⏱ CUTS SPEND ANALYSIS TIME 60%
💰 Procurement
Cost Analyzer
Excel-based procurement model pulling from SQL-aggregated PO data. Delivers supplier comparison tables, spend heatmaps by category, and automated cost-saving alerts whenever a supplier's price exceeds the category average by more than 10%.
€2.84M
Total Spend Analysed
€214k
Saving Opportunities Found
23
Overpriced PO Lines Flagged
60%
Faster Spend Analysis
// live dashboard
Spend Analytics Overview
📊 Total Spend by Category — 12-month cumulative (€)
🏆 Supplier Spend Concentration — top 6 suppliers
📈 Price vs. Category Average — variance % per supplier
📉 Monthly Spend Trend — all categories combined (€)
🌡 Spend Heatmap — Monthly Spend Intensity by Category (darker = higher spend)
Each cell represents one month of spend. Hover for details.
⚠️ Live Saving Opportunity Alerts — suppliers exceeding category average by >10%
▶ Problem
- Procurement teams lacked visibility into supplier pricing trends across categories — cost-saving opportunities remained invisible in fragmented PO data spread across 3 systems.
- Spend analysis previously took a senior buyer 2–3 days per quarter using manual Excel exports — now completed in under a day with automated SQL aggregation.
- No benchmarking mechanism existed: buyers had no way to know if a price quoted by Supplier A was above or below what other suppliers charged for the same category.
- Spend was concentrated: top 3 suppliers accounted for 71% of total spend, yet no consolidation strategy or volume negotiation had been attempted in 18 months.
▶ Solution
- SQL pipeline queries PO header and line tables from ERP, calculates category average unit price per quarter, and flags any supplier line where actual price exceeds average by >10%.
- Excel model consumes SQL output via Power Query refresh — one click updates all charts, heatmaps, and saving opportunity alerts for the full 12-month dataset.
- Spend heatmap built in Excel conditional formatting shows monthly spend intensity by category — immediately revealing seasonal procurement patterns and spend concentration.
- Saving opportunity alerts categorised by tier: High (>25% above average), Medium (10–25%), with estimated EUR saving if price aligned to category average.
▶ Key Findings
- MRO (Maintenance, Repair & Operations) category had the highest price variance — 3 suppliers charging between €8.40 and €14.20 per unit for equivalent items, a 69% spread. Immediate consolidation opportunity worth €47,200.
- Raw Materials spend spiked 34% in Q3 driven entirely by a single supplier (Kovač Chemicals) invoicing at 22% above the category average for 4 consecutive months without buyer challenge.
- Top 6 suppliers account for 68% of total spend — strong consolidation leverage available if volume is used in contract renegotiations during the next sourcing cycle.
- Packaging category shows lowest price variance (±4%) — suppliers in this category are price-aligned. Effort is better directed at Logistics and MRO where spreads are widest.
- 23 PO lines flagged as overpriced totalling €214,000 in addressable savings — equivalent to 7.5% of annual procurement budget accessible without changing any suppliers.
// projections
📈 12-Month Forward Spend Forecast with Savings Opportunity
📉 Projected Annual Procurement Spend · solid = historical · dashed = projected
Base scenario (no action): Total annual procurement spend is projected at €3.12M — a 9.8% increase driven by commodity inflation in Raw Materials and increased Logistics volumes. With savings realised: If the 23 flagged overpriced lines are renegotiated to category average and the MRO consolidation is actioned, projected spend falls to €2.91M — saving €214,000 vs base. Inflation +8% scenario: Assumes commodity price increases flow through unchallenged, projecting spend at €3.38M — underscoring the urgency of locking in price agreements with key suppliers before Q2.
// dataset
📊 Raw Dataset
Real data used in this analysis — 50 rows shown. Download full dataset below.
| PO Number | Supplier | Category | Item Description | Unit Price (€) | Quantity | Total Spend (€) | PO Date | Lead Time (d) | vs. Avg (%) | Saving Opp. (€) |
|---|
// strategic guidance
💡 Advice for Companies with Similar Challenges
💡 Practical Recommendations
- Centralise all PO data into a single SQL table before attempting spend analytics. Even a simple union of ERP exports into one table — cleaned and deduplicated — gives you more spend visibility than most companies have ever had. The analysis itself is straightforward once the data is unified.
- Basic price benchmarking across suppliers in the same category typically surfaces 8–15% in addressable savings within the first quarter. You don't need an external benchmarking tool — your own historical PO data is the benchmark. Calculate category average unit price and compare every active supplier to it.
- Target the highest-variance categories first, not the highest-spend ones. A 20% price reduction in a €200k category beats a 2% reduction in a €1M category. Identify where your price spread is widest and that is where your negotiation effort delivers the most return per hour spent.
- Run the spend analysis quarterly, not annually. Supplier pricing drift is subtle — a 3% quarter-on-quarter increase goes unnoticed but compounds to 12% by year-end. Automated SQL refresh means the quarterly run costs a buyer 30 minutes rather than 2 days.
⚡ Key Takeaway
Procurement savings are not found in negotiation rooms — they are found in data. Companies that build even a basic spend visibility tool consistently find 7–12% of addressable savings sitting in plain sight in their own PO history. The constraint is never the negotiating skill; it is always the lack of data to support the conversation.