Omdia, technology research and consulting firm, was formed at the start of 2020 by unifying the depth and breadth of expertise from Informa Tech’s legacy research brands: Ovum, IHS Markit Technology, Tractica, and Heavy Reading. Today, Omdia helps organizations make better technology choices for their business and enable technology innovators to better understand and reach the markets they hope to serve. A couple of weeks ago, Omdia introduced its new report that sheds light on how RPA and intelligent automation are gathering increasing momentum in the enterprise technology marketplace. The report was named “Fundamentals of RPA & Intelligent Automation – 2021” and here are some details that were given by Cassandra Mooshian, senior analyst for AI and intelligent automation at Omdia, who shares her thoughts about a few of the report’s many takeaways.
Why is it important for organizations to have a strong data architecture before they implement RPA/IA?
“It is important for companies to have data management, governance, and security policies in place ahead of implementing RPA/IA as these solutions work across multiple enterprise applications. Ensuring roles-based permissions and access is one component and ensuring data integrity is another, among many others. Automating a broken or error-prone process will not fix the process; rather, it’ll just break faster. For intelligent automation especially, training an ML model on “bad” data can lead to process errors and inefficiencies.”
Low/no-code IA platforms help democratize automation and scale cost and time-saving benefits. Could you explain how?
“No-code, drag-and-drop features are increasingly common among IA platforms which are more business user-friendly. Outside of IT and development teams, not many folks know how to write code. But by being able to drag and drop and/or choose from a list, these platforms can be usable/accessible to more users who can create bots or automate a task. The more automation, the more time and cost savings.”
How do process and task mining and intelligent document processing (IDP) extend the reach and effectiveness of process automation solutions?
“Process mining is used to obtain a wide lens over business processes and workflows within a company by examining event logs across systems, including how variable they are and where there are bottlenecks. The less variable the process, the greater its potential candidacy for RPA/IA, though other factors must be considered as well.
Task mining is used to understand how a user is interacting with systems and where there are opportunities for automation. Both of the above help identify automation candidates throughout an organization.
IDP is a use case of IA and is growing in popularity, as there are so many document-intensive processes across organizations that impact many employees. IDP has the potential to help save companies a lot of time, and AI models are getting smarter and smarter, further improving IDP outcomes.”
What is the best industry-specific use case of RPA and IA that you have seen?
“This is a tough one because there really isn’t one “best,” and a lot of the use cases are horizontal in that they’re applicable to a business function and apply across industries. Top of mind, I’d say financial services have been one of the first-movers regarding uptake of the technology, and there have been many use cases/customer success stories that have and continue to come out of the industry. Some common use cases in financial services are loan processing, mortgage processing, customer onboarding, customer service, and others.”
You can find more answers from the interview with Cassandra Mooshian on the source page.