A Measurement Method for Quantifying Application Landscape Complexity with Enterprise Architecture

The Information Technology (IT) landscapes of large enterprises are in constant transformation, leading to complex application ecosystems with overlapping functionality and data. Without effective tools to measure and manage this complexity, organizations incur higher costs, inefficiencies, and delayed decision-making. The main contribution of this paper is the proposal of a systematic method that addresses the problem of measuring Application Landscape Complexity (ALC) through Enterprise Architecture (EA). Supported by a mixed research methodology for literature review and case study analysis, we identified three key indicators that significantly capture ALC: number of interfaces, functionality overlaps, and data overlaps. We operationalised these indicators in a measurement method along with a prototype, enabling the derivation of a tangible complexity score from EA models. The method was evaluated using expert opinion and used in a real-world setting to derive a complexity score, demonstrating its practical applicability. By providing a structured way to interpret ALC, this research contributes by offering EA practitioners a method and a tool to quantify application landscape complexity and support decision-making. The method exemplifies how socio-technical artefacts can be designed and evaluated in less controllable, real-world contexts, providing insights into the costs and management strategies associated with IT landscape complexity.