Four steps APS agencies can follow to improve data practices

By Shannon Jenkins

Friday July 3, 2020

Parliament House, Canberra, Members Hall. Image: design-net.biz

The Office of the National Data Commissioner has developed a set of principles to help Australian Public Service agencies effectively manage data.

In a report launched on Thursday, the ONDC set out the Foundational Four — simple first steps that seek to improve data capability and shift culture across the APS.

Culture is an “outcome of organisational settings, behaviours and activities”, the report notes. It says that a number of policy statements and reports recognise that the APS must shift its culture and build data capability, including the Productivity Commission’s inquiry into data availability and use and the government’s response to the Thodey review.

Last month, APS commissioner Peter Woolcott also signalled a push towards making that change to better utilise data, with the appointment of Australian Bureau of Statistics head David Gruen to lead the APS’ data profession.

The report notes that while APS-level staff should contribute to the shift, “champions for change are needed at the Senior Executive Level together with leadership from more experienced APS agencies”.


Read more: Commissioner reveals next professional stream as APS looks to increased use of data


The Foundational Four complement existing advice and experience from across the APS, draw on international best practice approaches, and can be further built on by future initiatives.

The principles are leadership, strategy, governance, and asset discovery.

Leadership — The senior data leader will:

  • Lead, and be accountable for, the development and implementation of the agency Data Strategy,
  • Set the standards and approach to data management,
  • Improve data governance,
  • Oversee and coordinate data functions such as data literacy, data quality, data architecture, business intelligence, data security and data protection,
  • Drive data culture change,
  • Build positive relationships with other agency leaders,
  • Support and promote staff who work with and manage data.

Strategy — An agency should have a clear vision and plan for using data to achieve objectives. Key elements of a data strategy include:

  • Vision statement,
  • Alignment with government data policy,
  • Alignment with internal policies and strategies,
  • Strategic objectives,
  • Initiatives/areas of focus,
  • Measurable outcomes/indicators of success,
  • A roadmap.

Governance — Mechanisms exist to oversee data management. There are several key elements to a successful data governance program:

  • Appropriate style of governance,
  • Senior executive support,
  • Staff buy in,
  • Scope of governance program,
  • Defined roles and responsibilities,
  • Relevant policies and procedures,
  • Clear implementation and review plan, including a data governance framework.

Asset Discovery — Data assets should be identified and recorded. Ensuring data is discoverable has many benefits. It can:

  • Prevent data duplication and reduce costs,
  • Promote reuse of data for improved outcomes and a reduced unit cost of managing data,
  • Ensure that constraints on data use are known,
  • Manage the risk of loss of corporate knowledge,
  • Make managing data quality easier.

The document says agencies who have some or all of the points in place should reflect on their effectiveness and consider whether there are opportunities for further improvement.

“If you don’t have all of the elements in place, then action is needed,” it states.

Once the four steps have become operational, agencies should ask several key questions when thinking about what to do next:

  1. Is the agency driven by policy, service delivery or research outputs? What would help deliver these functions in a more joined up way?
  2. What outcomes is the agency trying to achieve and what role does data have in supporting those outcomes?
  3. How can data be used to help build trust in the services and policy the agency delivers?

Agencies with a policy focus could increase capabilities to use data to better answer complex policy questions through advanced analytics or data integration, the report says. To do this, they should assess and improve the quality of data assets, and invest in staff data and analytics capabilities.

On the other hand, agencies with a service delivery focus could increase capabilities to use data as an input into business intelligence to improve service delivery. They should standardise data collection methods, improve data quality at the source of information capture, and improve interoperability of data to ensure data can be exchanged easily and securely between service delivery agencies.

There are also some core areas which every agency could consider. They should:

  • Create a framework that describes how to value data assets. This can help “define how you trade-off the effort of managing data against the benefit derived from the use and reuse of data”, and “identify business critical data which can then help inform security and business continuity requirements”.
  • Invest in further data awareness and education to ensure all staff see the value of data in their agency, and know how to best use it in their daily work. Understanding the value of other agencies’ data is also important.
  • Work towards increasing transparency of data holdings through releasing more data as open (where appropriate), or publishing details of the data assets so that other parties can seek access to data holdings. Agencies must adopt metadata standards, remediate existing metadata, and integrate metadata management into data management practices in order to do this.
  • Reach out to peers to gain insights into what others are doing, which current initiatives may be leveraged, or where agencies could collaborate to make cross-agency improvements. The report notes that working together in a whole of APS way will “continue to drive a shift in data culture, modernise the public service and enable the benefits of improving data practices to be realised”.

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