Effective downstream logistics processes—the movement of products from their final production or packaging sites to end users—are a critical part of pharmaceutical companies’ service offering to their customers. Accurate product picking, on-time delivery and uninterrupted cold chains are vital elements of these processes. Despite their importance, the logistics systems of most companies are unnecessarily complex and inefficient, however. Worse, they usually pay too much for the service they receive.
This state of affairs has its root in the historical development of pharma logistics chains. Most companies have relied on their strong sales and marketing organizations in individual countries to develop logistics systems that suit the needs of their local markets. The result has been a wide diversity of approaches, considerable redundancy between adjacent regions, and significant management complexity. The logistics service providers contracted to execute these processes have had little incentive to improve them. Instead, they have been able to charge a “pharma premium” to their clients, making the industry a particularly profitable niche.
Now an increasing number of companies are recognizing that they have the opportunity to simultaneously improve service levels and reduce costs by adopting a more holistic approach to logistics network design. As they do so, they have made some surprising discoveries.
Problems with Prices, Not Costs
Companies can reduce the costs of their outsourced logistics networks in two ways. Commercial levers involve negotiating more favorable prices from service providers, usually as a result of competitive pressure, or in return for increases in volume or longer service contracts. Structural levers involve reductions in the actual cost of delivering the service, usually by optimizing the size and positions of warehouses and the transport flows between them. In most industries, structural levers offer by far the largest opportunity to reduce costs, but in our experience with a number of medium- and large-sized companies, the reverse is true for the pharmaceutical sector. In practice, at least half the potential savings in pharma logistics costs come from commercial renegotiation.
Build Better Benchmarks
The size of the potential logistics cost savings comes as a surprise to pharma logistics executives, who feel they have been diligent in reviewing their supplier costs by regularly benchmarking their current contracts against competitor offers. Unfortunately, as high costs are endemic to the sector, such benchmarking efforts fail to reveal the true savings potential. In addition, many pharma supply contracts are framed in a way that bears little relationship to the actual costs incurred by service providers, being invoiced on a percentage of sales basis, for example.
To escape the benchmark trap, leading companies are turning to first principles as the basis for their logistics contract renegotiations. Rather than starting with their existing agreements, these companies are adopting a “clean sheet” approach, in which they build a model of the real costs of running their networks from the ground up then look for providers who can offer that service at an appropriate price.
Clean sheet models can cover long-haul distribution from plants to warehouses, the costs of handling and storage and transportation to the end customer. They will typically take into account details like driver wages, specific route distances and shipment frequencies as well as labor, energy and space costs for warehouse storage and packing operations. While such granular analysis may seem daunting, proprietary models are available with detailed in-built cost databases for many regions around the world.
One company that used this approach discovered that, even including a reasonable profit margin for the logistics service provider, every tender it received for logistics services was at least 40 percent too high. The company immediately abandoned the tendering approach in favor of aggressive renegotiation of terms with providers.
The clean sheet approach provides powerful benefits when applied to structural levers too. Once companies have a picture of the real costs involved in storing, picking and transporting products across their networks, they can model and compare alternative scenarios to explore the options for improving logistics performance through network optimization. Does it make sense to close warehouses in individual countries and supply customers using cross-border shipments? Will the efficiency benefits gained from consolidating more product movements through a single warehouse and a single service provider outweigh any potential increase in transportation costs?
Most companies find it useful to apply a phased approach when conducting such analyses. They might begin by building an “unconstrained” model, designed to fulfill current logistics requirements at the lowest possible cost. Such models can suggest dramatic cost reductions, but their implementation is rarely possible since there will be significant commercial, political or regulatory constraints requiring companies to retain certain product flows or warehouse locations. The first model acts as a useful benchmark, however, allowing companies to compare the impact of potential network changes against an ideal system, rather than their current one.
In subsequent modeling phases, companies can add their business constraints to the model and explore the network designs possible within those constraints. They can also compare the savings delivered by certain network changes with the cost, complexity and risk associated with implementing them, allowing them to quickly distinguish structural changes that generate real savings from those that achieve only moderate savings and yet require major transformations.