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Benefits of Measuring RPA Metrics and Visualizing with Intelligent Dashboards

Robotic Process Automation (RPA) and Intelligent Automation (IA) are transforming the way businesses function by increasing efficiency, lowering costs, and enhancing accuracy. This article discusses how to identify, track, and measure RPA metrics. It also emphasizes the value of viewing these indicators using interactive dashboards. These dashboards, created using BI technologies, enable real-time monitoring of bot performance, financial benefits, and scalability. It also covers how to select the appropriate RPA metrics, gather data, and construct an effective visualization dashboard to display the results.

🤖Robotic Process Automation (RPA)

RPA is the use of software robots, or “bots” to automate repetitive, rule-based operations typically done by humans.

✔️Benefits:

Cost Savings – Accuracy – Scalability – Increased Productivity – Rapid Deployment

🤖Intelligent Automation (IA)

RPA is combined with AI, ML, NLP, and OCR to create Intelligent Automation. This integration allows for more complex automation activities that require decision making and adaptability.

✔️Benefits:

Advanced Decision-Making – Process Optimization – Improved Customer Experience – Data-Driven Insights – Adaptability

Before using RPA, process measurements must be collected to establish a baseline. This guarantees that you understand your present activities, which is used to evaluate automation enhancements.

Baseline metrics

  • Benchmarking: A baseline refers to pre- and post-implementation performance to evaluate RPA efficacy.
  • Objective Evaluation: Examines RPA’s influence on efficiency, accuracy, and costs objectively.
  • Target Setting: Set reasonable aims and expectations for the RPA project using baseline data.

💡How do I identify RPA Metrics?

  1. Bot Utilization Rate
  • Definition: The average time a bot is active versus idle.
  • Importance: High usage suggests good bot use, whereas low utilization may imply underuse or process inefficiencies.
  1. Process Accuracy
  • Definition: The rate at which a bot completes tasks without errors.
  • Importance: High accuracy ensures reliable output, reducing the need for human intervention.
  1. Average Handling Time (AHT)
  • Definition: The average time taken by a bot to complete a task.
  • Importance: Monitoring AHT helps in understanding the efficiency of the bot.
  1. Exception Rate
  • Definition: The fraction of bot-unfinished jobs that require human involvement.
  • Importance: High exception rates may point to process complexities or bot limitations.
  1. 5. Cost Savings
  • Definition: The reduction in operational costs due to the implementation of RPA.
  • Importance: Demonstrates the financial benefits of RPA.
  1. Scalability
  • Definition: Increase bot processes or transaction volume.
  • Importance: Shows the bot’s capacity to handle growing business needs.

Tracking and capturing the metrics:

Integrated Tools:

  • Integrating tools for metric tracking: Some automation technologies have built-in metric tracking. For example, UiPath’s Orchestrator and Insights enable comprehensive monitoring and reporting.
  • Cross-tool metrics: Metrics across the process flow are essential when automating using different technologies. This may need bespoke integrations or monitoring solutions.

💡How do I achieve it?

Collecting Data: Continuous data collection is needed to measure these indicators. How do I collect the data?

  • RPA Logs: Bots often output activity logs. These logs can provide bot use, average handling time, and success rate.
  • Exception Reports: Record exceptions to assess failure rates and causes.
  • Measure process correctness and identify areas for improvement by collecting user input from bot interactions.
  • Determine cost reductions by comparing pre- and post-implementation expenditures.

Centralized Data Repository:

  •  Database: Create a relational or NoSQL database to store metrics. This might be an on-premises or cloud-based database (AWS RDS, Azure SQL Database).

Data Cleaning:

  • Implement data cleaning procedures to ensure data consistency and accuracy.

Metrics Dashboard Development:

  • BI Tools: Use business intelligence (BI) tools like Tableau, Power BI, or open-source solutions like Grafana to build interactive dashboards.

 Real-Time Monitoring:

  • Streaming Data: Implement streaming data pipelines using tools like Apache Kafka or AWS Kinesis for real-time metrics.
  • Alerts and Notifications: Integrate alerting systems (e.g., Slack, email, SMS) to notify stakeholders of critical events or anomalies.

Dashboard ideas

Customers like dashboards that provide crucial process indicators because they demonstrate automated system performance and efficiency. Process accuracy, bot utilization, average handling time, error rate, cost savings, and scalability are all critical. Businesses utilize these measures to assess bot performance, identify development opportunities, and calculate the financial benefits of automation.

Overview :

  • Utilization Rate: A gauge chart showing the utilization time of a bot.
  • Average Handling Time: A line graph showing the trend of AHT over the past month.

Performance:

  • Process Accuracy: A pie chart indicating current accuracy.
  • Success and Exception Rates: Side-by-side bar graphs showing success and exception rates.

Financial:

  • Cost Savings: A graph comparing monthly operational costs pre- and post-RPA implementation.
  • ROI Calculation: A text box displaying the calculated return on investment.

Scalability :

Trend Analysis: A line graph indicating bot process growth.

  Sample Dashboards for Visualization

Sample Dashboard for Visualization

RPA bot performance and cost efficiency on the dashboard:

  1. Invoice processing accuracy: A pie chart on the dashboard shows that the bot processes invoices 96% of the time without difficulty.
  2. Comparison of Bot Accuracy: Bot accuracy is compared using a bar graph. The Excel download bot fails 20% of the time, maybe due to SFTP server or network difficulties.
  3. Another graph shows the total cost of ownership (TCO) for a single procedure over three years. It demonstrates how RPA implementation’s early development expenses and decreased operational costs lead to considerable savings over time.
  4. The monitor also shows strong bot instance growth. Over the past year, bot-managed instances have more than quadrupled, exhibiting efficiency and scalability.

Following these procedures lets you measure and visualize RPA bot performance for ongoing improvement and stakeholder validation. Well-designed dashboards give information and help make educated decisions to maximize bot performance and meet company goals.

💡Key Takeaways:

  1. RPA and IA are transforming contemporary business processes by increasing cost, accuracy, and efficiency. RPA automates regular work to free up human resources for important projects, whereas IA uses advanced technology to improve processes and make complicated decisions.
  2. A baseline of current processes and important indicators like bot usage, process correctness, handling time, exception rates, cost savings, and scalability show RPA’s influence.
  3. Accurate tracking is achieved by logs, reports, user input, and operating expenses, centralized data repositories, and strong ETL procedures.
  4. Interactive dashboards created using Tableau or Power BI provide real-time monitoring and analysis of bot performance, financial advantages, and scalability.
  5. This complete strategy maximizes automation advantages, saving money, improving accuracy, increasing productivity, and driving growth and innovation.

 

🤝 Ready to experience the transformative power of RPA and take the first step towards unlocking efficiency and innovation within your organization. Schedule an expert consultation today. sales@valueglobal.net

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