Nevedha Ayyanarappan

• Built predictive models for forecasting and demand planning to analyze historical data and forecast next purchase date and corresponding quantity of Make-to-Order (MTO) SKUs expected to be ordered in next 180 days.
• Performed thorough Exploratory Data Analysis (EDA) as part of data cleaning and identified key features that significantly improved coverage accuracy to nearly 65% for rolling period of 180 days, with deviation of +10/-10 days.
• Enhanced forecasting model has been recognized by Institute of Supply Chain Management (ISCM) for reduced operational costs and improved supply chain efficiency of 20%.

Big Bazaar:

• Developed and implemented data cleaning and transformation process using python and reduced data errors by 30% and improved data accuracy.
• Conducted statistical analysis on customer behavior data, leading to identification of key factors affecting customer retention and increasing the customer retention by 15%.
• Created interactive dashboards in Power BI for sales team, facilitating real-time tracking of sales performance and contributing to 10% increase in sales revenue.
• Collaborated with cross-functional teams and created data models to understand product demand, resulting in 20% reduction in excess inventory cost.
• Prepared monthly reports for executive leadership, summarizing key insights and actionable recommendations, which improved decision-making processes.

Decathlon France:

• Performed preliminary data exploration and migrated country homologation report from in-house tool to Tableau, ensuring data accuracy and alignment with business requirements.
• Conducted data assessments and data mapping to understand structure and logic of existing report, facilitating smooth migration.
• Optimized existing SQL queries in Redshift by using CTEs and materialized views for frequently used queries which resulted in 40% reduction in query execution time.
• Collaborated with data engineers to enhance data infrastructure and improve data availability for reporting.
• Led user training sessions on Tableau reporting, enabling end-users to navigate and interact with dashboards effectively.

• Analyzed existing systems to identify gaps, inefficiencies, and areas for improvement and providing end-user training to enable seamless adoption and optimal use of integrated solutions.
• Reorganized existing database to establish dependencies between numerous data sources and normalized schema which improved the performance of internal tools by 75%.
• Built interactive dashboard that aids upper-level management in making informed staffing decisions and/or planning for talent acquisition.