Purchase Orders Over €20,000 Q1 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Mar 2023	Davy Property Holdings	Property rental charges.	Purchase Order	€25,000.00
31 Mar 2023	Attentius T/A Osborne	Job application shortlisting services & agency staff placement.	Purchase Order	€25,309.88
31 Mar 2023	Energia Switched On	Electricity provider.	Purchase Order	€39,646.69
31 Mar 2023	Datapac Ltd	Managed Print supplier, ICT Hardware supplier and related supplies.	Purchase Order	€43,725.69
31 Mar 2023	Micromail	Software quotation, purchasing and licensing management services.	Purchase Order	€47,143.84
31 Mar 2023	Mayan Construction Ltd	Property rental charges.	Purchase Order	€58,550.64
31 Mar 2023	Benchmark Hainault Property	Property rental charges.	Purchase Order	€58,809.38
31 Mar 2023	Georges Quay Management	Property service charges.	Purchase Order	€90,866.58
31 Mar 2023	Unity	ICT managed helpdesk.	Purchase Order	€92,197.11
31 Mar 2023	Vodafone	Network and Telephony Services.	Purchase Order	€150,829.84
31 Mar 2023	Henderson Park	Property rental charges.	Purchase Order	€184,868.64
31 Mar 2023	Eir Evo Hibernia Services Ltd	Managed Infrastructure Services running core ICT systems.	Purchase Order	€255,483.32

^* 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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