Purchase Orders in Excess of €20,000 Q2 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
30 Jun 2023	Office of the Comptroller and Auditor General	Purchase order	Purchase Order	€21,200.00
21 Jun 2023	Pricewaterhouse Coopers	Purchase order	Purchase Order	€38,502.08
15 Jun 2023	Core Full Solutions Ltd	Purchase order	Purchase Order	€33,631.89
07 Jun 2023	KPMG	Purchase order	Purchase Order	€64,959.00
07 Jun 2023	Codec dss Ltd T/A Codec	Purchase order	Purchase Order	€99,630.00
30 May 2023	Version 1 Software	Purchase order	Purchase Order	€22,363.74
30 May 2023	Arkphire Security Limited t/a Presidio	Purchase order	Purchase Order	€46,125.00
30 May 2023	Datapac Ltd	Purchase order	Purchase Order	€49,144.96
26 May 2023	Greenville Procurement Partners Ltd	Purchase order	Purchase Order	€32,118.00
24 May 2023	Deloitte Ireland LLP	Purchase order	Purchase Order	€26,254.84
10 May 2023	Mediavest Ltd T/A Starcom Media	Purchase order	Purchase Order	€81,379.87
28 Apr 2023	Vodafone ECS a/c 072	Purchase order	Purchase Order	€62,729.87
28 Apr 2023	Arkphire Services Ltd t/a Presidio	Purchase order	Purchase Order	€177,284.82
19 Apr 2023	Numac	Purchase order	Purchase Order	€426,250.00
12 Apr 2023	Conscia Limited	Purchase order	Purchase Order	€45,391.92
12 Apr 2023	Crowleys DFK	Purchase order	Purchase Order	€114,059.52

^* 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.

Here is a project that encountered similar issues