Best Practices at Process Level

Opportunities for RPA

Identifying opportunities for RPA at the process level involves a meticulous review of existing workflows to pinpoint tasks that could benefit from automation. Best practices for this process ensure that RPA deployments are effective, deliver a good return on investment, and achieve the desired outcomes without introducing new risks or complications. Here are the best practices for identifying RPA opportunities at the process level:

1. Focus on High-Volume, Repetitive Tasks:

  • Look for tasks that are performed frequently and consume a lot of employee time. Examples include data entry, invoice processing, and report generation.

2. Prioritize Rule-Based Processes:

  • Processes that are based on clear and consistent rules are prime candidates for RPA. For instance, if an invoice is above a certain amount, it's routed to a specific manager for approval.

3. Target Processes with Low Variability:

  • Processes that remain consistent over time, without frequent changes in steps or rules, are ideal. Constantly changing processes might require frequent bot reconfigurations.

4. Assess Error Rates:

  • If a process frequently results in human errors, automation can help improve accuracy. For example, RPA can eliminate common data entry mistakes.

5. Review Manual Data Transfers:

  • Processes that involve transferring data between systems manually, especially if the systems aren't integrated, are ripe for RPA. Bots can bridge the gap between disparate systems.

6. Evaluate Structured Data Sources:

  • RPA works best with structured data. Processes that use well-defined data sources, such as databases, spreadsheets, or structured forms, are suitable candidates.

7. Shortlist Stable Legacy Systems:

  • If an organization uses legacy systems that don't have easy integration options or APIs, RPA can be a workaround to automate tasks within these systems without major overhauls.

8. Identify Bottlenecks:

  • Any processes that are bottleneck points in a workflow, causing delays and inefficiencies, might benefit from automation to speed up operations.

9. Understand End-to-End Process Flow:

  • Before automating a specific task, it's essential to map out the entire process flow. This helps ensure that the automation won't disrupt subsequent or preceding tasks.

10. Gather Feedback from Employees:

  • Frontline employees who handle day-to-day tasks often have insights into the pain points and inefficiencies of current processes. Their feedback can be invaluable in identifying areas where RPA might help.

11. Consider Compliance & Auditing Needs:

  • Processes that require strict compliance or have robust auditing needs can benefit from RPA, as bots can maintain consistent operation and provide detailed logs of their actions.

12. Analyze Financial Impact:

  • Focus on processes where automation can provide a clear financial benefit, either through cost savings, reduced error rates, or increased throughput.

13. Test and Pilot:

  • Before a full-scale rollout, consider piloting the RPA solution on a smaller scale to ensure it addresses the process's needs effectively and to iron out any potential issues.

14. Stay Open to Process Reengineering:

  • While RPA can automate existing processes, it's also an opportunity to rethink and optimize those processes for better efficiency and outcomes.

In conclusion, the key to successful RPA implementation lies in thoroughly understanding the organizational processes, knowing the strengths and limitations of RPA, and then aligning the two in a manner that drives efficiency and value.

Efficiency Drivers for RPA

When assessing processes for RPA, it's critical to identify the efficiency drivers that can optimize the effectiveness of the automation initiative. Efficiency drivers for RPA at the process level pertain to the elements or characteristics of a process that, when present, make the process an ideal candidate for automation. These drivers can lead to substantial time and cost savings, reduced errors, and improved process outcomes. Here are the primary efficiency drivers for RPA at the process level:

1. Repetitiveness:

  • Definition: Tasks that are performed regularly and consistently.
  • Efficiency Gain: By automating repetitive tasks, organizations can free up employee time for more value-added activities.

2. High Volume:

  • Definition: Tasks or processes that are executed frequently or deal with large amounts of data.
  • Efficiency Gain: Automation can handle high volumes at speed, allowing for faster processing times.

3. Rule-Based Decisions:

  • Definition: Processes that operate based on a predefined set of rules without needing human judgment.
  • Efficiency Gain: Bots excel at consistently applying rules, leading to uniform and predictable outcomes.

4. Low Exception Rates:

  • Definition: Processes where exceptions or deviations from the norm are infrequent.
  • Efficiency Gain: With fewer exceptions, bots can operate smoothly without interruptions, ensuring consistent throughput.

5. Stable Processes:

  • Definition: Processes that do not undergo frequent changes in terms of steps, rules, or criteria.
  • Efficiency Gain: Stability ensures that once a bot is deployed, there's minimal need for reconfiguration or maintenance due to process alterations.

6. Digital-Readable Inputs:

  • Definition: Processes that rely on digital or structured data sources, such as databases, spreadsheets, or electronic forms.
  • Efficiency Gain: RPA bots can swiftly and accurately read and process digital inputs, reducing the need for manual data entry or transfer.

7. Manual Data Entry & Transfer:

  • Definition: Tasks that involve manually inputting data into systems or transferring data between systems.
  • Efficiency Gain: Automating data entry eliminates human error, ensures data integrity, and speeds up data processing.

8. Process Bottlenecks:

  • Definition: Points in a process that cause delays or backlogs.
  • Efficiency Gain: By automating bottleneck areas, overall process flow can be accelerated, reducing wait times and improving service delivery.

9. Compliance & Audit Trails:

  • Definition: Processes that require strict adherence to regulations and the maintenance of detailed logs.
  • Efficiency Gain: Bots can ensure compliance by following the exact process steps every time and can maintain detailed logs for audit purposes.

10. Scalability:

  • Definition: The ability of a process to handle increased workloads without proportional increases in costs.
  • Efficiency Gain: RPA allows for quick scalability; bots can be replicated or scheduled to meet varying workload demands without significant additional costs.

11. Standardized Processes:

  • Definition: Processes that are uniform across departments or units, following a standard set of steps.
  • Efficiency Gain: Standardization makes it easier to implement and roll out RPA solutions across the organization, leading to wider efficiency gains.

Incorporating these efficiency drivers into an RPA assessment at the process level ensures that automation efforts yield maximum benefits. It's also a reminder that while RPA is powerful, it thrives best in specific environments. Tailoring RPA initiatives to processes driven by these efficiencies can significantly boost the return on investment and overall success of the automation project.