Rupam Baijal, Director of Procurement at Algoma Steel, discusses legacy data challenges in extractive industries and the need for digital transformation. He highlights the expertise gap between data science vendors and heavy industry subject matter experts. The conversation explores the obstacles in dealing with outdated data systems and the potential solutions, including AI integration. Additionally, the podcast delves into the complexities of legacy tech stacks, data governance, and the role of AI in enhancing heavy industry operations and decision-making.
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Quick takeaways
Legacy data challenges hinder collaboration between data vendors and heavy industry experts.
AI integration in procurement workflows optimizes supply chains and enhances operational efficiency in heavy industries like steel production.
Deep dives
Legacy Data Challenges in Extractive Industries
In the extractive industries like mining, legacy data poses a significant challenge as technology developed decades ago still forms the basis of operations. Over time, data accumulated in various formats, creating layers of complexity that are hard to interconnect. AI holds the promise of organizing and grouping this diverse data, but bridging the technological gap between data science vendors and heavy industry experts remains a hurdle.
Navigating Legacy Systems and Data Complexity
Addressing legacy data systems requires an understanding of intricate layers of information stored in archaic formats such as punch cards or scanned documents within heavy industries. Vendors struggle to swiftly provide results beyond low-hanging fruits due to the complexities involved in deciphering and unifying disparate data sources. This underscores the critical need for subject matter expertise and efficient collaboration between vendors and industry specialists.
Optimizing Procurement Workflows with AI and Data Sharing
In heavy industries like steel production, the integration of AI in procurement workflows can streamline processes by leveraging consumption data to optimize supply chains. Improved data sharing among industry players can facilitate proactive procurement strategies by predicting maintenance schedules and enhancing operational efficiency. This shift towards data-driven decision-making heralds a future where AI acts as a strategic advisor, revolutionizing industry practices.
Today’s guest is Rupam Baijal, Director of Procurement at Algoma Steel. Algoma is a fully integrated steel producer based in Ontario that sells hot and cold rolled steel products, including sheet and plate. Rupam joins us on the program to talk about legacy data challenges in extractive industries and the need for digital transformation across the sector. Throughout the episode, Rupam measures the expertise gap between data science vendors and heavy industry subject matter experts and explains why it hinders collaboration. This episode is sponsored by Arkestro. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.
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