Easy access to data on all government services
We continually strive to get a deeper understanding of people’s experiences across government to access information and services — what they’re accessing, why and how. We also want to know how these experiences might be improved. This understanding supports us to evolve Govt.nz to ensure we provide information that meets people’s needs — where, when, and in the ways they need it.
In April 2019, Government Information Services, part of the Department of Internal Affairs, led a piece of research to identify all the public facing services that government provides. This was part of wider work to support the ongoing development of Govt.nz.
We’ve developed a visual, interactive map of government services, and a dataset to support wider benefit across all of government and NZ.
What we did
Spire Digital was commissioned to support the discovery exercise with 72 agencies over a 2-month period. By the end of June, 51 agencies were engaged, 48 of whom had public facing services.
After a few attempts we landed on an approach. We provided a researched view of an agency’s services and then tested this with a group of representatives from that agency.
A big shout out to all the agencies involved, without you we wouldn’t have the robust data that we have.
Data by itself isn’t useful unless you have a way of sharing, visualising and analysing it. With this in mind, we decided to make the data available through a visualisation tool called Kumu, and to make it public.
A map of government services
Kumu is a web-based data visualisation platform that creates a visual map to help people to understand and interact with complex relationships, simply and easily. The map is easy to share, and we’ve made this publicly available.
The video below talks you through how the map works and a link to the map itself.
An open dataset of government services
We’re planning to share this raw government services data on www.data.govt.nz in due course. This allows agencies, NGOs, and businesses to be able to add to and validate the dataset, or to pull this dataset into a business process, or analysis tool, thereby adding even more value.
Analysis of the data
We also did some high-level analysis of our own.
- We engaged with 51 government organisations, 48 of whom had public facing services.
- We identified 303 service areas, which are ‘groups’ that services fit into. An example of this would be at ACC — one service area would be injury prevention services, and then sporting injuries or workplace injuries would be services that sit underneath that area.
- We identified 1, 213 services as part of our research.
- We gathered 628 triggers, or reasons why people come to need services — that is, what happened in their life to trigger this need?
We categorised services areas and services as being either:
- public — for the general public, or
- partial — publicly available but targeted and mostly designed for a certain professional field.
We categorised our end-users, or customers into 3 types:
- general public — for services broadly designed for anyone and everyone
- specific public — for services that have eligibility criteria associated with them
- professional — for services mainly used for professional reasons.
We recorded engagement options, or communication channels, for each service. The main ones were:
We further categorised services that could be accessed online. They were either:
- informational, or
- service transactions — full or partial. Partial services are those where only part of the transactional service can be done online, for example downloading a form from a website that then needs to be sent by mail.
Of 1,172 identified online services, 798 (68%) were classified as informational, and 374 (32%) as service transactions.
Of the 374 identified service transactions, 159 are fully delivered online and 215 are partially delivered online.
Note: some of the data hasn’t been fully verified, and due to resource restraints, this is only a partial picture of government services. Further work will have to be done to augment the data going forward.