Around 70% of CFOs say that there forecasting process is “respected”, “inclusive” and “strategically aligned”, but only 40% say that the outcome is “insightful”, i.e. reveals unexpected insights and pathways to better performance. Despite the huge effort expended in the forecasting process it seems that it often fails to live up to expectations. So, the obvious question is how can organisations make their forecasting process more insightful?
FSN’s 2017 survey, “The Future of Planning, Budgeting and Forecasting” (PBF), crowd-sourced from the FSN Modern Finance Forum on LinkedIn not only shines a light on the characteristics of insightful forecasting, but also points to the benefits and limitations of technology, including the more experimental technologies such as AI and machine learning.
FSN examines the performance of the PBF process in three dimensions, (i) the ability o re-forecast in under a week, (ii) the ability to forecast earnings with a tolerance of plus or minus 5% and finally, (iii) the ability to forecast out over the time-horizon more than a year.
What we find is that “insightful” organisations excel in all three dimensions.
So, what are the characteristics of an insightful organisation? There are in fact four standout qualities of insightful organisations:
1. They have a higher dependency on rolling forecasts: 43% of organisations that say their forecasts are insightful use rolling forecasts compared to just 29% who say their process is not insightful.
2. They leverage non-financial data: 65% of insightful organizations say that management appreciate the value that non-financial data brings to forecasting
3. They are more likely to use specialist software for forecasting and are therefore less dependent on spreadsheets: 15% of organisations that say their forecasts are insightful use specialist cloud software vs 10% who say their process is not insightful. And 35% of insightful organizations use specialist on-premise software vs 21% who say their process is not insightful.
4. They make more use of “cutting-edge” technology for analytics: 59% of those with insightful processes described their approach to analytics as ‘cutting edge’ compared to 26% of organisations who say their forecasting process is not insightful.
What is immediately striking is that insightful forecasting relies on a blend of technology and accounting technique. Two of these emblematic characteristics, namely; rolling forecasts and non-financial data relate to accounting technique and the other two are technology enablers.
Reassuringly, “Cutting-Edge” technology is not as advanced as the description might at first seem – it is within the reach of most organisations. In the survey we define “basic technology” as the use of spreadsheets, “advanced technology” as using pivot tables and BI tools, “cutting edge” as the use of advanced data visualisation, charting and graphing and finally, “Experimental” as using machine learning and Artificial Intelligence to drive analytics.
It transpires that cutting-edge technology is the most influential on forecasting accuracy and looking out further on the time-horizon, but loses out to machine learning and AI when it comes to the speed of reforecasting. Experimental technologies can churn large data models more quickly.
But what contributes most to insightfulness – technology or other factors? Well, when we compare the impact of cutting edge technology and insightful organisations on forecast performance, we find that insightful organisations do better.
The moral of the story is that if you want your forecasts to be more insightful you need to take a balanced approach, namely, using non-financial data, rolling forecasts, specialised PBF software and cutting-edge data visualisation.