Modeling dynamic economic systems
Modeling dynamic economic systems
Putting the enterprise into the enterprise system
Harvard Business Review
Toward an integrated framework for modeling enterprise processes
Communications of the ACM - Homeland security
Modelling of Voltri terminal Europe in Genoa using system dynamic model simulation
ICOSSSE'08 Proceedings of the 7th WSEAS international conference on System science and simulation in engineering
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Nowadays Services and Manufacturing are merging in an unique model of business featuring common drivers of profitability (i.e. customer satisfaction), common goals in operations (i.e. minimize capital investment and be rapid, responsive and flexible) and common enabling factors such as digital electronic computing and communications, better integration between operations, Business Process Re-design (BPR). Therefore, a new management area, called Business Performance Management (BPM) has developed, which is able to set an integration of planned, elaborated and collected performances through an advanced setting of data analysis and summary based on ERP systems. First data seem to confirm that BPM may produce hypothetical improvement in several fields such as banking, financial, medical, pharmaceutical, governmental and manufacturing ones. Actually, BPM represents an evolution of Business Intelligence (BI) based on the idea of Business Activity Monitoring (BAM). The aim of the integration of BAM solutions overtakes the physical boundaries of a deployment or of a department, and the idea of real time (time required for one or more data processing) is not necessarily expressed in nanoseconds but it is rather determined by the business process bill. Therefore, BPM is in general an amount of services and implements offering an explicit management process in analyzing, planning, programming, executive and monitoring areas. Both BPM and CPM (Corporate Performance Management systems) are based on parameters permitting to determine the efficiency of an aspect of the company activity objectively; these parameters have been defined Key Performance Indicators (KPI). Actually, they provide the base for strategic decisions. About 86% of the companies is expecting a competitive benefit reducing the time wasted to collecting and answering to information, while a good 74% of the companies has executive managers demanding IT manager to restrain the clue operation data receiving time. Nevertheless, today only 35% of the companies is able to exploit the benefits received from real time information. What makes the difference between the value expected from applications and the applicability of them in order to goal the planned results? Considering the target to achieve, the proposed methodology is able to link primary performance indicators with objective indicators based on decreasing hierarchical level (top-down) by analyze the existing connection between KPIs as well as the relation between one KPI and the others and identify, at the same time, the relevant coefficients using Multivariate Analysis of Variance and Neural Network Metamodels. From a methodological point of view this process is similar to the identification of the unknown function y = (x1, x2, ..., xn), where y is the dependent KPI and xi are the independent ones. For specific application System Dynamics simulation may replace metamodels to better define interconnections between independent and dependent KPI, by applying Design of Experiment to the simulation output and Response Surface Methodology. Thus, a powerful tool which can effectively support decision making and foreseeing processes is obtained. This is a necessary condition for choosing real priorities and discovering KPI's interconnections in the services business as well as in the manufacturing one. The paper presents the methodology from a theoretical point of view and brief summary of a real life applications to Supply Chain Management, a second application for the Highway maintenance management sector is briefly outlined.