Cognitive Computing and Intelligent Process Automation are the New Black

Less rigid, more adaptable intelligent automated systems take the pain out of process

As consumers, we’ve been spoiled by the riches of online convenience—much of it delivered by automated systems and process intelligence that’s invisible to us. Business leaders, department managers and process owners in the B2B world have begun to see their day to day work lives change because of this rise in consumer convenience and customer expectations.

As the pace of change accelerates, technology innovation races ahead and the bar for customer satisfaction gets set higher and higher, companies of all sizes are increasing setting aside the status quo to embrace a new breed of process automation: one that is intelligent, flexible, adaptable, affordable and user-friendly.

Stop me if you’ve heard this one before. But THIS time, when it comes to automation, the complexities, costs and overhead that were once a hallmark of process automation are fading away. That’s because reliance on IT and development to address all the complexities and unpredictability of doing business in the real world has been replaced by self-learning systems that can learn from process owners.

In other words, the rules have changed. And they’ll continue to change in a way that our software systems and tools can adapt to.

Enter the Cognitive Age of Computing

What makes all the new hype about intelligent process automation so different?

First, a brief history lesson.

In the beginning, computing relied on mechanical systems to tabulate results. That first age of computing lasted more than fifty years. These single-purpose mechanical systems delivered better results than a manual operator, but often at a huge cost, with narrow applicability.

Then, along came programmable computers. These amazing systems could handle multiple functions by functioning within parameters defined by a prescribed set of rules. These systems grew increasingly cost effective and could handle a broader range of tasks, including managing complex processes involving multiple documents, data sources, tasks and task owners.

But, there was a problem. In the real world, these systems often failed when process owners couldn’t anticipate every real world scenario. When exceptions occurred, they were costly. In fact, they still are. That’s in part because of the manual labor or dealing with exceptions the old fashioned way, along with the cost and risk of potential errors or compliance violations. On top of that, the cost and overhead of relying on an IT department or a developer to rewrite and recode the rules limits the kinds of processes that these systems can handle cost effectively.

In that context, the rules have literally (and figuratively) changed. And with cognitive computing, the rules will change and continue to adapt without the need for a coder or a programmer. Instead, the power is in the hands of the process owner.

Instead of coding systems to follow a prescribed set of rules, self-learning systems provide a user-friendly interface for a human operator to interact and manually address an identified exception when it first occurs. Human operators rely on old fashioned mouse clicks, keystrokes and (not so) common sense to sort out why an exception has occurred and how to fix it.

In this scenario (for example, a duplicate invoice or a data entry error), the self-learning system isn’t a passive observer. The system records the actions of the process owner and compares them to its current rule set. It can then translate the user’s actions into an automated set of action steps to address the same problem the next time it occurs.

Putting Cognitive Computing and IPA into Action

At Artsyl Technologies, we’ve applied cognitive computing and IPA to solving the problem of dealing with scanned paper and digital documents like email attachments, transforming them from unstructured content into structured data that can be inform and drive process automation.

In the past, extracting information from unstructured documents was possible through traditional rules-based techniques, but the inflexibility of these systems inflated costs and demanded too much overhead from IT and development staff.

We’re excited about the possibilities and continue to push the envelope, so that dull, manual tasks are replaced—but workers are retained, retrained and elevated to do more meaningful work and adding more value.

As these tools and technologies advance, more complex processes can be tackled—but also simple, routine tasks that previously lacked the volume or dollar impact to be justifiable. Leading to less tedium, less waste and more opportunity for innovation and added value to the customer.

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