A PIM (Product Information Management) or MDM (Master Data Management) solution is often used to store product data and its main objective is to facilitate data enrichment. Often the vendors of these solutions refer to a connection with any data pools or global classifications, in this article we take a closer look at these two terms.
What are data pools and data classifications?
Data pools
Well-known data pools include GS1, 2BA and ICECAT. A data pool is a central environment in which different suppliers can collect all their product data. In this, for example, supplier A provides all information about a bottle of cola of brand X and supplier B provides all information about a bottle of cola of brand Y. The companies that subscribe to these suppliers’ product data can then use this in their own systems.
One advantage of data pools is that they often focus on certain sectors, meaning the information is specific to a particular market. Especially companies focused on food, DIY, plumbing, technology… use data pools. The advantage of this is that they automatically – when set up correctly – keep abreast of the latest product changes without having to process them themselves – manually or otherwise – in their own PIM or MDM solution. Especially in terms of legal obligations, this is often a “must”.
The most important thing as a company is to consider which data pools will contribute most to your own product range and where using these data pools can reduce the workload of your data team.
Data Classification
To keep the entirety of data pools clear, reference is often made to the use of classifications. These are clear predefined structures where products are organised according to certain characteristics and where there is a focus on their global use.
One of the best-known classifications available for different sectors is the GPC (Global Product Classification) used by GS1 to structure data. A classification ensures that different suppliers will only provide the relevant information in the same way for a given product based on a defined uniform structure, the data classification.
In our example where we have different suppliers all delivering bottles of cola, the buyers – retail – will benefit if these different suppliers do so using a predetermined uniform standard. Thus, the data classification will determine what characteristics a bottle of cola has and what makes these products distinctive compared to other products. This eliminates the need to set up n integrations to read the same kind of data from different suppliers.
As with a data pool, a distinction can also be made for different sectors, e.g. there is ETIM for construction and installation companies, ICE CAT for firms specialising in electronics…
Conclusion
Despite having much in common, the two are slightly different in terms of how they work. For instance, data pools are mainly about the supply of data by suppliers and global classifications are mainly about the standardisation of the data structure. Both have the main goal of facilitating data enrichment and delivery of correct data.