Robotic process automation (RPA) is a series of tools that enable the development of automated processes without the intervention of a software engineer (Figure 1). Initially, RPA was introduced to reduce employee burden and improve efficiency and accuracy by giving repetitive tasks that can be performed more efficiently and more accurately through automation to software ‘bots’ that mimic humans interacting with digital systems and software. More recently, the concept of RPA has been extended to the use of cooperative robots (cobots) in manufacturing, warehousing, and logistics operations.
Figure 1: RPA software bots can efficiently and accurately perform mundane and repetitive tasks. (Source: TarikVision/Shutterstock.com)
Today, there are three ‘flavors’ of RPA implementations:
The various implementations of RPA use some form of intuitive user interface, such as drag-and-drop, to develop what’s called ‘no code’ or ‘low code’ automation. Each has its strengths and weaknesses, but the one thing they all have in common is a lack of standardization. As RPA use grows, so do the problems associated with the lack of RPA standards. Ultimately, the lack of standardization greatly hinders the ability of RPA to bring democratization to automation. This blog examines the reasons for the lack of RPA standardization and the next step in RPA evolution.
The problems start at the beginning of an RPA deployment during the process discovery phase. Efficient and accurate process discovery is needed to ensure the best return on investment (ROI) from RPA deployments. Existing process discovery tools specify process automation in different ways, often requiring manual intervention to restructure the results before they can be used on RPA platforms. As a result, it can be costly and time-consuming to identify processes that are good candidates for RPA implementations. And the problems continue to grow from there, including:
The lack of compatibility and interoperability among the various RPA solutions results in serious consequences for RPA users in terms of the portability and scalability of RPA deployments. While portability is important, scalability is touted as one of the key benefits of implementing RPA. Without a clear path to scalability, the benefits of RPA diminish.
RPA can appear to be good at solving specific tactical problems in various departments of an organization, but it has to be approached at a more strategic and centralized level to account for potential scalability concerns. An organization must choose an RPA platform with the right capabilities for long-term use to support scalability. That may not necessarily be the ‘best’ platform for early RPA adopters in the organization.
To maximize the long-term benefits of RPA, the overall strategic reasons for implementing an RPA program must be aligned with the overall capabilities of specific RPA vendors. Of course, there’s danger in getting locked into an RPA vendor with a strategic vision different from that of the organization; or an RPA vendor whose vision morphs away from that of the organization.
Lack of portability is a serious risk associated with RPA. If, for any reason, a chosen RPA vendor is no longer able to support the RPA vision of the organization, the consequences can be dire. The lack of compatibility and interoperability inherent in solutions from different RPA vendors could leave the organization locked into an incumbent vendor or require rebuilding a complete RPA network from scratch, regardless of the time or cost incurred.
The opportunity for RPA standardization may have been missed. The current participants are too entrenched and too far down their various product development roadmaps to retrace their paths and return to a standardized environment. But the emergence of intelligent process automation (IPA), also called smart process automation (SPA), is providing an opening for the development of standards. IPA is the application of artificial intelligence and related technologies to RPA (for a discussion of RPA and IPA, check out the companion article on “Democratizing Automation with RPA and AI”). With the introduction of IPA, the IEEE skipped past RPA and moved on to IPA standardization.
Promising IPA standardization, the IEEE Standards Association published IEEE 2755.1-2019 ‘Guide for Taxonomy for Intelligent Process Automation Product Features and Functionality’ to provide a guide to the “assessment, evaluation, comparison and selection of robotic and intelligent process automation products and features. Not quite a standard, this ‘guide’ provides common language for the assessment of over 140 IPA features and functions. It identifies their relative importance and provides guidance on their assessment. IEEE 2755.1-2019 is an extension of an earlier IEEE IPA standard, IEEE 2755-2017, ‘IEEE Guide for Terms and Concepts in Intelligent Process Automation.’
Current RPA tools and implementations are not compatible or interoperable across vendors as a result of a lack of standardization. That increases the complexities and risks associated with RPA and reduces the ROI that can be expected for RPA deployments. While it is unlikely that RPA standardization will occur in the future, there’s another path to standardization through the IEEE’s efforts to develop guides, and possibly future standards, for IPA technology, which is the next step in the evolution of RPA.
Jeff has been writing about power electronics, electronic components, and other technology topics for over 30 years. He started writing about power electronics as a Senior Editor at EETimes. He founded Powertechniques, a power electronics design magazine with a monthly circulation of over 30,000. He subsequently founded Darnell Group, a global power electronics research and publishing firm. Among its activities, Darnell Group published PowerPulse.net, which provided daily news for the global power electronics engineering community. He is the author of a switch-mode power supply textbook, titled “Power Supplies,” published by the Reston division of Prentice Hall.
Jeff was co-founder of Jeta Power Systems, a maker of high-wattage switching power supplies acquired by Computer Products. Jeff is also an inventor. His name is on 17 U.S. patents in the fields of thermal energy harvesting and optical metamaterials. He is an industry source and frequent speaker on global trends in power electronics. He has been invited to speak at numerous industry events, including the Plenary Session of the IEEE Applied Power Electronics Conference, Semicon West, Global Semiconductor Alliance Emerging Opportunities Conference, IBM Power and Cooling Symposium, and Delta Electronics Senior Staff Seminar on Global Telecommunications Power. Jeff has a Masters Degree in Quantitative Methods and Mathematics from the University of California, Berkeley.
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