Robotic Process Automation (RPA) is a new technology type that is used to replicate human actions interacting with a computer system. RPA can be used to automate tasks that are otherwise handled by a human, involves time, routine, and high volume work. When combined with machine learning (ML) and artificial intelligence (AI), RPA can be used to deal with varied and challenging business scenarios. The origins of such automation can be traced back to excel macros and screen scraping technologies, using which tasks were automated to a fairly good extent. But this had its own set of limitations and still required considerable human intervention and effort. A similar concept is also used in the case of test automation. Tools such as Selenium allows the recording of user actions and playing it on-demand to test an application. Over the past 4-5 years the technology for process automation matured and tools such as Blue Prism, Datamatics, Pega, etc. evolved, making RPA very popular. These tools are business friendly and requires involvement from IT to deploy the software.
Typical Use Case
Take the example of a customer support center which collates enquiries from end customers. For a company with global operations, this is typically a 24×7 task with a dedicated process team receiving customer emails, acknowledging these mails, allocating the enquiries for follow-up, and lastly, updating information in a CRM application. The above set of processes are repetitive, mundane, effort-intensive and mostly rule-based. When considered for RPA, each of these steps can be configured for the tool to handle with very little human intervention. Once deployed, these software robots can sieve through email inboxes, send acknowledgements upon email receipt, assign enquiries to relevant customer support staff and update the CRM application.
Benefits of RPA
Cost, quality and time are three aspects which are difficult to be improved simultaneously. RPA achieves this end to the best possible extent. It automates mundane and manual tasks, with efficient computer programs or software bots. With RPA, RoI is quick, quality unmatched and there is time saving in addition. Unlike traditional automation techniques, the biggest advantage of RPA is that it does not require any complex programming skills. RPA tools have business-centric interfaces with drag & drop, visual elements making it easier for enterprise adoption. Since the existing IT applications/ infrastructure is untouched, the extent of change management required for deploying the process is also minimal. Since high volume, low-value processes are automated, the need for additional human resources (and associated overheads) is limited when RPA is adopted. Software robots can take over such tasks, whereas cost-intensive human resources can be repurposed to handle core business tasks or drive new business initiatives.
The future of RPA will be closely linked to Machine Learning (ML) and Artificial Intelligence (AI), where rather than handling tasks based on rules, robots will be able to learn and think while handling tasks. The process would then be called cognitive robotic process automation. (CRPA) For example, consider the business scenario where robots are required to receive unstructured data, in different formats. Using ML & AI, robots can be made to learn these formats, interpret unstructured data and then perform automated tasks. This will take RPA to the next level, where human intervention is more or less eliminated to the fullest extent, while handling tasks from start to finish. Experion recently completed a project where invoices received from different sources are handled using RPA. In the first stage, data from client invoices in the form of PDF files, scanned images, etc. were extracted using software robots. The data is then interpreted & matched against payments made, entries posted into financial accounting software and finally consolidated into daily reports. The project was carried out by the Digital Transformation business unit of Experion which provides customized solutions to clients within emerging technologies such as RPA and ML/AI.