RPA and The Model for Customer Service

August 10, 2016 by Luke Tucker

We are in the “Age of the Customer” according to Forrester Vice President, and Principal Analyst Craig LeClair. Craig noted in an August 3rd webinar that, “The power has shifted away from the institutions to the customer.” In response to changing customer expectations, organizations are looking for new and innovative ways to automate customer-facing processes, without sacrificing quality.

Craig went on to say, “There’s excitement around [Robotics Process Automation] technology because it has the potential to have the machine learn without having the machine programmed. This is unattended learning… And this is the model for customer service that everyone’s trying to get to.”

Click Here To Watch The Full Webinar

That was just a teaser on some of the gems recorded in our recent webinar with Forrester, where we had over 150 people participate in this informative presentation and Q&A session. 

We welcomed Brian Cox, Head of Insurance and Financial Services at Captricity, and Forrester’s Craig LeClair, to discuss how RPA and Advanced Capture are Improving Productivity & Customer Experience in the Enterprise.

Key topics covered include:

  • Top Trends in Enterprise Technology as it relates to Big Data, Robotics Process Automation, and Capture Solutions

  • How RPA and Data as a Service solutions can drastically impact customer experience and even financial performance

  • Keys to look for in your business that are the “low hanging fruit” for RPA and process automation wins

  • Understanding where RPA should sit in the organization: Business Intelligence or Technology Systems?

  • RPA is one tool in the toolbox that can help achieve business process efficiencies, but in reality you need a robust technology partner to work end to end from Capture to Validation to Formatting and Delivery

To dive into some of the info, Craig had an excellent slide where he talked about a few of the most popular RPA use cases he is seeing in the marketplace.

The “low hanging fruit” or bonus territory is organizations using RPA to basically automate processes that can eventually link to higher order analytics - to the illustrious cognitive capabilities.

“When you start to combine RPA with the human decision making, you not only have the brains but the arms for execution,” Craig went on to say.

And this insight is actually a nod to the power of Captricity’s technology as we combine two powerful resources for getting things done: 1) Massive computing power through comparable data centers, and 2) Human intelligence through crowdsourcing. And both are programmable, interweaving into a set of deep learning algorithms. To find out more about our solution, see our Technical White Paper available for download.

Shifting back to the webinar, Craig went on to further describe what he called “the ROI land grab”, instances where he’s seeing wholesale cost-savings with RPA technologies: Shortening turnaround times, improved data, and lower costs. All are major wins for an organization, especially as the magnitude of scale increases.

A final point we’d like to emphasize is what Craig calls, “The Cognitive Scale”. This is where RPA’s value climbs even further (refer to slide 22):

Stage 1 of the cognitive scale is Basic digitization - task schedulers, populating data tables, etc.

Stage 2 is Enhanced digitization - natural language processing, content analytics, text mining, and process automation.

Stage 3 is Cognitive decision management - cognitive computing, data mining, and pattern recognition.

We are proud to be one of the organizations leading the charge in innovation language processing and dynamic modeling with our deep learning technology, pushing the envelope of cognitive decision management and empowering the enterprise of the future.

To view the full webinar, head on over to our resources page. And make sure and stick around to the end of the presentations, for some great Q&A, where Craig and Brian dive deeper into key concepts around RPA and address common questions that arise from operations teams and business intelligence departments.

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