Kartik Pant, Head of Data & AI for Manufacturing & Supply Chain, and Shreyas Becker, Head of AI & Data Products at Sanofi, delve into the critical disconnects between marketing and supply chain workflows. They discuss the concept of an 'end-to-end control tower capability' to streamline data tools, enhance demand management, and tackle stockouts. The duo also explores how AI can optimize localization and compliance in supply chains and the need for effective marketing strategies that inform production during crises, showcasing innovative technology's role in decision-making.
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Quick takeaways
Disconnects between marketing and supply chain workflows can lead to stockouts and demand forecasting difficulties requiring enhanced collaboration and better data integration.
Implementing an AI-driven control tower approach improves supply chain visibility and responsiveness by enabling ongoing demand forecasting and scenario planning.
Deep dives
Challenges in Marketing and Supply Chain Integration
Disconnects between marketing and supply chain workflows can lead to significant issues such as stockouts and fulfillment delays. Marketing provides essential demand signals that are often not aligned with supply chain capabilities, leading to difficulties in accurate demand forecasting. For instance, while marketing might assert a certain demand based on trends or campaigns, the supply chain may not have the necessary data to support this request, resulting in overproduction or stock shortages. Addressing these silos requires enhanced collaboration and improved data integration to ensure a more accurate reflection of demand within the manufacturing process.
Leveraging AI for Localized Labeling and Compliance
In the pharmaceutical industry, managing product labeling compliance across various markets presents unique challenges that can complicate the supply chain. Specific regulations for labeling and serialization can necessitate rapid adjustments in product labeling as market demands fluctuate, affected by government tenders and changing regulations. AI can significantly enhance these processes by automating the creation and management of product quality documents for each market, ensuring compliance while reducing manual labor. This integration of AI into the labeling process facilitates better tracking and tracing of products, vital for maintaining quality and meeting regulatory requirements.
Building a Control Tower for Enhanced Decision Making
A control tower approach can optimize supply chain visibility and responsiveness to demand changes by integrating various forms of data. This involves establishing mechanisms for ongoing demand forecasting, inventory management, and scenario planning, allowing companies to react dynamically to any changes in supply or demand. Even initial implementations of AI-driven predictive analytics can provide substantial benefits, effectively guiding supply chain decisions without necessitating a full-scale AI overhaul. This method enables organizations to monitor critical supply chain indicators and optimize resource allocation, ultimately leading to improved operational efficiency.
Today’s guests include two senior executives from Sanofi’s manufacturing division, Head of Data & AI for Manufacturing & Supply Chain Kartik Pant and Head of AI & Data Products, Manufacturing & Supply Shreyas Becker, respectively. The pair join us on today’s podcast to identify disconnects between marketing and supply chain workflows that commonly lead to issues such as stockouts and fulfillment delays. Later, they share insights on building what they describe as an ‘end-to-end control tower capability’ for data tools to solve these and similar logistics challenges in life sciences spaces. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI consultants, visit emerj.com/p1.
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