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Evaluation and optimization of innovative production systems of goods and services ” AGENT-BASED PREDICTIVE OPERATIONAL BENCHMARKING MODEL

This research establishes an Agent-based Predictive Operational Benchmarking model (A-POB), an advanced framework with the capability of performing automatic, predictive and comprehensive benchmarking. The model, standing as one critical link on iCognitive’s evolutionary benchmarking roadmap, was designed, developed and implemented to predict companies’ future performance by reviewing and analyzing its past Supply Chain Management (SCM) performance metrics in accordance with the Supply Chain Operational Reference (SCOR) model. A-POB is a six-step process embracing agent-based communication, competitive analysis, advanced benchmarking (by Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA)), prediction by Genetic Algorithm (GA), second time advanced benchmarking, and control and result analysis. A-POB is an updated version of POB, but empowered with agent-based communication and simulation demonstrates higher levels of efficiency and data accuracy. An off-the-shelf A-POB software program was developed to assess SCM performance at the aggregated level while covering both operations and business aspects. It is an effective and efficient tool to examine and forecast a company’s overall strength and sustainability in the future business setting, primarily in terms of profit and growth. Consequently, it enhances strategic decision-making for investments with a long term horizon. Furthermore, the software has been tested for a SCM Benchmarking Study involving 272 companies in South East Asia (SEA). Comparing predictive results against actual data, approximately 45% of companies were positioned in the correct performance category in terms of effectiveness and efficiency.