This project simulates a real-world procurement process for a construction company. Built entirely in Microsoft Excel, it analyzes supplier performance, spend behavior, bid comparisons, and future material costs to support smarter purchasing decisions.
| File | Description
| Procurement_Project_Dataset1.xlsx | Full dataset with sheets for purchase orders,
suppliers, bids, pricing history, forecasts, KPIs,
dashboards.
| Procurement_Project_Report.docx | Analyst-style report documenting key findings, recommendations, and procurement insights from the project.
| Material_Price_Forecasting_SOP.docx | Step-by-step SOP for forecasting material prices using
Excel’s FORECAST.ETS.
Project Scope
Simulated for a mid-size construction firm managing multiple suppliers and core materials (Cement, Gravel, Steel).
Each phase of the procurement lifecycle was analyzed:
✅ Key Components
- Purchase Order Analysis
Tracked order volumes, lead times, and delays
Identified the most frequently ordered materials
Flagged suppliers with recurring late deliveries
- Spend Benchmarking
Compared company_spend vs. the average market prices
Found cost-saving opportunities (e.g., SUP01’s cement pricing)
Recommended renegotiation or supplier consolidation
- Supplier KPI Dashboard
KPIs tracked: On-Time %, Delay Days, Spend, Cost per Order
Underperforming suppliers are identified using clear thresholds
Added risk ratings to guide supplier decisions
- Bid Evaluation Matrix
Compared supplier quotes for Steel
Scored across price, lead time, warranty, and documentation
Used a weighted matrix to select the optimal bid
- Forecasting Material Costs
Used FORECAST.ETS to project pricing trends for (Cement, Gravel, Steel)
Cement remained stable, Steel showed a rising trend
Recommendations made to lock contracts or monitor closely
- SOP Checklist
Documented required compliance items for each procurement phase
Included folder naming rules and internal file tracking
Ensured readiness for audits or internal standardization
📊 Tools Used
Microsoft Excel (formulas, pivot tables, dashboards)
FORECAST.ETS (time-series forecasting)
Weighted matrix for bid scoring
Conditional formatting and data validation
📌 Key Takeaways
Supplier performance directly impacts cost and delivery timelines
Transparent bid evaluation improves decision accuracy
Market benchmarking helps uncover hidden savings
Forecasting supports proactive budget planning
SOPs reduce compliance risk
📈 Suggested Next Steps
Expand to include more POs and supplier categories
Automate parts of the dashboard using Power Query
Build a real-time dashboard in Power BI or Google Data Studio
Use this framework to guide sourcing decisions and quarterly reviews