From Ideation to Realization: Essential Steps and Activities for Realizing Data-Driven Business Models

Data have become a key resource for competition in several industries. As a response to this challenge, companies seek to create and realize data-driven business models (DDBMs). Although the ideation of DDBMs has been the subject of research, the realization of DDBMs remains an under-researched area. In this paper, we present a four-step process for guiding the realization of DDBMs. This process is grounded in a two-step literature review of research related to DDBMs and business model realization (BMR). By drawing on the four steps of BMR and six dimensions of DDBMs, the process locates 54 activities for realizing DDBMs. Furthermore, we cluster the activities to develop a consolidated model and demonstrate the application of the process by applying it to three case studies from the literature. The process is a starting point for further research on the realization of DDBMs and helps companies structure their activities for realizing a DDBM.

I. Introduction

How to create value from data is a current and highly relevant topic for practice as well as for research. Through the massive commercial success of data-driven giants from Silicon Valley, this topic has become increasingly relevant for incumbent companies of many industries. Chen et al. [1] showed how Lufthansa connected data about the customer relationship system with external social media data to deliver a personalized customer experience and increase passenger turnover. Alfaro et al. [2] described how the Spanish bank BBVA successfully developed a data monetization portfolio by investing in different projects over time. Similar to Lufthansa and BBVA, many other companies are trying to capitalize on big data and advanced data analysis approaches. Although consulting and IT firms offer support for companies interested in becoming a “data-driven company,” it is still perceived as one of the greatest challenges in the digital transformation journey.