Evidence and Insights (Practising)

70% on-the-job learning

• Develop a strategic relationship with your agency’s data team, so they are familiar with your requirements.
• Identify and communicate themes from data analysis results along with methodology strengths and limitations.
• Participate in policy projects that have a significant information and evidence base.
• Apply the design thinking, behavioural insights, and futures thinking guidance in the Policy Project’s Policy Methods Toolbox to one of your projects. 
• Have a rich quantitative and qualitative understanding of the people who are impacted by your subject area and how they are impacted.
• Use with confidence and interpret data and evidence regularly in your policy work to tell a coherent story, enrich analysis and enable well-informed decisions.
• Demonstrate awareness of how data and evidence can reflect and reinforce stereotypes and institutional bias, and how this can be mitigated.
• Build into your projects opportunities to revisit policy assumptions based on the evidence base.
• Use a variety of methods to bring data and information to life for non-specialists.
• Commission complex data extraction and collection internally and externally.
• Ensure that policy projects allow sufficient time for data collection and analysis.
• Critically evaluate the accuracy, completeness, consistency, uniqueness and timeliness of data you use as evidence.
• Establish strong relationships with agencies that have a key role in data and research collection and remain up to date with new developments.
• Learn how to design and implement or commission an evaluation or review of a policy initiative.
• Share and present your data analysis and evaluation findings from specific projects and discuss lessons learned.
• Mentor and coach others in developing strong evidence-informed policy.
• Consider available information and thinking on Māori Data Needs, Rights, Sovereignty and Governance (see Ngā Hua | Resources, Co-designing Māori data governance, and Indigenous Data and Governance). 

20% learning from others

• Consult and work with data specialists, survey design specialists, co-design and public participation experts, and evaluation experts to learn about and ensure the appropriateness of the:
  • design and collection of data and research
  • design and use of survey tools for collecting qualitative information (e.g. Survey Monkey)
  • design of evaluation tools to measure the effectiveness of current policy interventions or post policy implementation effectiveness.
• Join relevant communities of practice or networks (e.g. Government Economics Network).
• Develop relationships with Māori academics and others who have an interest in data in your subject area.
• Discuss with experienced colleagues how to balance apparently conflicting analytical approaches.
• Where appropriate, consult with any chief science advisors in your agency to see how they can advise on use of evidence.

10% formal learning

• Consider more advanced courses on statistical analysis and methodologies for drawing insights from the ‘citizen-as-customer’. 
• Attend conferences such as indigenous data summits (e.g. Ngā Pae o te Maramatanga).
• Undertake a programme evaluation course (e.g. Programme Evaluation – Supporting Evidence-Informed Practice by University of Auckland).
• Complete a privacy micro-credential, such as Privacy in the public sector from Wellington Uni Professional.