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Building evaluation capital in government: a Queensland departmental approach

Goswami, Sarah and Lane, Vicki (2017) Building evaluation capital in government: a Queensland departmental approach. Evaluation Journal of Australasia, 17 (4). pp. 39-49. ISSN 1035-719X

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Publisher URL: https://www.aes.asn.au/resources/evaluation-journal-of-australasia.html
Organisation URL: https://www.aes.asn.au/images/stories/files/conferences/2017/64SarahGoswami.pdf

Abstract

Increasingly, government departments are being held accountable for investment in public services. In Queensland the Financial Accountability Act 2009 (Queensland Treasury, 2016) requires that accountable officers and statutory bodies ‘achieve reasonable value for money by ensuring the operations of the department or statutory body are carried out efficiently, effectively and economically’ (Section 61).
Whilst there is a directive for agencies to evaluate and demonstrate value for money, it has in practice been difficult to embed long term, as many systems and decision makers have neglected the role of organisation-wide evaluation capital.
This paper will outline the work being undertaken in the Queensland Department of Agriculture and Fisheries (DAF) to implement an Impact and Investment Framework, which will support and embed evaluation in a multidisciplinary setting. A central tenant of this framework is ‘business empowerment and learning’— building the evaluation culture in the organisation by first establishing evaluation building blocks, through business empowerment, support and utility.
The framework is comprised of five key elements and is built on the principles of evaluation and evaluation capacity building disciplines. It has been designed to be low-cost, effective and efficient, whilst enabling business improvement, meeting accountability needs and allowing the Department to demonstrate the value of its work.

Item Type:Article
Business groups:Horticulture and Forestry Science
Subjects:Agriculture > Agriculture (General) > Agricultural economics
Science > Statistics > Statistical data analysis
Deposited On:04 Dec 2017 02:20
Last Modified:04 Dec 2017 02:24

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