Using data trusts in garden communities

Planned communities, urban estates, shopping centres and campuses generate data on an individual and organisational level, and from land, buildings and infrastructure. Where appropriate, a data trust can gather, analyse and use that data in order to make the most efficient use of existing facilities, recommend improvements and even, in some cases, develop and monetise new data-driven products.

Of course, for this data to be valuable, the data trust must have the right to use and exploit any data collected in a way which is compliant with applicable laws and any contractual licensing arrangements, while also protecting the data and restricting access to it by others. Pinsent Masons has produced a comprehensive guide to data trusts for garden communities (24-page / 6MB PDF).

Sources and uses of data

Energy data

Potential sources of energy consumption and efficiency data include smart meters in homes and commercial units; utility service provider information; electric vehicle charging points and community battery storage schemes. Energy suppliers will be able to provide information about the sources of energy being used – for example, what percentage of energy consumed, where and when is from renewable sources.

A data trust could, for example, use this data to recommend incremental improvements in energy consumption, energy efficiency and renewable energy usage as part of a development-wide carbon reduction plan, or in respect of building refurbishments and lettings.

This could then be dovetailed with the national drive towards more open energy data as part of the Modernising Energy Data programme, a joint programme from the UK government, Ofgem and Innovate UK building on the recommendations of the Energy Data Taskforce in June 2019. These recommendations included directing the UK energy sector to adopt more open data, and creating a unified digital system map of the energy system.

Transport data

Data on car and public transport usage, journey patterns, peak times and congestion can be gathered from highways authorities and strategic transport bodies; public transport operators; taxi companies, cycle hire operators and car club operators; telecoms companies; surveys of individual travellers and any local congestion charging scheme. It can also be gathered from transport-related infrastructure including parking and traffic cameras, automatic number plate recognition systems and electric charging stations.

This data could be used to deliver efficiency improvements to the public transport network and local roads, developed in response to the actual needs of local travellers; or to plan for safer and healthier journeys. The data could also be used to develop a holistic transport carbon model for the development, monitoring and ultimately finding ways to reduce emissions.

Consumer data

Data on retail, leisure, hospitality and community uses can be collected from shopping centre owners, retailers, food and beverage operators, leisure operators and hoteliers and sports grounds and facilities; through consumer surveys and directly from individuals.

This data could be used to establish how a new community or urban estate is being used, helping to evolve masterplan design and learn lessons for future phases of the scheme. It could also feed into future retail, leisure and community facility design and operations, and be used to attract advertisers and set appropriate rent levels and service charge arrangements with tenants and users.

Healthy living data

Data from sports and leisure operators, health providers and the public could be used to inform the planning and delivery of sports and recreational facilities, public transport options and pedestrian and cycling routes.

Pooling the data

Planned communities often have a centralised stewardship strategy, with areas of the development managed, maintained and operated by a vehicle such as a management company, land trust, community interest company or company limited by guarantee. If well-funded, with a particular focus at set-up on their ability to deliver a regular income stream, they can become self-financing or even profit-making.

Stewardship vehicles can have a variety of shareholders and income streams, of which a data trust component is one. A stewardship vehicle is made up of stakeholders such as freeholders, long leaseholder, infrastructure providers and other who hold the main real estate interests in the development is the natural platform from which to negotiate data pooling arrangements.

The stewardship vehicle can incorporate or work alongside a data trust to enter into data sharing contracts or other arrangements with data source providers, and to pool data sources, in order to:

• maximise the utility of the data collected;
• ensure that data is used in a regulatory and ethically compliant manner; and
• monetise that data, where appropriate.

Data can be stored via cloud data storage or on site as required, subject to the appropriate regulation.

The stewardship vehicle will need to come up with a data strategy focused on objectives, management of and evaluation of data. The strategy should incorporate how to manage data security; the use of personal data, including GDPR compliance; data sharing arrangements and agreement with third parties; how data will be analysed and anonymised where appropriate; and the approach to how data is generated, gathered and flows.

The global data monetisation market is poised for rapid growth, and there may be opportunities to appropriately monetise data gathered and utilised by the data trust while ensuring regulatory and ethical standards compliance. The value of the data gathered by the data trust will depend on a variety of data value drivers including uniqueness and exclusivity; its timeliness, accuracy and completeness; and whether there are any restrictions on its use or potential liabilities and risks associated with its use. There are recognised methods of valuing data which the data steward can take advice on.

Potential monetisation opportunities include data provision to:

• unit occupiers, to help them improve the customer experience and attract customers from target areas or markets. This could be factored into a service charge, rent or specific agreed data sharing payment arrangement;
• advertisers or goods and services suppliers looking to target certain markets in certain locations within the development;
• delivery, logistics or servicing companies seeking to avoid congestion and develop more efficient and timely delivery arrangements to local businesses and residents;
• market research companies looking to assess demand for goods or services in the development;
• bus and train operators, car clubs, cycle hire companies and leisure operators seeking to understand journey habits within the development;
• housing associations and private rented sector (PRS) landlords, to help them enhance the tenant experience;
• insurers, subject to appropriate anonymity;
• universities and other research organisations looking to analyse data on garden communities; and
• residents and occupiers moving to other developments stewarded by the data trust, engendering customer loyalty.