Insights from generative sessions
Service design methods need to account for networks to better understand what the value (i.e. benefits and risks and their interplay) is for the network actors. Therefore, we propose contextual interviews drawing on generative methods1 as a valuable source of network insights. Empathic listening and visual artefacts help service designers explain network complexity. In particular, network visualisations (i.e. mappings of network contexts) are useful in eliciting users’ tacit knowledge and uncovering value co-creating streams. Allowing users to freely show their understanding of network dynamics through mappings and shared narratives clarifies their perceptions on ‘how it is now’ and ‘how it will be’ after the introduction of a technology-based service.
Specifically, there are three stages that are essential for a successful network approach:
- Organise generative interviews/workshops: use tangibles (e.g. cards, markers, post-its, canvasses) and ask users to map out a particular network context. Through easy-to-understand visuals or prototypes, introduce your service innovation. Finally, ask them to visualise a new condition, again using different generative prompts. Repeat such interviews/workshops with different stakeholders (e.g. focal users, other service beneficiaries).
- Empathise with your users: do not presume your users’ experiences, but instead motivate them to express their own views through a set of ‘what’ and ‘how’ questions, followed by deep-probing ‘why’ questions. Your service innovation can radically disrupt their network contexts; thus, pay attention to how it transforms the value for not only the focal user, but also for other actors.
- Abstract your findings: exploit both narratives and visual artefacts. Network mappings offer a very vivid representation of both current contexts and future scenarios. Listen to your users’ data-rich stories, and try to understand what they wish to communicate through their visualisations. Can you identify clusters of similar mental models? Are their maps instrumental to values they express as their priorities?
User research on social service robots
We collaborated with the elderly care unit of the Zuyderland hospital (in The Netherlands), Cáritas Coimbra (Portugal) and the GrowMeUp2 project, whose main aim is to increase the quality of life and the years of active and independent living of seniors (65+) with only minor physical or mental health problems. They are developing a social service robot that understands social cues through facial and voice recognition, and assists seniors with health monitoring and household activities to prolong their independent living. With the aim of understanding how this disruptive service innovation affects the care-value networks of the elderly, we conducted contextual interviews through generative cards activities. To better capture the complexity of the network, we engaged different actors: the elderly, formal caregivers (i.e. professional care staff), and informal caregivers (i.e. family members and friends).