Purchase Orders Over €20,000 Q4 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2023	Lowry Construction Limited	Building Refurbishment	Purchase Order	€43,194.48
31 Dec 2023	Lowry Construction Limited	Building Refurbishment	Purchase Order	€150,957.16
31 Dec 2023	High Precision Motor Products Ltd.	Plant Maintenance/Repairs	Purchase Order	€105,780.00
31 Dec 2023	The Design Concept	Erection of Shelving	Purchase Order	€24,285.00
31 Dec 2023	H J Lyons ( Architects) Limited	Architectural Services	Purchase Order	€66,579.25
31 Dec 2023	N.C. Plant Hire Ltd	Housing Works	Purchase Order	€26,950.00
31 Dec 2023	Fingleton White & Co. Ltd.	Biomethane Strategy	Purchase Order	€22,126.47
31 Dec 2023	N.C. Plant Hire Ltd	Housing Works	Purchase Order	€45,450.00
31 Dec 2023	N.C. Plant Hire Ltd	Landscaping Works	Purchase Order	€41,070.00
31 Dec 2023	Emergency One (UK) Ltd.	Plant Maintenance/Repairs	Purchase Order	€64,400.00
31 Dec 2023	Felix O'Hare & Co. Ltd.	Building Construction	Purchase Order	€955,026.40
31 Dec 2023	Felix O'Hare & Co. Ltd.	Building Construction	Purchase Order	€834,331.36
31 Dec 2023	Felix O'Hare & Co. Ltd.	Building Construction	Purchase Order	€1,017,206.47
31 Dec 2023	Felix O'Hare & Co. Ltd.	Building Construction	Purchase Order	€746,361.41
31 Dec 2023	Circle K Ireland Energy Ltd.	Fuel	Purchase Order	€61,969.66

^* 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