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Procurement-Insight-Analysis

Procurement Analysis Project, used to teach Excel & Power BI skills to a new data analyst.

Project Overview

This project uses a Procurement KPI dataset sourced from Kaggle. The dataset contains purchase order (PO) details from suppliers and allows analysis of delivery timelines, order statuses, negotiated savings, compliance, and procurement performance.

Objective

The objectives of this project are to:

  1. Calculate the duration between Order Date and Delivery Date.
  2. Analyze the number of orders delivered, cancelled, or pending.
  3. Measure the total negotiated savings (Unit Price vs Negotiated Price).

Data Understanding

The dataset consists of 777 rows and 11 columns.

Column Description
PO_ID Unique purchase order ID
Supplier Supplier/Company fulfilling the order
Order_Date Date when order was placed
Delivery_Date Date when order was delivered (if applicable)
Item_Category Category of the purchased item (e.g., Office Supplies, Raw Materials)
Order_Status Status of the order (Delivered, Pending, Cancelled, Partially Delivered)
Quantity Number of units ordered
Unit_Price Original price per unit
Negotiated_Price Final negotiated price per unit
Defective_Units Number of units received as defective
Compliance Whether the order met compliance standards (Yes/No)

Missing Data:

  • Delivery Date → 87 missing values (likely pending or cancelled orders).
  • Defective Units → 136 missing values (may indicate no defect report).

Methodology

Excel

  • Data cleaning: removed duplicates, handled blanks, standardized formatting.
  • Created calculated fields (e.g., delivery duration, amount saved).

Power BI & Power Query

  • Created new columns for delivery duration and negotiated savings.
  • Built interactive dashboards for visualization.
  • Applied DAX for KPIs (e.g., average delivery period, amount saved, total orders delivered).

The Dashboard

Screenshot 2025-09-17 191006

The Insights

  • Average Delivery Period: 53.68 days.

  • Total Orders Delivered: 560 (out of 777 orders).

  • Amount Saved: ~4 million through negotiated prices.

    Delivery Timelines:

    • 691 orders delivered in time.
    • 76 orders had unknown delivery periods (likely pending/cancelled).
    • 8 orders were above/extra time.

    Amount Saved by Categories:

    • MRO → 902K
    • Office Supplies → 844K
    • Electronics → 743K
    • Packaging → 733K
    • Raw Materials → 709K

Order Status Breakdown:

  • Delivered → 560
  • Pending → 81
  • Partially Delivered → 73
  • Cancelled → 63

Recommendations

  1. Focus on categories like MRO and Office Supplies, which generate the highest savings.
  2. Investigate suppliers associated with delayed or unknown delivery timelines.
  3. Develop stricter follow-up processes for pending and partially delivered orders.
  4. Reduce defective unit rates through supplier performance reviews.
  5. Expand negotiations in low-saving categories like Raw Materials to improve cost efficiency.

Conclusion

This procurement analysis shows how Excel & Power BI can be applied to monitor supplier performance, track delivery efficiency, and optimize cost savings. With an average delivery period of 54 days and savings of 4 million, organizations can leverage these insights to improve compliance, negotiate smarter, and streamline procurement operations.

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Procurement Analysis Project, used to teach Excel & Power Bi skills to a new data analyst.

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