Accounts receivable forecasting is a strenuous yet necessary task for a company’s growth. However, forecasting accounts receivable accurately can be challenging since payment terms are often agreed upon but not followed through.
Here’s a complete guide to forecasting accounts receivable using days sales outstanding (DSO). In this guide, you will learn the three essential steps to accurately forecast accounts receivables.
Before delving into the steps involved in forecasting, let’s explore what accounts receivable forecasting is and its importance.
Accounts receivable forecasting is a vital component of effective cash management. It entails monitoring both historical and anticipated receivable payments. By analyzing past payment patterns of clients, you can make informed predictions about when you can expect future payments.
Cash flow is the lifeblood of any business, and accounts receivable plays a pivotal role in maintaining it. Accounts receivable forecasting is a vital financial analysis technique that enables businesses to anticipate and prepare for future customer payments. By examining historical sales data and customer payment patterns, businesses can project their future accounts receivable balance and make informed decisions accordingly.
In essence, accounts receivable forecasting is essential for assessing a company’s profitability, offering clarity on cash inflow to the CFO. Here are some key benefits of accounts receivable forecasting:
To make sound financial decisions, the CFO’s office must stay well-informed, and accounts receivable forecasting plays a pivotal role in this process. Let’s delve into the step-by-step process of forecasting accounts receivable using DSO.
Forecasting accounts receivable is a valuable tool for CFOs to anticipate future payments and manage cash flow effectively. Among various methods, one of the most accurate approaches is utilizing the metric known as DSO. Let’s delve into how DSO can simplify the process.
Start by projecting your sales, which involves estimating the anticipated sales revenue for a specific period. An effective method for accurate sales forecasting is to examine your historical sales and analyze changes in financial data. Consider these key factors that may evolve over time and should be taken into account for sales forecasting:
While the execution of these factors may require some time, they form the foundation of a reliable sales forecast. Other approaches can also be employed, including historical data analysis, deal stage assessments, and custom forecasting models incorporating variables like lead scoring.
Here’s a common formula for forecasting sales:
Sales Forecast = (Last Month Revenue + Expected Growth – Expected Churn)
For instance, if last month’s monthly recurring revenue was $100,000, and sales revenue has consistently grown by 10% each month for the past 12 months, with a monthly churn rate of 1%, the sales forecast for the next month would be calculated as follows:
Putting these numbers in gives us:
Sales Forecast = $100,000 + (10% x $100,000) – (1% x $100,000) = $109,000
Irrespective of your industry, DSO is the most popular metric for estimating the financial health of a business. It can be defined as the average number of days a company takes to recover its receivables after a sale. For a CFO, it is better to keep DSO as low as possible.
Different industries have different approaches towards DSO calculation but, the common formula is:
DSO = (Accounts Receivable / Total Credit Sales) x Number of Days in the Period
For instance, if there’s a company, Company X, with net credit sales totaling $100,000 and accounts receivable for 50 days amounting to $60,000, you can calculate its DSO as follows:
(60000/100000) x 50 =30 Days
From the above calculation, we could say that company X recovers its dues within 30 days, and hence its DSO is 30 days. Generally, a DSO of less than 45 days indicates low DSO, which means the company has consistent cash flow and fast-paying customers.
After forecasting sales and calculating DSO, you’ll have the necessary numbers to estimate accounts receivable. The formula to calculate the accounts receivable forecast is:
Accounts Receivable Forecast = Days Sales Outstanding (DSO) x (Sales Forecast / Time)
For instance, let’s assume that Company X has a sales forecast of around $40,000 in 60 days, and as we know, DSO is 30 days. You can calculate the accounts receivable forecast as follows:
Accounts Receivable Forecast = 30 x ($40,000 / 60) = $20,000
By leveraging automation and utilizing accounts receivable forecasting tools, businesses can significantly improve the accuracy of their accounts receivable forecasts. According to Pymnts and American Express, companies that rely on manual processes take 67% more time to follow up on overdue accounts than those using AR automation.
Moreover, automating the accounts receivable forecasting process offers several advantages for businesses:
As we highlight the efficiency gains from automating accounts receivable forecasting, consider industry leaders like Hershey’s. Our analysis of their working capital metrics, including DSO, DIO, DPO, and the Cash Cycle, reveals strategic financial management. The comparison with competitors and insights into Hershey’s Order-to-Cash modernization efforts offer a glimpse into effective financial strategies and innovation driving operational excellence.
HighRadius offers an e-invoicing and collections app that aids CFOs in achieving accurate accounts receivable forecasting. Our AI-powered solution offers a holistic view of your financial data, leading to enhanced financial health by effectively reducing DSO and minimizing bad debt risks.
Forecasting collections in accounts receivable (AR) is a crucial aspect of financial management as it allows organizations to predict the timing and amount of cash inflows from outstanding invoices. This helps organizations optimize cash flow, manage working capital, and make informed business decisions.
You can model accounts receivable monthly by analyzing historical data, tracking changes in customer payment behavior, and adjusting for economic conditions.
By leveraging advanced accounts receivable forecasting tools, automating data collection, and regularly updating your forecasting model you can increase your accounts receivable forecasting accuracy.
An effective tool for analyzing accounts receivable is an AR automation platform, which streamlines data collection, provides real-time insights, and improves forecasting accuracy.
To forecast accounts receivable, divide DSO by 365 for a daily collection rate. Multiply this rate by your sales forecast to estimate future accounts receivable. This method helps predict the amount you can expect to receive over a specific period. Regular updates ensure accuracy.
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