It’s nearly impossible to talk about the future of robotic process automation (RPA) without talking about the future of automation as a whole and, by proxy, the future of our workforce entirely.
Before we dive into the future of RPA, let’s level-set on its history and current state: RPA has existed since the early 2000s, has been part of the common tech lexicon for at least a decade, and is currently enabled in at least small, siloed instances at most large organizations. Even in limited implementations, current iterations of RPA increase efficiency, effectiveness and agility in business processes by automating high-volume, repetitive activities where human effort does not add business value.
Today’s modern automation drives organizational success by supporting overall digital transformation objectives and business efficiency. According to Frost & Sullivan, there is a positive correlation between the intensity of RPA and the profitability of an organization. By automating repetitive busywork, employees are free to spend their time on creative or customer-facing work and efforts that drive innovation, customer experience and revenue.
According to the Deloitte Global RPA Survey, 2018, RPA can improve workforce productivity by 86%, improve quality and accuracy by 90% and improve compliance by 92%.
By all measures, RPA implementation at any level is a net positive for an organization, if the application is a good fit for the technology. And as other automation-enabling technologies, like artificial intelligence and machine learning, gain sophistication and speed, usage and ROI of RPA will accelerate in tandem.
Currently, robotic process automation is something of a misnomer. RPA actually automates tasks within a process that can then be connected for a sum total of end-to-end process automation. But to be a good fit for today’s RPA, those individual tasks to be connected should:
- Follow the same repetitive, rule-based pattern every time
- Take up a large amount of employee time (but not necessarily brainpower)
- Rely on template-based information acquisition
- Be easily repeatable and controllable
Essentially, today’s automation requires a detailed understanding of the labor-intensive business process before that process can be automated. The people implementing RPA must identify the most time-consuming, repetitive, bottleneck-causing tasks in their operations and introduce them to the technology before it can then learn, replicate and automate the tasks.
That means RPA has limits: it cannot anticipate or automate any activities that a human was not previously conducting manually.
Does that make RPA a less valuable investment? Of course not!
Imagine RPA as a calculator when you’re faced with a difficult, multistep algebra problem.
The automation of the calculations (via the calculator tool) makes it much more likely that you’ll get the right answer, and you’ll get there with much less stress and time commitment. However, effective use of the tool still requires that you know all the correct variables to input and the order of operations in which to address them.
RPA is similar. In the future, however, advancements in RPA will mean it can identify and improve processes within — and across — your systems without human intervention. That means your organization will be able to do more than automate processes: It will be able to get in front of them entirely.
Automation and the technology that facilitates it move quickly. For those who make smart decisions early, this quick advancement is an advantage that allows for agility years into the future.
Think back to how organizations viewed the cloud less than a decade ago. The decision to move business-critical information to the cloud was seen as “bleeding edge” and inherently risky. After all, how could you trust the security and longevity of information when you didn’t have on-premise control?
Now, however, in an era of dispersed workforces and globalization, the cloud is synonymous with information management and organizational resilience. Those early adopters of cloud-based practices were better situated to adapt to changes brought by time and circumstance (i.e., the pandemic).
Comparably, RPA will soon become synonymous with process management. Every business process will be scrutinized through the lens of automation: How can we make today’s processes more efficient, more effective, less risky?
What will determine RPA’s effective evolution?
A key component of RPA’s evolution is the integration of the tool into an organization’s content universe.
Already, RPA as a stand-alone product is beginning to show its limitations in application. That means pure-play RPA platforms (those that offer only RPA as a product) are not the best choice for most organizations.
Leading analysts predict RPA will soon be commoditized as a productivity enhancement tool. Key differentiation factors will revolve around how the RPA tool can function in tandem with intelligent enterprise automation — a collection of integrated technologies that may include intelligent capture, artificial intelligence, machine learning, case management, workflow, low-code capabilities and cloud-based content services.
As these other tools become smarter alongside RPA, it makes less sense to invest in a pure-play RPA platform and instead invest in one that natively integrates with the other capabilities that bring the most value and drive the highest, quickest ROI.
RPA technology alone can analyze, build, run and manage your identified business processes, and it will continue to be a crucial component. But, RPA will be just one of many components in a broader intelligent automation strategy.
After all, RPA automates tasks within processes — it’s up to humans or other technology to identify those processes, tightly integrate them with other tools and systems to address business problems, analyze cross-system data and make strategic decisions.
Organizational takeaway: To capitalize on their digital transformations, organizations should build a tactical automation strategy and implement integrated solutions that address their business problems, increase efficiency and consistency and allow them to achieve performance goals.
Undergoing an automation paradigm switch
The future of RPA is not the North Star — it won’t guide every organization toward enterprise automation. Instead, consider RPA part of a constellation. As RPA and other automation technologies continue to advance, their paths and use cases will converge into industry-specific solution configurations that drive unique operational goals.
This means your automation strategy should be driven by your business initiatives and your customer expectations, not by capitalizing on what the technology is currently capable of.
For example, when an organization implements a modern platform run by a future-focused technology provider, it can set lofty, shoot-for-the-stars goals and trust that the solutions will be there to support those goals, rather than worrying about what’s possible with the technology available today.
“Traditionally, automation projects have been driven by technology advances,” says Alan Pelz-Sharpe, founder of Deep Analysis, a technology analyst firm. “Today, however, automation projects are increasingly being driven by a more considered, holistic and intelligent mindset that starts with the business challenges to be resolved rather than the technology.”
In the Forrester guide Is Your Tech Ready for Customer Obsession?, the research and advisory firm advises organizations to “invest in technology innovation chains,” which it defines as “a series of related technologies that build upon one another synergistically to create breakthrough opportunities.”
Organizational takeaway: The future of automation is being driven by the intelligent application of intelligent processes. Your organization needs a broad suite of intelligent automation tools, including RPA, available to support its goals, strategies and initiatives, however they evolve.
“The focus of any automation project should be on doing business better, not on doing business with as few human beings as possible.” – Deep Analysis
For more than a century, a robotic workforce has been a cornerstone of every imagined future. Depending on the social, political and economic climate, the idea resurfaces again and again either as an exaggerated, imaginative trope or as a legitimate underlying fear.
Research has shown that people with an annual household income of $25,000 or less had 856% higher odds to perceive automation as a threat to their jobs compared to those with an annual household income between $60,000 and $120,000.
Assuming that lower-income households are more likely to have a full-time earner working in manual labor, this varied trust (or lack thereof) in automation makes sense. After all, the fundamental purpose of automation is to accomplish the same or greater output through a reduced volume of work activities for humans, and repetitive manual tasks, like those performed by some blue-collar workers, have often been portrayed as the easiest to automate.
But in reality, the line between blue-collar and white-collar automation and job redundancy is not so clear.
Blue-collar vs. white-collar vs. automation
Automation often generates negative feelings, but the case against it is more about perception than numbers. The World Economic Forum, for example, noted in its Future of Jobs Report, 2020, that by 2025, emerging technologies will create 12 million more jobs than it displaces.
Blue-collar workers in particular are thought to be vulnerable to displacement by industrial robots and automation. But in fact, these workers have been hard for employers to find, and according to CNBC, blue-collar and manual services wages have trended upward for the past several years — growing at a faster rate than white-collar jobs. While automation has and will impact these workers, there are, and will continue to be, jobs for skilled blue-collar workers.
For white-collar workers, the future is perhaps less stable than pop culture has often indicated. Many white-collar, computer-based tasks in accounting, reporting, payables and analytics functions automate more easily than those reliant on more physical labor (it’s logistically more feasible for tiny computer bots to function flawlessly inside a technology system than big, human-sized robots doing large motor skill tasks in the real world).
These white-collar automation capabilities may results in less need for headcount in those computer-based functions. For white-collar workers who retain their jobs, the automation of their repetitive work allows them to focus on higher-value, more engaging work. For employees who have seen their responsibilities automated, the experience has largely been positive, especially in automation categories that reduce risk and physical exertion, such as materials movement and physical work areas.
The positive case for automation
Plus, trends have shown that for every one job replaced by automation, two more open in its place. Just as RPA automates some tasks in a process, not entire processes in a workflow, RPA is likely to automate some responsibilities in a role, not entire roles in an organization.
A survey by Hyland and YouGov found 58% of office workers said they spend too much time on rote, repetitive tasks, with 36% reporting they would rather spend time on creative work and 28% wishing to dedicate their time to customers. Automation can make this shift toward knowledge work possible, as creativity and customer experience are two areas in which robots are still lacking.
There’s a lot at play regarding automation and the workforce of the future. Technology will continue to change how we work, yes, but overwhelmingly for the better. When RPA and related automation technologies are used at their best, the automation projects augment the work of humans rather than replacing it.
So what’s next on the docket for modern RPA innovation?
- Attended automation: While unattended RPA — where bots work in the background with no human intervention — seems higher-tech on the surface, attended RPA — also known as Robotic Desktop Automation (RDA), where the bot serves as a digital assistant to a front-office employee by accelerating task completion — is more difficult to get right. It’s attended RPA that is likely to drive more substantial improvement in customer experience. For example, an attended bot can be deployed to handle data entry or document retrieval for a customer service rep during a support call.
- Unstructured and semistructured data: Leveraging intelligent data capture and AI capabilities, RPA will be able to recognize, categorize and correctly handle data that is less structured and template-based than is required today.
- Self-healing bots: Like any other technology, RPA is not immune to bugs. As more processes are automated, more oversight and maintenance will be required to keep them running smoothly. Today, any errors in an RPA process must be recognized, identified and fixed by humans. In the future, self-healing RPA bots will be able to scan automated process sequences for errors and right themselves, lessening that need for human oversight.
- Process mining: Process mining as a capability is fully functional today, but it will continue to get more sophisticated and integrated into the future of RPA. Bots will be able to discover opportunities for RPA to automate tasks and processes, extending efficiency, effectiveness and agility beyond what organizations may have considered.
- Extended business process management (BPM): As RPA becomes more integrated with intelligent automation suites and that automation is applied more broadly than it is today, it will be able to securely automate processes not only across systems and functional teams, but between external partner ecosystems.
- Hyperautomation enablement: Hyperautomation, defined by Gartner as “a business-driven approach to identify, vet and automate as many business and IT processes as possible,” is a 2022 buzzword, and for good reason. For hyperautomation to hit the mainstream, it requires “orchestrated use of multiple technologies, tools and platforms, including RPA, low-code platforms and process mining tools.”
Choosing an RPA provider in 2022 should be about more than the ROI it will drive immediately. It should be a thoughtful decision that considers your organization’s business goals, automation strategy and how the tool will scale and integrate to continue proving its value far into the future.
Frost & Sullivan recommends factoring the following into your RPA decision:
- Usability of the general interface, automation designer and administration panel
- Integration with other relevant cloud- and web-based systems, apps and repositories, including cloud and web-based
- Agility that allows easy changes to automations when business requirements change
- Flexibility in deploying RPA to different areas of business
Because of how tightly the future of RPA is entwined with the future of your workforce as a whole, it’s also smart to consider partnering with a provider whose expertise goes beyond RPA. An innovative, intelligent suite of products and capabilities will support your entire enterprise automation strategy in the future and make your objectives more achievable, no matter how they evolve. A customer-focused partner will understand that different organizations require different combinations and configurations of tools and technologies to reach their goals.
Look for an RPA partner that:
- Focuses on your key business objectives, including efficiency, effectiveness and agility
- Enables automation at scale by integrating and co-creating with existing solution providers
- Considers its (and your) longer-term automation strategy
- Improves your customer facing capabilities
- Increase the quality and speed of your decision-making
- Expands your capacity to handle transactions, customers, product releases or other services
This article originally appeared on Hyland.com. Inpute are proud to be a partner of Hyland.