This project focuses on analyzing and improving supply chain service performance for AtliQ Mart, a growing FMCG manufacturer based in Gujarat, India. The analysis is carried out using Power BI to monitor delivery performance metrics and identify gaps affecting customer satisfaction.
The objective is to help management take data-driven decisions before expanding operations to new metro and tier-1 cities.
AtliQ Mart faced customer dissatisfaction due to frequent delivery issues. Several key customers did not renew their annual contracts because products were either:
- Delivered late
- Delivered in incomplete quantities
To address this issue, management requested a daily tracking system for service-level performance so that corrective actions could be taken in time.
The following standard supply chain service metrics were analyzed:
- On-Time Delivery (OT %)
- In-Full Delivery (IF %)
- On-Time In-Full (OTIF %)
- Average delivery delay (in days)
Each metric was compared against customer-specific target service levels.
I worked on this project as a Supply Chain Data Analyst, responsible for:
- Designing calculated measures for OT%, IF%, and OTIF%
- Building an interactive Power BI dashboard
- Analyzing customer-wise and product-wise delivery performance
- Generating actionable insights beyond predefined stakeholder requirements
The interactive Power BI dashboard enables:
- Daily monitoring of service-level KPIs
- Identification of customers with frequent delivery failures
- Analysis of delay patterns across products and regions
🔗 Live Dashboard:
https://app.powerbi.com/groups/me/reports/127ba0a6-b0d6-4e26-9715-15610d484f81
The data model was designed to ensure efficient relationship management between orders, customers, products, and delivery dates.
- OT%, IF%, and OTIF% are significantly below target levels
- Orders are delayed by ~0.42 days on average
- Lotus Mart, Coolblue, and Acclaimed Stores contribute the highest number of delayed orders
- Dairy products such as Ghee, Curd, and Butter show maximum delays
- No significant improvement trend observed in recent months
- Large gaps in IF% suggest possible production or inventory planning issues
- Power BI
- DAX (Calculated Measures)
- Supply Chain KPIs
- Data Modeling
- Dashboard Design & Visualization
- Practical understanding of supply chain service-level metrics
- Hands-on experience with Power BI dashboards
- Translating business problems into analytical solutions
- Data-driven decision support for operations management
Raushan Yadav
Data Analyst | Supply Chain Analytics