What works, for whom, at what cost? The power of administrative data

23
Jun 17
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Policy makers and service designers are always striving to find out ‘what works’, but traditionally this has been a time-consuming and expensive process.  We’ve also been limited to using small, specifically collected data sets to produce aggregated results, which can’t easily be used to improve services.

The upshot is we’ve been using data to represent an ’average’ person in a world where our communities are diverse: every person has their own unique circumstances and needs. How can ‘what works’ for this imaginary average person be expected to work for a real human being?

Applying a social investment lens

In New Zealand, by applying a social investment lens, we’ve been learning how to use matched, de-identified administrative data collected by a range of government agencies. These data are integrated by Statistics New Zealand through their Integrated Data Infrastructure (IDI) and can be used to better understand the relationship between resourcing and effectiveness: what works, for whom, at what cost. 

Data are provided by Inland Revenue, the Ministries of Social Development, Health, Education, and Justice, the Department of Corrections, and the Accident Compensation Corporation, along with a host of other sources.

The Social Investment Unit has recently made these integrated data collections easier to use by developing a range of tools including:

  • Social Investment Measurement Map (SIMM) – a scoping tool providing information on what type of measures are available before authorised IDI users access the data.
  • Social Investment and Analytic Layer (SIAL) – events-structured tables, arranging a version of data in the IDI into a consistent format, making it easier and faster to use and understand. The data are reusable, and can save analysts months of work.
  • A Data Exchange – making it easier and safer to move data around the system. This will be a system-wide, two-way Data Exchange (beyond the IDI), that allows both anonymised and non-anonymised data to be shared between organisations.

For more analytic tools, and further information see: https://siu.govt.nz/tools-and-guides/ and http://www.stats.govt.nz/browse_for_stats/snapshots-of-nz/integrated-data-infrastructure.aspx

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Submitted by Emily Mason

Emily Mason

Emily Mason is passionate about helping those in the social sector better answer the question “what works for whom, at what cost” by bridging the gap between data science and government (policy) decision-making. This focus is the result of almost 20 years’ experience in policy and analytics teams working to turn data into information useful for decision-making. Emily has worked in strategic and operational roles across New Zealand’s central government and enjoys providing advice and presenting on using data science to build a fairer and more evidence based state sector. Emily is currently Lead – Analytical Products, at the Social Investment Unit, New Zealand. Previous roles include work with the Ministry of Education, the Accident Compensation Corporation (ACC), and Statistics New Zealand. Emily has a Master’s in Public Policy (MPP) from Victoria University of Wellington and was awarded the Prime Minister’s Public Policy Prize (VUW) in 2004. Emily can be contacted at emily@noos.nz, or https://www.linkedin.com/in/emilymasondatainpolicy.

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