The City of Helsinki Data Strategy

The City of Helsinki’s Management Group approved the objectives and policies of the City’s Digitalisation Programme in March 2019. The programme describes how the City Strategy’s vision of Helsinki becoming the most functional city in the world that makes the best use of digitalisation will be achieved through digitalisation. One of the key objectives of the Digitalisation Programme is to develop the City’s data, artificial intelligence and robotisation capabilities with the aim of facilitating the creation of a city that proactively responds to its residents’ service needs on their terms. Data is the key to of all of the strategic objectives of the Digitalisation Programme (see Figure 1). The digital leap is only possible with the efficient utilisation of data and artificial intelligence.

Figure 1. The City Strategy’s vision and the strategic objectives of the digitalisation programme based thereon

Figure 1. The City Strategy’s vision and the strategic objectives of the digitalisation programme based thereon

The aim of the data strategy is to bring about the following four changes and benefits:

1. Data is utilised to create a city that proactively responds to residents’ service needs on their terms

Helsinki exists for its residents. The City should always strive to provide better service to its residents. In this context, better service means offering residents individual, targeted and proactive services when they are needed. This type of proactive targeting of services requires the widespread employment of analytical methods. Furthermore, people should be able to personally determine how their data is utilised in accordance with MyData principles.

2. Data-driven decision-making

To ensure smooth, high-quality and efficient operations, the City must also expand and speed up the utilisation of knowledge refined from data in its operational management. Data on the City’s operations, residents and development is constantly being generated at various levels. There are already various types of reports, statistics and studies that refine raw data into research-based knowledge about various subject matters that can be utilised by decision-makers. However, at present the City lacks the capacity to make full use of the potential offered by modern data lakes, data warehouses and analytical methods in its decision-making and operative activities. For example, the creation of a digital twin model of the city would enable the City’s operations to be examined and simulated from various perspectives.

3. The City’s operations and resources are optimised with the help of data

Access to up-to-date data coupled with advanced analytics, such as machine leaning, dynamic optimisation and predictive models, also makes it possible to optimise and steer the operations and resources of City employees for the purpose of improving efficiency and generating cost savings. Robotic process automation and data make it possible to automate and seamlessly align internal processes. The difference compared to the previous objective of data-driven decision making is that here the aim is to optimise resources automatically with the help of data and algorithms.

4. The sharing of data drives business and the utilisation of external resources

In addition to being utilised internally, the data managed by the City should be shared and made available to the partners in the external ecosystem, such as communities, universities and businesses. This will allow external operators to carry out research and develop services that the City’s own operations and services do not cover.

To promote these changes, the data strategy establishes the following data vision:

The data generated by Helsinki is the most usable and used city data in the world by 2025

The City possesses great potential when it comes to improving the utilisation of data. In terms of the efficient shared use of data, there is a great deal of development potential in the City’s information systems and the ways in which its master data is managed. At present, the sharing and aggregation of data between the City’s divisions, municipally owned companies and group companies is very low, considering how many potential opportunities there are for doing so. This is in part due to the City’s operating culture and partly due to a lack of shared guidelines for promoting cooperation within the City. Furthermore, a large portion of the City’s data consists of personal data, making it difficult to assess the legal basis for its utilisation.

We hereby outline the following nine principles:

I. The City has the right to use all of the data that its operations and services generate.

II. The City’s shared master data, such as client data, is only recorded once.

III. All data is accessible via APIs and in machine-readable format.

IV. All data can be utilised internally within the City across division boundaries and by municipally owned companies, unless restricted by legislation.

V. The City utilises external data and shares its own data as openly as possible to promote the vitality of the city ecosystem.

VI. The lawful and ethical utilisation and sharing of data is facilitated and ensured though the processing of precedents.

VII. The City’s shared data and analytics platforms support and speed up the independent service provision of the City’s divisions.

VIII. Data and analytics capabilities are developed based on the needs of the City’s divisions and concrete use cases.

IX. In accordance with MyData principles, clients can determine how the data collected about them is utilised.

Initial measures (the principles that the measure promotes are listed in parentheses):

1. The assembly and procurement of data and analytics platforms that will be used for various purposes throughout the City, providing tools for the aggregation of different types of data and the comprehensive utilisation of advanced analytics, including: (IV, V, VII)

  • data lake and analytics platform, API management
  • data warehouse, reporting and desktop solutions for management
  • 3D city model for visualisation, analysis and simulation.

2. The establishment of necessary cross-divisional working groups, which will monitor of the implementation of the Data Strategy and clarify measures:

  • data utilisation working group: the development of shared data policies and a case database related to the utilisation of data based on data protection and other relevant legislation (IV, VI)
  • data governance working group: promotes the quality and interoperability of data and the management of master data at both the City and data area level (II)
  • together, these working groups maintain the City’s shared data classification model.

3. Providing city residents with the services to transparently monitor and manage the processing of their personal data: (IX)

  • a Helsinki profile and consent management in accordance with MyData principles
  • an algorithm register that describes the logic and ethical principles of algorithms.

4. The incorporation of the following provisions into the procurement contracts for information systems and services:

  • the City has the right to use the data that it generates and procures (I)
  • any utilised or developed algorithms comply with ethical principles (VI)
  • the system to be procured or developed is always accessible via an API (III, IV, V).

5. The City’s data and analytics capabilities will be developed through the establishment of a data and analytics team under the City Executive Office’s Strategies Division, which will be tasked with supporting the City organisation in the accomplishment of the data vision (VII, VIII)

  • recruiting of internal data scientists and engineers through the establishment of new vacancies
  • supporting the team with the help of external consultants, if necessary
  • training the City’s existing personnel in the area of data and analytics.

The aforementioned objectives, principles and measures are described in greater detail in the rest of this document. Since the digital operating environment relevant to the data strategy is constantly changing, the detailed descriptions will be constantly updated and are thus excluded from the decision itself.