Ventana Research Analyst Perspectives

Robotic Process Automation (RPA) has emerged as a core digital technology for finance and accounting organizations. It can drive significant gains in productivity and efficiency by automating mechanical, repetitive accounting processes in a continuous, end-to-end fashion. RPA improves efficiency, ensures data integrity and enhances visibility into processes.

There is a strong business case for incorporating RPA tools in finance operations as well as developing the skills to use them because accounting involves highly repeatable tasks that lend themselves to automation. RPA is a key technology capability for what Ventana Research calls the Finance/IT organization. A FIT group is made up of individuals who are well-grounded in core finance and accounting disciplines but also knowledgeable about software and information technology.

Justification for having a FIT group goes beyond RPA. Our latest Office of Finance Benchmark Research found that organizations with a FIT group performed a range of basic departmental tasks considerably better than non-FIT groups, including financial analysis (50% of FIT departments execute financial analytics very well compared to 29% without), cost accounting (48% versus 20%) and budgeting (46% versus 20%).

RPA software takes the place of humans, acting as a “digital worker” that performs rote, repetitive jobs so humans can concentrate on work that requires their experience and judgement. At a basic level, the technology can be used to link disparate financial, compliance, operational and other necessary systems, eliminating the need for human intervention and associated errors and delays in workflow-supported processes. that span multiple applications.

Today’s RPA systems can perform business-critical tasks that require connecting multiple systems and data stores reliably at scale. In this respect, RPA supports what I call continuous accounting by enabling straight-through processing of transactions. RPA also facilitates the acquisition of external data that enhances the business value of financial and managerial accounting, an essential component in the use of artificial intelligence for budgeting and planning. Organizations are using RPA to streamline and reduce the cost of enterprise resource planning migrations, especially from legacy, on-premises system like SAP, Oracle and others to newer and more modern ones in the cloud.

RPA is proving to be a versatile tool. Ongoing advancements in hardware capabilities enable these digital workers to perform increasingly resource-intensive and time-consuming tasks and processes. The use of RPA is evolving to include a broader set of more complex automation capabilities. By infusing intelligent methods and techniques in processes, RPA can be instrumented for very sophisticated processing. The list of possible uses is long, but RPA can handle any volume of simple and complex tasks, providing a competitive advantage through faster completion, consistently accurate data, greater control, and lower costs.

The next generation of RPA represents a step forward from its initial use in automating discrete tasks within multi-step processes to manage complex workflow and workloads. This highly versatile tool can bring advanced digital techniques to bear, such as text and speech translation, blockchain integration, sentiment analysis and response, elastic search, and machine learning. This sophistication enables RPA to handle increasingly complex tasks, allowing a higher percentage of processes to be managed by exception.

RPA’s ability to perform more complex operations and apply reusable components to a range of tasks across a broader set of applications has significantly increased the addressable value of the technology while cutting costs and shortening the time to realize that value. A new level of reliability brings improved resilience to the enterprise, and this impact can be measured by the number of digital workers that automatically carry out any number of tasks in a workflow for business processes across departments, business units and to external parties. The sophistication of the processing enables a wide breadth of workload options for linking to devices, applications, systems and data sources. And new computational techniques in ML now enable these digital workers to perform their tasks without human intervention. Taken together, these advancements mean the scope of applications that can utilize RPA will continue to expand across a wide range of business processes and enterprise applications.

While the tools are available, using RPA strategically in finance and accounting means developing a departmental competence. This is less daunting than it might have been in the past. In addition to a broader set of capabilities, RPA has advanced “low-code” or “no-code” functionality, so non-developers and a wider set of business users can now apply RPA without having to be software programmers. The skills needed to configure these tools are more easily accessed, reducing the cost and time of resources and increasing potential ROI.

I recommend that all finance organizations have a Finance IT group along with a basic competence in using robotic process automation. For those already using RPA, it’s important to invest in building professionals’ RPA skills to ensure the technology is used efficiently and the department is able to exploit the capabilities of RPA to its fullest.

Regards,

Robert Kugel