Building digital infrastructure for Wales

The Welsh Revenue Authority (WRA) needs to support geographically varied land and property taxes.

One example is the Land Transaction Tax, a tax that applies to all land and property transactions in Wales. The tax is changing so that in certain areas there will be an additional rate of tax for second homes and holiday lets.

To implement this policy the Welsh Revenue Authority will need to be able to identify the exact location of a parcel of land or a property.

LTT is not the only tax the WRA handle. They also handle the Landfill Disposal Tax, and there are other taxes in the pipeline, such as Council Tax Reform and a Tourism Levy.

Each of these taxes will have its own set of location-related needs. Some of them will be unique to a tax policy but a lot of them are common needs. For example;

I need to know if a property/plot of land/business/etc is in a specific area.

The Land and Property Data Platform (LPDP) project explored how a land and property data platform could meet these needs and become a common building block for digital services in Wales.

A slide showing a number of boxes, representing services, stacked on top of rules and functions, and data boxes which make up the platform. — Framing what we mean when we say 'Platform'

Defining a mission and goals

I joined after an initial 12-week proof-of-concept stage.

It was important the team was on the same page so we kicked off the second phase by defining a mission statement.

Mission statement

Make Welsh public services simpler to deliver and digital-age policymaking a reality through the access and exchange of land and property data

And, setting some goals.

Goal 1

Learn how to operate a platform that meets the needs of (some) real users and policymakers
Goal 2

Test constraints of working with real data
Goal 3

Understand where potential future users of a platform are and their needs - wider landscape

A mission and goals give the team a focal point and are tools to use when making decisions. Sharing them helps stakeholders to hold us to account.

A zoomed out view of a miro board we used for capturing user research notes. All notes are blanked out but the landscape view is very wide showing the breadth of findings. — Research findings on our virtual board

Enable modern policy-making

A data platform gives Ministers and policy-makers more options to achieve policy outcomes by bringing together data into one place.

It makes it possible to build tools that allow policy-makers to test their ideas and finely-tune parameters for a policy.

A wireframe showing a monochrome map of Wales with an area outlined in yellow and a larger outline in dashed red. There are 2 user controls, 1 that allows a user to select an extent and the other to add a buffer. There is also a box showing some important numbers that represent the impact of the choices. — An early wireframe of a tool that allows users to tweak a couple of parameters

A platform also makes it possible to build tools that help users understand a policy. For example, the WRA could create a tool to help Local Authorities understand changes to the LTT policy. This tool could help users more easily assess the impact any implementation options may have.

I designed and iterated a policy explorer tool to show how this might work for LTT. An interesting challenge for me was exploring different interaction patterns for the different policy levers.

A picture of 4 related wireframes. The wireframes are for a LLT explore tool. Each wireframe builts upon the last showing how we planned to build something usable at each stage. The last wireframe shows a map with areas selected, a list of the selected postcodes and then numbers relating to the selected postcodes. — Policy tool wireframes - delivering something usable with each iteration

We introduced the potential of these types of tools through our Show and Tells. This opened up ongoing conversations with Welsh Treasury and Local Authorities, and allowed us to get direct feedback on our work.

Working with data

Working with real data is the best way to uncover, learn about and understand the challenges any users of that data experience.

It is easier to show the impact of discrepancies and inconsistencies in the data with real examples than to explain hypothetical challenges.

For example, I could highlight the unnecessary steps I had to take to assess the data. And show how much extra code I had to write to use the inconsistent data for the "Tell me about a location" prototype.

A flow diagram showing the steps you need to take to use the geography data in its current, inconsistent form. There are examples of 4 different data records showing how each is different and has different attributes. Then on the right is a simplified flow showing how it could work if geography data records were consistent. — A proposal to make geography data easier to use

Once I had a better grasp of the challenges using the existing data I could make better-informed design decisions about what the platform would need to do to support service builders.

A screenshot of a board we used to plan what order to build features for the platform. The diagram shows a card for each feature. The x-axis is used to display priority order (left should be done first). The y-axis shows how some features will be built on other features. — Planning what we needed to build for a policy tool MVP

Each existing set of data comes with its own licensing, attribution, maintenance and quality issues. We were able to manage this reality by tackling these challenges one dataset at a time.

Prototyping to learn

I built a series of prototypes to help us learn more about the problem space and to demonstrate the potential value of a platform.

As a team, we felt prototyping was the best way we could learn about:

the needs of service builders - building prototypes allowed us to think about what users need from a land and property data platform and how they would need to use it
the shape of existing data and the difficulties using it
different interaction patterns and how to build them

Screenshots of 4 prototypes. One shows the data returned by the 'Tell me about a location' prototype. The middle one shows a large map - this is the data explorer prototype. The 2 on the right show the 'transactions by postcode' prototype at different iterations. One of these is also in Welsh because this was a bilingual prototype. — Screenshots of prototypes

We based each prototype on insights from user reasearch and what we’d learnt from previous prototypes. Our collection of prototypes is a good record of how our thinking evolved over the course of the project as we learnt more and, just as importantly, learnt about what we still needed to learn.

Working in the open

As a team, we committed to working in the open.

We did this with weekly show and tells, publishing updates and blog posts on the team site, and making our prototypes available for anyone to explore.

These artefacts demonstrated our progress and turned project governance into ongoing engagement. Working in the open led to more conversations and allowed people to scrutinise what we were doing, ask us questions and give us feedback.

Working in the open also means others can build on the work we are doing.

For my part, I created a page per prototype. This is where I recorded the intent behind each prototype and captured what we'd learnt.

A screenshot of the page for the 'page per prototype' write up. It lists the 7 prototypes from 'Find your local authority' to 'Ways to construct areas' — Write up for each prototype

Outcome

We created a small, proof-of-concept platform for the WRA to use for their implementation and roll-out of Regional Land Transaction Tax. This will allow them to learn about operating a platform.

And we laid the groundwork for new digital infrastructure for Wales. There are ongoing discussions between the Welsh Treasury, WRA and Centre for Digital Public Services (CDPS) about how to structure and fund the next phase of the project. I expect it to continue soon.