There is a snag with you and me: we both suffer from a condition: the human condition. It means we make mistakes, it means data that we help generate can be prone to errors. That is where RPA can enter the story. A number of organisations that have applied the technology have experienced disillusionment, robots might sit in a metaphorical cupboard, collecting dust made from ether, leading to claims that RPA has been hyped. But Sarah Burnett, executive vice president and distinguished analyst at Everest Group, has a different take.
Part of the problem lies with inflated expectations. Promise the earth and only deliver the moon, and there is a sense of disappointment. Say, ‘but it is so easy’ and individuals within organisations responsible for technology, CTOs perhaps can become cynics, converts to the RPA is hype mantra.
The 30% club
“Yet,” says Sarah Burnett, “we have actually done studies that show companies achieve about 30% cost savings.”
So that’s 30%, that does not feel like the stuff that the ‘RPA is hype’ narrative is made of.
Part of the difficulty lies with exactly what this 30% saving applies to. That’s “before and after automation, the cost of process before, compared with the process after,” explains Sarah Burnett. But how significant that cost saving really is, whether it is a one of those game changers, that the RPA hype would have us believe, depends on how big that process was in the first place.
She put it this way: “30% of a small process isn’t much.”
RPA: we take a look at UiPath, Blue Prism and Automation Anywhere
RPA and data
There is another difficulty. Some of these benefits are not so obvious.
Take data, there are moves afoot to include data in a balance sheet, try and put a value on it, but up to now, most of those moves have not really got passed the tip toe stage — as it were, the move afoot can’t get passed a foot. “There are qualitative intangible measures that a lot of companies don’t even measure yet. These include things like ‘I’ve created much more capacity, I’ve got fewer errors’.”
That is where data enters the story. For one thing, by having a robot carrying out tasks that were previously undertaken manually, more data is collected. For another, the data that is collected is accurate.
Too err is to be human, but as Burnett said: “If a person enters a bit of data, they can so easily accidentally switch some numbers. Fixing that error, the further down the process it travels, the more expensive it becomes. You could be having people, whose time is very expensive, chasing this error and trying to fix it, a long way down the process swim lane. Robots if they’re developed correctly and are maintained and run smoothly, will not make those mistakes. We are hearing from organisations that say they kept testing their robot apps and they never found a mistake once they’d tested it, it was 100% accurate …always.”
Give it time…and effort
Maybe part of the problem with the technology that has helped spawn the RPA myth argument lies with its newness. We all like the new, a brand new car, which has a mileage clock, saying ‘0,000.00’, but the moment we drive it down the road, the 0.00, becomes 0.01,’ the thrill begins to fall away, like petrol burning up. With RPA though, the problem is not quite like that. “It’s still a relatively young technology,” explained Burnett. “A lot of organisations are still learning about what to automate, how to automate and how to make the most of it. That seems to be where the challenge is, it’s not just about automating a few processes, and getting positive feedback, but how do you join these things up?”
RPA hype: scaling is the challenge and potential big reward
“At the moment, it’s still dabbling and small,” but the real challenge, and it is a challenge that has eluded some organisations, lies with scaling.
It seems the case for a large organisations that carry out extensive, repetitive tasks, is easier to make. Process driven organisations, such as banks or insurance firms, or where compliance requirements means certain processes need to be carried out time and time again, seem to be perfect matches for what has become known as unattended RPA — automating a long drawn out process, end to end. It’s a form of RPA that companies like Blue Prism set a lot of store by.
But you talk to other RPA players, companies like UiPath and Automation Anywhere, that sit in both the attended and unattended camps, and you hear predictions that attended robots, the type that can help an individual directly, more like a kind of software personal assistant, are set to surge in popularity.
RPA: the key players, and what’s unique about them
Burnett explained it thus. For unattended, for example, “there are telecom companies that are processing millions of transactions. So that’s one way of scaling, which is doing something that has naturally got high scale and you’re processing loads of things”
And for attended, “each robot might be doing small things, but you join them up. So you might not have the millions of transactions that telecom companies have, but you might join things up and manage to process millions of documents.”
Joining up all those small processes, creates one big challenge.
“We are now at a stage where organisations are trying to learn those things. How do I do it? Do I need a business process management tool to sit on top of my RPA? Do I need improved workflow? Do I need to use more orchestrators within the RPA?
“I think it’s really important to get these things right because there is a risk you might just end up with a few automations and you think, ‘so what’! I’m moving on to other things because that’s as much as I can get out of it.
“There’s also the fact that people don’t quite understand all the moving parts that would make a robot fail. There could be a very small change somewhere to the process and somebody might do something slightly differently and that might affect how the robot operates. Then they fail to see that and they blame the RPA, whereas it might literally be a process problem.
“I think, whenever there’s been a hype, and there’s been huge hype about RPA, it’s always very likely that there’ll be disappointment as well because people’s expectations are raised and then they fail to see the reality of what it is.
“You still need to work on your RPA projects, you need to maintain them and treat them as any kind of digitalisation investment and you need to keep it going. It takes effort, it takes time and effort. In terms of deploying it, it’s easier maybe than some technologies but you do need to manage the change. Changing processes from a human-oriented process to a robot-oriented process takes a bit of work.”
Scaling RPA: before automating processes, improve them
Maybe the lesson here is that it takes some work to save on a lot of work — but, for those who do put the miles in, suggests Burnett, the gains are considerable. Not only can there be a 30% cost saving on a process, not only can new, extremely accurate data, result, there is another benefit.
Burnett said: “RPA is very much focused on the enterprise users. Tech savvy ones could automate their own, even if it was only the equivalent of a macro, they could do it themselves.
“It’s opened eyes to see that this is what technology can do. There are many other technologies that have been around for a long time that can be used too. There’s micro-services, there’s integration via other methods, APIs, service-oriented architecture solutions, which people have traditionally not liked because it means involving IT, involving developers.
But it seems once we get past the RPA hype phase, the technology could be a trailblazer, opening up in people’s minds the idea of automation technology. Yesterday it was RPA and hype, today, maybe there is a little bit of disappointment, tomorrow, as we learn the benefits, RPA may move into the mainstream. But to to misuse the name of a film, the day after tomorrow other automation technologies will follow in the path created by RPA.
