Beyond IT Service Management: ITIL as a Strategic Enabler of Data Governance and Management
# ITIL
Why Modern Data Governance Requires More Than Data Frameworks Alone
June 16, 2026
Yurguen Penaranda Thomas
Beyond IT Service Management: ITIL as a Strategic Enabler of Data Governance and Management
1. Introduction: The Growing Importance of Data Governance
Nowadays, due to the undeniable technological dependency organizations have for their operations, massive amounts of data are generated and consumed at every moment. This includes: customer or user data, employee data, financial data, competitor data, supplier data, and technological performance data, to mention a few examples.
This has led more and more organizations to adopt a data-driven culture, where strategic and operational decisions are supported by the analysis of quantifiable information, instead of depending solely on intuition or the judgment of the organization’s leaders.
Evolving into a data-driven organization is not something achieved overnight and may present several challenges: lack of information traceability, information silos, poor data quality, and information security risks, among others. If these challenges are not managed correctly, the fulfillment of the three pillars of Information Management may be affected: ensuring the availability, integrity, and confidentiality of information.
Can ITIL help structure data governance and management? This article will address how a proper adoption of ITIL can contribute to effective data governance and management within the organization.
2. ITIL Foundations Relevant to Data Management
The ITIL Value System (ITIL VS)
The ITIL Value System is a model that shows how all the organization’s components and activities work together as a system to generate products and/or services that enable the co-creation of value between the service provider and the service consumer. This model and the generic concept of “value” presented by ITIL allow it to be adapted into specific value streams according to the different value approaches identified by the organization.
Under this generic approach, the organization can define value streams focused on data governance and management, applying the components of the ITIL VS to this specific value focus.
Key Management Practices
Management Practices are one of the five components of the ITIL VS. These practices can be adapted for data governance and management. Below is how some ITIL management practices can be adapted for data governance and management topics:
- Configuration Management: This practice allows, through a CMDB, the identification of which Configuration Items (CIs) are part of each service, what their characteristics are, and how these elements are interrelated. Expanding the scope of a CMDB to a data-focused approach makes it possible to identify where data sources are stored and what infrastructure supports them. This will be broadly addressed later in the article.
- Change Enablement: This practice can be adapted for change control in data structures and for change control in the infrastructure where such data is hosted and processed, ensuring that an adequate impact analysis is carried out, minimizing the possibility of affecting data availability.
- Information Security Management: From a data perspective, this practice ensures that topics such as access management policies for data sources, definition of roles, profiles, permission types, and access management are defined. This is intended to ensure that people only have access to the data sources and reports they truly require, thus reducing the possibility of risks associated with access to and/or modification of data to which the person should not have access.
- Incident Management: This practice focuses on the management (detection, analysis, and resolution) of incidents related to data, ensuring the availability and integrity of the data.
- Service Request Management: This practice focuses on handling service requests related to access to data sources and reports. Addressing requests such as granting new access, modifying existing access, or even revoking access. This aligned with the policies and restrictions defined by the Information Security Management practice, in order to avoid data leakage situations.
The Strategy Management, Portfolio Management, and Project Management practices allow the identification of what types of technological adjustments can be made in order to achieve more efficient data governance and management, and subsequently, how to execute these adjustments through project management.
The Relationship Management and Supplier Management practices allow the identification of how data is received from and shared with other organizations. The Continual Improvement practice allows the identification and execution of improvement actions for data governance and management.
3. The CMDB: From IT Assets to Data Assets
A CMDB generally focuses on the characteristics and relationships of IT components that enable the execution of digital services and products (servers, databases, applications, telecommunications elements, etc.).
However, the generic CMDB model proposed by ITIL makes it possible to reimagine this tool with a focus on data management. This is achieved by including CI categories specific to data management, such as ETL Pipelines, Datasets, and Reports.
For the data management approach, this makes it possible to take advantage of the benefits of having a well-defined and updated CMDB, such as when coordinating a change in technological infrastructure, being able to identify which elements related to data management may be affected (applications, databases, datasets, reports, etc.), and thus validate whether it is necessary to take actions to reduce or fully mitigate the impact on these data assets, such as rescheduling the execution of the change to a time when these assets are not being used.
Another use case for having the data management layer within the CMDB is that when an availability or performance incident occurs in data management assets, the CI relationships maintained in the CMDB can facilitate finding the infrastructure component generating the impact on the data assets, thus speeding up the restoration of normal operations and even enabling the identification of the root cause and implementation of a permanent solution more quickly.
4. Practical Implementation Approach
Below is a proposal on how data governance and management can be included within the organization’s management practices:
1. Expansion of the CMDB Model:
Define new CI types related to data (such as those mentioned above), indicating what their attributes and relationship types will be. Then, the configuration of these CI types must be carried out in the ITSM tool used by the organization in order to finally load all CIs of these types.
2. Complement ITIL Adoption with the Adoption of a Framework for Data Governance and Management:
There are globally recognized frameworks focused on best practices for data governance and management. These include recommendations for topics such as: architecture, storage, quality, security, data modeling, metadata, and data warehousing, among others. These frameworks can be complemented with ITIL in order to enhance the value of both frameworks by having a holistic view of data management and IT management.
3. Integration of the CMDB with the Data Catalog:
The Data Catalog is a common element in data management and governance frameworks. It can be defined as “a tool where the organization registers and describes its data so that people can know what information exists, what it means, where it is located, and who is responsible for it.”
This tool can be complemented with the CMDB, providing greater data traceability, thus making it possible to relate what type of data exists in each report, which repositories it consumes, in which database it is stored, in which application the reports are executed, and, in turn, on which infrastructure the application runs.
4. Integration with ITIL Management Practices:
As previously explained, data management and governance can be included within the ITSM management practices proposed by ITIL. Data incident models and data change models must be defined, establishing how these types of incidents and changes will be handled. Define how the layer of data CI types in the CMDB will be managed, including the creation, modification, or deletion of CIs of these types. In addition, define at the Service Desk and Information Security Management levels how access requests related to data assets will be managed, having clarity regarding the type of profiles and permissions, and the approval and review flow for these types of requests.
5. Conclusion
As shown, the ITIL framework has a native integration with data governance and management, since nowadays practically all data is generated, stored, and shared digitally through information systems. The CMDB plays a key role in this integration, serving as a “bridge” between the Data Catalog and all the technological infrastructure that supports data governance and management.
For ITIL best practices to contribute to data governance and management, specific value streams must be defined for handling topics (incidents, changes, service requests) specifically related to data. Today, ITIL is no longer only a framework for IT management, but even in this use case, it can become an enabler for data governance and management.
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