In my conversations with finance executives and industry experts, one of the most common themes I hear is that finance teams have to more fully embrace big data strategies. True, finance has lagged marketing and even HR in implementing big data projects. But that’s changing.
Philip Peck, who heads the finance transformation practice at Peloton, tells me the emerging digital age is fundamentally changing the way that financial planning and analysis (FP&A) needs to think about the world, where intangible assets now make up 80 percent of corporate valuation.
As the leader of AFP’s FP&A practice, I make sure to speak to dozens of FP&A professionals. They all agree that the role of FP&A is quickly changing; it’s moving from the back to the front of the boat. To stir the corporate ship in the right direction—and course correct when necessary—finance needs to fine-tune its forecast and become more agile so it can help management make smarter decisions. The variety, volume and velocity of data is providing FP&A with quick input; new technologies and in-memory tools are cutting down the processing time of millions of records from hours to seconds, so finance can answer questions on the fly and produce actionable information easily and frequently. Many of these new tools are called self-service; in other words, they can be used by financial analysts without IT intervention.
Ultimately, it’s all about asking the right questions, and finding those answers through models that take into account key business drivers, unstructured and structured data and internal and external sources of information.
That’s new to finance; FP&A is used to dealing with internal numbers that are easy to check and audit. So finance execs have legitimate concerns about data integrity and governance. But those are becoming easier to address. It’s also important that finance plays nicely with IT and develops the right skills (or even hires data scientists) so it can move beyond Excel and simple queries to using advanced analytics. In this new era, analytics is a team sport. It’s not something analysts do in isolation using their own Excel models.
Indeed both practitioners and experts often point to the lack of skills as the biggest obstacle to the adoption of big data strategies. Current educational, training and certification programs do not teach data discovery and analytics. That’s one of the reasons why AFP has launched the Certified Corporate FP&A Professional designation, to better prepare practitioners for the demands of the new FP&A profession.
The bottom line is that finance and FP&A can significantly improve their core planning, forecasting and analysis activities. Embracing big data projects is not a matter of whether but of when—if finance is going to help its business customers stay competitive in a fast-changing business environment.