When "Good Enough Data" is Not Good Enough

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For years, a longstanding Dun & Bradstreet customer in the wood product manufacturing industry relied on D&B Finance Analytics to automate their credit operations, which enabled their fast-growing business to expand by a factor of ten while maintaining credit process and policy discipline with the same two-and-a-half team. 

However, a low-cost credit provider teamed with a third-party software provider and approached the wood manufacturer's procurement team with a proposal for "enhanced workflows" and comparable data that would undercut Dun & Bradstreet’s price by 40%. The customer was promised the same quality of data and automated processes comparable to Dun & Bradstreet, so they decided to save the money and move to the low-cost providers. 

Signs of Trouble

The wood manufacturer was heavily reliant upon their established automated processes and agreed on a three-month implementation timeline. In the interim, the small credit team manually shouldered the approximate 400+ monthly credit decisions. Given the detailed nature of the credit review process, the team was stretched.  The quality of the decisions suffered both because of the manual process and the quality of data. The team immediately noticed the quality of data in the new provider’s credit reports was inferior to Dun & Bradstreet’s credit data.

While the client had known the new, lower-cost provider’s data was not as comprehensive or predictive as Dun & Bradstreet’s, they were hoping that they could get close to the same decisions with the “good enough” data.

"The other data provider consistently lacked the level of insight required to confidently perform even basic credit reviews. We wound up having to verify the customer's information through Google and then contacting their trade references, which is quite a manual process. It turned from a simple process into a pretty hands-on and time-consuming one. So instead of being able to provide credit decisions in a few hours, it turned into days,” the company’s credit manager said.

Promises Broken

In addition, once the agreement was signed, the new vendor provided very little support for integrating the data and implementing the software.

“The support we received during the transition was minimal at best. Promises were made about the ability of the software that just were not met,” the credit manager said.

The customer decided to end the relationship with the low-cost provider when the software could not be configured to meet their needs, despite being told it could, and the system was still not deployed several months after the promised date. The poor-quality data and limited software capabilities caused too much disruption in their credit operations.

Back to Dun & Bradstreet

The customer turned back to their Dun & Bradstreet account team for a further enhanced solution, which increased their operational efficiency through integration and automation, ensuring they spent minimal time evaluating over 5,000 credit decisions each year. They were quickly up and running again. Returning to their automated processes and Dun & Bradstreet’s trusted data allows them to continuously evaluate the risk of their entire A/R portfolio while delivering great results. 

“We depend on Dun & Bradstreet’s scores like the PAYDEX and the Failure Score to power our scorecard and our own rules for assessing risk and setting up credit limits. We use Account Manager for monthly updates on all our accounts. As for reporting - it's easy to upload your own in-house information and create reports. Without D&B Finance Analytics we'd be waiting for our own IT team to try to come up with these reports for us, which would never happen,” the credit manager said.

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We like to share our customers’ successes and inspire other teams that may face similar challenges. Due to the sensitive nature of some customers’ businesses and their data strategy, we respect their privacy and do not identify them by name on dnb.com.