In recent years digital maturity models have been developed in order to help companies to address questions about the company’s overall status with regards to its digital transformation by assessing their digital maturity. However, the existence of a wide range of digital maturity models result in that companies cannot see the wood for the trees, hence, companies risk selecting a maturity model that do not fit the organizational purpose of the maturity assessment. This is the main research problem and motivation behind this thesis, and answers following research question:
How can digital transformation maturity models be defined, classified, and selected?
The research question is answered through an exploratory mixed-model study and provides a comprehensive analysis of existing digital maturity models (N=25). First a qualitative content analysis has been conducted in order to answer how digital maturity models can be defined by examining what is measured and how the maturity is measured, which is summarized in a conceptual model in order to strengthen the foundation of these models in academia. Secondly, in order to answer the second part of the research question a quantitative cluster analysis of the sampled models and a multidimensional scaling have been conducted to create a meaningful comparison, distinction and classification of the sampled maturity models. Lastly, the insights gained from the qualitative and quantitative analyses are used to create classification-trees that help practitioners to select the maturity model that best fits their organizational needs.
The main findings of the thesis are that digital maturity models assesses the status of a company’s digital transformation by measuring what the company has already achieved and transformed in terms of their digital initiatives in five main capability areas. Furthermore, the sample of 25 maturity models has been classified in three clusters. Based on the most common properties in each cluster, the classification analysis has shown that the purpose of use and the methodological approach are linked to each other, as the assessment is addressed in more detail when moving from the beginner-oriented (descriptive) to benchmark-oriented (comparative) to the most detailed namely the consulting-oriented maturity models (descriptive, prescriptive, comparative) with regards to the data collection, determination and presentation. The classification-trees are based on aforementioned insights, which help the practitioner to select the most appropriate maturity model in a systematic manner.
|Educations||MSc in Business Administration and E-business, (Graduate Programme) Final Thesis|
|Number of pages||138|
|Supervisors||Till J. Winkler|