Srinivas Suresh, Supply Chain Lead at Joby Aviation, brings a wealth of experience from tech giants like Tesla and Apple. He shares insights on creating innovative supply chains for groundbreaking technologies like electric aircraft. The conversation emphasizes the transformative power of data intelligence and the critical need for adaptable strategies in manufacturing. Suresh also highlights the potential of AI and robotics in reshaping processes, while discussing Joby’s ambitious vision for flying cars to revolutionize transportation.
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Rapid Iteration and Unknown Challenges
Prioritize rapid iteration using the design, build, test, learn cycle.
Address unknowns by planning for potential disruptions and having mitigation strategies.
insights INSIGHT
Lessons Learned and Challenging Norms
Learning from past mistakes, specifically understanding "what not to do," is crucial for improvement.
Question the status quo and focus on "why not?" instead of accepting industry norms.
insights INSIGHT
Building a Culture of Innovation
Aligning company leadership around outside-the-box thinking is crucial for fostering a culture of innovation.
Design adaptable and resilient supply chain strategies that can handle micro and macro business needs.
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"When you're working on new technology, none of these product and manufacturing processes exist. Getting to build, identify, and create those supply chains, and that's the best part of my job," reflects Srinivas Suresh, Supply Chain Lead at Joby Aviation, capturing the excitement driving innovation in manufacturing today.
The challenge of building supply chains for cutting-edge technologies is becoming increasingly complex as manufacturers push the boundaries of what's possible. From electric vehicles to commercial drones, and now revolutionary ridesharing aircraft, supply chain leaders must create entirely new processes while ensuring reliability and scalability.
Suresh's journey to Joby Aviation spans multiple innovative industries. After moving from India to Dubai and then to the United States for higher education, he built his career across procurement, supply chain, and manufacturing operations at companies including Tesla, Impossible Aerospace, and Apple. This diverse experience gave him unique insights into scaling production from prototype to full-scale manufacturing.
In This Episode
This episode explores how data intelligence is transforming supply chain management, the importance of building adaptable and resilient strategies, and the future impact of AI and robotics on manufacturing. Suresh shares valuable perspectives on sustainability, supply chain disruption management, and the exciting potential of electric aircraft to revolutionize transportation — from short urban hops between San Francisco and San Jose to eventual cross-continental travel.
Topics
The importance of rapid iteration and velocity in supply chain management for new technologies, focusing on design, build, test, and learn cycles.
Building resilient supply chain strategies that can adapt to disruptions through diversification and strategic planning at all supply chain levels.
Leveraging data intelligence and analytics to optimize supplier selection, quality control, and supply chain decision-making processes.
Balancing sustainability goals with business objectives in pre-revenue companies while maintaining focus on long-term environmental impact.
The critical role of supply chain system automation in maximizing value across the entire manufacturing process.
Implementing effective data governance strategies to ensure high-quality data supports meaningful supply chain decisions.
The future impact of combining AI and robotics in transforming manufacturing processes across various industries.
Creating adaptable supply chain strategies that can respond to geopolitical tensions, material shortages, and natural disasters.
The evolution of electric aircraft manufacturing from urban mobility solutions to potential cross-continental transportation.
Building supply chain processes that support innovation while maintaining quality and reliability in aerospace manufacturing.