1. Data Policies & Standards: Establish the Rules

  • Related Issues:
  • Lack of clear data policies, leading to inconsistencies in data quality.
  • Misalignment between systems, causing incorrect sales data.
  • Discrepancies in data analysis results.
  • Poor reporting conditions for business data.
  • Need for Improvement:
  • The lack of clear data policies reduces data consistency and quality.
  • Errors arise due to misalignment between systems and reporting inconsistencies.
  • A unified data policy and standard framework must be established to enhance clarity and integration.

2. Data Stewardship: Who Manages the Data?

  • Related Issues:
  • Differences in sales and management indicators.
  • Lack of connection between sales data analysis and dashboards.
  • Difficulty in extracting the true business value of data.
  • Challenges in monitoring business and project performance.
  • Need for Improvement:
  • Without clear ownership, data inconsistencies arise.
  • Organizations struggle to derive insights or establish reliable monitoring indicators.
  • Define the roles of data stewards and assign responsibilities for better accountability.

3. Metadata Management: Create a Data Dictionary

  • Related Issues:
  • Difficulty in understanding the business value of data.
  • Lack of connection between duplicated or fragmented data across systems.
  • Need for Improvement:
  • Insufficient metadata management makes it difficult to track data meaning and relationships.
  • A structured metadata repository should be built to enhance business value and system connectivity.

4. Data Quality Management: Can We Trust the Data?

  • Related Issues:
  • Unclear data quality standards.
  • Discrepancies between sales and management data.
  • Inaccurate sales reports due to system misalignment.
  • Reports generated from unreliable data sources.
  • Need for Improvement:
  • Poor data quality results in untrustworthy insights and discrepancies.
  • Strengthen data quality management processes and perform regular quality checks.

5. Data Security & Privacy: Keep Data Safe

  • Related Issues:
  • No direct issue, but security concerns affect all aspects of data governance.
  • Need for Improvement:
  • Weak security and privacy controls could compromise data integrity and impact business operations.
  • Strengthen data access control policies and privacy frameworks to enhance security.

6. Data Lifecycle Management: Managing Data from Start to End

  • Related Issues:
  • Duplicated and fragmented data across systems.
  • Difficulty in utilizing data for business insights.
  • Need for Improvement:
  • Poor lifecycle management leads to data redundancy and wasted resources.
  • Implement a structured data lifecycle plan to optimize data storage, use, and disposal.

7. Data Governance Committee: Collaborative Decision-Making

  • Related Issues:
  • Misalignment between sales data analysis and dashboards.
  • Lack of coordination between business information and project monitoring indicators.
  • Need for Improvement:
  • The lack of a centralized governance body leads to inconsistent reporting and decision-making.
  • Establish a data governance committee to align collaboration and decision-making across teams.

8. Change Management & Communication: Ensuring Smooth Transitions

  • Related Issues:
  • System misalignment affecting sales data accuracy.
  • Disconnected communication between sales data and reporting tools.
  • Need for Improvement:
  • Poor communication and change management lead to errors during system updates.
  • Strengthen change management processes and establish effective communication channels.

9. Metrics & KPIs: Are We on the Right Track?

  • Related Issues:
  • Lack of business performance and project monitoring indicators.
  • Inability to extract true business value from data.
  • Need for Improvement:
  • No clear success metrics exist to measure business outcomes.
  • Define measurable KPIs and set up a monitoring system to track progress.

10. Continuous Improvement & Feedback Loop: Keep Getting Better

  • Related Issues:
  • All issues require ongoing improvements.
  • Need for Improvement:
  • Current governance processes lack a continuous improvement mechanism.
  • Introduce a feedback loop to ensure constant evaluation and optimization.

By ByteBloom Morgan

The author has lived and breathed the life of a data steward for years, wrestling with data to keep organizations on track. Through countless hours of consulting—both giving and receiving advice—learned one thing: explaining and leading data governance is no easy feat.

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