Emerging automation technologies and an unprecedented surge in data are creating a unique opportunity for organizations to optimize business processes to achieve greater operational efficiencies. They’re unlikely to hit many roadblocks until unstructured data enters the mix. At that point, the process stalls – or even comes to a screeching halt. This is a problem for companies that want to take full advantage of what robotic process automation (RPA) has to offer, including greater efficiency and a lower total cost of ownership (TCO) for their automation initiatives.
Documents and other unstructured data, such as PDFs, videos, photos, emails and websites, make full end-to-end automation of business operations difficult because they require a human to analyze, understand and make a decision based on the information contained within each. This creates bottlenecks and dramatically slows workflow – quite the opposite of what organizations want to achieve with their automation initiatives.
This increasingly prevalent scenario poses a significant threat to many companies’ automation ambitions. As much as 60 percent of business processes contain some sort of unstructured data. That means 60 percent of the time robots must stop their work until a human intervenes.
For example, in the claims processing world, nearly every aspect of the process remains paper based. People mail or email physical or scanned documents to a system, where humans must then review and classify them by hand. For those with end-to-end automation ambitions, this is understandably daunting.
It also might explain why, despite two decades of business process management (BPM) implementations, full process automation is still the exception. According to AIIM’s 2019 Emerging Technologies Market Report, “two-thirds of organizations say that specific core back-end processes are less than 50 percent automated.”
And while some industries are using RPA for records management, customer correspondence, check processing and other paper-intensive processes, fewer than one in five organizations have fully automated their core back-end processes, AIIM found.
Meanwhile, the turmoil introduced by unstructured data is only going to get worse. Half of respondents to the AIIM survey say 70 percent of the data in their organizations is unstructured. At the same time, organizations are anticipating massive data growth. According to the survey, 35 percent expect the amount of data to increase fivefold over the next two years. It’s no wonder that 70 percent of organizations surveyed by AIIM say unstructured information is the “Achilles’ Heel” for many RPA implementations.
RPA + AI = Automation Maturity
So how can businesses reach mature levels of automation?
They must combine RPA with artificial intelligence – a core capability of an intelligent automation platform. With advanced cognitive capture and entity extraction, analyzing and interpreting unstructured data becomes a reality. Intelligent automation enables organizations to digitally transform knowledge-based business processes, turning what was a bumpy ride into smooth sailing.
An intelligent automation platform can manage document separation, classification and routing, increasing the speed of processing and accuracy, while reducing the need for human involvement. Thus, routine tasks that previously derailed a robot are handled more efficiently.
Think for a moment the steps that take place when a customer trying to open an account via the bank’s mobile application uploads a photo of their driver’s license. The image must be read, and the data extracted. Or how RPA alone handles a patient email that includes important details about a recent claim. In both cases, the RPA bot can’t handle this sophisticated data. A human must step in to read, understand and make a decision.
With an intelligent automation platform that leverages cognitive document automation (CDA), information is captured, read and understood. Because CDA can read data in a variety of formats, it can transform the driver’s license and the email into usable information. Using machine learning and natural language processing, the intelligent automation platform then interprets the data and determines what happens next.
An intelligent automation platform handles this job more effectively and at a lower cost than a “bolt-on” solution. The result? Organizations can create greater efficiencies, lower TCO and fully automate their business operations end-to-end.
Unstructured data isn’t going away. For organizations struggling to achieve more mature levels of automation and eliminate bottlenecks and slowdowns, a key consideration should be implementing a solution that integrates RPA with artificial intelligence. This way, organizations can advance automaton initiatives from repetitive transactional use cases to more complex knowledge-based business processes – enhancing customer experiences and operational excellence. With the combination of AI and intelligent automation technologies, your teams can begin working like tomorrow - today.
Ready to learn more? Download the eBook "Your Intelligent Digital Workforce: How RPA and Cognitive Document Automation Deliver the Promise of Digital Business."