Cutting through the backlog
Establishing clearly defined policies and putting them in place for all new content is a solid start, but that doesn’t automatically take care of the existing piles of obsolete content within the firm. This highlights a practical challenge around tackling ROT: it’s not realistic to ask an associate to sift through years of accumulated files manually. The sheer volume of data and the fear of deleting something important can lead to high stress levels.
Fortunately, this is where technology is rapidly evolving to meaningfully change the equation. AI capabilities in the DMS are approaching a stage where they can analyze stored content, generate a detailed audit of content the firm actually holds, and classify content by type.
For instance, they can help identify documents that are older than a defined threshold, classify them accordingly, and distinguish between materials that require long-term retention – such as wills, which may need to be preserved for nearly a century – and those that do not. They can also surface documents containing personal data that should have been deleted long ago under EU-GDPR, FINRA, or other US state-level regulatory directives that have strict requirements around how long data can be retained.
This process of analysis and identification can also include large files that have been provided as part of a case. These can include high-definition images, medical imaging data, or massive CAD files if it’s a case involving a faulty construction. If no longer needed, these files can be disposed of – freeing up a significant amount of valuable storage space for the firm. This level of automated classification is critical for cutting ROT down to size. Without it, firms will feel overwhelmed and risk non-compliance repercussions.