68 percent of organizations believe that the lack of a uniform language and unambiguous data definitions (taxonomies) systematically leads to noise and miscommunication in the data. This is according to a study by IT service provider and data exchange specialist SureSync, which surveyed 433 decision-makers at organizations with more than 250 employees. The lack of taxonomies translates into extra work for decision-makers. For example, 61 percent report that they often have to manually adjust incoming data because the quality is insufficient.
In addition to the lack of taxonomies, the technical integration between supply chain partners can also contribute to data noise, as a poorly configured integration makes proper data exchange impossible. In practice, however, only 5 percent of organizations have a fully integrated system connection with supply chain partners. For the largest group—43 percent—the systems are connected only to a limited extent.
Well-functioning technology and a uniform language are not the only prerequisites for high-quality data exchange, however. Collaboration between parties also plays an important role, as the lack of clear agreements within the supply chain can lead to confusion. Sixty percent recognize the scenario where, when a data problem arises, everyone in the supply chain points fingers at each other without anyone solving it. It’s not just the supply chain; organizations themselves also fall short. For example, 65 percent indicate that work pressure leads to data quality being given lower priority.
Sander Odijk, managing director at SureSync: “Organizations invest heavily in integrating systems such as ERP and HR, but they assume too readily that these systems will automatically understand each other as a result. An integration only indicates whether data arrives—not whether its content is accurate or interpreted the same way by everyone. If the integration isn’t up to par, data arrives distorted, and employees spend endless hours correcting it instead of looking ahead. The solution, therefore, is not merely technical but largely organizational: agree with your supply chain partners on the meaning of terms, work with clear taxonomies and definitions, and establish ownership by designating a data owner for each domain. Technology connects systems, but a common language ensures that they truly understand one another.”