New services and their business models increasingly involve a large number of actors or parties. For example, this complexity is evident when choosing an accommodation via Airbnb, which requires not only a user, the Airbnb website, and a host, but also includes other users, family members, advertisers or legal authorities. Any actor involved can be a “showstopper” to the user’s decision.
Yet, attempts to understand user decisions typically focuses on the relationship between the user and one actor (e.g., “what does the user want from Airbnb website?”). The workshop took a holistic view and invited participants to scrutinize the benefits and risks perceived by users and other involved parties in the service network. This is especially valuable in current dynamic times when services are disrupted. The emergence of new technologies and new parties change the playing field of services essentially across all industries.
The goal of this workshop was to:
- Understand the values (benefits and risks) that a service user sees in current and emergent service parties
- Simulate interventions (e.g., new technologies, new parties) that change the service network
- Develop ideas as to how an organization may respond
- Sensitize organizations and its employees for planned and unplanned changes.
The workshop was conducted by Dominik Mahr (Associate Professor at Maastricht University, Scientific Director of the Service Science Factory), Damien Nunes (Service Designer at the Service Science Factory), and Stefan Holmlid (Professor at Linköping University). This workshop is a practical translation of ongoing research that our SDIN researchers Martina Caic (Value networks & technology) and Vanessa Rodrigues (Prototyping & organizational learning) are working on.
The workshop steps:
- Introduce the network view of service adoption
The example of the automotive industry demonstrates the need to consider the roles of various actors in a network and familiarized the participants with the terminology of value networks, users’ expectations (hope and fears) and planned and unplanned interventions.
- Explain the healthcare challenge of Ambient Assisted Living for elderly
During the workshop we worked on a simple, practical case of Ambient Assisted Living (AAL) where elderly have the opportunity to live autonomously for a longer period in an elderly home. Preventing and detecting a fall is a key challenge in this context. Given the condensed workshop setting, we focused on the network relationships that an elderly person has with informal caregivers (e.g., family) and the formal caregivers (e.g., nurse).
- Interrupt the service network
The rising healthcare costs drive innovation in healthcare. A social robot, which among other functionalities enables fall detection, is a promising technology innovation that is the focus of our research. While the introduction of the social robot can be planned, the temporary absence of the informal caregiver is representative of an unplanned intervention. Both planned and unplanned changes can have a positive and negative impact on the relationships in the network. We simulated both interruptions in the workshop. Teams of participants developed a new value network with users’ expected benefits and risks per relationship in the network.
- Develop responses towards planned and unplanned changes
The teams collectively developed ideas on how to respond to the changes to the network. The diverse ideas included new functionalities for the robot, automated mood trackers, nurse trainings, treatment guidelines, privacy regulations, robot names, sound alerts and communication processes between network parties, to name a few.
- Share ideas of organizational and employee response
The teams shared their ideas with each other and reflected on the potential responses to the changes in the service network.
The process practiced in the workshop is rooted in service design and stimulates holistic thinking. It not only translated state-of-art research on service design and innovation into practice, but also fed back practice thoughts towards science. In a real-life setting, such a process supports organizations to anticipate changes in complex services and develop more resilient structures and processes.