Simple Multi-Attribute Rating Technique (SMART)
Contents |
Abstract
Simple Multi-Attribute Rating technique (SMART) is a technique for conducting Multi-Criteria Decision Making (MCDM), in which assessment and selection of the best alternative, amongst the different alternatives, is based on a list of relevant socio-economic criteria. MCDM is a relatively new method for assessing alternatives or projects and it stems from the science of operations research. MCDM differs from traditional evaluations methods like the cost-benefit-analysis (CBA) in multiple ways. Where a traditional CBA compares costs and benefits on a monetary scale, MCDM allows the assessment of alternatives on a monetary as well as non-monetary scale. SMART is considered as one of the main techniques for MCDM and the overall purpose of SMART is therefore to assist the decision maker when trying to choose the best option amongst several alternatives. SMART is based on a linear additive model, which means that a performance score for all individual alternatives can be calculated as the sum of the relative performance of each alternative on each identified evaluation criterion multiplied by the relative importance of that specific criterion (the criteria weight). The best alternative is thus found by calculating a total performance score for each alternative and then selecting the one that reveals the highest total performance score. SMART provides a simple and intuitive method for supporting the decision maker. The method has become fairly popular in recent years and is used throughout many areas of application such as transportation and logistics, problem planning, project selection and manufacturing.
Big idea
Limitations
Explanation of strengths and weaknesses of the SMART tool.
Annotated bibliography
Edwards, W. and Barron, SMARTS and SMARTER: Improved Simple Methods for Multiattribute Utility Measurement Organizational Behavior and Human Decision Processes, Elsevier
DTU Transport, Multi-criteria decision analysis for use in transport decision making, 2014.