Product master data: NDC, GTIN, drug name, manufacturer, dosage form, and other product details.
Location master data: Business name and address details associated with a company GLN or other identifier.
There are a couple of issues with master data when it becomes supply chain master data—data that is shared with trading partners. One is the lack of automation involved in its exchange. When trading partners begin pilot tests with one another, the exchange and configuration of such data is typically done manually (such as through spreadsheets). There are several problems with this:
1. It doesn’t scale. Manual setup is fine for a pilot or two, but such a setup process doesn’t scale across dozens or hundreds of trading partners.
2. Standardization doesn’t yet exist for some of the specific data elements that need to be exchanged.
3. Different companies may request different formats with different data element names depending on their EPCIS implementation.
4. Supply chain master data changes over time. Package configurations, dosage changes, and other product details may change over time. A manual data exchange process is an inefficient (and tough to validate) way of transmitting those updates.
As you scale your deployment, it becomes important to automate the file format and the method for exchange. Some thoughts to keep in mind as you ponder supply chain master data:
1. What do you need from others? You need to understand what supply chain master data you need from your trading partners.
2. What do your supply chain partners need from you?
3. How will you manage updates? Until you can automate a scalable synchronization process for exchanging supply chain master data, you will need to put into place some sort of process for all trading partners to manually keep one another’s master data up-to-date.
Liked this article? Download the entire playbook here.
