Merck, the Germany-based pharmaceutical, needs to stockpile medications to make sure it has enough on hand because some expire before they can be used. Its supply-and-demand forecasts are about 85% accurate. To sharpen its predictions, Merck plans to use analytics and machine learning to predict and prevent drug shortages, a move that could also save it money. Its new platform, from TraceLink Inc., can analyze data in real time from organizations within Merck’s supply chain, including pharmacies, hospitals and wholesalers.
The U.S. had 600-1,200 drug shortages every year from 2014 and 2019, reports The Wall Street Journal (Oct. 15, 2019). Shortages can happen due to issues with manufacturing, supply-and-demand forecasts, and natural disasters. Drugs in short supply have included antibiotics, chemotherapy and cardiovascular treatments. More precise supply-and-demand forecasts mean pharmaceuticals could save hundreds of millions of dollars annually, a benefit of not having excess drugs on hand and avoiding expedited shipment costs.
On average, pharmaceutical companies carry 156 days of inventory. For retailers selling consumer products, it is 78 days. For IT equipment, it is 57 days. Pharmaceuticals traditionally have predicted demand for drugs based on historical data and input from sales teams. But as many as 10 entities handle a drug before it gets to a patient, including manufacturers, pharmacies and wholesale distributors. “It’s a highly complex supply chain,” said TraceLink’s CEO. The TraceLink network includes data from more than 275,000 organizations world-wide, including hospitals, retail pharmacies, wholesale distributors and drugmakers.
TraceLink’s algorithms give Merck signals about the days of inventory for a specific drug and how long it will take for a drug to get to a particular phase in the supply chain. A better supply-and-demand forecast also makes it easier for Merck to expand into locations without a reliable supply-chain infrastructure, such as parts of Africa and Southeast Asia.
Classroom discussion questions:
- Why do pharm firms carry such a large inventory?
- How might data analytics improve forecasting at Merck?