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Best Practices for Achieving RPA at Scale

Explore best practices to achieve RPA at scale and strategies to avoid common challenges that organizations face as they transform.

Best Practices for Achieving RPA at Scale

Once companies have successfully implemented RPA and automated a handful of processes, they realize that to achieve the full benefit and ROI of automation, they need to achieve RPA at scale. When we say “scaling,” we mean going beyond those swivel-chair tasks and automating those complex, multi-layered processes that an RPA tool alone cannot do. This means looking at business processes from end-to-end and understanding how it interacts with other departments, applications, and legacy systems. By looking at your business processes within the context of the enterprise, not only will it be easier to scale, but it will also be easier to recognize the full value of RPA. 

Three best practice to achieve RPA at Scale:

  1. Optimizing processes before automating them — To achieve RPA at scale, first, you must understand how your business operates. By reviewing the current state of your business processes, organizations will be able to eliminate waste, simplify processes, and optimize them for automation. Reengineering your business processes before any automation work begins helps you build bots that are effective, resilient, accurate, and scalable within your enterprise

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  1. Consider process mining tools to improve your existing processes — Process mining tools are essentially data mining tools that identify patterns in event log data. They allow organizations to thoroughly map out their processes and potentially discover opportunities for automation that were previously never considered. They also allow organizations to accurately identify the business processes being executed. In a recent report on the state of RPA published by Abbyy, 60% of organizations stated they frequently deviate from their business processes to meet customer needs, meaning that even the most well-defined and mapped-out process isn’t the one that’s always being executed.
  2. Invest in your RPA toolchain — Let’s be honest, to achieve RPA at scale an RPA tool alone won't be enough, you need a tool that will capture your current-state and a tool to help you optimize and According to Forrester, adopting multiple complementary technologies that each serve a discrete purpose and easily integrates with your existing enterprise architecture is necessary to achieve enterprise-scale RPA. When you invest in dedicated tools with a dedicated purpose, you’re able to accurately identify and define RPA opportunities to see the flow of value more clearly, understand areas for optimization, and make better business decisions. Multiple tools that serve a specific yet essential purpose also makes it easier to govern processes and reduce maintenance costs. As a simple framework, consider tools that cover a broad spectrum of processes within an enterprise: a tool for process mining, one for process discovery, another to optimize your processes to be automated that provides context and visibility to all stakeholders, and lastly, a platform to orchestrate and monitor all your bots in production. 

Business and IT alignment is necessary to achieve RPA at scale

Digital disruption is continuously challenging organizations to reimagine their business processes, customer communication, and service delivery. To keep up with the changing demands of the marketplace, companies are looking to automation. However, to achieve RPA at scale across the enterprise organizations must not only address changes in technology, but also the changes in people, tasks, and structure. 

In many cases, RPA projects are initiated and configured by the business with limited involvement from IT during the Proof of Concept phase. The lack of alignment between both groups can lead to frustration, insecurity, and a skeptical view on the new technology and its adherence to security and compliance requirements as organizations look to scale across the enterprise. 

To achieve RPA at scale, business and IT alignment are absolutely critical. Some organizations have begun decentralizing IT and shifting it closer to end-users, melding the knowledge-base to the business strategy. By having the business sit closer to IT the value of RPA can be communicated more clearly to the organization, therefore it will be easier to get acceptance from the rest of the organization. But, achieving business-IT alignment is not easy, it requires a strategy that works to change the culture of both groups. 

To align business and IT, consider these best practices: 

  • Change your thinking, change your doing: Most companies are siloed, so business teams rarely work with IT. Instead, think of all your business units, including IT, as a strategic and continuous loop. Changing your thinking means teams will work closely together, function better, and understand the needs of RPA better. This will increase efficiency, reduce risk, and enable future engagement. 
  • View IT as an instrument for business transformation: Because most organizations start their RPA transformation with limited involvement from IT, this is a critical point that needs to be emphasized. If you want to achieve the full benefits of RPA, it needs to be scaled, and IT must be involved. Integrate IT teams with business teams so that everyone can learn from one another and understand the full value of automation from end-to-end. 
  • Make the customer experience the #1 factor: Every single business unit, person, and the task should be about improving the customer experience. Aligning everyone under one common goal will make it incredibly clear what the strategy should be for implementing RPA and improving the customer experience. In addition, alignment around a specific goal can help break down silos between the business and IT teams, further enabling collaboration. 
  • Use a single language: The key to strong alignment is communication, so it’s important that both teams understand each other and that a single language is being used throughout the planning, design, and development phases.