Taking charge of data is a key factor in making financial planning software artificial intelligence and machine learning ready, according to Gartner, Inc.
Although these technological advancements have been no doubt the talk of the town for a while now, finance leaders are still prone to doing some things wrong.
Matthew Mowrey, senior director analyst at Gartner, says finance leaders pursuing AI and ML, along with advanced analytics, tend to zero in too much on the distant promise of what technology might achieve rather than on the business outcomes they want to see in their organisation.
Gartner says 75% of finance leaders are not satisfied with their function’s progress towards advanced analytics, with 62% encountering major obstacles to data-enhanced planning, and 83% expecting investment to increase in the near term.
Mowrey explains that the reason why finance leaders focus too much on these is because it is more engaging: planning out technology, looking at vendor demos and visualising the world of what could be, asking, “What are other finance functions doing with this technology?”
The Gartner senior director analyst points out that finance leaders should focus on the business outcomes (problems) that are critical and then finding the technology to deliver them.
Once the important business problems have been defined, Mowrey says finance is in a far better position to identify the data requirements for solving those problems.
Further, a common misconception that tends to delay these kinds of initiatives is that the function will need to acquire more technology-based knowledge, skills and behaviors. Most of the required skills already exist to some extent in FP&A.
