Pharma: Strategy and Analytics to Control Shipping Costs
The pharmaceutical supply chain is complex, and involves a certain level of uncertainty and risk. Of course, with high customer expectations and shorter product life cycles, the pharmaceutical supply chain must overcome major obstacles to achieve customer satisfaction while reducing costs.
According to recent research, the pharma supply chain is under immense pressure to improve efficiency through supply chain risk management (SCRM) techniques. Read on to understand the major challenges in the pharmaceutical supply chain and how data analytics can be leveraged to address shipping challenges in particular.
With a complete transportation spend management solution, Trax offers pharmaceutical companies of all sizes the chance to minimize risk and maximize profits. The advanced analytical features available in the Trax product suite gives enterprises the tools they need to overcome challenges in pharma.
Supply Chain Challenges in Pharma
Over the past several years pharmaceutical companies had to face not only the COVID-19 pandemic, but also inflation, geopolitical conflicts, and mixed therapeutic modalities. Together, these obstacles have led pharmacos to develop new operational strategies surrounding sourcing, manufacturing, and the supply chain.
According to McKinsey and Company, the pharma industry is facing operational forces that both enable and constrain the industry. For example, while advances in digital technology offer significant growth opportunities for pharmacos, opposing forces include labor market shortages, inflation, and general supply chain disruptions. How can enterprises leverage the growth opportunities while also mitigate constraining factors?
The key is that while external activities influence the pharmaceutical industry, the industry itself also affects the environment. Therefore, the pharma industry is creating opportunities through new modalities, innovation, and the diffusion of individuals' payers' power. While pharmacos continue to face challenges related to rising research and development costs, by leveraging the power of big data, global enterprises are becoming more agile and resilient.
Pharmaceutical Shipping Challenges
Pharmaceutical companies face unique challenges related to freight and delivery. For example, because many drugs require a specialized container closure system to ensure its shelf-life and efficacy, there are additional costs related to maintaining quality by design.
Recently, global regulatory agencies have begun to enforce specific Good Storage and Shipping Practices, greatly impacting cold chain management.
Therefore, manufacturers and wholesale distributors need to be diligent when it comes to quality assurance, while also being mindful of excessive costs. The goal is to balance efficiency and quality in such a way that the product and/or the customer doesn’t suffer while the seller can continue to make a profit. This has led to increased emphasis on developing more innovative shipping technologies.
Pharma Supply Chain and Data Analytics
Implementing and understanding data analytics is a priority in the pharma supply chain. From manufacturing to production, transportation, and sales - data visibility is crucial for optimizing processes and driving ROI.
According to Bain and Company there are five high-impact digital manufacturing trends emerging in pharma. Innovative solutions like production performance management, predictive analytics, changeover support, and advanced planning are expected to roll out in two waves. Bain and Company describes the first wave as “No Regrets” because the solutions are easy to implement and result in quick cost savings. The second wave, however, requires more work to implement.
For instance, while using predictive analytics to maintain equipment is a quick implementation, leveraging predictive data for quality management involves catching problems before they arise by identifying patterns in the data, which many pharmacos haven’t yet managed to adopt.
Trends in Pharma Data
The pharmaceutical supply chain becomes more sophisticated as companies continue to leverage big data. A few of the trends in pharma data today include predictive analytics, industrial internet of things (IIoT), and the precision medicine initiative.
While pharmacos are getting better with data mining and modeling to develop predictive techniques related to maintenance and quality management, there is more to this trend. Predictive models will be used for research and development, bioprocessings, and simulations. In addition, the success of these initiatives hinges on whether companies along the pharma supply chain lean into a more collaborative mode of data exchange.
The IIoT is an important part of a pharmaco’s digital transformation. By combining robotics, artificial intelligence, advanced analytics, and more, enterprises improve efficiency throughout the supply chain.
Precision, or personalized, medicine involves customizing generic drugs to the patients based on their genetic makeup. For instance, by collecting data from the human microbiome, manufacturers can determine which drug is a better fit from a patient.
Types of Data in Pharma
In general, big data in pharma will fall into one of three buckets: unstructured, structured, or semi-structured.
Unstructured data includes free text, such as comments made on social media accounts. Oftentimes, unstructured data isn’t put to good use because it requires extensive cleaning and processing to feed a machine learning model. However, using unstructured data can make a big difference to a pharma co, specifically related to understanding off-label uses of drugs and customer feedback.
Structured data is the big data that pharmaceutical companies typically leverage. This data is already processed and clean enough to feed a machine learning algorithm to drive insights. However, more often, data will end up being semi-structured. This means that there may be some text that requires tools like natural language processing as well as quantitative data that requires some human input before generating a predictive model. All three types of data are important to pharmacos and therefore, it is imperative to leverage all forms of data available to a company to drive meaningful results.
AI for Pharma Data
Even though AI is a buzzword in most industries today, it can’t be overemphasized in the pharmaceutical industry when it comes to improving efficiency. An article by Ignat Kulkov (2021) explores the role of artificial intelligence in pharma with regards to business process transformation.
There are two main areas that AI impacts - predictions and recognition. We’ve mentioned predictive analytics previously, but now it’s time to go into more specific use cases. AI can be used to find the probability of specific events occurring, which then allows analysts and data scientists to predict when something will occur based on real-time data. For example, AI algorithms are useful for predicting equipment load during production.
Going a step further, pharmaceutical companies can even use AI to enable robotic control of order preparation. By automating aspects of the warehouse that were once tedious, AI systems can increase productivity by 20% or more, according to Forbes’ study of Lineage Logistics.
Software for Pharma Shipping Data
Having proprietary predictive models and automation systems give pharmaceutical companies a competitive edge in the market. Likewise, those that employ the most reliable and advanced software for pharma have an advantage. When it comes to software for pharma shipping data, there are three concepts to keep at top of mind: Traceability, Transparency, and Efficiency.
Traceability & Transparency
Traceability in the supply chain refers to the ability for information to be tracked and traced. In the pharmaceutical industry, companies tend to employ traceability technologies to detect counterfeit drugs. A good example of this type of technology is Radio Frequency Identification (RFID). When drugs are ready to be shipped, they can be scanned by RFID to ensure that authentic products are being distributed. Another innovative solution is blockchain, which can serve as the basis for a prescription drug monitoring system.
Efficiency
Of course, maximizing efficiency during shipping is a major goal in pharma. RFID and predictive analytics work together to enhance efficiency at multiple levels of the pharma supply chain. Key examples include Pick-by-Voice systems used for inventory management during storage and delivery phases. Pick-by-Voice solutions use voice messages to manage inventory, rather than relying on paper or electronic orders.
Pharma Freight Rate Data
When it comes to pharmaceutical cold chain logistics, freight rates have been reported as stable for about half of the global enterprises but increased 10-20% for about one-fifth of businesses, according to research by Li et al. (2020).
Maintaining visibility into freight rates is an integral part of managing shipping costs in pharma. Freight audit and payment systems benefit pharmaceutical companies by improving visibility, empowering companies to become more proactive, and saving costs. From validating invoices to and making data-driven decisions, the right logistics partner plays a major role in the pharma supply chain.
Pharma Freight Audit and Payment for Streamlining the Supply Chain & More
If you’re looking to streamline your pharmaco’s operations, consider partnering with Trax. As a global leader in transportation spend management, Trax offers the software and data management capabilities necessary to combat fluctuating shipping costs. By identifying inefficiencies and opportunities for both cost and time savings, it is possible to remain competitive in today’s pharmaceutical industry. Contact Trax today to learn more about our data, carrier, and financial management solutions.