Finance is commonly mentioned as a business unit ripe with opportunities for Robotic Process Automation (RPA). It makes sense: RPA is often a fit for repetitive, high-volume, computer-based tasks. Finance is full of those, from invoice processing to financial reporting and plenty more.
When Gartner interviewed more than 150 corporate controllers last year about RPA, the vast majority (88 percent) said they expected to have some form of RPA implementation in place in 2020. By Gartner’s count, a corporate finance department could save its accounting team around 25,000 hours of manual rework each year caused by human error each year in their financial reporting processes alone. That 25,000 hours of rework costs a company with a 40-person accounting team $878,000 annually, according to the research firm.
[ Want a primer? Read also: How to explain Robotic Process Automation (RPA) in plain English and How to identify Robotic Process Automation (RPA) opportunities.]
You can zoom in from 30,000 feet and see this phenomenon at the ground level. Tom Thaler, senior product manager, ARIS at Software AG, tells us that one of the firm’s customers in France (one of the world’s largest energy suppliers) expects 45 percent of all its financial transactions will be automated this year. That’s a result of an RPA project that used process mining to identify bottlenecks and automation opportunities in its financial transaction processes.
RPA helps data-intensive departments such as HR
So RPA hype is growing among finance executives for a reason: These aren’t small-change opportunities. On the flip side, though, this creates a potential misunderstanding that RPA is mainly for finance departments. RPA’s a fit for repetitive, high-volume, computer-based tasks? Cue up the folks in IT, HR, and other information-intensive departments: Yeah, we’ve got those, too.
Here’s a good way of thinking about RPA fits beyond finance: Look anywhere you have processes that span systems that aren’t integrated. If those processes involve moving data between those systems, that very likely involves manual, repetitive effort – and probably intensively boring effort, to boot – on the part of a person.
Those kinds of unintegrated applications or systems can be found all over the place – not just in finance. In fact, sometimes they might be core, mission-critical systems – but hold that thought for a moment.
“RPA is a versatile way to build on existing automations and make them even more efficient,” Cosette Dwyer, product manager, RPA, at Laserfiche. “By enabling staff to record themselves performing manual, repetitive tasks across application screens, RPA bots can take care of the activities that may have been previously deemed an ‘automation gap’ – for example, where legacy or proprietary systems lacked APIs or other backend integrations.”
Four example RPA use cases
Those “automation gaps” are another good way of thinking about RPA opportunities. These often exist in processes where some – perhaps even plenty of – automation is already in place, but where there’s a point in an end-to-end workflow that requires manual intervention.
Below, Dwyer and others share four key examples of RPA uses beyond finance and accounting tasks.
1. HR onboarding
Consider the paperwork involved with hiring a new employee: The paper might be largely digitized, but that doesn’t mean the work is always efficient.
HR automation is already underway. Dwyer notes that some recruiting teams already use tools that automate employment application processes, for example. But what happens when that application turns into an accepted job offer?
“Once an employee is hired, their information might need to be entered into an entirely different system,” Dwyer says. “If the systems involved lack APIs or backend integrations, staff may have to manually transfer new hire data.”
This is an example of one of those automation gaps Dwyer mentioned. A streamlined process becomes suddenly – and often painfully – manual, with an experienced HR pro stuck copy-pasting the new employee’s data (or otherwise re-entering it manually) into other systems as part of the person’s day-one onboarding.
“With RPA, staff can record themselves performing this transfer, automating it for each time a new employee is hired,” Dwyer says. “With the race for talent becoming increasingly competitive, recruiting teams can use this reclaimed time to focus on finding and engaging candidates rather than copying and pasting information [from one system to another].”
2. Core systems that aren’t integrated
Some marketing pitches might lead one to believe that every organization these days is operating tightly integrated systems where data moves with ease – and without human effort – across the organization. But that’s simply not the case. For all manner of reasons, organizations run all manner of applications, often across heterogeneous environments – and they aren’t always integrated. They might lack APIs or backend integrations, as Dwyers notes above, or they might be siloed for other reasons. Regardless, these sometimes include a business’s most critical applications – and create a lot of manual effort as a result. RPA might help.
Thaler says that another Software AG customer, GOL Linhas Aéreas (GOL), is using RPA to solve one of its biggest operational challenges since the Latin American airline’s founding: Continuously reviewing and adapting schedule plans in response to operational requirements. That had been a labor-intensive effort, to put it mildly, because it involved hundreds of daily updates in two asynchronous systems that weren’t integrated: a route management system and a reservation and ticketing system.
“Updating data in the reservation and ticketing system was time-consuming and demanded many manual tasks be performed by dozens of highly skilled professionals,” Thaler says. “This impacted the availability of tickets and limited commercial decision-making for new routes and new business opportunities.”
In an industry where operational efficiency isn’t just a management platitude but a matter of profitability or bankruptcy, that’s a big deal. GOL launched a significant RPA project to streamline the effort these two systems required, and it is already bearing fruit.
“Prior to RPA, processing 1,300 flight changes required 20 working days. Currently, RPA bots process the same workload in only one day,” Thaler says. “After the project was deployed, GOL eliminated its backlog of systems updates and is now able to plan flights three months in advance. A great example of a focused automation of a core process, which is highly affecting the competitive advantage.”
Let’s dig into two more use cases, the first near and dear to IT’s heart:
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