Supply Chain Analytics

The analysis is done for the supply chain domain of 'AtliQ Mart,' an FMCG company, where the no. of customers renewing the contract is decreasing. The company is present in Vadodara, Surat, and Ahmedabad city and sells its various products in the Dairy, Food, and Beverages Categories. And the stakeholders are the director and head of the supply chain of 'AtliQ Mart.'

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Problem Statement

Background

AtliQ Mart is a growing FMCG manufacturer headquartered in Gujarat, India. It is currently operational in three cities Surat, Ahmedabad and Vadodra. They want to expand to other metro/tier1 cities in the next two years.

Challenge

AtliQ Mart is facing a problem where a few key customers still need to 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 total over a continued period, which could have resulted in bad customer service. Management wants to fix this issue before expanding to other cities and requested their supply chain analytics team to track the ’On time’ and ‘In Full’ delivery service level for all the customers daily 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 daily against the target service level set for each customer.

My Task

Assuming I am the data analyst in the supply chain team who joined AtliQ Mart recently, I have been briefed about the task in the stakeholder business review meeting.

So now I am excited to take on this challenge and build this dashboard and perform the following task:

• Create the metrics according to the metrics list.
• Create a dashboard according to the requirements provided by stakeholders in the business review meeting.
• Generate relevant insights not offered in the metric list/stakeholder meeting.

KPIs used

1. OT%
2. IF%
3. OTIF%
4. LIFR%
5. VOFR%
6. Customer Order Cycle Time (COCT)
7. Delay in Delivery (DID)

Topic Distribution

1. Background Information
2. Analyses
3. Insights
4. Recommendations

Data Model

Analyses Pages

Overview Analysis -

KPI Based Analysis -

Product Analysis -

Customer Analysis -

Insights Pages

Insights 1 -

Insights 2 -

Insights 3 -

Recommendations Pages

City-wise Recommendations

Product-wise Recommendations

Final Insights

• OTIF is a 'Hard' metric from customer's point of view, but we are unable to meet the customer's demand both by quantity ordered and timely delivery in all the cities. We are trailing with an average of 36.6% in all cities, which is hampering the reliability of customer.

• VOFR is performing good compared to LIFR in all the cities which means we are unable to deliver all requested products from customers. So, we should be prepared with inventory beforehand. At least in the demand season.

• 'Delay in Delivery' has been a major problem in all cities. We were able to deliver 18% of order before agreed delivery date. But, for so many orders were unable deliver 'On Time'. The delay is seen for 1,2, and 3 days with an average of 1.21 days.

• Vadodara, being our biggest market, has much efficient supply chain compared to other two cities since COCD in Ahmedabad and Surat is very high. We should have serious attention to this particular case.

• Customers who are our biggest client and facing serious issues are follows. Their issues should be resolved first.

  • Acclaimed Stores.

  • CoolBlue.

  • Lotus Mart.

  • Vijay Stores.