Article Published in CSIMQ Journal

We are happy to see the first article in the domain of EA Debt being published. It results from two Master’s theses and addresses the need to more effectively identify EA Debts in organizations, as previous approaches were time-demanding. A first set of interviews revealed an additional list of candidates for EA Debts. Having identified EA Debts, the question arises of when a debt is perceived as “bad” or “good” for an organization. Therefore, an approach is suggested for how experts can determine thresholds for a certain EA Debt.


The term Enterprise Architecture (EA) Debts has been coined to grasp the difference between the actual state of the EA and its hypothetical, optimal state. So far, different methods have been proposed to identify such EA Debts in organizations. However, these methods either are based on the transfer of known concepts from other domains to EA or are time and resource intensive. To overcome these shortcomings, we propose an approach that uses an interview format to identify EA Debts in enterprises and a method that allows a qualitative assessment of identified EA Debts. The proposed approach is supported by the designed framework that consists of an interview format and a process for determining thresholds of certain EA Smells.

Related Publications

Daoudi, Sara; Larsson, Malin; Hacks, Simon; Jung, Jürgen

Discovering and Assessing Enterprise Architecture Debts Journal Article

In: Complex Systems Informatics and Modeling Quarterly, no. 35, pp. 1–29, 2023.

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