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Organising Smart City Projects: Lessons learned from Amsterdam

sca_projectsThis report, issued by the Amsterdam University of Applied Sciences in cooperation with Amsterdam Smart City, analysed 12 smart city projects in Amsterdam to draw lessons and make future smart city projects more effective. The idea was to analyse the non-technological aspects of smart city projects (partnerships, business models, scaling potential) since smart city solutions are not just about developing and applying technology.

Solutions demand new networking and management competencies as they are not developed and implemented by one single company, but take shape in networks and with the involvement of citizens/end users. Partnerships are formed, they all work differently and face different challenges. In this study, a number of smart city projects in Amsterdam is analysed in their wider context.

This report focuses on questions as:

  • How do organisations with different agendas, collaborate on smart city projects?
  • What challenges do they face?
  • What kind of value is created?
  • How are risks and returns shared, and how are users involved?
  • What is the upscaling dynamic of smart city solutions, if any?
  • How can smart city projects be managed professionally?

Based on the key insights on the project level, the authors created a checklist for anyone who considers to initiate or join a smart city project. This checklist contains some questions that are relevant to answer before starting a project:

  • Partnership: What type of partners do we need from the start? What is the role of the city administration? How can the partnership stay open to new input?
  • Ownership and project leadership: What is the commitment of each partner to the project? Who considers themselves the owners of the project? Who will be the project leader?
  • Goal and prospective value: What is the goal of the project? What kind of value (economic, social, ecological) will we create by the project? For whom? What will be the value for each partner involved?
  • User involvement: Who are the prospected users of the project? To what degree will they be part of the partnership? How will the users be involved? In what stages of the project?
  • Data science: What kind of data will we use or generate in the project? How will we analyse, share and visualise this data? And will we protect the privacy of users or clients?
  • Knowledge: What is the technology this project depends on? Who will bring in what knowledge? What new knowledge do we expect to create? What is the strategy towards intellectual property?
  • Financing: What kind of financing does the project need? What can partners bring into the project? How will we share costs, benefits and risks?
  • Business model: How is the project financed? How can the value be translated into value streams? What might be a viable business model for the project?
  • Impact analysis: When is the project considered successful? How can we measure the impact of the project? What is the project’ s baseline?
  • Upscaling: Is upscaling relevant for this project? What type of upscaling is applicable? What is necessary for successful upscaling after the project ends?