Automation: A necessity in the Innovation toolkit?
Automation can no longer be considered an optional value-add. It is inevitable for businesses to automate certain recurring tasks and focus on value creation. But, how exactly is value created through automation?
We all know that automation is making minimal use of human effort at work, and relying on machines and technologies, to increase operational efficiency and consistency. With the increasing cost of human capital, and the technology at a mature stage to significantly cut down the manual work, automation heavily influences the bottom-line for most businesses. According to a McKinsey research report, about 45% of the activities that require a manual workforce, can be automated using the existing technologies, which translates to about $2 trillion in annual wages. Automating certain workflows or processes is not just about cost savings, they also lead to better employee engagement, by freeing them from mundane tasks and turning them into knowledge workers leading to better value creation for businesses.
Business Process Automation:
Business Process Automation(BPA), an overarching term for various types of automations in an organizational context, and a subset of Business Process Management(BPM), is an approach to optimizing the business processes or workflows using tools and technologies to reduce repetitive tasks and thereby, increase the efficiency of the workflow. BPA takes a holistic approach by understanding and analyzing the end-to-end workflows involved in an activity and then assessing the problems or bottlenecks in the existing processes. This approach to streamlining processes requires building solutions from scratch.
Robotic Process Automation:
Robotic Process Automation(RPA) is in-turn, a subset of Business Process Automation, which uses software tools to automate specific tasks by mimicking human interactions with a system or software, by applying some rules and thus carrying out the repetitive work through a set of defined procedures. Unlike Business Process Automation, RPA does not require solutions to be built from ground-up but rather can serve as standalone solutions for certain bottlenecks within a system. Deloitte’s global RPA survey mentions that the average payback period for RPA adoptions is at less than 12 months, with about 86% increase in productivity.
To help you better understand how this works, I’d like to share a specific use-case from my previous venture, which involved selling organic produce in a farm-to-fork model. Once a customer places an order, he/she is keen to track the order and know when it gets delivered. For that reason, they either contact our support team through a call or write to us over an e-mail. Our team was small, and this whole information sharing process took some time, which sometimes frustrated both our employees and the customers. We had to streamline this process in a way that any queries related to order tracking were attended by a bot, which takes information from our transport management system and then shares it with our customers. This process reduced the friction on both ends, freeing our team from these repetitive tasks and allowing them to focus on providing better customer support. On the other hand, the customers were happy to receive prompt updates about the order. This is possible using Robotic Process Automation using tools such as chatbots, and other workflow management tools.
Source: EY — Intelligent Automation
Intelligent Automation or hyper automation, is the application of Artificial Intelligence(AI) to existing RPA solutions to perform complex tasks by integrating various data services, machine learning(ML), and Natural Language Processing(NLP) technologies to learn the existing system, recognize patterns, and thereby, help to make decisions based on the changing nature of requests. One of the drawbacks of the RPA solutions is that if there are any changes in the way a system performs, or if there is an update to the functionality that is automated through RPA, the automation no longer works and it has to be automated again. This is a drawback that is fixed by Intelligent Automation solutions, by the use of AI and ML algorithms.
Intelligent Automation = RPA + ML + NLP + AI
A Gartner report mentions that “by 2024, organizations will lower operational costs by 30% by combining hyper automation technologies with redesigned operational processes.” This briefly helps us understand how automation is touted to significantly change the way businesses function.
Apart from business process automation, the other most common use-case of automation is in software testing. Automation testing is testing the software with a set of tools or software, easing the work for manual testers, by reducing the need to run repetitive or regression tests. The benefits that test automation provides are reliability in the tests performed, and faster execution of the tests. Imagine, how long would it take to manually test your business’s website or mobile app, and how many resources does it need, but what if all these tests were automated? Since test automation has significantly matured over the years, there are a lot of frameworks and tools that help businesses get started in test automation.
Selecting the right processes, applications, and tools will not only help businesses automate certain tasks and lower their costs, but will also lead to greater engagement with employees, and customers.
We, at 91social, can help you get started in your automation journey, thus making work fun for your employees. Visit us at 91social.com, or alternatively, you can contact us at email@example.com or on +91 95130 07587.
This blog is originally posted on our Medium account