Use the Development Pathways Tool

The Development Pathways Tool can help you identify how to develop your skills (or your team’s skills) to the next level of policy practice.

Get started by selecting the skill you wish to develop and by selecting the development level you want to achieve.

The Development Pathways Tool takes each element of knowledge, applied skills and behaviours required to become a policy professional (as described in the Policy Skills Framework)

We found 3 result(s). Results are available in HTML and as individual PDF versions below.

Evidence and Insights

Level:

Developing

Developing
Draws on a range of evidence and insights to support analysis that informs each stage of the policy process. Aware of the reliability of the evidence.
- Becoming familiar with how to use evidence throughout the policy cycle.
- Growing an understanding of the different kinds of qualitative and quantitative evidence, evidence sources, and evaluation types.
- Learning how to summarise and synthesise evidence to draw conclusions (e.g. on key issues, their magnitude, root causes and possible solutions).
- Learning how to incorporate end-user perspectives accurately and empathetically into analysis.
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.
PDF version

Evidence and Insights skill: Developing level – Development Pathways Tool

PDF

333.62 KB
Evidence and Insights

Level:

Practising

Practising
Draws on a range of evidence and insights to support analysis that informs each stage of the policy process. Aware of the reliability of the evidence.
- Can synthesise diverse information and evidence, distil what is important, and use it to tell a coherent story.
- Can competently assess the quality and limitations of evidence, data and research. Understands empirical methodology, principles of data integrity, and the basics of statistical analysis.
- Understands methodologies for drawing insights from the ‘citizen-as-customer’ and the frontline, and how those insights can inform policy.
- Can identify measurable and meaningful indicators of effectiveness, plan (and possibly execute) fit-for-purpose evaluations, and extract lessons learnt to help build an ongoing evidence base.
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.
PDF version

Evidence and Insights skill: Practising level – Development Pathways Tool

PDF

372.73 KB
Evidence and Insights

Level:

Expert / leading

Expert / leading
Draws on a range of evidence and insights to support analysis that informs each stage of the policy process. Aware of the reliability of the evidence.
- Applies expert knowledge to lead others in developing strong evidence-informed policy.
- Develops and guides others on the right lines of enquiry.
- Draws on the right capabilities to mine data and use ‘big data’ for insights that can enable better decisions and create value.
- Can commission and execute monitoring and evaluations, and build findings into policy development, at early and subsequent stages in the policy cycle.
70% on-the-job learning
- Engage with decision makers to illustrate how the research, information and data generated by you and your colleagues can assist in achieving policy goals.
- Consider how regular data flows can provide alerts about emerging patterns and potential issues.
- Understand predictive analytic models and methods for improving insights, and their limitations.
- Use multiple sources of data to get a better picture of situations and issues.
- Have a rich understanding of the characteristics of the people affected by your subject area and advise others on useful ways to demonstrate potential impacts of different decisions.
- Regularly scan relevant research and evaluation findings and interpret them for policy insights.
- Build into your projects opportunities to revisit policy assumptions based on the evidence base.
- Identify with specialists which policy interventions need evaluation, and institute an appropriate methodology.
- Identify data and other evidence gaps for your agency, and lead work on future data needs and building the policy evidence base.
- Share and present your evaluation findings from specific projects and discuss lessons learned.
- Mentor and coach others in how to develop strong evidence-informed policy.
20% learning from others
- Co-design data requirements with specialists and incorporate them in policy projects for analysis.
- Engage with academics to foster research interest in long running policy issues to generate research insights.
- Engage with non-specialists and other agencies to illustrate how the research, information and data you hold will help them achieve their goals.
- Develop a collaborative relationship between policy makers, analysts and data specialists.
- Incorporate data specialists in project teams (either as direct or virtual team members).
- Cultivate a working relationship with any chief science advisors in your organisation to support your policy development and practice.
10% formal learning
- Take an online course on how to work with data strategically (e.g. Strategic Data Skills from the Open Data Institute).
- Consider more advanced courses on statistical analysis and econometrics.
PDF version

Evidence and Insights skill: Leading Level – Development Pathways Tool

PDF

172.77 KB

What policy topics are you interested in?

Evidence and Insights

70% on-the-job learning

20% learning from others

10% formal learning

PDF version

Evidence and Insights

70% on-the-job learning

20% learning from others

10% formal learning

PDF version

Evidence and Insights

70% on-the-job learning

20% learning from others

10% formal learning

PDF version

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