When we talk about the capabilities of Robotic Process Automation (RPA) tools, we tend to focus on processes and tasks that are repeatable and clearly defined; intuitively, this leads to the conclusion that bots are limited to 'simple' activities like transferring data from one application to another. While they are certainly good at executing such tasks, robots are also highly adept at performing extremely complex jobs that involve multiple steps and convoluted processes. Indeed, as long as those multiple steps are clearly defined, documented and repeatable, robots have a distinct advantage over humans.
When people are charged with managing a task that involves multiple rules and actions, over time they will inevitably – either consciously or not – cut corners and eliminate steps to complete the task. Robots, on the other hand, aren’t smart enough to find ways to make the job easier on themselves. If they are configured to follow a 50-step process to the T, they will adhere to the rules without deviation or complaint.
This characteristic can be valuable to a number of industry-specific processes. Consider, for example, what’s involved when a telecom company decommissions an active circuit for a customer. The process involves multiple levels of communication between the telecom provider’s account and operations teams, as well as the transfer of data between multiple applications. When the change in service is implemented, all circuits, facilities, and third parties impacted by the change must be documented and tracked at multiple levels.
In this environment of fragmentation and multiple moving parts, opportunities for errors abound – errors that can results in thousands of dollars a month in unnecessary facilities fees. At the same time, the byzantine processes involved in circuit decommissioning can be clearly defined and documented – making them ideally suited for rules-based RPA programs.
Complex, multi-step processes are also common in the healthcare industry, where errors and sloppiness have potential life and death consequences. Hospitals, for example, require double and triple checks of processes related to the restocking of ambulances after a run, or the scheduling of tasks involved in routine reviews of charts. Here again, RPA is ideally suited to enabling consistency, accuracy, and auditability.
As enterprises deploy RPA tools for a wide range of business processes, as well as explore the potential of more advanced machine learning capabilities, they continually discover surprising new ways to drive savings and create business value. The use of configurable robots to execute highly complex processes is a prime example of such an opportunity.