How can you design and configure RPA workflows effectively in the development phase?

Recognizing automation opportunities within a process is the first step in designing an effective RPA solution. Creating a detailed process map or flowchart provides a visual representation of the entire workflow. This map helps developers and stakeholders gain a comprehensive understanding of the process, including decision points, dependencies, and data flows. Knowing the data inputs, outputs, and transformations within the process is crucial. This understanding guides developers in configuring data handling and manipulation tasks effectively, ensuring accurate and reliable outcomes. Critical and high-volume tasks are often prioritized for automation to achieve maximum efficiency gains.

Understanding the process is likely a part of development lifecycle. It helps to identifying suitable processes for automation,designing & developing automation scripts,testing,debugging and deploying the automated solution. Also, helps divide the automation process into Modules & prioritizing interms of ROI too. Interms of designing helps to go with attended or un-attended solution based upon the process ->Helps to draw PDD & SDD with good design/approach ->Evaluate the suitability of identified processes for automation ->Environment Setup,including the installation of the selected tool,integration with other software ->Understand the decision points,data inputs & outputs. Design the automation flowchart or workflow based on this analysis

In my view, to create a digital worker I would like to be a manual worker to under the process end to end. If we would participate in the manual work then we can identify the application behaviours and risk factors in the process. Also participation in the manual work can make us to easily identify the exceptions. Then go with preparation in the to-be as per as-is. This makes us simple to identify the complexity and prerequisites for the process to develop.

We always initiate our RPA design with a fast-forward video to present a clear and simplified visual representation of the intended automated process, ensuring alignment across all stakeholders. Following this, we employ tools like Visio for detailed workflow diagramming, which allows us to meticulously break down the process into logical components. Each component undergoes its own sub-analysis, where we scrutinize for potential optimization areas, dependencies, and bottlenecks. This granular approach not only enhances our understanding of both the broad and detailed aspects of the process but also fosters collaborative input and feedback, essential for refining our workflow diagram.

In my experience, this phase is one of the most important for a successful RPA project. My recommendation is to design customer journeys based on the current and future operation, based on the organization's strategy. As a second step, I recommend identifying and listing the activities or steps that have a dependency or a stopper derived from manual activities. As a third step, it is necessary to carry out a high-level analysis taking into account, among others, whether they have a digital input, defined business rules, a digital output. Finally, I recommend prioritizing by complexity and benefit according to the quantitative and qualitative benefits to determine the first processes to be automated.

Choosing a right tools on development phase is crucial for the success & efficiency of automation projects ->Tool should integrates seamlessly with existing systems & applications ->Allowing both technical and non-technical users to create & manage automation processes ->RPA tool that scales according to the organization's needs & tool should be capable of handling an increasing number of processes and workflows ->Prioritize tools that adhere to security standards and compliance requirements ->RPA tools with cognitive abilities,such as natural language processing & machine learning,enhance automation capabilities. Integration with AI ->Assess the availability of a supportive user community and robust customer support from the tool provider

Test each RPA tools vendor's ability to uniquely identify and robust automate your business users core apps (include the hard apps (old fat clients, thin clients, complex web, Java, dynamic web pages). Just testing a few easy apps proves nothing and likely disappoint later. This won't take long to test most of them and if it does, it's the wrong RPA product. Vendors try to get you to skip this. If your apps change frequently, build a test and then run it against different app versions to see how robust it is. Remember, it's the breadth of your OWN apps the RPA product actually works with, not just the vendor saying it works with that will score you the most success.

After more than 8 years of experience in RPA, I recommend to my clients to evaluate a tool based on the following perspectives: Deployment: Cloud or on-premises Security: Certifications Scalability: Roles and profiles Democratization: Programming language Integration: Connection with business applications

In today's landscape, RPA tools share many similarities, reaching a point where they can all automate most applications/systems within organizations with slight differences. So, how to choose? Consider three aspects without a specific order: Technical: Does the tool address my specific needs? Should the deployment occur in my infrastructure, or can I utilize the vendor's cloud? Besides solving my problem, what complementary features does the tool provide? Cost: Does my organization have any agreements that could secure a better price for licenses/solutions? How does it compare to the competition? Ease of use: Do I expect it to be used by citizen developers from the business team, or do I want a dedicated technical team?

Choice of tools is also a work made easy step to take in developing RPA. This step is a very crucial step especially in this digital age. There are tools like Uipath, Automation Anywhere, MS Power Automate, Blue Prism and many others available to choose from depending on your business needs and budget. Your choice of tools should factor in operational regulations, customer expectations, stakeholders desires.

You cannot expect to implement a successful design without first running through the default flows of each process AND as many variances as your users can recall and show you (they will NOT likely be documented). Even then, you will NOT cover them all. 1st plan for exceptions as the norm. This is where attended RPA comes in because your bots will always work, by calling on the human when they get stuck. Log these exceptions & put them into the automation/design queue. Eventually (maybe) these bots can move to unattended RPA. If you apply this to the high volume/costly processes you can use the short term ROI to fund the rest. You almost cannot fail with this approach but since not all RPA vendors do attended well, they don't share this.

1. Think of end to end scalable solution: - Start by thinking about the whole solution. What's the end goal? 2. Break it Down: - Make it simpler by breaking the solution into smaller components. 3. Step-by-Step Logic: - Use loops and conditions for the building business logic 4. Handle exception Smoothly: - Include safety nets (try-catch blocks) to catch and deal with error without crashing. 5. Follow the best practices framework - Use frameworks like REFramework. Modify it as per your need and architecture

The most important thing in this phase in an RPA project is to ask the right questions to the user. For example: What is the goal of the process? Who uses the output of this process? What value does this process add to the area's objective? What or who depends on the correct execution of this process? Based on the previous answers, I recommend to consultants to challenge the current process and define the to-be model, always taking into account the organization's policies and aligning with the business area strategy and, if possible, with the organization's strategy.

N?o há como implementar uma boa automa??o sem conhecer e desenhar bem o processo e todos os seus possíveis caminhos. Quando nos deparamos com dúvidas durante o desenvolvimento há um grande impacto na produtividade pois muitas vezes é necessário reunir-se novamente com a equipe responsável pelo processo para sanar aquela dúvida. Entretanto, se houvesse um desenho bem completo de todo o fluxo, isso já n?o seria um problema pois quase que certamente ele já estaria mapeado

Establishing precise triggers, loops, and error-handling mechanisms in your code is essential for robust performance. I advocate for modularizing the code into distinct segments. This approach allows for effective handling of failures with retry mechanisms, enabling seamless flow execution, testing, and proper deployment.

Some RPA vendors now let you separate the element identification from the workflow, or create mini reusable workflows themselves.. This is key because if done right, the mapping and integration in each and every app you automate will become reusable (common RPA workflows also become reusable here (login, search, update, note taking, alerting) and can be built by inheriting the elements already built. Then, say an app changes that requires a bot change, once done, all upstream automations will automatically continue to work. Otherwise, apps that change can break so many bots, your team is then inundated with the common "bot breakage" syndrome.

Attended RPA still requires testing but if built right, the testing is simpler because you roll out into controlled user groups who can continue to work even if part of the automation process blips. The human can continue manually to get the process past the blip and the bot can carry on again immediately it sees where to pick up. Since again, few RPA products do attended RPA this well, they steer you to automate most, if not all of the flow with unattended RPA from the outset. But this is risky, costly and doesn't necessarily return the largest ROI anyway. Involving IT and change control (internal and external apps) is crucial because you can't test, until the change happens - sometimes only when app is LIVE!!!!

One key challenge is managing and dealing with dynamic data. Often real-world processes require variable data formats or dynamic inputs, making it challenging to maintain consistency. One way to address this is implementing robust data handling strategy. Utilize variables and parameters dynamically, allowing your workflows to adapt to varying scenarios. Also, establish clear communication channels with stakeholders to stay informed about any anticipated changes in data structures or formats.

Comments, Comments, Comments! All code, even if low-code/no-code, need to have comments. The process documentation should have been done upfront, this is different. Documenting the flow should have details on how it works, what happens if we need to add something, change something, etc. The documentation should be uniform, starting with the same details each time: By (who), Purpose (why), version (when), Inputs (or Precedents) and Outputs (or Dependents) (what), References (where to look), common issues/resolutions such as errors that would be encountered. Ex. If you have a new account number, ensure to add it to this mapping table. In the end, you need enough information to fix/resolve/avoid issues down the road. Happy Automating!

This is crucial for when you or someone else revisits this RPA workflow. Try to: - Elaborate on technical jargon - Keep naming and styling conventions consistent and simple - Be concise, and expand details only when necessary Furthermore, it may be useful to point out any issues you encountered when developing that process so Devs in the future can be aware of it.

1. Select Suitable Processes: 2. Define Clear Objectives: 3. Optimize Processes: 4. Choose the Right RPA Tool: Select an RPA tool aligned with process complexity. 5. Design Scalable Workflows: Create adaptable workflows for future changes. 6. Thorough Testing: Rigorously test workflows in diverse scenarios. 7. Document and Collaborate: Document decisions and collaborate with the team. 8. Ensure Security and Compliance: Adhere to security standards and compliance. 9. Version Control: Implement version control for tracking changes. 10. User Training: Train end-users and stakeholders on automated processes. 11. Monitor and Maintain: Set up monitoring and a maintenance plan for regular updates.

Here are some of the ways to design RPA workflows effectively: 1. Clear Requirement gathering 2. Detailed PDD(Process Definition Document) 3. Sufficient amount of test data to test all the scenarios. 4. Applying RPA best practices 5. Breaking down complex process into modules. 6. Robust and Scalable To-be solution or SDD.

Training & Knowledge Transfer Essentials! ??Beyond the code, prioritize Training & Knowledge Transfer. ??Training sessions foster collaboration and shared understanding. ??Cross-training ensures everyone comprehends the entire RPA ecosystem, reducing dependencies. ??Key benefits: ??Bottleneck Reduction: Disperse knowledge to eliminate single points of failure. ??Enhanced Collaboration: A trained team fosters seamless innovation. ??Agile Adaptation: Pivot swiftly in the dynamic RPA landscape, staying ahead. ??Invest in success! Training and knowledge transfer are crucial investments for the longevity and triumph of your RPA initiatives. #RPA #Automation #Collaboration #Training #KnowledgeTransfer #Innovation

Reimagining the process and eliminate waste. Automation of process is an opportunity to assess current process and identify the waste to lean or simplify it. Simply automating existing using RPA could lead to challenges in future due to complexity and frequent change in base application structure.