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The use of data and artificial intelligence (AI) makes it possible to create new ways of working in both the private and public sectors. New ways of using of data not only create a competitive business advantage but also play a key role in promoting social development and sustainability.
Various sectors must consider how data can be used in value creation to benefit individuals, communities and society as a whole.
Sitra has long been involved in efforts to build a human-centred and fair data economy based on European values. Our goal has been to foster a culture in which data is used to develop better services while ensuring people have the ability to influence how data collected about them is used. This ultimately benefits both communities and society.
Innovations that aim to make an impact require effective and responsible ways to share and use data across silos. Partnerships between the public, private and third sectors play an essential role in building a fairer data economy.
Creating change through collaboration
Innovation and efforts to bring social changes require collaboration between the private, public and third sectors. By combining the public sector’s societal insights and ability to influence structures with the private sector’s agility and technological expertise, we can create more sustainable and efficient solutions to societal challenges.
At the same time, the third sector’s and researchers’ in-depth expertise in the topics at hand enriches public discussion and decision-making. Such synergistic collaboration can foster sustainable economic growth, improve people’s well-being and enhance social cohesion.
Three lessons from the Sitra Lab change programme on the opportunities of using data in service development
In the Sitra Lab change programme, which began in spring 2024, eight pilot teams explored new ways of using data to develop services and data solutions. The programme concluded in September 2024.
The pilots provided three key lessons for data-driven development:
1. Data is a strategic asset
Data is a valuable resource, and its importance increases when it is skilfully combined and enriched from various sources. With data, we can make high-quality and fact-based decisions. To support this, we need new data solutions that help different actors succeed at various stages of the value chain.
It is important to understand how data can be used in new ways to create value across sectors and among different actors.
For the private sector, data is particularly beneficial in creating new business opportunities, strengthening the competitive advantage and deepening customer understanding. Data can also be used to optimise resource use and automate processes, leading to significant cost savings.
In the public and third sectors, data use supports effective decision-making. Data-driven decision-making enhances the effectiveness of services and allocates resources more efficiently. It also helps anticipate people’s needs and increases the transparency of operations.
High-quality data-driven leadership fosters trust among citizens and partners and promotes societal well-being and environmental responsibility.
2. Effective data solutions are built together
The change programme’s pilots developed service solutions in which the use of data creates conditions for new business models and ecosystems of complementary actors. The pilots demonstrated that sharing data and expertise can generate significant economic and societal value.
However, collective value creation does not occur solely by sharing data; it also requires the ability to analyse and refine it responsibly together. Furthermore, it is important to develop practices that encourage actors to commit to common goals and participate in implementing solutions. This calls for openness and the strengthening of trust among actors.
When ecosystems are built in this way, they create sustainable value and impact across sectors and silos.
3. Data creates opportunities that lead towards a more sustainable society
The needs and opportunities for data use must be explored more broadly than before. Value chain analysis should extend to the stages in which target groups and customers use new data-driven services in their daily lives. For companies and organisations, this means looking further ahead when designing services, considering the needs of their customers and even those of their customers’ clients.
Value creation is based on how successfully we can guide change towards fair, transparent and human-centred service models with data. We need holistic thinking that considers both people and the environment and helps develop sustainable, inclusive and accessible solutions.
Through close collaboration between the public, private and third sectors, we can create a society in which data not only generates economic value but also builds a fairer and more humane world.
Sitra Lab pilots
Outreach work for older people provides solutions to the challenges of an ageing society
What challenge did the pilot address?
Population ageing and the strain on public finances challenge us as a society. Preventive measures are being cut, while intensive services consume scarce resources. From the perspective of wellbeing services counties and older people, there is a risk that we will not have enough resources to ensure a dignified old age.
Outreach work for older people supports the well-being of those at risk of being left outside the services provided by society. By identifying and supporting these individuals, it is possible to help them live as independently as possible in their own environments and avoid premature reliance on more intensive services.
What was the solution?
The goal of the pilot was to build a data solution that supports outreach work for older people, making the need, benefits and impact of such work more visible.
The pilot mapped existing monitoring and reporting practices and examined the need for and impact of outreach work for older people. It also investigated what type of information about the situation of older people could support decision-making.
The next phase of the project will focus on collecting data on the effects of various phenomena and developing metrics to evaluate the impact of outreach work for older people, as well as its economic and well-being impacts.
Challenges such as elderly individuals living alone, a lack of social support, loneliness, exclusion and the weakened capacity of the service system to meet the needs of an ageing population make assistance difficult. Many older people do not receive sufficient support due to factors such as mental health issues, declining physical ability or social isolation.
The absence of preventive work shifts the focus to intensive services, increasing care and subsequent costs. Collected data concretely shows how outreach work for older people saves resources and improves their quality of life.
What was learned?
We need solutions that enable a dignified old age while saving societal resources. The development of a data solution supports both practical operations and decision-making, representing a step towards more systematic and effective outreach work for older people. The benefits extend to all stakeholders: older people, the service ecosystem consisting of multiple actors, decision-makers and society as a whole.
The greatest lesson from the pilot was recognising the critical role of organisations as part of a broader ecosystem that enables and supports outreach work for older people.
With the help of the data solution, we can convince decision-makers of the value of this work and ensure that a dignified old age is secured in the future as well.
Who were involved in the pilot?
Päivi Tiittula, VALLI Union for Senior Services
Helena Norokallio, Turku Senior Services Association (Turun Lähimmäispalveluyhdistys)
Sanna Jokinen, Fingerroos Foundation
Kaisa Nyberg, Living Skills
Henna Grönberg, MEREO
More information
Päivi Tiittula, VALLI
Data as a tool to prevent youth exclusion
What challenge did the pilot address?
Youth unemployment and mental health challenges are on the rise, and many young people drop out of their education. Outreach youth work and youth workshops respond to these challenges related to youth exclusion.
Outreach youth work helps young people address challenges and guides them towards services and education. Workshops, on the other hand, offer practical work tasks and coaching that strengthen young people’s life skills and support them in their studies and entry into working life. Outreach youth work and youth workshops are often the only low-threshold services available as local support for young people in vulnerable situations. Cuts to these services could endanger the support provided to thousands of young people.
A significant amount of data has been collected on outreach youth work and youth workshops, produced by the Regional State Administrative Agency and Into – Association for Outreach Youth Work and Workshop Activities. The Regional State Administrative Agency’s quantitative data is compiled and visualised annually on the nuorisotilastot.fi statistics website, but the resources for analysing qualitative data have been limited.
The pilot aimed to strengthen the use of data in decision-making and service development. Services that respond to young people’s needs benefit society as a whole by enhancing youth participation and preventing exclusion.
What was the solution?
The pilot implemented an AI-based analysis tool that allows the processing of large amounts of data more efficiently. The Regional State Administrative Agency collects nationwide data on outreach youth work and workshop activities through client information systems and surveys. Into maintains the Sovari indicator, which measures the social impacts of services on young people. With AI, open-ended survey responses can be analysed more accurately to produce clear reports and visual presentations.
The challenges and successes experienced in outreach youth work and youth workshops in 2023 were visualised at a regional level on the nuorisotilastot.fi website. This makes the collected survey data more widely available and usable, providing decision-makers with accurate information about the impact and challenges of services. This promotes data-driven decision-making.
The pilot increases the visibility of outreach youth work and youth workshops and supports the allocation of sufficient resources. The goal is for young people to receive timely support, which reduces exclusion and enhances their well-being.
What was learned?
The pilot results improve the quality of decision-making and ensure that resources are allocated efficiently where they are most needed. The pilot received expert support in the use of AI and text analysis. AI tools have been integrated into everyday work, and their use will continue in collaboration.
The AI tool deepens understanding of the processes in youth workshops and outreach youth work. The text comprehension of the AI used has been developed to a level at which categorisations and summaries of responses can be produced with reasonable effort. However, the AI does not yet enable research-level or automated analysis.
The AI itself cannot perceive complex, underlying cause-and-effect relationships contributing to youth exclusion. However, by training and developing AI tools, it is possible to use them for analysing large data sets, thus enhancing the use of collected data, nationwide surveys and Sovari responses. Human input is still required before publication.
Read more about the topic in Into’s blog.
Who were involved in the pilot?
Riitta Kinnunen, Into – Association for Outreach Youth Work and Workshop Activities
Tarja-Liisa Riipinen, Into – Association for Outreach Youth Work and Workshop Activities (currently the Hoksaamo services)
Arto Manninen, Regional State Administrative Agency for Western and Inland Finland
Ruth Bamming, Regional State Administrative Agency for Western and Inland Finland
More information
Riitta Kinnunen, Into – Association for Outreach Youth Work and Workshop Activities
Home life-cycle data: Organising building information
What challenge did the pilot address?
Everyone lives somewhere, and every home is owned by someone. A home is often a person’s most significant asset. Over time, houses also undergo renovations. The better maintained apartments and housing companies are, the better they retain their value, ensure healthy living conditions and improve energy efficiency.
Currently, no single entity compiles life-cycle data related to buildings and property maintenance. New regulations are continuously emerging in this field. Ensuring compatibility between data from various sources requires a unified definition of the data.
The EU mandates that building owners must be in possession of information related to the maintenance of their property. At present, this data is often fragmented and difficult for the average resident to comprehend. The collection and refinement of this information would also encourage service providers in the housing sector to develop new business models, such as those accelerating the circular economy.
What was the solution?
The pilot aimed to create a method for incorporating renovation data into property information in an understandable way so that various stakeholders can use the information for their purposes.
A simulated window renovation was conducted during the pilot. The process of a housing company’s window renovation was examined, identifying the parties involved in the renovation, and how information was managed during the process. The parties involved, i.e. operators with expertise in housing, property management and housing company renovations, were interviewed. The goal was to determine what information exists in different data systems, and whether it can be automatically made accessible to residents and housing companies.
The pilot used existing tools as well as a traceability pilot from the Real-Time Economy project. The window renovation data was transferred through related e-invoices to the housing company’s electronic maintenance log. The solution is scalable to other housing-related topics and applicable to other industries. The solution can be found as a demo version on the MiniSuomi platform, which facilitates agile and flexible experimentation in public administration development projects.
What was learned?
The pilot found that housing and construction involve processes and services such as zoning and permits, material flows and logistics, emissions and product life cycles, financing and insurance, taxation and building supervision, real estate transactions and maintenance company services. For this reason, the development of data-driven services in housing and construction involves multiple perspectives that benefit from collaborative refinement.
As a follow-up, we gathered stakeholders at the end of 2024 to discuss the establishment of a targeted ecosystem or collaborative network. This will also provide an opportunity to outline a data space for construction information, in which each data user can access their portion according to agreed usage rules. Enhancing the use of construction data can create competitive advantages for companies and accelerate sustainable growth in Finland.
Who were involved in the pilot?
Johanna Kotipelto, Tax Administration
Jukka Kyhäräinen, Tax Administration
Tiina Lokka-Lepistö, National Land Survey of Finland
More information
Johanna Kotipelto, Tax Administration
Fact designers: Fact-checking for the building information system
What challenge did the pilot address?
The building and property register data of Finnish municipalities have significant deficiencies. The information held by various authorities differs from one another. Incomplete data cause substantial tax revenue losses for municipalities and can lead to the unfair taxation of residents.
What was the solution?
A new national building information system is being developed in Finland, to which data will be transferred from municipal registers. For the pilot to succeed, it was crucial that the data was accurate to ensure the building information system would function as effectively as possible.
To address deficiencies and inaccuracies in the data concerning the built environment, the solution was to use national open aerial imagery and map data for automated comparison. These resources helped locate buildings missing from the register and verify the accuracy of existing information.
What was learned?
The pilot used data that had not previously been used in this manner for such a purpose.
The most significant challenge lay in the limited resources of municipalities. This type of work has not been previously undertaken because it has been considered too laborious compared to the benefits gained.
However, those municipalities that have conducted similar work manually have achieved significant benefits. The future goal is to resolve the problems with building and property register data efficiently through collaboration and automation with partners.
Read more about the topic on the CGI website.
Who were involved?
Jouni Ojala, CGI
Henna Helminen, CGI
Matias Artman, CGI
Julia Järvelä, CGI
Sanna Partanen, CGI
More information
Jouni Ojala, CGI
Digital assistant for families to support children’s learning and skill development
What challenge did the pilot address?
Parents find it challenging to monitor, manage and use information related to their child’s learning and skills. This information is often fragmented and difficult to use, even though it could be valuable when choosing a place of study, changing schools or planning support services for learning.
What was the solution?
The pilot developed a digital service called TIPU, designed to help families monitor and use information related to their child’s learning and skills. TIPU functions as a ‘data wallet’ controlled by the family and integrates information related to the child’s education, hobbies and learning.
Through the service, families can securely share relevant information with those involved in the child’s development, such as teachers and other important adults. Once the child reaches adulthood, TIPU provides a comprehensive and cohesive record of their learning path. This can help the young adult transition smoothly and confidently into adulthood.
TIPU aims to be an easy-to-use tool for families to support lifelong learning. The service uses secure AI and gamification to provide insights that foster learning, self-confidence and a positive attitude towards learning. TIPU assists in practical situations such as applying for summer jobs, creating study plans and making career choices, supporting the shared growth path of the child and family.
What was learned?
The pilot involved the development and testing of user interface prototypes, secure data architecture models, cognitive AI experiments and business ecosystem strategies. It highlighted both the potential and challenges of family-centric solutions.
Key areas for further development include data architecture and privacy management, defining the minimum viable product (MVP), pricing model development and consideration of children’s rights. Moving forward, the focus will be on assessing the social impact of the concept (SROI) and developing the service based on user feedback.
Who were involved?
Paula Bello, Paula Bello Consulting
Anu Passi-Rauste, Headai
Harri Ketamo, Headai
Tiina Norton
Teemu Ropponen, MyData Global
More information
Paula Bello, Paula Bello Consulting
TIPU: Empowering Families with Data – Inspired by Sitra Lab 6 – Headai
Sports Data Hub: Developing a national sports data repository for physical activity and sports data
What challenge did the pilot address?
Finnish sports data, particularly data related to coaching, is fragmented and inconsistent. A significant amount of information is collected in various smart devices and data systems, including smartwatches commonly used by people who do physical exercise and sports, as well as training and testing software.
The goal of the Sports Data Hub is to develop a national operating model and data system to better use physical activity and sports data.
What was the solution?
The solution compiles data from different sources into a single service that supports competitive sports. In competitive sports, maintaining the right balance between training load and recovery is crucial. With the data provided by the service, coaches and athletes can monitor the situation daily and make informed decisions to enhance performance and maintain health.
More generally, these challenges also apply to physical exercise and sports among the public, although the requirements differ from those of competitive sports. If the service can be developed to meet the needs of athletes, it could also be adapted for broader use.
The wider aim is to help Finns adopt and sustain an active lifestyle throughout their lives.
The service is being piloted in Olympic Training Centers, where 300 athletes and coaches are using it as a daily tool. The service’s functions and use are being expanded and further developed with a user-centric approach.
What was learned?
Defining users’ data needs and obtaining user feedback are critical for the solution. Through user testing, immediate feedback and insights into the service’s effectiveness were gathered.
To support the justification of data needs, the Sports Technology Unit at the University of Jyväskylä also conducted a scientific review of the monitoring of training, performance and recovery. This review is being used in the further development of the service’s content.
Who were involved in the pilot?
Juha Saapunki, Finnish Olympic Committee
Topias Koukkula, Finnish Olympic Committee
Juho Kurki, Finnish Institute of High Performance Sport KIHU
Petra Torvinen, University of Jyväskylä
Pietari Outinen, Urhea/National Olympic Training Center Helsinki
More information
Juha Saapunki, Finnish Olympic Committee
From a regional pilot in South Ostrobothnia towards a nationwide employment services ecosystem
What challenge did the pilot address?
Employment services and learning environments are undergoing a significant transformation. Current systems, often organisation-centric, do not sufficiently support individuals in managing their own skills and knowledge but primarily focus on their core tasks. This leaves many clients such as unemployed people and students overlooked: they become frustrated when unable to progress according to their own goals.
The pilot tackled this challenge by focusing on the use of people’s own data to support employment and on developing organisational processes within a human-centred service ecosystem or collaborative networks.
What was the solution?
The pilot developed a regional data network and service ecosystem that allows jobseekers and students to manage and grant access to their own data. The model was based on cross-organisational collaboration, placing people at the centre. The pilot demonstrated how the use of people’s own data can streamline and enhance employment and learning service networks, i.e. ecosystems.
What was learned?
Adopting new ways of working begins with changes in attitudes and mindsets and progresses to concrete organisational processes and practices. A true systemic change requires commitment and courage in addition to technology and data. The pilot led not only to technical and process innovations but also to a deep understanding of the roles of different actors, overlaps and the functioning of a human-centred service ecosystem.
When services are based on human-centric data management, the service ecosystem emphasises interactions rather than information retrieval. In such an environment, ethical, power-related and legal questions are essential.
The challenge was not so much the movement of data or technical compatibility, but how actors can best support individuals’ progress. The regional lessons learned from the pilot serve as a model for other employment areas, in which everyday challenges often hinder long-term development work.
This pilot opens new opportunities, and its lessons will be scaled for other regions to use in the Kohtaantotalkoot campaign. If you want to contribute to advancing a human-centred service ecosystem, join us and make use of the successful pilot’s results in your own region!
Who were involved in the pilot?
Petri Tuomela, Vastuu Group
Mikko Sierla, Vastuu Group
Ilkka Rintala, City of Seinäjoki
Aki Ruotsala, TE Office of South Ostrobothnia
Anu Portti, Into Seinäjoki
Marja-Terttu Kurunsaari, Seinäjoki Education Consortium Sedu.
More information
Petri Tuomela, Vastuu Group
AI-driven assistance for job seeking
What challenge did the pilot address?
Job seeking is undergoing a transformation, and reducing unemployment is a significant societal and often personal challenge. Many jobseekers face the question of how to find work that matches their skills and aspirations.
The pilot developed a client-focused solution that aims to tackle these challenges and improve jobseekers’ chances of finding positions that suit them.
What was the solution?
Recent legislative changes have paved the way for broader collaboration in supporting employment. Unemployment funds can now actively participate in promoting employment.
This pilot combined the process of applying for earnings-related unemployment allowance, artificial intelligence and job advertisements into a unique service that helps jobseekers efficiently discover new opportunities.
Jobseekers, who typically visit the service around four times a month, can now search for jobs listed in multiple sources in one unified search. The AI scans job advertisements and suggests suitable positions to jobseekers that they might otherwise miss.
What was learned?
The pilot demonstrated that the solution works well. Jobseekers were asked to describe their skills, and the AI was able to quickly and accurately suggest suitable job positions.
High-quality data was crucial for success, making it essential to assist jobseekers in describing their skills accurately and relevantly.
One of the major challenges in the job market is aligning the needs of jobseekers and employers. This solution not only speeds up the job-seeking process but significantly reduces the friction in matching jobseekers with employers.
The solution benefits both individuals and the job market as a whole, creating new dynamics in the job market and a potential for making job seeking smoother and more human-oriented for everyone involved.
Who were involved?
Auli Hänninen, YTK Unemployment Fund
Petja Eklund, YTK Unemployment Fund
Ilona Kangas, YTK Unemployment Fund
More information
Ilona Kangas, YTK Unemployment Fund
How to gain a competitive advantage from data? Discover lessons from digital transformation and apply them
Are you interested in learning how to use data more effectively for organisational development, or considering your organisation’s data strategy as part of your work?
At the closing event of the Sitra Lab change programme, Professor of Strategy and Digital Transformation Mohan Subramaniam provided valuable insights into these questions.
The various data strategies presented by Subramaniam offer every organisation – whether in the public or private sector – powerful methods to harness data and create new value.
Subramaniam proposed four data strategies:
- Enhancing efficiency through internal data. Data can be used to optimise operations and resource use, enabling significant improvements in productivity.
- Using customer data to improve services. With customer understanding, organisations can develop solutions that better meet and target customer needs.
- Creating shared value through customer data. Customer data can be used to generate new services such as subscription-based solutions or smart technology-based additional services that provide additional value to customers.
- Collaborating in ecosystems and with third parties. By integrating data into multi-stakeholder ecosystems, organisations can develop entirely new service and revenue models.
These strategies enable organisations to strengthen their competitiveness, engage in more agile innovation and create value in a sustainable and customer-centred way.
If you wish to deepen your understanding of the topic, watch Subramaniam’s complete keynote speech.
