Insight
June, 2023
Correct master data is a prerequisite for the digitalisation of numerous processes in retail. Brands within this sector face various challenges due to data quality related issues. Delays in time-to-market and higher fees due to not providing the right product data to customers are amongst the consequences. To mitigate those risks, companies often conduct manual, time-consuming data correction measures, which are often not compliant with industry wide data standards.
The Global Data Synchronization Network (GDSN) is an example of a data standard that is used to exchange product data between trading partners. The goal of GDSN is the adherence to GS1 standards, ensuring that the data exchanged is accurate, up-to-date, and consistent, which is essential for efficient supply chain management.
GDSN is used by a wide range of businesses, including manufacturers, distributors, retailers, and healthcare providers. The market for GDSN-compliant products is growing rapidly, with more than 22 million Global Trade Identification Numbers (GTINs) registered in the GDSN by 2023 and over 3000 different attributes available to be associated with each trade item. GDSN has brought many economic benefits to participants, including a simplified global trade, uniform terminology, common business rules, and implementation guidelines.
Data quality within GDSN is vital as it affects supply chain efficiency, consumer trust, and regulatory compliance. High-quality data is essential for ensuring that supply chains operate effectively and that buyers can trust the product information they receive. GDSN has a central role in providing standardized data sets that help maintaining this standard of data quality.
For retail companies, maintaining high data quality in accordance to GDSN can be daunting due to the complexity of product portfolios and manual data entry processes. The root cause lies within the respective source systems, where the standards are not consequently enforced. Data quality issues can entail, amongst others, incomplete, inconsistent, inaccurate, as well as duplicated product master data. Mostly, data is corrected in an ad-hoc manner and data quality issues are constantly reappearing due to a lack of enforced mater data governance concepts, such as continuous data quality validation. Finally, manual correction efforts are not only time intensive but also error prone.
If a business fails to adhere to GDSN standards, it risks losing trading partners, as they may switch to other suppliers who are GDSN-compliant. This can lead to a loss in revenue and market share. In addition, non-compliance can result in errors in product data, which can lead to incorrect orders, delayed shipments, and lost sales. Furthermore, non-compliance can result in regulatory fines and legal action, which can be costly and damaging to a business’s reputation.
Therefore, it is essential for businesses to adhere to GDSN standards to ensure efficient supply chain management, maintain trading partner relationships, and avoid costly errors and legal action. By adhering to GDSN standards, businesses can ensure that their product data is accurate, up-to-date, and consistent, which can lead to increased revenue, improved customer satisfaction, and a stronger market position.
With the Data Quality Navigator, BearingPoint offers a solution that ensures full transparency, progress monitoring, and high data quality for businesses. It includes an extensive content repository of data quality validation rules, which have been curated by our experts, to ensure compliance to industry standards. Our clients benefit from these out-of-the-box checks on their data, which yield actionable findings, guiding data owners to immediately improve data quality issues. These checks are continuously applied on the data to monitor compliance to current standards and proactively warn if non-compliant data was newly entered in a source system. With the help of concise management dashboards, decision makers retain transparency of the current state of the data, such that they retain the overview of potential data quality driven risks in their organization.
High data quality in GDSN is indispensable for an effective supply chain. BearingPoint can support your clients to stay up to date with current standards, by maintaining high data quality and data harmonization. With our Data Quality Navigator, we ensure that enterprises remain compliant and competitive in a data driven market.