Executive Q & A: Models Matter

Q: Let’s start by putting manufacturers’ challenges in context. How should they view/ start the distribution planning process?

A: Distribution strategy is just as much of an art as it is a science. There’s rarely a perfect answer to the question “How do I plan my distribution strategy?” It’s all about balancing the benefits versus the trade-offs.

One distribution model might offer the manufacturer a broader network of dispensing locations or sites of administration—but reduce the level of data visibility at any given time. Another model might give a manufacturer realtime data on utilization and patient demographics—but create some access hurdles for the healthcare providers who are administering the product. Starting the process with the understanding that there will always be trade-offs is a key step in ensuring realistic expectations and success.

In terms of the models, while one approach certainly does not fit all, every manufacturer’s needs also do not demand a completely unique solution and model. If you think of building a distribution network in terms of physical construction, most scenarios can be addressed as a modular construction project rather than a fully custom build. Changes to existing distribution models can and should be made to accommodate individual manufacturer needs, but it’s far more cost-effective and timely for a manufacturer to work from an existing model than to try and create something from scratch. More often than not, it ends up yielding better financial returns as well.

Q: What are the keys to selecting the right distribution strategy and channel?

A: The pharmaceutical manufacturers that we’ve worked with successfully have kept in mind three primary factors when selecting the appropriate distribution channel: sites of care, expectations for service and balance of needs. Manufacturers must accurately assess sites of care. They need to know whether or not the sites that will be ordering a specific product are accustomed to ordering, paying for, administering and supporting that product type.

They’ll also need to align internal expectations and expectations with their distribution partner. For example, how much working capital will the manufacturer have and need? What will the fee structure for services look like? What types of services will be required—and how will manufacturers see reporting and data to measure value?

Finally, selecting the right distribution channel requires evaluating the balance of needs. What should the balance be between product access, data capture and cost? (Pull Quote) This is the decision-making lens that manufacturers most often struggle with when evaluating distribution models, and while there’s no magic formula for determining a “right” answer, it’s something that can’t be ignored in the process for evaluating distribution models.

Q: Keeping these considerations in mind, what are the data points manufacturers should focus on?

A: A lot of it revolves around numbers and characteristics. The numbers are numbers of sites and patients. Then it’s types of sites, other manufacturer services, product characteristics (cost, allocations or other special needs) and usage—whether it’s acute, chronic, immediate or scheduled. These are the attributes manufacturers are evaluating and measuring as they make decisions around distribution channels and strategy.

Q: How might all these considerations be practically applied to specific specialty distribution models?

A: We can look at two different models with fairly divergent characteristics to give us a picture of how distribution impacts product strategy (and vice versa). There’s the dropship model, with stocking in one location and one data collection point. This model offers high control over customers and a holistic view of costs. The model works well for manufacturers that encounter supply-side challenges around meeting productions demands; however, it does require some customer education to minimize process disruption.

Model Match-Up:

A Snapshot Of Two Distribution Models And Drivers For Using Them.

Dropship Model

• Low-volume products
• Limited availability products
• Short-dated products
• Detailed data collection requirements
• Few administration sites
• High per-order costs
• Stringent storage/shipment/security requirements

Specialty Pharmacy Model

• Hub-administered patient support and data collection
• Reimbursement challenges
• Controlled distribution
• High need for patient advocacy/education or adherence support

Manufacturers might consider the dropship model for low-volume products, products with limited availability, short-dated products and ones that require detailed data collection. It’s also a model that’s used for products with comparatively fewer administration sites, high dollar-per order costs or when there are more stringent requirements around product storage, shipment or security.

Compare that to the specialty pharmacy model, in which a manufacturer stocks and collects data from anywhere from one to 12 locations. The specialty pharmacy model is often accompanied by a third-party hub that manages how patients are routed to selected specialty pharmacies, normalizes and collects data and provides patient support services. The specialty pharmacy model works well for products that present reimbursement challenges, such as payer-driven prior authorization issues or high Part D copays. Manufacturers also consider specialty pharmacy when they want controlled distribution or there is a strong need for patient advocacy, education or adherence support services.

Q: Can you share any examples of how different distribution strategies have impacted a manufacturer’s supply chain effectiveness?

A: In the case of a manufacturer we’ll call “Manufacturer X,” we’ve seen tremendous gains in terms of increased supply chain efficiency. Manufacturer X initially had an open distribution model for a specific product—“Product X”—that was shipped to pharmacies, wholesalers and clinics through a third-party logistics (3PL) distribution model.

Manufacturer X’s goal was to maximize access to Product X; however, Product X had high potential for abuse and was closely monitored by the DEA, which meant each shipment underwent extensive review. Adding to Manufacturer X’s challenges was the fact that the breadth of its distribution network was causing payment issues.

In an attempt to streamline access, Manufacturer X narrowed its distribution network, shipping Product X only to known and trusted wholesalers. As a result, supply chain effectiveness increased and both product diversion and outstanding receivables decreased.

Q: How is distribution changing? What innovations are you seeing in distribution models?

A: The consumer mindset in pharmaceutical distribution is no different than it is across other parts of our lives—we want real-time data and we want control. And manufacturers want those things without a drastic, negative impact on product access. There is a distribution model within AmerisourceBergen that takes data and control one step further. The depot model allows data collection at the time of order by requiring providers to input provider- and patientspecific info. This effectively eliminates delays in reporting and the need to integrate multiple data sets or use external data bureaus. It does require additional effort on the hospital, pharmacy or practice when they place an order—so while the model has substantial benefits for manufacturers, thus far we’ve seen it best applied for high-value, unique products.

Q: Any final thoughts?

A: Manufacturers have to remember that products don’t exist in a vacuum. They always need to be mindful of what competitors are doing with their distribution strategies. If they don’t keep up, it will be difficult to catch up—asking a customer to order one product through a more cumbersome channel than competitor products is unlikely to prove successful. Supply chain efficiency is also critical. If you can leverage the same channels or the same logistics partner for multiple products, you can see value manifested in cost savings and increased productivity in how you’re managing and acting upon your distribution data. And finally, think long-term and globally. Keep future expansion in mind all the time—new products, new geographies, new channels. There are always new possibilities for optimizing your product’s performance, but you have to plan for it.

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