Host Shashank Garg welcomes Prateek Shrivastava, Advanced Analytics Manager at Cummins, to The Intelligent Leader Podcast for an insightful discussion on the intersection of AI and supply chain management. Prateek shares how his journey from business intelligence to advanced analytics has driven real-world impact, from optimizing grocery pickup forecasts during COVID-19 to predicting truck failures before they happen. They dive into the evolving role of data science, emphasizing the shift from siloed modeling to AI-driven business integration. The conversation also touches on cutting-edge trends like automation, explainable AI, and the rapid advancements of platforms like Databricks. Whether you're a data scientist, supply chain leader, or tech enthusiast, this episode delivers valuable insights on the future of AI in business.
In this episode of The Intelligent Leader Podcast, host Shashank Garg sits down with Prateek Shrivastava, Advanced Analytics Manager at Cummins and a seasoned data scientist passionate about solving complex supply chain challenges. Prateek shares how his early fascination with math and computers evolved into a career that has taken him from business intelligence to pioneering data-driven solutions at companies like 84.51° and now Cummins. From forecasting surging grocery pickup orders during COVID-19 to predicting truck failures before they happen, he breaks down the real-world impact of AI in ways that go beyond buzzwords. With a mix of technical depth and business pragmatism, Prateek explains why data scientists today must shift from building models in silos to embedding AI into business workflows—where the real magic happens.
The conversation also dives into the latest trends shaping the future of AI and supply chain management. Shashank and Prateek explore how automation, predictive analytics, and even generative AI are transforming operations, making supply chains more resilient in the face of disruptions like tariffs and compliance regulations. They discuss the importance of explainable AI, the rapid evolution of platforms like Databricks, and how companies can scale AI successfully without losing business buy-in. Whether you're a data science leader, a supply chain professional, or just someone curious about the intersection of AI and business, this episode is packed with insights you won’t want to miss.
Key Quote:
“With AutoML, what has happened is you don't have to migrate or move your data from one system to another system. You can just put your data all together in one place, and try out all the models that are already there, it will do a lot of feature engineering for you as well. The data science role has gone from is building models to actually knowing what data is. So if there are any external parameters that you think that will help the system and that has increased a lot of productivity,”
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