Robotic Process Automation (RPA) promises to replace mundane, low-value manual desktop tasks with robots, turning your enterprise into a well-oiled, people-free productivity machine. And sure, when it comes to automating clicks to reduce costs, RPA—deployed correctly—can definitely help.
But most enterprises have much bigger fish to fry than just keeping operational costs low and bridging technology gaps. And when it comes to actually delivering business outcomes—from on-time delivery to revenue growth or the elusive customer experience—RPA is really a small piece of a much bigger picture.
RPA stands for Robotic Process Automation: an emerging form of process automation technology which replaces repetitive manual work with software ‘robots.’ Traditionally, RPA has focused on simple tasks — what The 2019 Forrester Wave report on RPA calls ‘the rule of five for task automations’ — tasks that require fewer than five decisions, five accessed apps, or 500 clicks.
RPA is easily confused with intelligent automation. It’s been hailed as the ultimate time-saving, productivity-enhancing, headcount-reducing silver bullet — but it’s also automation for its own sake. It’s missing ‘smart’ learning capabilities. It’s essentially like Excel macros on steroids–someone else still needs to define whether automation is actually the most appropriate course of action to improve your processes in each instance.
For example, RPA can be used to match POs to invoices and goods receipts. It can’t optimize PO processes end-to-end to free up working capital. Achieving that kind of business outcome requires an order of magnitude beyond what RPA can deliver.
And while RPA needs to be deployed in the right places and at the right time, companies are still struggling to identify when and where that might be. One of our clients commented that their RPA teams often don’t fully understand the business processes they’re automating, while the process owners implement bots without truly understanding how they work. The wrong tasks or processes get automated, and you just replicate inefficiency — at speed.
Process improvement — or better yet, process excellence — is at the heart of achieving business outcomes. Smooth, efficient processes, whether manual, automated, or both, underpin every experience your business delivers. Google’s search engine, Netflix’ streaming services, or shopping on Amazon–these are all fantastic customer experiences, powered by equally customer-centric processes.
We all know that for companies to say competitive, they need to deliver on customer experience. To deliver on customer experience, they need outstanding processes. And to reach process excellence, you need to truly understand your processes, and focus on value-generating activities first–and then invest in the tools that will help you identify, remediate and remove the pain points obstructing the smooth running of your enterprise.
This is where Process Mining comes in. The technology leverages both business data (time-stamped event logs) and user interaction data to deliver a real picture of what processes actually look like. We’re talking every step in any given process — and all the actions people are taking in between those steps to make that process happen.
That living, breathing, moving snapshot enables enterprises to discover friction, remove it, and continuously monitor and enhance the impact of those changes on your business outcomes.
RPA is undeniably a part of that, streamlining user interaction tasks in the right places — places it becomes much easier to identify when you need visibility over what’s going on in your business. But it’s only one of the many tools at your disposal to achieve process excellence and implement a fully-integrated and frictionless process and systems landscape.
Sometimes processes need to be corrected, optimized, or orchestrated differently across multiple systems or departments, rather than simply automated. In fact, process excellence doesn’t actually require automation nearly as often as you might think.
We’re just at the beginning of the 4th industrial wave. The next level of automation will be unlocked when machine learning capabilities and artificial intelligence become smart enough to deploy RPA intelligently.
But to look at automation as the be-all and end-all is to miss the bigger picture–one where automation is only a single part of achieving process excellence. It’s a part that needs to be orchestrated in the context of that broader vision, alongside other tools that deliver what RPA alone cannot: visibility, intelligent optimization, and a direct impact on overarching business outcomes.
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