{"id":115441,"date":"2026-11-11T07:38:06","date_gmt":"2026-11-11T06:38:06","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=115441"},"modified":"2026-11-11T07:40:19","modified_gmt":"2026-11-11T06:40:19","slug":"designing-analytics-based-services","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/designing-analytics-based-services\/","title":{"rendered":"Designing Analytics-Based Services"},"content":{"rendered":"\n

Exploring Design Requirements for Methodological Tool Assistance in \u00a0Service Design Teams<\/strong><\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

Analytics-based services (ABS) apply analytical methods to data in \u00a0order to enable customers to make better decisions and solve more complex \u00a0problems. While it is widely acknowledged that ABS pave the way for new \u00a0value creation opportunities, surprisingly little is known about their systematic \u00a0design. Service design teams still struggle to create ABS solutions \u00a0systematically, i.e. to define what is to be done, how this is going to be achieved \u00a0and how decisions are taken during ABS design projects. In this research, we \u00a0report on the first iteration of our design science research project which aims to \u00a0build design knowledge on methodological tools that can support service design \u00a0teams in this particular context. We derive and evaluate four meta-requirements and four design principles \u2013 thus contributing to a more profound design knowledge base that can support researchers in developing new methodological tools in the field of ABS in the future.<\/p>\n\n\n\n

Introduction<\/h2>\n\n\n\n

In the wake of business changes enabled by the digital transformation [1], large \u00a0amounts of data accompanied with advances in analytics technology provide \u00a0companies with novel opportunities to create meaningful value for their customers [2\u2013 4]. Analytics-based services (ABS), a new type of services, are introduced to the \u00a0market that leverage analytical methods (\u2018analytics\u2019) applied to data in order to help their customers make better decisions and solve more complex problems to ultimately \u00a0reach their goals more effectively [5, 6]. Researchers and industry experts agree that \u00a0ABS provide a promising path for companies to gain new competitive advantages [7, \u00a08] by enabling a much deeper customer connection [9], by allowing a broader role in supporting the customer’s value creation [10], or even by opening up entirely new markets [11]. Thus, systematically realizing new ABS opportunities has received  research priority [7] and is being actively explored by companies [12].  <\/p>\n\n\n\n

Service design is a formalized, multi-disciplinary approach that helps innovate \u00a0service offerings. Thus it could potentially serve as a means to guide and stimulate the \u00a0development of new ABS [13]. Surprisingly, little research has been reported to \u00a0advance service design literature in this regard and actionable insights to better \u00a0manage ABS design are still lacking [14]. As a result, service designers in practice \u00a0still struggle to develop services that appropriate the expected value from data and \u00a0analytics in novel service offerings [14, 15]. In particular, creating and refining the \u00a0service concept remains a challenge in ABS design. At the core of service design \u00a0processes, the service concept serves as a means of specifying the nature of the \u00a0service to be provided [16]. As such, it provides a detailed description of a service \u00a0idea with regard to its value creation and delivery processes [17]. Thus, a clear and \u00a0shared understanding of the service concept within service design teams, which we \u00a0refer to as service concept comprehension, is crucial in order to ensure consistent \u00a0decision making during the course of a service design project \u2013 yet, actionable insights on ABS-related service concept comprehension remain scare. \u00a0<\/p>\n\n\n\n

Methodological tools assisting service design have the potential to solve this issue. \u00a0Prior research has found that creative and interdisciplinary tasks can particularly \u00a0benefit from tool-support by promoting a better comprehension through visualization, \u00a0communication, and documentation [18]. This could positively influence the \u00a0performance of service design teams during ABS-concept development in practice. \u00a0However, design knowledge which helps researchers to build tools specifically \u00a0assisting service concept comprehension is scarce. Researchers lack theoretically \u00a0sound guidance through clear principles for designing such tools in general terms. To \u00a0this end, we propose a design science research (DSR) project seeking to address this \u00a0literature gap by tackling the following research question: How to design methodological tools assisting ABS design in order to increase service concept \u00a0comprehension? \u00a0<\/em>In this research, we report on the first iteration of our project and present initial \u00a0design requirements which are meant to serve researchers as a more profound design \u00a0knowledge base when building new methodological tools in the specific field of ABS \u00a0design. In the remainder of the paper, we first provide necessary foundations and \u00a0related work relevant to our research. This is followed by our research methodology \u00a0in section 3. The findings of our research are reported in section 4 and 5, structured \u00a0chronologically reaching from the design requirements derived to their instantiation \u00a0and evaluation. We then discuss our findings in section 6 before we briefly \u00a0summarize our results, acknowledge limitations, and provide an outlook on future \u00a0research in Section 7.<\/p>\n\n\n\n

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