Know your Place, realise your Value: exploring the Concept of Data-Driven Value Networks
This is the third in a series of blogs we are writing as we create a City Data Market Strategy for London. In the most recent post, we presented a new leadership pattern to create data infrastructures for smart cities called “middle-out” approach. This new leadership pattern is formed on the basis of social influence and collaboration, and taking into account the unprecedented worth of having a strong value network of collaborators who will provide the expertise needed to deliver a data infrastructure.
In this blog post we present the important concept of value networks and the crucial role they play in the development of data infrastructures for smart cities. My PhD thesis defines a data infrastructure as “the basic physical, digital, organisational and governance structures and processes needed for the management of all data that underpins the decision making processes in smart cities” (Suzuki, 2015).
Often, the supply chain of data and services is almost exclusively composed by a platform provider, limited data providers and the consumers of city data. This city data supply chain may have once upon a time have worked but is today too simple and unduly expensive.
Today’s simple reality is that cities find it tremendously difficult to specialise in all the competencies involved in designing, building and maintaining an intelligent data infrastructure. Because we are yet to create a true blueprint for a value network, cities have neither the incentive nor the means of bringing external partners round to the necessary new way of thinking. The danger of not doing so soon is that complexity overtakes us – the development of data infrastructures becomes longer than a simple ICT project, and as a consequence, more expensive and difficult to design and maintain.
So cities can be better served by taking account of the relationships that make the value network more competitive in a way that produces lower costs, better data and services, and which lower risks for each of its members. This is the concept of Data-Driven Value Networks (DDVNs) (Suzuki, 2015).
The concept of DDVNs is based on a platform-centric approach, which enables the pooling of multiple organisations’ knowledge bases. Android and iOS are examples of organisations that have successfully become platform intermediaries and which now lead the telecommunication industry. Even powerful organisations like Google and Apple need to collaborate with the various members of their value networks (e.g. developers) in order to provide unique and inventive services and applications to end users.
A DDVN integrates processes and data in orchestrated supply chains which enable collaboration and ‘co-opetition’ (the notion of collaborating in some parts and competing in a healthy way in other parts) in the provision of city data and services, as well as ensuring a response to demand that creates innovation and value.
There are three basic types of partners in a DDVN: structural partners, contributing partners and supporting partners with varying degrees of power within the value network, based on their resources and capabilities.
- Structural partners: have the most power in the network and are often formed by the platform providers and advisory partners.
- Supporting partners: are the providers of service and data within the data infrastructure, such as open and proprietary data providers, and application developers.
- Contributing partners: are providers of feedback and creators or knowledge and insights, such as end users, data integrators and knowledge creators.
This network of partners can potentially bring insights about specialised domains and different application markets that one single organisation or city government developing a data infrastructure for smart cities would struggle to maintain in-house. Basically, this concept drives cities to deeply specialise in their core competence – governance. As a consequence cities are able to decentralise their city data portals and platforms to create specialised supply chain networks which involve many partners, forming a large ecosystem of expert collaborators.
Government – assuming the role of provider or manager of a city’s data infrastructure – must make decisions about what expertise should be provided in-house and what is left to supporting partners. This means carefully assessing the opportunities that arise to enter complementary markets (e.g. commercial exploitation of city data) and making use of mechanisms they have at their disposal to stimulate innovation within the ecosystem. This can include disclosing technical and data architecture details (as we ourselves intend to do), sharing and outsourcing expertise, creating partnerships, and integrating supporting partners’ solutions into the infrastructure itself.
We also find important to highlight that the success of data infrastructures will also be co-determined by the contributing partners. Governments should not simply instigate one-way communication of their data but should expect or actively solicit feedback and be able to make sense of it. We will discuss the notion of feedback loops in our next blog post.
So in conclusion, the core principles of DDVNs are:
- establishing and maintaining both competitive and collaborative relationships with collaborators;
- supporting competition and joint innovation;
- providing incentives for participation in the value network; and
- harnessing the power of feedback loops.
Through the combined effect of these actions, we can create the environment in which collaborators can most readily advance their own businesses and innovation efforts.
Suzuki, L.C.S.R. 2015. Data as Infrastructure for Smart Cities. PhD Thesis, University College London.