Intro - on the importance of housing data

In the ever-evolving landscape of urban development, the key to creating thriving communities lies in the precision of our planning. This blog post delves into the importance of accurate housing data in planning new developments that better integrate with their surroundings. PlaceChangers is a leading proptech starting to make granular housing data easy to use source for town planners.

Join us as we explore how data-driven decisions pave the way for sustainable, community-centric urban growth and why planners, architects, and policymakers need access to comprehensive and reliable housing information.

What location data is helpful for planning and housing? 

For planning new developments, having a high-level and bird's eye perspective on a place's qualities and current situation is helpful. Most projects start with a desk review of the local area. However, only some projects have a spatial understanding of high-level housing information to shape proposals according to local needs. 

A 2021 report commissioned by the Geospatial Commission reviewed the range of data sources used at the planning and design stage and found that while a substantial amount of information is available on local places, the geospatial dimension often needs to be readily identified and shared in data sets. 

The data that is useful for planning and should be available at a granular level should include the following: 

• Land co-ordinates and public land ownership
• Building and planning data 
• Residential lettings data
• Utilities and amenities data 
• Traffic data
• Demographics and household income level data

This information is relevant at the outset for the project team to generate feasibility studies before site acquisition and understand the local area and the likely considerations for successful planning permission (e.g. housing need). This information is also relevant once a site is committed to continuing the conversation with local stakeholders at the pre-application stage. 

How housing data can improve developments

Good quality and reliable location-specific housing data, combined with awareness of local demographics and resident challenges, can help validate assumptions for the provision of new housing. 

Understanding locally-specific housing need

Accurate housing data allows planners to tailor new housing solutions to local communities' needs and preferences. It ensures that new developments align with the housing demands of the area, whether that means affordable housing options, family-sized homes, or accommodations for older people.

Affordability Assessment

Housing data combined with local demographic information allows policymakers to assess housing affordability accurately. It helps identify areas where affordable housing may be scarce and guides initiatives to make housing accessible to all income levels.

Sustainable Urban Planning

Good housing data can help identify sustainability issues in existing homes. Combined with awareness of tenures, building sizes, and built types, good housing data enables characterisation of, e.g. groups of tenures particularly exposed to poor quality unsustainable homes. 

Engagement with community and local planners:

Accurate housing data facilitates better community engagement and clarifies conversations with local planners, letting everybody sing from the same hymn sheet more easily. When residents and local planners see that their needs and concerns are being considered in new housing developments, it fosters a sense of ownership and involvement in the planning process.

Data-Driven Decision-Making

Finally, data-driven decision-making reduces the risk of costly mistakes. It helps validate assumptions, ensuring that investments in housing and infrastructure are made with high confidence in their success.

Challenges accessing housing data in the UK

In the UK, housing data is helped in various places, some of which will be geospatially linked. The best quality housing data is highly granular, down to the Unique Property Reference Number (UDRN).  

Typically, there are several challenges with housing data, including: 

Data Accuracy and Quality: One of the foremost challenges in working with GIS-referenced housing data is ensuring its accuracy and quality. Inaccurate or outdated data can lead to flawed analyses and decision-making. 

Data Integration: There has yet to be a common data standard for presenting housing data for application in town planning. Housing data often comes from various sources, including government agencies, private organisations, and community surveys. Integrating these disparate datasets can be challenging, as they may use different formats, coordinate systems, and naming conventions. 

Privacy: Housing data typically contains sensitive information about individuals and households, such as addresses and income levels. Balancing the need for transparency and public access with privacy regulations and ethical considerations can be challenging. The matter is also not clear. For instance, some government departments have often classed energy performance data as private data, and others do not.

Addressing these challenges requires a combination of data validation and cleaning processes, robust data integration techniques, and a commitment to ethical data handling practices. Additionally, staying up-to-date with evolving data standards and regulations is essential for those working with GIS-referenced housing data to ensure the data's accuracy, integrity, and ethical use in planning and decision-making processes.

Make housing data accessible: PlaceChangers place analytics

The emerging proptech sector makes essential planning data more readily available in convenient and standardised formats. Taking the example of PlaceChangers, a leading UK proptech startup used by town planners in planning and design, housing data is available in convenient geospatially referenced and granular analytics views. 

Digital tools such as PlaceChangers Site Insights are handy for: 

Quick Context-Specific Summary of Housing Characteristics in an Area

PlaceChangers Site Insights for housing offer a valuable tool for obtaining rapid, context-specific summaries of housing characteristics in a given area. By harnessing this technology, urban planners, developers, and policymakers can gain insight into local housing demographics, property types, and housing conditions. This enables informed decision-making, as it helps stakeholders grasp the unique housing landscape of an area, leading to more precise planning and resource allocation.

Overview of Energy Efficiency and Affordability Challenges

PlaceChangers Site Insights delves into the crucial energy efficiency and affordability issues within local housing. By analysing data related to energy consumption, costs, and affordability levels, this tool empowers communities and authorities to identify critical areas of improvement. This knowledge is instrumental in crafting sustainable and affordable housing strategies, making it easier to pinpoint where interventions are needed most and allocate resources accordingly.

Awareness of National and Regional Comparisons:

PlaceChangers Site Insights extend beyond local insights, offering a broader perspective through national and regional comparisons. This allows housing stakeholders to understand how their area compares to others, both in terms of housing characteristics and challenges. Such awareness is invaluable for benchmarking, drawing inspiration from successful models, and tailoring policies and interventions to match a given region's specific needs and aspirations.

Visual Maps for Feedback:

PlaceChangers Site Insights inclusion of visual maps for feedback is a game-changer in community engagement and planning. These maps provide an intuitive and easily digestible way to convey complex housing data to diverse audiences.

Citizens, community groups, and stakeholders can readily visualise housing conditions, accessibility, and potential improvements, fostering a sense of involvement and collaboration. Visual maps facilitate constructive feedback and enable collective decision-making, ensuring that housing initiatives align with the aspirations of the community they serve.

Conclusion

For town planning, access to relevant location data is increasingly paramount. Reliable housing data is essential in informing development briefs, especially from a view of urban design and housing needs, and therefore promises more development proposals that are responsive to local needs. 

With the abundance of location data and the emergence of leading place analytics tools in the proptech space, such as PlaceChangers site insights, planners and architects can enrich early design and plan with better insights on a larger scale without the need for complex GIS environments or in-house data science expertise.