After identifying your project scope, selecting your deployment mode and constructing your automation processes (following layered design principles), you will need a way to administer them in production. Process Administration provides the necessary capabilities to deploy and manage automation solutions. This blog will explore the versatility of process administration systems and provide advice on the features to look out for when selecting the right robotic process automation (RPA) tool. By the end, you should have a proficient understanding of each of the points listed in the infographic below.
Put simply, process administration makes it possible for your business to monitor and track the progress of deployed processes. This provides administrators with the operational agility to properly maintain and upgrade the RPA system. Aside from analytical benefits, process administration can also offer queue management and remote management capabilities. Tasks such as resource allocation and task designation can all be handled through administration portals. The system level configurability that each of the tools above provides is what makes process administration so useful.
RPA tools, designed for central orchestration, make use of a central interface from which all commands are issued. Conceptually known as the control panel or control center, this feature orchestrates the automation akin to a control panel in a PC. The key takeaway here is that a control center allows administrators to launch each management tool from a centralized user interface.
The next half of the blog will explore the 3 most important tools to search for in administration interfaces.
Another critical feature of process administration is error handling. Monitoring and handling errors goes hand in hand with upgrading and maintaining an automation. Many control panels will list real-time errors in the process queues. When a process encounters a system exception, that specific instance will be labeled with an error. Often times, RPA tools can be configured to send notifications when errors are encountered. More comprehensive monitoring systems will provide detailed logs of each specific queue item, along with traceable details, allowing a team to track down problems in less time. A critical feature in the handling of errors is the ability to retrigger the failed cases so that the automation can be re-run. This is particularly helpful if errors occur when a system is temporarily down. Symphony has found that having a maintenance team that monitors and fixes any recurrent errors, whether it is in-house or third party, is the key to ensuring that process run at their full potential.
RPA analytics is driven by global process tracking. Monitoring the status of each process through the control panel helps administrators reduce inefficiencies. It is also common practice to check in on the real-time status of each process to ensure that the system is up and running and performing as intended. Many enterprise-level RPA tools take advantage of real-time analytics to present a dynamic dashboard on the control panel. These typically include visuals based on statistics like resource usage, process completion time, and transaction success rates. When it comes to auditing an automation, accessible analytics simplify the performance review process and highlight areas of improvement. When paired with the appropriate actions, analytics can foster continuous improvement in automation quality.
Controlling resource usage is another key function to look for in RPA tools. This is how you would act upon the analytics data gleaned through process monitoring. Control centers will often have a section dedicated to resource allocation. This is both where administrators select which machines will perform the tasks at hand and where the specific tasks are designated. In other words, you can control the task that each machine will perform. Full control of the automation system enables administrators to make the most out of license value and limited resources. What makes the best RPA tools stand out here is how the assignment of resources is handled, among constraints such as environment, run time and task schedules. Ideally, the necessary configuration settings are built into the software architecture, so workarounds are not needed.
In conclusion the ideal control center will have real-time analytics, resource allocation, and comprehensive error handling. In an ideal deployment, analytics provide the basis for workforce oversight, while data from analytics drives the optimization of resource allocation and continuous improvement. Meanwhile error tracking enhances the debugging/testing process and ensures all processes run smoothly throughout.
From this overview, you should now have a sense of what features to look for in an RPA control center. From our experience, this repository of management tools not only bolsters your RPA operations, but can also be a good indicator of an RPA tool’s overall capabilities and layout.
The good news is that due to the importance of administrative features, there is pressure to constantly improve them. Many top RPA tools are rapidly evolving their control panels to be more sophisticated and capable. Our advice to buyers is, whilst administrative tools are an important element of an RPA tool, they are just one selection criteria. we would be happy to advise on your selection of a tool or alternatively please continue to read through this blog series to hear about the other important elements to consider in tool selection.
This is part 4 of a 22 part blog series by the leading experts at Symphony Ventures. It addresses how to choose the right RPA tools for your business needs. Drawing from our global team’s extensive knowledge in automation consulting, implementation, and managed services across a range of diverse industries, we’ve drilled into the technical criteria to consider when selecting which RPA software best enables your company’s digital operation strategy. Read part 3, A Guide to the Modes of Automation.
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