Without effective forecasting, companies are essentially flying blind into the future. We look at the role of new technology evolving to help tackle this challenge.
While much of the finance function has digitised in recent years it’s fair to assume that most cash forecasting activity, even in very large corporates, is still spreadsheet-based. The spreadsheet is often the default tool for many planning, forecasting and data modelling activities due to the fact it is available to everyone and used for so many other activities as the aggregation point for data from a host of different systems. As Conor Deegan, CEO of cash forecasting provider CashAnalytics, says, “a spreadsheet is the easy choice”.
However, despite that easy familiarity, inevitably with spreadsheets, the cash forecasting process is often manually-intensive and time-consuming. And not only are they difficult to scale for a growing business, they can also be error-prone. As Paul Smithwood, Director of Product Development, Data & AI, Bank of America, notes, errors that are not detected can lead a company to believe it has materially more or less cash than expected. If that company then makes decisions based on those erroneous numbers, at best finding the offending cell is like looking for the proverbial needle in a haystack, at worst it can prove costly.