Warehouse worker using tablet to manage inventory; data-driven logistics concept

How Data-Driven Pharmaceutical Logistics Improves Fulfillment

“It has become painfully clear in recent years that potential supply chain disruptions across all industries have become more the rule than the exception,” writes Suzanne Shelley in a Pharmaceutical Technology piece about the need for data-driven logistics.

These disruptions cost pharma companies both money and time. Nor does their impact stop with the pharmaceutical manufacturer. Delays or failures in order fulfillment also impact pharmacies, providers and patients. Repeated delays or failures can damage a pharma company’s relationship with payers as well.

A data-driven approach to logistics can help improve fulfillment. Improved fulfillment offers improved outcomes for everyone involved.

Meeting Supply Chain Challenges With Data

Traditionally, supply chain challenges have been addressed only after a delay or failure of fulfillment occurred. Lacking the data or tools for real-time tracking, companies all over the world took a “fix it only when it breaks” approach.

That approach has always had its shortcomings. In a world where real-time data collection and analysis is an option, however, the “step in only after a problem occurs” method is increasingly unworkable — and unacceptable.

Many options exist today for collecting logistics data in real time, analyzing it efficiently, and responding to potential, developing or actual issues that may affect fulfillment. Yet adoption of these tools has been inconsistent among pharmaceutical companies.

“In an ideal world, I’d like to see life sciences supply chains break down the linear and functional siloed approach that exists today to become a dynamically connected ecosystem that integrates the full supply chain network in a collaborative and optimized way,” says Stephanie David, a principal partner, advisory, at KPMG.

To achieve this goal, pharmaceutical supply chain participants need robust data analysis tools, reliable sources of information and an overarching vision of the goals to be achieved by the use of these tools.

Worker scanning packages; data-driven logistics concept

Choosing the Right Data Tools to Improve Fulfillment

One way to think about meeting supply chain challenges with technology is through a Pharma 4.0 lens. Rather than relying on outcomes (such as successful order fulfillment) to monitor the success of the process, Pharma 4.0 deploys AI and other technologies for real-time monitoring and adjustment, writes ThermoFisher Scientific’s Nicola Gardner.

While originally created as a way to improve the pharma manufacturing process, Pharma 4.0 can help to improve supply chain performance and order fulfillment as well. In logistics, the model is also referred to as “control tower technology.” Similar to the way an airport’s control tower tracks all incoming and outgoing flights, control tower technologies in pharmaceutical logistics provide a single centralized point of information for tracking and fulfillment of orders.

“Milestones for courier delivery are fed directly into our system, so that we know when it is at the airport, when it is handed from the courier to the airport’s ground handler, and when it is on the flight,” says Adalheidur Palmadottir, vice president of business development at supply chain management company Controlant.

One way to put control tower or Pharma 4.0 thinking to work is by incorporating a single platform to track manufacturing, orders, distribution and related information such as payer participation and patient medication use. This data provides a 360-degree view of key issues related to fulfillment, from how medications travel to whether a patient’s needs are likely to change the volume or frequency of medication orders.

Supply chain challenges will remain a key concern in the biopharma industry for some time. Companies that respond with comprehensive tracking technologies will improve logistics and order fulfillment — becoming more efficient and building stronger reputations.

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