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:
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:
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:
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:
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.
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:
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:
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:
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.
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:
The more sophisticated your RPA initiative becomes, the more roles you’ll want to add and employees to fill those roles.
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.
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:
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.
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.
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:
To choose the right processes for automation, consider the following:
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.
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.
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.
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: