Aligning Operational Decisions to Enterprise Objectives Through a Dynamic Enterprise Architecture Approach Available to Purchase

As the rate of change in both business models and business complexity increases, enterprise architecture can be positioned to supply decision support for executives. The authors propose a dynamic enterprise architecture framework that supports business executive needs for rapid response and contextualized numerical decision support. The classic approaches to business decision making are both over simplified and insufficient to account for the dynamic complexities of reality. Recent failures of historically sound businesses demonstrate that a more robust mathematical approach is required to establish and maintain the alignment between operational decisions and enterprise objectives. We begin with an enterprise architecture (EA) framework that is robust enough to capture the elements of the business within the structure of a meta model that describes how the elements will be stored and tested for completeness and coherence. We add to that the analytical tools needed to innovate and improve the business. Finally, dynamic causal and agent layers are added to account for the qualitative and evolutionary elements that are normally missing or over simplified in most decision systems. This results in a dynamic model of an enterprise that can be simulated and analyzed to answer key business questions and provide decision support. We present a case study and demonstrate how the models are used within the decision framework to support executive decision makers.