One upside to electronic records management is the potential to reduce labor and increase accuracy. In fact, one of the core objectives of any organization engaging in a digitization project is reducing administrative burden while enhancing record quality.
To that end, electronic records management opens up new avenues for efficiency and effectiveness, and one of the most exciting ways is through automation. We’ve put a spotlight on automation before, but there’s still more to automation than meets the eye. For one thing, there are multiple approaches to automation that agencies can adopt, as their use of electronic records management (ERM) tools becomes more sophisticated. Here are four ways organizations can think about automation in their records management process.
1: No Automation
This is the approach where most organizations are starting, so it’s worth mentioning. Admittedly, there are occasional situations or use-cases where automating the process isn’t going to make sense. High-level approvals of highly sensitive documents, for example, might necessarily require human intervention. That said, if your own organization’s approach is a flat “no automation,” it’s worth asking why. Is this approach forced on you by a technological constraint? Is it an active choice being made even if the capability to automate is available? Understanding resistance to automating is key to figuring out which of the following approaches will be the best fit for your needs.
2: Rules-Based Automation
Where organizations do use automation, it’s usually rules based. In other words, the organization sets up business rules that govern how and when records are captured, categorized, stored, accessed, and/or disposed. The ERM then algorithmically follows those rules to determine what action to take with each record depending upon specific triggers. The rules can be quite sophisticated, including a wide range of triggers and actions based on records’ content, metadata elements, or other attributes.
3: Business Process and Workflow Automation
A more advanced form of automation is the automation of entire workflows. The automation is still algorithmic – in other words, the system isn’t “smart,” so we’re not talking about AI here – but the automation handles and supports the flow of data and records throughout an operation. For example, it may be possible to automate the process of routing citizen applications through a review, approval, and notification process with minimal or no human intervention required.
4: Autocategorization
Here, we start getting into more AI-driven automation where the ERM itself decides how to handle certain records. The technology learns to identify common patterns in the records and act accordingly. The ERM, on some level, is thinking for itself. In most cases, this analysis requires a combination of machine learning and training (where human users “teach” the AI by presenting examples of what the AI should do in different situations). This AI-driven automation can be very powerful, but it also has some serious limitations. Processes must include some kind of quality control to prevent errors, and it typically requires a significant amount of training of the ERM/AI agent.
About PSL
PSL is a global outsource provider whose mission is to provide solutions that facilitate the movement of business-critical information between and among government agencies, business enterprises, and their partners. For more information, please visit or email info@penielsolutions.com.