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Updated by Charles Bystock on 05/05/2021

Spending on robotic process automation (RPA) increased by 57% in 2018 and is expected to reach $2.4 billion annually by 2022. It’s the latest trend in intelligent automation — and it’s just getting started. The core functionality of RPA seeks to automate multi-step high volume manual tasks. One of the challenges is that these are often done across multiple legacy platforms, which makes scaling any RPA process challenging. As organizations go from small applications of RPA within the enterprise to a growing reliance on these tools, new issues will emerge to challenge its usage. Currently, there is a lot of friction around RPA, how to use it, and how to scale. How can enterprise organizations redefine RPA to make better use of these tools?

 

Scaling RPA will be challenging

 

So far, we’ve applied RPA to single use cases within a department or existing workflows. The successes we’ve seen have been from pilot cases. The next phase is to take what we’ve learned and scale it, but doing so won’t be easy. Right now, organizations are trying to figure out how to take their initial use cases and apply them consistently. The problem is that RPA impacts more than the legacy patchwork of applications found in most enterprise organizations — RPA also impacts human workflows. If we don’t deploy RPA well, these tools will create more work than they will save.

 

Tech Beacon says, “An RPA solution needs to be resilient enough to withstand the changes to the applications you’re automating.” This requires a process discovery system that unites an organization, specifically:

 

  • Carefully evaluating and vetting the organizational areas
  • Weeding out any less applicable use cases
  • Road mapping tasks related to the application of the RPA within specific organizational areas
  • Following applied RPA processes with metrics on utilization rates

 

To scale RPA requires a crystal ball approach. Carefully selecting the workflow to automate isn’t enough. Organizations must also be able to see how these technology upgrades affect the people around the tool, then envision how the RPA application can scale.

 

Scaling RPA

 

RPA governance should be top of mind

To scale RPA, someone needs to own it — but not necessarily IT, who should stay focused on deploying RPA rather than seeking stakeholder buy-in. Also, because RPA is meant to be applied cross-functionally, the key stakeholder should include input from cross-functional teams. The goal is to develop an RPA process team that can review RPA use cases from a process mapping perspective.

 

The goal of RPA governance should be to develop a sponsor or champion to own the initiative. Like any functioning group, it should have documented policies, goals, and roles. Each iterative process the committee undertakes should be measured and improved. Each RPA deployment should be tied to business values with a defined ROI. The governance structure should include:

 

  • Solutions architects and/or developers as the technical implementation resources
  • Change managers/project managers to keep human and technical processes moving smoothly
  • Business analysts to analyze specific RPA use cases
  • Department representation/managers, who work on the front lines within departments where RPA is deployed

 

Ultimately, the goal of this governance team should be to do more than just deploy RPA, but also to capture best practice use cases to ensure the technology is more scalable across the enterprise.

 

Data privacy

 

Data privacy (and security) will emerge as an RPA issue

 

Customer data privacy and IT security, in general, are emerging as big issues within RPA. RPA is often deployed to capture delicate customer details, such as the application process for a loan. Traditional data mining processes are often housed at the back of the enterprise, with information flowing between ERP applications. RPA occurs at the user interface level, which increases the potential for data leaks. This necessitates analysis of RPA deployments by use case and within the framework of both customer privacy and cybersecurity. This approach will further complicate the scalability of RPA, but the alternative is unthinkable.

Digging deeply into the RPA process will create uncomfortable moments in many organizations because ultimately, RPA is as equally a change management tool as it is automation tech. It will uncover redundant processes and organizational dysfunction at a very human level. However, this is necessary and important work for enterprise organizations seeking process improvement and competitive advantage. In these efforts, it’s often best to seek the expert outside counsel of a firm like the Windsor Group. We help organizations conduct process improvement and change management. Start the conversation with our firm to keep your organization moving forward.