g-f(1)21 Successful Digital Transformation Projects at Repsol: Continuous Learning with AI

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Extra-condensed knowledge

Repsol, a global energy and utility company based in Spain has successfully implemented more than 190 digital transformation projects. Seventy percent of them incorporate artificial intelligence in some way. The bulk of this report offers an evidence-based view of how organizations learn with AI — both the scope of its challenge and its opportunity to transform the organization. Notably, Repsol does more than teach machines how to drill, blend, and serve. In effect, Repsol changed its processes to continuously learn with AI. Process improvements beget new behaviors and new human knowledge, which is then fed back to machines. These dynamics play out continuously, deliberately, and systematically across the organization. Repsol’s ability to learn with AI is fundamental — as our research shows — to obtaining significant benefits with AI.

Genioux knowledge fact condensed as an image.

                                                                         

Condensed knowledge

• Based on over 3,000 survey responses from organizations in 29 industries around the world, as well as interviews with academics and executives, we offer insights into cross-industry adoption of AI, along with a quantitative analysis of those companies achieving significant financial benefits with AI.
• In 2018, Repsol, a global energy and utility company based in Spain, launched an ambitious digital transformation effort. Up and down the company’s value chain, Repsol executives identified and began implementing more than 190 digital transformation projects. Seventy percent of them now incorporate artificial intelligence in some way. These projects are not experiments: They make essential contributions to Repsol’s business model, from upstream drilling operations to personalized offers at downstream retail service stations. “AI is now a cornerstone of an overwhelming majority of the most relevant digital cases transforming our business units,” says Valero Marín, Repsol’s CIO and chief digital officer.
• At its upstream facilities, Repsol created an operations excellence center to use AI to optimize the process of drilling productive wells. Analyzing more than 100 million data points a day, AI solutions help reduce nonproductive time by 40%-50% across 30 drill sites.
• At its midstream refineries, Repsol prepares crude oil for commercial sale, a complex process that coordinates oil blending, storage, and delivery. Repsol uses AI to reduce more than 5 million scenarios to a small set of feasible production options for 30-day time frames. Human engineers then analyze the AI-generated options, incorporating difficult-to-quantify context, and feed their own analyses back to the AI system. Engineers and operations managers collectively changed how they work in order to work with AI.
• Downstream, the company uses AI to prepare personalized offers for 8 million customers across its international network of more than 5,000 service stations. The system generates between 200,000 and 400,000 offers each day. After machine learning algorithms process the resulting outcomes data, managerial insights improve the AI systems that prepare the offers. The personalized promotions have led to a large sales increase — the equivalent of having 3%-4.5% more service stations.

Category 2: The Big Picture of the Digital Era

[genioux fact extracted from MIT SMR + BCG]

Authors of genioux fact

Fernando Machuca

References

EXPANDING AI’S IMPACT WITH ORGANIZATIONAL LEARNING, Sam Ransbotham, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu, And Burt Lafountain, October 19, 2020, MIT Sloan Management Review, Findings from the 2020 Artificial Intelligence Global Executive Study and Research Project, In collaboration with BCG.

 

ABOUT THE AUTHORS

Sam Ransbotham (@ransbotham) is a professor in the information systems department at the Carroll School of Management at Boston College, as well as guest editor for MIT Sloan Management Review’s Artificial Intelligence and Business Strategy Big Ideas initiative.

Shervin Khodabandeh is a senior partner and managing director at BCG, and the co-leader of BCG GAMMA (BCG’s AI practice) in North America. He can be contacted at shervin@bcg.com.

David Kiron is the editorial director of MIT Sloan Management Review, where he directs the publication’s Big Ideas program. He can be contacted at dkiron@mit.edu.

François Candelon is a senior partner and managing director at BCG, and the global director of the BCG Henderson Institute. He can be contacted at candelon.francois@bcg.com.

Michael Chu is a partner and associate director at BCG, and a core member of BCG GAMMA. He can be reached at chu.michael@bcg.com.

Burt LaFountain is a partner and managing director at BCG, and a core member of BCG GAMMA. He can be reached at lafountain.burt@bcg.com.