The document discusses New Zealand's Government Enterprise Architecture (GEA-NZ) which includes several dimensions such as strategy, governance, standards, identity/privacy/security, business processes, data and information, and technology. Data and information governance is important to guide how data is created, transformed, and shared across government agencies. The goals of data governance include increasing consistency, maximizing benefits, and managing risks around data use. The document outlines New Zealand's data governance structure and principles, which include having common data definitions, documenting data assets, defining roles and responsibilities, assuring data quality, and guiding how data is used and managed. Agencies conduct self-assessments against a maturity model to evaluate their progress on data governance practices

1. Intro…
I designed the GEA-NZ which has several dimensions: Strategy, investment & Policy; Governance &
Performance; Standards; Identity, Privacy & Security; Business –which includes
customer/channels/product & services/people & organisation/processes-; Data and Information, and
Technology which enables all of this.
Data & Information is at the core of everything the Government does, so we need a strong Data
Governance strategy to guide the creation, transformation, and sharing of data & information.
This Silver Fern symbolises Governance
According to Maori legend, the Silver Fern or Ponga once lived in the sea. It was asked to come and live
in the forest to guide the Maori people. Maori warriors used the silver underside of the leaves to find
their way back home. When bent over it catches the moonlight and illuminate a path through the
forest.
Governance is also a path that guides the usage of our government data and information.
Throughout my presentation you will hear me talk about Data & Information, not just Data. This is
because at an AoG level Data from one agency can be Information for another and visa versa. Data &
Information are very closely linked and therefor need to be aligned with each other.
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2. The NZ Government aims to transform service delivery through digital self-service channels and to
unlock the full economic potential of Government Information.
It supports the focus area Information is Managed as an Asset.
As I already mentioned, Information is at the core of all Government services and the Government is
the guardian of that information on behalf of the public.
Exercising this responsibility, while making effective use of it, is the reason why it is very important that
we have a strong Data and Information Governance strategy.
The digital strategy seeks to:
- Create effective & efficient integrated services delivery models to be used by all agencies.
- Realise new value from Government Information.
- Optimise the use of scarce resources and capabilities.
- Manage the risks around the use of Government Information.
- Assure the quality of the Information.
- Partner with the private sector and NGSs.
- Increase the pace of change.
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3. What is Data Governance?
Data Governance is a set of processes, around Data and Information:
- Ensuring that key Information is formally managed throughout the Government/Enterprise.
- Ensuring that the Information can be trusted and that people can be made accountable so that the
Information is fit for purpose and that the value of those assets are fully realised.
- Altering the way of thinking around Information, how to handle information so it can be used by the
entire organisation/Government/Country.
Some of the goals are:
- Increase consistency
- Maximise benefits
- Minimise rework
- Optimise efficiency
- Manage business risks
- Optimise investment
- Etc.
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4. Here are a couple of examples of what can go wrong if you do not have a strong Data Governance in
your organisation.
BTW these scenarios do not refer to specific incidents, but are based loosely on anecdote collected over
the years from a number of organisations.
- Two business units provided a minister with significant different statistic results for the same KPI.
Reason: (1) Definition of the input information was not consistent.
(2) There were different assumptions in ‘correcting’ the input information.
Attempts to ‘fix’ these problems were fragmented and siloed and therefore the same discrepancy re-
occurred.
- A technology flaw caused a serious privacy breach.
Reason: There was no clear and effective business accountability and therefore no control of
the use of the data and information
- A business case was multiple times approved because of insufficient baseline operational data.
- A major debt recovery campaign was instituted based on wrong estimates. The true value was only
50% of the estimate and the campaign was poorly targeted.
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5. One of the processes we use to get High Quality Data –data that can be used for decision making- is a
four level filtering.
Level 1 is around the Data Definitions and the Master Data Management which includes validating and
structuring the Data and Information.
Level 2 is a Data and Information Quality Framework which looks at what needs to be planned,
documented, executed, and controlled at strategic, governance, business, technology and standards
level. This includes rules, de-duplication, cleansing, monitoring, etc.
Level 3 is about which Information to use for reporting, creating statistics and analysis.
In the last level we look at which information is usable for decision making.
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6. Having access to reliable HQD is a pre-requisite for delivering meaningful information to and from
agencies.
To obtain benefits out of our Data and Information we need a good collaboration between Business and
Technology. That is why the NZ Government established the partnership framework between agencies,
where tier 1 & 2 from different agencies look at the overall strategy of Government and Tier 2-3 look at
the investment, technology, service innovation and information between agencies.
This ensures that processes, people, technology and information are aligned across Government and
their business partners.
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7. The Data Governance structure within the NZ Government is as follows.
We have an AoG Steering group which has the authorisation and mandate to make changes around
information.
Next to this there are several forums:
- Data Definition forum, which makes sure we have a common definition for the data and information
assets across Government and their business partners
- Data Quality forum, which looks at the quality of Data and Information and sets the rules around
sharing, copying, modifying, etc.
- Information and Knowledge forum, which define what opportunities we can get out of our
Information
- and the Education and Communication forum to make sure those changes are well communicated
across Government.
Within agencies we have the:
- Enterprise Design Authority who provides sign-off authority
- Investment Board who provides investment priorities
- And EPNO who ensures the Data Governance within projects.
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8. Why do we need a Data and Information Governance?
- First we need to understand our data processes to successful manage our data.
- Once we understand our Data we know who can manage and control it.
- If Data is managed we can develop a common understanding to simplify and Data and Information.
- To have HQI we need to keep Data and Information complete, accurate, and current.
- HQI gives us the confidence to use it for making decisions.
And these are the 5 principles we follow and asses.
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9. The first principle is having a common Data and Information language. Agencies are using common
definition and models by using our GEA-NZ Reference Models and Taxonomies.
The second principle is about documenting and cataloguing the Information assets. The use our
Information discovery process to identify the Information Assets, us the Taxonomies to categorise the
assets and are using the asset templates to catalogue them with meta-data.
The next (#3) principle is about the roles and responsibilities, create polices, and define standards
which are described in the Data and Information Quality Management Framework.
This (#4) principle is around assuring the quality if the Data and Information, this is also guided by the
Data and Information Quality Management Framework.
The last (#5) principle is about the use of the Data and Information – the reporting processes and
record management.
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10. The Maturity Model we created has 16 questions surrounding those principles.
It is a self assessment tool which agencies use to periodically assess their Data governance processes.0
It gives them a view of the improvements they made, the focus areas, and the recommended next
steps.
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