Published On December 01, 2020
The advantages of an automated records management system are outlined in the results of a 2020 survey from the Association for Information and Image Management (AIIM), which found that organizations with high levels of automation have more rigorous governance practices, better lifecycle management procedures and a superior foundation for digital transformation.
But many organizations are still struggling with the basics of what to keep and what to throw away. In the AIIM report, one expert tells of the difficulty of getting rid of 400 boxes of useless information taking up space in a storage room.
"I did an information inventory and concluded the boxes could be destroyed," the expert wrote. "But nobody wanted to be the one to actually sign off on destroying any of those boxes."
If this scenario sounds familiar, then you know why so many organizations struggle with information governance (IG), a records management strategy comprising best practices for managing all types of information. The path to IG is beset by executive indifference, a deficit of clear governance definitions and lack of coordination between the records management and IT departments. Organizations that want to realize the advantages of an automated records management system will have to overcome these obstacles.
The Tangible Benefits of Automation
AIIM has consistently noted a correlation between good IG practices and business performance. Forty-five percent of respondents in the 2020 AIIM survey that consider themselves as having above-average IG competence assessed their transformational readiness at 76 on a 100-point scale, compared to an average of 60 across the entire data pool.
One of the biggest challenges in moving up the maturity scale is finding ways to deliver value from information rather than simply mitigating risk and cost. Fifty-eight percent of respondents recognized that they needed to move up the information management value chain to enable business. But those organizations are up against myriad challenges.
For one, there's simply too much information to manage. On average, respondents said they are girding for 4.5 times the data they have coming in now to come in over the next two years. Equally challenging is that they expect 57% of that data to be unstructured (such as in an email or an image) or in semistructured documents (like an invoice or form). Data that isn't structured can't be easily ingested and analyzed using conventional data processing tools.
Another impediment is the lackadaisical attitude of senior executives toward IG. Many senior executives regard it as a cost center rather than a source of strategic advantage. Information and records managers can help their cause by making the case that information delivered in context helps achieve business growth objectives — something that's high on every executive's priority list.
"It is generally agreed that the only way to avoid being swamped by the tide of information chaos is to automate as much of the information management process as possible," AIIM writes.
Organizations should develop a process automation strategy that defines the vision, key performance indicators and critical success factors for automation, then attack processes one a time, starting with those that deliver the highest value.
Organizations that have already gone at least part of the way down the automation path reported that they're in a better position to handle the information flood. More than half of the organizations surveyed by AIIM have an organizationwide strategy for metadata (53%), automated processes to identify and protect personally identifiable information (52%) and automated processes for creating and sharing workspaces (51%). Even so, 74% of those organizations said that they're struggling to turn unstructured information into actionable data.
Methods for Managing Data Growth
Machine learning might be a big part of the solution. The volume of unstructured data is growing so rapidly that humans can't possibly classify and tag it all. But computers can be trained to recognize patterns in textual data and elements in photos and videos nearly as well as humans can. They can automatically extract and enrich both physical and digital content and add structure to unstructured sources even recognizing information in paper documents and images. Finally, machine learning algorithms can automatically apply governance categories and retention schedules.
Automated records management system based on machine learning doesn't just let organizations manage large volumes of information — it digitizes manual workflows in the process. AIIM notes that 74% of organizations said turning unstructured information into actionable data is a significant problem for their organization yet only 12% are using machine learning on a widespread basis. This is clearly a major area of potential growth.
Another solution to data growth is to throw it away. According to AIIM, 47% of advanced organizations said that they have processes to dispose of redundant, obsolete or trivial information — like those 400 boxes of useless information — in a disciplined way. Only 28% of less-advanced organizations said the same thing.
At a time when the volume of information is growing faster than ever and when organizations are under pressure to transform around digital tools and processes, the need to understand data, categorize it and develop disciplined rules about how to manage it has never been greater. The multifaceted advantages highlighted in the AIIM study underscore the importance and value of automation in records management.