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Machine Learning and AI for Back Office
Processes Turns the 80/20 Rule On Its Head,
So Employees Can Focus on More Meaningful Work

September 13, 2018

“The future is here—it’s just not evenly distributed.” – William Gibson, Sci Fi Author

Click on any business or trade press article these days and you’d believe that the sci fi future of artificial intelligence has arrived. Dig just a bit deeper and look at how leading companies are automating dull, routine tasks for back office operations like accounts payable vendor invoice or customer sales order processing and you might conclude that the future has been here for a while.

Companies that have embraced automation to manage manual, inefficient vendor invoice approvals and payments and sales order processing are no longer cutting edge. They do, however, remain in the minority. That’s changing quickly—and it’s these kinds of back office processes that are leading the way.

The case for embracing automation for these kinds of routine, repeatable processes is well established, and implementing them has becoming easier and more cost-effective.

Firms that rely on digital transformation platforms like Artsyl’s docAlpha V6 employ machine learning to “read” a document with increasing accuracy by recording interactions with human operators rather than relying on hard coded definitions for various document types and formats. These solutions often include everything that’s needed out of the box, with no need for custom coding. As a result, implementation timelines can be measured in weeks rather than months an ROI in in 6 to 12 months is not uncommon.

Humans and Machines Working and Learning Together

Even so, these fully automated systems need to be “taught” how to walk before they can run. Existing AP staff members, along with finance leadership, need to be involved in defining processes for these “robots” to execute. Once these systems are in place, they typically do an amazing job of automating the routine—while flagging exceptions to be reviewed and handled by their human coworkers. As a pattern emerges for exceptions and how to handle them, these “exceptions” also can be managed as part of the routine.

At the same time, today’s intelligent, automated systems are able to extract meaningful information from unstructured data sources like invoices, quotes or order forms, in a way that provides greater visibility to human staff members and managers about the business impact of the process. In the case of accounts payable, this allows finance managers to have access to more timely accrual reports and a greater ability to monitor and control cash flow. Today, these business decisions remain in the hands of seasoned, qualified professionals who are more empowered to make impactful decisions because of automated processes.

AI and the 80/20 Rule

Today, process automation lacks the precision and reliability to extend fully into human decision making. But it DOES allow humans to elevate their roles from data entry clerks and paper shufflers to taking on roles as analysts—something AI systems have yet to fully achieve.

In recent Wired Magazine article, Eden Shochat, partner at Alephe VC was quoted writes, “AI…has to be perfect - and most software engineering projects are not perfect. Unlike a bridge that can't be 90 per cent done, software can be "good enough". In software…the initial 80 per cent of the reward has 20 per cent cost. The remaining 20 per cent of the reward would take 200 per cent of the cost and time.”

It is in that remaining 20% then where we find the cost/benefit of human workers over their robotic counterparts. It’s also where employees get the most satisfaction from their work—when they are making meaningful, impactful decisions.

Turning the current model on its head, freeing employees to spend the majority of their time on meaningful work, is the real promise that process automation is poised to deliver.

To learn how your employees can do more meaningful work and better support corporate strategic goals contact your Artsyl Technologies representative.

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