How can you govern RPA effectively?

As a UiPath MVP and Technology Architect in Singapore, I prioritize RPA initiatives with a strategic approach: Alignment: Align RPA efforts with business goals for maximum impact. Assessment: Evaluate processes based on complexity, value, and risks. Risk Management: Mitigate risks associated with high-priority processes. Value Focus: Prioritize processes offering tangible benefits and value. Integration: Plan for seamless integration with existing workflows and systems. Resource Optimization: Optimize resource allocation to avoid wastage. This ensures an efficient and effective RPA implementation that aligns with both immediate automation needs and long-term organizational success.

# Define RPA Strategy and Objectives Clearly articulate the strategic goals and objectives of RPA within the organization. Align RPA initiatives with broader business objectives to ensure that automation efforts contribute to overall success. # Establish a Governance Framework # Robust Risk Management # Data Privacy and Security # Performance Monitoring and Measurement # Change Management # Resource Management # Training and Skill Development # Continuous Improvement # Documentation # Vendor Management

In my humble experience , I have seen it as two step process : Step 1 : Setting up # Establish, measure and report metrics # Maximize Value delivered # Right fit Process identification and prioritization # Buy in - IT, Compliance, Security, Procurement etc # Efficient use of automation vendors, Tools, and Licenses # pool of quality resources (all phases) # Standards for Design, Implementation & Support # Reuse of robot assets and code Step 2 : Scaling up # Establish support of Advisory (COE) & E2E Implementation # Strengthen in-house talent eco system # Proactive Enterprise Strategy # Developing/ defining in-house/ enterprise approved automation toolkit # Generate business impact instead of just a cost saving tool

Involves streamlining and optimizing business processes through the use of technology. Defining the scope of automation is crucial to ensure that efforts are focused on the right areas. This includes identifying the specific processes, tasks, and activities that will be automated. Process Identification - Clearly identify the target processes for automation, considering factors such as repetitive tasks, rule-based activities, and high volume. Prioritization - It involves determining the order in which processes will be automated based on factors such as business impact, complexity, and dependencies. Prioritization ensures that automation efforts align with organizational goals and deliver maximum value

In my experience it is always good to identify the process not only on the complexity but also by looking at the business need and what specific problem it solves. This not only helps the business need but also gives confidence to the end user that automations can work along with use and can enhance the output that can be delivered by an individual or a team. Gaining the business confidence plays an important role in increasing the effective use of automation. #insights #scope # prioritize #rpa #business

To govern RPA well, design your code smartly by following best practices. Use reusable parts and break big tasks into smaller, manageable ones. Make rules in workflow analyser for checking workflows, and only use approved official packages for development to keep things safe and in line with regulations. This helps create a secure and compliant environment.

This is the next phase in the process automation lifecycle where you need to design and development your solutions by enforcing best practise. Here are some best practices on this area 1. Follow SOLID principle whenever possible to apply in your solution 2. Ensure coding standard by enforcing workflow analyzer rules or similar mechanism based on the RPA platform 3. Development your solution with security aspects in mind. Means avoid capturing or storing confidential information anywhere 4. Develop your solution with test friendly capabilty

There needs to be one person responsible for the success of each project. This is usually best when it is a head of a department where a process is being automated within. This individual can then go to more technical folk when they have questions or need assistance. However, they are the ones with the most to gain & therefore ultimately responsible for the success of the automation.

I would say that this step is highly significant in effectively governing RPA by establishing a clear and comprehensive design process. Clearly define the scope of the automation project and the specific objectives that it aims to achieve. Once the RPA solution has been designed, the next step is to develop it according to the approved design specifications. Throughout the design and development process, it is crucial to maintain effective governance practices.

In my experience using RPA is easy is what everyone thinks but using it in the right way is the key and that is where most of the people struggle with and loose the game. Making a good code is done by most. But when you make it reliable and maintainable that it when it becomes a great code. So think from the perspective of when a change comes or when a support person looks at the code is he able to understand and fix it. Adding complex logic is easy for many coders but adding the right comments, explaining it and making it reusable and maintainable is where the true coder in you would be unleashed. Last but not the least, is to choose the right mix of lowcode features and code. striking this balance is important. #rpa #develop #coder

When it's coming to deploy and monitor area, CI/CD are integral components in the software delivery lifecycle. CI is a contemporary approach embraced by software developers to enhance the efficiency of code changes, fostering spontaneous and collaborative work in a better manner. The implementation of CI is help to identifying and addressing issues early in the development cycle, reducing the cost of corrections. Simultaneously, CD is an automated process consisting of diverse technical stages wherein software undergoes building, testing, and deployment to various test and production environments. CI/CD streamlines and accelerates the software delivery process, ensuring a more effective and expedited delivery of software products.

Build a Deploy strategy such that it is non-intrusive as much as possible and can be deployed quickly, effectively and efficiently. The use of automated tools is thus a must - CI-CD pipeline tools are a good example for seamless automated deployment. RPA objectives do not end at deployment but also extend to monitor the change delivered. Whether the change serves the purpose and has not caused any other unintentional side effects. Whether there are any systematic or performance issues in the process delivered. Any corrections found therein must be accounted for and corrected at the earliest keeping the relevant stakeholder informed.

When it comes to this deploy as automations have matures enough we have a CI/CD pipeline that would ensure proper compliance is met. This also helps in tracking the changes and also for code reviews and deployment of your dependencies as well Now in monitoring, there might be instances where the automations might get stuck. Identifying, fixing and proper communication to the end user is where we make the difference. There is a scope of improvement always, try to identify them and improvise on the user experience,on the time taken by the bot etc. As the number of automations grow monitoring might be chaos think of it as an oppurtunity to build a monitoring bot. At the end even RPA developers need a breathing space.

Deploying RPA solutions is like orchestrating efficiency. Post-build, use a robust platform for deploying various bot types—attended, unattended, or hybrid—managing their deployment, scheduling, execution, and performance. Vigilant monitoring, employing metrics and dashboards, ensures efficiency, effectiveness, and accuracy. It acts as a guardian, swiftly identifying and addressing anomalies or errors, ensuring sustained delivery of expected results and value. This vigilance solidifies RPA solutions as transformative assets in the organizational ecosystem.

Well, Deployment step should include 1. Environment preparation 2. Bot deployment 3. User training 4. Post-deployment testing While Monitoring include, 1. Performance monitoring 2. Resource utilisation 3. Exception handling 4. Compliance monitoring 5. Continuous improvement

Continuous monitoring of automation solutions will aid us in comprehending the gaps within the automation process. The review will assist us in understanding the challenges faced in the product environment. The ideal approach is to monitor both business and transactional statistics through the RPA Analysts application. For instance, UiPath Insights is an RPA analytics solution that empowers your business to track, measure, and manage the performance of your entire automation program.

Totally agreed . Technology is evolving rapidly and the way everything is implemented is also changing at that speed. Nothing is a permanent one. Even an automated solution needs improvement via various lenses. Let it be the end user experience, an upgrade on a system, new ways of dping the samething , add more to what is already automated, chaining varioud automations together to make it an enterprise level solution , the list does not end here . The possibilities are endless and we need to embrqce it and welcome. One important part is to Foster collaboration between the business and IT teams. Ensure that IT is involved in the planning and execution of RPA initiatives to align with broader IT strategies and infrastructure considerations.

Regularly reviewing and enhancing RPA solutions is more than a practice—it's a commitment to aligning with dynamic business needs. Gathering insights from stakeholders and users offers a holistic view, while data analysis informs refinements. Embracing continuous improvement methodologies ensures agility in addressing challenges. This dynamic governance approach guarantees relevance, responsiveness, and resilience. RPA governance demands ongoing collaboration, maximizing the potential and benefits of solutions in tune with organizational evolution.

In the continuous cycle of reviewing and improving RPA implementations, evaluate performance regularly, integrate user feedback, refine processes, analyze errors, and provide ongoing training. Benchmark against industry standards, conduct periodic cost-benefit analyses, assess scalability, and remain vigilant for new automation opportunities. Keep documentation updated for efficient knowledge transfer and troubleshooting. This ensures that RPA efforts consistently align with business goals and deliver value.

Regular Review: Periodic assessments to align RPA solutions with evolving business needs. Feedback Integration: Incorporating feedback from stakeholders, users, and customers. Data-Driven Analysis: Utilizing data insights to inform decisions and identify trends. Outcome Evaluation: Measuring the effectiveness of RPA solutions through outcomes and impacts. Continuous Improvement: Implementing lean or agile methodologies to address gaps and optimize solutions. This approach guarantees that RPA solutions remain relevant, responsive, and resilient, maximizing their benefits for organizations.

When it comes to RPA governance, adopting a centralized application is the best approach. For example, within the UiPath Ecosystem, UiPath Automation Ops serves as a centralized, web-based platform. It provides a straightforward and convenient means to manage and implement governance policies based on user profiles, and to oversee the feeds available within the organization. Automation Ops is an administrative feature accessible in UiPath Automation Cloud.

There are many ither things to be considered and few are as follows 1. Training and Development - A major part is to improve on the skill set 2. Performance metrics and Reporting - Any system let it be good or bad, you dont know till you analyze it and show it to a broader audience 3. Vendor Management - Large enterprises rely on many vendors to develop their automations and it is important to have an effective strategy around it to avoid any deviation to organizations long term goals 4. Standardize Development Practices - This includes coding standards, version control, and documentation. 5. Center of Excellence (CoE) - Setting up a dedicated team helps in may ways to standardize,scale, develop, foster training and grow the team

My view on Key Pillars of Effective RPA Governance 1. Establish Clear Governance Framework 2. Prioritize RPA Opportunities 3. Structured Design and Development 4. Robust Change Management 5. Strict Security Standards 6. Continuous Monitoring and Improvement 7. Foster Collaboration and Communication 8. Adapt to Evolving Technology

Effectively governing RPA involves establishing clear policies, defining roles and responsibilities, and ensuring compliance. Develop a robust framework for RPA deployment, emphasizing security and risk management. Regularly audit processes and monitor performance. Foster collaboration between IT and business teams, encouraging communication and knowledge sharing. Implement change management practices to adapt to evolving needs. Continuous training and updates on best practices contribute to a well-governed RPA environment.

1.Establish a Center of Excellence (CoE): Form a centralized CoE to oversee RPA initiatives, define best practices, and provide guidance across departments. 2.Develop RPA Governance Framework: Create a governance framework outlining roles, responsibilities, policies, and procedures for RPA implementation, maintenance, and scalability. 3.Change Management and Communication: Develop strategy to prepare employees for the adoption of RPA, addressing concerns, and highlighting benefits. 4.Risk Mitigation and Continuous Monitoring: Identify potential risks associated with RPA and create mitigation strategies. 5.Continuous Improvement and Evaluation: Foster a culture of continuous improvement by regularly evaluating and optimizing RPA processes.