Companies' digital transformation promises to dramatically change finance and accounting functions, as well as the types of people CFOs will hire, finance executives said in a CFO.com webinar on Tuesday. 

There’s no one definition of digital transformation, but executives generally agree it has something to do with putting in place the infrastructure and tools to generate and analyze massive amounts of data to transform how companies make decisions.

“When folks talk about a truly data driven organization, I would say they’re talking about an organization that has at its fingertips massive amounts of data and massive amounts of insights,” said Bob Dutcher, vice president of Oracle Business Analytics and Big Data.

The data-driven organization also empowers the finance staff with a self- service capability when it comes to generating reports, and that same capability extends to other function areas in the business. “This means, as an organization, I’m going to be much more agile," Dutcher said. "I can get information that took me weeks or months and compress that into minutes or hours, so I can make decisions much faster, and it provides a repeatable, secured, governed methodology as well.”

In a digitally transformed company, the marketing executive, for example, will use the massive amounts of data to track precisely how much in new revenue a campaign is generating. Right now, executives have limited visibility into that, making it hard to say to what degree a campaign is directly responsible for sales.

“Attribution has always been a big problem,” Dutcher said. “If I don’t know how my marketing spend is directly impacting my actual revenue, that becomes both a marketing and a financial problem.”

That lack of visibility affects the financial planning and analysis (FP&A) function as much as the marketing function because the CFO needs to have a sense that money allocated to the campaign is an efficient use of resources.

Evolving finance staff

Finance chiefs are already adapting to digitization in the way they manage their finance and accounting functions.

To an increasing degree, finance teams automate data entry and tracking, which lessens the importance of the traditional accounting skill set and increases the importance of the data analysis and interpretation skill set.

“You do need some core skill sets regarding data extraction and manipulation, but in our hiring practices, we think about the long-term,” said Valentino Hafalia, vice president of Western Alliance Bank. “If you think about FP&A, we’re really storytellers. So, the skill sets we’re looking for now are leaning more toward emotional IQs, softer skills, people who can communicate things. We think the tool sets available now are good enough to do a lot of the heavy lifting for us.”

Universities are adapting to this change, too. “I think the universities see the problem on the horizon, and they’re focusing the coursework on the skill sets that we’re going to need in the next generation,” said Dan Rashba, director of finance for TripAdvisor. “We used to look at CPAs, we used to look for people who could handle high volumes of transactions with accuracy. Now I’m looking for people who are SQL coders and people who can tell the story much more than any of the transactional stuff because [that part] will be automated.”

More predictive data

Looking ahead, the massive data that companies collect, and their use of machine learning and AI to filter it, will enable them to supplement their analyses with predictive analytics. 

Hafalia said they are close to the point where they can use the data in banking to make lending decisions, or to alert customers to new options based on future predictions. 

“We have a long-range plan to take a look at how our lenders are making decisions,” Hafalia said. “Why are some lenders really good at coming up with credit-based decisions, why some are not, crunching all that data through AI to figure out the best way to lend money to people. Eventually, we think, as we move toward something like a zero-cost margin business, AI and machine learning will do a lot of the heavy lifting for us: ‘You should lend to this person because of x, y and z.’” 

The data can also help executives predict M&A opportunities. 

“We’re always evaluating potential M&A opportunities,” said Hafalia. “Part of the M&A game is to think about what the profitability of the particular target will look like in the future and there we use predictive modeling to give us an instant snapshot of where this business is heading and that gives us additional time to look at that target in depth if we think it’s worth our while.”

Finance professionals attending the webinar agreed their enterprises will be hemmed in until they fully embrace digital transformation; just under 80%, in a poll conducted during the event, said the manual data processing they do now is slowing them down and keeping them from being competitive.

“This seems to correspond to what we’re hearing from folks out there in the industry,” Dutcher said. 

Oracle was a sponsor of the webinar, called Leveraging Analytics for Predictive, Data-driven Insights.