Supplier Cost and Order Optimization Table

In this project, I analyzed supplier data to evaluate performance and identify cost-saving opportunities. The dataset included key metrics like product category, unit cost, lead time, and reliability. To measure cost-effectiveness, I calculated a

Cost Efficiency Score by dividing reliability (%) by cost per unit. This helped me determine which suppliers offered the best value. Using a pivot table, I organized the data by supplier and product category. This made it easy to compare total costs and order quantities across suppliers, highlighting key differences.

For example:

• Supplier C stood out as the most cost-efficient option.

• Supplier D had the fastest delivery times, which is important for urgent orders.

• Supplier A was the most reliable, but its higher costs suggest an opportunity for negotiation.

The use of Pivot table:

I used a pivot table to summarize the supplier data efficiently and organize it into a clear format. The pivot table allowed me to compare total costs and order quantities across different suppliers and product categories. This approach helped highlight key metrics like the highest and lowest total costs and provided a structured way to identify trends and inefficiencies in procurement.

Conclusion:

This project demonstrates my ability to analyze supplier data, identify inefficiencies, and propose improvements to optimize procurement decisions. Using Excel for pivot tables, calculations, and formatting allowed me to streamline data analysis and present actionable insights. These skills align closely with the responsibilities of a Procurement Analyst, such as extracting data, maintaining systems, and driving process improvements.