Prior Situation / Scenario:

  • Business decisions were not based on data
  • Many data sources were dispersed and not fully integrated
  • Different reports measure the same business KPIs (Key Performance Indicators) across the departments
  • Complexity to implement predictive ML (Machine Learning) models

Client Challenges:

  • Develop a data centric organization strategy
  • Define and prioritize Analytics use cases in order to improve business decisions, processes and reduce operation costs

Strata Solution/ Key Enablers:

  • Workshops to prioritize use cases, knowledge sharing to educate on importance of data and capabilities of advanced analytics
  • Set up a cross functional team to develop data driven use cases
  • Design and implementation of ML models for collection, fraud prevention, preventive maintenance and demand planning


  • Data availability for advanced analytics and reporting
  • Business decision-making based on KPI results
  • ML models for collection and fraud prevention, demand planning and preventive maintenance
  • Data driven corporate culture improvement


The new digital approach represents a significant change in the company by creating a Data Lab Team of 5-30 people that has already delivered significant results, going from one to eight-trimester projects