Information Governance is an organisation-wide framework for managing information throughout its lifecycle and for supporting an organisation’s strategy, operations, and ethical, legal, regulatory, risk, and environmental requirements. IG establishes the authorities, processes, capabilities, structures, supporting mechanisms, and infrastructure to be a useful asset while reducing liability.
Data Governance vs. Information Governance: Closing the gap
Information Governance is generally accepted as a framework for managing information in all its formats, including the basic building blocks of data. But where does Data Governance fit in? Experts weigh in on the IG and DG relationship and how to maximise your information’s value and drive business goals by understanding each.
Iron Mountain’s 2024 Education Series kicked off with our first webinar of the year, Data Governance vs. Information Governance: Closing the gap. Addressing the long-standing relationship between information and data governance and what it means for organisations today, our panel of experts included Elizabeth W. Adkins, CRM, CA Emeritus, IGP at Davis Wright Tremaine LLP, and Patricia Fitzpatrick, Senior Director of Compliance, Privacy & Risk at Seyfarth Shaw LLP. We began the discussion with a poll where only 22% of the nearly 600 webinar participants said they understood the difference between Information Governance (IG) and Data Governance (DG). By the end of the discussion, this number jumped to a confident 89%.
Understanding the relationship between Information Governance and Data Governance involves not only clarity around definitions and functions but also the unique and dependent roles of each in furthering technology, compliance, and other organisation-wide ambitions.
How do these two disciplines collaborate and complement each other within the broader scope of achieving enterprise goals?
Defining Information Governance and Data Governance
In today’s technology-driven world, managing information effectively is paramount for organisations of all sizes and in every industry. Information Governance and Data Governance emerge as indispensable frameworks for overseeing data, records, and information throughout their lifecycles. But how do we define these two disciplines, where do they intersect, and what role do they play in organisational objectives? It’s crucial to explore and understand not only the difference between IG and DG but also how they operate in tandem, ensuring that organisational goals are met effectively. Defining the two terms and their functions has been the subject of some ambiguity in recent years.
Data Governance is a set of policies, processes, and practices to maintain an enterprise data model that addresses data quality, integrity, reliability, and usability within an organisation. These include the management of data elements/metadata to ensure the data is standardised, accurate, consistent, and complete across systems. By informing both the business and in support of operational goals and strategies, DG allows organisations to turn data into information, knowledge, and insights.
While no two organisations will treat IG and DG the same, it is evident that these disciplines, while distinct, necessitate a harmonious approach to data lifecycle management. By understanding the relationship and interplay between IG and DG, organisations can better position themselves to achieve compliance, enhance security, and leverage data for strategic insights, thereby reinforcing their operational and competitive stance in the market.
The convergence of Information Governance and Data Governance for enterprise-wide business goals
Organisations grapple with various challenges in managing data and information effectively. These challenges include developing system controls for data classification and loss prevention, establishing retention and destruction protocols, and ensuring compliance with regulations such as GDPR and HIPAA. Today’s data, records, and information management leaders recognise a clear interconnectedness between IG and DG, albeit with varying degrees of integration across their organisations. The confluence of Information Governance and Data Governance represents a critical shift in organisational strategies toward managing data assets comprehensively and purposefully.
A key component of the convergence of IG and DG involves viewing both structured and unstructured data through multiple dimensions, including compliance and business purposes. Clean, reliable data enables organisations to extract valuable insights through analytics, facilitating the development of tailored pricing models and enhanced customer engagement strategies. The concept of a data supply chain underscores the dynamic nature of data as it moves through various stages within and outside the organisation. By implementing comprehensive tagging and tracking mechanisms, organisations can effectively manage data throughout its lifecycle, ensuring its relevance and usability at every stage. This entails developing system controls and protocols for data classification, loss prevention, retention, destruction, and minimisation. These foundational elements are crucial for ensuring proper access, security, and management of data assets across various repositories.
Additionally, organisations are turning to the importance of collaboration between Information Governance and Data Governance practitioners. While IG professionals may focus on retention limits and dispositioning data for compliance purposes, DG leaders prioritise data accuracy, completeness, and usefulness. A collaborative approach enables organisations to strike a balance between regulatory compliance and leveraging data effectively for operational and strategic objectives.
The convergence of IG and DG signifies a holistic approach to managing data throughout its lifecycle, from creation to disposition. By integrating these disciplines and fostering collaboration across functional areas, organisations can optimise the value of their data assets while ensuring compliance with regulatory requirements and business objectives.
The crucial role of Information Governance and Data Governance in the age of AI
Integrating IG and DG principles provides a roadmap for maximising the value of data assets and driving sustainable organisational growth in the era of AI-driven innovation. As advanced AI tools become more prevalent across various industries, investment in both IG and DG becomes a strategic imperative for organisations aiming to harness their power effectively.
AI tools are playing a major role in influencing IG leaders to evaluate and further manage the security and access of their organisation’s enormous volumes of information. Information Governance is essential to ensure that there are stringent controls for the responsible implementation of AI. Individuals may have access to data and know what they want to use it for, but do they have the appropriate permissions?
The influence of AI and analytics on Data Governance is profound in its demand for the highest quality data to function optimally. Ensuring that data is appropriately tagged with relevant metadata is essential for AI algorithms to generate valid and complete results. Consequently, the foundational work of DG in maintaining accurate and reliable data is more critical than ever. The best use of AI emerges from having up-to-date, accurate, reliable data that is well-organised and properly protected from unauthorised access.
The symbiotic relationship between IG and DG underpins the successful application of AI within organisations, ensuring that data is not only compliant and secure but also positioned to provide actionable insights that drive business value.
Closing the gap
Building relationships across organisational departments is essential for information governance professionals seeking to understand and integrate data governance principles. As technology continues to advance and data plays an increasingly pivotal role in various domains of enterprise success, addressing IG and DG challenges will be essential for harnessing the full potential of data while ensuring privacy, security, and ethical integrity. By focusing on collaboration, preparing the framework for the adoption of AI, and demonstrating value through measurable impact on business goals, practitioners can continue to effectively bridge the gap between information and data governance to drive organisational success.
Foster cooperation and collaboration between the two functions
Interested in learning more about this topic? Visit the Iron Mountain 2024 Education Series to watch the on-demand recording of Data Governance vs. Information Governance: Closing the gap and to register for upcoming webinars.
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