CFRI 2017

Robots Helping Companies Optimize Talent Pools

Why RPA is really about talent management.

Improvements to efficiency, cost structures and talent management are among the factors driving the expanding use of robotics process automation (RPA) and machine learning in a growing number of organizations, according to panelists at FEI’s Current Financial Reporting Issues (CFRI) conference.

“RPA is really about talent management,” said EY Partner Fran Exley. “Think about the jobs you have in your organization and what makes sense in terms of automation. Opportunities to improve efficiency will have an impact on your talent as low-level jobs start to disappear, and the interaction between higher-value jobs and bots will become critical.”

RPA involves the use of software to automate sequence-driven manual tasks that traditionally have been performed by staff members, such as account reconciliation or taking information from one finance system and entering it into another platform or report.

“You’re typically automating a lot of work that people don’t want to be doing anyway,” said Ronald Edmonds, Controller and VP of Controllers and Tax, Dow Chemical Company, and a member of FEI’s Committee on Corporate Reporting (CCR).

“By automating a lot of lower-level busywork, you’re able to deploy people to get information to executives more efficiently. If people aren’t taking information and putting it into Powerpoint, you can speed your access to data and improve your executives’ ability to make decisions,” Edmonds said.

Exley said repetitive tasks that are being performed today in shared services centers or offshore may be good candidates for automation as companies become more comfortable with deploying the technology.

“Automation is not just a cost takeout play,” he said. “RPA and automation lead to improvements in consistency and speed. If you can increase the speed of your account reconciliations to real-time or near-real-time, that can create massive improvements in your business.”

Alice Jolla, Assistant Corporate Controller of Microsoft and a CCR member, described how her unit is incorporating machine learning to automate the company’s account reconciliation process. With a large volume of data, automation helps Microsoft’s finance team complete reconciliations as journal entries as posted.

“By automating this process, we allow the staff to work more efficiently and spend more time using analytics to develop stronger business insights,” Jolla said. “If we discover an issue during the close process, we’re able to resolve them in a more timely process. The staff is spending more time on more value-added work, and we’re also seeing a financial savings in the finance process.”

Jolla added that automating finance processes has helped to improve the internal controls environment because the tools help ensure controls are completed.

Keith Goodwin, VP, Finance and Q2C Transformation, IBM Corporation and a member of FEI’s Committee on Finance and IT, said his company has a number of machine learning and artificial intelligence (AI) projects underway, including a cognitive chatbot designed to help traveling IBM employees answer expense-related questions from the road. The company loaded frequently-asked questions into an automated system to provide real-time support regardless of whichever time zone an employee happens to be in.

As companies consider automation projects, the panelists said, as with any data-related initiative, cybersecurity and governance processes are critical. EY’s Exley said companies granting bots access to their systems and data need to consider potential implications to their policies and procedures, and to ensure the appropriate controls and access rights are established.

At Microsoft, Jolla said, a data-governance team reviews automated tools as part of the deployment effort and internal controls processes.

Despite the governance considerations, however, panelists said the compelling benefits of automating routine tasks means RPA and machine learning are likely to gain momentum in the near future.

“The key to this technology shift is just to get started,” said IBM’s Goodwin. “Get your feet wet and get some pilots going to see how this can create real value. Those tasks that require the most manual effort are the best areas to point to as you look at this technology.”