Just as a civil society relies on the rule of law, robotic process automation (RPA) at scale requires good governance to enable success while helping to mitigate associated risks. In this post, the first of two highlighting key points from our recent RPA webcast, we look at some elements of good RPA governance.
Governance – the establishment of polices, and the implementation and monitoring of those policies under a governing body – is a foundational component of any RPA program. RPA program governance is not unlike the governance of other technologies, in that it requires a clear strategy, effective risk management, discipline and commitment, good documentation and information sharing, and regular self-evaluation.
Some signs an organization might lack good RPA governance include:
- Lack of a sponsor/champion
- Poorly documented or non-existent policies
- Poorly defined roles
- Knowledge not captured and shared
Let’s break that down, starting with the role of champions. Although it is generally understood that projects such as an RPA rollout require an executive sponsor, it is equally important to have strong support across the organization. Ultimately, it will be the regional and business unit champions who have the most direct influence on how the program is implemented and sustained at the operational level.
Champions are a part of cross-functional operating teams, or Centers of Excellence, that help promote project goals, monitor program performance, and serve as resources to the business units. These teams don’t have to reside within IT, but they need to partner with IT to ensure proper system access and support.
Operating teams should be guided by clearly defined policies, or rules, establishing how and why RPA will be implemented, including a value proposition requiring business units to articulate their program objectives and quantify the expected return on their RPA investment.
Members of operating teams should have clearly defined roles. In addition to the executive sponsor and regional or business unit champions, important roles include:
- Infrastructure engineers and solution architects – Typically centrally located, these technical resources understand how all the systems work and design the automation so that it is done in an intelligent and efficient manner. Solution architects define the architecture of an RPA solution and hand off their work to infrastructure engineers who install infrastructure components supporting the RPA solution and help to troubleshoot them once the solution becomes operational.
- Developers and project managers – Also centrally located, these are the implementers who put ideas into action. Project managers oversee the development and implementation process and work with developers to design, develop and test bots.
- Change managers – Change managers serve as gatekeepers to coordinate and manage changes to avoid confusion and redundancy, but also to capture and share knowledge. They are responsible for creating a change and communication plan in order to ease RPA adoption in the organization.
- Business analysts– These are process subject-matter experts who act as intermediaries and work with the business units to document processes and transfer that knowledge to the solution development team. They are also in charge of making sure that the solutions created by the developers meet business needs.
- Supervisors and support services – This is the front line in RPA, supervising and servicing bots once they become operational.
Once the organization has identified what it wants to accomplish and addressed the why, how and by whom, the final element of good governance is the ability to capture and share knowledge collected during the rollout so that the process can be replicated and operationalized automations can be supported on an ongoing basis. The implementation and scaling of RPA is a structured and specialized process, and it often falls outside the day-to-day skillset of most organizations. It can also be extremely tedious and time consuming. This makes it important for an organization to take advantage of implementation expertise that is available during the rollout and to capture and share lessons learned both during the initial implementation as well as during daily operations. As a result, many organizations choose to partner with an external party to support their implementation of RPA and to transfer relevant knowledge.
In Part 2 of our RPA discussion, we will address several operational challenges related to security, change management and business continuity that an organization may encounter when implementing RPA. Subscribe to receive the next installment in your inbox.
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