Dynamic case manage systems that can handle complex sets of data, documents and decisions have been around for decades, delivering the ability to help track and manage complex processes in a more sophisticated, efficient and predictable manner. For the most part, these systems have delivered on their value proposition — with a few exceptions.
Really, what we mean here is that ANY exception to the rules that define those systems. As long as data, documents and decisions fall within known, defined parameters everything functions according to plan. Until someone or something falls off the rails. A misfiled document, a mis-keyed piece of information, an approval assigned to a user who is on vacation (or no longer with the organization) has the potential to wreak havoc on systems defined by hard-coded or by a pre-configured and inflexible rule set.
In that context, Murphy’s Law has broad application when it comes to multi-decision, multi-document management solutions. A missing document in an onboarding process, a mis-typed invoice number for an AP vendor invoice process, a duplicate customer order for sales order processing, all have the potential to bring a streamlined, automated process to a halt.
When it comes to rules-defined processes, with multiple steps of data entry, document filing, submission, review and approval, exceptions ARE the rule. A recent survey conducted by AIIM suggests that more than half of common business processes are unpredictable. When it comes to processes where a hierarchy of documents and decisions are involved (and a case file or structure is involved), that number climbs to 62%.
In the past, the only way to address this problem was old fashioned manual labor. The process owner and relevant stakeholders conduct a paper chase, looking for where the system failed and the rules broke. But today, innovations in AI, machine learning and Intelligent Process Automation (IPA) suggests a better way.
Rather than re-writing/defining the rules to nail down every possible exception, modern process-oriented companies are adopting self-learning technologies that work hand in hand with process owners to record a user’s manual steps and interpret them into a new algorithm that is able to handle the same sort of exception the next time.
What this means in practical terms is that intelligent process automation solutions, like Artsyl’s ActionSuite of solutions for processes like AP vendor invoice or AR sales order processing, flag exceptions when they occur and alert the appropriate process owner. That person is able to log into the system and review an invoice or an order, along with the associated data, to manually correct the problem.
Nothing new there. Where things gets interesting, is that the system records the specific mouse clicks, keystrokes and actions taken by the process owner within the system. Rather than going back to IT/Engineering to recode and address the problem, IPA systems rewrite their own rules. In human terms, they learn from other’s mistakes.
For intelligent process automation to work in the real world, it needs to be flexible and adaptable enough to function in a world where there can be more exceptions than rules.
This requires these systems to support:
To learn more about how to evolve your processes from manual to automated to intelligent, contact Artsyl Technologies and request a demonstration of the ActionSuite of intelligent process automation applications for accounts payable, accounts receivable, claims management and more.