DSCSA Deadline Represents A Crossed Threshold Into The SCMD Era

iStock_000055622022_SmallerThere is a not-so-secret situation that has been festering for years in the internal IT systems of many companies in the U.S. pharma supply chain.  In the past, nobody liked to admit it, but most would, because the full extent of the problem was hidden away from public view.  It was an internal problem mostly affecting only internal systems.

The problem was that the quality of the local master data was poor.  Master data is the data that companies hold in internal databases to describe their trading partners (customers and suppliers), products (their own and those of other companies), contract parameters (pricing, authorization, terms and conditions, etc.), and facilities, etc.

Companies get lulled into thinking this data does not change very often, because, that is one of the defining characteristics of “master data”.  But, in fact, for a big company, there are important changes to master data that occur on a daily basis.  Keeping up with those changes is a constant battle.  If you get behind, your business will suffer in subtle but costly ways.  Because of the subtlety, the connection to the cost can be easily overlooked.  It can just fade into the company’s overall SG&A.

Before last fall the master data quality problems of companies in the U.S. pharma supply chain were their own internal problems.  The poor master data quality of one company did not normally induce additional cost on their trading partners so it was not their concern.

But that all changed when companies began exchanging transaction data in advance of the January 1, 2015 deadline of the Drug Supply Chain Security Act (DSCSA).  Those required transaction documents must be accurate, or companies cannot legally receive the corresponding product into their inventory.  Any product that does not match the corresponding DSCSA transaction documentation must be placed into a quarantine status until time-consuming and costly corrective actions can restore it to saleable status.

Notice that these costly corrective actions–which are necessitated by the seller’s poor quality master data–must be undertaken by the seller and the buyer.  In fact, the buyer is forced to rely on the seller and how quickly they can fix their side of the problem.  The buyer’s costs rise the longer the seller’s fix takes.

The biggest culprit is the Transaction Information, or “TI” which every seller must now provide to the buyer along with the drug shipment (enforcement of this requirement and others by the FDA has been delayed until May 1, but the original deadline still stands; see “FDA Postpones Enforcement of DSCSA Transaction Data Exchange Until May 1”).  The data fields contained in this statement are populated by the seller from their multiple internal master databases, including “products”, “trading partners” and perhaps “contracts” and “facilities”.  Data quality problems in those databases can result in incorrect TI, which will probably result in the shipment being quarantined upon arrival at the customer.  This is exactly what happened to too many shipments from manufacturers to wholesale distributors in the last 9 months.

Were those data quality problems fixed after they came to light as the result of these real-time problems?  Yes and no.  Yes, companies probably fixed the problem in their master data files that caused the immediate shipment problems, but unless those companies used the opportunity to crash-implement a company-wide data quality initiative, and implement a long-term program designed to keep up with the steady stream of changes, then, no.


In my view, the experience the industry just went through last fall and winter is a reflection of the fact that the local “product” and “trading partner” master data held by these companies has now become Supply Chain Master Data (SCMD).  That is, this master data is no longer just an internal resource, it is now a supply chain resource, and all companies in the supply chain have a stake in maintaining the accuracy of that data.  When SCMD is not kept up-to-date, all companies in the supply chain suffer—all companies pay for the inefficiencies that result.

Now that the industry has crossed over the threshold separating the local master data era from the SCMD era, it is finally time for the industry to adopt GS1’s master data synchronization service known as Global Data Synchronization Network (GDSN).  For the first time, GDSN makes sense in the US pharma supply chain because it will save companies money by providing a mechanism that automatically maintains their local copy of the SCMD—the master data that is actually owned and maintained by their trading partners—rather than maintaining it themselves manually.

My hope is that company leaders will take a close look at GDSN and realize it is a better solution than simply implementing their own local master data cleanup program.  That local approach is not a long-term solution because those programs inevitably end and errors creep in again.  In fact, that local cleanup is just the first step to adopting GDSN (see “Before You Sign Up For GDSN, Get Your Data In Order With A Data Quality Program”).

Through this recent stressful experience, the senior leaders of companies in the US pharma supply chain should now have a better appreciation for the value of clean master data and they should be more willing to consider ways to improve their own situation.  For the first time there is a quantifiable cost associated with inaccurate supply chain master data.  Based on that, companies can now justify paying the fixed cost of GDSN.

This industry finally has a cost justification for GDSN, but GDSN only offers an ROI to individual companies if it is widely and deeply adopted throughout the supply chain.  GDSN is now the right long term solution for companies, but it must be adopted by the industry.  Here is something else that the industry must organize and commit to doing as a group or it will not happen (see “DQSA: The U.S. Pharma Supply Chain Must Organize, Or Risk Failure“).

See my earlier essays about GDSN, SCMD and data quality, but keep in mind that all of these were written before the industry crossed the threshold into the SCMD era described above: