Business Analysis · Public Procurement · Data Analytics
EU Digital Procurement Competition Monitor
An audit-ready decision-support system designed to identify competition patterns and supplier concentration across EU digital procurement notices using official TED data.
Independent end-to-end case study · Public data · Documented stakeholder scenarios
60–90 second overview
The case at a glance.
- Business question
- How can public-procurement teams screen digital procurement results for competition patterns while retaining a traceable, reproducible evidence trail?
- Scope and role
- I documented requirements, defined the evidence cohort and KPI rules, and connected the analysis to data checks, UAT and reporting outputs.
- Intended users
- Procurement directors, category managers, supplier-management leads and data-governance reviewers.
- Key result
- A reproducible screen across 38,971 notices, including a 47.7% observed single-bid rate within 27,100 competition-evidence notices.
- Guardrail
- The screen prioritises follow-up questions; it is not evidence of fraud, non-compliance or supplier risk.
An analytical decision
Keep the denominator visible
The single-bid rate uses the 27,100 notices with competition evidence, not all 38,971 notices. Keeping that boundary visible prevents missing evidence from being treated as a competitive outcome. The result is a screening signal for further investigation, not a finding of misconduct.
Review the KPI definition, evidence cohort and validation checks.Analytical chain
Project evidence
Artifacts that make the work reviewable.
The dashboard is a real repository output. The traceability and UAT previews reproduce verified rows from the project documentation.
Executive dashboard
Competition and supplier-concentration decision view
Verified project output generated from official TED result notices.
Why it mattersIt keeps the evidence cohort, coverage and screening limitations visible beside the headline measures.Traceability matrix excerpt
Requirement → implementation → verification
Excerpt from the repository’s Requirements Traceability Matrix.
Why it mattersIt demonstrates that published measures can be traced back to a requirement and a defined verification route.UAT evidence excerpt
Acceptance checks protect interpretation
Representative scenarios from the verified UAT plan.
Why it mattersThe tests cover eligibility, denominator reconciliation, anomaly handling and cross-artifact consistency.Problem & scope
How can public-procurement teams screen digital procurement results for competition patterns while retaining a traceable, reproducible evidence trail? EU-27 contract-result notices for digital procurement, scoped to CPV divisions 48 and 72 and published from 2025-01-01 to 2026-07-30 in the verified build. Official TED Search API result notices scoped to EU-27 digital procurement. A reproducible source manifest preserves the extraction context and public-data provenance.
My contribution & intended users
I documented requirements, defined the evidence cohort and KPI rules, and connected the analysis to data checks, UAT and reporting outputs. Procurement directors, category managers, supplier-management leads and data-governance reviewers.
Requirements & calculation rules
Business requirements define scope, reproducibility, calculation behaviour and the evidence required before a KPI can be displayed. Every reported measure has a defined numerator, denominator, cohort and data-quality condition. Known award value is kept separate from records where currency or value cannot be compared reliably.
Analysis & outputs
Management questions were translated into analytical cohorts, explicit KPI rules and acceptance criteria. Python and SQL pipelines apply controls before data enters the reporting layer. A SQLite analytical model separates notice, buyer, supplier and award perspectives so measures can be reproduced and interrogated without relying on one flattened export. The portfolio analysis observed a 47.7% single-bid screening rate within 27,100 competition-evidence notices and analysed €72.7B in quality-screened known EUR award value.
Validation & traceability
UAT scenarios connect requirements to transformation rules, SQL outputs and published measures, creating a clear route from question to reported result. Coverage checks, currency handling, deduplication rules and explicit exclusions protect the interpretation. A single-bid signal is a screening indicator—not evidence of fraud, corruption or misconduct.
Recommendation & limits
The output helps prioritise follow-up questions about market participation, supplier concentration and data completeness. It does not determine wrongdoing or legal compliance. The analysis depends on the completeness and consistency of published TED fields. It is a portfolio study of public records, not a regulatory investigation or claim of commercial impact. The screen prioritises follow-up questions; it is not evidence of fraud, non-compliance or supplier risk.