Analysis of the Scale Types and Measurement Units in Enterprise Architecture (EA) Measurement

Aim/Purpose: This study identifies the scale types and measurement units used in of enterprise architecture (EA) analyzes admissibility mathematical operations used. Background: The majority solutions proposed EA literature are based on researchers’ opinions many with limited empirical validation weak metrological properties. means that results generated by these may not be reliable, trustworthy, or comparable, even lead to wrong investment decisions. While proposes a number solutions, designs measure have yet been independently analyzed. It is imperative community works towards developing robust, widely accepted solutions. Only then can senior management make informed decisions about allocation resources for initiatives ensure their yields optimal results. Methodology: In previous research, we identified, through systematic review, classified them entity types. subsequent study, evaluated metrology coverage from both theoretical perspective. was designed using combination evaluation theory, best practices software including context model, representational theory evaluate whether satisfy criteria. research reported here presents more in-depth analysis within each type, operation examined terms inputs, transformations operations, impact types, outputs. Contribution: adds body knowledge offering metrology-based approach analyze design better validity type use explicit allow consistency usage decision-making models. Findings: findings this reveal some important quantification issues overlooked literature: produce numbers unknown often result an aggregation undetermined assumptions rather than quantitative knowledge. significance such uncertain, leading suffered information loss lack clear meaning. also unclear if it appropriate add multiply together. Such deemed low quality could potentially incorrect serious costly consequences. Recommendations Practitioners: provide valuable insights professionals field EA. Identifying limitations weaknesses existing indicate, instance, practitioners should wait before until has strengthened. addition, choices select robust design. This, turn, will benefit architects, engineers, other decision making, enabling take into consideration factors adequately as cost, quality, risk, value when assessing features. study’s thus contribute development reliable effective Recommendation Researchers: Researchers greater confidence admissible develop new Other researchers carry address identified propose improved ones. Impact Society: Developers, managers making inappropriate seriously flawed providing undue waste bad Better tools ultimately domain, domains long history rigor tools. advancements practitioners, meaningful measurements making. Future Research: described explicitly applied evaluating examine respective