Posted by Adrian Tay August 28, 2017
Advanced analytics gives CFOs a new language
In a recent quarterly survey of finance execs, 45 percent of surveyed CFOs say they have already made investments in finance and accounting analytics, and about 52 percent say they will invest more in the future. The financial services sector shows the highest levels of past investment among respondents, at 64 percent, with the health care sector highest for future investment at 71 percent.1
What’s more, through in-depth conversations we’ve recently had with numerous CFOs around the digital transformation of the Finance function, whose insights culminated in our Crunch time: Finance in a digital world (insert tagged URL) series, advanced analytics was identified as a key “exponential” technology (or digital tool) that’s delivering new and different capabilities for Finance to help improve performance and serve the business more effectively.
Many companies are already making significant investments in advanced analytics, and it has already made its way into the toolset of many finance teams around the world. As finance organizations work to meet growing expectations for value-added insights, the trend will likely continue with talent increasingly focused on analysis and interpretation, including application of sophisticated algorithms used by data scientists.
Companies are beginning to build centers of excellence focused on finance analytics and looking to treat analytics as a core competency that is on par with traditional finance functions like the controllership and financial planning and analysis. Core controls and processes are being placed around analytical models to ensure their quality and consistency as the model outputs feed into the daily business workflow. Data is also being collected and archived before uses are determined for it. This is driven by the growing recognition of data as an asset and the continued reduction in cost of storage.
For example, one company that adopted advanced statistics applied advanced algorithms internal and external data within its forecasting models to generate an automated baseline forecast. All business problems are now able to be addressed using newly available data and statistical methods.
Finance is beginning to speak a new language, one that is no longer just limited to the mean and standard deviations. As summed up well by a finance executive I recently spoke to, “finance organizations are becoming transmission agents and data scientists, quite frankly.”