Cash forecasting is often described as an arduous task. However, it is a critical process that shows how much cash a business will generate and what cash will be needed to fund future working capital and expansion. In most organisations cash forecasting has a bad name due to the amount of time it takes to do it properly and the poor results it often produces. As with forecasting of any type the results calculated will never be 100% accurate and, in a world where absolute precision is demanded at all times, this can be disheartening.
The flip side of lack of confidence is over confidence. Forecasting with 99% accuracy the day before an event isn’t very impressive and ultimately provides little decision making value. Somewhere in between this false confidence and the valley of despair lies the point of most value for your company.
In this post we look at three key elements to cashflow forecasting best practice. A process that combines direct human input with cash flow information stored in systems and the projections generated by forecasting models will produce the most accurate and reliable results. The mistake most companies make is to focus too intently on one element, ignoring the others, in the hope that it will produce a respectable forecast. In many cases it will but it won’t produce something that you can use for decision making or strategic planning on a daily basis.
Forecasting user input
It could be argued that humans sit behind each of the three elements we discuss, which they do, but for this discussion we will treat them as the source of information that doesn’t sit in a system or can’t be modelled. Generally this information relates to special projects, acquisitions or seasonal events.
In many cases domain or situational knowledge, such as knowing a specific customer’s payment patterns, allows adjustments to be made to a forecast that will dramatically improve its accuracy. This critical thinking is the essential ingredient in any planning based discipline.
Cash forecasting systems
Many companies fall into the ‘over-automation’ trap when designing a forecasting process by assuming that they can fully automate their way to an accurate forecast. This often leads to huge amount of time and money being spent on projects that will only be judged successful if 100% automation is achieved.
Systems don’t provide a silver bullet solution but are important for two reasons. Firstly they contain information necessary to complete the forecast itself and secondly they help with the automation of manual processes and analysis of data. As such they play a very important role but only as part of an overall solution.
Cash forecast modelling
Modelling your way to an accurate cash forecast is almost as difficult as full scale automation. It’s convenient to think that a sophisticated spreadsheet model will provide the right answer as this would save a lot of time and effort. Modelling can produce a believable projection but it is unreliable for short and medium term forecasting where a greater level of timing precision is required.
Modelling is necessary however for certain components of a cash flow. Revenue and input prices are typically dependent on external factors such as customer demand, raw material costs and FX movements which can be modelled and then tweaked using the latest available information.
Understand what’s needed in a cash forecasting process
A cash forecasting process that captures information from humans, systems and models will produce the most accurate projections of future cash flow. No two companies will have the same cash forecasting requirements but an understanding of what each element can provide as well as its limitations will allow you design a process that provides maximum value to your organisation.
Why Finance is Driving the Advanced Technologies Agenda
Working with finance and treasury teams on both sides of the Atlantic, a trend we increasingly see is that IT teams are no longer the gate-keepers when it comes to purchasing technology. Rather, it is finance and treasury themselves who identify and engage the technologies they need to enhance performance. ...John Champion - May 09, 2019
Data visualisation: accelerating the rise of finance and treasury
In a recent post, we discussed how data visualisation techniques can be used to uncover insights in cash forecasting data. That post offered examples of cash forecasting data visualisations and demonstrated how they enable users to spot insights that might be missed when simply wading through raw data. These insights ...John Champion - May 01, 2019
How will machine learning, artificial intelligence, and automation help accounting and treasury?
As machine learning, artificial intelligence, and automation transform the finance function, teams are finding new ways to enhance decision support and strengthen their organisations’ competitive advantage. With more organisations recognising the potential of data to drive business development and growth, expectations of finance are shifting. Teams are beginning to focus ...Conor Deegan - April 23, 2019