Business processing now requires more computational and processing capacity with the volume of data that can continues to grow

Cognitive automation is delivering increased efficiency, and speed and reduced costs, and more with intelligence and sophistication. It can learn on its own how to manage changes within the system, make sense of unstructured data, take decisions like a human would, analyze the processes, and data it interacts, with offers suggestions to optimize the processes further.

Payeli Ghosh and Shreyas PC, co-founders, Option3, speak more about the coginitive robotic process automation. Excerpts:

BW CIO: What are the major driving forces that tend to increase the demand for cognitive robotic process automation during the forecast period 2018-2026?

Shreyas PC: There are many factors.

The pursuit for excellence
While traditional rule-based automation has been delivering results with increased efficiency, and speed and reduced costs, cognitive automation goes beyond that by delivering all of these and more with intelligence and sophistication.

It means, it can now learn on its own how to manage changes within the system, make sense of unstructured data, take decisions like a human would, analyze the processes and data it interacts with offers suggestions to optimize the processes further. Cognitive capabilities add more dynamism to automation, and businesses stand a lot to gain from it.

For example, if there’s a change in a process in the form of data input, or an additional step for validation, rule based RPA solutions would need to be programmed in order to facilitate automation. With cognitive RPA, the bot analyses the change and tries to understand the context and content all by its own and then acts accordingly due its self-learning and decision-making capabilities.

Automating complicated processes
Business leaders start looking at cognitive automation when rule-based automation fails in simplifying processes that are complex and dynamic in nature, such as non-standard exceptions, and unstructured data. This requires logical decision-making capabilities in the RPA platform which is possible only through cognitive RPA.

For example, when it comes to a decision to match an invoice to a goods receipt, in most cases there are no pre-determined rules, and requires a correlation capability with an understanding of the system in place. Cognitive RPA helps to match it by checking the records and understanding if the goods have been received by the merchant.

Big Data
As businesses grow, so does the data. Business processing now requires more computational and processing capacity with the volume of data that can continues to grow. Cognitive RPA, while minimizing the burden of the repetitive tasks, can also store the data which can be used for its learning. This makes it powerful enough to hold all this knowledge to understand patterns and trends and create reports and metrics for businesses to understand and achieve their goals.

BW CIO: Could automation force a re-organization of the industry?

Payeli Ghosh: It’s similar to how tractors came in and revolutionized agriculture. The outcomes have not changed, but farmers adopted technology to increase efficiency and quality of farming. It enabled them to focus more on other areas such as sourcing, distribution, and sales.

Automation is similar in many ways, as people will start focusing more strategic activities, and result in them moving up the value chain. Automation will create new roles and open new opportunities for industries, and we can also see teams working in tandem with virtual agents to achieve outcomes in a smoother way.

BW CIO: What are the major challenges inhibiting the growth of the global cognitive robotic process automation market?

Payeli Ghosh: Most organizations are pursuing RPA in varying degrees, but when it comes to cognitive RPA, they don’t know where to start. They are usually advised to achieve a degree of familiarity with rule-based or standardized RPA before venturing into cognitive or Intelligent Automation. It is not the right approach as they would miss out on a lot of efficiency that would be gained through a cognitive solution in the initial stages.

Another case that has been observed is organizations hitting the reset button and opting for a fresh start with cognitive RPA when they fail to realize the results through rule based automation. Had a holistic approach been considered, a lot of these challenges could have been overcome.

Another challenge is the common perception among decision-makers and influencers that cognitive RPA solutions are difficult to build and integrate to their business. It’s true in some ways, as a cognitive solution would take more time to build than a rule based automation platform, but with the right RPA product, it is much more faster and a lot more efficient.

For example, to create a standard cognitive robot does not take more than 6 weeks with JiffyRPA and if it is based on any of the predefined solutions, it does not take more than 2 weeks to bring up a cognitive bot.

BW CIO: What are the types (services and platforms) of cognitive robotic process automation market that will dominate in the coming years?

Shreyas PC: RPA solutions integrating Natural Language Processing and AI capabilities will become standardized in the coming years. Robots will be more human-like in nature where they would be able to interpret and respond to situations on their own without any manual intervention required.

It will continue to be a partnership between solution providers and service integrators to deliver results for enterprises.

BW CIO: What is the total market share of the multiple industries (finance and banking, insurance, healthcare, telecom and IT services, and others) in the global cognitive robotic process automation market?

Payeli Ghosh: Riding on the successes of RPA and cognitive capabilities that are rapidly increasing, there is a rise in demand across industries and functions looking into cognitive RPA. According a 2017 report by Shared Services and Outsourcing Network, Intelligent Process Automation market is expected to hit US$ 1.2 bn by 2021.

BW CIO: What are the major opportunities that cognitive robotic process automation companies foresee?

Payeli Ghosh: As elaborated earlier, cognitive automation comes in place to automate complicated tasks that require a level of intelligence to replicate human-like decision making. Opportunities are many, as businesses look to invest more in simplifying complex tasks to ease the burden on their employees and increase their productivity while accelerating business outcomes.

This includes reading and processing documents, forms and invoices which are in different formats, processing and preparing contracts, autocorrecting unstructured data and so on.