3| Socio-technical Systems in the Digital Age

Proceedings of RSD7, Relating Systems Thinking and Design 7
Politecnico di Torino, Turin, Italy  23th-26th October 2018

Section content 

Das B., Nahar P.
Circular Economic Service System Design for Community Based Flood Resilience. Designing a collaborative grain storage and service system for the annually flood prone communities of Assam, India

Fiore E.
New strategies for the refrigerator in the transition towards a circular economy

Germak C., Giuliano L., Abbate L.
Co-design processes for cleaning and facilities services system

Lomas J., Patel N., Forlizzi J.
Continuous Improvement: How systems design can benefit the data-driven design community

Tamborrini P., Remondino C., Marino C.
Data, Fashion System and Systemic Design approach: an information flow strategy to enhance sustainability

Valpreda F., Cataffo M.
Participatory Design for Service Robotics

Circular Economic Service System Design for Community Based Flood Resilience. Integrating Systems Design and Behavioral Science to Address a Public Sector Challenge from Within. Designing a Collaborative Grain Storage and Service System for the Annually Flood Prone Communities of Assam, India

Das Bhaskarjyoti, Nahar Praveen
National Institute of Design Ahmedabad, India

System Design
Service Design
Social Entrepreneurship
Social Innovation
Design Democracy
Design for Well-Being
Design for Circular Economy

The role of a designer is gradually being believed to be that of a social scientist and a leader who designs or facilitates innovation of newer ecosystems of products, services and systems; developing social capital along with resource effectiveness and economical benefits. The social and environmental imperatives have compelled designers to look beyond satisfying human desires, from merely creating problem-solving products towards focussing equally or more on generating overall well-being in the society — both individual and societal, and thus engender meaningful interactions of users with their surrounding environment through corresponding product-service-systems. As Professor MP Ranjan, a notable design educator blogs, “…(design offerings) are synthesized and developed in such a way that they vibe with the context and add value to the social, geographic and historical situation that is being addressed.”

In current times, emerging world issues like climatic aberration, exponential increase in population, heavy product consumption, it’s post-usage waste generation and poor resource management have been gradually leading to chronic problems of sustainability, such that the vision of a plausible tomorrow questions the mere existence of humans and the symbiotic relationships it share with its surroundings. With multiple causes and its complex interdependencies, these problems are deeply entwined within our lifestyle behaviours, aspirations, desires, social beliefs, and our response to the evolving environment. Shifting from the linear process of resource usage, consumption and disposal, circular economy believes in the core principle of re-circling material resource and preserve existing stock for a sustainable and resource abundant tomorrow. Enabling resource effective ecosystems today by ensuring collaborative usage, shift to renewable sources of energy and improved manufacturing processes and logistic cycles, Design-for-Circular-Economy (DfCE) is one of the first stepping stones towards creating future ecosystems of well-being living.

As a part of an academic applied design research project, this paper explores design of a circular economic service-system to facilitate community based resilience and enable a well-being ecosystem among the annually flood prone communities of the Brahmaputra Valley in the state of Assam, India.
Threatening a sustainable lifestyle and scope for socio-economic development, the villages in the Brahmaputra Valley of Assam, India, experience massive floods annually, leading to basic need deprivation, impoverishment, weakness and extreme social, physiological and cognitive vulnerability. Primary ethnography and design research revealed that being exposed to an annual vulnerability to basic survival needs, accompanied by the absence of adequate and permanent flood resilience systems, these communities have been completely dependent on external aid for relief and rehabilitation.

This dependency, however, has reduced the overall desire and capacity for self-reliance and the community’s resilience to such situations of emergency.

Approaching through holistic design thinking and system oriented design intervention, this project attempts to collaboratively design a service system to facilitate an ecosystem of self-reliance, effective community interactions, resource effectiveness and participatory local innovations for flood-resilient village development.

Understanding and mapping the process of systemic circular design intervention

In order to understand and decipher the methodology and process of thinking and designing holistically, several social design methodologies, community well-being design frameworks, philosophies and narratives were studied to create a design artefact, 10-Q-2-d-i. The tool enabled to evaluate a generated design concept or idea from multi-stakeholder design development perspectives.
Analysing various case studies of circular economic design interventions, a set of circular economic design trends have also been compiled and segregated as idea trigger cards — ‘Design Intervention Cards for Design-for-Circular-Economy (DfCE)’ to engage into participatory design ideations. These cards, as initial design directions, focussed on the design objective of enabling circular economy in a given context and aid designers and design students to channelize concepts generation process.

Exploring circular economic design opportunities for cultivating well-being among the flood prone communities of Assam, India

As primary research and end-user design inquiry, ethnographic research was carried out in three flood-prone areas of Assam to understand the current lifestyle scenarios, the severity of experienced problems, perceptions of well-being and prevalent behavioural biases of the primary stakeholders. Design dimensions for well-being and social sustainability ecosystem generation were mapped to the principles of circular economy in order to generate a system design approach framework. This framework was used to identify the leverage points for design intervention in the contextual system. Subsequently, a trans-disciplinary co-creation workshop was curated for idea generation, concept segregation and collaborative design development.

Contributing to flood-resilient village development: developing a collaborative grain storage and service system through social entrepreneurship

Using the system design framework, a social entrepreneurial model was conceptualized for the flood prone communities of Assam to facilitate and enhance self-reliance of food availability. Collaborative Grain Storage and Service (CGSS) System enables a user family to effective plan their farm-produce consumption patterns, and have on-demand access of food grains during any emergency scenarios like floods. The different service touchpoint implementation strategy was further developed and validated with the users.

Effective implementation of circular economic behaviour today in terms of collaborative or shared services that generate higher numbers of livelihood opportunities, effective user experiences, and aids communities to adapt renewable energy sources that reflect visibly on their household expenditures will make communities and villages in India evolve to a more resource effective system.

Within the contextual constrains, service system design can be approached through stakeholder participation and systemic design methodologies. The paper/presentation highlights how system oriented design can work on complex social problems by creating product-service-systems that enables the stakeholders in their capability-building, addresses local sustainability issues and creates a global implication through its replicability.


Ellen MacArthur Foundation. (2016). Circular Economy in India: Rethinking growth for long-term prosperity., 1–86. Retrieved from https://www.ellenmacarthurfoundation.org/assets/downloads/publications/Circular-economy-in-India_2-Dec_2016.pdf

Ellen MacArthur Foundation. (2012). Towards a Circular Economy – Economic and Business Rationale for an Accelerated Transition. Greener Management International, 97. https://doi.org/2012-04-03

Ellen MacArthur Foundation and IDEO, http://www.circulardesignguide.com, accessed on 02/01/2017

Larsen RJ, Eid M. Ed Diener and The Science of Subjective Well-Being. In: RJ Larsen and M Eid, (Eds.) The Science of Subjective Well-Being. New York: Guildford Press, 2008:1–12.

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Woodcraft S, T Hacket & L Caistor-Arendar 2011, Design For Social Sustainability: A Framework for Creating Thriving New Communities, The Young Foundation, London

Van Dijk, G. (2010). Design Ethnography: Taking Inspiration From Everyday Life. This Is Service Design Thinking, (August), 1–3.

Lucy Kimbell and Joe Julier, The Social Design Methods Menu, http://desis-lab.org/wp-content/uploads/2015/11/Social-Design-Methods-Menu.pdf, accessed on 30/12/2016

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New strategies for the refrigerator in the transition towards a circular economy

Fiore Eleonora
Politecnico di Torino

Predictive maintenance
Circular strategies

In the last decade, the values of the traditional economy have been strongly challenged, considering the concept of development of the last century as the main cause of many environmental issues that we are facing today. Recently, new strategies have been introduced to provide a renewed concept of development, including the creation new business models in the context of the circular economy, a greater importance of intangible value, the merging of products and services (de Arruda Torresa, 2017) as successful strategies to oppose the classical economy. Nevertheless, both designers and companies still consider projects as ‘finished’ at some point. In the same way in which, before the introduction of waste regulation, manufacturers paid scant attention to their products’ end-of-life, today many companies seem no longer interested in their products after the sale once they have been sold and the warranty has been expired, i.e. while the product is in use. However, the usage phase impact more in products such as the refrigerator, which is characterised by a long lifespan (according to Bakker at al., 2014 the ‘optimal lifespan’ of new purchases is now estimated around 20 years) and a continuous use (400-1100 KWh/y according to the related energy class).

In this paper, instead, we take into consideration how products could continuously evolve after their implementation (Hansen et al., 2008) and how companies could benefit from them throughout their life cycle, delivering new services while changing their business model completely. This approach leaves room for addressing every step of the traditional life-cycle in a more circular way, shifting the focus on a more complex vision about the product. This scenario could radically change by introducing new business strategies such as reducing product ownership through sharing, remanufacturing activities and so forth, while extending the product lifespan, without the need to rely on outdated strategies such as planned obsolescence or the push on the purchase of more goods.

We adapted some of the strategies of the circular economy listed by Kirchherr et al. (2017) within the standard life cycle of the product, by facing the gap of a certain lack of circular strategies related to the use phase (Figure 1). Hence five strategies have emerged, three of which are suitable for exploring new scenarios based on the concept of flexibility and two strategies based on the idea of predictive maintenance.

Product flexibility

This section provides three non-inclusive examples of exploring new scenarios based on flexibility, empower the user to personalise the object and develop new behaviours of use and consumption.

− Reduce ownership: A first scenario could be the integration of a pay-per-use and sharing strategies that leads the user to reduce the ownership of goods, by paying for the actual product use, saving money when the product is used in a virtuous way. In this paper, an in-depth analysis of scenario is carried out, based on the literature which considers ownership and planned obsolescence as two obsolete strategies.

− Product evolution: Software update is just an example of a product that evolves over time, changing and adapting to technological changes. What if the same concept would be extended to every part of the product and every step of the lifecycle? In this scenario, the user purchases/rent a product and then he/she could transform and shape it according to his/her needs with components and functions that can be integrated.

− Product adaptability: What if the product would change its behaviour according to contextual factors, usage information and the habits of those who use it? In this scenario, the user purchases/rents a product, he/she starts using it and after a while his/her expectations will be delivered, because the product evolves to meet user’s requirements. Equipping products with intelligence makes them adapt and respond to change and remain fit-for-purpose over longer time periods (McAloone and Pigosso, 2017; Ellen MacArthur Foundation 2015). IoT data can be used to improve current products, but also for developing virtual services and sharing economy platforms to support the technical lifetime.

Predictive maintenance

The second part of the paper investigates how to combine IoT data with the design of new products, suitable for addressing other parts of the lifecycle. McAloone and Pigosso (2016) suggested that combining IoT data with participatory tools IoT could be one driver for the success of the circular economy, together with sustainable design/eco-design and Business model innovation. The circular economy can benefit from this intelligence for up-cycling processes, monitoring the condition of individual components or whole product systems. Data about the real use of a product can be collected for a short time, with an object instrumented ad hoc for the experiment or alternatively on the marketable products.

Monitoring experimental products: in the first case, the product or its components can be monitored with experiments, to make their recovery suitable for a second valuable use. The R&D or design team, indeed, could study a prototype and then make projections over time of the expected use to determine when the object should be replaced or updated to obtain the maximum value from it. This could be the case of the following three examples, considering:

• Functional groups of components, i.e. a system of parts grouped by a specific function;

• Essential components, whose breakup will compromise the whole product functioning, eventually leading to replace it;

• Wearing parts, which can be easily replaced. Some relevant indicators should be defined and verified by measuring them through ad hoc experiments on these components, providing a more precise knowledge of the system.

Monitoring the final product: monitoring some parameters of the refrigerator as a form of predictive maintenance could also be performed on real products, to provide added value services throughout the lifecycle. It could be done by introducing a few sensors on the final product that will be delivered to the user, to allow continuous data transmission of the most important indicators. Among the possible outcome, detect failures in advance, notify, inform, communicate are only a few possibilities and it raises the need for learning systems able to recognise patterns, together with a platform on which to share and communicate directly with the user.

These two scenarios have different purposes.
The first deal with instrumented objects used for testing and monitoring objects to intercept the product to the suitable time in which it could be fully exploited, before it reaches its end of life, avoiding the product disassembly by preserving its integrity. The second aims to reconfigure the product to obtain real-time data and intervene promptly, shaping the object behaviour on the user habits and behaviour (i.e. by interacting with the user, facilitating the predictive maintenance, upgrading or replacing parts, improving the product or eventually allowing the product to adapt to changed conditions and learn from users’ usage).

Both scenarios would require analytics to measure and combine data inputs over time (Henne, 2015). The proposed strategies are suitable for both current product-centred economy and a future service-centred one, providing directions for future studies that want to address the extension of the product life cycle, while promoting an efficient use of products. IoT data open a variety of possibilities in monitoring, accessing more precise knowledge of goods and households, useful for design purposes.


Bakker, C. A., Wang, F., Huisman J., and den Hollander M. C. (2014). Products that go round: Exploring product life extension through design. Journal of Cleaner Production 69: 10–16.

de Arruda Torresa P.M. (2017) Design for Socio-technical Innovation: A Proposed Model to Design the Change, The Design Journal, 20:sup1, S3035-S3046

Ellen MacArthur Foundation (2016) Intelligent Assets: Unlocking the circular economy potential, Report of the Ellen MacArthur Foundation, February 2016.

Hansen, S., Berente, N., Lyytinen, K. (2009) Requirements in the 21st century: current practice and emerging trends. In: Lyytinen, K., Loucopoulos, P., Mylopoulos, J., Robinson, B. (eds.) Design Requirements Engineering. LNBIP, vol. 14, pp. 44–87. Springer, Heidelberg

Kirchherr, J., Reike, D., Hekkert, M. (2017). Conceptualizing the circular economy: an analysis of 114 definitions. Resources, Conservation and Recycling 127, 221-232

Henne, B. (2015) How IoT Data Becomes Valuable Intelligence. Retrieved June 20, 2017 from http://blogs.ptc.com/

McAloone, T.C. and Pigosso, D.C.A. (2017) From ecodesign to sustainable product/service-systems: a journey through research contributions over recent decades. In Sustainable Manufacturing: Challenges, Solutions and Implementation Perspectives (ed. R. Stark, G. Seliger and J. Bonvoisin), pp. 99–111. Springer International Publishing.


Click here to download the working paper

Co-design processes for cleaning and facilities services system

Germak Claudio, Giuliano Luca, Abbate Lorenza
Politecnico di Torino

Sustainable Fashion
Big Data
Systemic Innovation Design
Information flow

The paper illustrates a co-design research project performed with different stakeholders who represent a cleaning system consortium for the cleaning contract market sector, with the scope of social inclusion and creation of a sample of what Micheal Albert defines as participatory economics [1]. Today, the cleaning market sector is very prosperous and competitive, considering the purpose of efficiency necessarily mindful, at the single company level. Industries involved in this innovation process, in many cases offers not only services related to cleaning tasks but logistic and furniture services also (i.e. management, security, and training). In particular, those industries work in the contract market sector for big environments (i.e. hospitals, schools, industries) where hygiene standards are very high, and the commitments demand a high degree of quality and innovation through very selective invitation to tenders.

Commonly, the companies belonged to this market sector work in four main directions:
1- research and development of innovative and sustainable hygiene solutions
2- integrated and computerised management of cleaning and logistics services
3- speed up and optimisation of cleaning operations
4- ergonomics of cleaning equipment.

To the operational teams on site, meaning the workers settled in the cleaning site, are given particular attention, both in economic terms because they are the principal source of costs for the company and in training terms, because of the lack of professional skills in some worker category. However, for the future, a paradigm shift is forecasted. It is thought that this significant market sector will be able to absorb, even temporally, exodised workers also, namely that one expelled in the middle of their age from the employment market; surely with a high cultural level and familiarity with digital technologies.
Referring to this scenario, a famous Italian cleaning system group has started the research project described in the paper and based on the SMART PRODUCTION 4.0 industry model “… new production technologies shared by production-related actors that foster collaboration between people, machines and systems.” [2] In this first step of the experimentation, a SMART SERVICE is described. As reported by Consulting o McKinsey, SMART SERVICES consist in “a new generation of information and technical infrastructures that helps manage and monitor systems, exploiting the logic of maximum integration between all the actors of the production chain, including customers “. [3] The reference to the principles of Industry 4.0 is a requirement for our research because they are revolutionary towards the way of manufacturing products and organising work according to a systemic logic:

• Automated and interconnected production models;
• Intelligent and communicating products;
• Traceability of processes that fosters collective information;
• Shared and collaborative production model at the supply chain level;
• Cloud storage of a significant amount of collected data and their accessibility.

The cleaning system group, in particular, has requested to the University Design team, skilled in the development of ICT based services, HCD and Interaction Design, to direct the project by identifying the virtuous relationships among actors, processes and tools to implement them systematically in the supply chain of cleaning activities. Therefore, the project framework consists of two ambits of work, the first one consisting of the cleaning site in which people are living the spaces (users), cleaning operators and team coordinators collaborate, and the second one external to the cleaning site, consisting of service companies, distributors and manufacturers producer. The co-design chain created in this way involves all the different actors in one single process, each with its role, personal problems, needs and behaviour [4]. Employing UCD User-Centered Design techniques, the human being has been placed at the centre of the design process; the result is a new process system structured by new generation of APPs and Big Data Management platforms. Figure 1 describes the new process diagram highlighting how different actors can communicate each other, report malfunctions or issues, convey needs and provide data that the system collects and transforms into inputs, in order to make:

• the cleaning and maintenance process participated among final users, operators and cleaning system consortium;
• the control of cleaning services and the maintenance of spaces more effective and efficient, thanks to the real-time communication of issues between the user, operator and cleaning supervisor (coordinator);
• the cleaning company more aware of energy consumption, the effectiveness of the materials used (consumer products and equipment) and the efficiency of its workers;
• the production of products and equipment more sustainable developed for reducing the fatigue and increasing safeguarding the health of workers and the environment.


Agrawal, Mani K., and Minsok H. Pak. “Getting smart about supply chain management.” The McKinsey Quarterly (2001): 22.

Albert, Michael, and Robin Hahnel. The political economy of participatory economics. Princeton University Press, 1991

King, Stanley, et al. Co-design: A process of design participation. Van Nostrand Reinhold Company, 1989.

Schmidt, Rainer, et al. “Industry 4.0-potentials for creating smart products: empirical research results.” International Conference on Business Information Systems. Springer, Cham, 2015.


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Continuous Improvement: How systems design can benefit the data-driven design community

Lomas James 1, Patel Nirmal 2, Forlizzi Jodi 3.
1, Delft University of Technology
2, Playpower Labs Inc
3, HCI Institute, Carnegie Mellon University

Data-Driven Design
Continuous Improvement
Systemic Design


Currently, the learning science community is exploring the use of data-driven design to improve K12 educational systems. These “continuous-improvement systems” aim to align strategic goals, outcome metrics and human-computer system processes to support improved learning outcomes. However, the learning science community has only begun to apply systemic design to practical implementation of these systems.

In this paper, we present several examples of data-driven design in K12 educational systems in order to identify aspects that can benefit from systemic design. Through these case studies, we focus on three concepts: 1) systemic designers can ensure that the system is capable of measuring successful outcomes; 2) systemic designers can ensure that system optimization will improve intended outcomes while minimizing unintended consequences; and 3) systemic designers can portray what a future with these continuous improvement systems will be like to the educational community, before any resources are committed to building the technology.

Example #1: Ensure that the system is capable of measuring successful outcomes

Data can be used to inform system stakeholders about the success of designed systems; that is, how well outcome measures align with system intentions. For instance, after providing an instructional activity (lecture, small group, video, etc) in class, a teacher might assign their students an “exit ticket” quiz to assess whether the instructional activity was successful. These quizzes support data-driven decisions about how to spend time and effort in the classroom. Variations in student performance give teachers an understanding of the students who need greater attention and the learning objectives that need greater attention. Further, digital data from exit tickets or other formative assessments can be aggregated across teachers to provide school administrators with continuous insight into the areas of need, such as students or teachers who need additional help or learning objectives that are posing special challenges. Providers of digital instruction can then aggregate usage and performance across many schools in order to identify successful and unsuccessful usage patterns. Data-driven continuous improvement can occur at multiple levels (i.e., teacher, school & software provider) when systems are designed to generate valid outcome metrics of success (goal achievement).

Example #2: Ensure that system optimization will improve intended outcomes while minimizing unintended consequence

Success metrics can be used by human teams and AI systems to drive continuous improvement. However, the optimization of metrics can produce unintended consequences when chosen metrics are not fully aligned to intended outcomes and when feedback loops about metric suitability are impoverished. In this case study, an online educational game is designed with the goal of motivating students to practice math problems. After being deployed online, the game attracts several thousand students a day; these players are randomly assigned to different game design variations to observe how

the effects of different designs on key outcome metrics (e.g., duration of voluntary play). To investigate the role of AI in system design optimization, we implemented a UCB multi-armed bandit (a reinforcement learning AL/ML algorithm) to automatically test variations in the existing game parameter space (e.g., time limits, etc). The algorithm is designed to optimally balance the exploration of potential game designs with exploitation of the most successful designs; sometimes it will randomly search the game design space for configurations that maximize metrics (duration of voluntary play time) and sometimes it will deploy the most successful variations. While the algorithm worked as intended, the system “spun out of control” and primarily deployed malformed game designs that were maximizing the outcome metric but were misaligned with the original educational intent: the game variations were likely played for long periods of time because they were absurdly easy. This shows the pitfalls of having AI systems engage in automatic optimization without humans in the loop as a governing feedback system. Systemic designers need to design feedback systems to monitor system AI to ensure that outputs are meaningfully aligned to system intentions.

Example #3: Portray what the future will be like

Artificial intelligence has the potential to facilitate the work of teachers by reducing the effort required to use data to inform personalized instruction. However, AI can be intimidating or off-putting to teachers who do not understand its operation or intentions. In this case study, we deployed a teacher-facing recommendation system that uses reinforcement learning to continuously improve recommendation usefulness to teachers. To design a reinforcement learning AI system, there must be data representations of the system state, the space of possible actions and a reward signal tied to a success metric. In our case, the system state is student digital performance on learning activities, the action possibilities are the different digital items that teachers can next assign to a student and the reward signal occurs when teachers act upon a recommendation (i.e., when they assign those digital activities recommended by the system).

This system embodies two key elements that diverge from most existing work in “adaptive learning” or “intelligent tutoring systems.” First, the system emphasizes human-technology teamwork, in contrast to human replacement, so that teachers are empowered by the assistance of the AI. Secondly, the artificial intelligence is deliberately constructed as an aggregation of human intelligence: the system learns from the activity-assignment decisions that are made by thousands of other human teachers and aggregates them into artificially intelligent recommendations. To promote adoption of this system, a key role for systemic design is making the intended future vision accessible and attractive to teachers and other stakeholders. Systemic designers can help to engage humans to participate in the decision making by presenting a glimpse of what a data-driven future might be like in the classroom.


Across these case studies, we show how systemic design can aid diverse participants in the implementation of data-driven design and optimization. Systemic design insight can contribute to the negotiation of meaningful and robust metrics of success, to the construction of human-in-the-loop governance of AI systems and to the representation of potential futures. We expect designers to play a crucial role in taming the complexity of practical AI-human systems and aligning system outcomes to sustainable, humanistic values.

Data, Fashion System and Systemic Design approach: an information flow strategy to enhance sustainability.

Tamborrini Paolo, Remondino Chiara, Marino Cristina
Politecnico di Torino

Sustainable Fashion
Big Data
Systemic Innovation Design
Information flow

Nowadays, the role played by the fashion industry in contributing to the degradation of natural systems is increasingly acknowledged.
The impacts on the environment are mainly linked to the use of non-renewable raw materials, water pollution and waste generated. In addition to these socio- cultural implications deriving from the use of cheap labour and undignified working conditions resulted from ‘fast’ fashion business model, where economies of scale deliver standardized fashion at high volume and low price. Overlaps to all this a significant lack of information and communication between stakeholders make the interpolations of the system difficult to be clear.

In this context therefore characterized by complexity, intricate interdependencies and flux, and a wide span, geographically, epistemologically and in term of disciplines and discourses it draws together since was first introduced to the realm of fashion (Fletcher, 2008) system and design thinking, has provided a helpful viewpoint on the area.
The ambition of this paper is to offer a perspective that faces this complexity and align fashion with sustainability values through insights gained from data.
Specifically using systemic design as a catalyst of change, this research looks through data generated inside fashion system in a holistic way, defining all the process, service and actor as a dynamic whole and not as a fragmented sum of its part.

Contrary to what happens with the sustainability strategies currently in use, which are focused on symptoms, and endorse methods that try to solve single problems not caring about existing relationships, systemic design approach can be an effective tool to restore the lack of information that concern the whole process and all actor.
This approach, which looks at the larger picture, focuses on the transition from a linear vision, where individual environmental issues are addressed, to a systemic approach, where an improvement of the individual components, if put in relation, corresponds to improvements for the whole industry (Bistagnino, 2011, 2016).
To planning the process linked to the paradigm shift, we chose to undertake information flows strategy, allowing the whole system components to be aware of their role and to make the flow of information functional to the objectives of environmental sustainability.
A preliminary literature review reveals in fact that acting in terms of information flow from a systemic perspective does not represent a parametric adjustment, nor a reinforcement or a weakening of an existing cycle.
According to Meadows (2008), the structure of information flows can be an effective leverage point in the fashion system, if the information is delivered where it was not before, causing people to change behaviour. Adding or restoring information, in a fashion system where the information circulating is sometimes not linked to ethical and social value, can therefore, represent a powerful intervention, usually easier and cheaper than reconstructing physical infrastructures.

In the fashion industry, adding to or changing the flows of information between companies in a supply chain or between retailers, designers and consumers can create large changes for little effort (Fletcher, 2008).
However, to trigger action, it is necessary to couple new information with resources and incentives to support the behaviour change.
To fill the information gaps, this research starts from the selection, the organization and matching of a set of data that represent a quantitative input and reveals the importance of a qualitative output graphically and appropriately represented.

Data matched with a Systemic Innovation Design Methodology becomes a useful tool to analyze, organize and understand visually all the complexity of process, behaviour and pattern related to fashion system. Mapping the entire lifecycle (fig. 1) highlights that some data are not effectively harvested and appears the need of generating new asset of data collection able to bring the intangibility of shopping and consumption experience to the tangibility of dress and people, spreading the awareness of the entire process inside the system.

Taking advantage of new technologies able to harvest personal data in almost any context we chose to undertake the collection from mapping body shape and consumer habits until the potentialities of open data.
The Body shape set of data assisted with wearable technologies generates information not only useful for companies but able to increase consumer awareness about his purchasing and consuming habits .
In fact, a high empathic value is a key to clothing with a longer life cycle, according to Chapman (2005) work by cultivating an emotional and experiential connection between person and object, we can disrupt our dependency on consumption of new goods to construct meaning and our sense of self.
In this research this operation is supported by the collection of personal data through Near Frequency Communication and IoT devices, concerning wardrobe data, to create personal narratives through customization, personalization, mapping thus the real attachment with specific garments in a particular context and collecting sustainable practices in real time.

In conclusion including open data gathering with RFID technology allow to generate a global overview of warehouse movements and production system making the data collection even more transversal and inclusive.
While IOT, RFID, and Near Frequency Communication are powerful tools by themselves regarding data collection, when combined with distributed ledger systems such as blockchain, they enable an authentic traceability, increasing the potential to create a fashion system that is not only sustainable in terms of behavior and resources but also transparent in the processes and transactions.
The focus of the entire research is the use of a systemic design approach to navigating on a complex behavioural system and global supply chain networks. To underline the importance of collecting the interaction and the relationship in a significant dataset, highlighting how it is possible to generate a unitary and coherent understanding of the entire system capable of allowing and supporting sustainable development.
Since fashion is more than the materials that garments are made of, data give us the opportunities to go beyond discrepancies, help businesses make better-informed decisions about the production and distribution of goods and make the customer aware of socio-environmental problems related with their choices.


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Participatory Design for Service Robotics

Valpreda Fabrizio, Cataffo Marco.
Politecnico di Torino

System Design
Service Design
Social Entrepreneurship
Social Innovation
Design Democracy
Design for Well-Being
Design for Circular Economy

The spread of technologies as Cloud and Distributed Computing, the Internet of Things (IoT) and Machine Learning techniques comes with a few paradigm changes with highly disruptive innovation potential and consequent design imperatives. Digital Abundance is a shorthand that introduces us to the economy of information as a non-depletable resource, as it can be continuously copied, while exponentially increased due to “cheap and small” sensor technology. High connectivity of devices and machines is shaping not only sensing and monitoring capabilities of different application fields, but also describing ever more ubiquitous and diffuse computing capabilities, affecting decision-making with a wide range of assisting tools and methods, like context-aware AI fuelled by a yet unmatched data flow.

On these premises, applied research at Polytechnic Interdepartmental Centre for Service Robotics in Turin, Italy, focuses on the development of a service robotics platform able to operate on the local scale and capable of adapting to evolving scenarios. Useful to this purpose is Robotics-as-a-Service (RaaS) framework, a cloud computing service model that allows to seamlessly integrate robots and embedded (IoT) devices into Web and cloud computing environment. As a service-oriented architecture (SOA) for robotic applications, a RaaS unit has the environmental potential of decoupling the production of economic value from energy and resources consumption. It includes services for performing functionalities, a service directory for discovery and publishing, and service clients for user’s direct access. This platform allows to manage robotics components both as an increasingly granular integration of control over automated tasks and as part of a largely aware whole emerging from their connectivity.

With the scaling potential of moving beyond its contemporary application such as industrial facilities monitoring, precision farming and agriculture, healthcare and risk management scenarios, RaaS is bound to involve an increasingly fluid and diverse range of users, shaping new socio-technical systems where practices, habits and relationships will evolve in respect to its adoption.
For this product-service system we propose a Socio-Technical Innovation framework to balance the efficiency of simple stable technological systems with the capacity for resilience and adaptability of more complex, unstable social systems that surround them.
Complex systems high connectivity leads to difficulties in centralized control and predicting causes and effects, driving the need of localizing decision-making when possible. Chances of identifying a single ‘optimal’ solution for the whole system width are low; great part of current information and implementation happen on a local scale, necessitating a decentralized approach. While in simple and stable systems homogeneity of input is favoured over a more problematic diversity, in complex social systems heterogeneity is incredibly more valuable, both increasing the range of current information and of solutions generated.

A wider network of stakeholders, reaching out to growing community of users and producers, allows organizations to see more opportunities than those dependent on previous choices. Local decision-making made by a variety of actors with shared interests, is likely to be the most successful: though the larger system is complex and difficult to predict, its subunits are less so. Laying our foundations on Participatory Design (PD) research we propose the Actor-network social theory as a tool to analyse the intricate relationships that define the structure of groups where humans are not the are not the only participants, as artefacts concepts and design itself function as intermediary. Thinking of stakeholders in PD as a network of actors is useful as it allows researchers or designers to understand cultural practices, power relationships and the roles of mediating artefacts or concepts, as recognizing the mechanisms through which power is exercised is vital.

In a User Experience Design context, a particularly useful term to describe possibilities of action emerging from the reciprocal relation between an actor and his environment, is affordance in its original definition proposed by psychologist J. J. Gibson in 1977. (Vardouli 2015). In his paper Vardouli argues that the notion of affordance could be analogized with the one of embedding, as they refer to possibilities for engagement of the subject with a context.
To support heterogeneity of solutions fitting diverse use cases and even different application fields we investigate service robotics case studies for modular design, to generate a product-service system of non-independent solutions.
A designed system of product components and services follows the purpose finding principle (Jones 2016). As Jones further explains in his paper on Systemic Design Principles, the purpose principle provides a whole-to-part view of problem space. The diversity of solutions provided by a modular configuration of functionalities, delivered in the form of services, guarantees a balance between fixed purposes and what Jones refers to as creative framing.

We will then explore the literature on PD solutions to usability issues. To answer interrogatives about the collection of end user requirements, about their involvement in a continuous development process and how to achieve a common understanding among the actors, we look for methods to explicitly model the interaction relationships between server and client, producer and consumer, designer and user in order to increase the learning capacity of a RaaS ecosystem through the integration of diverse experiences, while distributing means of production and innovation capacity


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