With over 450 process implementations, we know exactly what the crucial parts of a successful Process Mining initiative are
“RPA is too much hassle for nothing.” There is more to it
RPA or traditional automation?
RPA is an emerging automation technology that offers many benefits to traditional workflow automation. In the latter case, a software developer produces a list of actions to automate a task and an interface to the back-end system using application programming interfaces (APIs) or dedicated scripting language. In contrast, RPA bots and systems work directly in the Graphic User Interface of the third-party application They are configured to execute steps identically to a human user: they develop the action list by watching the user perform a certain task using demonstrative steps. Finally, they perform the automation by repeating those tasks directly in the GUI.
Same old processes
This works out well for high-volume and basic processes with not too much variation, like data entry or validation across multiple systems. Robots and bots don't make human errors, they work faster, can be scaled up to match fluctuating process demands and repeat the task with pinpoint accuracy and efficiency. The benefits go on and on and are indeed very promising. However, many enterprises run many of their processes the same way they did 20 years ago. Although they outsource tasks, use shared service centers or move to the cloud, they still operate the same process – the only difference to the initial processes being that now part of them are done offshore or in the cloud. RPA has not changed that reality as it could not inspire enterprises to rewire their processes – it is often just used to move data faster and require less manual intervention.
Strategic RPA
For companies to gain strategic benefits and break-even with associated costs for getting RPA to work, they need to first have solid understanding of the as-is processes, legacy systems and the right overview of automation opportunities – and that includes a clear strategic alignment of business and IT. That is where other technologies, like Process Mining, come into play. Process Mining gives clear insight about how a process is carried out in the real world, it also tells what kind of lead times are common and enables companies to precisely specify and measure the possible benefits of a RPA system for certain tasks. For instance, it can clarify how many minutes, hours or days of manual work can be saved or the effect the automation will have on different KPI and PPI. But the opportunity is bigger than many companies anticipate.
Uncovering more value
Many enterprises use Process Mining to check conformance or analyze outliers, but they have not yet considered using their Process Mining software to entirely redesign a processor sub-process. Instead of fully or partially automating processes that have been designed in the days when the Nokia 3310 was the latest cellphone, redesigning a process with RPA in mind will yield stronger benefits that range from better efficiency and reliability to saved time and money. In this context, the motto is “Automation needs to support transformation, not legacy.” Knowing that it is possible to build simple many, automated RPA bots or systems, even with specialized triggers, processes can be designed in an ambitious way. Instead of trying to push 40 process variations into the corset of a single process that needs plenty of manual efforts and rework due to variations, building 10 or even 20 main process variations that all are executed effectively due to effectively adapted RPA triggers for various scenarios will make, in certain situations, companies more agile and processes more efficient.
RPA is well-suited to automate processes and process steps that are time-consuming and standardized with minimal exception handling. But to create value besides improving the efficiency of existing processes by a few percent, RPA needs to be considered on a higher business level and furthermore combined with other emerging technologies, like Process Mining or Digital Process Automation/Intelligent Automation.
Thomas Kerschbaumer
Head of Delivery
t.kerschbaumer@processand.com
Alexandra Tyrkich
Head of Data Science
