7 steps to restart a failed RPA initiative

a woman in front of a visual representation of a process automated by an rpa initiative

Identify why your RPA initiative failed and how to get it back up and running again

Automation solutions are becoming increasingly popular, but many organisations struggle to leverage RPA effectively. Without proper planning and implementation, these projects can quickly become costly failures that leave companies with nothing to show for their efforts.

Restarting a failed RPA initiative requires a comprehensive approach that focuses on the root cause of the problem and identifies any potential issues before implementation begins. Here are the seven steps you should take to get your RPA initiative back on track:

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1. Analyse your original project plan

Start by closely examining your original project plan. An in-depth analysis will pinpoint the factors that contributed to the failure of the initial attempt, such as inadequate resources, misaligned expectations, or poor communication between teams.

This process should involve all key stakeholders to ensure a shared understanding of the challenges faced and the lessons learned. A thorough analysis of the original project plan sets the stage for a more effective and well-informed approach to your project, increasing the likelihood of long-term success.

man examining work results on a laptop

2. Set clear goals and objectives

Establishing clear goals and objectives is a fundamental step to restarting a failed RPA initiative. Only by articulating well-defined targets can all teams and stakeholders fully understand the desired outcomes of the project and work collaboratively toward achieving them. Involvement from your subject matter experts is crucial so they can conduct user acceptance testing and make sure what has been built for them is what they truly need.

Remember that you need to define the benefit you expect to gain from your RPA initiative. Your previous one may have automated a process that, over time, you’ve learned is rarely used. While it was not a failure in a practical sense (it automated the process you targeted), it does not deliver the value you were expecting because it does not have a big enough impact on the results you want to achieve.

Some clear goals and objectives that you could set include:

  • Process Efficiency: Improve the efficiency of a specific process by reducing its completion time by X% within Y months.
  • Cost Reduction: Achieve a cost savings of X% in targeted business operations within Y months by automating manual tasks.
  • Error Reduction: Decrease the error rate in a particular process by X% within Y months through automation, improving data accuracy and quality.
  • Employee Productivity: Increase employee productivity by X% within Y months by automating repetitive tasks, allowing staff to focus on higher-value activities.
  • Scalability: Successfully automate X number of processes within Y months, with a plan to scale up the automation to additional processes in the future.
  • Compliance: Ensure that all automated processes meet industry-specific regulatory requirements and maintain X% compliance within Y months.
  • Customer Satisfaction: Improve customer satisfaction scores by X% within Y months by automating customer-facing processes and reducing response times.
  • ROI: Achieve a return on investment (ROI) of X% within Y months after implementing the automation solution.

3. Ensure proper documentation

Comprehensive documentation provides a clear understanding of the processes, requirements, and decisions made throughout the project, ensuring that all stakeholders are on the same page.

It is important to document everything from the analysis of the original project plan and the new goals and objectives to the technical specifications and change management strategy. By creating organised and accessible documentation, teams can effectively track progress, identify potential issues, and ensure continuity in the event of staff changes. Proper documentation can aid in compliance with regulatory requirements and simplify future maintenance and scaling efforts.

4. Create a change management strategy

Change management helps to ensure the successful adoption of new technologies and processes by addressing the human aspect of change. A successful change management strategy should include clear communication of the benefits and goals of the RPA project, as well as providing adequate training and support for team members throughout the transition. It should also involve managing resistance to change by addressing concerns and fostering a culture of collaboration and continuous improvement.

By defining the roles and responsibilities of stakeholders, setting timelines for implementation, and establishing milestones to track progress, tech leaders and managers can create an environment where team members are engaged and committed to the success of the RPA initiative. This ultimately leads to more effective adoption of automation solutions and better long-term results.

visual representation of an rpa bot mimicking a human process

5. Ensure you’ve selected the right automation platform

It’s now time to evaluate your automation platform and discern an important factor of your failed initiative: is your platform unsuitable for your objectives, or was it simply not utilised correctly?

Consider factors such as compatibility with existing systems, ease of implementation, scalability, and long-term maintenance. If you find your current platform to be unsuitable or lacking in certain aspects, explore the possibility of extending its capabilities through integrations, add-ons, or customisations. Engaging with the vendor for support and guidance can also help maximise the platform’s potential.

If, after your evaluation, you decide to replace your existing automation platform with a new one, you must engage all key stakeholders (including IT teams, end-users, and decision-makers) in the selection process. Develop a transition plan outlining the steps required to switch from the old tool to the new one. This includes any necessary data migration, process redesign, employee training, and documentation updates.

6. Consider legacy systems, IT constraints, and other technical challenges

Although some problems with your initiative may be remedied by making changes to your automation platform, you must take into account other technical challenges that could impact the success of your next project. Addressing these issues early on helps to mitigate potential roadblocks and ensure a smoother implementation process.

Challenges you might experience include:

  • Legacy systems: Outdated software or hardware that may not be compatible with modern automation platforms, such as old mainframe systems or custom-built applications that lack APIs for integration.
  • IT constraints: Limited resources, such as insufficient server capacity, bandwidth limitations, or inadequate IT staff to support the RPA project, can hinder the successful implementation and maintenance of the initiative.
  • Integration issues: Difficulty in integrating the automation platform with existing systems and applications, which might require custom coding or workarounds to ensure seamless data exchange between systems.
  • Security concerns: Ensuring that the platform complies with your organisation’s security policies and adheres to industry-specific regulations, such as GDPR or HIPAA, can be a significant challenge.
  • Scalability: Your automation platform may have limitations in scaling to accommodate growing automation needs or struggle to handle complex processes, leading to performance issues.
  • Vendor lock-in: Committing to a specific platform might limit flexibility in the future if there is a need to switch vendors or integrate with other automation solutions.

You should also be mindful of any budget constraints that may impact your ability to invest in the necessary hardware, software, or training required for successful implementation and ongoing maintenance.

7. Use analytics to measure performance

With the rest of your RPA initiative analysed and corrected, the final step is to ensure you’re tracking your performance accurately and measuring it against the goals and objectives you set earlier.

Effective analytics can help identify areas where the automation implementation may be underperforming, enabling prompt adjustments to improve outcomes. It is important to establish a baseline before restarting your RPA initiative and to continuously track these metrics which will enable data-driven decision-making. By leveraging analytics, you can drive continuous improvement in your RPA initiatives and demonstrate the value of automation to stakeholders across your organisation.

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