The knowledge economy has shaped cities. As part of the startup gold rush, civic administrations have toiled to create conditions that will attract entrepreneurs keen to set up shop and create intellectual property. But while doing so, cities have overlooked the fact that they have also been generating valuable knowledge.

The planning process intrinsically requires urban environment models to understand the best courses of action. These are often, though by no means always, based on data, perhaps formalised in a spreadsheet or jotted in notebooks. Regardless, they capture patterns, insights, and observations about how a city works, today and in the past; and are used to forecast how they may continue to work in the future.

Cities invariably don’t solve all of their problem alone. That’s because many – such as as, say, improving air quality or reducing traffic congestion – require expertise and resources that they don’t possess. In those cases, they turn to experts to help them.

But, the relationship between the two is broken. Cities pay large sums for experts to create models or refine existing ones, often with a great deal of input from the city authority. And yet cities ultimately retain the rights to use only a small proportion of the work for which they’ve paid: a report, perhaps slides from a presentation, maybe some results from the model in a spreadsheet if they’re lucky. Rarely, if ever, do they retain the model itself.

That means that, when the time comes to revise a strategy or plan, the city has to start from scratch. The Greater London Authority, for instance, has an annual budget of around £500,000 to employ external experts to update the London Plan. The majority of it is used to revise and refresh existing studies and models, rather than build new ones – and some of that could be done more efficiently in-house

The problem is exacerbated by the fact that domain experts hold the newly generated IP, which they can either sell on to other clients or else use to leverage new contracts. In extreme cases, the dual role played by experts – in supporting both cities and organisations that work for cities – can lead to perverse consequences.  The knowledge gained in developing affordable housing policies is, for instance, also useful to developers seeking to minimise exposure to such projects. In these cases, cities pay a consultant, give away their own IP, then allow other parties to use the knowledge against them.

City authorities and their staff must be far more pro-active in understanding and valuing the models and knowledge that they use to support the planning process. In the future, it should be the case that cities design, build, and own their own models of their city. These will still require the input of domain experts – but instead of handing over intellectual property, they will pay for the knowledge of others to create models that they can re-use, edit, and build upon, enabling the planning process to move far faster.


This will prove expensive in the short term. It will require cities to employ data scientists to capture and codify their knowledge, as well as altering their expectations about IP in relationships with contractors.

But costs will be easily recouped. First, cities will act as the gatekeeper of models built on their own data, that other organisations – housing developers, utilities companies, even other cities – will seek to utilise, and the city will be able to charge accordingly. Second, those same models could be used to inform broader city planning and service delivery, reducing duplication of effort and increasing consistency across the local authority.

At Future Cities Catapult, we’ve already started investigating how cities could adopt these kinds of approaches. With Space Syntax, we’re developing an innovative project called Tombolo that will provide an open source platform to streamline the connection of multiple urban datasets and models. Currently, we’re working with Leeds, Milton Keynes, and the Royal Borough of Greenwich to understand how their data and models could be simply and easily fused, to give policymakers new insights into complex challenges.

Tombolo, though, is just one of three large-scale products being funded by Innovate UK which are investigating how data modelling can be used to inform real world issues – and this must all be seen as part of a much larger trend towards the concept of modelling-as-a-service, which is being led by the likes of Andreessen Horowitz-funded London startup Improbable.

If UK cities take advantage of this trend and use their own intellectual property, they will be able to interrogate assumptions that sit deep within the myriad planning documents that currently remain inaccessible. Ultimately, that will allow them to perform land use planning with increased speed, efficiency, and transparency. By using their own knowledge, cities will finally be able to develop as effectively as possible.

Stefan Webb is head of projects at Future Cities Catapult.

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