RPA Deployment Challenges

You set up a Process Automation CoE to streamline workflows, boost ROI, and accelerate digital transformation—yet you’re still wrestling with low-impact initiatives, fragmented tech stacks, and skill gaps that stifle progress. Sound familiar? In every RPA CoE, these roadblocks are all too common. But what if you could unlock a blueprint that not only crushes these obstacles, but also turns your CoE into a well-oiled, innovation-driven powerhouse that consistently delivers tangible business value? Pain Points in Process Automation CoEs 1. Lack of Vision and Strategy: Misaligned objectives and absence of a scalable automation roadmap. 2. Limited Stakeholder Buy-In: Resistance to change and poor communication of the CoE’s value. 3. Weak Governance: Lack of policies, standards, and compliance frameworks for automation. 4. Skill Gaps: Inadequate technical expertise in advanced automation, RPA, AI, and ML tools. 5. Fragmented Technology Stack: Poor integration with legacy systems and underutilization of AI and predictive analytics. 6. Poor Process Selection: Automating low-impact processes with minimal ROI. 7. Scalability Challenges: Limited reusability of automation components across business units. 8. Change Management Issues: Resistance to automation and insufficient employee upskilling. 9. Inadequate Performance Monitoring: Limited tracking of ROI, productivity gains, and KPIs. 10. Security and Compliance Risks: Gaps in data governance and adherence to industry regulations. 11. Leadership Deficiency: Absence of a skilled technical leader to align CoE with business goals. Strategies to Strengthen the CoE for ROI and Growth 1. Set Clear Goals: Align CoE objectives with organizational KPIs and define a phased automation roadmap. 2. Build Robust Governance: Standardize policies, compliance frameworks, and success metrics for sustainable automation. 3. Foster Stakeholder Engagement: Conduct workshops, showcase automation success stories, and secure leadership buy-in. 4. Invest in Skills: Upskill teams in RPA,AI/ML. 5. Modernize Technology: Integrate tools into a unified platform and leverage advanced capabilities like AI and IoT. 6. Prioritize High-Impact Processes: Use data-driven methods to identify and automate processes with maximum ROI. 7. Plan for Scalability: Develop reusable automation components and build a sustainable pipeline of opportunities. 8. Change Management: Reskill employees, address resistance, and communicate automation benefits effectively. 9. Monitor Performance: Implement dashboards to track KPIs, optimize processes, and measure ROI. 10. Ensure Security & Compliance: Strengthen data governance and adhere to industry-specific regulations. 11. Appoint Skilled Leadership: Hire a seasoned CoE leader with expertise in process automation, AI, and strategy. #IntelligentAutomation #RPA #AI #ML #DigitalTransformation #CoE #AutomationROI #Leadership #cognitbotz #Innovation #AutomationStrategy #BusinessGrowth

RPA gets a bad rep for being unstable and unreliable. It can be that, sure. However, in the vast majority of cases that's not really because of the tool, but rather because of poor implementation. It can also be because of processes being automated when they shouldn't, or being automated AS-IS. But even in the nice cases of reviewing and potentially re-engineering the processes, there are certain practices in RPA that make those flows much less reliable. If your RPA flows use any of the following practices, they'll most likely require quite a bit of support and maintenance: 📌 OCR (especially basic, non-AI based Windows/Tesseract or similar engines) 📌 Image recognition for UI automation 📌 Co-ordinate based mouse activities 📌 Keystrokes In most cases, these are used either as a way to build the solution with minimal possible cost (such as using a free OCR engine instead of something that may incur some additional cost for consumption) or as a way to automate a UI that isn't exactly automation-friendly. In some cases there simply is no other option - you either need to go this route or cancel the entire project. This is usually the case with the not-very-automation-friendly UIs. With OCR there's always a better choice and it's just a matter of accepting some extra cost (or re-engineering the process to avoid scanned documents altogether). But in most cases, there usually is an alternative. First of all, even among the bad practices, some are worse than others. Co-ordinates and OCR for UI automation are pretty much the worst. Image recognition is the next worst thing, as it relies heavily on screen resolutions, element classes, popups, etc. Keystrokes are the lesser evil of the four. They can usually be sent relatively reliably, and there are ways to make them work or at least check and verify if they worked properly. And that is the other important topic here - if you must use any of these, you must also build in additional rollback/fallback functionalities, as well as plenty of checks to verify that whatever the flow was supposed to achieve was actually achieved. This will slow those flows down, sure, but it will at least make them a bit more robust. And when using any of these practices, speed should always be of much lower priority than any robustness, traceability and quality. That's simply how it is. You don't want lots of work items being processed quickly but incorrectly. You'll just have more work to do in fixing all those bad transactions manually afterwards. You'd be better off doing the work manually in the first place. But if you implement it properly, prioritize functionalities that offer more reliability, add checks and verifications, as well as fallback options, and structure your flows properly in a way that it is easy to re-run a certain batch of transactions through a certain step that may have failed, instead of the entire process, then it could really work, and your maintenance needs will be much lower.

𝗬𝗼𝘂𝗿 𝗥𝗣𝗔 𝘄𝗶𝗹𝗹 𝗰𝗿𝗮𝘀𝗵 𝗮𝗻𝘆𝘄𝗮𝘆! You can not avoid this simple fact when automating systems out of your control. Instead of looking to RPA errors as a consequence of some weakness in your team, you should address it as a part of the process. Robotic Process Automation (RPA) error handling has its particularities. Usually, we develop UI automation in systems that can change for multiple reasons. Therefore, in cases like web systems that are updated very often, RPA crashing is part of the game. Since it is tough to predict and prepare for those changes, it is better to detect and react faster to re-deploy a new version of your automation with less downtime. 𝗥𝗲𝗮𝘀𝗼𝗻𝘀 𝗳𝗼𝗿 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 𝗶𝗻 𝗨𝗜 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗔𝗱𝗱𝗿𝗲𝘀𝘀𝗲𝗱 𝘄𝗶𝘁𝗵 𝗥𝗣𝗔 In most cases, the RPA team can not predict or be aware of changes in the target systems the bots will face in the subsequent execution, as we discuss as follows. 𝗡𝗲𝘄 𝗦𝘆𝘀𝘁𝗲𝗺 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 Many modern systems deliver updates without user consent. It simply updates its features, UI experience, and informs users through a release note or a log of changes. The intention is to constantly deliver system improvements to users who can figure out how to use the system after minor changes in the UI. However, if your bot automates UI actions based on component ID or is sensitive to component layout, it will no longer work properly. 𝗡𝗲𝗲𝗱 𝘁𝗼 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝘁𝗼 𝗔𝗰𝗰𝗲𝘀𝘀 𝗡𝗲𝘄 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 In some systems, users need to authorize upgrades or do it manually, giving more control to the IT department regarding system changes. It is not just automation; many ERPs have layers of customization and integrations that system updates might impact. Nevertheless, updating systems is a good practice to reduce security risks, improve performance, and have access to new features. Large companies use several systems in each department. Therefore, it is common for RPA teams to get surprised by systems upgrades by IT teams without being notified. 𝗨𝘀𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 𝗮𝗻𝗱 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗜𝗺𝗽𝗮𝗰𝘁𝗲𝗱 𝗯𝘆 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Many systems support field and business rules customization for better modeling your company's needs. It is not unusual to see your bots crashing due to some new customization that your team was not notified. Your company departments want autonomy to get the most out of the systems they use. 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺 𝗨𝗽𝗱𝗮𝘁𝗲𝘀 𝘁𝗵𝗮𝘁 𝗗𝗲𝗺𝗮𝗻𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗨𝗽𝗱𝗮𝘁𝗲 Not every system update will crash your bot... (...) === 𝗙𝘂𝗹𝗹 𝗔𝗿𝘁𝗶𝗰𝗹𝗲 - 𝗬𝗼𝘂𝗿 𝗥𝗣𝗔 𝘄𝗶𝗹𝗹 𝗰𝗿𝗮𝘀𝗵 𝗮𝗻𝘆𝘄𝗮𝘆 – 𝗠𝗼𝗻𝗶𝘁𝗼𝗿 𝗮𝗻𝗱 𝗿𝗲𝗮𝗰𝘁 𝗳𝗮𝘀𝘁𝗲𝗿 𝘁𝗼 𝘂𝗻𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗮𝗯𝗹𝗲 𝗲𝗿𝗿𝗼𝗿𝘀 https://lnkd.in/dUPhVRuW #rpa #roboticprocessautomation #intelligentautomation