Predictive analytics help CFOs use data for more accurate planning, forecasting, and decision making based on what’s happening now and what’s likely to happen, rather than what happened in the past.
Finance professionals today recognize the need to extract value from the inundation of data. As their job gets more complex, the need for tools that allow for increased efficiency is crucial. In fact, a recent global survey from SAP and CFO Research found that three-quarters of CFOs and financial executives anticipate making effective use of Big Data over the next five years. But how can data best be harnessed in order to gain valuable insights?
Predictive analytics is one of the key use cases for Big Data that forward-looking finance organizations are implementing to forecast future performance and drive strategic decision-making. For background, predictive analytics refers to the capability of an organization to discover and communicate meaningful patterns in data to predict and improve business performance, recommend action, and guide decision-making. Financial organizations can use predictive analytics to identify trends and play out “what-if” scenarios in real-time.
Traditionally, software has been useful in reading and analyzing structured data, but the volume of unstructured data – from external financial reporting systems, RFID sensors, and social media, for example – is exploding. Predictive analytics can help CFOs and other finance professionals harness data for more accurate planning, forecasting, and decision making based on what’s happening now and what’s likely to happen, rather than what happened in the past.;