Evolution of Robotic Process Automation (RPA): The Path to Cognitive RPA
The Robotic Process Automation landscape is undergoing massive transformations right before our eyes and it has barely to do anything with the invasion of emerging technologies like machine learning, AI, natural language processing, text analytics, AI or even digitization.
Undoubtedly, these technologies are going to fall into place over the upcoming 2–5 years and make quite a transformation. But today’s limelight belongs to the robot-ready advancements that are making waves with the trickiest audience of all- real customers with real work to get done.
GAME-CHANGING INNOVATIONS IN ROBOTIC PROCESS AUTOMATION OVER THE YEARS
Evolution of Robotic Process Automation can be described in four distinct phases.
Assisted RPA or RPA 1.0 is where the RPA software automates various activities and applications running on the user’s desktop. The simplest example of this could be a simple cut and paste of information from one screen to the other.
Assisted RPA proved to be effective in cutting down average handling times, improved customer experience and resulted in cost savings. It also meant that long, complex processes were conveniently replaced with single mouse clicks, significantly cutting down the time taken to train an agent on to it.
Though, assisted RPA should only be applied when real-time human-system interaction is needed.
Unassisted RPA or RPA 2.0 is where the RPA software is deployed on several machines to run without the requirement for the automation to be attended.
The automation here doesn’t require an employee to go to a particular machine, log on, trigger the processes to begin, observe its performance and close down the automation when it is finished.
These steps can be automated and could be simplified through dashboards, which provides a window to assign tasks to machines, adjust priorities and queues and intervene with a specific robot’s performance as and when needed.
This unlocks great possibilities as the robots can work 24*7 and replaces human interactions with business processes.
Autonomous RPA can be defined as the best of two worlds where it is built leveraging AI and related new technologies like cognitive automation, machine learning, computer vision and more to the RPA.
This splendid convergence of various technologies generates capabilities that radically elevates business values and gains a cutting advantage for users. This is the current “latest” version of RPA.
Cognitive automation uses several distinct algorithms and technology approaches like natural language processing, data mining, semantic technology, text analytics, machine learning and more making the most of both structured and unstructured data.
Unstructured data like customer interactions can be seamlessly analyzed, processed and structured further into useful insights for the next steps of the process like predictive analytics.
With cognitive RPA, decision-making processes are all performed by the robots such that all the long, complex tasks could be automated. This is in the making.
The most fascinating factor is the rate at which this technology is growing. According to Forrester, the global RPA market is predicted to touch $2.9 billion by 2021.
One could morally protest robots and automation technologies replacing human jobs with innovative robotic processes. This is for sure a valid concern. But, practically, a considerable majority of mundane and repetitive tasks presently handled by workers has either been offshored or is being carried out by a workforce who probably would rather be doing something else.
Our next foretold issue is the lack of technical skills in the RPA domain. Today, if you put a glance at the partner landscapes for RPA, the main contenders in the RPA software are Accenture, Deloitte, IBM etc. who would generally play only with key corporate houses and charge fat premiums for their branding. There are limited midmarket channel players who develop the RPA skills in both technology and business process re-engineering to execute RPA properly.
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