Procurement Spend Overview & Risk Analysis

User_W9LCF · Mar 2, 2026 6:14AM

1. Which dataset did you use?

I used the Spend Transactions dataset provided by the Oracle.

2. How did you analyze or prepare the data?

I prepared the data by reviewing and categorizing fields as attributes or measures and grouping transactions by supplier, category, and agreement flag to assess compliance and concentration risks. Then I built summary metrics, bar charts, treemaps, and line charts to visualize total spend, supplier distribution, category breakdowns, and monthly trends, highlighting anomalies such as the July 2024 spike in Computer Equipment spending.

3. Who is the intended audience for your visualization?

Procurement Managers: To monitor supplier concentration, contract compliance, and spending efficiency.
Finance Teams: To evaluate budget allocation across cost centers and categories.
Executives & Decision-Makers: To identify risks (off-contract spending, supplier dependency) and make strategic procurement decisions.

4. What is your visualization about, and what question or problem does it address?

The visualization provides a high-level overview and risk assessment of procurement spending.

It addresses the following key business questions:
Is procurement spend overly concentrated among a few suppliers?
What proportion of spending is compliant with contracts versus off-contract?
Which categories dominate procurement costs?
Are there recurring or abnormal spend spikes that require governance review?

By answering these,the dashboard highlights supplier dependency risk, contract compliance gaps, and IT-driven spend dominance, while also identifying potential cost optimization opportunities.

5. Did you use any Oracle Analytics AI features when building your visualization (ex. AI Assistant)? If so, please describe how they were used.

Yes, Oracle Analytics AI features were used to enhance efficiency and insight discovery by applying AI-assisted insights to automatically detect trends and outliers in monthly spend patterns, leveraging smart visualization suggestions to identify optimal chart types for supplier and category analysis. These capabilities enabled faster identification of anomalies and risk patterns while ensuring analytical accuracy.

6. Did you upload your visualization image and dva file?

Completed!

Analytics and AI Challenge 2026.dva