Andres Bucchi on Rebuilding an Airline for the 21st Century: LATAM's Data-Driven Transformation
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LATAM Airlines
Andrés Bucci is the Chief Data Officer at LATAM Airlines, where he leads the company’s transformation into a data- and AI-driven organization. His team spans domains from pricing and marketing to operations and safety, scaling experimentation and applied machine learning across one of the world’s most complex industries.
Before LATAM, Andrés was VP of Data & Analytics at Sodimac, Latin America’s largest home improvement retailer, where he built experimentation and analytics capabilities at scale. He previously spent four years at Uber in San Francisco and Chile, working across operations, strategy, and applied machine learning in pricing.
An entrepreneur at heart, Andrés also co-founded Experimento Social, a software and analytics consultancy in Chile, and today advises early-stage AI companies on strategy and adoption.
Delphina
Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He is the host of the industry podcast Vanishing Gradients, a podcast exploring developments in data science and AI. Previously, Hugo served as Head of Developer Relations at Outerbounds and held roles at Coiled and DataCamp, where his work in data science education reached over 3 million learners. He has taught at Yale University, Cold Spring Harbor Laboratory, and conferences like SciPy and PyCon, and is a passionate advocate for democratizing data skills and open-source tools.
Key Quotes
Key Takeaways
Legacy Data is Gold: The Untapped Potential of Historical Data.
LATAM’s decision to retain decades of data, even without immediate applications, proved invaluable. This highlights the strategic importance of data preservation and the potential for future value discovery.
From Months to Weeks: Accelerating Experimentation in a Complex Organization.
LATAM drastically reduced experiment cycles by fostering a culture of experimentation and investing in the necessary infrastructure. This demonstrates a path for data leaders to drive rapid iteration in traditionally slow-moving industries.
The Decision Bottleneck: Beyond Model Performance.
As models improve, the limiting factor shifts from model building to the speed and quality of human decision-making. Data leaders must focus on enabling informed decisions based on AI insights, not just generating those insights.
GenAI as Applied Engineering: A Pragmatic Approach to Adoption.
LATAM’s strategy of treating GenAI as a software engineering problem – leveraging existing talent and focusing on integration – offers a practical roadmap for enterprise adoption, avoiding costly research projects.
Grounding for Trust: The Importance of Data Lineage and Explainability.
Like with agentic systems, demonstrating clear data lineage and explainable reasoning is critical for building trust and driving adoption of AI-powered solutions.
Cross-Functional Data Teams: Breaking Down Silos for Maximum Impact.
LATAM’s data team spans nearly every department, enabling a holistic view of the business and unlocking value across diverse domains. This underscores the need for cross-functional collaboration and data literacy.
Fuel Savings & Fraud Detection: Unexpected ROI from Data Investment.
LATAM’s success in areas like fuel optimization and fraud prevention demonstrates the potential for significant ROI from data initiatives in unexpected areas.
The Future of Data Leadership: Orchestrating Human-AI Collaboration.
The ultimate challenge for data leaders is not building AI, but orchestrating a collaborative relationship between humans and AI, maximizing the strengths of both.
You can read the full transcript here.
Timestamps
00:00 The Scale of LATAM Airlines and the Data Function
00:52 Meet Andreas Bucci: From Uber to LATAM Airlines
02:01 Building an Experimentation Culture in a Traditional Industry
06:54 LATAM Airlines: Data-Driven Growth and Experimentation
10:20 Optimizing Operations and Fuel Efficiency with Data
21:02 Experimentation and Zero-Based Budgeting at LATAM
23:58 The Challenges and Benefits of Zero-Based Budgeting
24:13 Fraud Detection in Latin America: Challenges and Solutions
29:21 Generative AI: Current Deployments and Future Vision
37:44 Scaling Data Work: Challenges and Strategies
42:04 The Human Aspect of Decision Making in AI
43:34 Exciting Future of Data, ML, and AI at LATAM
49:17 Conclusion and Final Thoughts
Links From The Show
Transcript
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