In a global survey of 1,544 CFOs and finance executives by CFO Research, three-quarters anticipate making effective use of Big Data over the next five years. Finance organizations will need to make significant changes in their processes, skills, and technology to use this data to their advantage.
The best finance organizations are using predictive analytics to forecast future performance and drive strategic decision-making. To be clear, predictive analytics refers to the organizational capability to discover and communicate meaningful patterns in data to predict and improve business performance, recommend action, and guide decision-making. Rather than relying primarily on historical information, finance organizations can use predictive analytics to identify trends, analyze key variables, examine what-if scenarios, and so on – live.
Here are some examples of how the smart use of predictive analytics has contributed to the success of some companies and enhanced the impact of the finance organization.
Increasing forecasting frequency, reducing cycle time
Many Americans look to the American Automobile Association (AAA) for travel assistance, insurance, and emergency towing. To optimize service from the AAA motor clubs across the United States and Canada, the AAA national office built a centralized “action center” to provide better insight into member needs. With next-generation predictive analytics, AAA could better understand customers’ needs by having real-time access to data. This led to enhanced marketing campaigns and reduced customer attrition rate.
Live Oak Bank lends exclusively to small businesses and specific professions like veterinarians and pharmacists, and due to the nature of these customers, the bank values speed and flexibility. The bank is guided by executives who are industry leaders in both finance and technology, bringing innovation and efficiency to the lending process. The bank leverages real-time analytics to make better decisions more quickly. With the predictive analytics platform, decision-makers now enjoy greater collaboration and transparency, and the team can respond quickly to managers.
As the UK’s largest insurer and a leading provider of insurance and asset management, Aviva protects around 31 million customers worldwide with insurance, savings, and investment products. Tapping into predictive analytics models helped Aviva gain the insight needed to serve clients with offers most relevant to their interests. The company made use of predictive analytics to generate propensity models for more targeted customer groups, rather than a generic group, which allowed staff members to make better decisions and more accurate projections for clients.
One of the world’s most renowned manufacturers of skylights, VELUX from Denmark, uses predictive finance to optimize the balance sheet by better understanding the financial impact of warranty claims, and therefore improve customer service.
Use cases for different financial processes can add some ideas to your agenda.
Harnessing unstructured data
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 harness it 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.
To learn more about how finance executives can empower themselves with the right tools and play a vital role in business innovation and value chain, review the SAP finance content hub, which offers additional research and valuable insights.