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BBVA Fuels Digital Transformation Progress with a Data Science Center of Excellence

By

Elena Alfaro Juan Murillo Arias Fabien Girardin Barbara Wixom Ida A. Someh

Learning Objectives

  • Evaluate why BBVA established its data science center of excellence as a separate legal entity, and how that structure helped attract talent, pursue external data products, and experiment outside traditional banking routines.
  • Examine how the CoE created value through a mix of external monetization, social-good projects, and internal business-unit initiatives that improved costs, revenues, customer experiences, and decision quality.
  • Analyze how BBVA balanced short-term project delivery with long-term capability building through co-location, partial business-unit funding, shared platforms, reusable data engines, and data “rainmaking.”
  • Assess how BBVA measured the economic impact of data science projects and used that measurement discipline to manage its portfolio and demonstrate value to the bank.
  • Consider how training, communities of practice, common tools, and executive-level data leadership helped spread data science practices and shift BBVA toward a more data-driven culture.

Abstract

BBVA was a global financial group that established a data science center of excellence (CoE) in 2014 to co-create high-value analytics-based solutions with BBVA project teams; create innovative BBVA data science capabilities; and lead BBVAís data-driven culture change. BBVA established the CoE as a wholly owned subsidiary called BBVA Data & Analytics, and by 2017, the CoE had taken several noteworthy actions, which included (1) launching more than forty data science projects for approximately one-third of the business units at BBVA; (2) commercializing a flagship data product for markets in Spain, Mexico, and Colombia; and (3) developing an active, BBVA-wide data science community of practice. The case illustrates exemplary CoE activities and describes lessons learned that can help managers accelerate the spread of data science and maximize financial returns from their own data science investments.

Appropriate for the Following Course(s)

digital transformation, data management and analytics, data monetization, organizational design, and organizational culture

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THERE IS NO TEACHING NOTE FOR THIS CASE STUDY.