27 Apr, 2021 • 3 min read

From insights to automation - Conversational Data Intelligence and RPA

Robotic Process Automation (RPA) is a method of automating high-volume, rules-based repetitive tasks and business processes. It follows the same rules and steps that a human employee does, but with the ability to scale. At its core, RPA is about creating business efficiencies and it has a wide range of applications. 

RPA can be transformational for businesses, freeing up people from routine, mundane tasks and redeploying them in areas where they can add real value: innovation, creativity, growth, or system design. 

However, the promise of RPA is constrained, a reason RPA can struggle to scale is its inability to work with unstructured data.

Many of the processes and tasks that require the most admin are often those that involve unstructured data, including communications channels such as email, chat or tickets. 

These unstructured input channels are fundamental and are one of the reasons that RPA has struggled to go beyond the automation of simple data entry in many organisations.

It's not that RPA can’t help with the activity that occurs within these channels, more it can’t understand the task it needs to complete due to this unstructured input – That is where Conversational Data Intelligence can help.

 

Current, and future, applications of RPA

RPA is used across various industries for a variety of purposes. A great example that is commonly implemented across organisations taking their first steps in RPA is its use in post sales administration and reporting. 

A human employee might log into the company’s ERP system, create and complete a transaction, get the transaction approved, process the invoice for payment, create a report, and log back out of the system. 

RPA will mimic the exact same process, keystroke by keystroke – but in a fraction of the time, and eliminating the potential for human error. 

Other common applications of RPA might include:

  • Claim management for insurance companies
  • Invoice and payment processing 
  • Inventory management
  • Data entry and management
  • Technology and security diagnostics
  • Audit trails for compliance and governance
  • Automated appointment scheduling

When organisations first consider RPA, they tend to think in terms of individual task automation, rather than thinking about how it could be used to transform the business. This is where Machine Learning comes in, helping businesses to automate entire business processes to meet a strategic goal. 


Conversational Data Intelligence and RPA

Conversational Data Intelligence platforms generate insights and actions from communications - think email, tickets, chat etc. Every communication – both those held within a business and externally – has value, and in mining conversations your organisation can see exactly what that value is.

As we know, RPA can only work with structured data. What Intelligent Conversational Data platforms do is convert each message in a conversation into structured, machine-readable data in real-time so that your business can simply plug a structured output into your chosen RPA software to deliver customer, supplier and employee transactions in your core applications.

Intelligent Conversational Data Platforms:

  • Connects to, and works with, your existing systems
  • Mines your communications data for frequent questions and processes 
  • Trains custom machine learning models on working with your communications data
  • Monitors your communications data to produce real-time insights
  • Triggers automated processes in real-time and monitors them

By integrating with leading RPA providers - UiPath, Blue Prism and Automation Anywhere – Intelligent Conversational Data solutions can generate the maximum value for your data. They do this by creating automation triggers – these allow RPA solutions to respond to, and process, messages in real-time. It also learns from exceptions and continually improves.

Gartner forecasts that by 2023, we’ll see a 30% increase in RPA used in front-office operations. The organisations that get a head start on introducing RPA to manage their processes and gain insight from their data will be at a distinct advantage. 

Not only due to the increased amount of RPA they will have been able to deploy, but also from the valuable insights they will have been mining in their communication data, and the data exhaust from the RPA processes being completed. 

This data driven thrust that is enabled through Re:infer & RPA will provide a data lens that few organisations will have access to. Not only showing what was completed, but also what was said, when, by who and what was requested to be completed. 

This end to end understanding has been missing from the Enterprises for decades, but for the early adopters, it’s now assisting them in significant efficiency gains, and gaining competitive advantage.

 

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