Preparing the finance function for an analytical future

25th September 2017

On any given day, the most commonly found search term on Google is the “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 or 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 favour of meteorological websites that provide endless streams of data about weather patterns, forecasts and probability.

In fact, weather forecasting puts business forecasting and planning to shame. Modern meteorology uses vast and complex computer models to simulate weather systems, it takes data from all sorts of sensory devices out in the field and it uses advanced statistical techniques to give 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, the tools are antiquated and 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 brush terms, there are three crucial actions, namely;

1.      Up-skilling

Modern finance needs to recognise that the analytical skills of the past are no longer ‘fit for purpose’.  Heads of FP&A 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. 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. 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 organisational agility and accuracy but does not help finance professionals see further out into the future.

If organisations 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 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 largescale 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 set(s).

If finance professionals want to put the “A” (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” (Analytics) back into FP&A please listen to this on-demand webinar recording.

 

 

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