Purchase Orders Over €20,000 Q3 2020

Spending records

Payment date^*	Supplier	Description	Kind	Amount
25 Sep 2020	Hays Recruitment	Professional fees	Purchase Order	€25,721.70
25 Sep 2020	Nicholas O'Dwyer Ltd	Professional fees	Purchase Order	€32,257.98
25 Sep 2020	Kennedy Security	Services	Purchase Order	€72,545.40
18 Sep 2020	DBFL	Professional fees	Purchase Order	€26,494.20
18 Sep 2020	OCSC	Professional fees	Purchase Order	€35,631.56
25 Aug 2020	Grafton Architects	Professional fees	Purchase Order	€36,334.20
25 Aug 2020	Irish Water	Services	Purchase Order	€61,848.05
25 Aug 2020	Hays Recruitment	Professional fees	Purchase Order	€79,950.00
14 Aug 2020	IAC ‐ Irish Arhcaeological	Professional fees	Purchase Order	€85,387.41
14 Aug 2020	O'Donnell Tuomey	Professional fees	Purchase Order	€89,175.00
13 Aug 2020	RPS Group	Professional fees	Purchase Order	€82,914.30
11 Aug 2020	Hays	Professional fees	Purchase Order	€23,511.38
11 Aug 2020	Dunwoody & Dobson	Professional fees	Purchase Order	€42,923.58
11 Aug 2020	O'Donnell Tuomey	Professional fees	Purchase Order	€187,421.25
23 Jul 2020	Taylor McCarney Architects	Professional fees	Purchase Order	€76,598.87
14 Jul 2020	TU Dublin	Professional fees	Purchase Order	€25,311.09
09 Jul 2020	Nicholas O'Dwyer	Professional fees	Purchase Order	€56,019.12
01 Jul 2020	Ernst & Young	Professional fees	Purchase Order	€82,129.56

^* 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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