TY - JOUR
T1 - Data science for service design
T2 - An introductory overview of methods and opportunities
AU - Kunneman, Youetta
AU - Alves da Motta-Filho, Mauricy
AU - van der Waa, Jasper
PY - 2022
Y1 - 2022
N2 - To support effective and successful projects, Service Design practitioners rely on insights that mainly build on qualitative research methodology. The literature on data science promises to help transform how design research is done, adding sophisticated quantitative analyses, complementing existing methods with the power of machines. Due to this potential, data science receives widespread attention from both design practitioners and academics. However, the literature is fragmented and specialized, making it hard for designers to engage with data science. This paper addresses the opportunities and challenges for data science to support Service Design projects, evaluating existing technologies from designers’ perspective and providing an entry-level guide for service designers. These methods can help increase the quality of design research, making hidden information accessible and assisting creative processes. Together, these results are expected to inspire organizations to advance their data science resources for Service Design projects.
AB - To support effective and successful projects, Service Design practitioners rely on insights that mainly build on qualitative research methodology. The literature on data science promises to help transform how design research is done, adding sophisticated quantitative analyses, complementing existing methods with the power of machines. Due to this potential, data science receives widespread attention from both design practitioners and academics. However, the literature is fragmented and specialized, making it hard for designers to engage with data science. This paper addresses the opportunities and challenges for data science to support Service Design projects, evaluating existing technologies from designers’ perspective and providing an entry-level guide for service designers. These methods can help increase the quality of design research, making hidden information accessible and assisting creative processes. Together, these results are expected to inspire organizations to advance their data science resources for Service Design projects.
KW - data mining
KW - data science
KW - practice-based design research
KW - service design
KW - service design methods
UR - http://www.scopus.com/inward/record.url?scp=85126232045&partnerID=8YFLogxK
U2 - 10.1080/14606925.2022.2042108
DO - 10.1080/14606925.2022.2042108
M3 - Article
AN - SCOPUS:85126232045
VL - 25
SP - 186
EP - 204
JO - The Design Journal
JF - The Design Journal
SN - 1460-6925
IS - 2
ER -