<img src="https://ws.zoominfo.com/pixel/jFk6PDgyyU2wBGPuZQTg" width="1" height="1" style="display: none;">

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

forrester governance

  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. 

Learn More: Forrester Report - Create a Governance Strategy to Meet the Process Imperative

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. 

Strategic positioning for RPA at scale 

Establishing an end-to-end organizational strategy for RPA is one of the keys to implementing RPA at scale. A recent report by HFS Research and KPMG found that a major factor impeding implementing RPA at scale is the absence of an enterprise-wide strategy. It’s also not just enough to have a clear, communicated, and transparent vision across the enterprise; the strategy itself must be in sync with the organization’s business objectives and strategic direction, ideally led by a C-level champion.   

Without an aligned and clear enterprise-wide vision, RPA efforts can become tactical and reliant on low-hanging fruit. The pilot project often closely resembles the full-scale implementation where the only identifiable difference is the slight increase in the number of simple, swivel-chair business processes being automated that deliver little return of value. Without an enterprise-wide strategy that is in-line with the organization’s larger business objectives, the complex, end-to-end business processes where the real ROI resides can never be automated.

To successfully strategically position RPA, a rudimentary recipe might look like the following:

  • Explicitly define how RPA contributes to the organization’s business objectives
  • Establish universal best practices
  • Set up an RPA Center of Excellence (CoE) to implement, govern, maintain, and scale RPA efforts across the enterprise
  • Gain buy-in from both the C-suite and enterprise employees

Why you need to gain executive buy-in if you want to achieve RPA at scale

Positioning RPA to your executives is so important because they’re the ones that need to sponsor it. The key here is to align RPA implementation with high-level business goals and objectives—explain how RPA contributes to the most common business objectives that all organizations strive for such as:

  • Increased customer satisfaction and engagement due to enhanced efficiency. For example, think of the positive operational impact automated processes have on processing customer requests during spikes in demand
  • More efficient and higher quality process execution saving thousands of hours of effort. Without human error, there is less rework necessary and bots execute processes with more efficiency leading to better quality.
  • Reinforced regulatory compliance. Bots that are aligned to and governed by regulatory compliant steps, strengthen compliance when compared to humans who regularly deviate from processes for several reasons.
  • Increased bandwidth for the organization’s talent to drive innovation and value because they can focus on higher-value tasks instead of completing mechanical and mundane processes

CIOs, here are Three Strategies to Help You Drive a Culture of Innovation Inside Your Automation Initiatives 

How to gain employee buy-in for RPA at scale

For employees, the positioning for RPA buy-in is just as important and a little sensitive because of the stigma associated with automation. While RPA does lead to reduced costs, the misconception is that it does so because it eliminates the need for human resources. That hasn’t been the case. In fact, job churn during a time when automation is booming is at an all-time low. RPA reduces costs because processes can be executed with greater accuracy and efficiency, bots run 24/7 without interruption, and employees spend less time on rework, therefore, reducing the cost of errors. 

The key to positioning RPA for employees is that you have to communicate how it will free them from having to complete repetitive, mechanical tasks and allow them to work on much more compelling and engaging work that delivers increased value to the business. For those that will be part of the automation initiative or RPA Center of Excellence, it’s a good idea to highlight how they will be equipped with new skills to support RPA which is only getting bigger and more important across all industries.

Changing company culture to achieve RPA at scale

To achieve RPA at scale, companies must have a culture that fosters innovation. We’re in a digital economy which means that every company is fundamentally a tech company or needs to be if they want to remain competitive. Regardless of whether the product or service being offered is not technical, the way the product or service is being provided, built, marketed to customers, and even managed is dependent on technical architecture.  Digital disruption is no longer a buzzword, it’s a reality, and more than ever it’s vital to adapt the company culture to embrace innovation, agility, and adaptability.

The way you frame technological change plays a central role; the benefits must be explicit for both the business and the employees. That’s why strategically positioning RPA and changing your company culture are so interconnected and co-dependent. A company culture that drives innovation is one that understands the benefits of innovation because the initiative has been positioned and aligned accordingly. The executives understand what it means for the business and the employees clearly understand what it means for them as professionals because a global vision was established and communicated.

Consider adopting the following best practices when trying to change your company’s culture to one that nurtures and encourages innovation and agility:

  1. Lead by example – As an executive, be the first to embrace new ideas, innovation, and change, which in turn encourages all others to follow your lead.
  2. Embrace new technology – The rate at which it evolves can be dizzying but disruptors often take their market shares because they’re willing and agile enough to embrace the cutting-edge technologies that give them an edge. RPA is an excellent example where numerous process mining, discovery, optimization, and orchestration providers are available that can be easily integrated into your current architecture.
  3. Communicate – Ensure everyone understands why new initiatives are being launched and reinforce how they tie into your organization’s objectives and goals. Be compelling and clear so it resonates and encourages buy-in from the top-down and end-to-end.

Monitoring and managing regulatory compliance in bots is critical for RPA at scale

All industries have important regulations that they must comply with and as organizations expand their automation efforts, many are realizing that compliance is a strong candidate. From an enterprise perspective, the realm of compliance involves adherence to laws, policies, and regulations that are designed to maintain data integrity, data security, and safeguard the privacy of both employees and customers. The processes to maintain these compliance standards are typically stable, rule-based, require structured inputs, manual, and repetitive in nature - the ideal scenario for any organization that is trying to achieve RPA at scale. Those who have implemented RPA are already reporting promising results, such as: 

  • Improvement in productivity between 40-50% for regulatory processes that are affected by RPA
  • Work availability changes dramatically as bots can be deployed quickly based on demand and work at all times 
  • Costs for a bot are typically 20-35% lower than that of a human 
  • Error is significantly reduced as bots follow exact scripts without deviation 

However, when organizations are in pursuit of RPA, they often focus more on the value of the technology rather than on what they’re going to automate and the risks that may be introduced in the process. Innovation is not without risk, but when you operate within a regulated industry it’s important to take a step back and determine how to effectively monitor and manage your bots. 

Before implementing RPA, consider the following four factors: 

  1. Involve IT from the get-go - In most cases, RPA is initiated by the business side because it’s a lightweight solution that doesn’t require a heavy technical background. However, to truly reap the benefits of RPA it must be scaled across the organization, and in cases like that, IT must be involved from the get-go. When in the pursuit of RPA adoption, organizations need to give sufficient consideration to the importance of strong IT general controls. It is critical to design appropriate security, change management, and IT operational controls to help mitigate the risks associated with unauthorized access to the bots, excessive access to the bots themselves, data loss, or data integrity issues. 
  2. Involve internal audit - Engage internal audit or other internal control teams from the starting line to help identify surface risks and ensure that proper governance and controls are established during the process design and discovery phase, prior to bot implementation. 
  3. Document, document, document - All your bots should be well documented during their design and development phases. This means a bot’s requirements, system access, designs, and actions should be thoroughly documented, versioned, and stored in a centralized space that can be accessed by team members whenever necessary. This is incredibly important because auditors will want to know if the bots actions match the actions of a person, including exceptions. Read More: What is a Digital Blueprint and Why Do You Need One?
  4. Verify outputs - Processing integrity is critical. Just because it does something properly once, does not mean you can set it and forget it. Compliance owners need to make sure the automated processes are completed effectively by monitoring logs and flagging unexpected processing activities or errors. 

Achieving RPA at scale by opening your Center of Excellence

One of the final steps to achieving RPA at scale are establishing your RPA Center of Excellence (CoE). An RPA CoE is a team that’s responsible for driving your RPA initiatives across your organization by consolidating and sharing RPA knowledge, governing RPA, identifying processes to automate, and working with all teams to identify RPA opportunities, deploying bots, maintaining them, and assessing and reporting on RPA.

Learn More: How to Break Down Automation Silos by Creating an Automation Command Center

At this point, it may be a good practice to identify the roles that will make up your RPA CoE, if not the actual team members that will fill those roles. At its most basic, an RPA Center of Excellence comprises of the following:

  • RPA Leader – Similar to a product owner, an RPA leader drives RPA strategy, execution, and overall RPA management while also being the initiative’s evangelist.
  • RPA Analyst – The main responsibility of the RPA analyst is to identify and assess RPA opportunities (that is, business processes that can be automated), optimize those processes for automation, and monitor the RPA initiative via reporting, providing updates to the RPA leader to present to executive sponsors and the organization where ROI is concerned.
  • RPA Developers – Developers are needed to actually develop, test, and then deploy the bots, in addition to providing maintenance and support for any defects, enhancements, or changes in regulations or policies that need to be reflected in the automated process.

The more sophisticated your RPA initiative becomes, the more roles you’ll want to add and employees to fill those roles.

Common Challenges Faced When Trying to Achieve RPA at Scale

Why do most Robotic Process Automation projects experience difficulties when trying to move beyond the Proof of Concept or Pilot phase? While most organizations are advised to start with automating the ‘low hanging fruit’ first, the truth is that it can create traps that will impede your ability to achieve RPA at scale. In fact, scaling RPA into the organizational structure is fundamentally different from implementing a conventional software product or other process automation. It’s critical to take a holistic change management approach that is focused on aligning, people, processes, and structures to the strategic business goals of the enterprise.

Organizational pitfalls

Organizations typically make a set of consistent choices on how to carry out organizational processes and how to achieve goals. These elements are interrelated and keep each other in balance when processes are carried out. As a result, a lightweight IT solution such as RPA doesn’t naturally fit into the organizational structure which could be a significant barrier to achieving RPA at scale.

To successfully scale RPA, organizations need to overcome two major risks caused by their current organizational structure:

Separation of business and unclear automation responsibilities

Traditionally, technology solutions are implemented and governed by IT stakeholders. However, because of the lightweight nature of RPA tools, it’s usually driven by the core operating business functions like HR, finance, or procurement. There is a common misconception that RPA does not require any involvement from the IT team, but this is far from true.

As organizations try and move beyond the pilot and achieve RPA at scale, the project requires IT knowledge for tasks such as hosting, governance, support, security, scalability, and assurance. But IT still needs business knowledge to identify the right processes, model these processes, and set the vision for the technology. 

But this means that achieving RPA at scale fundamentally contradicts the traditional organizational structure that separates the roles and responsibilities of business and IT groups. Scaling RPA will require new alignment mechanisms that redefine the roles and responsibilities of IT and business stakeholders.

Enterprise-wide approach and support 

Implementing a traditional IT solution requires an enterprise-wide approach because its use will affect many other organizational systems and processes. But as we’ve identified, RPA is a lightweight solution that can be initiated and configured by the business with limited involvement from IT. The absence of an enterprise-wide approach means organizations will run the risk of local, ad-hoc automation solutions where no end-to-end enhancements are achieved or even considered.

This means that as organizations attempt to achieve RPA at scale, they’re faced with the challenge of sorting through the web of bots and determining how each one fits within the enterprise. Scaling RPA will require that all stakeholders involved to agree to the benefits and uses before implementation to build organizational support and enhance operational effectiveness.

Because RPA is more of a lightweight and flexible solution, it’s easy to start by automating the ‘low hanging fruit’ within one operational department. But by purposefully selecting processes with a high potential for automation and low complexity, teams unknowingly buy into a false expectation that all future automation will perform the same way. And as the organization ramps up their use of RPA, they are executing on false pretenses because they have not determined if there is a demand for RPA in other departments or if it is truly a value add.

Without visibility into organizational departments and a deeper understanding of added value, organizations may face pushback from employees, and limited acceptance of RPA, hindering an enterprise-wide roll-out.

Discover Blueprint's Enterprise Automation Suite

Process pitfalls

One of the most common challenges that organizations face when trying to achieve RPA at scale is simply the rush to get started. As they rush to digitize their processes and automate them, many realize that implementing RPA is simple, but by no means easy. Many reach the same roadblock – what are the right processes for RPA and how do we optimize them?

There’s no doubt that this is an extremely important question to answer. In fact, some research suggests that a poor choice of processes during the initial pilot is the leading cause of project failure. And because we know that 30-50% of initial RPA projects fail, it’s vital for organizations to ask themselves:

  • What can we automate?
  • Does it make sense to automate?
  • How do we optimize?

To choose the right processes for automation, consider the following:

Choose processes that don't change frequently

Processes that change frequently aren’t good candidates for RPA. Because RPA usually interacts with user interfaces and minor changes to those interfaces add complexity to deployment which may even lead to a broken process. In addition, changes upstream and downstream, even during bot configuration, can significantly delay bots being put into production. A Forrester report noted that because of frequent changes, some organizations may not meet their expected ROI because of the added infrastructure and maintenance costs.

Always consider the business impact before you begin automation

Processes that have a low business impact are probably not worth the time and effort to automate. It’s important to consider processes within an enterprise context prior to development to determine the actual business impact it will have. Of course, you want to be able to say you were able to build 100 bots in less than a month, but if the proper analysis is not complete and if bots are not modeled and optimized from end-to-end, your 100 bots will end up costing you in hours of rework, errors, and general maintenance. In addition, without considering processes end-to-end, you’re more likely to build redundancy into your production environment. As a result, you’re likely diminishing the value of the bots built.

Learn More: Business Process Reengineering - It's Back and More Important than Ever

Consider if your technology will drive end-to-end automation

RPA is a generic solution. It’s only one part of a very complex system. You want to make sure that you have an integrated solution that is able to design, model, and optimize processes for large scale, end-to-end automation. Because most organizations have hundreds, if not thousands, of processes that beg for automation; defining, managing, and monitoring them with a single, generic RPA tool simply is not enough. Forrester recommends a mix of intelligent automation technologies to avoid common automation challenges and drive an effective and sustainable automation program.

Technical pitfalls

We’ve outlined many strategic recommendations on how to structure your RPA initiative and achieve RPA at scale, but what about the actual technical side of things? Below are some technical pitfalls that most people run into as they try and scale their RPA program: 

  • RPA Coding Standards and Principles: No matter which RPA vendor you are using, it’s critical that your development team is aligned on coding standards and principles to ensure everything is consistent and accurate across production.
  • RPA Programming Methods: When creating a TaskBot there are two key programming methods that are usually applied: User Interface and Background Programming. Before creating your structure and flow you need to determine which programming method will be applied. Keep in mind that selecting the most appropriate one will depend on the vendor you are using, it’s integration capabilities and your process environment.
  • RPA Business Continuity: The RPA development environment should provide a guaranteed source code repository that is always available and consistent in order to ensure business continuity throughout the RPA initiative.
  • RPA Code Control Framework: Having a Version Control System properly integrated into your RPA development environment will lead to consistency and high-quality deliverables, as well as remove any extra rework that would be required if one was not created.