How to Generate an Accurate Cash Flow Forecast

3 Key Factors Crucial to Achieving Success

Do corporates really know what is “eating and feeding” their cash? Why are treasury staff still wasting time extracting balances manually, fumbling with bank portals, and then dealing with endless spreadsheets? Here, Mark O’Toole, Head of Sales & Strategic Partnerships – Americas, Fides, explains how treasurers can streamline cash flow forecast processes and, in turn,  fuel business growth.

Many of us would imagine that treasury and finance departments have by now perfected their cash forecasting, giving the CFO a level of confidence in the numbers. Surprisingly, that doesn’t appear to be the case. In fact, in recent years, global benchmarking studies from PwC and Deloitte have highlighted cash and liquidity risk as the most important challenge to manage.

The reason for this emphasis is simple: having an accurate cash flow forecast and understanding the underlying drivers can help treasurers foresee potential problems that may arise in the year ahead.

With increased global uncertainty, interest rate rises and regulatory change combined with the challenges around managing a complex internal ecosystem of multiple banks, ERPs, FX exposure, and geographic entities, many companies globally are increasing their efforts regarding cash flow forecasting. Some accomplish this with more impactful results than others.

There are three key factors that can help organisations turn bad cash forecasting (i.e. not transparent, manual, inaccurate, and time consuming) into good cash forecasting (i.e. accurate and efficient).

1. Being able to drill down into actual cash flow drivers and using transaction-level/granular data

Many corporate treasurers are seeking an accurate cash forecast, which is a delicate combination of well-chosen cash flow drivers and assumptions. But to what extent do they have a good view of these cash flow drivers? Do they know what is really eating and feeding their cash – which is more than the typical high-level AR and AP treasury flows that a TMS will consolidate?

 There isn’t that much visibility, unfortunately. The classic TMS will typically consolidate basic forecasted flows from the different operating companies (OpCos). The problem is that these OpCos’ cash forecasts are already consolidated from the underlying business transactions. This blurs any insight into the real cash flow drivers and provides no assurance whatsoever on data quality.

To build a good forecast, it is important to have clear and error-free access to the underlying business transactions. Thanks to advances in technology, particularly APIs, treasury aggregators, and Big Data analytics, treasurers can have instant access to the details of the underlying cash movements and are given the ability to drill down to the transaction-level details.

Being able to automate and connect with all the banks, gather daily balances and transactions accurately is step one. Treasury  teams shouldn’t have to log into bank portals, fumble with hard tokens, download statements, then extract those balances and add to a spreadsheet, which then gets emailed to HQ, where all the divisional Excel reports are then consolidated onto yet more spreadsheets.

Treasury also shouldn’t need already scarce IT resources to manage host-to-host connectivity and the myriad formats required for cash reporting. By automating bank connectivity with a provider such as  Fides, those IT resources can be freed up to add value elsewhere inside the organisation.

2. Applying the right forecasting logic

Cash flow forecasting is often associated with a stack of Excel sheets and manual work. Treasurers are forced to turn to spreadsheets to calculate their forecasts because classic TMSs do not offer the required flexibility.

Getting insights into all the OpCos’ cash flow drivers is one thing but combining all these data sources and applying the right logic/rule is another.

Let’s take the easy example of applying payment behaviour. It makes sense to enrich invoicing and sales order details with data on actual payment patterns. Many companies, however, struggle to take the actual payment data into account. In general, they haven’t found the appropriate algorithms to include into their forecasts. Hence, they face inaccurate forecasts and so much time is spent explaining (over and over again) why it was inaccurate.

Applying the right forecasting logic is crucial for a good forecast, but defining this logic in a smart way is a real challenge. Yet, if your goal is to achieve an accurate forecast, a set of smart logic algorithms is invaluable. Again, modern technology proves to be a great asset. Progressive companies are using technology-driven, smart engines to calculate and automate their cash forecasts, taking over the manually intensive work.

3. Using the cash forecast to drive action

Even if a forecast is produced, it might be underused, or not used at all. To make a real impact, there should be actions taken based on the forecast results.

There is plenty of potential in accurately predicting what might happen in the future, and this potential should be translated into value. There is even more value in considering multiple scenarios by changing some of the underlying assumptions (e.g. payment runs). Unfortunately, changing assumptions might trigger a lot of additional manual work (when working in Excel or a TMS) and is thus often avoided.

To get the most out of the forecasting process, it makes sense to build multiple forecasts and assess the impact of each of these scenarios on cash optimisation. Driving action, combined with building multiple scenarios, is what transforms finance departments into business partners for fuelling a company’s growth.