AtliQ Mart, a growing FMCG manufacturer headquartered in Gujarat, India, is currently operational in three cities: Surat, Ahmedabad, and Vadodara. They plan to expand to other metros/Tier 1 cities in the next 2 years. However, they are facing a challenge where a few key customers did not extend their annual contracts due to service issues. It is speculated that some of the essential products were either not delivered on time or not delivered in full over a continued period, which could have resulted in bad customer service.
To address this issue, the management has requested their supply chain analytics team to track the 'On time' and 'In Full' delivery service level for all the customers on a daily basis so that they can respond swiftly to these issues. The Supply Chain team decided to use a standard approach to measure the service level in which they will measure 'On-time delivery (OT) %', 'In-full delivery (IF) %', and 'On Time in Full (OTIF) %' of the customer orders on a daily basis against the target service level set for each customer.
This project aims to provide these insights using Power BI for data visualization and analytics. By leveraging data visualization and analytics, we aim to identify bottlenecks, inefficiencies, and opportunities for improvement in the supply chain.
The data used in this project comes from various sources within AtliQ Mart's operations, including sales data, inventory data, and more. This data is then processed and visualized in Power BI.
The project includes several visualizations, including:
- Sales over time
- Inventory levels
- On-time delivery (OT) %
- In-full delivery (IF) %
- On Time in Full (OTIF) %
These visualizations provide a clear picture of the state of AtliQ Mart's supply chain and highlight any potential issues or areas of improvement.
Through this project, we hope to provide AtliQ Mart with the insights they need to optimize their supply chain operations and make data-driven decisions.
Going forward, we plan to incorporate more data sources into our analysis and create more complex visualizations to provide even deeper insights into the supply chain operations.