Purchase Orders Over €20,000 Q3 2020

Spending records

Payment date^*	Supplier	Description	Kind	Amount
30 Sep 2020	DEPT. OF CULTURE, HERITAGE & THE GAELTACHT	Energy Costs	Purchase Order	€39,725.00
30 Sep 2020	ESB INDEPENDENT ENERGY T/A ELECTRIC IREL	Electricity Charges	Purchase Order	€45,400.00
30 Sep 2020	MATER HOSPITAL	Secondment Fees	Purchase Order	€34,000.00
30 Sep 2020	CORK UNIVERSITY MATERNITY HOSPITAL	Secondment Fees	Purchase Order	€31,180.00
30 Sep 2020	HAYS SPECIALIST RECRUITMENT(IRELAND) LTD	Agency Staff Fees	Purchase Order	€23,829.04
30 Sep 2020	MHR INTERNATIONAL CELTIC LIMITED	Payroll Services	Purchase Order	€63,525.00
30 Sep 2020	MATER HOSPITAL	Secondment Fees	Purchase Order	€117,000.00
30 Sep 2020	AUXILION IRELAND LTD	Consultancy	Purchase Order	€21,175.00
30 Sep 2020	EIR MOBILE PHONE SERVICE A/C 89835013	Mobile Phone Charges	Purchase Order	€96,800.00
30 Sep 2020	SCHOOL OF NURSING & MIDWIFERY(UCC)	PhD and Stipend Fees	Purchase Order	€23,770.00
30 Sep 2020	CORK UNIVERSITY MATERNITY HOSPITAL	Secondment Fees	Purchase Order	€108,000.00
30 Sep 2020	OFFICE OF PUBLIC WORKS	Rent & Service Charges	Purchase Order	€142,289.55
30 Sep 2020	CODEC LTD T/A DECISION SYSTEMS (PSWT)	ICT Consultancy	Purchase Order	€20,146.50
30 Sep 2020	CLARION CONSULTING LTD	ICT Consultancy	Purchase Order	€27,830.00

^* 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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