9 Robotic Process Automation Best Practices

Sep 1, 2023 | Best Practices, Test Automation Insights

Ranorex AI


Robot process automation (RPA) tools allow organizations to automate essential tasks. They’ve increased in popularity because of their ability to improve the efficiency and accuracy of crucial business processes. RPA processes can access information from critical business systems faster than human workers. They also free up employees from mundane tasks to focus on work requiring human intervention and in-depth personal analysis and judgment. 

Effective use of RPA requires adhering to best practices for implementation, maintenance, and monitoring, and this helps companies overcome challenges related to technical ambiguity, team structures, logistics systems, resource sharing, and platform adoption.  

✅ Benefits of Adopting RPA Best Practices

As organizations start their automation journey, business leaders typically seek to achieve digital transformation. As a result, companies can save money, boost productivity, and improve operational efficiency. RPA can cover a wide range of business use cases, including:

  • Accounting
  • Invoicing
  • Data management
  • Payroll
  • Hiring and onboarding 

RPA can perform everyday tasks like:

  • Updating databases
  • Logging into applications
  • Extracting content from documents
  • Performing website scraping
  • Using machine learning and artificial intelligence (AI) to standardize processes and decision-making
  • Copying and pasting large quantities of information

Using best practices for RPA implementation gives companies a solid foundation for building automated solutions that scale to fit their needs. They can optimize essential workflows, reduce the number of repetitive operations requiring human intelligence, and cut down on data entry errors. 

RPA helps ensure consistency and reliability in the performance of automated processes. That type of stability is critical in building trust in the output, maintaining quality, and ensuring that the desired business outcomes aren’t affected by discrepancies. 

These best practices help organizations adhere to established security strategies and guidelines while following compliance requirements. Businesses can also use RPA to ensure data privacy security standards to avoid incurring fines and penalties from regulatory authorities. 

RPA also helps companies reduce manual intervention and streamline workflows so that organizations can respond more quickly to customer issues, enhancing service quality.

📝 Top 9 Robotic Process Automation Best Practices

The following RPA best practices help businesses establish a roadmap for designing, implementing, and managing automated solutions so organizations (maybe yours) can make the most of their RPA investment and achieve their operational and cost savings goals. 

1. Map Out Clear Process Workflows and Automation Scenarios

Start by researching the processes you wish to transform into an automation solution. Evaluate how suitable each scenario is for different types of automation. Business processes that occur frequently and involve a lot of transactions are a good fit for the RPA model. 

After narrowing down your list of candidates, calculate the savings you could achieve through automation. Your final choice should include processes that are stable and require minimal changes. Analyze all business processes for potential bottlenecks, inefficiencies, and sustainability and simplify any steps that seem overly complex or unnecessary. 

Create a visualization of the process workflow using modeling tools like flowcharts or process diagrams. Include any decision points, loops, exceptions, and branching logic. Label each step and decision point for clarity. 

2. Use a Modular and Reusable Approach

After selecting your automation scenarios, identify distinct tasks, phases, and sub-projects within each. Use that information to turn them into smaller, more manageable modules or components. Look for dependencies between different modules. 

Next, define the purpose of each module. Include any input requirements, output results, and expected outcomes. Identify the tasks and steps for each module and determine which triggers or events initiate its execution. 

Prioritize each module based on its importance, the level of complexity involved in implementation, and the potential of each to impact business goals. From there, start developing each module independently. You can have teams working on them concurrently or sequentially. 

Finally, establish standards for coding, naming conventions, documentation, error handling, and logging. That makes it easier for RPA project teams to maintain consistency across every module. 

3. Ensure RPA Security and Compliance With Data Protection Regulations

The best way to protect data is by controlling who gains access. You can accomplish this by implementing authentication mechanisms that ensure only authorized users can access and interact with RPA processes. Stick to the principle of least privilege, meaning that human users and other robot processes gain only the access required to perform tasks for their roles. 

Perform data encryption when at rest or during transit. Use secure coding practices when building automation scripts. RPA developers should avoid hardcoding sensitive information like credentials or passwords into the code. 

Organizations can also ensure data compliance by employing a secure credential management system for storing and managing credentials like passwords and API keys. Businesses should also implement logging for capturing robot activities, any actions taken by RPA processes, and every system interaction. An audit trail makes it easier to trace suspicious or unauthorized activities. 

Make sure all RPA processes and data handling practices align with any data protection regulations and security standards applicable to your industry. Limit the amount of personal information collected and handled by software robots to that required to accommodate a task. 

4. Establish a Feedback Loop for Continuous RPA Process Optimization

Put monitoring tools in place to track the real-time performance of RPA bots. Make sure you gather information like execution success, processing times, and exceptions. Define the key performance indicators (KPIs) aligning with your organizational process goals and objectives. Examples include:

  • Efficiency metrics
  • Accuracy rates
  • Processing times
  • Error rates
  • Cost savings

Next, perform data analysis to identify any areas of efficiency or pain points that adversely impact the performance of your RPA bots. Use those insights as part of your optimization efforts. You can also improve the user experience by collecting feedback from individuals like front-end users, process owners, and stakeholders who interact with the RPA processes frequently. Schedule regular review meetings with the RPA development team and other stakeholders to review KPIs and feedback to identify other RPA opportunities. 

5. Involve Stakeholders and Employees 

Stakeholder input is critical for RPA success. Solicit information from everyone impacted by the selected RPA process. Keep lines of communication open by setting up regular meetings and using collaborative tools. 

Always involve stakeholders in requirement-gathering sessions so you clearly understand how to improve the user experience. Review the current state of RPA projects and provide information about potential optimization strategies. 

Take advantage of opportunities to educate stakeholders about RPA concepts and benefits. That way, stakeholders come away from sessions with a good understanding of how projects will benefit their workflows.

6. Develop a Roadmap for Scaling RPA Initiatives Across the Organization

Take an honest evaluation of your company’s current RPA capabilities. Your assessment should identify current stakeholders like IT, operations, business units, and senior management. 

From there, define the strategic goals you wish to achieve by scaling RPA. Identify your desired business outcomes and ensure your RPA strategy aligns with broader organization digital transformation goals. Look for use cases that allow you to demonstrate the value of RPA, prioritizing them based on impact, complexity, and feasibility. 

Start with a pilot phase to perform software testing, try out control systems, and implement the RPA use cases in a controlled environment. Gather feedback and make any necessary adjustments. It’s also a good time to outline your KPIs and establish an RPA governance framework. Make investments in building RPA capacity by providing training for RPA team members. 

Consider setting up an RPA Center of Excellence offering expertise, guidance on best practices, and support for scaling up RPA efforts. You should also establish a change management plan to help work through the changes the work culture will face during RPA adoption. 

Set up feedback mechanisms that allow users and stakeholders to improve RPA implementations. Finally, establish a long-term vision for RPA adoption throughout your organization. 

7. Explore Emerging Technologies and Their Potential Impact on RPA

Follow new technological developments in the media, and send representatives to conferences, workshops, and webinars on emerging automation and digital transformation technology. 

It’s always good to engage with other experts, researchers, and thought leaders in the RPA world. Look for opportunities to network at events or through online platforms. Perform regular assessments of emerging technology and their impacts on your company’s RPA initiatives and automation processes. 

8. Leverage Analytics and Insights to Identify Areas for RPA Enhancement

Use the information collected from RPA bots, process logs, and other sources to locate areas of improvement in your RPA processes. Review the process metrics and performance data to see where human intervention may still be required. 

Review your data for trends, patterns, and recurring RPA process issues. Look for the root cause of any errors, delays, and inefficiencies. They could be due to factors like system issues or problems with data quality. 

Use comparative analysis to evaluate performance metrics before and after initiating an RPA process. Set benchmarks for RPA workflows against industry standards to help you find areas to improve. Other analytics you can perform to improve your RPA environment include:

  • Cognitive analysis — Helps you understand user behavior and decision-making patterns
  • Data mining — Lets you extract hidden insights from large volumes of process data
  • Predictive analytics — Helps you anticipate potential issues within RPA processes and take proactive measures

9. Monitor and Audit RPA Activities

Set up comprehensive logging mechanisms and store them in a centralized repository for review and analysis. Use real-time monitoring tools that give you visibility into bot operations. Create dashboards and reports that give users an overview of all RPA activities, like completed tasks and errors. 

Perform regular audits of RPA process execution to ensure they align with expected outcomes. Use version control when rolling out RPA scripts and component updates to track changes and updates. You should also document any changes to ensure the ability to detect any unusual RPA patterns or behaviors. 

⚙️ Implement RPA Best Practices With Ranorex

Ranorex test automation tools allow organizations to establish a robust, reliable RPA framework. Learn more about the benefits of using Ranorex for your test automation needs.

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