With the end of Robert Jenrick’s tenure as Secretary of State for housing, and indeed the end of MHCLG (to be replaced by DLUHC), it would appear that the Government’s ambitious strategy to revolutionise the English planning system has been shelved. This is a shame, as one of the key drivers of the proposed reforms was an overhaul of the country’s geospatial open datasets to improve outcomes in the built environment. This agenda is no less critical to the concept of “levelling up,” which is, above all, about addressing regional inequality in the UK, and especially health inequality.
At PlaceChangers, we advise many of our clients on the use of location data. In particular, we are champions of the use of geospatial context datasets in early design phases. When combined with proprietary asset data, insights gained early can help “bake in” design quality - for example, by highlighting the underprovision of community assets within walking distance. This approach is suitable for public health, but it’s also good for the bottom line, and it can be undertaken as early as the business case phase.
I want to talk about how we go about it - and the ramifications for a wider “data revolution” in the industry. There is a change coming to the way we build neighbourhoods. Those astute enough to see what it looks like before it arrives will be best placed to exploit its opportunities. As in many industries today, this change will be driven by innovation in and around the collection and use of data. Specifically, the key to this innovation in the built environment sector will be “design quality”.
What do I mean by this?
What changes are on the horizon?
In March 2021, Arup published a whitepaper commissioned from the Open Data Institute entitled “Exploring new approaches for sharing data in the built environment”. The whitepaper found that, due to the highly siloed nature of the built environment sector, the immense economic value of the data collected by professionals in that sector - engineers, architects, urban designers, land managers, planners - presently goes unrealised. The ODI has written extensively about the value of data in the private sector, inspired in part by McKinsey, who, in 2013, estimated the unrealised value of open data at $3-5 trillion globally.
In June 2021, the Geospatial Commission released its Annual Plan 2021/2022, which emphasises the role of geospatial data in the economic recovery from the COVID-19 pandemic. It announced the Commission’s intentions to build out the National Underground Assets Register and invest in regional pilots of a “joined-up” approach to collecting and coordinating land use data. I’ve written about the limitations of the chaotic existing public sector land data ecosystem elsewhere.
There is an impetus for change here. There is a push from the public and the private sector to improve the use of data in planning. I argue that “design quality” is the motivator behind that push.
What is design quality?
Design quality is defined economically as "resistance to depreciation". In simple terms, given two comparable goods, e.g. two houses, the higher "quality" good is the one whose resale (or, indeed, rental) value falls more slowly (or rises more quickly) than that of the other. A 2002 Design Council/CABE report finds that this premise is intuitive to 72% of people interviewed and, more importantly, supported by evidence from the Urban Land Institute, which finds that neighbourhoods that embody urban design principles have 11% higher house values than comparable neighbourhoods that don't.
As intuitive a definition as this may be, its usefulness as an indicator in the housing market is presently distorted by a substantial - specifically, 13.4% - and consistent rise in house prices since 2019 driven by the COVID-19 pandemic. This is as true of lower quartile house prices as it is of median house prices: even affordable housing is less affordable than it has been since 2007, when house prices spiked right before the global financial crisis.
Meanwhile, like consumers, housebuilders are price takers, not price setters. The cost of land is a function of house prices, which is a function of (under-)supply and demand, meaning the only element of profitability over which housebuilders have any control is construction costs. Construction costs are associated with design quality, which means there is a natural incentive for housebuilders in the UK to build for quantity over quality to save money.
It's worth mentioning that this situation is liable to change soon. Land valuation is increasingly data-driven, and the quality and reach of that data are growing. Specifically, property valuation is moving toward a "system-wide focus" approach which exploits the "blurring of silos" already seen in the built environment sector. Other factors, precisely design quality (in the sense of resistance to depreciation), will play an increasingly important role in land valuation, especially insofar as design quality is a function of site context.
In the meantime, we need a more workable definition of design quality. In a June 2018 article published in the Journal of Urban Design, Matthew Carmona proposes such a definition, based on a meta-analysis, of "place quality" defined in terms of "place value", where the latter is defined in terms of "occupier utility" (roughly: the extent to which someone's life is improved by where they live). This analysis is supported by a February 1993 article published in the Journal of Real Estate Research, demonstrating a clear link between occupier utility and resistance of rental values to depreciation. Design quality, in other words, is whatever elements of design maximise occupier utility.
Key among determinants of occupier utility, meanwhile, are health and wellbeing, and, as the Spring 2017 issue of the Urban Design Group Journal notes, "the UK's most pressing health challenges, such as obesity, mental health issues, physical inactivity and the needs of an ageing population, can all be influenced by the quality of the built and natural environment." A recent review by the UK Green Building Council concluded that "Residents want to live in a safe community with opportunities to interact with neighbours. People desire access to local shops, and services with good transport links. Gardens and green space are important, supporting people's preference for healthy surroundings."
A May 2019 study published in Land Use Policy explicitly links "quality design" to health, and cites "organisational and professional silos, ignorance, lack of resources and a reactive planning regime" as the key barriers to healthy design, highlighting the challenge of convincing private developers that design quality doesn't mean "damaging their financial interests."
In 2001 the Commission for Architecture and the Built Environment commissioned research from UCL's Bartlett Faculty of the Built Environment which showed that quality design "responds to occupier demand", leading to "high returns on investment" for housebuilders by "attracting investors and pre-lets" as well as improving "company image", which in turn attracts further investment down the line. These factors play an increasingly crucial role as investment decisions become data-driven.
It is vital to be clear on this point. The land valuation and finance sectors are moving ahead and innovating with data. As investors consider greater number of data points, housebuilders that don't keep up will be left behind. Marginal profitability, as above, is a function of build costs. Long-term profitability, however, is a function of design quality. Finally, building for quality has long-run returns and de-risks individual projects in the short run by bringing presales/prelets forward.
Importantly, this is as true of existing estates as it is for new builds. As long as they are targeted intelligently, even straightforward improvements to thermal efficiency, urban greenery, active travel infrastructure, etc., can turn a neighbourhood with a high churn rate into one with a waiting list overnight. You already know this if you're a housebuilder with existing build-to-let stock. The million quid question is: what can you do about it?
How do we improve design quality by understanding health impact?
According to an analysis by Urbanist Architecture, unexpected building costs arise, above all, around “areas of the building that are there for the entire lifespan of the building, [that] affect the occupiers negatively or positively depending on the decisions made at the beginning of the project.”
At the very start of a project, at the business case phase, a developer will typically run an exhaustive site analysis. This is fundamentally a data collection exercise and requires weeks of manual work, much of which is data entry. From the moment the data comes in, typically in the form of documents, design decisions are already being made.
The return on investment in design decisions is highest, as the decisions are cheap to make, and the ramifications for project cost are significant. At present, this data collection is typically commissioned on a per-project basis. This approach is inefficient and expensive. How much work is duplicated doing things this way? How much work isn’t done at all?
During the planning phase, local planning authorities will typically be engaged to undertake design review. Public Practice has recently codified the steps involved in a design quality appraisal to streamline the pre-application process on the public sector side. Unsurprisingly, the resulting checklist emphasises outcomes for health and wellbeing.
These processes fall short when there is a lack of human resources, which is often the case in both the public and the private sectors. How much of this work could be automated? As the Arup/ODI report finds, the key is data sharing. Indeed, a 2017 study by Deloitte reaches fundamentally the same conclusions.
We’ve argued elsewhere for open data standards in the built environment sector. The 2020 JLL/LaSalle Global Real Estate Transparency Index survey explicitly brings “health and wellness [...] to the fore”, emphasising the value of accurate and readily available real estate data, as well as the role of proptech firms like PlaceChangers, to investors, and, as such, to the economic growth of cities. Unsurprisingly, London ranks at the very top of the index. What does London do that the rest of England doesn’t?
In London, it is compulsory to “assess the potential impacts of development proposals and Development Plans on the mental and physical health and wellbeing of communities [...] for example through the use of Health Impact Assessments.” Meanwhile, PHE’s 2020 Health Impact Assessment in spatial planning report asserts that “An HIA is most effective when it is undertaken prospectively [...] before decisions are made.” Indeed, the 2019 Islington Council HIA guidance recognises “that developers have incurred significant costs at the point that a planning application is submitted to the council” where a HIA has been undertaken retrospectively.
Accelerating the business case with design quality
This is why, at PlaceChangers, we are working with local governments and governmental organisations such as Public Health England to ensure that the critical data concerning the health impacts of your planned sites are available to you at the click of a button. It accelerates both your new build and your renovation projects, but it also improves their design quality, which in turn means faster sales at higher prices and increased long-term profitability and access to investment.
The reality is that developers across the country already have existing site data. Moreover, there is already a wealth of information in a site boundary alone: any developer can undertake a rapid assessment of potential net gains for health and wellbeing at phase zero. This kind of analysis is vital to future economic growth and returns on investment across the country. Call it “levelling up” or “building back better” if you like. For PlaceChangers, at any rate, it’s about seeing ambitious housebuilders succeed.
The Lichfields 2020 Start to Finish report finds that the average turnaround time, from business case to the first completion, is 3.3 years for sites over 50 dwellings - 8.4 years for a place with 2,000+ units - noting explicitly that much of this is “significant amounts of pre-application engagement and work.” However, the report also finds that this lead time has shortened since 2016.
The report does not explain this shortening of lead times. However, at PlaceChangers, we believe an explanation can be found in a 2019 McKinsey study that finds that “digital leaders [...] can be four times faster, and twice as powerful, as those of their peers.”
Early adopters have a competitive edge in the AEC industry in England. That competitive edge will soon overcome the economies of scale presently exploited by the most prominent developers in the country. Combined with a push by national and local governments and real estate investors for higher standards of design quality, the impetus to adopt data analysis and insights technology could not be greater than it is at present.
Taylor Wimpey has invested over £10 million in software in the last two years. That money funded the development of a brand new, proprietary geospatial data platform called LEADR. Taylor Wimpey - one of the largest volume housebuilders in the country - has seen the change I’ve discussed in this article coming. They are ahead of the curve on this front, and, as a result, they now have a massive advantage over their competitors. Of course, they also have £10 million to invest in software. Most housebuilders don’t. This is why PlaceChangers exists.
I’ve written in greater detail about the power of a business-case phase desktop site study using the PlaceChangers platform. If you’re interested in learning how PlaceChangers can help you leverage your site data to accelerate your projects and improve your returns on investment, book a call with us today.
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