Housing Need and Demand Assessment (HNDA) Tool Instructions (2026)

1. Preparation

Aim

These instructions explain how to prepare for, set-up and run the HNDA Tool. This includes a step-by-step guide and an explanation of the choices and scenarios available. It explains how to interpret results and how to input local data and scenarios if required. If users have any questions please email the CHMA Mailbox.

IT Issues

The Tool is an Excel spreadsheet with additional code.

If using the Tool on a laptop the clarity of the image may be enhanced by zooming in or zooming out using the buttons at the right hand corner of the screen. It is a lot easier to navigate the Tool with a mouse plugged into the laptop rather than using the laptop’s touchpad.

The Tool includes Macros and these must be enabled before it will function. Some operating systems may not let Macros run. In this case it is possible to change system settings to allow this if the system operators/ IT department agree to this because the Macro is from a trusted Scottish Government source.

Preparatory Reading and Analysis

Before using the Tool, the user should be familiar with the HNDA Managers Guide and HNDA Practitioner’s Guide (in particular Chapter 4 about how to estimate housing need and demand).

It is also advisable to complete Chapter 2 of the HNDA before running the Tool. This will evidence the key factors driving the local housing market, a thorough understanding of which is essential before running the Tool.

Scenarios, Alternative Futures & Sensitivity Testing

Future house prices, rents and incomes are difficult to predict long-term and with a great deal of precision. However, HNDAs must project housing estimates into the future to enable medium and long term planning of housing. The Tool does this, in part, by projecting house prices, rent prices and incomes to make an assessment of the future affordability of different housing tenures.

The Tool is populated with a range of scenarios about future incomes, house and rental prices (alternative futures). However, it is for HNDA Practitioners to decide which scenario or scenarios best reflect what might happen in their local area in future. It is worth bearing in mind that a good predictor of the future is what happened in the past. Analysing what happened to incomes, house prices and rental prices in the past is a good way to anticipate what may happen to them in future and, in turn, to help decide on future affordability scenarios.

With this in mind, the Tool is designed to produce a range of BROAD, LONG RUN housing estimates about several alternative futures; any of which might occur but one or two of which are more likely to occur based on previous housing market trends and local knowledge of housing markets.

The user’s choice of scenarios should NOT attempt to predict future housing estimates with complete precision. Instead, it should be based on producing a range of broad housing estimates. This gives the user a range of housing estimates that can be accepted or rejected as the future of the housing market unfolds. A single housing estimate that is too precise cannot provide enough flexibility to plan for a future will always contain some uncertainty.

Users should keep the number of scenarios to a minimum as a further way to help constrain the level of resource required to produce the HNDA. No more than six scenarios are recommended (the key findings template reflects this) and no less than three:

(1) a baseline scenario

e.g. moderate economic growth and moderate household growth

(2) a low scenario

e.g. low economic growth and low household growth

(3) a high scenario < less likely in future>

e.g. high economic growth and hight household growth

It may also be advisable to adjust only one or two factors between scenarios. If too many factors are changed at once it may be difficult to understand and explain how this is affecting differences in the results across scenarios.

A sensitivity test in research modeling is a method used to assess how changes in inputs or assumptions affect the output of a model. It helps in understanding the robustness of the model's results and identifying factors that drive the outcomes. With the HNDA Tool this would involve altering the inputs one at a time to see what effect they have on the results before choosing the final inputs and scenarios. For example, you could alter the income distribution scenarios to see what impact would have on your results before choosing your final income distribution scenario.

The Tool will be run several times using several scenarios. Each time the Tool is run a copy must be saved. Otherwise results will be lost. A copy of the Tool for each final scenario should be submitted to the CHMA as part of the robust and credible appraisal submission process.

The user can input their own income, house and rent price scenarios into the Tool. The practicalities of doing this are set out further on. The decision to do this should be determined by what resources are available to produce the HNDA and whether the use of local scenarios would add sufficient value to the estimates to justify additional resource; whilst always bearing in mind that HNDAs are designed to produce a broad housing estimates; not precision estimates.

Default (core) settings in the Tool

In order for an Excel model of this kind to function, and be tested, it was necessary to populate it with default (core) settings. This allows the users to see how their housing estimates change when they change these settings according to local circumstances.

The default settings were chosen to reflect, as far as is possible, the prevailing state of the Scottish housing market and economy when the Tool was refreshed in 2026. Each default setting is explained within this document.

Data used to populate the Tool

The Tool is populated with nationally available datasets. A list of data sources is set out at Annex A. Users may overwrite national data with local data and the method for doing this is set out within this document.

Any decision to use local datasets or a local survey/research should be weighed against whether their use adds sufficient value to justify the resources required to design, source/ collect, clean and input local data into the Tool; bearing in mind that HNDAs are meant to provide broad range of housing estimates rather than precise estimates.

If this choice is made, the rationale must be set out clearly in the HNDA write-up. The Tool will be updated every two years following the publication of the bi-annual National Records of Scotland household projections.

Issues of geography

The Tool outputs at three main geographies; City Regions (groups of local authorities), unitary local authorities and functional Housing Market Areas (HMAs) within each of these. National Park areas are also available. Local authorities provide the SG with their HMAs and these are then input to the Tool.

Some of the data used to run the Tool are built-up from data zones to create larger geographies i.e. HMA level outputs, then local authority level outputs etc. However, the smallest geography for which National Records of Scotland (NRS) household projections are available is local authority level and a method had to be found to disaggregate these to HMA level.

This was done using NRS’s household estimates which are available at data zone level. Firstly, the number of households in each HMA was built-up from data zones. Secondly, the relative proportion of households in each HMA across an local authority was worked out. Thirdly, these relative proportions were then applied to the household projections (at local authority level) to estimate household projections at HMA level.

If within HMAs there are any specific rurality considerations these should be set out in the relevant chapter of the HNDA. After national data source and local administrative data sources have been exhausted, but there is still a need for more evidence, local studies or surveys should be considered. The CHMA can provide advice on gathering local data.

Benefits of using the Tool

Quick scenario testing - it allows HNDA Practitioners to test and compare different scenarios and see the results of this in real time. This is useful when HMP meet to discuss and agree scenarios as it can be done ‘live’ at a meeting.

Frees up thinking time - time saved sourcing, cleaning and computing data can be spent thinking about which scenarios are best to use and what the results mean for housing policy and planning.

Consistent results - as data sources are consistent within and between areas and authorities, it means that estimates can be compared consistently, for example, with neighbouring authorities or the HMAs within an authority.

Less costly - where previously, some authorities, may have contracted out their HNDAs at considerable cost this is no longer required. This should mean substantial cost savings.

Understanding and skills - the Tool allows all authorities to produce HNDAs in-house rather than contracting out. This means that authorities are likely to acquire a deeper understanding of their HNDA results and the skills for HNDA production will remain with authority staff.

The next section explains how users set up the Tool