Designing with the use of data for a better understanding of people and operating contexts in sociotechnical systems

The complex systems defined as ‘sociotechnical systems’ are made of software, hardware and people, somehow linked to the policy and a large number of stakeholders. They show complex dependencies and functional-based constraints. Over the last decades, the need to cope with the complexity took different forms, evolving in research activities and new disciplines. Systemic Design (SD) is an approach to manage the complexity that draws its origins into the General System Theories, cybernetics and generative science of the twentieth century, up to the recent attention towards systems thinking. Cyber-physical systems (CPSs), on the other hand, draws its origins from software and mechanical engineering, merging theory of cybernetics, mechatronics, design and process science. In CPS computing and communication are tightly coupled with the monitoring and control of entities in the physical world (Cheng and Atlee, 2008). The idea behind CPS is similar to the idea of the Internet of Things (IoT), with which it shares the same architecture. IoT is growing importance also in the design field. As design research by definition is intended to produce knowledge, this knowledge can be acquired by merging different methods, e.g. qualitative and quantitative. The data collected and made available from IoT technologies quantifies aspects that were not measurable before, providing content for other research activities such as ethnographic research and participatory activities. The designer could query some physical object and obtain useful data for the design. In this paper, we seek to address the design process in the era of the IoT, exploring the use of data in the early design stages as a means to investigate the application domain and stakeholders’ interaction with products.