Measuring advancement in analytics

• Look at analytics journey and key components of maturity – IT Infra (Data Engineering), Data lake, Operational Analytics and advanced analytics
• Derive significant business value from internal data across functions through operational analytics
• Build complimenting capabilities and ecosystem led by domain and data science

Key Takeaways

• Assessing current status and maturity of Data/Analytics
• Building the right infrastructure for operational analytics and data science
• Assessing where to use operational analytics through mathematical models (creating right frameworks and KPIs, segmentation) vs. advanced predictive models (forecasting, projecting for samples, predicting certain outcomes)
• Focus on outcomes and not techniques – actionability is the key with clear owners and defined KRAs
• Used case-based application of advanced analytics

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Bio

Ayush Jain – Manager – Strategic Analytics & Data Science | Hindustan Coca-Cola Beverages

Data Ops and Data Science Enthusiast with Retail & FMCG experience; Part-Time mentor for Career Transitions; HCCB | Ex-Tesco | Ex-AB-InBev | Ex-Infosys