Identifying the Best Business Processes for Robotic Process Automation

Credit unions were some of the earliest adopters of robotic process automation (RPA) and initially had little trouble identifying which repetitive, rules-based business processes represented the best candidates for automating. But as obvious processes such as member onboarding and accounts payable were automated, it has become increasingly challenging for credit unions to determine which processes should be automated next.

Clearly, RPA holds the potential to lower costs, improve productivity and drive innovation. The catch, however, is that automation is only effective when it can be applied to those business processes that showcase its strengths. Generally, that means processes that depend on clearly identified, predictive business rules; use structured, readable input (such as Excel spreadsheets or PDF files) and occur frequently.

Business processes that exhibit low or no exception rates, require rekeying data across multiple systems and impact member satisfaction also represent strong candidates for automation.

To identify the best (although not necessarily the most apparent) processes to be automated, many credit unions are turning to task capture or process mining software for help. Using these tools can go a long way toward identifying all of the processes currently being employed, as well as the associated tasks required to perform each process from end-to-end, drive automation, and maximize process efficiency and continuous improvement across the entire enterprise. But do credit unions need both software tools and, if not, which one will be most beneficial?

Let’s start with task capture, which is a complementary technology used to process mining. Task capture software enables credit unions to discover, understand and analyze all of the individual actions (or tasks) needed to execute a specific step in a business process. Traditionally performed by a business analyst monitoring employees’ actions and then mapping the results, task capture software employs a manual recorder to capture employee interactions in each of the applications they use, taking screenshots and recording data such as keystrokes, clicks and data entry.

That information is then combined with context recognition to identify the low-level details of how specific tasks are executed according to metrics and key performance indicators (KPIs) defined by the credit union. KPIs potentially might include a decrease in completion time for a specific task or a reduction in errors committed during task execution. Ultimately, all of this information will provide guidance for RPA developers to automate each of those tasks, driving operational efficiency and higher-quality output, while reducing errors and enabling employees to spend more time on value-added, engaging activities.

Beyond fast-tracking the entire automation process, task capture software enables users to construct a comprehensive database of task and process documentation that captures even the most complex workflows. That institutional knowledge, in turn, can be used to inform all future developments, assuring that the work of business analysts and RPA developers is aligned.

In contrast, process mining software discovers entire business processes – i.e., any cluster of related, structured work in which a specific sequence of activities produces a product or service for a particular member. Processing monthly statements, for example, represents a business process.

While interviews and workshops traditionally were used to monitor and analyze processes, process mining software automates this procedure by using tools to investigate data stored in the enterprise systems’ event logs (those banks of data that store information such as software logins in the enterprise tech stack, interactions in that software and logoffs) to determine the end-to-end processes that a credit union is performing to complete work. These digital footprints are then analyzed by the software to present the process that has been successfully mined, along with process variants and suggestions as to how to optimize and automate that process.

Process mining’s ability to comprehensively scrutinize processes across the entire enterprise, targeting bottlenecks and inefficient processes, and driving compliance and efficiency improvements, is perhaps its greatest strength. Unfortunately, that ability to produce mounds of data can be overwhelming and may leave users needing the assistance of data scientists to make sense of it all. Process mining software is also very expensive, particularly when compared to task capture software.

The bottom line for credit unions is that both task capture and process mining deliver tangible value. While both are capable of contributing to higher-level outcomes such as improved efficiency and increased automation, they serve different use cases. Thus, if a credit union already has the right governance framework and budget in place and is primarily interested in identifying end-to-end business processes, process mining software might be the preferred choice.

If, on the other hand, a credit union is more focused on identifying the tasks its employees perform to improve workforce efficiency, better understand current processes being used and determine additional automation opportunities, task capture software probably represents a better option. Because many of the automation opportunities identified by task capture are less complex than those captured through process mining, they represent good candidates for citizen designers. As such, they are ideal for credit unions that are looking for a more cost-effective, user-friendly approach.

Dan Shimmerman is President/CEO for Blueprint Software Systems, a provider of digital process design and management solutions based in Toronto, Ontario, Canada.