Payments Over €20,000 Q2 2020

Spending records

Payment date^*	Supplier	Kind	Amount
10 Jun 2020	Comptroller & Auditor General Professional Services	Purchase Order	€20,100.00
12 Mar 2020	GL Industrial Services UK Ltd Professional Services	Purchase Order	€28,202.42
12 Mar 2020	Willis Towers Watson (Ireland) Professional Services	Purchase Order	€29,367.00
06 Mar 2020	DNV GL Limited Professional Services	Purchase Order	€20,636.40
06 Mar 2020	Drury \| Porter Novelli Professional Services	Purchase Order	€26,764.17
27 Feb 2020	South Dublin County Council Rates	Purchase Order	€32,333.40
20 Feb 2020	Datapac IT Equipment	Purchase Order	€29,527.38
14 Feb 2020	Gutteridge Haskins & Davey Ltd Professional Services	Purchase Order	€251,178.50
07 Feb 2020	MJ Flood (Irl) Ltd IT Licence Fees	Purchase Order	€22,115.51
07 Feb 2020	GH Investments Ltd Rent and Managed Services	Purchase Order	€102,983.25
24 Jan 2020	Drury \| Porter Novelli Professional Services	Purchase Order	€101,263.53
10 Jan 2020	RSM Ireland Business Advisory Recruitment Services	Purchase Order	€22,679.43
10 Jan 2020	DNV GL Limited Professional Services	Purchase Order	€27,581.36
10 Jan 2020	Benchmark Property Rent and Managed Services	Purchase Order	€33,733.15

^* 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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