From 150,000 to 3,000 euros write-off a year on bad debt
SEW-EURODRIVE is an established name in powertrain processes. The German company operates in more than 50 countries and, in some of them, SEW relies on Altares Dun & Bradstreet to facilitate the assessment of credit applications. “We are a leading company that stands for quality,” says Harold Nelson, Credit Manager at SEW. It therefore makes sense that we do business with companies with the same high quality in their information system.”
SEW Eurodrive
+4.3
billion turnover in 2021
20.000
colleagues
52
operations in 52 countries
We used to spend 100,000 euros or even 150,000 euros, on writing off bad debt every year. Last year, this was reduced to only about 3,000 euros. Our information system played a part in that."
1. The Challenge
From periodic check to constant monitoring
Scorecards as a result of internal and external data.
The world is changing, and the creditworthiness of customers is changing with it. “And so is our demand for relevant data,” says Harold Nelson. “In the past, we asked Dun & Bradstreet for individual trading reports when we felt it was necessary. But in recent years, we felt the need to constantly monitor the status of our customers in a portfolio management-like environment.”
SEW uses scorecards to assess the creditworthiness of new and existing customers. Compiling those scorecards, which are the result of external data such as that provided by Altares and internal data such as payment history, was easier said than done. The link between the collection of data required for this purpose and a user interface is usually integrated in a cloud solution. “We didn't want to put this in the cloud, but on our own servers,” says Nelson, “and Altares Dun & Bradstreet helped us figure out the solution.”
2. The Solution
Linking of financial data in ERP system
Altares Dun & Bradstreet has the technology to link with SOA People, which in turn is a component in SEW-EURODRIVE's SAP ERP system. Altares now prepares relevant data on a daily basis, which is automatically loaded into SAP via SOA People. Normally users need a new interface to access the data, but now it integrates seamlessly. In addition to the quality of Altares' data, it provides Nelson and his team with great ease of use and more speed. The credit management department at SEW only needs a few FTEs.
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Nelson: “As soon as something changes in the data of Altares Dun & Bradstreet, we automatically get the update. This means that our customers' scorecards are automatically updated, enabling us to assign customers to a risk category.” This allows SEW to deal liberally with a customer who scores well and apply tighter limits for companies with a higher risk. “Sometimes we also ask for an upfront payment to limit the risks,” adds Nelson. “If customers object to this, we can present them with a report justifying our decision. Then, it's up to them to explain why we shouldn't do that.”
3. The result
Better grip on our accounts receivable portfolio
"We used to spend 100,000 euros or even 150,000 euros on writing off bad debt every year," the CCM explains. This means that SEW simply lost uncollectible receivables from customers who went bankrupt. “This has now been reduced to only about 3,000 euros a year. Even though we are sometimes taken by surprise, with the data from Altares Dun & Bradstreet we see problems coming much faster. Obviously, this is no guarantee.”
Before collaborating with Altares Dun & Bradstreet, Nelson had to blindly trust what his own data, and the assessment of colleagues, said about customers. “It's only afterwards that you'll hear about problems, such as non-payments on the customer's part.” He also expects problems on the customer side to increase in the coming months. The war in Ukraine, the expired NOW scheme (temporary emergency bridging measures introduced during the Covid pandemic), and higher gas prices have impacted the manufacturing industry, where most of SEW's customers are operating. Reserves are running out. “We used to know companies based on their reputation. But past results can't help predict the future. The data from Altares Dun & Bradstreet, supplemented with our internal data and algorithms, can do that much better.”
