Fashion Retail · 27 brands · 22K employees · R$14.2B revenue · 100+ stores
Reserva (AR&Co / Azzas)
RESULTS
Reduction in data quality incidents
Potential logistics savings (~15%)
ML model accuracy (vs 52% baseline)
Directors and CTO advised
CONTEXT
Reserva, part of LATAM's largest fashion group (Azzas/Arezzo), needed to transform its data operations. Legacy BI in disconnected tools, no governance and a distribution center with significant operational inefficiencies.
CHALLENGE
Legacy BI fragmented across SQL Server, Pentaho and Tableau. No data governance, logistics inefficiencies in the distribution center and low sales forecasting accuracy.
SOLUTION
Strategic data & AI consulting. Team restructuring, cloud migration (Databricks + AWS), governance model, ML forecasting and customer service redesign.
WHAT I DID
Advised CTO and directors on restructuring the data team into a strategic squad with OKRs. Led migration from legacy BI to cloud-native stack. Implemented governance model reducing incidents by 90%. Built ML model (XGBoost) for forecasting at 73% accuracy vs 52% baseline.
WHAT WAS HARD
Advising without executing: as an external consultant, the challenge was influencing strategic decisions without direct control over execution.