Twixors’ approach towards Robotic Process Automation vs Digital Process Automation

Twixors’ approach towards Robotic Process Automation vs Digital Process Automation

In today’s dynamic digital marketplace, organizations face an increasing need to adapt to technologies that transform and automate existing business processes to drive customer engagement, employee productivity, and business resiliency. While every organization lately has been rushing towards deploying the jargons Robotic Process Automation (RPA) and Digital Process Automation (DPA), failing to understand how these technologies would digitally transform their core business activities and what would be reaped ultimately.

According to IDC, 65% of all organizations will have accelerated the use of digital technologies by 2022. Automation is no more constrained to internal processes to increase operational efficiency rather than crafting customer-centric strategies. According to Think Automation, the DPA market is now worth $6.76 billion and is expected to rise to $12.61 billion by 2023.

Is RPA sufficient enough to address the automation needs of organizations?

Leslie Willcocks, professor of technology, work, and globalization at the London School of Economics’ defines RPA as ‘a type of software that mimics the activity of a human being in carrying out a task within a process. It can do repetitive stuff more quickly, accurately, and tirelessly than humans, freeing them to do other tasks requiring human strengths such as emotional intelligence, reasoning, judgment, and interaction with the customer.’

Simply put, RPA is the technology that allows businesses to automate mundane, repetitive tasks. The return on investment for RPA is between 30-200%.

A big challenge of using traditional RPA is that it still requires substantial human assistance and intervention to keep automated processes functioning seamlessly. While RPA does lessen the burden of manual work, it faces challenges around scaling for end-to-end automation and often fails to adapt to evolving processes, requiring a lot of hands-on intervention.

Moreover, the time and effort in transforming legacy systems with clerical operating procedures should not be limited to back-office administrative functions. Arguably, the customer-facing office is more of a concern, and not only because of the inefficiency in automating customer query resolutions but also the deteriorating customer experience that drives business.

A Strategic Shift from RPA to DPA

This paves the path for Digital Process Automation(DPA).

DPA both automates a process and optimizes the workflow within an automated process. A big focus of DPA is to improve employee and customer experiences by taking friction out of the workflow.

In its March 2019 report, “RPA, DPA, BPM, And DCM Platforms: The Differences You Need To Know,” Forrester used the term digital process automation as a replacement term for business process management, the long-established discipline that uses a variety of methods to discover, model, analyze, change and optimize business processes.

DPA strategies seek to utilize the synergy of a range of automation technologies in a deliberate way to address the broadest range of work automation opportunities to the greatest extent possible.

Bringing it all together

There is a need for collaborative and agile technologies.

Twixors’ low-code DPA platforms and tools enable teams to collaborate and work iteratively on use-cases across functions and industries, and deploy them faster, with higher quality and lower overall costs of building and maintenance.

In addition, there are several platform capabilities, including

  • API led data integration capabilities, ensuring backward compatibility with existing enterprise applications, and forward compatibility with any new platforms in the future
  • Simple to use, drag and drop modeler, with training facility to ensure your teams can ramp up and build use cases yourselves without reliance on external third parties
  • Omni-channel front-end, that allows automate workflows, secure data access and personalized services, at messaging scale
  • AI/NLP engines, Rich Cards and Live Agents for conversational, engaging and bionic interactions
  • Analytics and Reports to get end-to-end insight across business processes

Impact ranges from

  • 20-30% Cost Savings
  • 30-40% Improvement in productivity
  • 80+% Increase in customer engagement and satisfaction

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