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Preparing the finance function for an analytical future

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Preparing the finance function for an analytical future

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When it comes to forecasting, it might be a good idea for the modern finance function to talk about the weather.

On any given day, the most commonly found search term on Google is “weather.” Roughly 45 million times a month people around the world want to know whether they need to leave home in the morning clutching an umbrella orYes a tube of sun cream. It seems that we have an unquenchable thirst for certainty.  But fascinatingly, households appear to be abandoning traditional gut feel and the household barometer in favor of meteorological websites. They seem to prefer endless streams of data about weather patterns, forecasts and probability.

Weather forecasting versus business forecasting

The power and sophistication of weather forecasting puts business forecasting and planning to shame. Modern meteorology uses vast and complex computer models to simulate weather systems. Meteorologists apply advanced statistical techniques to data from all sorts of sensory devices out in the field to get a range of possible outcomes and probabilities.

Businesses face no lesser challenge when it comes to mastering market volatility, uncertainty and change. Yet the skills applied are decades old and the tools are often antiquated. The best outcome that most finance functions can muster is a “best,” “median” and “worst” case forecast with no sense of the probability of each scenario occurring.

No wonder that FSN’s “Future of Planning, Budgeting and Forecasting Research” finds that 50% of finance organizations are unable to forecast revenue beyond the 6-month time-horizon. And, 60% are unable to forecast revenue to within plus or minus 5%.

So, what can the modern finance function learn from weather forecasting? How can finance functions introduce more dependability into forecasts and, in the process, transform insight into foresight?

In broad terms, there are three crucial actions.

1. Up-skilFP&A graphic--finance functionling

Modern finance needs to recognize that the analytical skills of the past are no longer “fit for purpose.” Heads of financial planning and analysis (FP&A) organizations already appreciate this. FSN’s research found that 50% of heads of FP&A do not believe accounting bodies are producing the FP&A specialists for the future compared to just 25% in traditional finance roles.

(Image source: FSN Future of Planning, Budgeting and Forecasting Research 2016)


44% are convinced that FP&A will become a separate discipline from the accounting function (compared to 18% of traditional CFOs), even going as far as suggesting that FP&A will eventually become a separately recognized function with its own accounting body.

2. Building larger and more granular models

The FSN research makes a compelling case for larger, more granular planning models shared by all relevant stakeholders in the cloud.  But there is a “sting in the tail.” Although the ability to engage with so many more stakeholders builds trust and confidence in the model, it doesn’t necessarily increase accuracy.  The finance function of the future will need to engage stakeholders from other business functions if it is to improve accuracy. Furthermore, having more information at its fingertips enhances organizational agility and accuracy but does not help finance professionals see further out into the future.

If organizations want to see further out into the future, the research shows that they need to leverage non-financial data as well.

3. Using the best technology for predictive analytics

It is not yet a widely held view that finance professionals of the future will need to be data scientists. But what is already clear is that the spreadsheet, the analytical tool of choice for most finance professionals, is no longer a match for the mounting variety and volume of data. Turning insight into foresight requires a step-change in capability. The key to unlocking the potential of large scale models is to use what IBM calls “exploratory analytics” to prise open what the data has to offer, rather than the traditional, more prescriptive approach to data analysis that limits the questioner’s field of vision to predetermined data sets.

There’s an A in finance function

If finance professionals want to put the “A” (for analysis) back into FP&A, then they will need to upgrade their skills, build bigger and more granular business models and use more advanced tools for predictive analytics.

To learn more about the putting the “A” back into FP&A please listen to this on-demand webinar recording.

About the blogger

Gary Simon is the Chief Executive of FSN and Leader of the Modern Finance Forum for CFOs on LinkedIn. His profile is in the “Top 10” most viewed Leader profiles on Linkedin in the UK. He is a highly sought-after lecturer and trusted provider of thought leadership and analysis about finance and business systems for CFOs.

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