Master Data Management would like to congratulate our partner, Precisely, for their recognition in The Forrester Wave™: Data Governance Tools 2023

Forrester Research’s Michelle Goetz summarises key findings in her blog post Are Data Governance tools ready for Data Governance

• Data governance has traditionally been IT-centric but is shifting towards a strategic enterprise competence.
• Shifting from project-oriented data governance to a strategic program requires rethinking the operating model, introducing new business-driven roles, responsibilities, and processes.
• Data management technology should focus on business outcomes and strategy, not just automation and scalability.
• Data governance tools are evolving towards Data Governance 2.0, emphasizing business ownership, strategy, and outcomes.

What is Data Governance 2.0?

“Data Governance 2.0” refers to an evolved and more advanced approach to data governance compared to traditional or earlier versions. It represents a strategic shift in how organizations manage and govern their data assets. Here are the key characteristics and elements associated with Data Governance 2.0:

1. Business-Centric: In Data Governance 2.0, the focus shifts from being primarily IT-driven to being business-driven. It involves business leaders, stakeholders, and subject matter experts in the governance process. Data governance becomes closely aligned with business objectives and outcomes.
2. Strategic: Data Governance 2.0 places a strong emphasis on aligning data governance efforts with the strategic goals of the organization. It involves defining a clear data strategy that outlines how data will be used to drive business value and competitive advantage.
3. Emphasis on Business Outcomes: Unlike earlier versions of data governance that may have focused on technical aspects or compliance, Data Governance 2.0 seeks to measure the impact of data governance initiatives on actual business outcomes. It connects data conditions, data quality, and data management practices to tangible business benefits, such as regulatory compliance, cost reduction, revenue growth, and risk mitigation.
4. Holistic Approach: Data Governance 2.0 recognizes that data governance is not limited to a single tool or technology but requires a holistic approach that covers various aspects of data management, including Master Data Management (MDM), data quality, Information Lifecycle Management (ILM), metadata management, and data security.
5. Advanced Tools and Solutions: Organizations implementing Data Governance 2.0 may require advanced tools and solutions that support not only the technical aspects of data governance but also the strategic and business-oriented aspects. These tools should enable better reporting, analytics, and decision-making related to data governance.
6. New Roles and Responsibilities: Data Governance 2.0 often necessitates the creation of new roles and responsibilities within the organization. This may include data stewards, data champions, and data owners who take ownership of data governance activities and ensure alignment with business goals.
7. Continuous Improvement: Data Governance 2.0 recognizes that data governance is an ongoing process, not just a one-time project. It involves continuous monitoring, assessment, and improvement of data governance practices to adapt to changing business needs and data challenges.
8. Integration with Business Processes: Data governance practices are integrated into various business processes, ensuring that data is managed and used effectively in day-to-day operations.

Overall, Data Governance 2.0 represents a more mature and business-focused approach to data governance that aims to maximize the value of data as a strategic asset for the organization. It acknowledges the evolving nature of data management and its critical role in achieving business success.

What does Michelle think you should take into account when considering data governance tools?

Key Technology Considerations for Data Governance 2.0

• There is no single solution, but data quality, MDM (and reference data management) and metadata management often are tightly connected to governance and capabilities should be integrated into any tool
• Identify tools that enforce best practices for the administrative aspects of data governance – keep in mind the end user is the business and may not be a “data geek”.
• Look carefully at what it takes to connect data conditions and processes to business outcomes as this effort may be a BI on Data project.
• Understand the vendor roadmap – choose those that have solid strategies and prototypes/early releases geared toward the strategy, process, and administrative aspects of governance, not just data management and data processing.

Reference clients cite the ability to enable data governance for business and the solution’s workflow, configuration, and customization options as key decision points

Forrester Research on Precisely Data360

Backed up by IDC

Forrester’s findings are backed up by the 2022 IDC Marketscape report for Data Catalogs, which also positions data360 as a Leader. According to the report, Precisely should be considered “when looking for a business-focused solution with integrated data catalog, data quality, and data integration capabilities.”

Companies that are ready to move beyond the technically driven approaches of the past, and are ready to embrace data as a strategic business enabler should talk to us.