Purchase Orders Over €20,000 Q3 2022

Spending records

Payment date^*	Supplier	Description	Kind	Amount
30 Sep 2022	VERSION 1 Payments are inclusive of VAT where appropriate. 1.	Contractor	Purchase Order	€22,711.50
30 Sep 2022	VERSION 1	Contractor	Purchase Order	€22,711.50
30 Sep 2022	VERSION 1	Contractor	Purchase Order	€23,793.00
30 Sep 2022	DATAPAC	IT Hardware	Purchase Order	€62,788.80
30 Sep 2022	INSPIRED SPACES BUNDLE 5 IRELAND LTD	Building Projects	Purchase Order	€130,801.60
30 Sep 2022	DUN LAOGHAIRE AND RATHDOWN COUNTY COUNCIL	Building Projects	Purchase Order	€180,221.90
30 Sep 2022	NATIONAL TREASURY MANAGEMENT AGENCY	Building Projects	Purchase Order	€197,765.58
30 Sep 2022	ENTERPRISE IRELAND	Payment for the promotion and marketing of Ireland’s higher education system and higher education institutions (HEIs) in priority and high potential markets on behalf of DFHERIS	Purchase Order	€650,000.00
30 Sep 2022	FOCUS EDUCATION (NMC) LIMITED	Third Level Building and Infrastructure	Purchase Order	€1,697,895.69
30 Sep 2022	CSM PPP SERVICES LTD	Third Level Building and Infrastructure	Purchase Order	€2,123,076.94
30 Sep 2022	ERIUGENA DESIGNATED ACTIVITY COMPANY	Building Projects	Purchase Order	€5,281,876.18
30 Sep 2022	HIGHER EDUCATION AUTHORITY	Third Level Building and Infrastructure	Purchase Order	€52,952,156.52

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

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