AN ANALYTICAL FRAMEWORK WITH SENSITIVITY ANALYSIS TO QUANTIFY MANAGEMENT CONSULTANCY SELECTION
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Abstract
This paper provides a comprehensive review and critique of a firm's management consultancy selection, and presents a new analytical framework with sensitivity analysis to quantify the priority of criteria and sub-criteria in the management consultancy selection. The advantage of this analytical framework is that it adds the quantitative precision and sensitivity analysis to increase applicability and ease of use for decision making in the consultancy selection. Through literature reviews and in-depth interviews and case studies, this paper clarifies the importance of criteria in overcoming the difficulty of ex-ante evaluation due to information asymmetries when using the analytic hierarchy process. It also extends the alternatives of consultancy selection from a management consulting company to academic consultants, and explores the possibilities of a dynamic selection mechanism depending on the nature of the problem, and the circumstances. The results show that the most important criterion is the type of solution (43.51%), followed by interviews and case studies or reviews of case studies and consultant’s ability (25.79%), then the type of problem (24.17%), and lastly the perceived benefits of the consulting project (6.53%). Also, the results suggest that a management consulting company is preferred to academic consultants. Further analysis of the Limit Matrix and sensitivity analysis shows that the type of solution, the consultant’s ability and the perceived benefit of the consulting project have direct and dominant influence in the consultancy selection, and the type of problem has the opposite effect in the consultancy selection. This paper contributes to the theoretical research, and improves the practitioner’s ability to achieve a proper selection in management consultancy.
http://dx.doi.org/10.13033/ijahp.v5i1.167
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Multiple Criteria Decision Making, Management Consultancy Selection, Analytic Hierarchy Process, Priority Analysis, Sensitivity Analysis
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