Blinkit Business Insights | Achyutha Ravula

Problem Statement

Ensuring a 10-minute delivery promise requires hyper-efficient logistics. The goal was to identify bottlenecks in the delivery pipeline and analyze customer ordering behaviors to optimize resource allocation.

My Role

Cleaned and prepared raw logistics data for analysis.
Designed interactive dashboards to track Key Performance Indicators (KPIs).
Conducted root cause analysis for delayed deliveries.

Tools & Tech

Tableau SQL Data Viz Analytics

Dataset / Inputs

Logistics data including order timestamps (placed, packed, shipped, delivered), courier location data, order values, and customer feedback ratings.

Approach

1. Data Preparation

Ingested raw data, standardized timestamp formats, and filtered out outliers to ensure data quality.

2. KPI Definition

Defined core metrics such as Average Delivery Time, Late Delivery Rate, and Orders Per Zone.

3. Visualization

Built comprehensive Tableau dashboards to visualize spatial and temporal patterns in delivery performance.

Key Insights

Identified specific time windows (e.g., Friday evenings) where delivery times spiked by 20%.
Pinpointed high-friction zones where courier handoffs were slowing down the process.
Found a correlation between lower basket delivery times and higher customer retention.

Business Impact

Operational Efficiency: Insights helped re-allocate rider workforce to high-demand zones during peak hours.
Strategic Planning: Data supported decisions for new dark store locations to minimize travel time.
Performance Monitoring: Enabled real-time tracking of logistics health for store managers.