Evidence and Insights (Developing)

70% on-the-job learning

• Learn about the strengths and limitations of key data and statistical collections available in your agency and externally (e.g. from Statistics New Zealand, the Treasury, Ministry of Social Development).
• Research how to source quantitative and qualitative data information from these sources for policy development.
• Read the Policy Project’s conversation tracker on the Superu (Social Policy Evaluation and Research Unit) Making Sense of Evidence – A Good Practice Guide.
• Read Making sense of evidence: A guide to using evidence in policy (Superu 2018).
• Review briefing papers that have a strong evidence base.
• Learn about the strengths and weaknesses of the different quantitative and qualitative methodological tools available by reading relevant textbooks, and speaking with colleagues who are knowledgeable on Māori perspectives on data and data use.
• Use problem trees to identify the relationships between adverse outcomes and the root causes of policy issues.
• Do a literature review of a policy issue, drawing on articles that use qualitative and quantitative information.
• Practise using, summarising and communicating key themes from research, information and data results.
• Familiarise yourself with the content and resources provided on the Policy Project’s Evidence and evaluation page.
• Learn how to commission simple and medium-complexity data extraction and collection internally and externally.
• Work with a senior colleague on a policy project where you need to identify the characteristics of the people the policy will serve and design a method to seek their views.
• Learn about what data is available through the Integrated Data Infrastructure and how it can be accessed.
• Apply different approaches to understand the personal stories and lived experience of the policy’s end user. Read the material in the Policy Project’s Policy Methods Toolbox on design thinking, behavioural insights, and futures thinking.
• Review information and advice on privacy, security and risk (see Your privacy responsibilities and Privacy security and risk).
• Review information and advice on data (see Data toolkit).
• Understand which data and digital standards may apply to your work (see Government Digital Standards Catalogue).
• If your agency has chief science advisor, familiarise yourself with what they do and how their role fits into your agency’s policy process.

20% learning from others

• Learn about your internal data analysis team (if you have one) and find out more about what they do.
• Learn about your behavioural insights team (if you have one) and find out more about what they do.
• Learn about your futures thinking team (if you have one) and find out more about what they do.
• Review high quality research work conducted by others to get insights on how to approach research tasks.
• Identify and meet with data, research and evaluation specialists in your areas to understand what data and information they collect, and what it can and cannot tell you.
• Consult with senior colleagues to assess various sources of evidence for relevance.
• Ask colleagues with relevant skills about statistical concepts (e.g. margins of error and confidence intervals).

10% formal learning

• Take an introduction to statistics course.
• Take an online course to build your understanding of statistical methods.
• Complete training in the use of Microsoft Excel and Power BI.