DPUP — data analysis, research and evaluation cycle
There are some high-level, general steps that a piece of analysis, research or evaluation will typically go through. These are outlined below with some ideas about how the DPUP Principles might or could apply. The Principles are: He Tāngata, Manaakitanga, Mana Whakahaere, Kaitiakitanga and Mahitahitanga.
DPUP summary — for data analysis, research and evaluation
Keep in mind that people often think of information they have supplied, or that is about them, as personal, even when it has been de-identified or anonymised and is being used in a non-personal form.
Whenever your work is about people, then being clear about purpose, supporting transparency and choice, enabling people to access their information and sharing the value of the insights developed using people’s information, are key parts of good practice.
Steps for using the DPUP Principles
Some practical ways you can put the Principles into practice at each step of the life cycle are outlined below.
Step 1: Identify
The question to answer or topic, problem or issue to learn about.
- Keep focused on the He Tāngata Principle. Be clear about how answering this question or learning about this issue will help service users, their whānau, people in similar situations to them or their community to better serve New Zealanders.
- Uphold the Mahitahitanga Principle and work with others, including service users, to understand the issue or problem and why it’s important to answer it and how doing so can help them.
Step 2: Plan
What data or information is needed and how will it be used?
- Mahitahitanga Principle — decide with others what data or information is needed and how to use it. This could be organisations who provide data, community representatives, frontline workers or cultural experts.
- Uphold mana — include service users or service user groups in designing the approach and deciding what is fair and respectful for this purpose.
- As a kaitiaki, check the proposed use of people’s information is ethical and legal. Get advice from a privacy officer, an ethics board, your managers and others.
- Support Kaupapa Māori, ‘for Pacific peoples by Pacific peoples’, or the ownership of analysis and research by those who it is about. Recognise the importance of ‘nothing about us without us’ — Manaakitanga Principle.
- Design the approach to allow people as much choice as possible about the use of their data and information even if it does not identify them. This is the Mana Whakahaere Principle.
Step 3: Find, collect or create
Sourcing the data or information.
- Support the Mana Whakahaere Principle — provide explanations for service users about how their data or information will be used, who by, why and what choices they have about it.
- There are some situations where it might not be safe or appropriate to tell people or give them choices. Consider how you will uphold the Manaakitanga Principle and what negative impact it could have on people’s trust. Think carefully if the purpose truly justifies not being transparent.
- ‘Just in case’ is not an okay reason to collect data or information and ‘we have it so let’s use it’ is not a fair and reasonable approach to being clear about purpose and good practice for transparency.
- Think about your role as a kaitiaki and the importance of building and maintaining people’s trust.
- As a kaitiaki think minimum necessary, not maximum possible when collecting data or information. Do not collect identifiable information if it’s not needed.
Step 4: Analyse
Make sense of data or information: check accuracy, limitations.
- Keep any data or information safe and secure. It’s part of the role of a kaitiaki.
- As well as offering people choices and respecting the choices they make, Mana Whakahaere is also about upholding people’s right to access data or information that identifies them and ask for corrections to it. Make sure information is stored in a way that makes this easy.
- Collaborate and work together — Mahitahitanga — with others (different professionals, organisations, cultural advisors, community representatives) and service users to understand and make sense of data or information.
- Test your assumptions and interpretations with them, include them in analysis and ask for them to review your work. Appreciate the knowledge and skills that others can bring.
Step 5: Conclude
What is the answer, findings or results? What recommendations should come from this?
- Consider how the learnings can be applied to other organisations or situations — He Tāngata.
- Collaborate with and involve others — Mahitahitanga — in developing recommendations so they are set in a sound understanding of reality, the social sector context, and the experiences of service users.
- Keep focused on He Tāngata — what does this conclusion or learning tell us about how best to support service users, their whānau, people in similar situations to them or their community?
Step 6: Share
- Mahitahitanga — grow collective knowledge by safely and appropriately sharing what's been learned.
- Explain and present findings in different ways to engage different people.
- Share appropriate data or data sets with others so they can use them to develop more insights. As a kaitiaki, do this in a safe and respectful way.
- Design information about what has been learned in a way that is engaging for service users and find ways to let them know about it. This is a way to support Manaakitanga and show how sharing their data and information can help them or people in similar circumstances.
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