Whenever the term Robotic Process Automation (RPA) was mentioned, it is not hard to conjure images of cold, mechanical machines doing physical labour and replacing jobs in rendering human workers redundant. However, such perception could not be further from the truth, not just because of how the word “robotic” can be misleading, but also the lack in understanding what RPA is beyond the headlines.

The Subject

So what is RPA? Unlike many other topics discussed on this site here, there is one specific, official definition published by a governing authority (in this case, a diverse panel of industry participants). According to the IEEE Guide for Terms and Concepts in Intelligent Process Automation published by the IEEE Standards Association, RPA is defined as a “preconfigured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management”.

Now, often the problem about standard definitions is that the meaning can often be lost in a sea of words. One site has actually cited this definition, and has to include a simpler analogy: software robots that mimics human action.

This, however, should not be confused with Artificial Intelligence (AI), which the same site likened to human intelligence being simulated by machines. In fact, RPA is illustrated in a lower rank than AI in a doing-thinking continuum, where RPA is more process-driven whereas AI is data-driven.

So how does RPA works? Several sites have pointed out that RPA existed as an evolution from several technologies. Notably, the most cited technology in which RPA was evolved from is screen scraping, which is the collection of data displayed on screen usually from a legacy application to a more modern interface. Another technology cited is (traditional) workflow automation (or in this case, where a list of actions were programmed into the software to automate tasks while interacting with back-end systems through application programming interfaces (APIs) or scripting languages.

RPA, being evolved from those technologies, develops the list of actions through monitoring users performing the task in the Graphical User Interface (GUI) and then perform the automation through repeating the tasks on the GUI. Furthermore, RPA does not require a physical screen to operate as the actions would need to take place in a virtual environment.

The Pros and Cons

It’s not too hard to look at the continuum above (also called as the “Intelligent Automation Continuum”, albeit a simpler one) and relate the benefits and risks to that which have been discussed, such as Machine Learning and Artificial Intelligence. However, seeing RPA is more process-driven rather than data-driven, there would be difference in the benefits as well.

Multiple sources cited the benefit of achieving greater efficiency, as RPA is able to conduct repetitive tasks quickly around-the-clock with minimal error. With such efficiency, organisations that uses RPA may reap the benefits of cost savings from staffing, since such tasks no longer require the same number of staffing.

Some sites were more subtle on the message of reduced staffing, by pointing out that RPA may free up staff from monotonous and repetitive tasks to conduct more productive and high-value tasks that require creativity and decision making, or exploring the opportunity for people to be re-skilled and obtain new jobs in the new economy.

But just like the many other topics discussed on this site, human worker redundancy is the pink elephant in the room. According to estimates from Forrester Research, RPA software could displace 230 million or more knowledge workers, which is about 9 percent of the global workforce. Furthermore, in some cases, re-skilling displaced workers may not be within the organisational users’ consideration, since there may not be as many new jobs available for these displaced workers, not to mention that re-skilling may negate the cost saving benefits achieved. With that said, currently many organisations have already resorted to Business Process Outsourcing (BPO) for many current tasks which RPA is suited to deploy on, and hence displacement may be more serious in BPO firms.

Another benefit of RPA cited by certain sites is how RPA can be used without the need for huge customisation to systems and infrastructure. Since RPAs are generally GUI-based, they do not require deep integration with systems or alterations of the infrastructure, and are supposedly easy to implement. In fact, automation efforts can be boosted by combining RPA with other cognitive technologies such as Machine Learning and Natural Learning Processing.

That being said, RPA’s dependency on systems’ user interfaces carries a risk from obsolescence. RPA interacts with the user interface exactly as how it monitors/programmed to do, and when there are changes to the interface, the RPA would break down. And remember, RPA is also reliant to the exactness of data structures and sources, rendering RPA rather inflexible. This inflexibility is a stark contrast to how easily humans can adjust behaviour to changes as they arise.

Then there are APIs. Modern applications usually have APIs which are a more “resilient approach” in interacting with back-end systems to automate processes, relative to the brittleness RPAs had to face from the limitation described earlier. Furthermore, APIs may be seen as a more favourable option in an end-to-end straight through processing ecosystem involving multiple operating systems and environment.

The Takeaway

There are many use cases for RPA these days, that it is not exactly a new topic. Plus, with the criticism of dependency on features which may change or become obsolete, RPAs many not seem as alluring these days. In fact, some rule of thumb is to consider whether the processes could be processed straight-through with existing capabilities, before resorting to RPA.

Organisations should identify tasks that RPA may be applied and remain relevant in years to come before making the decision. Others would advise a more broad-based approach in investing automation – to consider the whole continuum instead of expecting RPA as the silver bullet to operational efficiency.

As for the redundancy problem, it has been the recurring theme in this age of digitalisation. Reiterate several posts written here, the society as a whole needs to confront with such issues and answer grave, philosophical questions concerning human jobs and roles in the future. It is an essential discourse to take place, in which is not happening enough with due significance unfortunately. And if we were to take reference from history, not doing much is simply equivalent to a Luddite approach.