For enterprises on the path of digital transformation, robotic process automation (RPA) is often the first choice to automate critical processes and extend the life of legacy systems. In fact, Gartner notes that RPA is the fastest-growing enterprise software category.
While the adoption of the technology is gaining momentum, scaling the initiative has become a major challenge that is limiting the benefits of the technology. Most RPA implementations pilot with a low-hanging opportunity within a single business unit. While this is a great approach to foster confidence and gaining sponsor buy-in, enterprises won’t be able to reap full benefits without tapping into processes that bring the maximum value. As Phil Fersht from Horses for Sources puts it, “The reality of moving into an automation arbitrage environment is that you can’t just replicate that work into an even cheaper robotic environment without really figuring out how to do this effectively.”
RPA Is Not A Set-it-and-forget-it Program
One of the common reasons why RPA fails to scale across the enterprise is not having complete insights into how their processes work and evolve. Real-world processes vary from the documented processes. Variations and exceptions creep in overtime. If these variations are not identified and addressed in time, bots break and fail to deliver the promised benefits.
On average, 87 percent of enterprises deal with some level of bot failure, only 39 percent of bots get deployed on time, and 50 percent of bot implementations are harder than expected. These challenges impede enterprise-scale RPA implementation, instead, they become short-term, band-aid fixes that turn costly and inefficient in the long run.
Three Ways to Achieve Enterprise-scale RPA
When we say “scale RPA to enterprise-level”, we mean going beyond piece-meal, swivel-chair tasks and automating complex, end-to-end processes that span several departments, applications, and legacy systems. Use the following 3 approaches to get a comprehensive picture of your “AS-IS” processes to identify the best automation opportunities.
- Leverage continuous discovery to optimize automation: Process discovery tools like SurfaceInsight’s surfaceAI help you to understand and review your current state of business processes to identify which processes need to be standardized, automated, or eliminated. Adopt continuous discovery to spot process improvement opportunities every few months, and update bots to be resilient and effective.
2. Invest in the right tools: Today you see a plethora of process discovery and automation tools in the market. You need to be cognizant of your unique business requirements to evaluate and choose only the best tool for your enterprise. Choosing an automated process discovery tool helps you visualize and document processes quickly. This documentation can be pulled into your RPA tool to expedite the automation process.
3. Align business and IT teams: Achieving RPA at scale across an enterprise requires addressing changes in both technology and people. Most of the time, RPA projects are initiated by the business teams and IT teams are engaged only during the Proof-of-Concept phase. This lack of alignment from early in the process can lead to frictions when it comes to enterprise-wide scaling. For instance, IT could push back because they are skeptical about security and compliance requirements. Viewing IT as an important part of a business transformation program enables quicker adoption.
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