The "Good Enough" Trap: Why Functionally Adequate Isn't Impactful

What Leaders Really Need (Hint: It's Not Just More Data)

1. Actionable Insight, Not Just Raw Data: Leaders aren't short on data; they're often drowning in it. They need the 'So what?'. Simply delivering data doesn't guarantee its use; it needs to be embedded in decision-making processes and clearly answer strategic questions. Think of it as the difference between handing someone timber (data) versus blueprints and instructions (insight) for the bookshelf they need.

2. A Compelling Narrative, Not Just Charts: Those articles you see about 'data storytelling'? They're onto something crucial. Numbers alone rarely inspire action or secure buy-in. You need context, a narrative that connects the dots and explains why it matters. Research confirms that stories make data more memorable and persuasive, helping to bridge the gap between analysis and action. It's translating complex data language (like kinetic chain reactions in gait analysis) into a human story that resonates. Just showing a dashboard isn't storytelling; that's like pointing at a dictionary and calling it a novel.
How to communicate insights with data storytelling
Data storytelling can be used to put data insights into the context and inspire action from the audience. 

https://www.sharpcloud.com/blog/how-to-communicate-insights-with-data-storytelling

3. Answers to the Next Question: The best data products anticipate follow-up questions. This requires stepping outside our technical bubble and genuinely understanding the leader’s strategic landscape, their pressures, the policy context (climate change, healthcare, education – each with its own lingo and goals). It’s like figuring out why your teenager is obsessed with a particular band – there’s usually a deeper layer.

4. Robustness Under Pressure: Does the analysis hold up if conditions shift? Have we considered biases, ethical implications, or the 'technical debt' in our choices? Leaders need to trust the insights aren't fragile. Public sector work demands rigorous attention to data privacy and ethics; it's not just a checkbox but a core responsibility when handling citizens' information. We must also ensure our work aligns with Te Tiriti o Waitangi principles, respecting Māori data sovereignty – a non-negotiable aspect of integrity in Aotearoa. It’s like building a deck – it needs to withstand a classic Wellington southerly, not just sunshine.
Te Mana Raraunga
Our Data, Our Sovereignty, Our Future

https://www.temanararaunga.maori.nz/

Dr Huang's Approach: A Public Sector Data Workshop Mindset

1. Embrace the Mission & Debug the Request: Remember why you're here. Public sector data is a public asset, meant to serve citizens. Treat the initial request like buggy code. What are the hidden assumptions? What policy goals are driving this? Talk to stakeholders – it’s ethnographic fieldwork to understand their world before designing the tool. Align your analysis with agency goals, not just flashy metrics.

2. Build Data Literacy Bridges: Most colleagues aren't data fluent. Even your boss might struggle to interpret the data, let alone know what questions to ask. Frequently, the request you get is just: “I need the data on XXX, can you pull that for me?” Your job is translating complexity. Host 'data 101' workshops (less lecture, more play), sit in on policy meetings to listen, and use analogies. Explaining predictive modeling like planning a rugby play often clicks better than discussing algorithms. Increasing data literacy across government is fundamental for smarter decision-making.

3. Prototype the Insight & Pilot Small (MVP Thinking): Forget the 'big reveal'. Share early findings, mock-ups, napkin sketches. Government isn't a startup, but agility matters. Start with small, outcome-focused pilots – like testing a tiny feature before scaling. Nail a quick win (e.g., cutting service wait times), show measurable impact, and broadcast that success to build buy-in. Use rapid prototyping with basic models on small datasets, then iterate. And remember, as discussed, your colleagues and leaders often don't even realise the potential of data. Putting something in front of them, even an imperfect prototype, is usually necessary to give them a concrete starting point. That's when they can grasp it, raise questions, and meaningful follow-up discussions can actually start.

4. Master the Craft (Pragmatic Tools & Essential Skills):
• Tech Stack (Kiwi DIY Style): Embrace cost efficiency. Open source (Python, R) and accessible BI tools (Tableau, Power BI) are your mates. Focus on the tools that solve the problem effectively, like ensuring you can build that bookshelf rather than buying the fanciest drill. Seriously though, don't underestimate Excel. Why? Because it could very well be the only data tool your colleagues or boss are comfortable with. You can build the most sophisticated reports, but at the end of the day, you might still need to dump it into Excel just so they can approve or sign off on it.
• Data Wrangling is King: Get your hands dirty cleaning and preparing data. GIGO (Garbage In, Garbage Out) is real. Know the data inside out – like fixing a wonky fence, it takes effort but yields solid results.
• Visualization as Storytelling: Craft dashboards and reports that tell a compelling story, making insights accessible.
• Skills Beyond Code: Sharpen critical thinking (question data, scrutinize sources, identify bias), problem-solving (be a data detective), and communication (simplify, tailor your message, back it up). These are vital, just like figuring out if your teen really did their homework.

5. Navigate the System & Yourself: Government has its complexities – silos, red tape, risk aversion. Navigate with empathy. Understand stakeholder fears and frame solutions as low-risk, high-reward. Be patient; culture shifts take time, like sanding rough wood. And optimize your personal OS. Set boundaries, reflect weekly ("What worked? What's my technical debt?"), lean on your network of fellow data nerds, and commit to lifelong learning. Avoid burnout; this work carries weight.
The Government Data Strategy and Roadmap - data.govt.nz
The data strategy and roadmap provides a shared direction and plan for New Zealand's data system (the people and organisations that collect and use data in New Zealand).

https://data.govt.nz/leadership/strategy-and-roadmap
OECD Good Practice Principles for Data Ethics in the Public Sector
The Good Practice Principles for Data Ethics in the Public Sector presented in this paper seek to shed light on the value and practical implications of data ethics in the public sector. They aim to support public officials in the implementation of data ethics in digital government projects, products, and services such that i) trust is placed at the core of their design and delivery and ii) public integrity is upheld through specific actions taken by governments, public organisations and, at a more granular level, public officials.

https://www.oecd.org/en/publications/oecd-good-practice-principles-for-data-ethics-in-the-public-sector_caa35b76-en.html

Final Thought: Data as a Craft for the Public Good