The iterative aspect of machine learning has succeeded at increasing accuracy in cash forecasting.
When it comes to finances, we all wish we could predict the future. Where it concerns business finances, there isn’t a crystal ball that predicts upcoming success. However, there are powerful forecasting tools that can help you make better decisions about the direction your business might take.
Cash forecasting can be tricky when an FP&A team relies on manual tools, data collection, and calculations. Even though it’s long been the case that an exact balance is not completely necessary, and a good estimate is acceptable, there are some instances where that’s no longer true.
If you’re trying to project enough incoming cash to make next month’s payroll or, whether it’s a good time to take on a new project, a close ballpark figure may still be good enough. However, when it comes to being able to confidently inform leadership that funds can be expended towards a major strategic business advancement, accuracy becomes more crucial. Hoping there’s enough to “make it” crosses the line into unacceptable risk.
Automating cash flow forecasting has become a key component of making future business decisions much like checking a map app would be when planning a trip. One of the main reasons you check a map app is to gauge, with relative certainty, approximately what time you will arrive at your destination. The map app may not always be 100% exact in its calculations, but it does help to know if you should leave earlier or if you’ll arrive “fashionably late.”
Ideally, your cash flow forecasts would be more accurate than a map app, but there’s not much difference in the reasoning. Cash flow forecasting will inform your current decisions and future actions to ensure the best possible outcome with a higher probability. When automated and powered by AI and machine learning, it should provide intelligence and higher accuracy that was once missing from the manual process; very much like how a printed map doesn’t have traffic projections based on real-time data that a map app delivers.
Best-in-Class Performance is Built on Data and Integration
However, it takes more than straight automation to make cash flow forecasting more efficient and accurate. The data matters and it starts with enabling collaborative platforms that the FP&A, A/P, and A/R teams can leverage. For instance, when the A/R team uses software that includes predictive scoring to segment late-paying customers, it can help you determine who may pay one month late and who may pay two months late. That enables the A/P team to better understand their incoming cash. This level of detail, updated with real-time data and automatically transferred across teams, can lead to a more accurate cash flow forecast for the FP&A team at any given moment.
Why Manual Adjustments Deliver Poor Quality Forecasting
Developing a more accurate cash flow forecast can help business leaders make smarter decisions and manage risk more effectively. In a business environment where a cash flow forecast includes manual intervention, there is a higher likelihood that the picture is less accurate. Whether a team member attempts to inject an optimistic adjustment that results in an 8% increase in Q4 sales or reduces office expenditures by 10%, any human interaction, or subjective bias, almost always introduces a problematic factor that can become detrimental.
Typically, these issues are introduced in the manual creation and management of spreadsheets. Not only is this process prone to mistakes from human intervention, it’s extremely time-consuming and tends to yield poor quality because the calculations are often forced to be more generic, and nearly static. And, since financial narratives can change rapidly, the data collected in spreadsheets can become quickly outdated; often being irrelevant or inaccurate by the time they are completed. Spreadsheets, even those that are tied together with formulas and links, are still one-dimensional in that they can’t ingest information as it changes, nor can they begin to understand and learn from fluctuations or patterns.
With the advent of technology that can merge data, learn, predict behaviors, and over-time improve itself iteratively, a finance team can begin to build more sophisticated forecasting methods with even more agility and efficiency; providing a fully automated, objective forecast that is not only more accurate, but can also facilitate an up-to-date rolling forecast that is far more meaningful. It becomes more reliable because it recognizes and includes receivables intelligence data such as broken promises-to-pay, pending disputes, and DSO – again, much like a map app adjusts your ETA based on traffic or real-time events that could slow you down.
Automating cash forecasting with D&B Finance Analytics Receivables Intelligence can help improve the process – as well as your company’s cash flow. This powerful, AI-driven software provides an intelligent way to help collections and cash teams leverage industry-leading predictive analytics, applied machine learning, and real-time receivables activity to forecast cash more timely and accurately allowing your business to make key strategic decisions when it matters most.