Although Robotic Process Automation (RPA) is one lever in a spectrum of automation technologies contributing to a new definition of work, its status as a common entry point into automation brings added pressure for RPA programs to succeed quickly and at scale.
After a successful RPA pilot project – where an initial tranche of automations are operationalised and lessons are learned in how to work alongside automation – there can be a push to rapidly scale these results at higher volume, with more scenarios, or in other parts of the organisation. Many are moving beyond proof of concepts (PoCs) and pilots with RPA, and are now attempting various pathways to repeat success at scale.
This is a critical point in any automation program – after buying into the value proposition displayed by the PoC, decision makers and advocates from the wider business will watch closely to assess ability to execute at scale.
In this article, we’ll explore five tips to scale an RPA program, with the overarching approach to go slow short term to go fast long term.
Initial steps made with consideration of long term objectives rather than short-term tactical wins will lay the tracks for velocity down the line (see Figure 1 – Hockey Stick Growth). This means acknowledging as an organisation that the first handful of processes may not achieve the “rapid benefits” often quoted on the RPA tin.
Figure 1. Achieving “Hockey Stick” growth.
Key insights:
The importance of getting it right
Due to RPA’s position as arguably “easy to learn, hard to master”, defining “good” and aligning both internal and external expectations becomes especially important.
In scaling RPA, resisting the temptation to hyperextend while building capability creates an incubator for learnings and establishing scalable foundations. Conversely, kicking off a strategic automation journey without an equally strategic approach to scaling delivery often causes down the line setbacks or doubt in whether automation is the right fit for your organisation.
Current capabilities will be disrupted by automation – it could be RPA, RDA, or Chatbots. Building capabilities to adapt to the technology, as well as having the structures in place to efficiently manage the lifecycle, is what is going to deliver exponential benefits long term; much more so than one successful automation project.