Robotics Process Automation (RPA) has been a hot topic across several industries over the last couple of years and leading firms across the world have embraced the technology, or are in the process of doing so. KPMG's NewTech advisory team has worked with numerous clients to help them get started on their RPA journey and take it to scale – a process that most often starts with a Proof of Concept on a single back office process and then extends across the entire company.
From our team's experience implementing RPA across Scandinavia, Europe and the Middle East, we have seen that companies generally succeed quickly with introducing RPA to their organizations. However, companies often experience challenges when it is time to scale upgrade the technology or operate a stable "run" environment across departments, countries and divisions. These challenges arise for numerous reasons that vary from company to company, but some trends we repeatedly see are:
- A lack of consistent and clear RPA strategy: The lack of a comprehensive RPA strategy dooms numerous cross-company initiatives, as various units within the business undertake RPA journeys that are not aligned or compatible with each other.
- Undefined processes for establishing a scalable infrastructure that supports RPA: We have seen from several engagements that companies often attempt to establish a scalable, internal infrastructure without having a planned approach for the task. The resulting outcome is often an infrastructure built in an ad-hoc manner that does not facilitate long-term scalability.
- Lack of know-how about own business processes: Some clients run into problems because many of their internal business processes are known solely by daily users, which often arises due to poor follow-through of internal standards or because processes have grown to become so complex that they do not follow one defined pathway.
- Lack of sufficient internal RPA capabilities: We have witnessed that companies often launch large robotics initiatives before even securing the right capabilities to execute effectively on such a program. This is especially accurate for companies that want to undertake their RPA journey themselves without the support of external expertise.
- Poor intra-organizational collaboration on RPA: Another common problem we experience to scaling RPA is poor collaboration and transparency between departments, country offices and divisions within a company. In this case, major challenges and delays arise due to misaligned requirements and processes, differing priorities and general slow communication.
Fortunately, most of the challenges we see can be avoided – usually through planning and preparation while scaling RPA across the company. What should you keep in mind before moving from Proof of Concept (PoC) sprints to establishing a scalable RPA programme?
- Create a clear RPA Strategy: Before moving towards RPA, it is essential to define a clear strategy detailing how the firm will leverage the technology. This includes: identifying the type of processes to target, establishing a clear business case and timeline for value realization, deciding how much external support to depend on, defining what will happen to impacted employees and managing RPA across the various departments and divisions within the firm.
- Ensure that the vision for the RPA infrastructure is clear, feasible and aligned across the organization: The move from local workstation RPA execution during PoCs towards the virtual workstations needs to be managed effectively, which usually means close collaboration with the IT function. Thus, it is crucial that the approach is carefully thought through and that the technical preparation is prepared as much as possible, as IT usually tends to treat RPA as a "slow moving" IT solution. The RPA requires the establishment of a clear vision in regards to key topics: The central RPA infrastructure should be managed by the central IT function as opposed to localized set-ups (by location or department/division) and the responsibility for robot user/access rights process should also be allocated.
- Establish a RPA Centre of Excellence (CoE) to maintain and manage the RPA initiative in the firm: It is critical to establish a RPA CoE in order to scale and implement the technology effectively and quickly across the company. CoE responsibilities should include: guaranteeing that the appropriate RPA skills exist (as needed) are in place across the entire company, managing the relationship with the relevant RPA solution vendor and supporting consultancy, maintaining an overview of all RPA activities within the organization and pushing the RPA agenda throughout the company at all levels. Additionally, the CoE should be established to facilitate a firm-wide collaboration. The collaboration ensures a collective ownership of processes and mandates to effectively scale the RPA and reduces the bottleneck risk.
- Develop the necessary RPA capabilities internally: If an organization aims to scale its RPA, the project team is required to have the competences to lead and facilitate the initiative. In other words, the teams involved with Proof of Concepts (usually done in partnership with an external consultancy) must have acquired the necessary knowledge to effectively identify and document processes, perform the actual configuration of processes and manage the scheduling and execution of processes with RPA. Given that RPA will likely be commoditised in the long term, we suggest leveraging delivery partners to actually perform the configuration while maintaining a core internal team to manage the overall initiative.
- Define an Operating Model aligned with the rest of the organization (especially IT): Once the strategy is developed, the next step is to build an RPA operating model across the company. The operating model should include governance perspectives, key role definitions, responsibility definitions, and clear process definitions (i.e. how to get the appropriate accesses).
The right answer to this question will vary by company. Regardless, strategies should be thoroughly evaluated before and during any RPA scaling initiative.