Formative Evaluation of Data-Driven Business Models – The Data Insight Generator

New technological developments such as Big Data or, the Internet of Things lead to exponentially increasing amounts of data created and stored by organizations. As a consequence, new data-driven business models (DDBMs) appear. These business models have special characteristics which need to be included in the business model development process. Thus, different methods and tools have emerged to support the development of DDBMs. One of these is the Data Insight Generator (DIG) which seeks to combine the key resource and value proposition of a DDBM. This paper comprises the application of the thinking-aloud method for a formative evaluation of the DIG. The contribution of this paper is twofold. First, the usability of the DIG is tested and implications for further development are derived. Second, the paper provides empirically-based insights into development of DDBM that facilitate the future development of such business models

Making Data Valuable for Smart City Service Systems - A Citizen Journey Map for Data-driven Service Design

Due to the digital transformation of smart cities (SCs), improved access to digital technologies can enable gathering and utilization of data which can serve as key resources for services to improve citizens’ quality of life. SCs face challenges making data valuable for the design of such data-driven services. Service literature lacks in providing methods to facilitate the design of these services while addressing the requirements of SCs as smart service systems. This paper presents the Data-driven Citizen Journey Map (DCJM), a method which supports designing data-driven services in collaborative Design Thinking (DT) workshops. Following design science research (DSR), we developed and evaluated our method through five iterations of workshops, interviews, and questionnaires with SC experts and students. Our evaluations indicate that the DCJM, including all promoted constructs, is useful to support data-driven service design in SCs and that it can be combined with existing methods in comprehensive service development processes

GESCHÄFTSMODELLE 4.0: Baukasten zur Entwicklung datenbasierter Geschäftsmodelle

Die Digitalisierung ermöglich Unternehmen den Zugriff auf einen neuen Schatz an Ressourcen: Daten. Doch wie sind diese Daten wirtschaftlich zu nutzen? Das Praxishandbuch zeigt Ihnen, wie Sie datenbasierte Geschäftsmodelle entwickeln, um gezielt einen strategischen Wettbewerbsvorteil aufbauen zu können. Hierfür steht ein Baukasten aus methodischen Werkzeugen zur Verfügung, welcher Sie Schritt für Schritt durch die Entwicklung Ihres individuellen datenbasierten Geschäftsmodells führt

Requirements for Representing Data-Driven Business Models - Towards Extending the Business Model Canvas

Business modeling has become an essential tool in practice for analyzing and generating business models. In recent years, digital innovation with data-driven services gained an important role for the development of new or improved business models. As a consequence of this development, the impact of data on business models in general and business modeling in particular becomes an important issue in research as well as practice. Yet, research on business modeling for data-driven business models (DDBM) is a burgeoning field of research. Hence, this paper surveys the extant literature of DDBM to assess the state of the art in this area. Based on these insights, the paper suggests requirements of DDBM and opportunities for future business modeling research that could improve the analysis and generation of DDBM. As a consequence of these requirements, we suggest opportunities to extend the Business Model Canvas for data-driven business models

DATA-DRIVEN BUSINESS MODELS - BUILDING THE BRIDGE BETWEEN DATA AND VALUE

In the wake of an ongoing digital transformation organizations are seeking to understand and generate new data-driven business models. While data is a key resource, generating value from data is a key challenge for innovating data-driven business models. Extant tools for business model representation offer little help. In this paper, we propose the design of a Data Insight Generator (DIG) artefact that can support the design process of data-driven business models at a crucial step: connecting data to value propositions. The artefact is positioned as a complement to the Business Model Canvas, the most widely used tool for business model representation. The DIG connects two key elements of the business model, namely key resources and value proposition through six data-specific elements. Further, the DIG supports an iterative process of discovery for these elements as a boundary object between business and data science/IT participants of business model innovation. Based on a formative evaluation we demonstrate the usability and utility of the DIG

Making Data Tangible for Data-driven Innovations in a Business Model Context

As digital transformation has occurred over the last decade, organizations have been compelled to seek new business models. As a consequence of this development, the impact of data on business models has become a focus of interest in research as well as in practice. Based on typical characteristics of data-driven business models (DDBMs), this paper develops 19 design principles for their visual representation. The design principles were derived from semi-structured interviews with experts in the field of DDBMs and were clustered into the Business Model Canvas (BMC). The contribution of this paper is threefold. First, the developed design principles deepen the knowledge base on DDBMs. Second, other business model representations can be assessed against these design principles and new or aligned representations can be developed. Third, the design principles can be used by practitioners to develop a DDBM

Making Data Tangible for Data-driven Innovations in a Business Model Context

As digital transformation has occurred over the last decade, organizations have been compelled to seek new business models. As a consequence of this development, the impact of data on business models has become a focus of interest in research as well as in practice. Based on typical characteristics of data-driven business models (DDBMs), this paper develops 19 design principles for their visual representation. The design principles were derived from semi-structured interviews with experts in the field of DDBMs and were clustered into the Business Model Canvas (BMC). The contribution of this paper is threefold. First, the developed design principles deepen the knowledge base on DDBMs. Second, other business model representations can be assessed against these design principles and new or aligned representations can be developed. Third, the design principles can be used by practitioners to develop a DDBM