Cognitive automation can process unstructured data like emails and documents of any size and shape, and then use that data to drive automation at a higher level. Cognitive RPA can perform Categorization, Optical Character Recognition/ Image Processing, Voice Recognition, Text Analytics, Predictive Analytics, Categorization, Classification or Chatbot Analytics.
The Global Cognitive Robotic Process Automation (RPA) Market is projected to grow from USD 4.81 billion in 2021 to USD 9.93 billion in 2030, which is driven by the increasing need for enterprises to automate their processes, increasing need for cost reduction, and reduce manual errors. (source of data: IDC Corporation)
Why choose Cognitive RPA over RPA?
Cognitive or analytical skills
RPA can perform a rule-based task that does not require any cognitive thinking or analytical skills like answering queries. RPA can be applied to 60% of tasks at an enterprise level. 40% of tasks involve large amounts of human interactive skills such as decision-making based on context, complex relationship understanding, conversation with others, continuous learning, etc. Cognitive RPA can mimic these human-like non-routine tasks using Artificial intelligence.
The dissimilar foundation of processing capabilities, methodology, and technologies
RPA is rule-based technology, so it is easy to implement using macro scripts and workflow automation using an ‘if-then’ approach which does not involve much coding. Cognitive RPA is a ‘knowledge-based’ technology that can help make sound business decisions.
Let’s look at the use cases of CRPA
Most enterprises, specific marketing teams usually store their data, which makes it hard for the sales agents to track all their customer’s touchpoint and understand their buyer’s journey. It is important for marketeers to know how customers feel for their brand.
Here cognitive RPA comes in action. It analyses emotions and tones in what customers write online and assign a numerical score to predict whether the customers are happy, sad, confident, and more. Also, cognitive RPA can be useful as “Conversation Automation Bots” to improve the purchasing lifecycle and revenue by converting leads into sales.
Finance and Accounting
Cognitive automation is also beneficial to the finance department. By installing “Software-bots”, Account teams can automate the process to receive the information of invoices from an email or other files like PDF/word and launch them into the accounting system. In this scenario, “Software-bots” mimics the series of human actions of accessing emails, extracting information from the invoices, and then copying them into the accounting system.
Intelligent Document Processing
As old processors must re-enter the text to replicate the information from files into the system, Cognitive RPA uses technology like OCR (Optical Character Recognition) tools to automate the process, so the processor can supervise and take decisions based on extracted and persisted information. Capturing and processing of new application documents can be automated by Optical Character Recognition (OCR). Thus, this kind of Intelligent automation helps handle some of the business functions more efficiently without human errors. Employees can spend time on other important tasks than tending to the process of tedious paperwork or handling trillions of unstructured documents of all sizes and shapes.
Most of the HR bandwidth is required in the employee onboarding process, which is complex, multilayered, and manual. Cognitive automation has an important tool called “Employee Onboarding Bots” which rapidly helps in processing tasks. This tool can help in creating automatic computer credentials and offhand logins, new hires enrolling in training based on their department, and scheduling meetings with their manager.
The process of supporting customers involves replying to emails, chats, etc. Bringing Cognitive RPA which combines RPA plus NLP (Natural Language Processing) will decrease the human arbitration in this process. To organize the email streams, the email needs to be either sent an automatic reply or further escalated to the respective department. Here NLP with RPA software will help to gauge the purpose of the email and reply accordingly or forward it to the department. This is how CRPA can make the customer support process very efficient, quick, and easy to manage.
Thus, RPA when merged with AI technologies like chatbots, predictive analysis, Natural Language Processing (NLP), etc. has a broad spectrum of use cases that can help save immense time and human efforts.
eInfochips takes Traditional RPA a step further with our Cognitive RPA capabilities for more information contact us.