When RPA first came on the scene a decade ago, many companies believed it would be easy to implement and they would reap the benefits more or less instantly, with minimal effort. But the reality is very different. Many companies have been left feeling underwhelmed by its impact.
At its core, RPA is a brilliant notion; it allows businesses that currently have costly processes that are bottlenecked by a lack of resources to unlock the potential of scaling their business. After all, a robot doesn’t rest, a robot doesn’t eat, and a robot can work when all your employees are asleep. It sounds simple: you train a robot to do some work that real people currently do, and then those people can move on to purposeful value elsewhere.
However, the realities of RPA are very different.
The missing step in RPA implementation
One key consideration when implementing RPA, that is so often overlooked, is identifying the processes that need to be translated into an automation This can take significant amounts of time and knowledge. Also, people’s actions are often unconscious and extracting all the steps or information can be laborious and require several iterations.
The next aspect to consider is whether you upskill the person to create the RPA process, or deploy an RPA Engineer – for example, someone that understands how to implement processes in a specific RPA tool and knows how to translate that into a functional process. In an ideal world, this is all done by the same person, someone that expertly understands your processes, and someone that is also capable of driving or building an automation. In reality, this often means that a business has to hire Automation Engineers or train current employees.
Once you’ve finally managed to convert a current process into an automation, you think “great,” but then what happens when something goes wrong or changes? You’re back to needing the domain expert and the RPA Engineer and the process starts again. Does this scale any better than hiring more people? Does this mean your business can explore new ventures or markets? Or are you now bogged down in implementing the processes that have the highest return? What’s more, have you been locked to a specific vendor and a way of implementing and running those automations?
Processes can’t progress without people
You may think that by using robotics within your processes, you eliminate the need for human input, but this is a misconception. Processes have been developed, for the most part, at the human scale. Time frames are dictated by the physical availability of people, meaning that processes naturally inherit those time gates. Certain parts of some processes (advanced reasoning, customer response, interactivity) cannot be done by a robot.
So, now your hyper-efficient shiny rocket ship of a process is being held captive; it cannot progress without people, and they leave at the end of the workday. Often this reliance on humans can be accomplished in automations if they are built with that in mind – smaller more event-driven actions, not long linear flows. Think of manufacturing, it used to be long brittle workflows that were developed over decades. Now the best and most efficient companies use advanced logic and smaller sets of tasks that can re-order to adapt and meet demand.
Automating at scale is a marathon not a sprint
There are other costs to automating at scale, even when successful. For example, if you have 50 employees, they each need a specific system to perform their jobs, so that’s 50 software licenses. Suddenly, you implement automation and there are hundreds of robots – do they share the same license pool and simply operate faster? If so, this introduces a whole set of problems around orchestration and optimization. Or, perhaps you pay for additional licenses? In an ideal world, the cost would be outweighed by the profits generated by the robots.
All of this has meant that the expectations of RPA haven’t yet lived up to reality. There is an innate desire, probably an intrinsic human need, to optimize that exists at a cellular level. For example, look at the late 1800s and the Industrial Revolution. Right now, we are at the same stage as those steam-powered industrial mills and textile companies, which needed many tiny hands to stay the course of the machine. We had visions of cars, planes, and the future even then, but unfortunately, even with the advent of steam and then a consensus agreement that it was vital to forge onward, it took us decades to align with and realize our expectations.
Revolution and sleeping giants
The RPA model must be simplified. Currently, building and implementing an automation is costly: allocating people, implementing the system and testing. What if a company built discrete actions that integrated with the most commonly used technologies and workflows that closely aligned with known outcomes of a given industry or sector? What if that company used a technology that was intrinsically baked into or already there, lying dormant in your environment, such as a sleeping giant?
We could use technologies like Power Automate, which is common across the Microsoft landscape and customer environments, to deliver pre-built actions and workflows that align with industry/sector requirements that are resilient and robust and can be consumed as and when needed. This breaks the cycle. No longer does every company in a given sector need to employ automation engineers and have domain experts. This really would make RPA easy.
RPA isn’t the main character, it’s a supporting role
Finally, if we are to progress with RPA, we need to get realistic about its capabilities. As it stands, RPA alone is not enough to transform and streamline your operations, super boost efficiency and create extra resource capacity. A holistic solution like Enate’s orchestration platform brings it all together. Orchestration enables you to view and manage end-to-end operations, assign tasks to the right human or digital worker and complete work consistently/on time. It’s the umbrella tool for technologies like AI, IDP and RPA to connect with and complement. Orchestrations value proposition will become more evident as awareness grows and more players come to the market.
As time goes on, Automation Centres of Excellence and RPA as an industry will likely advocate for orchestration. They’ll tackle complex, highly variable work areas where legacy BPM tools fall short because they require a high level of standardization and/or very long implementation times.
Watch this space.
