How do you measure success? It’s a tough, complex question in just about any walk of life. RPA is no different. RPA, short for Robotic Process Automation, refers to automated, software-based tools that can be used for carrying out repetitive, high-volume tasks in the workplace. However, while this broad description explains what RPA is, what may be less clear is what a successful deployment of RPA bots means in terms of success.
In the broadest sense, success means that these tasks — which may vary from populating databases to generating reports to helping process invoices — get completed as planned. But when it comes to being able to prove the value of these RPA tools or establish goals for an RPA development and deployment process, success can have many facets. These metrics are important to consider when you set out on your RPA roadmap and will help organizations to assess whether they’re receiving the outcomes they want from this breakthrough technology.
Here are four ways you can gauge the success of RPA:
#1. Speed and productivity
Certain jobs or tasks are easier to measure in terms of productivity than others. An admin assistant who can process 50 forms per hour is more productive — and, on a dollar-for-dollar basis, valuable — than one who processes half as many. On the other hand, a C-suite executive who takes twice the number of meetings per day as another may not be twice as valuable, without further evidence.
Fortunately, most of the tasks RPA is used for fall into the former, rather than later, category. That is to say, that these are rule-based, repetitive tasks that do not involve a whole lot of nuance or additional context.
Productivity is likely to be one of the main metrics businesses utilize RPA for. Unlike humans, who may work a 40-hour week with weekends and vacations off, RPA bots can keep churning through their workload 24/7. To measure the productivity of an RPA bot, simply look at whether certain processes are being carried out as rapidly as they were before. If so, then as long as the cost is deemed acceptable, then they’ve proven their business case.
A job done quickly isn’t always a job done well. Speed and productivity should therefore be assessed alongside accuracy. It may be that, in certain cases, getting a job done faster is worth a slight dip inaccuracy. But one of the big strengths of RPA is its rule-based attention to detail. Unlike a human employee, you’re not going to find that a data entry RPA bot starts to make mistakes toward the end of a Friday as the week catches up with them. Instead, these tools should offer a high level of consistency and accuracy regardless of the hour of the day.
Consistency is another valuable metric to assess. You could, for example, measure the number of errors with the processes in place before RPA was adopted versus the number, or frequency, of errors after these tools were deployed.
You could also look at issues that might stem from accuracy (or, more appropriately, a lack of accuracy.) If human error meant, for instance, that one out of every hundred customers did not receive an order correctly because of input errors, and that this affected their willingness to be a repeat customer, an RPA bot able to reduce these errors significantly has another metric by which to prove its worth.
Sticking to the rules is important in all sorts of areas. But nowhere more so than in businesses that have stringent compliance rules. Industries with strong regulatory compliance requirements not only have these rules for a reason but also punish infringers with strict punitive measures including heavy fines.
RPA bots can be designed to follow regulated rules as part of their coding, and will never forget or fail to adhere to these rules. Furthermore, RPA bots referred to as “attended automation” tools can assist human employees in following these guidelines by alerting them if they stray off-course in some way. Comparing previous or potential regulatory fines with the amount invested in RPA tools is yet another way of demonstrating their value.
#4. The value of freeing up humans
This is one of the harder, more nuanced ways to measure return on investment for RPA. It’s also one of the most important. Contrary to certain people’s fears, RPA isn’t about replacing humans; it’s about augmenting humans by automating the repetitive tasks that they do not wish to do. As such, employees can be freed up to focus on other, more rewarding tasks within the organization. Companies can look at added productivity from human employees who, no longer have to carry out certain tasks, can direct their time and energy elsewhere.
They could additionally assess overall employee satisfaction rates. Happier employees are not only likely to be more productive, but they might also be less likely to want to leave and take their skills elsewhere. Reduced staff turnover could therefore be a very real impact of RPA deployment.