In part one<\/a> of this two-part miniseries, our fictional example company embarked on a journey to build an RPA program. Starting with a small proof of concept, we ended up with 10 bots and a Center of Excellence<\/a> (COE) to support our growing capability. We\u2019ll pick up the story in part two and show how we went from a fledging COE to reach full maturity.<\/p>\n As a reminder, each organization is different, and the path to success will vary. We\u2019re outlining one possible progression based on our experience and observations. I do not mean for this to be a roadmap but a guide to inform your own journey and anticipate challenges.<\/p>\n Our COE is doing great, but we still can\u2019t seem to keep up. Every department wants bots, lead times are getting longer, and more effort must be spent on production support. This is a great problem \u2013 there are loads of opportunities to create value \u2013 but it\u2019s a challenge we must address.<\/p>\n As the COE continues to buy more licenses and deliver automation, we tackle our capacity issues by more fully utilizing employees from departments looking to benefit from automation.<\/strong> Sure, we started doing this when we launched the COE, but this phase is about turning them into full-fledged RPA champions.<\/p>\n It starts with training, not just for RPA awareness but also for business analysis and even citizen development<\/a>. Standard training can be self-service or even used by champions within each department to engage their own team members. Next, we encourage the federation of duties, so each department not only identifies its own candidates but also assesses, prioritizes and even documents them. Departments now have a toolkit for onboarding to the COE as well.<\/p>\n We\u2019re still doing the technical work, but business empowerment signifies a major shift from the COE out to the business. It also means we consider RPA for virtually every operational enhancement. In other words, RPA is moving from tactical to strategic.<\/strong><\/p>\n Had we failed to address these growing pains, we could\u2019ve expected a drop in quality with too much to manage, seen a decline in interest due to slow results, or both. Some departments lobbied not to take ownership at all \u2013 why can\u2019t IT just do it? \u2013 but RPA programs can and should lean on business users, process owners and folks outside of IT. And where some programs may have stalled or plateaued, we\u2019ve managed to keep excitement high and continue growing.<\/p>\n Flash forward: RPA is thriving. Departments across our company are largely self-sufficient, but we\u2019ve once again become victims of our own success. Problems now revolve around the technology platform itself, which has become unwieldy even for our experienced COE team.<\/strong> There are three central issues: reporting, maintenance and reusability. We\u2019re expanding the COE technical team, but that\u2019s not enough by itself. So, how do we streamline our processes and use automation to manage infrastructure better?<\/p>\n Our technical maturity ushers in new COE capabilities, most notably widespread attended automation that quickly increases bot volume. Though we\u2019ve used attended bots for targeted processes before, we\u2019re much more comfortable deploying and managing them broadly across the organization. At this point, everyone is confident in RPA at scale, which also means we can tackle more critical automations and ensure business continuity.<\/a><\/p>\n It\u2019s taken a couple of years, but, suffice it to say, RPA has become a mature and prevalent solution in our example company. The next step is enterprise automation, where we add tools beyond RPA to our core automation competencies. Though we\u2019ve built automation with other tools along the way, until now, it\u2019s been opportunistic and not part of the core strategy. Time to change that! Here are the areas we integrate it into strategy.<\/p>\n Adding these tools isn\u2019t easy because they require different skills and collaborating with more teams (for example, we worked with data scientists on a custom ML model). Not only that, but they target the activities of knowledge workers, which gets more pushback than the rote, mundane tasks targeted by RPA. It also means increased support costs, increased licensing costs and making a business case to justify these increases.<\/p>\n Nevertheless, the benefits are clear. Where RPA limited us to only fragments of an end-to-end process, we\u2019re able to capture a lot more of each process by combining complementary automation tools. Furthermore, we can now tackle processes that were totally beyond RPA\u2019s reach \u2013 like human-centered processes \u2013 making automation not just a goal but an expectation for almost every process improvement.<\/strong><\/p>\n Mission accomplished. Just kidding (sort of). The work is never done.<\/p>\n\n 20 Bots: Grow Without Growing<\/h2>\n
50 Bots: Enterprise Scale<\/h2>\n
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100 Bots: RPA in Your DNA<\/h2>\n
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