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Process transformation and automation are big priorities for CIOs. Deloitte's most recent global CIO survey found that IT executives named process transformation and automation as their top focus for digital transformation, with 69% of the 1,437 responding leaders listing it as a priority -- ahead of all other focus areas.
Meanwhile, Gartner reported that enterprise interest in process transformation is driving demand for robotic process automation (RPA) software, with revenue growing 63.1% in 2018 to $846 million. Gartner expects demand to push RPA software revenue to $1.3 billion in 2019.
RPA is just one of many process automation technologies that companies are implementing to drive organizational goals, from efficiency gains to digital transformation. The burgeoning automation sector encompasses numerous software options -- and corresponding acronyms from BPA to RPA to DPA -- with each promising to transform some part of the enterprise. Yet, the list of process automation technologies has also given rise to different interpretations and definitions, creating some disagreement and even confusion in the market about what exactly each one means and does.
RPA represents a significant portion of the automation market, as the Gartner statistics illustrate. Experts seem to agree that this class of technology is for targeted use, designed to automate repetitive tasks with its primary benefits being increased efficiency, lower costs and reduced errors -- all by replacing human efforts with bots.
"Bots communicate with business systems to streamline processes and reduce the burden on humans. But RPA doesn't inherently have any intelligence; a standalone RPA doesn't have [AI] or machine learning; it can mimic a human but it has no decision-making or judgment capabilities," explained Anurag Saxena, a partner for automation and cognitive at ISG, a technology research and advisory firm and IT service management company.
More specifically, RPA is about automating tasks to deliver tactical efficiencies, said Craig Le Clair, vice president and principal analyst at Forrester Research and author of Invisible Robots in the Quiet of the Night: How AI and Automation Will Restructure the Workforce.
Le Clair said business users are driving much of the RPA adoption, explaining that "it's very much bottom-up vs. top-down" with many business unit leaders employing outside consultants and IT service firms to implement RPA platforms and configure bots to the individual business' needs.
"It's a lot more business-driven than the other technologies," he added.
Forrester uses "digital process automation" as a replacement term for business process management (BPM) suites.
DPA is automating a process from end to end, Le Clair said, adding that DPA technologies are used for processes that are longer and more complex than the tasks that can be effectively handled by RPA. These processes typically contain multitudes of decisions that, if using RPA, would create bots that are too long and too difficult to maintain, he added.
"The DPA world is about transforming a process; it's about creating a new process," Le Clair said. "It has more of a broader end-to-end view of a process, and the assumption is that you'll be continuing to improve it over time."
In its March 2019 report, "RPA, DPA, BPM, And DCM Platforms: The Differences You Need To Know," Forrester relabeled BPM suites as DPA and further identified options as being either DPA-deep or DPA-wide (low code) platforms.
Forrester went on to describe DPA-deep as automation that transforms and improves a business process and because of the complexity, requires skilled technologists to implement and focus on continuous improvement.
On the other hand, Forrester described DPA-wide as aiming "to extend process design beyond small, highly skilled development groups to business users" and noted that these projects "should be managed by the business and delivered using low-code platforms and Agile methods."
RPA vs. BPA vs. DPA
Business process automation (BPA) is used by some experts as an umbrella term for the range of process automation technologies. However, there are different opinions on that term as well as others in the automation sphere.
For example, Gina Schaefer, intelligent automation lead at Deloitte Consulting LLP, said several terms -- DPA, BPA and RPA -- are practically interchangeable.
"Digital, business process and robotic process automation are essentially the same. When applied appropriately, these refer to comprehensive end-to-end process automation," she said. "Specifically, these terms refer to the use of scripted automation software to mimic human actions in the execution of rules-based 'swivel chair' type tasks, typically where an individual accesses and processes data from multiple applications."
Meanwhile, others define DPA similar to Forrester but add their own distinctions. Pegasystems, for example, announced on its site that "DPA is not another name for BPM, and it's more than RPA -- DPA is an end-to-end strategy for digital transformation."
Schaefer also offered another alternative definition for DPA, noting that it can refer to desktop process automation.
Similarly, there are variations with this process; some vendors using the term "desktop automation" apply it specifically to software robots that reside within an employee's individual computer where the bots perform specific tasks. Other vendors use robotic desktop automation, or RDA, to describe small-scale RPA for desktop applications.
Process automation technologies often rely on other technologies including natural language processing, which uses intelligence to interpret human language to move processes in the right direction, optical character recognition and intelligent character recognition to recognize written and printed text and transform it into standardized data that automation systems can use to run through processes.
Emerging technologies further expand the list of process automation technologies and the corresponding acronyms that CIOs must sort and parse. One such emerging technology to note is intelligence process automation (IPA).
Saxena said IPA represents an evolution of RPA where it is combined with intelligence such as machine learning and AI to make the automated process "smart."
McKinsey & Co. in its online piece on IPA described IPA as "an emerging set of new technologies that combines fundamental process redesign with [RPA] and machine learning."