Is a Collections Forecasting Tool on Your Holiday Wish List?


Year end is right around the corner — do you have the ability to estimate the collectability of accounts receivable for the remainder of 2017? If not, you may want to put a collections forecasting tool on the holiday wish list from your CFO.

Accurate collections forecasting is more important than ever in understanding where your company is financially. Businesses are investing thousands of dollars in forecasting tools that help grasp sales pipeline, expense management and budget. Yet, despite such investments in technology, the forecasting of collections often gets put on the backburner with a claim that it’s just too difficult to capture.

Sure, there’s no crystal ball that can predict which customers will pay or won’t, but there are definitely things you can do to make sure your collections forecast is as accurate and helpful as possible, as well as have tools to capture and report on it. Improving the measurement of collections can make a huge difference, including:

  • Increased accuracy of budgeting and profitability predictions
  • Actionable data for credit and collections managers for collector evaluations
  • Greater call prioritization efficiency for collectors

The traditional method of estimating collections has been to look at a group of large accounts and estimate collection percentages by aging groups of receivables. That’s a lot of time and a lot of data! These are two essential data points that need to be automatically captured for the most accurate collections forecast:

  • Days Sales Outstanding (DSO) — The average time that receivables are outstanding. Using this measure, you might find that your average days to collect is 70. Thus, you could use this average to project receivables collections:

Ending Total Receivables x Number of Days in Period Analyzed
Credit Sales for Period Analyzed

  • Promise to Pay — Transparency with what was communicated during collection communication in regards to Promise to Pay (e.g. what invoices, how much, when, etc.) is crucial. Details such as reason for lateness, dispute specifics, partial pay plan, and amount of promised payment are all crucial reporting elements of any collections strategy, but companies often have difficulty capturing this data, which impacts collections results and customer service.

If you don’t have an easy way to capture DSO and Promise to Pay details, collections forecasting becomes too challenging and, ultimately, you can’t get a handle on cash flow. By staying on top of your cash projections with tools like automated collections management, you can better understand where your business is headed financially. Having data that is automatically aggregated and displayed, giving businesses the ability to uncover late payment trends, Promise to Pays, recurring issues, and spotting underlying problems is crucial to providing an accurate collections forecast.

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