September 11, 2019
Raise your hand if you have deployed one or more robots in your operations. Good. Now raise your hand if you have deployed one hundred or more robots. Not there yet? No worry, as that is currently the situation in most businesses.
With robotic process automation (RPA) pilots almost everywhere, creating industrial scale has emerged as the new challenge for IT departments and shared service centers (SSCs) alike. The organization, processes, tooling and infrastructure required to quickly develop a few in-house robots cannot simply be incremented at scale. Enterprises need to re-design their entire approach.
According to a survey by HFS Research, the biggest gap in RPA services capabilities is not in RPA planning and implementation, but rather in post-implementation.
Here are five ways to meet the key challenges we hear from both IT and SSC executives about scaling robotics:
- Begin with the end in mind and start looking at an operating model strategy that supports the bots where they will eventually be running. However, whether you manage the bots from a centralized production environment or on agents’ desktops, there is no way around the IT department once you’ve decided to scale robots. IT departments have to make technical resources and support staff available; manage the configuration, software distribution and robot scripts; provide and maintain security access; plus track and respond to incidents. Unfortunately, it takes time and effort to configure such processes, and IT can have more pressing priorities, but presenting a clear operating strategy can help spur them on.
- If a business continuity plan has not yet been devised, it needs to be. If systems go down, the bots need to be re-started along with the entire software stack. Some organizations create mirrored environments they can switch to in case of extended system failures.
- Leverage the cloud. Cloud is generally acknowledged as the way forward for large-scale RPA operations. Cloud makes it possible to provision extra bots with one click, for example, to address sudden peaks in transactions. Cloud also enables efficient, consumption-based models. However, some large enterprises have ring-fenced clouds due to regulations in critical industries, such as in defense or banking, and this needs to be considered.
- Bring corporate security policies into force. Can hundreds of robots running in parallel access all corporate systems that require a human being’s credentials? They do not have an address, ID badge, a manager, an office, or a birth date – which may be mandatory to comply with existing corporate security policies. Corporate security policies need to reflect the new complexities.
- Realize that constant change is a rule, not the exception, for bots. Some companies leave the technical changes to IT, but manage the functional changes in the business units (finance, human resources, etc.) that own the business process, and this approach does provide more speed to resolution. For the same reason, the relevant business units can also maintain re-usable libraries of standard information. Things become more complex, though, when third parties are in the picture, like tool vendors, RPA consultants and/or business process outsourcing (BPO) providers. In fact, governance is most often cited by IT and SSC leaders as a key challenge here. It is common that RPA investments do not progress past development and test phases due to governance roadblocks. A preferred approach tends to be establishing a center of excellence — typically within the enterprise SSC organization — with responsibility over the policies, governance and tool/vendor selection for RPA. Still, once bots take a significant share of workload from human agents, does it make sense to keep the SSC and IT under separate organizations? And also, what is the impact on the human workforce? As we train bots to act as humans, businesses need to train and acclimatize their human workforce to co-operate with bots, understand how they operate and where to intervene.
In summary, RPA is a very hot topic currently and whilst a lot of the hype these days is around enabling technologies to accelerate the development of robots, the real challenge in scaling up your RPA digital workforce lies in better operating model design, a flexible cloud-based platform and of course, better appreciation of human nature.