Disappointed with FP&A? Ramp Up Tech Spending

Investing in today's analytics tools will easily pay for itself in staff time saved and better-quality analysis, AFP study finds.
David McCannOctober 7, 2016
Disappointed with FP&A? Ramp Up Tech Spending

It might not come as much of a surprise to learn that the more companies spend on analytics technology, the better the performance of their financial planning and analysis functions.

What might be less intuitive is just how extreme the advantage is when using more FP&A-oriented technology.

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In the Association for Finance Professionals’ new survey of 255 FP&A practitioners, 55% said they primarily use spreadsheets to deliver analysis for the planning, budgeting, and forecasting process.

AFP’s research, however, strongly suggests companies where spreadsheets are king are stuck fast in the past and falling far short of optimizing their FP&A functions.

The survey results reveal that where investment in technology accounts for less than 10% of total FP&A spending, companies expend an average of 384 FTE days per year, and a median of 60 FTE days, to collect and manipulate budget data (each “day” being the equivalent of one day of work by a full-time-equivalent staffer).

Spending incrementally more on technology makes a huge difference. Where technology is 10% to 19% of FP&A spending, the mean number of FTE days devoted to such activities falls by more than half, to 154, while the median also drops by half, to 30 days.

In fact, the more that’s spent on technology, the less time wasted on “grunt work.” Companies for which technology is 20% to 49% of the FP&A budget expend an average of just 62 days, and a median of only 14 days, to collect and manipulate data.

AFP cited a separate study conducted by Nucleus Research in 2014 that found the average return from each dollar spent on analytics technology was $13.01.

The ability to automate transactional and reporting activities represents a big move up the maturity curve for FP&A, which not many years ago was typically a mostly backward-looking function.

“Greater investment in technology liberates FP&A staff to do what they were hired to do, and what their organizations need them to do: conduct robust analysis and forecasting to better inform their company’s strategic decisions,” says Jim Kaitz, AFP’s president and CEO.

Many new analytics tools offer “self-service” functionalities that do not require IT-department intervention, which often results in bottlenecks and delays in delivery of timely analysis to management and business leaders, according to AFP’s report on the research.

Investment in technology also allows companies to look further into the future. Predictive analytics is a functionality that many FP&A teams see as the next big step forward, AFP notes. (See chart.)

FP&A Benchmarking Survey“Cloud-based solutions free up FP&A analysts to run their own queries, giving them a chance to use real-time information to feed predictive models,” AFP says. “FP&A functions that are not yet able to ask the ‘why?’ and ‘what’s next?’ questions realize they must acquire this capability.”

While large companies currently make greater use of predictive analytics than smaller ones, interest in the use of such technology is agnostic as to company size. Among those with annual revenue of at least $10 billion, 41% said they currently use predictive modeling for activities including forecasting and time-series analysis. And 45% identified it as a capability they expect to acquire in the future.

By comparison, only 15% of companies with revenue between $1 billion and $9.9 billion use predictive modeling. But 43% of them are looking to a future that includes that technology.

Interest is even greater among firms with revenue of less than $1 billion: while 13% of them use predictive analytics now, 58% are targeting it for future use.

Another finding of the study is that analytics technologies allow companies better access to data. At 40% of companies, according to the research, data is still locked at business-unit levels, with insights generated by departments and lines of business.

Only 9% of survey respondents said that “real-time, internal and external data is readily accessible across the enterprise based on need, information is shared extensively across the enterprise, and data-driven decision-making is part of the organization’s culture.”

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