Customer-Centric Subjective Vehicle Evaluation by Assigning Weights to Attribute Parameters using Analytic Hierarchy Process

Subjective vehicle evaluation is a critical and established method to validate, engineer, and refine vehicle attributes. Organizations have an array of products catering to different customer requirements and expectations. To achieve better customer centricity and focused vehicle product attribute targets, weightage factoring of its corresponding parameters is essential. Subjective evaluations by vehicle evaluators comprise of providing ratings and feedback about attributes during different development stages of the product. All attribute parameters are presumed to have equal significance to the end customer. At times the end customers have different preferences for different vehicle attribute parameters. The objective of this paper is to demonstrate the use of the Analytic Hierarchy Process (AHP) to obtain the weightage factors for attribute parameters. A conventional method to obtain an overall attribute subjective rating is a simple mathematical average of the sub-attribute ratings. The modified approach detailed in this paper involves weightage factoring for different parameters and derives a weighted average to determine overall attribute subjective rating. Since parameters share relative importance among them it is essential to assign weightage factors considering a defined decision-making matrix using AHP. Priorities are assigned to parameters from the experience of seasoned subjective evaluators and customer requirements concerning the product and its application. In AHP considering the qualitative and quantitative rationale for factors ensures minimizing the deviation of attribute rating from the true value. To elucidate this process weighted factors for ride and handling attributes for a commercial truck operating on highway and city applications are derived. Further, the difference between ratings obtained from conventional and weighted average methods are compared. The two approaches show variation in the final attribute rating and the magnitude of difference depends on a number of sub-attributes and factors used for an attribute. This customer-centric approach will result in precise attributes and higher satisfaction.