Why You Need an Information Governance Strategy

Companies both large and small are dealing with data overload, which underscores their need to develop a solid information governance strategy. Casepoint explored this topic in a recent article on its website.

Worldwide, the total amount of data that is consumed, created, copied, and captured is more than 60 zettabytes. That figure is expected to jump to 175 zettabytes of data in 2025. It’s critical that companies maximize value and minimize risk across the vast data sets.

Information governance (IG) is crucial for managing and protecting an organization’s data assets, ensuring compliance, and streamlining information management processes. It is a holistic approach that implements controls, processes, metrics, and roles to treat information as a valuable asset. It addresses unmanaged and inconsistently managed information, reducing legal risks and improving data utility.

IG’s key principles include educating employees, confirming data integrity, storing information appropriately, controlling information proliferation, disposing of obsolete data securely, ensuring data security, complying with legal requirements, and aligning systems with IG standards.

There are several challenges to IG implementation, such as managing big data volumes and navigating compliance and regulatory issues. Addressing these challenges requires strategic approaches, including the establishment of data classification programs and consistent policies for defensible disposal and retention management.

There is a difference between IG and data governance, as Casepoint explains in the article. While IG focuses on the holistic management of information assets, data governance pertains to policies governing data reliability and accuracy at various levels. Both are essential components of effective data management strategies, contributing to informed decision-making and organizational efficiency.

Through strategic implementation and technological integration, organizations can navigate the complexities of data management, maximize data value, and mitigate associated risks effectively.