Members benchmark and share approaches to making forecasts more accurate and more valuable.
A recent debriefing session analyzing the results of NeuGroup’s May 2022 Cash Forecasting Survey made clear that beyond discussions of methodology, accuracy, technology and the effort required, lies this fact: Treasury needs to clearly define the purpose of a cash forecast and identify the audience who will use it to make decisions that help meet strategic goals. In other words, if the information in a forecast is not effective at driving decision-making or triggering an action, it should be reevaluated.
Here are five takeaways from the debrief that address the details of creating forecasts that serve a clear purpose:
- Know where to get the right data. The biggest cash forecasting obstacle is a lack of visibility or predictability of future cash flows, cited by 88% of survey responses, often related to lack of access to cash data. Member discussion in the debrief session suggested that the difficulty in producing the forecast is as much about knowing whom to go to for the data; or even knowing where to go to find out who knows the most about it.
- More is not necessarily better. NeuGroup’s analysis reveals there is no direct correlation between the number of items included in the forecast and its accuracy. This raises the question of whether treasury needs to collect so much granular information, which can extend cycle time if the process is not fully automated. Currently, 93% use Excel to compile the data and generate the forecast, and of them 50% also rely on their TMS.
- One way to reduce the number of items while maintaining forecast effectiveness is to identify the key drivers of cash; this driver-based forecasting approach is widely used in the FP&A function and can be adapted to treasury’s needs.
- “Using Excel—even with the help of the TMS—can make it difficult to collect and analyze more than 50 items, so driver-based forecasting is a better option,” said Nilly Essaides, NeuGroup’s managing director of research and insight.
- As the forecasting process becomes more highly automated, it is possible to collect and analyze larger data sets. “If you use artificial intelligence or machine learning to model, you can initially look at hundreds of data points without increasing cycle time.” Ultimately, as the algorithms learn by identifying important patterns, it’s possible to whittle down that number to the KPIs that truly drive cash flow.
- Some who came to treasury through FP&A cited a failure in their eyes of FP&A to delve into the KPIs—and an overfocus on P&L that incentivizes them not to—leading them to take ownership of cash forecasting on the treasury side.
- When FP&A at one treasurer’s company owned the long-term forecast, “it was just a metric model.” Treasury has since taken over both forecasts at the company, which the member said is an improvement because treasury “actually understands the math.”
- Using direct and indirect forecasting allows for cross-validation, reconciliation and stress testing across the forecasting models for both, which leads to better cash insight and accuracy. Nearly 80% of members said they intend to own both the direct and indirect forecasts in an in-meeting poll. While FP&A produces its own, typically indirect and longer-term forecast, it’s important that treasury continues to use both approaches.
- “It’s important for us to keep both,” one member said. “At the end of the quarter, we run both models, using the indirect forecast from the income statement and direct forecast from the cash flow. This is great because we can reconcile the models.”
- The cash-forecasting approach is highly driven by whether the company is cash-rich or highly leveraged. “With cash forecasts, given the focus on managing working capital as efficiently as possible, a lot depends on how low investment grade you are. You probably see a greater emphasis on accuracy and short-term direct results on below-investment grade companies,” one treasury director said.
- Non-investment-grade companies, which have limited access to external liquidity, must be significantly more disciplined in their cash forecasting process to ensure they are cash positive so they can pay their bills and make good on interest payments, as well as comply with bank covenants and liquidity ratios demanded by rating agencies.
- Plus, investors are increasingly looking at the statement of cash flows, as opposed to solely looking at profitability, to make investment decisions.