This morning, an archived article from August 2023 on The Wall Street Journal website, Ozempic, Weight-Loss Drugs Carry Costly, Complicated Logistics, got my attention. The gist of the article was that though these drugs are popular and generate huge revenue, not all of that is being translated into bottom-line gains. And one of the primary drivers behind that is the specialized logistics cost.

As quoted in the article: “The gross profit margins on them are low, and then the operating expenses are a little higher because of the cold-chain nature of the product.” So, if we go by the classic gross margin formula, COGS seems higher than desired. Now I assume because of the nature of the product, manufacturing and packaging costs are high as well, and can also benefit from analytics. But in this article, let us focus on the logistics costs.

Traditionally, Pharma is no stranger to reefer or cold chain logistics. Let us analyze the components highlighted in the article as driving the high cost.

• Need to keep the shipments in a tightly controlled environment, ensuring temperatures are stable and the goods are also protected from odors that can affect them.
• Need to carry a higher level of insurance
• Need to be outfitted to keep the products secure to prevent theft, a particular risk with expensive drugs

We will focus on the first bullet in this article. We can’t do much about the second until we reduce the manufacturing cost significantly, and an article I wrote a few weeks ago covered the third bullet point.

As highlighted previously, Pharma companies are no strangers to cold chains. Due to the nature of the products, the entire chain needs to be at a specific, stable temperature. But based on my experience, pharma supply chains, specifically the logistics, are highly non-optimal. I suspect that with high margins on most drugs that need sophisticated cold chains, the cost had never been an issue. Hence, there was no need to significantly streamline the processes by leveraging AI or any other form of analytics.

This “habit” has also diffused to the distributor’s side. As you may have read in the WSJ article, distributors make good money on these shipments, and pharma companies have happily paid. The spot rate cost difference of $2.44/mile for cold chain vs the $2.07/mile for dry may not seem very big, but translated to large volumes, it means millions and millions of Dollars. And reducing that difference can help pharma companies improve margins.

So, how can you reduce that rate if you are a distributor? Let us start with warehouse design.

Cold chain warehouses are temperature controlled, but in my opinion, not temperature optimized. Large areas or sections are maintained at a specific temperature range. And though the area may house various products, that broader range can be divided into more temperature ranges to house those same products in different range areas. And that is possible by designing an AI-controlled reefer warehouse.

The first step is to leverage analytics on the SKUs and temperature requirements to create optimal, realistic ranges (since you can’t realistically have 100 temperature zones in a warehouse, which will also not help improve but will increase the cost).

If implemented effectively, this can cut down these warehouses’ operating costs by at least 20%. This will obviously lead to decreased storage costs for these products. Then comes the transportation part. This is more complex than warehousing to design and implement, but once implemented, in terms of people, processes, and technology, it can yield significant cost savings.

Like the warehouse design, it starts with data. You understand the temperature ranges, lanes, and volumes, among other parameters, and then design a fleet and network around that. This ensures you run trucks with “optimal” temperatures for specific products on particular lanes. Note that this also means changing refrigeration units currently leveraged on the trucks, which are not all “smart” units.

We have just done a high-level overview of the approach. An entire document detailing the approach can be written. But the gist is that there is an opportunity to significantly reduce the inefficiencies of these supply chains and, hence, improve gross margins by leveraging advanced analytics.