As an Analytics Lead in Supply Chain Analytics I've worked on multiple projects across supply chain.Seller Experience Improvement : Worked closely with multiple business teams to improve seller satisfaction score. Developed an RCA framework that helps in identifying various seller pain points leveraging data of key logistics performance metrics.Multi-Pickup speed goodness : Proposed a process change to improve end-to-end delivery speed. Simulated the process change with existing data to estimate the speed improvement and the cost incurred. Worked closely with business/product/engineering teams in implementing this new process.Supply availability prediction : Developed an availability prediction model to identify unplanned absenteeism in last mile network. This will help in taking necessary proactive steps to bridge the gap between last mile demand and supply. Productionized the model for real time prediction and consumption of the output.

At Flipkart I have worked across various teams building process KPIs, solving business problems and driving growth by leveraging data. Provided business solutions using various advanced analytical and data modelling techniques. Few of the projects I have worked on recentlySupply Chain Analytics – City Logistics• Developed a framework & tool for designing ‘Asset Lite Last Mile Supply Network’ based on projected future demand (i.e. delivery hubs locations, serviceable regions, delivery models to be on-boarded, etc.) leveraging Pixels, density & partition clustering and optimization techniques• Automated the process of daily route allocation by extracting the manual intelligence in daily route planning using PCA and implementing an optimization algorithm to maximize route familiarity• Performed in-depth analysis on customer availability during delivery attempt and identified key drivers, using Random Forest technique, to improve delivery conversion and reduce cost• Extracted dense customer hotspots across cities, using OPTICS clustering technique, to identify the potential and scale up a new delivery models using lockers, kiranas etc.• Designed last mile delivery network for groceries in multiple cities by applying K-Means clustering & cost optimization algorithms to identify the best locations for warehouse and delivery hubs• Evaluated various processes in city logistics network to identify all factors impacting the process performance and developed waterfall data models to measure the impact due to each factor and to take preventive and corrective actions to improve them

Supply Chain Analytics – First Mile• Pinpointed opportunities for cross utilization of assets among first mile and last mile operations to improve asset productivity & utilization resulting in cost reduction• Accurately apportioned the total first mile cost to individual shipment and evaluated the average pickup cost incurred for each seller to take key business decisions to drive cost improvement• Evaluated ideal time slots for seller pickup to improve slot adherence & seller experience

Hyderabad City - Business Analyst• Efficiently segmented driver partners based on their performance and optimally designing incentive schemes to maintain partner earnings. Successfully improved city profitability by improving Effective Net Take Rate (ENTR) from -20% to -3.5%• Proactively monitored customer demand sessions, supply availability, supply attrition and reactivation to take necessary supply shaping activities and reduce customer stockouts• Tracked day-on-day, week-on-week performance metrics to take live corrective actions to achieve platform growth & targets

Business Analyst - Multiple Analytics teams (Fulfillment Center, Affiliate Marketing, Large Appliances supply chain)1) Design and implement optimized data pipelines to address live visibility of supply chain operations, KPIs, various analytical reporting etc.2)Identifying and analyzing trends of multiple KPIs for end-to-end supply chain. Performing RCA to identify any deviation from trend and processes with scope of improvement3)Providing business insights for process redesign and process improvement with rigorous data analysis. Support the pilot runs for process redesign/improvement till the final implementation4)Automation of processes with manual intervention (to reduce human dependency) by implementing various intelligent data models, optimization algorithms