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The Mayor of London The London Assembly

The Middle Out Approach – A New Leadership Pattern to create Data Infrastructure in Cities

The need for data infrastructures (by this we mean data platforms, marketplaces, open data portals and so on) for smart cities is well established.  Cities of today must be prepared to cope with population growth, scarcity of natural resources and environmental issues. The answer to these problems can be found in high quality contextualised data. Hence, it is no surprise that data infrastructures and platforms for smart cities have received so much attention from researchers, private organizations, government, and investors.

However, led by this “buzzword”, many people have assumed that developing data infrastructures from a purely top down approach is the best tactic to follow. That may be a natural reaction, especially coming from private organizations which are willing to sell their solutions; however, it can be a dangerous one. By failing to follow appropriate leadership strategies, many initiatives created to smarten up cities haven’t worked out as planned.

Take the case of one of the first digital cities initiatives, Blacksburg Electronic Village, in which a virtual information space for the village, and it took them two years to set up computers, communications equipment, and other services. This initiative was mainly constructed from a technical perspective, and disregarded the stakeholders (e.g. citizens, businesses) expectations and requirements regarding the digital city. Within two years the activity of this initiative significantly decreased as a consequence of neglecting the several conflicting requirements and expectations which existed among technology providers and users regarding the community network.

This is what I call, the top-down leadership pattern, i.e., cities acting solely as “implementers of initiatives”. The problem in this leadership patterns is that it fails to recognize the importance of the expectations and needs of the users of the smart cities or data infrastructures (e.g. citizens, businesses, entrepreneurs, data scientists, research institutes, city councils).

Today, this leadership pattern is adopted in the majority of smart cities and data infrastructure projects. The lack of understanding of the combined impacts that technology, stakeholder requirements, and big data will have on the overall operation of the city environment has led to the creation of many isolated “smart cities platforms”. As a result, each initiative is composed by numerous fragmented data sources, and different technological standards and approaches.

Cities must change their leadership pattern when it comes to designing data infrastructures for smart cities. The “top-down approach” must retire.

I argue that a better leadership pattern for cities is that one which takes social influence into account while maximizing the efforts of other stakeholders who are working towards the achievement of the same goal: to create better data infrastructure which will unlock the data that realise smart cities.

I call this new form of design “middle-out approach”. This approach combines both a top-down and a bottom-up approach, the latter of which is emerging from communities advancing innovation and industry creating new standards. This new form of design when coordinated by efficient governance strategies can guarantee successful leverage of the innovation and knowledge creation made possible by the data infrastructure.

This middle out approach which is formed on the basis of social influence, and not authority, considers the following aspects:

– The unprecedented value in having a strong value network of collaborators who will provide the expertise needed to deliver a data infrastructure;

– The importance of having feedback loops to understand user’s perceived value, which will help decision makers to assess whether the delivered value matches the expected value of users;

– The implementation of efficient governance strategies. It broadly refers to the mechanisms through which the provider of the data infrastructure exerts influence.

While the technological elements of a data infrastructure can reduce structural complexity, governance can reduce behavioural complexity. Data infrastructure providers must shape and influence its ecosystem – not to direct it – besides respecting the autonomy of collaborators while also being able to integrate their varied contributions into a harmonious whole. This is the essence of city data marketplace orchestration. Its key function is to provide a context in which distributed innovation driven by value creators can emerge around the infrastructure. It is highly important to sustain a harmonious value network and make the necessary trade-offs that will enable the accommodation of users requirements and their alignment to the platform governance and technical architecture.

I suggest that the governance strategy of a city data marketplace should involve platform-based competition and focuses on development of appealing features, driving innovation by collaborators, and resolve the conflicting requirements of the entire value network who contribute to the marketplace by either providing data or services. Cooperation between the value network and city data marketplace providers is very important to develop and to maintain an efficiency data infrastructure that is for all.

These are the core concepts of the PhD thesis I am completing at UCL/Imperial College London. Basically, it proposes an integrated urban data management approach to design and realise smart cities, and how it can be best offered to systems and users through a semantic and intelligent data infrastructure that is provided and supported by multiple stakeholders. An alternative to the prevailing top-down approaches adopted in previous studies, it pioneers a “middle-out” approach putting both the data and stakeholders at the centre of interest.

At the GLA, the Intelligence Unit is implementing these concepts to create a city data market strategy for London, which gives all Londoners and businesses the ability to better collaborate on the basis of common, accurate, data to design and build more sustainable and cost effective buildings, transport, and other infrastructures.

If you want to get involved or learn more about this work, do please get in touch with LARISSA SUZUKI <>