Robotic Process Automation (RPA) tools are being widely adopted across a wide range of enterprises and industries. By executing narrowly defined, repeatable tasks, RPA bots can drive dramatic productivity increases and significant cost reductions. For as little as $10,000 to $15,000 a year to deploy and maintain, a single bot can perform the routine, administrative tasks of five to ten people.
RPA is being applied to a wide range of generic business processes related to Finance and Accounting, such as order management and invoice processing, as well as HR functions such as payroll and pension management. In additon, RPA bots are being deployed for industry-specific tasks such as credit card and loan processing in financial servcies, claims processing in insurance and third-party administration in healthcare.
Somewhat counter-intuitively, RPA is not just for “simple” tasks; indeed, the technology is ideally suited to convoluted workflow processes that are both labor-intensive as well as highly prone to human error. For example, in a large, complex environment, account reconciliation can be a painful undertaking that involves rigorous compliance standards and multiple steps to match and verify numbers and records. When people are in charge, they invariably get sloppy or take shortcuts. Robots, meanwhile, aren’t smart enough to cut corners; instead, they follow the directions they’re given to the letter, ensuring accuracy and compliance.
Benefits notwithstanding, traditional RPA systems have several major drawbacks. For one thing, the bots can’t handle anomalies or learn from experience. If the steps they’ve been instructed to follow don’t align with the reality of the function they’re working on, they can’t devise a solution. Rather, they report the anomaly as an exception that requires human intervention. This results in a productivity gap for shared services operations managing large volumes of unstructured data, because standard bots can’t navigate the nuances involved in, for example, email requests.
Today, self-learning applications are enabling bots to quickly identify a mistake and apply a fix, without requiring a rewrite of the bot’s instructions. When an exception arises, the cognitive tool flags the exception. And when that exception is fixed by a human administrator, the bot captures the fix and applies it going forward. As a result, the tasks of updating and optimizing RPA tools are significantly streamlined. Over time the expertise of these “cognitive bots” can match that of an operation’s top agents.
Natural language processing tools, meanwhile, analyze the context of words and phrases, enabling business users with minimal technical training to interact with RPA systems by using plain English commands. For example, a user from an accounting department can simply type, “I need to create a cost center for the marketing team,” and the robot understands what’s needed and executes the task. If the request is worded differently, such as, “Create a cost center for marketing,” the robot responds.
By simplifying and speeding the process of updating and reconfiguring RPA tools, integrating cognitive capabilities into basic RPA functionality reduces the need for constant intervention and oversight by technical experts. Given the scarcity of that technical talent in today’s market, smart tools can significantly reduce the productivity-sapping bottlenecks that characterize many RPA initiatives.
Optimizing BPO Capabilities
Cognitive-enabled RPA initiatives extend the benefits of automation and drive additional cost savings and increases in productivity. Equally important, by applying smart tools to continually optimize the automation of routine tasks, enterprises can focus their energies on strategic decision-making and on enhancing their shared services and Business Process Outsourcing (BPO) capabilities.
One characteristic of this strategic mindset is the ability to effectively deploy Agile methodologies that leverage collaboration between technology teams and business users – collaboration that is essential to reaping the full benefits of RPA. In addition, enterprises can focus on process optimization and identifying new opportunities to drive intelligent automation. Finally, a mature BPO strategy includes an RPA Center of Excellence (CoE) to enable oversight of the overall automation strategy, prioritize initiatives, manage organizational change and serve as a focal point of innovation.
RPA has had a dramatic impact on the ability of organizations to reduce costs and increase productivity in managing basic business processes. As the integration of RPA and smart tools continues to evolve, smart enterprises will seize the opportunity and leverage these emerging capabilities to fundamentally redefine their approach to managing business processes.