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6 Tips to Keep Up With GS1 Data Model Changes

Learn how to efficiently manage GS1 data model changes and boost your FMCG retail operations with our expert tips and insights.
March 10, 2022 • 6 min read
PIM  
PIM  
6 Tips to Keep Up With GS1 Data Model Changes
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Are you a retailer in the FMCG sector, connected to GS1, and do you have a machine-to-machine interface? Do you face the same challenges every quarter to keep up with the pace of GS1 Global Data Model changes, as announced in the GS1 release? Below, we describe the importance of the GS1 datapool for retailers and provide tips to help you successfully and systematically implement periodic GS1 data model changes. As a leader in Europe, with a successful data quality program, the Benelux data model is used as a basis in this article.

Since a retailer, unlike a supplier, must have everything in order on the day of the release, the pace of consecutive releases can be challenging for retailers. While a supplier has up to three months after the release to implement the changes, as they need to gather, record, and forward the new information, a retailer must do this before the release. This is especially challenging when it involves many, sometimes legally required, changes. Think, for example, of previous releases.

GS1 Datapool & Data Model  

GS1 provides a central source for high-quality product data across various sectors, including the FMCG sector. The Global Data Syndication Network (GDSN) is used, with 45,000 companies currently connected. The central source for product information is the GS1 datapool, where the data model is leading. In the data model, suppliers and retailers reach a consensus on what the standards in the sector should be. Besides expertise in product information from various sectors, legal guidelines also shape the data model. Think of legal provisions regarding ingredients, environmental levies, and hazardous substances. The standards are embedded in the form of fields with validations, input instructions, and code lists. Changes in international GS1 standards are always included when they concern the Benelux data model.

Given the continuously growing demand for information, stricter legislation, and changing international standards, it is crucial to keep the data model up to date. You could say that the pace of the world of product information dictates the pace of GS1 changes. Therefore, a new data model release takes place four times a year. The GPC product classification list is updated twice a year. These updates are incorporated into the releases, with two relatively larger and two smaller each year. By timely implementing the data model changes, you always comply with the law. Additionally, it positively impacts competitiveness because complete and correct product information contributes to the shopping experience and builds trust, encouraging consumers to purchase.

Impact on Your Organization  

The impact of a GS1 data model release on your organization varies depending on the size of the release and your product range. If your organization has a wide and variable assortment with a very fast turnover of products, it is almost impossible to create or enrich all product data yourself. The dependence on a datapool then becomes significant.

To succeed in PIM, a retailer must first look inward. What does my assortment look like? What product information is needed to ensure internal processes run smoothly and safely? What information is legally required to be shown to consumers? What product information positively impacts my competitiveness? The impact of the release thus depends on the purpose of the data.

Tips to Manage the GS1 Release  

Without in-depth knowledge of the assortment, it is very difficult to assess which data model changes apply to your organization and what the impact is. To gain insight into this, an integrated approach is needed, where data mapping and data governance are crucial.

Article data mapping is the process of matching fields, code lists, and validations between different systems. This allows data to be exchanged between GS1, your PIM system, and the underlying landscape. Since article data has different endpoints within an organization, accurate mapping reveals the impact on various systems and departments. Therefore, create a mapping between GS1, your PIM system, and the underlying landscape. This way, the impact of a change on different systems and departments will be visible at a glance.
Ensure that the GDSN name of fields and code lists is included in the mapping. These names are used to communicate between the different datapools in GDSN. Therefore, a GS1 data model release will always contain the GDSN names. Another major advantage of using GDSN names is that you can easily utilize the GS1 Attribute Explorer. This is an online tool designed to help you fill in product information. In the tool, you will find field descriptions with associated code lists, input instructions, validations, examples, etc. The easiest and most consistent way to search for this information is by using GDSN names, as a GDSN name is always unique, preventing any misunderstandings in the search results.
Another prerequisite for successfully implementing data model changes is an effective data governance structure. Practically, this is a structure that allows an organization to manage data effectively so that processes run smoothly and business goals can be achieved.
A good link for an integrated approach is a ‘product owner’ role. The product owner orchestrates the various facets of a data governance structure. In a GS1 release, the product owner takes a position between data owners in the business, functional management of different systems, and GS1. The product owner ensures that everyone speaks the same language and that the GS1 change is interpreted in the same way.
When your organization meets these basic requirements, it is important to create a business case and start a project. Maintain the same structure and GDSN terminology in the project as in the GS1 release documentation. It is necessary to use a project management tool to manage the workload and dependencies of a project. Use the tool to break the project into smaller chunks and monitor progress. This way, you can quickly see what needs to be done to meet the deadline.
Finally, ensure that you can receive both the new and old data models. Suppliers can still deliver data according to the old data model for three months. Some suppliers will transition to the new data model faster than others, but as a retailer, you don’t want to miss any data! Start early and allocate sufficient time for data migration and testing to ensure no data is lost and you are not faced with surprises on release day! Only after migration and this period is it safe to remove obsolete fields, code values, validations, hierarchies, and GPC bricks to keep the configurations in your PIM system up-to-date.

Conclusion  

For an initial implementation of a PIM system, GS1 data model, or other related digital transformations, Squadra uses the SCOPE model. This model supports clients at every stage of their digital transformation. In this article, you can clearly see some aspects of that model. If you would like to learn more about our SCOPE model or the implementation of GS1 in your organization, please feel free to contact us!

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