The benefits of Cognitive Automation

The McKinsey Quarterly, an article by the industry giant, McKinsey, and Company, stated that 45% of all human activities, which employers pay for can be automated. RPA is the most emerging trend in the world which integrates existing and new software with Artificial Intelligence (AI) and machine learning. RPA will take over high volume tasks that require more time to complete with little or no human interaction. RPA can also be referred to as Software Robots or Bots, which are capable of mimicking human actions. RPA complements the organization’s existing IT (Information Technology) structure while opening doors to develop and implement new ground-breaking technologies.

There is a difference between normal IT automation and cognitive automation technology. For example, a customer has entered a wrong data or left out a section completely while filling an e-form to open a new bank account. Existing IT systems will reject the form, flag it and wait for a human operator to make the necessary changes. Alternatively, in the case of cognitive automation processes, the system autonomously identifies and self-corrects the issue without any human intervention. This increases the efficiency of operations, reduces time and effort and results in a better overall customer experience.

RPA consists of screen scraping, workflow automation, and Artificial Intelligence (AI) among many other aspects.

Screen scraping, also known as Advanced Terminal Emulation, is the programming that translates data between legacy applications (software programs like mainframe applications etc.) and new user interfaces so that the logic and data of these obsolete software/legacy programs can still be used.

Workflow automation is the automation of organizational processes, centered on workflow guidelines and interaction between computers and human systems. It leads to increased productivity more efficiency and better customer experiences. Workflow automation leads to improved accuracy, audibility, and job satisfaction.

Artificial Intelligence (AI) is making a computer or a computer controlled bot or a software think intelligently. John McCarthy is known as the father of AI. The goals of AI are twofold, namely to create expert systems and to apply human intelligence in machines. AI is applicable in the world of gaming, natural language processing, expert systems, vision systems, handwriting systems, robots, and speech systems.

Industry Applications of Cognitive Robotic Process Automation (CRPA)
CRPA is the combination of RPA and cognition. It basically means the addition or application of human intelligence in a computer software or program, so that the software can do the tasks without any human intervention. Different industries have already started using cognitive automation tools to enhance their businesses.

AMELIA

IPSoft, an American technology giant has introduced Amelia, a virtual assistant, as one of their cognitive tools. Amelia has the most dynamic AI system and can understand up to twenty different languages. Amelia can handle all of a company’s service requests without the need for human intervention and help any company achieve Return on Investment without any risk. Like Siri from Apple, Amelia can talk to clients and solve their queries in a “conversational” language. She can manage processes which include checking out insurance policies for clients and helping customers open bank accounts. She will also be in charge of helping employees within businesses, providing HR services and helping employees learn company policies and guidelines. She has been deployed in many companies including Accenture, Deloitte, and Shell Oil.

VIRGIN TRAINS

Headquartered in London, United Kingdom, Virgin Trains are using CRPA and AI to manage company-customer relationships better. The company was finding it difficult to manage large volumes of customer complaints and ticket-cancellation and refund processes. As a result, the company shifted to Alexa, the virtual assistant from Amazon to handle their customer queries and complaints better. Their software bots are now responsible for the entire customer refund process. This cognitive automation solution has reduced daily processing time and manual labor involved in dealing with customer emails by 85 percent.

VANTAGE SOFTWARE

Vantage Software, headquartered in the United States of America was faced by a grave challenge, to provide accurate, real-time, fact-based recommendations on investment to financial managers. To help with this challenge, Coalesce, an IBM Watson powered cognitive computing technology was introduced. In the words of Greg Woolf, founder and CEO of Vantage Software, “With Watson, we can examine tens of millions of pages of documents, explore available market intelligence, risk profiles, and financial profile data to provide better information to analysts.” Another example of cognitive automation that has worked wonders for Vantage Software.

WELLTOK

Welltok, a leading software company for consumer health in Denver, wanted its customers to have access to reliable and up-to-date health information. Every day a lot of conflicting health-research articles are published all over the Internet causing confusion among consumers. This made the company come up with CaféWell Concierge, a cognitive powered tool. In addition to processing vast amounts of conflicting data, this tool can answer consumer queries intelligently by providing accurate and personalized recommendations.

Benefits of Cognitive Automation

The technological landscape has shifted towards cognitive automation. In the future cognitive RPA will come into play to monitor app health, optimize testing, and maintenance of self-health.The benefits of cognitive automation include

• Unequaled quality of service by reducing downtime and improving smart insights.
• Autonomous learning and cognitive computing will reduce operating costs by a large amount.
• Increased business performance and faster processing speed.
• Identifying patterns and running diagnostics to mitigate problems without any human intervention.
• Software bots work faster than human beings to extract and process data thereby increasing the volume of work-flow that can be achieved within a given time limit.
• Natural Language Processor (NLP), a tool used in cognitive computing, has the ability to communicate more effectively by resolving critical incidents reported by consumers.

IBM Cloud Automation Services combines cognition with analysis to provide business enterprises with the following advantages:

• A 50 percent reduction in server downtime in the past two years.
• Reduced average ticket time by autonomously resolving more than 1500 server tickets every month.
• 89 percent reduction in issues relating to critical incidents within six months.
• Has reduced the amount of time needed by an organization to solve a Severity 1 issue to 28 minutes from 19 hours.

A research report on the Cognitive Robotic Process Automation (CRPA) market by The Bureau of Indian Standards (BIS) shows us that CRPA services market was around $50 million in 2017 and it will grow at a compound annual growth rate of 60.9% between 2017 and 2026.

The Interplay between RPA and CRPA

There is a common misconception that RPA and CRPA are not related, but in reality, one complements the other. In simple terms, CRPA is a combination of RPA, Machine Learning, and AI. This small table shows us the difference in automated programs when AI is incorporated versus when AI is not incorporated.

The world is in a race to digitize itself. AI has vast applications and ranges from front to back office computer applications.

A study conducted recently by McKinsey showed that manufacturing, sales & marketing, supply chain, and customer service are the major industries where AI will spread the most and create enormous value. According to their study, it is predicted that global annual profits due to AI will be in the range of $3.5 trillion to $5.8 trillion.

Future of RPA and CRPA

RPA and CRPA are here not to replace humans but to make their work easier and faster. Artificial Intelligence today has found its application in predicting machine failure rates, sentiment detection, and facial image recognition. AI is expected to endeavor into human-level Artificial General Intelligence (A.G.I) very soon. AGI will make systems learn, plan and take decisions autonomously in addition to communicating in different natural languages.