Back to the Future: the need for predictive finance

CFOs must shift their focus from the past to the future, using data as their guide.

Back to the Future: the need for predictive finance
22 June 2017
Big data and analytics have gifted CFOs with the power to look into the future. Known as predictive finance, this approach can help them plan and carry out strategies that will improve the decision-making process and give their businesses the ultimate competitive advantage.

Turning data into actionable information

"The goal is to turn data into information, and information into insight," Carly Fiorina, former head of tech giant Hewlett-Packard, once said.

Although finance has always been data-driven, it has also, until now, always been backward-looking. With the digitisation of the economy and the huge amounts of data businesses produce, collect and store, CFOs have an unprecedented amount of information at their disposal.

Businesses can use this huge quantity of data and turn it into insights by identifying patterns and predicting future outcomes. This is the core proposal of predictive analytics, best described as the "art and science" of extracting information from existing data sets.

Due to its great potential for businesses, the predictive analytics market is set to explode globally. In the Middle East and Africa, MicroMarket Monitor expects it to grow from U.S.$101 million in 2013 to U.S.$406 million by 2019, an annual growth of 28.4 percent for the given period.

"The growth in the market in this region is rapid because of large investments by the IT sector in major verticals such as banking and financial services, government, healthcare, retail, manufacturing, and travel and hospitality for operational, marketing as well as risk and threat management," the research firm says.

Data: an asset

A major benefit of predictive analytics is the fact that so many applications and industry verticals exist: identifying what a customer will buy and anticipating future purchases, spotting corporate fraud, managing credit risk, or even determining how long an employee is likely to remain in the organisation. In marketing, predictive analytics is already used extensively to offer greater customisation, based on past behaviours.

Predictive finance incorporates big data and analytics, and complements it with other methods like statistical modelling. The benefits are also numerous in this field. In treasury for instance, predictive finance can help improve cash collection and forecasting. It can alert businesses to payment risk, and help prepare for adverse liquidity and market conditions. Predictive analytics systems can also incorporate relevant events like supplier contract-pricing changes or market changes. They can help sharpen revenue projections or shrink extraordinary expenses.

However, one of the most important benefits of predictive analytics is that it offers much greater visibility, by providing a more accurate and real-time picture of the business, simply by using the data that is already available.

Implementing predictive finance

Harnessing the power of predictive finance may seem, at first, a daunting task. Big data is overwhelming and it can be hard to know just what to track, where, and how to get useful information that is actionable.

Most SMEs will not have a chief data officer to assist them in this task, but that should not deter them from starting the process. So to begin with, CFOs may want to ask a question, try to solve a particular challenge currently encountered by the business or the finance department, or launch an objective.

The next and crucial step requires them to map out the data points and different sources inside and outside their department and the overall business, to understand all the interfaces that provide relevant and useful insights.

Centralising this precious information in the cloud is a pragmatic option, as from there it can be easily fed into a time-based predictive model highlighting the critical patterns that will turn raw data into gold.

From there, a course of action can then be identified to influence future outcomes positively and therefore not just help CFOs predict the future, but also positively influence it.

© Oracle 2017