Visual and Ontological Modeling Support for Extended Enterprise Models Sagar Sunkle and Hemant Rathod Tata Research Development and Design Center Tata Consultancy Services 54B, Industrial Estate, Hadapsar Pune, 411013 INDIA {sagar.sunkle,hemant.rathod}@tcs.com Abstract. Modern enterprises have to face changes brought on by multiple change drivers like evolving market conditions, technology obsolescence and advance, and regulatory compliance among others. Enterprises need to create and use both descriptive and prescriptive models such that prescriptive models leverage the de- scriptive models to operationalize optimum strategies in response to change. This paper presents a visual model editor and ontological support for aforementioned kinds of models of enterprise. The editor enables modeling a) motivations be- hind and goals in response to change, b) the AS-IS state of enterprise, c) possible TO-BE states, and d) operationalization model that captures paths from AS-IS to desired TO-BE states. The analyses required are carried out using ontological representation. Keywords: Enterprise Architecture Modeling, Intentional Modeling, Motivational Modeling 1 Introduction For enterprises to respond to changes in an efficient and effective manner requires com- plete understanding of AS-IS architecture, possible TO-BE architectures, a way to eval- uate TO-BE architectures based on some criteria, and an operationalization path from AS-IS architecture to the desired TO-BE architecture. In this regard, earlier we investigated an approach in which intentional modeling was treated as a enterprise problem solving technique [1]. We represented AS-IS enter- prise architecture (EA) models using Archi [2] and intentional models for TO-BE EA using OpenOME [3]. We carried out the evaluation of alternatives in OpenOME. Only a single alternative from amongst the optimum alternatives was then materialized over the AS-IS enterprise model. The AS-IS architecture model coupled with modification and addition of elements and relations would indicate a specific TO-BE architecture. This TO-BE architecture captured the intentional alternative found to be optimum. As we applied this procedure to several real world case studies, we found that it had shortcomings that we enlist below, which became evident when we started modeling large real world enterprise models-