Improving Days Sales Outstanding with Artificial Intelligence

Almost every company tracks days sales outstanding (DSO), and for 58 percent of credit and collection professionals surveyed by FIS, DSO is one of their top key performance indicators (KPI).

The difficult part is that almost every company measures it slightly differently. Even within the same company, I’ve found that it’s difficult to come up with the same calculation for DSO. One group may exclude some accounts, while others may not have visibility to all accounts that can impact DSO. The reality is, DSO is typically a high-level metric that means more to a CFO than it does to an Accounts Receivable manager.

But DSO can become a relevant metric. First, measuring DSO sporadically will not provide you with meaningful information. It must be measured on a consistent basis to provide a trend, which you can then use to measure the performance of your team over time. This allows you to adjust for variations, such as seasonal fluctuations, that impact the DSO figure. Only by measuring DSO through enough periods to see the seasonal impact can you understand how your team is performing.

Second, DSO does not provide a valid picture of performance if you use it as a metric all on its own. There are many factors that play into DSO performance, most of them being out of the control of the Accounts Receivable department. For a healthy view of performance, DSO should be used in conjunction with other metrics, like percent current, bad-debt write offs, and even dollar exposure at different risk levels.

Third, companies need to view DSO as a performance measure against their Best Possible DSO (BPDSO). Companies that have standard extended credit terms, say 120 days, will have a very different DSO than a company that uses a standard 30-day credit term. If your BPDSO is 90 days, it does not make sense to compare your actual DSO against a company that has a BPDSO of 30 days – unless you want to get into a broader cash flow discussion of changing your standard terms.

In our survey, 78 percent of organizations reported that over the last 24 months, their DSO has remained flat or increased. Best-in-class organizations have taken the DSO metric as a litmus test for measuring their overall credit and collections processes and use it to uncover improvement areas.

Many of these organizations are moving to a specialized solution that incorporates artificial intelligence (AI). The benefits of AI are continually evolving as more advancements are made and more valuable data is collected. One of the great advantages is that an AI solution continues to optimize based on new information. Once you institute a solution with AI, you will witness the DSO improvement that you are being asked to deliver. And while the cash flow equivalent of one day improvement of DSO varies between each company, the value can range from hundreds of thousands to multiple millions of dollars. Your technology investment is quickly returned through the reduction in DSO.

AI provides a platform for improving individual and collective performance, which helps to reduce cost and make teams more effective. AI identifies and helps teams focus on the credit risk and collection risk within their portfolio. It allows teams to be more effective with fewer resources. Finally, a solution featuring AI is scalable to grow with your business without having to add additional headcount.

The cumulative effect of leveraging AI within the credit and collections process improves cash flow month over month while driving down DSO and inching closer to the BPDSO.

For more information about the value of a solution with AI and the latest trends around DSO, download our report: 2019 Credit and Collections Market Report: Modernizing Credit-to-Cash with Artificial Intelligence (https://empower1.fisglobal.com/modernizing-credit-and-collections.html)