Strategic level decision-making is very complex in nature because it consists of numerous variables and most of which cannot be quantified. These decisions are assisted based on the information available, which are both qualitative and quantitative. When comparing of different alternatives, the decision-maker should consider both the tangible and intangible benefits of different alternatives, i.e., fuzziness. The decision may be wrong if one considers only the tangible benefits of the alternatives. So, the intangible benefits should also be considered while making the decision. Generally, it is difficult to quantify these intangible benefits, because they are often fuzzy, complicated and subjective. So, there is a need of a methodology to evaluate both tangible and intangible benefits simultaneously. The conjoint analysis is applied to arrive at the relative weightage for the attributes and the part worth values for the levels using techniques like dummy regression, linear programming and to find an alternative method to arrive at the relative weightage and part worth values in conjoint analysis using analytic hierarchy process (AHP). Validation of the model was done through a real-time example. Copyright © 2009, Inderscience Publishers.