What are the best ways to validate RPA processes?

Before initiating the RPA journey it is necessary to filter down to key process parameters which are required to be automated. Also, the process could have different variants which should be taken care of while automation. Task mining or Process recording will help to uncover the process variants so the most common variants can be taken for automation. Then the project success criteria defined at the start of the project should be compared at the end this help to identify deviation if any

Validating Robotic Process Automation (RPA) processes is crucial to ensure accuracy, reliability, and compliance. Here are some best practices for validating RPA processes: 1. Requirements Validation 2. End-to-End Testing 3. Input Data Validation 4. User Acceptance Testing 5. Error Handling Testing

While validating any RPA process we need to ensure that the smallest of the details are to be validated and not missed. That is because even a small change to an original expectation might lead to big difference post production. Let me give you an example here where a bot was created to resolve the service-now tickets. The validation during the UAT phase was to check if the bot has closed the ticket and if it has updated the comments.Everything was smooth, but later it was observed that the comments updated were not as expected.Because the validation of those comments with different variations was missing and the bot started updating wrong comments and closed tickets with wrong intent. This was a clear miss in the validation criteria.

Validating RPA (Robotic Process Automation) processes is essential for ensuring accuracy and reliability. The best ways to validate RPA processes include: 1. Testing: Rigorous testing with various inputs and scenarios to identify errors. 2. Peer Review: Collaborative reviews by RPA developers and subject matter experts. 3. Documentation: Comprehensive documentation of the process design, logic, and expected outcomes. 4. Error Handling: Implement effective error-handling mechanisms to address unexpected issues. 5. Continuous Monitoring: Ongoing monitoring and performance analysis for process improvement. 6. Compliance Checks: Ensure compliance with regulatory requirements and data security standards.

Any programming language needs a proper maintainable code. RPA is no less in that. When we say maintainable,code needs to be readable and also the logs needs to provide the trace of where the process logic is traversing. This trace is important as there might be many variations in the process and each case might go into different set of validations and to properly validate the process details ehen in doubt, these logs play a crucial role in giving the minute details needed to assess the process. Building a process is easy but building it without any design flaws is where we differ from a good process to best ones. This happens only when we have the process articulated to look and break the code as per proper modules mentioned as per design

Build in logging, telemetry, and alerts from the start to support monitoring and troubleshooting. - Leverage low-code RPA platforms with built-in auditing capabilities. - Create unit tests early in development to validate each component and use version control and code review processes for quality assurance. - Design modular, independent bots to allow incremental validation.

-Create test scenarios that are clear, concise, and cover each business rule noted in the PDD/SDD. - Test the Data, make sure of the input and the output.

When performing the tests it is important that the bot is tested not only with different scenarios but also tested with multiple variations of the load , multiple times of the day,different types of users etc. If we only rely on one type of testing we might end up with a process which is accepted but might fail or behave differently when deployed. Say we have done testing for all positive cases, then in production there might be scenarios where system exception is happening but the error might be little different. The process might fail on step A but due to bot moving to next step without validating the step A completion the error might be thrown on step B which is impossible to debug most of the times.

The best way to validate an RPA process is through thorough testing at each stage of development. Begin with unit testing to ensure individual components work correctly, followed by integration testing to assess their collaboration. User acceptance testing involves end-users to confirm the system meets requirements. Finally, conduct regression testing to verify updates haven't affected existing functionalities. Continuous monitoring and feedback from users contribute to ongoing validation, ensuring the RPA process remains effective and reliable.

Validating RPA processes post-production involves several key strategies: 1. Performance Monitoring: - Monitor execution time completion for tasks. - Analyze queues and transaction average handling time to ensure efficiency. 2. Server Resource Utilization: - Check server resource utilization to optimize performance. - Analyze logs for job sections to identify potential bottlenecks or issues. Applying these methods helps to maintain and improve efficiency of rpa processes

Hypercare is the most important phase of an RPA lifecycle. Thats because the bots are tested or used to the fullest and in a complete new environment for the first time with a great number of users than UAT. In this phase closely monitoring the bot is much needed as there might be more different use cases might be tested let it be positive or negative. As we have an open court to validate the outcomes and quickly act on them during this phase, it is important we monitor the processes pretty closely and also understand the pain points from business perspective and improvise on either the process or train the business to use the process to its best. This is possible only with a full analysis of the bot end to end .

Validation may include tracking of KPIs like task completion rate, cycle times, accuracy, system usage. Additionally, you can: - Monitor resource utilization, CPU, memory, network - to identify bottlenecks. - Analyze logs for trends and correlations - trigger alerts on anomalies. - Compare metrics pre and post-automation to quantify improvements.

Most of the times we might end up with a lot of feedbacks duting UAT. This is important to consider these feedback as the end user satisfaction is where the automation gets its ROI from. But through experience I would say have touch points with business or end users while developmnet as well to avoid suprises from both ends only during UAT or post production during hypercare. This ensures that we receive an early feedback and adapt to it as soon as possible and can make changes to the code as per the feedback maintaining the highlevel design intact. This also helps in understanding the changes that can happen to BOT values and we can maintain them configurable making it easy to change when needed

Seek a performance review from the business owners: they usually have a pretty firm idea of the benefits that the solution brought to them.

There are various ways in which you can seek feedback and review such as: - Interviewing process owners on potential enhancements or pain points. - Conduct periodic audits for compliance, security, accounting. - Request user feedback on quality, speed, transparency. - Analyze help desk tickets for recurring issues.

Stakeholder Feedback: - Gather feedback from stakeholders involved in or impacted by the automated processes. - Consult individuals who used to perform the process manually to ensure the RPA solution aligns with their expectations and needs.

Here's what else to consider: Conduct user acceptance testing (UAT) with real users performing real tasks to validate process flows. Observe where they get stuck or confused. You can benchmark productivity/efficiency gains versus human baseline performance before automation. Set improvement targets. Finally, evaluate change management needs to ensure staff are prepared for and embrace RPA rather than resist it. The key is taking a holistic view - validating not just the technical functionality but also the operational integration, business alignment, and change impacts of RPA. This builds confidence and enables continuous improvement of automated processes.

using process mining solutions is also one way to Identify processes best suited for RPA as they help to understand the underlying reasons behind processes’ suitability.

Como RPA Business Analyst, uma das melhores formas de validar processos de RPA envolve a colaboração com as partes interessadas para definir requisitos claros e documentar fluxos de trabalho detalhados. Realizar testes de unidade e integração para garantir que os bots funcionem conforme o esperado é fundamental, juntamente com testes de aceitação para validação final. Além disso, a criação de indicadores de desempenho (KPIs) e métricas ajuda a medir o impacto da automação.