As technology continues to advance, robotic process automation (RPA) has become a critical enterprise automation fabric technology. RPA products and ecosystems have evolved significantly over the years, with enterprises trying to build stable, scaled RPA programs that can help deliver the autonomous enterprises of the future. However, to achieve the desired success from RPA initiatives, automation leaders must take into account Forrester’s 10 golden rules of RPA success, which are presented in this report.
The first golden rule of RPA success is to weave RPA into a company’s automation fabric. RPA is no longer a lonely island in the sea of automation, and it should be approached as a steppingstone to building an automation fabric for end-to-end process automation across the enterprise.
The second rule emphasizes the need to build a sustainable business value model for RPA. It is crucial to structure a robust and repeatable business case for every candidate automation to neither overstate the potential value nor underestimate the costs involved.
The third rule stresses the importance of treating RPA as an enterprise platform. Technology and business teams are excited about the ease of deployment and clear value that RPA promises, but they must avoid the temptation of cutting corners early.
The fourth rule highlights the need to secure bots with zero-trust principles. Bots should be treated as digital workers, and formal policies should be established to identify and authenticate them as nonperson users and monitor their access rights.
The fifth rule recommends prioritizing processes when embarking on an RPA program. Technology teams should take a pipeline view of processes and build pipelines of candidate processes with intake, assessment, and prioritization for up to 12 to 18 months ahead, led by a center of excellence or strike team.
The sixth rule emphasizes laying early foundations for effective automation management and governance. Establishing repeatable methods for identification, prioritization, and pipeline management for processes to be automated is more important than merely getting processes automated.
The seventh rule emphasizes the need to plan for AI but not rush in. RPA is a deterministic technology, whereas AI deals with probabilities. Embedding ML into RPA-based workflows greatly increases the surface area of automatable tasks and processes, but with this great power comes even greater responsibility.
The eighth rule recommends taking an innovation view of intelligent automation. As programs scale and confidence in RPA grows, it can play a critical role in innovation.
The ninth rule recommends designing for humans. Human insight, labor, and support are often required to plan for, scope, deploy, and stabilize automations.
The tenth and final rule emphasizes fostering an automation-first culture. Organizations must pivot to thinking of automation as the primary model for all kinds of work to succeed with automation.
RPA has come a long way since its inception and has become a critical enterprise automation fabric technology. To deliver scale, value, and resilience through RPA, automation leaders must take into account Forrester’s 10 golden rules of RPA success. By doing so, organizations can future-proof their RPA initiatives and achieve the desired success from their automation programs.