The use of Robotic Process Automation (RPA) is expanding rapidly across industries, geographies, and organizational sizes, with organizations chasing benefits including cost reduction, operations optimization, improved customer experience, fewer errors, easier management and control, and quick implementation and ROI. That’s driving increasing RPA spending: Gartner projects spending on RPA software to hit $1.3 billion this year, and Forrester forecasts a $2.9 billion RPA software market in 2021.
While an organization can certainly implement RPA without a full-blown digital transformation program, most digital transformation programs would not really be possible without the inclusion of some intelligent automation capabilities.
[ What's the difference between RPA and AI? Read: Robotic Process Automation (RPA) vs. AI, explained. ]
An RPA software bot replicates the way a human would interact with an application or system and then automates that task. For many organizations, implementing RPA is one of the first (and most straightforward) approaches to automation in their digital transformation journeys. “The ROIs are very compelling and fast versus some other longer-termed technology change programs,” explains Chip Wagner, CEO of ISG Automation, the RPA division of global technology research and advisory firm ISG.
While many organizations may initially view RPA as a simple automation tool or a short-term fix, it can be the catalyst for greater change as part of a broader digital transformation strategy.
“Most RPA deployments emanate from the need to automate manual, repetitive operational tasks, creating the impression that RPA is most effective as a tactical band-aid to IT system inefficiencies,” says Siddhartha Sharad, director of IT and business services transformation advisory firm Pace Harmon. “However, organizations generate the most value from RPA deployments when integrated with other digital technologies such as AI, machine learning, smart workflow tools, and digital assistants to drive end-to-end digital transformation.”
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Examples of RPA use in digital transformation
“RPA can touch the back, middle, and front offices with dramatic reductions in cost, increases in speed, improved compliance, et cetera,” says Wagner. RPA can also relieve employees of their most mundane of their responsibilities, freeing them up to do more intellectually demanding work.
RPA is not on its own an intelligent solution. As Everest Group explains in its RPA primer, “RPA is a deterministic solution, the outcome of which is known; used mostly for transactional activities and standardized processes.” Some common RPA use cases include order processing, financial report generation, IT support, and data aggregation and reconciliation.
However, as organizations proceed along their digital transformation journeys, the fact that many RPA solutions are beginning to integrate cognitive capabilities increases their value proposition.
For example, RPA might be coupled with intelligent character recognition (ICR) and optical character recognition (OCR). Contact center RPA applications might incorporate natural language processing (NLP) and natural language generation (NLG) to enable chatbots.
“These are all elements of an intelligent automation continuum that allow a digital transformation,” Wagner says. “RPA is one piece of a lengthy continuum of intelligent automation technologies that, used together and in an integrated manner, can very dramatically change the operational cost and speed of an organization while also enhancing compliance and reducing costly errors.”
Indeed, RPA can be a critical part of the technology toolset available to enterprises to drive transformational change, according to Sharad. “RPA [can act] as the enabler for other digital technologies to function,” Sharad says.
[ Want resources for RPA training? Check out 8 Robotic Process Automation (RPA) training and certification courses. ]
6 factors to plan for: RPA as part of digital transformation
Part of the allure of RPA is the ease with which automation may be implemented. Top RPA providers offer some simple solutions designed to let someone with a few hours of training and limited or no development experience automate basic daily tasks. However, that’s the simplest flavor of RPA. As with any other aspect of digital transformation, IT leaders need a broader plan for RPA’s role. Issues to address include:
1. Strategic alignment
While setting up an RPA program, it is important to align program objectives with the overall DT strategy. “For example, if improving customer experience is a transformational focus for an enterprise, it is important to prioritize RPA opportunities that impact customer experience,” Sharad says. “Keeping the RPA program aligned with DT imperatives can help provide the appropriate executive focus and resources to scale.”
As RPA interest within the enterprise grows, IT leaders must plan for scaling these automation initiatives in the context of the digital transformation journey. “We have seen enterprises struggle with scaling. They tend to achieve early limited success with a few dozen bots, but struggle to get to the larger more impactful scale,” Wagner says. RPA and intelligent automation has been hyped as easy to scale, but it actually requires proper governance and a strategy for supporting large software bot fleets, according to Wagner.
3. System and process stability
RPA works best in a stable process and system environment. “Application changes can sometimes make the RPA deployment redundant,” Sharad says. “It is important that enterprises assess RPA’s viability in the context of their overall DT roadmap and avoid systems and processes that are going through significant near-term transformation.”
4. Organizational change management
Lack of proper change management planning and execution is one of the most common reasons RPA deployments fail. RPA and intelligent RPA can enable very new approaches to working for employees who have done their jobs a certain way for some time.
“This level of change can drive significant anxiety and confusion among employees, leading to resistance and, over time, weakened momentum,” Sharad says. “The successful sustainability and scale of RPA initiatives requires effective organizational change and cultural transformation management, with clear and transparent communications that drive employee awareness and adoption.”
5. Well-defined success metrics
It is critical to define the quantifiable benefits expected from an RPA deployment and measure and report achievement. “Without appropriate measures of success, enterprises stand the risk of creating false expectations and underwhelming stakeholders,” Sharad says.
6. Dedicated focus
RPA programs should not be an afterthought or an aside to digital transformation. “To ensure success, RPA initiatives require skilled resources, a robust governance model and controls framework, and well-defined deployment and production management processes,” Sharad says. “These capabilities take time, effort, and focus to develop and should be carefully accounted for while planning a digital transformation strategy.” A well-defined and disciplined RPA governance model with regular steering committee meetings is one way to ensure sustained support and focus.
[ Want to experiment with RPA without committing to one vendor just yet? Read also: Robotic Process Automation (RPA): 6 open source tools. ]
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