Back in the 80s, spreadsheet software changed financial forecasting forever. Along with word processing it was one of the first killer apps driving the personal computing revolution. Three decades on, many CFOs still rely on forecasting tools that haven’t changed much since Bananarama topped the charts. That’s a problem.
The rapid rise of digital is creating new business models that dramatically change the way companies operate, while simultaneously speeding up the pace of change. Evolving digital business practices are also generating more and more data – raw information that can help finance better predict performance.
The problem CFOs face is how best to gather and analyse that information and make their forecasts more reliable, even as the marketplace becomes more changeable.
The best finance teams updated their financial forecasting methods with predictive analytics. These systems have the power to dig into all the data being gathered to uncover meaningful patterns and improve business performance. Rather than relying primarily on historical information captured on spreadsheets as they did in the past, CFOs are now building data-based crystal balls to look closely at the impact of key variables on profitability, see trends, and even create what-if scenarios to help prepare for sudden changes in the business environment.
Backed up by predictive analytics, CFOs can build financial forecasting models that predict probable outcomes based on real-time inputs and variables, rather than point-in-time assumptions of what the key drivers are (or might be). Finance teams can use their data to produce forecasts based on customer or supplier profiles, and actual current demand, instead of treating previous results and prior-year trends as prime indicators of future results.
Accurate forecasts are essential if finance teams are going to instil confidence across the business for investment and spending decisions. Predictive analytics are fast becoming the centrepiece of financial forecasting best practice. Here’s why:
Getting to grips with all that data
Using spreadsheets, CFOs have to manually sort through of data to identify the most useful fragments, such as what is selling where and what is profitable in specific markets, then accurately predict the future by analysing current and past trends. Without analytics to slice data into digestible chunks, CFOs are faced with trying to interpret massive amounts of information.
Seeing is believing
The way data is presented affects a CFO’s ability to understand the information and influences how quickly they derive insights to make smarter, more informed business decisions. Analytics solutions typically offer access to visualised financial information in customisable dashboards. This allows CFOs to see quickly where forecasts may need to be adjusted, and easily share the information across the business.
Analytics software can also help CFOs manage their key performance indicators (KPIs) in real-time. Instead of running lengthy reports and analysis, Changes to, for example, sales and customer balances can be observed quickly. It can make decision making more nimble, and CFOs better able to react with better controls and predictability.
Access to information in real time
Analytics software for finance will automatically monitor data in real time and quickly identify errors as they occur, allowing finance teams to react quickly. Real-time data can also help organisations stay ahead of the competition, providing notifications the moment competitor has, for example, lowered its prices.
Making the shift to digital forecasting
The sheer volume of information businesses now collect is astounding. Many CFOs are becoming part-time data scientists as a result, combining traditional financial forecasting methods with emerging analytical methods and predictive technologies.
As time rolls on there will be even more ways to collect and store data. The challenge for CFOs is to transform it all into valuable and actionable insights. They can start by pulling together all their disparate information systems and formats in one repository, to create a single source of truth.
That’s not to suggest it will be easy. Embedding analytics to support forecasting and the decisions that fall from it required a high-level of commitment from CFOs. They’ll need to move finance and strategic decision making from from a backward- to a future-looking orientation. It will also require a willingness to invest in new tools with the necessary analytic capabilities.
Despite that it’s time for CFOs to say goodbye to old technology. Just as spreadsheets and pocket calculators freed finance teams from the computational drudgery of the past, predictive analytics will free CFOs from the manual processes that currently drag down forecasting, allowing them to focus on developing insights and adding strategic value to the business.
About the author
Alice Allegrini is UK Managing Director of prevero