Data governance and maturity in New Zealand's government: progressing but significant challenges remain

A recent conference in New Zealand had data governance and maturity as some of its foci, showing that the conversation has moved from a few of us ‘data nerds’ going on about it while everyone else falls asleep, to managers and leaders recognizing these are both key and an issue.

Last week, I travelled north across New Zealand’s South Island and the Cook Strait to its capital Wellington, to attend the 5th Annual NZ Government Data Summit as part of a panel on addressing the opportunities and ethical responsibilities of data sharing and open government data. Just as importantly, I was there to hear about the state of affairs in NZ government data governance and related topics.

The progress is heartening, but not fast or far enough at the moment to ensure that organizations will be able to face, let alone solve, the challenges communities face.

Over the course of the two days, I did not hear much that was new. I did, however, confirm what I have previously seen – that data maturity and governance continue to be major challenges in both local and central government. On the subject of challenges, some messages came up repeatedly about the main issues. People know they are a problem, but there’s still a lot of flailing about trying to figure out what to do about them. Here are a few that I heard.

Silos are everywhere, and there’s a major lack of coordination and connection within and between organizations.
For the most part, there is a severe lack of mature data governance.
Data maturity is, unsurprisingly given the above, often very low too. For example, many organizations still either completely lack, or are only now building, data catalogues.
Data access is a problem as well. People, including and perhaps especially internal staff, often do not understand well or at all what data organizations have, where they have it, what its quality is, and what people do with it.
Data is still treated as a tool, and a basic one at that, rather than as an important (and complex!) lever for generating insight and, ideally, common good.¹
There are far too many systems and stacks. I heard stories where there were more systems and stacks than employees in mid-size local government organizations, for example. This makes it near-impossible to connect or maintain all these systems and difficult to build organizational knowledge around them. It is a huge waste of resources (time, money, effort, etc.).

There seem to be three primary approaches people are taking towards data maturity and governance, and none work especially well.

Doing nothing (which is actually going backwards).
Stop-start or intermittent action. In some cases, initiatives start but then fall over with nothing learned, and no more action until a change of the guard.
Wheel reinvention. Organizations spend a lot of time and resources on coming up with new initiatives from scratch, rather than using, learning, and building from existing work.

In some cases, all three of the above interact. Wheel reinvention can lead directly to initiatives stop-starting or falling over (and nothing getting done afterwards due to risk aversion and lack of learning). The outcomes in these cases will be even more suboptimal, and potentially catastrophic.

That being said, all is not grim. There are also some really great paradigms and initiatives out there.

Some organizations are realizing how powerful ‘citizen scientists’ – volunteers in the general public with skills they can contribute, e.g. data scientists – can be, and are working to enable them with better access to data, as well as setting up communities of practice around them.
Growing recognition that, as one city representative put it, wanting to be “data-driven” isn’t optimal as it is “not all that compatible with democracy”– so they are aiming to be a data-informed city instead. That is to say, while data is a very important means to the end of a thriving city, data itself should not drive cities. It should inform them.
More government organizations are working on making federated data systems with the private sector. This reminded me a lot of the excellent Third Wave of Open Data report, in which cross-sector collaboration and contribution is important as the open and shared data situation evolves.
Digital twin work – which generally requires at least relatively good data maturity and governance – is becoming more common. Wellington City Council had some great examples².
Using a variety of data, including tree maps, bird calls, and so forth to enhance conservation efforts in the city and spread native birdlife out beyond reserves.
Understanding climate impacts on the city, for example, looking at how it might change the seed dispersal of the trees holding Wellington’s very hilly slopes together. If they aren’t going to be enough in future, the city needs to find substitutes now so the new trees will be sufficiently large in 30 years.
Major improvements in disaster response times. New Zealand is prone to major environmental disasters, from earthquakes to floods to fires. Such improvements help mitigate their economic and social impacts.

As a fun sidenote: Canada got a few shoutouts from speakers! British Columbia for its digital wallet work, and the federal government for its work on AI Legislation.

As I wrote about at the start of this piece, much of what I took away from the conference was confirmation – that organizations are increasingly realizing that good data maturity, management, and governance are vital to their success, and that it is not a simple process. (I think people often overcomplicate it, at least initially, but that’s a subject for another time.)

I have a long list of takeaways from the conference along these lines, so I will pull out some of my favourites.

Data is not an end in itself – it is a means to an end. The important thing is not the data, but the PEOPLE behind the data, and ensuring they are treated with respect.
Have a vision for where your organization and community are going, and where you want to go, including with your digital strategy.
Systems and the challenges we face as interconnected communities are complex – more effective use of data (and understanding things like complexity) means people can understand how pulling one string in a complex / complicated system might affect other strings, and make decisions appropriately.
Data governance is not the same as data maturity, and not the same as data management. And they don’t magically happen – they are a continuous journey.
Data is not an IT problem.
Data sovereignty is important, for people providing data to government as well as within government. Data ethics and equity interact very strongly here too.
Organizations need to take people on the journey of why they are doing what they are doing and how. Communication and engagement can also serve as potent forces for enablement, collaboration, and inspiration.
There is risk in not taking action, for example missed opportunities, technical debt, and so forth. It is far better, and more effective, to learn from previous ‘failures’ and keep going, rather than just stopping.
People, people, people. Organizations could (should) maximize their internal resources and leverage people anywhere they can, not just at executive or operational levels.
It is important to try out emerging technologies. That being said, nothing is inevitable and we can make choices in how technology is developed and deployed. For example, the EU places emphasis on protecting the dignity of individuals, the principles of necessity and proportionality when looking at existing or new technologies (for example surveillance), and the importance of safety and paying close attention. A representative of theirs at the conference used the example of air travel – it was able to become as widely used as it is (I am ignoring its climate effects here) because plane safety standards are rigorously set and heavily enforced.
And finally? Do not be afraid of details, especially where they affect decision-making. Much of the time the push is to move fast and work out the details later; one should think about them up front instead wherever one can. It will make things much simpler later on and help avoid unnecessary and possibly harmful blunders.

To sum up – as we have seen with government organizations in New Zealand, Canada, and beyond, people are battling with many of the same challenges. How can we overcome them, and do so faster and more effectively than is happening at the moment? The answer is to learn from what has and has not worked, share knowledge with each other about it – as well as resources wherever possible – and never be afraid to ask for help.

And get in touch with us! We can absolutely help you, and would love to hear from you, your organization, or anyone else interested. 🙂