Robots have long inspired fear and hope, from the all-powerful mechanical giant Gort in 1951's sci-fi film The Day the Earth Stood Still to the wisecracking domestic helper Rosie the Robot a decade later on the Saturday morning cartoon The Jetsons. Between those two works of fiction, and years before Newsweek magazine's 1965 feature on "The Challenge of Automation," economist Doris E. Pullman accurately predicted the benefits, costs, and inevitability of automation, including today's hottest version--robotic process automation (RPA). "Probably the most important effect of automation will be the employment changes," she wrote for the August 1, 1958, issue of the Journal of the American Association of Industrial Nurses (bit.ly/2k635mm). "Automation will reduce the dangerous, monotonous, heavy, fatigue-producing production jobs."
Automating the "danger" out of today's financial processes may be the only note that sounds a bit anachronistic when applied to RPA, unless you consider the danger to finance professionals of catastrophically bad business decisions based on faulty data handled incorrectly by humans. But certainly the financial processes--90% of which are suitable for automation--can be mind-numbingly monotonous, fatigue-producing, and, as a result, slow and error-prone.
RPA, according to the technology consultancy Gartner, is a set of advanced technologies that can be programmed to perform a series of tasks that previously required human intervention. McKinsey has described it as "taking the computer out of the human."
RPA can be used to automate virtually any software applications. This includes financial planning and analysis (FP&A) or corporate performance management (CPM) software. For example, RPA bots could be programmed to log in to your CPM solution, run a complex calculation, consolidate results, and then export this new data. The same bot could then be programmed to log in to a data warehouse and import this new data to be accessed by your business intelligence (BI) software application.
While some FP&A software incorporates elements of automation, RPA and FP&A aren't at all the same. It's like the difference between self-driving technology and the car itself. The self-driving technology automates the processes a driver would have to control (speed, braking, direction, etc.), while the car is the technology that's being automated. Some people enjoy driving, but for many others, driving is a boring but necessary evil.
The clear benefit of RPA is in taking dreary, repetitive, error-prone manual tasks out of the hands of sometimes bored and inattentive humans and giving them over to computers, or bots, which operate much faster, never tire or get bored, and don't make simple math errors if programmed correctly.
"The [bots] should add to the economic and personal status of individuals who will take on the new highly paid skilled jobs of engineering, controlling, maintaining and repairing (them)," Pullman wrote in 1958, except she called them "new machines" instead of bots. In other words, automation will free people from drudgery, enabling them to enjoy a better, more lucrative work life performing more valuable work.
Three Things RPA Fixes
When RPA, sometimes called smart automation or intelligent automation, is used to automate financial processes, it solves three fundamental problems humans face when doing the same tasks. It breaks through bottlenecks in financial departments; it takes over processes that have a high incidence of human error; and it scripts processes that finance professionals find tedious, time-consuming, and of low value.
Because bots relieve highly trained finance professionals of some of their most tedious and time-consuming tasks, those professionals have more time to engage in meaningful analysis. They can understand the stories the data is telling, rather than simply reporting the numbers.
RPA comprises two distinct components or levels: routines and licensed bots. Routines are specific scripts--like computer code--that you write to perform certain tasks, such as logging in to a system, collecting specific data from an identified source, or running a process on that data.
In finance departments that still rely on...