Modelling of Enterprise Architecture Debt


The idea that different languages are spoken among IT and other departments is a typical challenge in organisations. Fellow employees come from a variety of backgrounds, have different levels of understanding, and occasionally even have conflicting goals, making alignment more difficult. Enterprise Architecture (EA) plays an important role in connecting IT objectives with business goals, potentially resolving business and IT misalignments issues by providing a common language for them and adding more value to companies. There are a lot of approaches to resolve the communication issue and make EA management more straightforward. But there is one concept in this domain that lacks attention. Originally, the term “debt” was borrowed to IT from the finance domain. The concept of EA debt extends its focus to include business aspects. Enterprise Architecture debt is a metric that depicts the deviation of the currently present state of an enterprise from a hypothetical ideal state. To be able to communicate the severity of an EA debt to stakeholders, a management framework was designed. The main challenge in realising management activities is to integrate the employed documentation and communication approaches with the viewpoints and information interests of different stakeholders. And in this work, we try to resolve this issue and provide a tool that will align people in an enterprise providing a ground truth information point. We argue that a possible solution is to communicate EA debt using a modelling approach. As a visualisation tool, modelling adds structure to the management workflow, provides a bigger picture as well as different levels of abstraction for identifying the elements of EA debt. Communicating debt through the use of models will reduce the gap between a problem and an architectural state as they describe complex systems at multiple levels of abstraction and from a variety of perspectives. Therefore, modelling support is needed to specify, document, communicate and reason about EA debt. In this thesis, we introduce the extension for modelling notations which includes the EA debt specific elements to capture EA debt and make it easier to document and communicate it between stakeholders. The study begins with a literature review to collect domain insights and knowledge needed to define use cases of EA debt modelling. These use cases serve as proof of why the EA field will benefit from the modelling tool. Based on this information, we identified six core concepts of EA debt and built a meta-model that represents their relations with each other. Through interviews with experts and practitioners in the field, the developed meta-model was evaluated to ensure that all aspects of EA debt are covered. The expert comments gathered during the evaluation proved that, together with the proposed solution, the EA debt management process would provide more value to stakeholders allowing them to be more confident with their decisions.


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Thesis for degree:



Yevheniia Kashperuk