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4 Reasons Why RPAs Fail (And How to Avoid Them)

It is no secret that RPA are a game changer. From boosting productivity and reducing costs to freeing up employees' time to upskill, they empower organizations to transform the way they do business. However, if used incorrectly, RPAs might not achieve the desired outcome. It is important to note that in those cases, the failure of RPA is most likely not due to the tool itself, but to how it was planned, implemented, and deployed. It is crucial for organizations to know what mistakes to avoid before starting their RPA journey.

As experts in RPA development and consulting, we have worked with organizations in all major industries in planning, implementing, supporting, and troubleshooting RPA models. In this post, we will identify the three main reasons why RPA projects fail, and how to avoid them.

Mistake #1 - Not Setting an RPA Strategy

Once an organization decides to adopt RPA into its operations, it is advised to set in place a strategy for long term implementation and optimal use of RPA. The strategy should consider

  • How RPA will be used on the long term and how it will help reach organizational objectives.

  • How other operations and processes can be integrated with RPAs

  • How workforce planning and job descriptions will shift with RPA implementation

  • Establishing a culture of excellence around RPA and ensuring team members embrace it and are well informed on it.

  • Whether RPA solutions will be attended (work in conjuncture with humans), unattended (run automatically with no need for human triggers), or a hybrid of both.

Mistake #2 - Not involving stakeholders

Implementing RPA goes beyond just introducing a new solution; it changes the behavior of the organization as a whole, which means the organization will most likely face resistance to change. Before implementing RPAs, organizations need to be proactive in considering and addressing the following:

  • Middle Management: Middle management are the first people who will convey the new solution to their respective departments. Their role is critical in transferring the messages they get from senior management to the rest of the team. If middle managers did not understand the value of RPA, and if they prefer maintaining the status quo, it will spillover onto the employees.

  • IT Team: Although RPAs are designed to follow instructions and workflows automatically, they will need to be monitored, especially in the initial stages of deployment, to ensure that they are running smoothly. Additionally, occasional troubleshooting or modifications may be required especially if changes occur within the interfaces that RPAs interact with. For these reasons, it is important to ensure that your IT team has a good understand of and is well trained on the RPA workflows.

  • Other employees: The word ‘automate’ carries a negative connotation around it. When employees hear that some tasks will be automated, they might fear of losing their jobs, which will lead to a stressful environment and potential turnover. As organizations introduce the idea of RPAs to their employees, they need to make sure that employees understand that the software bots are not there to replace them, but they are there to reduce redundant workloads off their plates and help them focus on more value-added tasks and upskilling. When employees view RPAs in a positive light, they will be less likely to resist it.

Mistake #3 - Automating the wrong tasks

Many organizations get excited when they first hear about RPAs, which is understandable – RPAs are incredible! However, this excitement may lead to high expectations and hastiness; in other words, organizations may think that they can now automate everything. In reality, not everything can be automated; actually, not everything automatable is even worth automating. When organizations are assessing their RPA options, they should consider the following

  • Return on Investment: Organizations need to consider if the ROI of implementing the RPA is worth the initial cost and time that will be put into it. Does the task consume too much of the employees’ time? Is it often prone to human error or biases? If not, it is less likely to be worth automating.

  • Nature of tasks: As mentioned, RPAs can not automate everything. If a task has too many exceptions or special cases, automating it will probably not yield desired outcomes. Tasks considered for automation should be high volume, rule based, and low in complexity to ensure optimal use of RPAs.

There are many process mining tools that help organizations understand which processes and operations are worth automating based on how much time and effort they consume.

Mistake #4 - Hasty deployment

One of the common mistakes that organizations make is assume that the RPA is ready to deploy once the workflows have been set up.

Like all new software, it is essential to carry out continuous testing not only to the workflow itself, but also to how it integrates with other operations in the organization, how it handles exceptions, how it reacts in cases of changing interfaces involved with it, and how human employees are performing alongside it. This helps ensure that your RPA will not fail due to unanticipated complexities that could have been avoided.

Interested in Implementing RPA in your Organization?

Paragon Shift's team are ready to support your organization in its RPA journey. From advising, to planning, to implementation, to deployment, to support, we tailor our services to your organization's needs. Reach out to us or book a free consultation!

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