Usually covering a time period of 60 to 120 days, a short-term cash forecast is based on cash receipts and disbursements. Unlike a GAAP-based statement of cash flows, which starts with net income/loss and then adjusts for non-cash items (such as depreciation and amortization) and non-income statement items (such as capital expenditures, working capital changes and financing), a short-term cash forecast is much more direct, reflecting cash coming in and cash going out. Another difference between shorter-term forecasts and GAAP-based and longer-term forecasts is in the period measured. Longer-term outlooks can be annual, quarterly or perhaps monthly; the shorter ones reflect daily or weekly periods.
Figure 1 shows an example of a short-term cash flow forecast for a two-week period. As can be seen in this simplified example, major categories of receipts and disbursements are classified separately, and the cash balance is rolled forward through the forecast. Using a greater number of line items in the forecast allows different forecasting methodologies to be used for different items and also provides a better basis for tracking variances against forecasts. Companies that are fortunate enough to have in place a revolving credit facility with borrowing availability would incorporate this into the forecast (by rolling availability forward rather than cash balance). Following is a discussion of the more important considerations in forecasting each of the major categories.
The primary source of cash in any business is collections from the sale of goods or services. This line item also happens to be the most difficult one to predict, as it is not under management's control the way that many disbursements are. Methodologies for forecasting customer receipts vary greatly and are primarily dictated by the nature of the business. Companies with a few large customers, such as aerospace suppliers and large contractors, generally have well-defined payment dates and amounts based on contractual terms. These can be forecast by individual payment, and customer relationship personnel play a large part in deriving these forecasts. However, most companies receive a higher volume of collections, such as retailers that might have hundreds of thousands of daily cash and credit card transactions at dozens of stores, or manufacturers that receive checks in single or multiple lockboxes.
The better methodologies for forecasting collections in "cash businesses" (e.g., restaurants and retailers) are statistical in nature, as the volume of receipts lends itself to such analysis. For example, assume that a retailer collected $1, 000 during the third week of November last year. It has 5 percent more stores open this year, and same-store sales have been running down 10 percent. A reasonable forecast for the third week of November this year might be $945 ($1, 000 x 105% x 90%).
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