How CFOs can leverage real-time data to drive business success | GBAF

How CFOs can leverage real-time data to drive business success | GBAF

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Home > Finance > CFOs: are you making the most of AI in your forecasting?

CFOs: are you making the most of AI in your forecasting?

Published by Gbaf News

Posted on August 21, 2019

5 min read

Last updated: January 21, 2026

CFO analyzing financial data and AI tools for effective forecasting - Global Banking & Finance Review — An image of a CFO utilizing AI-driven analytics to improve financial forecasting accuracy. This illustrates the critical role of data in strategic decision-making for finance leaders.

By Richard Hilton, Managing Director EMEA, Miller Heiman Group

Across industries we’re seeing companies battle rising competition and economic and political uncertainty, fighting to stay in the black and keep the business profitable. The finance department, and particularly the CFO, is under greater scrutiny than ever before to ensure this – analysing the organisation’s strengths and weaknesses and proposing the best course of action.

According to EY and Forbes, 57% of CFOs view delivering data and advanced analytics for business intelligence and management as a critical capability for their finance functions in the future. But with data being a buzzword for several years, how can they ensure that they are using it effectively?

The danger of poor forecasting

Data is integral in the role of the CFO to forecast each quarter on how the business is tracking against its overall strategic goals and if it’s not performing as it should, deciding what should be implemented to get it on the right track. However, the problem is that many finance departments are still stuck making business decisions tracking on the quarter behind. And while looking back can be useful to a point, really, data should be viewed as a driver for behaviour going forward.

When forecasts deviate widely from actuals, it raises questions about the CFO’s ability to manage the business. When actuals are lower than forecast, inventory carrying, and capacity costs escalate. And if actual demand exceeds forecasts, revenue opportunities may be missed, and customer failures may occur.

The importance of real-time data

These avenues can be avoided if CFOs understand how data fits into forecasting. They need to consider that not all data is created (or logged) equally, in a standardised way across the company. This is a big issue – if they are to contribute to decisions on the right opportunities for the business to go after, whether that’s in the product mix, sales function, marketing or client services, then having access to real-time, quality data is fundamental. We’re seeing marginal movement towards this way of working but there’s still not enough consistency across companies.

One of the biggest reasons for this is that CRM tools – the foundation of most financial reporting – were never built with people in mind. They’re perceived by the majority of those working within a business as an administrative task rather than of strategic value; essentially a great big spreadsheet that captures data for management or operations teams only. This results in massive inconsistencies in the type and quality of data collected not only across business units but within entire teams too.

To counteract this, CFOs would benefit from pushing their counterparts to collect the data they need – identifying what insights will deliver advantage to them – and in real-time, so that they have an up-to-date view of how the company is operating and performing. The best way of doing this is to demonstrate the value it will deliver to a specific part of the business, otherwise it’s viewed as an admin job, with CFOs consistently struggling to get accurate data – a laborious task.

AI is changing the way we sift through data

As well as restructuring the way data is collected from a people perspective and clarifying the types of data they need, CFOs need to also consider the technologies in place too. Thanks to the explosion of new developments such as artificial intelligence (AI), we’re on the verge of CRM 4.0 which is bringing an end to the generic CRM interface we’re all used to.

Though there has – and still is – much negativity around AI, businesses should view it as a servant, rather than let it become the master of its users. It’s well known that the technology offers a world with less tedium and more opportunity for individuals to apply innovation and creativity to meet their customers’ needs. But it also helps deliver real impact to businesses.

Let’s take the sales function as an example. AI has the power to help organisations be more strategic in deciding the deals they put effort into closing and new business they go after, as well identify those that really aren’t worth their time. The technology essentially provides a link between insights on the buying situation and sales actions. Have they engaged us before? Is this the type of person we should be talking to?

AI is going in and taking a look at things, it’s taking a look at past results – wins, losses and no decisions. As salespeople continue to input data, an AI system refines its algorithms to make more precise recommendations on where the next big sell could come from. Not only does this reduce time wasted on low potential chasers, but it better equips teams to go after high-quality opportunities and ultimately makes them more effective.

More accurate forecasting will impact the bottom line

No-one will get forecasting 100% correct, especially when a company’s performance is at the will of external pressures such as fluctuating markets, for example. However, by considering data quality, internal structures and new technologies, CFOscan give themselves at least a headstart. Having real-time visibility into data, which can be turned into valuable, actionable insights, is vital for the finance department to be viewed as a strategic function in the business. It also helps business units across the company operate more effectively too, underpinning the success of the wider business’s top line.