Gone are those days when employees needed to put extra stress to execute mundane tasks. Today, we are living in a digitalized world where the philosophy of ‘maximizing productivity’ with ‘minimal’ human efforts is gaining popularity. And why shouldn’t it be when we have a fascinating technology like robotic process automation (RPA) to simplify business work. This technology is making significant strides in diverse business verticals and helping businesses to turn their fortune towards greater glory.

But wait!! There is a catch.

No matter how good this technology is, unless management takes care of certain vital things – right from idea inception to implementation stage, RPA success cannot be achieved. There are various things that people ignore and often lead towards robotic process automation (RPA) failure. What are those key things and how to overcome such challenges? This blog will help you to understand in great detail.

1. Choosing Incorrect Processes to Automate 

Not all business processes are considered fit for automation. RPA implementation works out best when you try to automate business processes that are highly repetitive, mundane, rule-based, and most importantly those require less human interaction. If you plan to automate processes where at every then and now you require human expertise or deep involvement of your critical resources then the team finds it difficult to manage in the long run and such RPA projects ultimately fail miserably. Remember that some involvement is manageable but too much is infeasible.

2. Unrealistic Business Expectations

Robotic Process Automation software is a blessing for entrepreneurs, employees, and customers as it provides multiple benefits like increased productivity, profitability, shorter project turnaround time, etc. But RPA software is not a ‘go-to’ solution for every single business problem. There are certainly numerous tasks that can only be handled best with human intelligence and cognitive capabilities. When management tries to ignore this facet, problems arise and lead to robotic process automation failures. Therefore, keep highly-complex tasks separate from automation where critical reasoning and decision-making abilities are required.

3. Wrong Estimate of ROI

Even if an RPA solution works best, improves efficiency, enhances productivity, and makes your work environment better, unless it proves economically feasible, it is highly unlikely to give something meaningful to the organization. As profit is the ultimate thing that decides the fate of anything important in the business world. Your total revenue generated from RPA software must be significantly much higher than the total cost of ownership of RPA projects. If the reverse happens or the profit margins dip sharper then it first affects the economic health of the organization and then the longevity of RPA projects. Selecting the right business process for automation and picking the right RPA vendors are the keys to avoid this failure.

4. Underplay Training

You hire an RPA vendor, develop a bot, deploy it successfully, and then all goes well on auto-pilot mode, right?


Even once the RPA projects are implemented successfully, they still require adept manpower to ensure their smooth functioning. Remember, the advanced version of RPA i.e. smart process automation (SPA) learns from different scenarios and may come across exceptional scenarios where you require skilled RPA technicians to handle exception handling. But many times companies think that shorter training over bots is sufficient to navigate the robotic process automation software easily and this is where again robotics process automation (RPA) projects fail. Further, there are several stakeholders involved in the working environment that are not very technical, you thus need to give proper RPA training with a 360* approach.  Training the manpower from junior employees to project managers before deployment is a key to mitigate this RPA failure.

5. Poor Change Management Communication

There are several robotic process automation implementation challenges but the one which companies often ignore at a great scale is ineffective change management communication. Due to the widespread misinformation surrounding RPA, many employees feel vulnerable and resist change. Management is also wary about infrastructure changes required for robotic process automation (RPA) project implementation and their effects on the existing environment. Unless you brief them about the overall benefits of RPA and win their confidence through the right RPA education, chances of RPA success look unpromising. The management should explain the need, advantages, and roll-out plan to each stakeholder before moving ahead with RPA. Solving their doubts is a great great idea to clear the misconceptions they might have about this fascinating automation technology.

6. Improper Testing

One of the reasons why RPA implementation fails is due to improper testing before the deployment stage. When you disrupt decades-old business processes using automation, precise analysis is required to map the physical output delivered by RPA bots. When executing an RPA project using standard operating procedures for testing, you might encounter some unexpected results where some minor cosmetic changes into the RPA code are required. Not checking each and every functionality as listed in RPA documentation and mapping it with expected output and missing taking notes of discrepancies can lead to big failures in later stages. It is the utmost responsibility of project managers to pass all bugs to developers to rectify the shortcomings. Remember, a small ignorance during the testing stage can lead to severe failure in the deployment stage. So test it properly before rolling-out the actual RPA project.

Final Words

Advanced technologies like RPA are no less than a blessing for enterprises but their thoughtful, effective, and pragmatic implementation only can help businesses to reap sweet fruits. Failure to adhere to well-established implementation norms can only lead to project failure. It is thus always a wise idea to learn from others’ mistakes and carefully analyze all bottlenecks well in advance to prepare better for hassle-free automation implementation.