| Globalization has resulted in a worldwide production market for both consumers and organizations. Consequently, there is a higher degree of uncertainty associated with the business environment (demand patterns, time to delivery and supplier relationships). A key challenge for organizations to remain competitive in such a marketplace is to quickly respond to any uncertainty, from both cost and efficiency perspectives. It is important for organizations to not only make the right business decisions at the organizational level, but also to generate feasible solutions at the operational level. However, many organizations often fail to simultaneously consider these potential changes to both operations and business processes while making those decisions. Although Enterprise Resource Planning (ERP) systems are expected to provide these decision making capabilities, they are found to be lacking in proactively identifying solutions to these production disturbances and uncertainties. Hence, a framework that enables the integration of the operational models with the business process models is a 'gap' that needs to be addressed.;In this research, a framework that enables an organization to 'optimize' both its operational processes (for example, shop floor or warehouse operations) and its related business processes (such as planning, order management, scheduling and inventory management) simultaneously, is proposed. Moreover, this research uses discrete event simulation technology to study the various "what-if" scenarios prior to decision-making at both operational and business process levels. Discrete event simulation has been used effectively as a strategic, tactical and operational decision making tool, with applications in the manufacturing, services, logistics and supply chain domains. One benefit of using discrete event simulation is the ability to foresee any undesirable consequences.;A unique aspect of this research is the approach adopted to identify the relationships between operational models and business process models. Although there are numerous techniques, such as pattern recognition (through Artificial Neural Networks), designed experiments and attribute-based classifications, that are available for identifying these relationships, they involve numerous assumptions. This research will use two key concepts of Systems Science, General Systems Problem Solving (GSPS) framework and Reconstructability Analysis (RA), for defining the aforementioned relationships. RA is a technique that is used by the systems community to establish the relationships between "wholes" and "parts" (or, systems and sub-systems). This methodology will be evaluated for its applicability in the problem being studied.;The framework developed in this research would enable the integrated optimization of business processes and operational processes in an enterprise. It allows the end-users to effectively manage the business processes and operational processes---a critical factor for success in today's marketplace. Hence, using this framework, called as the Business Process Driven Operational Management (BP-DOM), the impact of a small change in the operational process on the business processes can be studied (and vice versa). |
