If you can measure it, you can improve it. DSO – What is it? How do we calculate it? When is it useful?


DSO stands for Days Sales Outstanding. There are many variations of the definition. Some say it calculates how many days it takes to convert a credit sale to cash. Some say it shows the average age of your accounts receivable. Some say it is a measure of collections staff performance. Situationally, all of these definitions may be right or wrong, but in all cases, DSO is a key indicator of the health of a company’s credit sales. DSO can impact liquidity and it is a number that shouldn’t be ignored! It’s particularly useful as a big-picture view of AR and can be instrumental in forecasting cash flow and identifying risk.


The DSO calculation contains three elements: Accounts Receivable, Credit Sales, and Number of Days in a Specified Period. There are variations in the formula as well, but the common formula is:

*Accounts Receivable is sometimes represented as a Total as of a Point in Time, such as a month-end, or year-end, rather than an average. Depending on the nature of your business, using a three-month period can help to normalize the data by flattening increases and decreases.

The formula essentially calculates the dollar value of one day’s Sales in the period and then tells us that the Total AR is equal to the value of X number of days. (Note – Mercury! can automatically calculate DSO based on your specifications. This is invaluable!)

In an easy example, let’s say Average AR = $4,500,000 Total Sales = $9,000,000 and Days in the Period = 90. 
DSO = ($4,500,000/$9,000,000) X 90 = 45 Days. (One day of Sales = $100,000 so AR of $4,500,000 = 45 Days of Sales.)

What does this example tell us? In a vacuum, it doesn’t tell us much. There’s no hard and fast benchmark for DSO. For some companies, 45 is an excellent DSO; for others, it’s a terrible DSO. Context that includes credit terms, seasonality, and industry standards is helpful in interpreting DSO. For example, if a company offers credit terms of 60 days to all of its customers, a DSO of 45 is fabulous! It shows that they’re collecting most of their money before its due. But DSO of 60 would be great as well. If, however, a company’s credit terms are 14 days for all customers, a DSO of 45 is not so good.

DSO as a KPI

To use DSO effectively, trend analysis is important. DSO at a point in time is less telling than DSO performance over a period or as compared to other periods, such as month over month or year over year. Differences in DSO can pinpoint areas that need improvement as well as areas of success. Graphic depiction of DSO is impactful in showing progress or deterioration and can help you to anticipate peaks and valleys in cash flow. With Mercury, you have the ability to track DSO on a client level basis. This can be extremely helpful in identifying changes in clients’ payment habits, which can indicate anything from seasonal adjustments to cash flow issues to disputes with the quality of your products or services. Whatever the cause, tracking DSO can help you to get ahead of potentially perilous circumstances.

While DSO is a solid Key Performance Indicator (KPI) for credit sales, it does have its limitations. There’s an assumption that DSO is a good way to measure the performance of collections staff. But is it actually? Not always. The main reason is that the formula doesn’t allow for factors that are out of the control of the collections staff, such as Sales Volume and Client Credit Terms.

Significant variations in Sales can impact DSO, both positively and negatively, regardless of changes to AR. If Sales drop dramatically and AR remains the same, DSO goes up. Conversely, if Sales increase dramatically and AR remains the same, DSO goes down. In both cases, the collectors may have done nothing differently. To a lesser extent, the number of Days in a period can impact DSO (think a 28-day month vs a 31-day month) regardless of collection activity. Also, while companies often charge collections staff with the burden of driving DSO down, they sometimes neglect to consider what their best possible DSO is, in light of the credit terms or special arrangements they offer their customers. In using the example above again, if a company offers 60-day terms to all customers and the collections staff can’t move DSO below 60, this is not a measure of the collection staff’s ability to collect, but rather an indicator that the company’s model for credit sales might require modification. Even the best collectors are not likely to convince customers to pay their bills in full before they’re due. While DSO can be used as a collection measurement, it shouldn’t be used as the only collection measurement.

How to improve DSO?

So, how can DSO be improved? Or, more specifically, how can we enhance the story it tells? DSO is one small number representing a big pile of info. Buried in there are good sales deals and bad sales deals, good payers and bad payers, and everything in between. If you want to see what’s driving the number, you need context and you need the option to dig deeper. In addition to traditional DSO, dive deeper and calculate DSO at client level. Then contextualize that by pulling in credit terms as a comparison field so you can identify clients that need attention. Track client-level DSO across periods to spot trends and anticipate client payment patterns. Create a delinquent DSO by stripping out all the activity that is paid within terms and analyzing only the past due items. Create a weighted DSO based on credit terms to determine your Best-Case DSO. If you don’t know what your goal is, how can you reach it?!

Here is a summary DSO for a given period

Here are a few screenshots of DSO a few additional details of the DSO produced in Mercury!

When broken out by Payment Terms, it appears that the DSO is probably as good as it can be:

Invoices that have 30 day terms are being collected, on average, in 39.57 days. (the 3 month DSO looks even better, thanks to improving revenue in the last three months).

More screenshots for those times when you need to drill down for more detail.

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