Procurement | Innovation | Supply Chain | AI

The AI-powered lab supply marketplace: How AI is improving the customer buying journey

43% of procurement leaders are actively planning to implement generative artificial intelligence (AI) within 12 months. Yet, a recent ZAGENO poll discovered that only 14% are utilizing AI within the life sciences procurement function. While the integration of AI may seem intimidating, the potential benefits are exponential. In the recent March 2024 webinar, “The AI-Powered Supply Chain: How Supplier Diversity and New Tech Build Resilience,” ZAGENO’s supplier relationship partnership team unveiled how ZAGENO is already using AI to revolutionize the customer buying journey and accelerate scientific advancement.

AI and machine learning in the lab supply purchasing space

With hundreds of thousands of biotech and pharma lab supply purchases flowing through ZAGENO, it serves as an ideal platform to explore and optimize the transformative benefits of AI and machine learning utilization on the lab supply purchasing process and the broader supply chain. While the following offers insight into how AI is being leveraged at the ZAGENO lab supply marketplace to optimize the purchasing process, such learnings benefit the entire life sciences industry as we collectively strive to harness this technology to innovate, prevent shortages, increase morale, protect the supply chain from risk, and, most importantly, improve scientific outcomes. 

Utilizing AI to revolutionize the life science buying journey 

life science buying journey

  • Product discovery. The ZAGENO marketplace offers a continuously expanding selection of 40 million products from thousands of suppliers. Its diverse portfolio is designed to provide researchers with access to the established brands they trust, while also introducing them to numerous small and medium-sized brands they may not yet know.

    Chart - Growth of number of suppliers available on the ZAGENO lab supply platform

    Growth of number of suppliers available on the ZAGENO lab supply platform

    It is exceedingly time-consuming when biopharma and pharma companies attempt to manage the process of building and maintaining hundreds or even thousands of supplier partnerships on their own. Tasks such as account setup, payment term management, invoicing, and contract negotiations all demand significant labor and resources. The herculean task of catalog maintenance is also involved. Traditionally, the acquisition, loading, organization, and categorization of millions of SKUs has been labor-intensive and complex, with near-flawless data required for accuracy. Historically, product content has been the manufacturers’ responsibility, but many lack the resources to compile comprehensive sets of detailed descriptions, attributes, and images in a widely usable format for distribution partners. Furthermore, supplier catalogs and pricing are subject to frequent changes, making manual catalog upkeep nearly impossible without a massive team to scour site by site and file by file, an approach that is neither efficient nor effective.

    Herein lies the transformative power of AI and machine learning to enable automated data review, extract relevant information, and organize for quality assurance and publication. With each iteration, AI improves in accuracy and efficiency, aiming for a 100% success rate in catalog accuracy across all suppliers and products industry-wide. Coupled with ZAGENO’s agnostic search engine, researchers can swiftly discover their ideal products or explore new options to advance their scientific endeavors, all within seconds.

  • Product qualification. In the next phase, ZAGENO’s goal is to ensure that scientists have seamless access to the essential documents necessary to validate the suitability of discovered products. Utilizing AI capabilities, ZAGENO can efficiently source and compile associated product documents such as Safety Data Sheets (SDS), Certificates of Analysis (COA), manuals, white papers, and relevant publications. With this readily available information, the product search process is streamlined, empowering users to confirm that the products align with their requirements. This reduces the risk of purchasing the wrong products, minimizing both money and valuable time wasted on reordering.

  • Order processing and tracking. In this stage, ZAGENO employs AI to aid in the decision-making process of supplier selection. By analyzing shipment data from suppliers, ZAGENO generates a predicted ship date (PSD) that factors in the supplier's order processing speed.

    The PSD considers several key factors, including:
    • Supplier’s level of integration capabilities for immediate order processing
    • Efficiency of the supplier's pick, pack, and ship process
    • Location of the supplier's warehouse,  including international shipping considerations

Through continuous monitoring and evaluation, AI ensures the accuracy of the PSD, providing scientists with valuable information beyond just pricing—the estimated receipt date. This feature empowers scientists to make informed decisions and plan accordingly when urgent supplies are needed.

Future applications of AI to improve the lab supply procurement process

ZAGENO is introducing AI-driven request for quote (RFQ) functionality in April 2024. This enhancement will empower scientists to search for capital equipment on the ZAGENO platform, with ZAGENO facilitating direct communication with manufacturers regarding customization, technical inquiries, installation, and training. As this feature evolves, AI is poised to play a pivotal role, offering insights into customization options, lead times, and virtual training opportunities, further streamlining product selection. If the scientist discovers that the “right” product isn’t what they had in mind, AI can suggest alternative or complementary products, as well as recommend reorders or standing order options. 

Challenges of AI implementation

Implementing AI has proven to be a fascinating and multifaceted endeavor, presenting continuous learning opportunities. The complexity of AI becomes apparent in the details, such as taking into account the differences between a pipette tip and a primary antibody, each with its unique technical aspects. AI isn't a ready-made solution; it requires ongoing input of information and training to achieve the desired outcomes. 

With a team comprising industry veterans, including PhD-level scientists, software engineers, and AI experts, ZAGENO is poised to incorporate even more cutting-edge AI features in the future. Learn more about how AI is being used to revolutionize the customer buying journey and strengthen resilience with our free eBook.

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