How to write the perfect data strategy in just two pages
The illustration above dates from the 1840s, and it depicts a kākāpō1. The kākāpō is a large, flightless, nocturnal green parrot that is endemic to New Zealand.
It’s also critically endangered: there are only 252 kākāpō alive today.
As a reader of this blog you probably work with data a lot, so you may recognise the kākāpō from the cover of R for Data Science, the go-to guide for anyone getting started with the R programming language. It would be remiss of me at this stage not to direct you the Kākāpō Recovery Fund, as do the authors of R4DS.
Why am I opening this blog with some words about an endangered green parrot that can’t fly? It’s because the kākāpō is a example of something that is taonga.
Taonga
A recent episode of the Data Chief podcast featured a conversation with Jan Sheppard, Chief Data and Analytics Officer at New Zealand’s Crown Research Institute of Environmental Science and Research (known as ESR). Jan talked about the strategy she’d recently composed for the organisation, which you can find here (PDF).
I recommend you have a read of it now. It’s only two pages long, so I don’t mind waiting.
Pretty inspiration isn’t it?
Some of the language might seem unfamiliar to you if you’re not from New Zealand (or even if you are), but it’s worth pausing to reflect on some of the key ideas expressed in that document.
For example, here’s the vision Jan sets out:
It is through the taonga of the data under our care that we explore the unknown to see beyond the horizon, so we can build a better future for New Zealand and New Zealanders.
“Taonga” is the key word here. It’s a word (or kupu) in Te Reo Māori (the language of the indiginous Māori people of New Zealand) which was emphasised in the original text. What does it mean?
As a relatively recent immigrant to New Zealand (I moved here from England in early 2019), I need to be careful about applying my own interpretation to these terms. To help me out, here’s what’s said about it in the Te Aka Māori Dictionary:
(noun) treasure, anything prized - applied to anything considered to be of value including socially or culturally valuable objects, resources, phenomenon, ideas and techniques. Examples of the word's use in early texts show that this broad range of meanings is not recent, while a similar range of meanings from some other Eastern Polynesian languages support this (e.g. Tuamotuan).
This makes sense: after all, those of us who dedicate our professional careers to working with data consider it to be of tremendous value. But notice that the ESR strategy refers to the “taonga of data” (emphasis mine), reminding us that data isn’t valuable on its own. It possesses a value that can be realised by those of us who use it, or rather those of us who care for it. Jan talks about the idea of data as a living thing, and living things require care.
So data is a living thing that requires care, and from which we can realise value. But what does this value achieve, and for whom (or what)? That’s where this vision comes alive: it enables us to exlore the unknown, so that lives and the lands they inhabit can be improved.
Notice it doesn’t mention anything about improving decision making or building data products. It doesn’t even mention the organisation for whom this strategy was written. A good vision doesn’t need to, because it should reflect core values and it should endure.
You couldn’t take a single word out of that vision, and I wouldn’t want to.
Mana before mahi
To wrap up, I want to draw attention to the first of the five principles outlined in the document:
Mana before mahi: we build trust and understanding before we start the work.
The idea here is simple: if we neglect to build trust and understanding with our stakeholders first, then the value of our work is not fully realised. Why should anyone believe our analysis if we haven’t shown them who we are, and how can we be certain the analysis was worthwhile if we haven’t shown an interest in who they are and what they need?
I highly recommend reading through the rest of the strategy if you haven’t by this point. The language is beautifully concise and emphasises trust, respect, discovery, and generosity. You probably won’t read another data strategy quite like it.
The artist appears to be Henry Constantine Richter, probably based on sketches and notes belonging to Elizabeth Gould. You can read more about these artists, and the publications that showcased their work, via the Australian Museum