AL BAHARMAST    
Enterprise Integration Inc. (US)

Biography
Al Baharmast specializes in providing business transformation, information technology strategic planning, enterprise architecture and standard software solution implementation advisory services on behalf of Enterprise Integration Inc., an executive consulting firm in the United States. He has recently led sizeable consulting engagements at the United States Army's financial domain, the United States Air Force's logistics domain, the United States Army's Judge Advocate General's Corps. Prior to that, Al served as director of projects at the American Diabetes Association, a non-governmental health organization in the U.S. He received his Doctorate in Organizational Informatics from George Mason University in Fairfax, Virginia, and his Master's degree in International Transactions, also from George Mason University. Al completed his graduate field study in Economics, Trade, Technology and Finance at St Peter's College, Oxford University.

Presentation
Architecture-Driven Standard Software Solution Selection Methodology
The methodology proffered in this presentation defines a streamlined approach for using enterprise architectures to support Standard Software solution selection. Unlike traditional system requirements development, an architecture-driven approach for solution selection is intended to have enduring value by creating a framework for implementation and by delivering a range of artifacts that will have utility throughout the build, deployment, sustainment and reflexive analysis phases of the project. This presentation outlines four distinct cycles in the evolution of the architecture for solution selection – the As-Is state, the Target state, the Gap-Fit analysis state and the To-Be state. The unique value of the methodology described in this presentation resides in its presentation of a practical and expedient approach to developing each architecture state, managing the architecture’s natural evolution and extracting the resources necessary to enable selection of the optimal solution and propel implementation.

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