TRACKS 1,200+ POs IN REAL TIME PROCUREMENT SQL POWER BI

Purchase Order Analytics Hub

SQL extraction + Power BI model turning raw ERP PO data into a unified hub showing spend analytics, PO cycle times, approval bottlenecks, supplier concentration, invoice variance, and a real-time exceptions register for overdue, over-budget, and unapproved orders.

Project Overview

⚑ Problem

PO Data Trapped in ERP

Purchase order data exists in the ERP but surfaces only as raw transaction exports — 40-column flat files that require hours of pivot-table work to generate a spend report. No visibility into cycle times, approval bottlenecks, supplier concentration risk, or POs past due date until Finance raises a query at month-end.

⚙ Solution

SQL + Power BI Analytics Hub

A scheduled SQL query extracts, joins, and aggregates PO data into a star schema (PO fact + supplier/category/buyer dimensions). Power BI layers on top with a spend treemap, cycle time analysis, approval bottleneck waterfall, invoice variance flags, and a live exceptions register refreshed daily before the 8am procurement stand-up.

✓ Findings

€340K Invoice Variance Detected

62 POs flagged with anomalies across 1,240 tracked. €340K in invoice-to-PO variance identified — 68% attributable to a single supplier category (Raw Materials). Average PO cycle time 14.2 days vs a 10-day target; approval bottleneck concentrated in two buyers. 3-way match automation reduced invoice exceptions by 41%.

Live Exceptions Register

Spend Treemap

PO Spend by Category — Proportional View (€K)

Dataset Explorer

Spend & Cycle Time Analysis

PO Spend by Category (€K) — Actuals vs Budget

PO Cycle Time by Buyer (Days)

Invoice Variance — PO Value vs Invoice Value (€K)

PO Status Distribution

Monthly PO Volume & Spend Trend

Supplier Concentration — Top 10 by Spend (€K)

PO Register

PO ID	SUPPLIER	CATEGORY	BUYER	PO DATE	REQ DATE	RCPT DATE	PO VALUE (€)	INV VALUE (€)	VARIANCE (€)	VAR %	STATUS	APPR DAYS	CYCLE DAYS	EXCEPTION

6-Month Spend Forecast

Monthly PO Spend vs Procurement Budget — 6-Month Forward View

Company Advice

💡 Recommendations for Procurement Operations Teams

3-way match automation (PO → Goods Receipt → Invoice) reduces invoice processing cost by 60–80% and virtually eliminates payment disputes. Without it, the AP team manually reconciles mismatches that a simple SQL join would catch automatically.
The PO cycle time chart will show you where approvals bottleneck. Every day in approval is a day of supplier lead time consumed — a buyer with a 6-day average approval time is effectively making the supply chain 6 days shorter for their category.
Supplier concentration risk is invisible until it isn't. If your top-3 suppliers account for more than 50% of category spend, you have leverage concentration but also single-source fragility. Model a dual-source scenario before an event forces you to.
Invoice variance above ±3% at PO level is a red flag for either specification drift (the goods delivered don't match the PO), pricing errors, or fraud. Flag these for mandatory review at any variance above €1,000.
POs raised after delivery (retrospective POs) are the clearest indicator of a maverick spend problem. The analytics hub makes them visible; the fix is contract compliance training and a PO-first purchasing policy enforced in the ERP.
Run a monthly PO ageing report: any open PO older than 90 days with no receipt should be reviewed for cancellation or re-negotiation. Aged open POs inflate committed spend figures and distort budget visibility for Finance.

Key Takeaway: The PO is the first control point in the procure-to-pay cycle. Every downstream problem — wrong invoice, missed delivery, budget overrun — is traceable to a failure at PO creation or approval. Getting the data right at source, and surfacing it daily, is the foundation of procurement governance.