RPA is just the first step in a foundational shift for your business
One of the key trends in the coming years is the confluence of disruptive technology innovations such as Artificial Intelligence, Robotics, DNA Sequencing, Autonomous Vehicles, Blockchain and many more. These technologies create an S curve for growth, and when one or more of them are interspersed, they amplify the benefit accrued to the businesses, governments and society as a whole. Robotic Process Automation is one such technology that has been around for a while, but now the better adoption of AI components has made RPA even more impactful. AI replaces judgment with machine learning algorithms, humans with conversational intelligence chatbots, and consumes all forms of data e.g. numbers, text, pictures, audio and videos, to make automation more intelligent.
RPA automates low complexity, high volume task that require minimal judgment and are rather rule based. One example could be the intake of an invoice for a Finance Process, which can be broken down into simple and routine activity and then RPA can be applied to replace certain human tasks with bots. However, RPA is typically narrowly focused on one or more adjacent tasks and seldom replaces or redefines an entire role/function.
Intelligent or Cognitive automation handles more complex jobs and looks to completely digitize it. Understanding a language or text (Natural Language Understanding), recognising speech (Conversation Intelligence via Chatbots), or visually recognizing or reading characters (Optical Character Recognition), and interspersing this with simpler tasks that can be accomplished through RPA, traverses that journey.
The use of intelligent tools, such as virtual assistants and chatbots automates key functions in industries with heavy human interaction. Similarly, tools like OCR allows paper-intensive industries, such as healthcare or financial services, to automate text reading and understanding.
IA (Intelligent Automation) is underpinning straight through processing in several industries with the potential to drive significant productivity, improve accuracy, reduce turnaround time, save cost and enhance user experience. There are scenarios from three industries that are being used for the purpose of illustration.
Banking front and middle office, both for retail and commercial segments, have several activities in the value chain that are manual, paper-intensive and require various touchpoints and hand-offs, that are time-consuming, error prone and keep the Relationship Managers away from driving seamless experience for their clients. This begins with lead generation and includes customer onboarding, underwriting, funding, and several other front and middle office activities. All of these can be redefined through improved process design, identifying the right business process management framework, and bringing in the intelligent automation functionalities to reimagine the entire function.
The insurance industry also relies heavily on relationship management or agent model and has several steps in the value chain, i.e. insurance sales that can be made straight through without human touch, make policy updates that is typically low complexity and low-value activity and can be redefined. However, one of the biggest opportunities lies in claims management and processing, which has umpteen number of steps that are very manual and time consuming, and they can be revamped with Intelligent Automation, starting with image processing of vehicle damages, document upload to insurer cloud, and assisting claims handlers with prefilled forms.
Industrial export processing has a long cycle that requires the involvement of counterparties, banks and heavily relies on letter of credit as a funding mechanism for goods being exported. In one of our recent studies we observed that upto 80%+ processes are amenable to be made zero-touch, and the turnaround time is brought down from more than 25 days, to less than 10 days, and even further scope of improvement lying ahead, once processes are redefined. Initially, it was envisaged as a robotic process automation program, but eventually several AI interventions were imagined, along with a BPM tool deployment to take advantage of the full potential of AI-driven Automation.
Implementing IA is not without challenges, for example, process ambiguity is a challenge if the processes within the organization are not well understood. Process mining and process discovery remedy this challenge by helping businesses with process mapping — a necessity before embarking on an IA implementation. Lack of focus on standardization is another one. No standard approach to automation exists, so each automation product vendor may approach the same process differently, this poses problems while switching vendors. Automation platform selection is time consuming given there are many types of partners, from SaaS (Software as a Service) vendors to PaaS (Platform as a Service) vendors. Systems integrators play an important role as they select the solution and the automation software that works best for a given corporation.
Traversing the journey from RPA to Intelligent Automation is significantly changing jobs and, in some cases, an entire function for corporations, and almost creating digital twins. This presents a massive transformation opportunity for the industry that needs to be seized.
About the author:
Sanjay Ojha is a Senior Partner with IBM Consulting and leads Artificial Intelligence, Data and transformational technologies business for India & South Asia, and is based out of Gurgaon, India.