Accounts Receivable Forecasting

Accounts Receivable forecasting is often misunderstood,and it is sometimes ignored by the credit department. Simply using last month's or last year's collection performance as a benchmark to forecast cash inflows isn't precise enough to help your company manage its cash position.  When mistakes are made in forecasting cash inflows or cash outflows by whoever is assigned this task, the consequences for the compsny can potentiallly be devastating. Forecasting cash inflows accurately is an important factor in the success of any business.  At its most basic, cash management is concerned with three issues:

(1) Projected cash inflows,

(2) Projected cash outflows, and

(3) What to do with or about the difference. 

Here are some guidelines and thoughts about the process that include topics such as purpose, time periods, and formatting ideas.

Forecast Time Periods:  The time horizon and the regular reporting periods are key decision items. For instance, if the forecast is to be prepared monthly, it is important that it be coordinated with regular accounts receivable reporting so it does not create extra work for everyone and so it takes the most updated information. It should tie in to reported figures. This means that there will probably be some time delay necessary after normal accounting closing to provide the data. The time horizon is an important factor, but it is usually set when the forecasting system is first designed. For instance, the forecast may be for daily collections for the next week, weekly collections for the next month, monthly collections for the next year, or quarterly collections for the next two to three years. Obviously, the length of the time horizon will have an influence on the desired accuracy of the forecast and the amount of work required to prepare the forecast regularly.

Responsible Departments and Staff:  Establish a focal point for your forecasts: i.e., is it corporate treasury, or are you going to try to forecast for each major operating area?  Who has the information needed to successfully complete the forecast?

Analysis of Current Process:  Define the forecasting process for your company (if you already have not). Assess whether the process is sufficient. Have changes in your company's structure influenced the current forecasting process? Review major problems, shortcomings, and strengths of the current system, planning to keep the good and throw out the bad. Will the process need to be changed? What were the lessons learned from the last forecast? How will the lessons be incorporated?

Level of Detail and Accuracy:  Can the forecast be produced regularly and reliably? What is the level of detail required? For example, does it need to be at the country, region, product, or company level? Are total amounts enough or will each number need to be broken out into more detail?  How will the accuracy or lack of accuracy be accounted for? Shorter-term forecasts differ from longer ones in that they will usually involve higher degrees of accuracy. This is because their time periods are smaller, which means that there is little time to recover from or accommodate widely inaccurate estimates that could have severely negative effects on the tactical decisions being made on the basis of the forecast. Longer-term estimates, on the other hand, may not need such accuracy as they are used to make more strategic decisions.

Forecast Data Format:  The format of the forecast is the way in which the estimates are presented. For example, shorter-term forecasts including those up to one year,are often more meaningful if they are presented in a receipts and disbursements format, which shows the cash flows in common terms. The opposite of this type of format is a financial statement format, which may look like a statement of cash flows or extracted items from a balance sheet and/or income statement. This type of format is fine for longer-term forecasts, such as those for longer than a year, but it is very confusing and difficult to work with for shorter forecasts. Some senior managers may be accustomed to this format and may suggest using it for shorter forecasts, but it can provide estimates that are not understandable or that cannot be reconciled easily with actual data.

Edited by Michael C. Dennis