Robert Kugel's Analyst Perspectives

Robotic process automation (RPA) relies on programming or the application of analytical algorithms to execute the most appropriate action in an automated workflow. RPA enables business users to configure a “robot” (actually, computer software) to interact with applications or data sources to process a transaction, move or manipulate data, communicate with other digital systems and manage machine-to-machine and man-to-machine interactions. This technology is gaining increasing notice by finance departments, with good reason: RPA represents an important step beyond simple process automation in that it uses software to execute routine but complex workflows that require judgment. Rather than making an individual check-off a step in a routine approval, a robotic system applies an algorithm that decides the next step. The system thus does what people spend an awful lot of their time doing every day: making judgments that most of the time could be done by a machine.

RPA is an important technology that can serve as a cornerstone of the digital-enabled finance organization. This technology can automate a wide range of rote routines that today must be handled by individuals, for example, collecting data from multiple systems or spreadsheets and entering it into another system. RPA supports Continuous Accounting, an approach to managing the accounting cycle that can improve departmental performance, by automating accounting processes in a continuous, end-to-end fashion to improve efficiency, ensure data integrity and enhance visibility into processes, and distributing workloads continuously over the accounting period to eliminate bottlenecks and optimize when tasks are executed.

Workflow automation is a staple of enterprise systems but only works within a single application. An RPA system can work with multiple applications rather than just one, eliminating the need for an individual to open some other software to, for example, pull information about a transaction to confirm that a shipping invoice matches that order or to extract customer information from one mainframe legacy system to automatically enter a form into another mainframe system.

RPA systems essentially offload repetitive tasks from individuals to digital systems, enabling organizations to be more efficient. Moreover, just as manufacturing robots can perform actions more consistently than humans, RPA systems can improve the quality and accuracy of the work and shorten cycle times. In cases where they free up skilled employees to concentrate more on matters requiring their education, experience and judgement, they also make their organization more effective.

Finance departments can gain substantial value by implementing RPA because accounting involves performing rules-driven repetitive tasks that until now may have been difficult to automate without the aid of specialized tools. Automation can improve a department’s performance. Our Office of Finance benchmark research finds a correlation between the degree of automation used in the financial close and the time it takes to complete the process. Nearly three in four companies (71%) that use a substantial degree of automation are able to complete their monthly close within six business days. In contrast, only 43 percent of companies that use some automation and just 23 percent of those that use little or none in their close process are able to close in that time frame.

How quickly a company closes its books affects the timeliness of the information that the company receives. There is a correlation between how quickly an organization completes its close and the timeliness of the financial information that executives and managers have with which to make decisions. Three-fourths (75%) of those companies that close their quarter in one to two days said they have timely information, compared to 38 percent that take three to six business days and 10 percent that take 11 or more business days.

There are two basic types of robotic process automation systems: programmatic and algorithmic. Purely programmatic RPA executes rules-based tasks based on defined parameters – for example, taking a set of data from one system, placing it into a spreadsheet and, after using a macro to make adjustments, uploading the resulting data into a second system for additional processing or storage. Algorithmic RPA systems are more sophisticated in that they perform some analysis to determine what to do next. For example, the system may perform some ratio analysis and choose one of five courses of action based on the result of its analysis, or determine if two values are close enough that the difference isn’t material. RPAs eliminate the need for individuals to perform rote assessments of conditions or data, thereby speeding the execution of that process while ensuring that it is executed consistently. However, because ambiguities exist to some degree in almost all business situations, an algorithmic RPA is almost never fully automatic. Even so, it can be quite valuable because it enables organization to deal with these situations through exception-based management. Handling only the exceptions utilizes employees’ time, experience and judgment most productively, boosting the performance of finance and accounting organizations.

I recommend that all senior finance executives and managers familiarize themselves with the capabilities of RPA. Every midsize and larger company should undertake a pilot program to begin to develop the skills necessary for applying it on a broad scale. Robotic process automation is an important evolutionary step beyond decades-old business process automation. It supports a continuous-accounting approach to managing the department by streamlining processes and ensuring data integrity. By applying automation and analytics, it eliminates the need for skilled individuals to do tasks that are better performed automatically. And in doing so, it can enable a finance organization to use the gains in efficiency to concentrate on playing a more strategic role in its company.

Regards,

Robert Kugel

Senior Vice President Research

Follow me on Twitter

and connect with me on LinkedIn.