Not starting simple and instead trying to automate the end-to-end process. Each process contains multiple automation opportunities. Try to identify each one and focus on details. The end-to-end process can be automated in combination of RPA, analytics and artificial intelligence solutions.
Not spending enough time on exception scenarios. It is important to automate the straightforward processes, but it is equally important to understand all the exceptions within. Not all exceptions are suitable for automation. Identifying and automating the right exceptions could provide significant business value in the short term.
Not asking the right questions during the discovery phase. Even if a targeted process is well documented, ask about and identify what the operators are actually doing. Documented processes may be considerably different than real life scenarios.
Attempting to fix the process before automating it. Automate the “as-is” process. Fixing any process usually involves multiple stakeholders, technology and operational challenges. Don’t make this costly mistake.
Not digging deep in the analysis phase and defining boundaries of the targeted process. No matter how simple the process may appear, it is important to dig deep to understand all the details, including constraints and exceptions. Having defined all the details will help during the design phase and save a lot of time.
Not setting realistic expectations and communicating effectively with stakeholders.
Trying to implement automation between non-stable systems. If the systems RPA will be interacting with are unstable, and/or there are different software versions deployed in test and production environments, RPA won’t work.
Not understanding the differences between RPA and Artificial Intelligence (AI), and trying to get on the AI bandwagon. It is important to make sure that all stakeholders embarking on a RPA journey clearly understand key terminologies and their nuances. I am familiar with cases in which organizations planned AI implementations despite the fact that most of their problems were ideal candidates for RPA automation.
Thinking solely of short-term gains and not investing in the future. Implementing RPA solutions in “one-off” scenarios may help, but real gains are realized when key stakeholders and business processes are considered holistically as part of an RPA Center of Excellence. In this model, effective decisions can be made collectively on process selections, ROI calculations and designing an organization to create re-usable RPA components for long-term gains.
In summary, RPA can be a great tool for immediate cost reduction and creating process efficiencies. Companies that think and start simple with RPA have realized remarkable business value from their RPA investments. Working with an experienced partner such as Canon Business Process Services can shorten the learning curve considerably