Beyond the box: The digital impact on retention schedules

80% answered Yes; 13% answered No, 7% answered Unsure

This sentiment underscores the growing recognition of the link between data and traditional records management. But it’s the tougher questions that come next. As businesses generate vast amounts of data daily, the challenge of integrating this digital influx into conventional retention schedules becomes increasingly complex.

What impact does data have on records and information management (RIM)? 

Where is the common ground between records and data management?

How do we navigate data governance and retention in modern organizations?

The evolution of retention schedules

Retention schedules are an essential part of records and information management, dictating how long records must be kept to meet various requirements. These requirements can include everything from industry regulations to statutes of limitation and historical value. In recent years, the shift toward digital and electronic records and the complexity of privacy laws have made retention schedules more intricate and more difficult to transpose.

While some organizations may not include data in their schedules yet, there’s an appetite to start doing so, especially where personal identifiable information (PII) is concerned. Stricter privacy laws are prompting some organizations to revert from broad classifications to more granular data classes, thereby impacting retention.

Determining what makes a record and what makes data can also complicate how the retention of each is defined and decided. The panelists agreed that data is seen as raw, unorganized details that require context to become useful, akin to individual building blocks that only gain meaning when assembled into a coherent structure. In contrast, records are structured and contextualized data that document decisions, actions, or transactions.

Video clip: How do we define data vs. record?

Changes in Information Governance and Data Governance

The lifecycle of data is different from the lifecycle of records, and governing them requires different views and potentially different retention periods. But that doesn’t mean Information Governance (IG) and Data Governance (DG) work alone. By bringing IG and DG together, we can avoid data silos—those isolated pockets of information that no one can seem to find.

Video clip: The importance of Data Governance

The intersection of IG and DG views structured and unstructured data through multiple dimensions, including compliance and business purposes. Clean data fuels analytics that drive better pricing, customer engagement, and insights. A comprehensive data supply chain approach tracks data movement within and outside your organization. Tagging and controls ensure data quality and security throughout the lifecycle, from classification to destruction. These foundational elements are crucial for ensuring proper access, security, and management of data assets across various repositories.

Evolving collaboration between Information and Data Governance leaders ensures that the data we use is accurate, meets all the rules and regulations of our industries and jurisdictions, and gets stored or deleted according to a clear plan. It’s like having a central system for all your data puzzles, making it easier to find the right pieces and build a complete picture.

The road ahead for data and records management

The world of records management is on the cusp of significant change. As both a user of data and a creator of records, artificial intelligence (AI) presents new challenges and opportunities. The effectiveness of AI depends on the quality of the data it works with, and there are still challenges to be addressed in terms of terminology, context, and ownership. While we didn’t reach a definitive answer on how AI will be used in the future, our panelists all agreed on the importance of collaboration and clear communication.

Video clip: Retention strategies in modern organizations

Here are some key takeaways for organizations navigating the impact of AI and data on records management:

• Embrace a data-driven approach:

  Understanding your data is crucial. Identify its location, purpose, and users. This clarity is essential for informed decisions about retention and analysis.

• Standardize terminology:

  Ensure everyone involved uses the same terms when discussing data and records. This avoids confusion and fosters a more productive dialogue.

• Focus on consistency and governance:

  While achieving perfection might be unrealistic, strive for consistent practices and good governance in managing your records. Incremental improvements are key.

• Consider AI potential:

  While AI for retention schedules is still under development, its potential for legal update tracking and data analysis recommendations is promising. But remember the “garbage in, garbage out” rule: The quality of AI outputs hinges on the quality of your data.

• Start with an assessment:

  Before implementing major changes, conduct a thorough assessment of your current practices. This includes understanding existing policies, terminology, and ownership structures.

• Communication is the priority:

  Maintain open communication with stakeholders, including data owners and privacy groups. Discuss data purpose, usage, and retention needs before moving forward with program changes.

By working together and establishing clear communication channels, organizations can ensure their records management practices are efficient, compliant, and future-proof.

Watch the full webinar

Interested in learning more about this topic? Visit Iron Mountain’s 2024 Education Series to watch the on-demand recording of Beyond the box: The digital impact on retention schedules and to register for upcoming webinars.