Robotic process automation (RPA) is the application of technology that allows employees in a company to configure computer software or a “robot” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.
It is the use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required a human to perform.
Robotic process automation (or RPA) is an emerging form of clerical process automation technology based on the notion of software robots or artificial intelligence (AI) workers.
RPA vs Traditional automation
Software robots interpret the user interface of third party applications and are configured to execute steps identically to a human user. They are configured (or “trained”) using demonstrative steps, rather than being programmed using code-based instructions. This is an important concept in the RPA market because the intention is not to provide another “coding” platform for IT users (who already have the benefit of mature and tested software development and middleware platforms). Rather, the intention is to provide an agile and configurable capability to non-technical “business” users in operational departments. The paradigm, in summary, is that a software robot should be a virtual worker who can be rapidly “trained” (or configured) by a business user in an intuitive manner which is akin to how an operational user would train a human colleague.
The benefit of this approach is twofold. Firstly it enables operations departments to self serve. Secondly, it frees up the limited and valuable skills of IT professionals to concentrate on more strategic IT implementations such as ERP and BPMS rollouts. Such programs are often upheld as being transformational in nature, delivering huge returns in the medium to long term, whereas RPA is typically focused on immediate operational effectiveness, quality and cost efficiency. RPA is classically seen therefore as complementary to existing automation initiatives.
Characteristics of RPA software
One of the challenges of traditional IT deployments is that the transformation or change of existing systems is complex and risky. Thus, many large organisations are reluctant to redesign, replace or even to enhance existing systems through the creation of new IT interfaces (or APIs). For this reason, the philosophy behind RPA is to avoid the complexity and risk of such changes where they are not warranted, (or indeed to enable such changes to be prototyped and tested, simply by simulating equivalent input/output via the user interface in lieu of APIs).RPA tools therefore lean towards “light” IT requirements and do not, for example, disturb underlying computer systems. The robots access end user computer systems exactly as a human does – via the user interface with an established access control mechanism (e.g. logon ID and password) – so no underlying systems programming need be required. This is an important point because, from a security, quality and data integrity perspective, the UI of many applications encapsulates many years of requirements and testing for error prevention, data integrity and security access control. To bypass a UI by creating a new API is a risky undertaking and requires extensive testing in order that the same levels of functionality and protection are maintained.
RPA does not require programming skills: Business operations employees – people with process and subject matter expertise but no programing experience – can be trained to independently automate processes using RPA tools within a few weeks.Many RPA platforms present a flowchart designer, much like Microsoft Visio: process definitions are created graphically by dragging, dropping and linking icons that represent steps in a process.
- Business user friendly
RPA’s ease of use and low requirement for technical support perhaps explains why adoption typically originates inside business operations and not inside Information Technology (IT) departments. Because RPA projects do not require expensive IT skills and investment in new platforms, the economic threshold of processes with a viable business case for automation is substantially lowered.
- RPA software vendors
- Automation Anywhere
- Blue Prism
- Openspan (acquired by Pegasystems)
Impact of RPA on employment
According to Harvard Business Review, most operations groups adopting RPA have promised their employees that automation would not result in layoffs. Instead, workers have been redeployed to do more interesting work. One academic study highlighted that knowledge workers did not feel threatened by automation: they embraced it and viewed the robots as team-mates. The same study highlighted that, rather than resulting in a lower “headcount”, the technology was deployed in such a way as to achieve more work and greater productivity with the same number of people.
Conversely however, some analysts proffer that RPA represents a threat to the Business Process Outsourcing (BPO) industry. The thesis behind this notion is that RPA will enable enterprises to “repatriate” processes from offshore locations into local data centers, with the benefit of this new technology. The effect, if true, will be to create high value jobs for skilled process designers in onshore locations (and within the associated supply chain of IT hardware, data center management, etc.) but to decrease the available opportunity to low skilled workers offshore. On the other hand, this discussion appears to be healthy ground for debate as another academic study was at pains to counter the so-called “myth” that RPA will bring back many jobs from offshore.
The future of RPA
The future of RPA is subject to much speculation, as the early majority adopt the technology and discover new uses and new synergies. Possible future trends may include:
- A convergence of BPM and RPA tools, much in the way that the distinction between BPM and workflow tools is now blurred. The acquisition of OpenSpan in 2016 by Pegasystems is perhaps just one early indication of such a convergence.
- Greater incorporation of artificial intelligence (AI) for advanced decision making and inferencing. There is much in the way of analyst speculation,marketing and hype in industry media forecasting such developments but, as yet, it is not easy to identify verifiable public domain case studies which provide evidence of this type of technology being deployed alongside RPA.