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Top 6 Reasons Why RPA Projects Fail

When discussing the advantages of RPA, companies specializing in RPA solutions often showcase its benefits such as cost effectiveness and accuracy in various industries like education, insurance, and manufacturing. However, it’s crucial to acknowledge that many RPA projects encounter failures for several reasons.

More often than not, they fail to highlight these reasons. Therefore, whenever seeking the services of an RPA company in Dubai or anywhere else, ask them about any failed projects. Indeed, not all projects end up successful. A reliable RPA partner will not hesitate to share their failure stories.

There are several reasons why an RPA project may go haywire. Let’s explore the common causes behind RPA failure.

Why RPA Projects Fail

  • Automating the Wrong Processes

A frequent pitfall is attempting to automate processes that involve brainstorming, critical thinking, or those requiring substantial human input on a case-by-case basis. While RPA can be an excellent aid to humans, it’s unsuitable for automating such complex tasks entirely.

Remember, RPA can only automate repetitive, rules-based processes. However, hyper-automation may help take over complex tasks that require human input. Hyper automation combines RPA with technologies such as artificial intelligence and machine learning.

Businesses may sometimes implement RPA solutions in areas with limited scope or benefits, leading to dissatisfaction and opposition to the technology. To avoid this, it’s essential to identify the right processes for automation. Hold as many meetings as required with your RPA partner to identify the right processes.

It will help you avoid hassle in the long run. There are numerous stories of businesses which opted for ready-made RPA solutions. When they try to scale the solution to include new processes, the bot was incompatible. A good RPA partner will embed scalability in all RPA solutions from the very start.

  • Changing Interests

RPA projects involve multiple stakeholders with varying interests, which may change over time. RPA bots lack self-learning capabilities to adapt to shifting requirements. Open communication about RPA throughout the organization, establishing a common vision, and ensuring widespread acceptance can help mitigate this risk.

  • Failure to Account for Process Changes

RPA bots excel at executing tasks based on the predefined instructions they are programmed with. However, they cannot adapt when processes change. If the workflow is modified, the RPA bot will fail as it cannot learn or adjust to the new process independently.

Until RPA bots acquire advanced machine learning capabilities, they can only perform tasks as per their initial programming. In simpler words, unless your bot is combined with AI or ML technologies, you will need to update your bot as soon as the process changes. Otherwise, you will encounter errors.

  • Change Resistance

Implementing RPA often brings changes to job roles, and some employees may feel threatened by automation or require comprehensive training to work alongside RPA bots. Failing to manage employee resistance effectively can lead to project failure. Top management support is crucial before embarking on RPA implementation to ensure a smoother transition.

  • Scalability Issues

Some RPA solutions may not be scalable to accommodate the organization’s growing needs. RPA should be applied to automate repetitive tasks rather than trying to digitalize all processes. Understanding the limitations of RPA and aligning its usage with suitable tasks is vital to avoid disappointment and criticism.

  • Unrealistic Expectations

Unrealistic expectations can lead to frustration and resistance toward RPA solutions. Divergent perceptions of RPA’s impact among senior management and line managers can create discrepancies between expectations and reality. Collaborating with an RPA solutions provider and a clear understanding of the RPA bot’s capabilities are essential to prevent such issues.

Looking Ahead

Indeed, they are several other reasons why an RPA implementation may not achieve the desired results. However, if you address the most common causes, you can ensure a 99.8 per cent success rate.

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