Predicting cash receipts from customer payments is often the most complex part of cash forecasting. What makes forecasting A/R accurately for a business so difficult?
We’ll go through all the common obstacles businesses face with accounts receivable forecasting. Read on!
The common methods to forecast A/R are:
You have to determine the credit sales expected during a specific period by analyzing the historical data. Then calculate the A/R forecast using the formula:
Since the ADP varies for different customers and different invoice amounts, it increases the complexity to be calculated using Excel.
A/R forecasting can be carried out by using either direct method or indirect method of forecasting depending on the needs of an organization.
Direct A/R forecasting is suitable for short-term liquidity management purposes and it follows the bottom-up approach where transaction-level data is gathered from different teams and rolled up to the central treasury to create a global forecast. The direct method is preferred when there is a need for more detailed information at a granular level for drawing insights. Direct forecasting provides high accuracy within a short-term period.
Indirect A/R forecasting follows the top-down approach for forecasting changes in accounts receivable and cash as line items in the projected cash flow statement and as ending balances in a projected balance sheet It uses the three statement method with pro forma balance sheets, cash flow statements, and profit and loss statements. This method is mapped to the longer-term planning needs of a company.
Forecasting accounts receivable encounters various challenges due to the following reasons:
The factors that may cause variability in A/R include:
The above complications limit forecast accuracy, which hinders efficient financial and resource planning. Furthermore, reporting such inaccurate forecasts decreases credibility in and beyond the company. Thus it is very important to select an optimal process and/or tools for forecasting A/R accurately.
There is no one-size-fits-all method to accurately forecast A/R. But, there are some best practices that leading-edge companies follow to overcome A/R forecasting challenges. Here are few tips to improveA/R forecasts:
An AI-based cash forecasting solution provides real-time information, improves visibility with dashboards, and refines forecasts with time.
Incorporating richer data sets and robust tools provides deeper insights into A/R cash forecasting. This helps CFOs and treasurers to carefully assess volatile components and implement corrective measures, hence enabling confident business decision-making around liquidity and revenue growth.
Accounts receivable is one of the drivers that helps in assessing the liquidity and financial health of a firm. Not keeping track of accounts receivable leads to high DSO, thus negatively impacting the financial status. In order to maintain sufficient liquidity, forecasting accounts receivable at a granular level is a proper way to go ahead. However, an inaccurate A/R forecast leads to repercussions such as:
If the A/R forecasts are inaccurate, the false base data could lead to poor decision-making on investments, or dividends.
If your past dues are high, you might be offered low credit lines from the credit agencies.
Relying on an unclear or inaccurate view of your current balances would position you to borrow loans at high interest rates.
Accounts receivable or A/R represent the amount of invoiced sales that have not yet been received as cash.
The difference between Accounts Receivable and Accounts Payable is that A/R is the amount that customers have to pay to a company, whereas A/P is the amount that a company has to pay to its suppliers. Moreover, A/R falls under the bracket of assets whereas A/P falls under liabilities. Accounts receivable is often confused with collection, but collection refers to the amount still owed past the due date. Collection is a source of income/revenue and profitability for the company, but unlike A/R, it doesn’t fall under assets or liquidity.
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