Robotic Process Automation

The growth of robotic process automation (RPA) over the past few years has been nothing short of astounding. Even in the face of a global pandemic, spending on RPA software topped $1.5 billion in 2020 and is expected to jump nearly 20% in the year ahead, according to a recent report by Gartner.

On the face of it, RPA’s huge popularity makes perfect sense. Properly executed, RPA is able to automate a wide range of repetitive, rules-based processes, vastly reducing the time spent on routine tasks, as well as the potential for human error, which often accompanies such work. More importantly, RPA significantly improves productivity and drives innovation by freeing up employees to bring their creativity and problem-solving abilities to more meaningful work. That last benefit was particularly important over the past year when many employees were forced to work remotely due to COVID-19. While workers worldwide did their best to stay on the job while juggling work, Zoom calls and family from makeshift home offices, RPA kept everything from order processing and fulfillment to inventory and customer support rolling along, just as it had pre-pandemic.

Given that success, it is little wonder Deloitte has predicted RPA will hit almost universal business adoption in the next 2-3 years. Unfortunately, as the market has matured, cracks have begun to appear in the promise of RPA. Many of the companies that have implemented RPA are struggling to scale their automation initiatives, in large part due to the tremendous burden of maintaining the automations they have built to date. This has led to frustration over not only RPA downtime and the nearly constant automation break-fix cycles, but also the failure of chosen RPA vendors to deliver on the ease of automation execution that was promised when the sale was made.

There was also great hope that process discovery and task mining would yield higher quality, higher value automations. In large part, that has failed to materialize as recognition grows that most of the process discovery and process/task mining tools currently on the market simply aren’t ready for prime time. While all of these issues are concerning, they are unlikely to lead to a full-on retreat from RPA. Rather, there is a growing realization that achieving RPA success is not a trivial endeavor. If automations truly are going to live up to their full potential, businesses will need to undertake a back-to-basics approach of technology delivery.

For 2021, that translates into a step sideways for the RPA market. Adaptation of business automations undoubtedly will continue to accelerate as more and more companies recognize the critical role RPA has played, particularly in response to the pandemic. But while wider use may be a given, organizations will increasingly move to reevaluate the effectiveness of their entire automation delivery system, from planning to design to deployment. This will lead to a better understanding of those processes that simply don’t represent a good fit for RPA and subsequently a sharper focus on optimizing those processes that can best be improved through automation.

Shift to Intelligent Automation

As organizations direct more of their efforts to better planning and precise design, they are likely to put increased pressure on their RPA vendors to improve performance. Unfortunately, many of these vendors simply aren’t capable of handling the larger-scale needs their customers are now beginning to demand. This recognition will lead many companies to seek out alternate vendors who can actually deliver on RPA’s potential, although this is not a simple undertaking given the cost of switching RPA platforms and the challenges that arise due to lost credentials, missing audit logs, lack of code parity and more.

That won’t stop organizations from at least making the switch to new vendors or incorporating a platform migration solution. Only recently available, such solutions enable companies to switch from one RPA tool to another quickly, seamlessly and affordably, while adding value to their existing bot architecture. As these account migrations become more commonplace, the pendulum inevitably will swing from best-of-breed capabilities to consolidated platforms, just as it has done in every segment of IT tools. Given that likelihood, 2021 seems poised to see at least one IPO and one significant merger among the largest companies in the RPA market, with M&A (mergers and acquisitions) activity continuing to accelerate over the next 36 months. This ultimately will result in greater integration of the process and automation layers of RPA with each other and with complementary technologies like process mining and AI-fueled disciplines such as computer vision, machine learning and natural language processing.

While AI is still unlikely to be completely embraced in the year ahead – particularly given the other issues facing organizations already using RPA – automation tools that incorporate the cognitive capabilities of AI seem likely to replace those that don’t, ushering in a shift to intelligent automation. Blending the rules-based automation capabilities of RPA with the cognitive capabilities offered by AI and the trial-and-error learning capabilities of machine learning, intelligent automation can be used to create smart business processes and workflows that think, learn and adapt on their own.

By applying intelligent automation within enterprise operations, companies will be better positioned to increase efficiencies and gain new capabilities that go well beyond human abilities. Processing millions of documents daily, for example, while simultaneously identifying and resolving issues within each and making recommendations for improvement will suddenly become a possibility. Intelligent automation will also allow for one-of-a-kind, personalized customer interactions, leading to best-in-class customer experiences.

As the shift to RPA continues, it seems only logical to assume businesses in the forefront of RPA adoption will be among the first to realize the competitive benefits to be gained from taking the additional step into intelligent automation. Doing so will help them maintain their market edge over less tech-savvy competitors, while enabling them to leverage the learning algorithms and models contained in intelligent automation to fine-tune or even improve on task performance over time.

Introduction of Hyperautomation

Growing recognition of the greater value intelligent automation is able to bring to process automation at enterprise scale is likely to translate into increased investment in 2021. Broader interest and adaptation also has the potential to open the door for the introduction of yet another relatively new technology, hyperautomation. Defined as the extension of legacy business process automation beyond the confines of individual processes, hyperautomation merges AI tools with RPA and machine learning to enable organizations to automate virtually any repetitive task, including more complex and complete processes. It does this by implementing an end-to-end toolchain, essentially automating the automation by dynamically discovering businesses processes and then creating the bots needed to automate them.

By taking RPA to its logical conclusion, hyperautomation provides the means for real digital transformation to occur. It allows businesses to automate the integration, DevOps, monitoring and management processes that are compartmentalized by RPA into a single, more complete automated process. Doing so will boost efficiency and productivity on a larger scale than previously possible.

Intelligent automation and hyperautomation may represent the direction in which RPA is inevitably leading the business sector, but neither is likely to reach full potential or widespread industry use in 2021. While some adoption is certainly likely, most organizations will focus first and foremost on addressing the range of issues that contribute to break-fix cycles and the business value lost when bots are taken out of production. Dealing with RPA downtime will lead to many businesses establishing best practices in RPA and creating in-house centers of excellence, both of which will serve to standardize and better govern RPA.

Such measures will also better align RPA with the work being done by the organization’s IT team, establishing greater shared ownership of the automation function. Increasingly adding IT into the mix will bring an additional layer of technical expertise to the development and delivery of the company’s automations. IT will also be able to provide a better sense of the benefits and limitations of the current RPA. By eliminating the bottlenecks that inevitably arise from siloed ownership, organizations will be in a better position to identify RPA opportunities, capturing the process and optimizing it, while IT manages risk, ensuring that the automation is a viable solution.

These steps will create a synergy of expertise that streamlines automation from discovery to development for RPA to scale, all of which will yield the kind of ROI (return on investment) that originally was anticipated. ROI, in fact, will be the byword for 2021 as companies focus on maximizing RPA uptime and bot availability to capture all of the expected business value from their automations. If 2020 can be defined as the year of RPA adoption, it’s safe to say 2021 will be the year of looking to do RPA right, while keeping an eye on the next wave of automations that will allow RPA to reach its full potential.