How Robotic Process Automation (RPA) and digital transformation work together
The use of Robotic Process Automation (RPA) is increasing rapidly in various industries, regions and company sizes. Companies pursue benefits such as cost reduction, operational optimization, improved customer experience, fewer errors, easier management and control, and rapid implementation and ROI. This is driving RPA spending soaring: Gartner predicts RPA software spending will reach $ 1.3 billion this year, and Forrester predicts an RPA software market of $ 2.9 billion in 2021.
While a company can certainly implement RPA without a comprehensive digital transformation program, most digital transformation programs would not really be possible without the inclusion of some intelligent automation features.
An RPA software bot replicates the way a human would interact with an application or system, and then automates that task. For many companies, implementing RPA is one of the first (and easiest) approaches to automation in their digital transformation journeys. “The ROIs are very compelling and fast compared to some other longer-term technology change programs,” said Chip Wagner, CEO of ISG Automation, the RPA division of global technology research and consulting firm ISG.
“Most RPA deployments result from the need to automate manual, repetitive operational tasks, which gives the impression that RPA is most effective as a tactical aid to inefficiencies in IT systems,” says Siddhartha Sharad, director of the consulting firm for the IT and business services transformation Pace Harmon. “However, companies get the most value from RPA deployments when they are integrated with other digital technologies such as AI, machine learning, intelligent workflow tools, and digital assistants to drive end-to-end digital transformation.”
Examples of the use of RPA in digital transformation
“RPA can affect the back, middle and front office with drastic cost reductions, speed increases, improved compliance, etc.,” says Wagner. RPA can also relieve employees of their most day-to-day responsibilities and free them up for more intellectually demanding work.
Many RPA solutions are starting to incorporate cognitive skills, increasing their value proposition.
RPA on its own is not a smart solution. As the Everest Group explains in its RPA primer: “RPA is a deterministic solution, the result of which is known. Mainly used for transactional activities and standardized processes. “Some common RPA use cases include order fulfillment, financial reporting, IT support, and data aggregation and reconciliation.
As companies continue their digital transformation journeys, the fact that many RPA solutions are beginning to incorporate cognitive skills increases their value proposition.
For example, RPA could be coupled with intelligent character recognition (ICR) and optical character recognition (OCR). Contact center RPA applications can include natural language processing (NLP) and natural language generation (NLG) to enable chatbots.
“These are all elements of an intelligent automation continuum that enable digital transformation,” says Wagner. “RPA is part of a long continuum of intelligent automation technologies that, together and in an integrated manner, can dramatically change the cost of ownership and speed of an organization while improving compliance and reducing costly errors.”
According to Sharad, RPA can be an important part of the technology tool set available to organizations to drive change. “RPA [can act] as a trailblazer for other digital technologies to work, ”says Sharad.
6 factors to plan: RPA as part of the digital transformation
Part of what makes RPA so fascinating is the ease with which automation can be implemented. Top RPA providers offer some simple solutions that someone with a few hours of training and limited or no development experience can use to automate basic daily tasks. However, this is the simplest taste of RPA. As with any other aspect of digital transformation, IT leaders need a broader plan for the role of RPA. Problems to be addressed include:
1. Strategic direction
When setting up an RPA program, it is important to align the program objectives with the overall DT strategy. “For example, if improving the customer experience is a transformation focus for a company, it’s important to prioritize RPA opportunities that affect the customer experience,” says Sharad. “By aligning the RPA program with DT requirements, you can provide the appropriate focus and resources to scale executives.”
“We have seen that companies struggle with scaling. With a few dozen bots, they usually achieve limited success early on.”
As interest in RPA grows within the company, IT managers need to plan to scale these automation initiatives as part of the digital transformation. “We saw that companies struggle with scaling. You tend to have limited early success with a few dozen bots, but struggle to reach the larger, more impactful scale, ”says Wagner. RPA and intelligent automation were rated as easy to scale, but they require proper governance and a strategy to support 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 eliminate the need for RPA deployment,” says Sharad. “It is important that companies evaluate the profitability of RPA in the context of their overall DT roadmap and avoid systems and processes that change significantly in the short term.”
4. Organizational change management
The lack of proper change management planning and execution is one of the most common reasons RPA deployments fail. RPA and intelligent RPA can open up very new approaches to the work of employees who have been doing their job a certain way for a while.
“This level of change can create significant anxiety and confusion in employees, leading to resistance and a slowdown in momentum over time,” says Sharad. “Successful sustainability and the extent of RPA initiatives require effective management of organizational change and cultural transformation with clear and transparent communication that promotes employee awareness and acceptance.”
5. Well-defined success metrics
It is important to define the quantifiable benefits of an RPA deployment and to measure and report performance. “Without suitable measures of success, companies run the risk of creating false expectations and overwhelming stakeholders,” says Sharad.
6. Dedicated focus
RPA programs shouldn’t be an afterthought or side effect of digital transformation. “To ensure success, RPA initiatives require skilled resources, a robust governance model and control framework, and well-defined delivery and production management processes,” says Sharad. “Developing these functions takes time, effort, and focus and should be carefully considered when planning a digital transformation strategy.” A well-defined and disciplined RPA governance model with regular steering committee meetings is one way of sustained support and focus to ensure.