As you probably already know, implementing Robotic Process Automation (RPA) has allowed companies to become more efficient and cost effective. RPA has definitely followed through on its promise to be a driving force to improve processes—and productivity—across organizations. As attractive as simplified processes are, it’s important that you don’t rush thoughtlessly into an RPA initiative. It often can take several weeks, sometimes even months, to identify the areas that would benefit the most from automation and to attune the rules behind it. And although RPA has the ability to generate rapid ROI, most RPA implementations have met major roadblocks before they found success. With this in mind, let’s take a look at why certain RPA initiatives may fail and what you can do to course-correct to avoid further challenges.

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A Few Common Reasons Why RPA Initiatives Fail

• Poor process selection
• Failure to set expectations on recovery time in case of a failure or breakdown
• Not proactively communicating or getting a sign off on the risks/points of failure and developing a mitigation plan
• Failure to build an inclusive environment where IT is involved. Your project could get delayed or fail due to factors not within your control.

Ensure You Have Selected the Right Processes to Automate
Process selection is a very important criteria when choosing what to automate, especially when you are selecting processes for a pilot implementation. Here are a few tips for successfully selecting the right processes:  

• Look for a process that can be automated end-to-end, as opposed to an assisted automation. Assisted automation can get very complicated, very quickly!
• An ideal process for a pilot implementation is one that is well-defined and does not have too many exceptions. Choosing a pilot process just because it’s a pain or annoying is not the right approach to take. You can move onto these process once your pilot is successful.
• Make sure to observe the process being performed and then compare it to the documented process. In most cases, there will be a considerable difference between the two processes.
• Every organization is going to have its own unique environmental-related challenges. This will be the case especially if you are completely dependent on the vendor to run your project.

Common Misconceptions About RPA That Organizations Get Wrong
First off, organization and/or stakeholders may underestimate the need for dedicated roles such as a Business Analyst, Program Manager, and so on. This may be because the RPA pilot was executed with limited resources – but as you scale up it’s incredibly important to recognize the need for additional investment in order to build a strong and robust RPA program. It’s important to realize that you can’t scale by only adding developers to run the program. Secondly, the majority of people commonly underestimate the run time debt and maintenance requirements of RPA.  

Partnering with IT to Implement RPA & Overcoming Partnering Challenges
Business and IT stakeholders both share a history which may (or may not) have been a positive relationship, which will more or less play into how well they can come together to implement an RPA initiative. Business leaders will often bypass IT due to the fact that implementing RPA may not require extensive support from IT. However, business leaders must recognize that a certain level of IT support will be needed – and failing to recognize this will expose the project to risks, such as disconnected technology, performance, and various security-related issues.

Be Aware of the Hidden Costs Associated with RPA

• If you are using a vendor, a fixed-price project may be the best way to go. If you are paying time and materials (T&M), then there is definitely a risk of overshooting your budget.
• Some RPA software companies have very complex pricing strategies. License-based RPA software may not have any hidden costs, but it’s important to understand what you are paying for and what features do or do not exist. It gets very complex when the software is not license-based. 
• Make sure that you do not underestimate the run-time debt when the bot is operational. Bots may not need supervision, but they do require oversight to make sure they are operating properly – especially during the initial phases of deployment.
• Make sure that you also do not underestimate testing efforts and handling exceptions.