Show Notes
Daniele Petecchi didn’t realize how complex the process of producing tires was until he joined Pirelli, a company that’s been in the business of manufacturing tires for more than 150 years. But now, as head of data management and AI, he’s focused on leveraging the company’s wealth of data to meet the stringent technical, quality, and performance requirements of the Formula One racers and luxury vehicle makers — like Ferrari, Lamborghini, and BMW — that rely on Pirelli’s premium tires. In this episode, Daniele explains why virtualization and data are key to managing the complexity of an R&D and production cycle that includes using digital twins to predict how a tire will sound on the road and maximizing efficiency at plants that manufacture millions of tires each year. Read the episode transcript here.
Guest bio Daniele Petecchi is head of AI and data managementat Pirelli, where he leads critical initiatives that harness artificial intelligence technology to drive innovation and efficiency for the premium tire manufacturer. Petecchi earned his degree in telecommunications engineering, specializing in digital signal processing, which laid the foundation for his career in technology. He subsequently earned a Master of Science degree in information management, which equipped him with a strong strategic perspective. In 2018, he further reinforced his skill set by completing the General Management Program at ESCP Business School, enabling him to navigate the intricate intersection of technology and business. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Alanna Hooper. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.
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