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The lean and efficient use of raw materials, energy and products is a key principle in the circular economy. As a hypothesis, our activities and industrial operations can only be designed as circular in a holistic way if we share information across the value chain and between the stakeholders. In the Circular Design Network project (2020–2022), funded by the Academy of Finland, we have focused on understanding the opportunities and pathways to data-enabled circular operations, and on creating a network in data for circular design. This report analyses the findings and summarises the results of the stakeholder interviews (WP 1) mainly during 2020. The stakeholder interviews consisted of 81 company, R&D and regional support organisation interviews mainly in the value chains of batteries, textiles and food-carbon cycles, with a few interviews in the pulp and paper and chemical industries. We interviewed the stakeholders on their roles in the value chain, their data-related challenges and needs in circular practices, the role and data use in their current operations, the data tools, collaboration and activities around data, and the opportunities they saw in data for a circular economy. The findings were analysed per value chain and according to their position in the value chain: raw material suppliers, product manufacturers/solution providers, end users, etc. The role of the circular economy principles, as well as use of data, varies greatly depending on the business model and sector of industry. In general, all the interviewed organisations collect and use data for operations and customer management as a standard practice; but at the same time, most would like to better utilise data, also for circularity. Large manufacturing organisations have the means to invest in developing new data-based opportunities, and some have taken steps forward and are developing data platforms internally or with an external partner. On the other hand, some smaller innovative and data-oriented organisations design and implement new data-based approaches in an agile way. Data platform providers can play an important role in enabling organised data sharing and internal use. Overall, almost all of the interviewees had an interest in specifically expanding customer data collection and utilisation and to create new business models based on that. Traceability of materials through the value chain is a key driver and opportunity for data management. In particular, the stakeholders saw a growing need for localised and transparent LCA and sustainability data. Open data or data sharing at the general level was also regarded as interesting. However, the concrete data opportunities are still for the most part hazy, and few stakeholders are willing to share their own data unless there is a valid business reason and the means to control the use of the data. We deduct that in order to create a living data ecosystem, an initiator and driver, with a vision of a data-based (business) operation, is needed. We noted that the boundaries of the different roles in the value chain are blurred in a circular economy. New circular business models seek the value in combining, for example, circular products manufacturing to waste management, or end-of-life recycling service to retail or manufacturing. Connecting data to operations requires cross-disciplinary competences. In a circular economy, the roles are expanding and combining in innovative ways, which may shake up the traditional practices and collaboration in the value chains. New combinations of competencies may be needed. The changes may also cause some need for readjustments at the regulatory and public policies levels, such as end-of-waste processes or GDPR practices.

This report presents the both the development steps for agile cognitive industry and the dimensions of the maturity model that were developed for the implementation of ManuMaturity tool. The ManuMaturity tool was implemented to help manufacturing companies to proceed in digitalisation and to reach Industry 4.0 level or even beyond it. The maturity model has three sectors (Business, Technology and Responsibility) and seven dimensions: Customer, Business model, Processes, Data, Infrastructure, Employee, and Sustainability. With the implemented ManuMaturity self-assessment web tool, a company can discover its own maturity level in addition to strengths and weaknesses with regard to the seven dimensions. The questions and answer alternatives have been formulated to make it possible for the company representatives to complete it independently within 15-20 minutes. The web tool immediately displays the result graph based on the selections of respondent together with the average of all respondents.The ManuMaturity web tool is available at https://manumaturity.vtt.fi/ for self-assessment of companies. It is free for any non-commercial use.

Fashion industry is the second largest polluter in the world. To tackle the environmental crisis globally, we must minimize the environmental impact of fashion industry. The extension of garment lifetimes leading into smaller number of garments produced and sold has been identified essential towards sustainable fashion. This requires novel business models substituting volume-based fashion business. The purpose of this study is to investigate, how data can be used to promote the reuse of clothing and sustainable fashion. The first result is a state-of-the-art review focusing on clothing reuse. An integrative literature review method was used to examine the consumer challenges, current services and technologies. Previous research has identified challenges on reuse of different products as well as usage of consumer-to-consumer marketplaces to be on selling and buying experience, trust on the marketplace as well as quality of the product, and difficulties in finding the required size and style. The review provides a logical starting point for the second result, which is a multifaceted description of the Clothing Circulator concept. The concept presents a novel data-driven solution for extending the garment lifetimes and it was created as a multidisciplinary collaboration between fashion, consumer, service and technology researchers during a series of 7 workshops. Holistic, transparent view on the garment lifecycle from design to material recycling is the essence of the concept, which describes stakeholders and their roles, data sources in different phases through the garment’s lifecycle, key enabling technologies and consumer aspects that are relevant for the clothing circulator solution. The consumer gets tools to curate wardrobe with a stylish and sustainable selection of garments. It helps in reselling the underused items and estimates the value of the underused garments based on big data from the marketplaces. For the brands the concept provides data on usage of the garments: how often the items are used, how long the items are kept as part of the wardrobe, what kind of combinations are created with the brand items, what type of customers seem to like/dislike the items, what is the resale value of the items and finally, how the items are recycled in the end of the lifecycle. Based on these insights, the brands can base the design choices on measured data, which optimally leads to diminished waste of unsold items as the design and production would meet better the consumer expectations. This research is a first step towards data-driven approach to support reuse of garments, and hence extending garment lifetimes and more sustainable fashion. In the sustainable fashion research, the data-driven solutions to support reuse or decision-making in the design and production phases have not been extensively studied, even if sustainable consumption is a rising trend among “early adopter” consumers, especially in younger age groups. In the future, the research community should study the topic from a multidisciplinary perspective involving e.g. consumer, technology, data and business research together with the industry, targeting at the development of successful data-intensive solutions to support sustainable fashion.

Fashion industry is the second largest polluter in the world. To tackle the environmental crisis globally, we must minimize the environmental impact of fashion industry. The extension of garment lifetimes leading into smaller number of garments produced and sold has been identified essential towards sustainable fashion. This requires novel business models substituting volume-based fashion business. The purpose of this study is to investigate, how data can be used to promote the reuse of clothing and sustainable fashion. The first result is a state-of-the-art review focusing on clothing reuse. An integrative literature review method was used to examine the consumer challenges, current services and technologies. Previous research has identified challenges on reuse of different products as well as usage of consumer-to-consumer marketplaces to be on selling and buying experience, trust on the marketplace as well as quality of the product, and difficulties in finding the required size and style. The review provides a logical starting point for the second result, which is a multifaceted description of the Clothing Circulator concept. The concept presents a novel data-driven solution for extending the garment lifetimes and it was created as a multidisciplinary collaboration between fashion, consumer, service and technology researchers during a series of 7 workshops. Holistic, transparent view on the garment lifecycle from design to material recycling is the essence of the concept, which describes stakeholders and their roles, data sources in different phases through the garment’s lifecycle, key enabling technologies and consumer aspects that are relevant for the clothing circulator solution. The consumer gets tools to curate wardrobe with a stylish and sustainable selection of garments. It helps in reselling the underused items and estimates the value of the underused garments based on big data from the marketplaces. For the brands the concept provides data on usage of the garments: how often the items are used, how long the items are kept as part of the wardrobe, what kind of combinations are created with the brand items, what type of customers seem to like/dislike the items, what is the resale value of the items and finally, how the items are recycled in the end of the lifecycle. Based on these insights, the brands can base the design choices on measured data, which optimally leads to diminished waste of unsold items as the design and production would meet better the consumer expectations. This research is a first step towards data-driven approach to support reuse of garments, and hence extending garment lifetimes and more sustainable fashion. In the sustainable fashion research, the data-driven solutions to support reuse or decision-making in the design and production phases have not been extensivelystudied, even if sustainable consumption is a rising trend among “early adopter”consumers, especially in younger age groups. In the future, the research community should study the topic from a multidisciplinary perspective involving e.g. consumer, technology, data and business research together with the industry, targeting at the development of successful data-intensive solutions to support sustainable fashion.

The healthcare and wellness sector currently attempts to provide more proactive service models with data-driven solutions. This study examines the expectations and values related to personal data i.e. data valences from the perspective of service providers and individual users. The study is based on the analysis of extensive empirical material collected through interviews and a collaborative workshop. The data was collected in one cultural context, Finland. The results suggest that the potential service providers and users have similar expectations regarding self-evidence of data while the main differences concern the expectations of transparency. The results of the study propose some basic requirements for the development of personalised data-driven services in future. The study suggests that basic requirements for the development of future data driven services concern expectations to usable data visualisations, data as a motivator, data accuracy and data transparency. Even though there are varying expectations to personal health data and even some concerns, it can be seen that here different ecosystem actors primarily perceived the wider use of personal health and wellness data as a positive trend. It can be concluded that collaborative personal data-driven service ecosystems are an integral part of development towards proactive service models in healthcare.

This study explores how heterogeneous types of data, e.g., personal data, big data, public data, statistical data, third sector data as well as social media, jointly referred to as 'rich data', are currently being utilised in healthcare policy making, and what kind of implications data has on future decision-making. Conducted as a qualitative case study with municipal decision-makers in Finland, this study examines the use of data in the context of preventive mental healthcare services, and highlights mental issues as a complex, systemic kind with far reaching long term impact, where the needs ands requirements for right kinds of data extend beyond healthcare domain. Making rich data available for policy decisions is only one preliminary step in the road to data-driven policy decisions. Data analysis and visualisation are essential elements in making data usable for decision-makers in order to improve the health and wellbeing of the society.

Tämän tutkimuksen lähtökohtana on väestön ikääntyminen yhteiskunnassa. Lähtöoletuksena on, että uusiin teknologioihin perustuvilla sovelluksilla voidaan tukea ikääntyneiden itsenäistä selviytymistä ja parantaa heidän elämänlaatuaan. Tutkimuksen ensisijaisena tavoitteena on ollut selvittää matkapuhelimella koskettamiseen perustuvan käyttöliittymän ja siihen liittyvän interaktiotekniikan soveltuvuutta ikääntyneille ateriapalvelun asiakkaille. Tutkimus keskittyy tarkastelemaan myös kenttäkokeessa käytetyn ateriapalvelun hyväksyttävyyttä ikääntyneiden ateriapalvelusasiakkaiden joukossa. Tutkimus perustuu kirjallisuuskatsaukseen ja kenttäkokeeseen, jossa ikääntyneet ateriapalvelun asiakkaat käyttivät matkapuhelimella koskettamiseen perustuvaa ateriapalvelua valitessaan päivittäisen ateriansa. Kenttäkokeessa tiedonkeruumenetelminä käytettiin haastattelua, havainnointia ja päiväkirjaa. Kenttäkokeen avulla kerättiin ikääntyneiden käyttäjien käyttäjäkokemuksia heidän käyttäessään uutta ateriapalvelua. Ikääntyneet ateriapalvelun asiakkaat omaksuivat koskettamiseen perustuvan käyttöliittymän käytön helposti saatuaan lyhyen koulutuksen sen käyttöön. Kaikki ikääntyneet eivät kuitenkaan kokeneet uutta palvelua itselleen tarpeelliseksi. Vaikka tutkimukseen osallistunut ikääntyneiden joukko edustaa ikäjakaumaltaan laajasti eriikäisiä ikääntyneitä henkilöitä, tapaustutkimuksellisen luonteen vuoksi tutkimus ei tee laajoja yleistyksiä. Tutkimus antaa uutta tietoa koskettamiseen perustuvan interaktiotekniikan soveltuvuudesta ikääntyneille henkilöille, jotka tarvitsevat tukipalveluja elämänlaatunsa parantamiseksi.