Robotic process automation (RPA) is the fastest-growing segment of the enterprise software market. This technology, which automates business processes has had impressive growth of 63.1 percent in 2018, rising to a market value of $846 million, according to Gartner.
CIO magazine points out that that COOs in the financial vertical led RPA adoption, recognizing — and then capitalizing on — software robots’ ability to improve processes efficiency without hiring more staff. This vertical found that, in general, bots are cost-effective and easy to deploy, and, in some cases, bots, which can handle up to 15 or 20-step processes, are a transition to intelligent automation (IA) with machine learning or artificial intelligence solutions.
Malcolm Ross, VP of Product Strategy at Appian, shares his insights into the RPA growth phenomenon:
What factors do you attribute to RPA’s growth?
Ross: The exponential growth in RPA can be attributed to the pressing need for organizations to drive efficiency and eliminate waste in business operations. It also enables non-technical businesses and lesser equipped IT departments with the tools they need to build time-saving automations.
These elements fueled Appian’s decision to acquire Jidoka, the highest-rated RPA software according to Gartner Peer Insights, to create what we call “low-code automation.”
Prior to RPA adoption, businesses had the option of outsourcing routine, manual tasks, such as inputting data, extracting data from documents, reformatting data, or performing calculations. What are the benefits of RPA over outsourcing manual processes?
Ross: At Appian, we think about RPA as insourcing, not outsourcing. In order for RPA to perform at its fullest, however, humans need to manage and monitor all of the bots that they’re using.
How can RPA work with computer vision, natural language processing, or other emerging technologies?
Ross: Much of the complexity around repetitive human activities revolve around the use of humans to visually recognize elements or data on a screen and to extract and move that data. Because RPA bots try to emulate these same human characteristics — the ability to see a computer screen in the same manner as a human — getting this right becomes very important to ensure the overall success of an RPA implementation.
What advice would you give established or aspiring software developers working in the RPA space?
Ross: While there seem to be endless numbers of opportunities to apply RPA for quick organizational wins, it’s important not to lose sight of the bandwidth needed to completely overhaul processes. Take stock of the processes you’re attempting to “fix” with RPA — as they say, don’t automate a bad process.
RPA can often be perceived as a band-aid to process problems; however, larger business process management (BPM) platforms allow organizations to address those processes more holistically and re-engineer them to accommodate new business patterns.
The Downside of RPA
CIO points out that, like any tech solution, RPA isn’t the right choice for every operation. For example, an operation that often experiences changes due to regulations or other factors could find it difficult to constantly update their bots, and RPA solutions may present challenges when an operation scales.
To overcome pitfalls, it’s essential to manage your clients’ expectations and communicate exactly how RPA will function within your client’s operations. Also, work with your clients during design and implementation and be on hand to answer questions that arise during the solution’s lifecycle. Handled correctly, the result can be efficient, accurate automated processes that free humans to turn their attention to higher-value tasks.