How today’s Dynamic Case Management Solutions Rely on Intelligent Process Automation
		to Handle Exceptions Along with the Rules

How today’s Dynamic Case Management Solutions Rely on Intelligent Process Automation to Handle Exceptions Along with the Rules

While the promise of rules-driven systems that rely on computer intelligence to manage data, documents and decisions every step of the way has been with us for more than two decades, early forays into business process automation hit a wall when it came to handling exceptions to the rules.

This has been particularly true for systems that attempt to automate case management, where well- defined rule sets to handle things like managing payments, bidding on contracts, processing loan applications or organizing and managing legal matters, often ran afoul of a corollary to Murphy’s Law; for every rule, there is an exception.

Enter the huge opportunities we see today for AI, machine learning and intelligent process automation—and for today’s ERP and ECM VARs who embrace platforms designed to make implementing intelligent process automation simple and code free. Like Artsyl’s docAlpha transformation platform and ActionSuite of applications for AP invoice and AR sales order automation.

Herding Digital Cats

The challenge of exception handling still presents one of the biggest obstacles to automating most business processes. According to a recent AIIM Survey on Case Management and Smart Process Applications, a majority of respondents said that half or more of their business processes were not straightforward or predictable. Sixty two percent of those surveyed said that most of those processes involved assembling a case folder, claim file, project folder, proposal, etc.

The solution to the problem of business processes that won’t conform to a standard rule set has been a new generation of self-learning systems that use machine learning and AI to identify and adapt to exceptions. Tools like Artsyl’s docAlpha transformation platform are able to apply context to the content associated with a business process to determine how to select, modify or re-direct the next steps in an automated workflow and, when needed, to learn how to handle exceptions based on input/feedback from a human operator as part of the process.

Learning and Adapting as Conditions Change

AIIM’s study of case management and smart process applications distills the experiences of early adopters of case management systems to identify the requirements for automating business processes in the real world.

Survey respondents identified the following requirements as critical to success:

  1. Compliant but adaptive workflow, allowing flexibility in processing but ensuring end-to-end visibility and enforcement of necessary policy and regulation for a given process
  2. Integration with multiple repositories, records archives and line of business systems
  3. Monitoring, reporting and analytics that provide a single view of a case, including recommended actions a process stakeholder can take to advance the course of the case toward conclusion/ resolution.
  4. Multi-channel customer engagement, so that information can be captured from documents and web forms and outbound communication to stakeholders of case-related information

Put your visions for process automation into action

To learn more about how intelligent process automation can help your organization to intelligently automate business process in a way that adapts to exceptions and changing business conditions, contact Artsyl Technologies and request a demonstration of docAlpha V6.


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