When Analytics Meets Receivables - InformationWeek

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1/16/2014
01:25 PM
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When Analytics Meets Receivables

TermSync uses data analytics to help small and midsized businesses better understand how and when they're being paid.

Analytics is popping up in small corners of the world. I talked recently with Mark Wilson, whose company, TermSync, applies analytics to -- get this -- receivables.

That's right, receivables -- the amount businesses are owed by their customers.

Wilson, a CPA, started TermSync in 2010. Based in Madison, Wisconsin, the company offers a cloud-based service to improve transaction processing for small and midsized businesses. In 2012 it began expanding its features, offering customers data on their accounts and on how they compare to other companies.

"We just sent them notes questioning why, if you have 30-day term, is your average collection time 47 days?" Wilson says. That got customers' attention.

Companies make collection calls or send reminders about past due bills, Wilson says, but they don't formally track what they've been doing. TermSync's software automates the collection of that data so companies can start tracking metrics about their receivables over time.

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According to Wilson, companies don't pay much attention to their receivables. "It's historically a boring process that people [don't] put time and resources into it," he explains. "We're competing with Post-It notes and Outlook reminders and Excel spreadsheets."

Wilson says adding analytics was a difficult shift for his team to make because it is a different kind of development mindset. But it paid off in sharply higher sales.

TermSync, which remains a small company with less than $10 million in sales, runs its analytics on a quarterly basis, although customers can use its tools to perform their own analytics as often as they like. It looks at how fast companies pay and how much they write off, and offers insights into why customers don't pay on time. TermSync sends each customer a report showing how it compares to other companies in its industry.

So what do analytics tell a company about its receivables? How about this: If a bill is more than 60 days past due, it's most likely your own fault.

In fact, using incorrect purchase order numbers on bills turns out to be the number-one reason invoices are 60 days past due, according to TermSync's analytics. The second reason? Companies send their invoices to the wrong person. These explanations not only debunk the common assumptions that bills aren't being paid because of poor cash flow or because the customer is simply dodging the bill -- they also provide information about a problem the company can easily fix.

Receivables may not be the sexiest application of analytics. But the advantages of knowing more about when you're being paid are clear. And when it's being used to create innovation in a business backwater like receivables, the power of analytics really comes into focus.

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