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How Can Finance Functions Become Analytics Leaders?

Gary Simon -

Gary Simon is Chief Executive Officer FSN and Leader of the Modern Finance Forum for CFOs on Linkedin.

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Analytics in the finance function has been top of mind for CFOs for many years. Yet despite the column inches devoted to the importance of analytics, and the wide choice of supporting tools and technologies, insight, the pinnacle of analytic effort, remains stubbornly elusive. A newly released FSN survey, “The Future of Analytics in the Finance Function,” makes the point. It finds that only 14 percent of finance functions say their analytics are insightful.

A deeper evaluation of the survey results starts to reveal why analytics is missing the mark. For 22 percent of finance functions, analytics is merely “routine,” revolving around standardized ERP reporting with little effort to mine its analytic potential. The same reports are generated at the end of each month with little if any collaboration between business functions. A further 34 percent characterize their reporting as “reactive,” i.e., there is a high dependence on standardized ERP report production, but in exceptional circumstances the finance function will make the effort to probe performance more deeply. So, in aggregate, more than half (56%) of finance functions are on the sidelines of performance and unable to leverage analytics for insight and competitive advantage.

Reassuringly, the remainder are more data driven; for example, 30 percent actively employ business intelligence and data visualization tools to drive insight but, even here, the effort is confined to operational silos. Thus, these finance functions fail to take advantage of the synergies provided by a more holistic approach. The ability to merge processes as well as join operational and financial data is crucial to delivering more insight and enabling better decisions.

Leading the pack are the 14 percent of finance functions that claim an analytics mindset pervades everything they do, and that data is shared as a corporate resource. These financially intelligent organizations have learned to master their data and are adept at leveraging financial and non-financial data, as well as bringing on board novel data sources that might give them a competitive edge. FSN’s research shows that non-financial data is pivotal to being able to forecast further out on the time horizon.

So, the obvious question is: What does it take to be an analytics leader?

Helpfully, the research sheds light on this too. There are two main constraints, namely technology and data mastery. This year’s survey finds that technology constraints are getting worse, and at the same time, the number of finance functions claiming to be data masters is falling.

It seems that many finance functions do not have the technology they need to exploit the data at their fingertips. In the main, they are not complaining that they are “data constrained,” i.e., do not have the right data, nor that they are “data overloaded” i.e., too much data with inadequate governance and control.

So, what is the right technology? The research shows that organizations that invest in specialist technology for analytics (tools for financial reporting, data visualization, enterprise performance management, and predictive analytics) considerably outperform finance functions that rely on standard ERP reporting and spreadsheets. Furthermore, earlier FSN research (The Future of Planning, Budgeting and Forecasting 2018) shows how data visualization techniques and technology, such as, graphs, charting, and dashboards, are crucial to driving insight. Secondly, the research shows that specialized tools help with “data mastery,” inherently providing a degree of structure and order that drives confidence in the underlying data.

Finally, the research shows that after several years of headcount growth, the position is now flat, i.e., finance functions have to contend with increasing demands but without a commensurate increase in headcount. The inescapable conclusion is that if finance functions that want to be analytics leaders, they have to invest in specialized tools.

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