Best Sales Selection Using a Combination of Reciprocal Rank Weighting Method and Multi-Attribute Utility Theory

Abstract

The best salespeople are individuals who are not only able to meet or exceed sales targets, but also demonstrate exceptional skills in building relationships with customers, understanding their needs, and offering effective solutions. The problem of selecting the best salespeople often involves the challenge of an objective and fair assessment, as diverse evaluation criteria can affect the final result. One of the main obstacles is the presence of subjectivity in judgment, which can arise from personal preferences or pressure to maintain good relationships. This study aims to implement a sales performance evaluation model that combines the Reciprocal Rank Weighting and Multi-Attribute Utility Theory (MAUT) methods to obtain a more accurate and objective assessment of sales performance. This research contributes to the management literature and decision support systems by offering a new approach in sales performance evaluation. This opens up opportunities for further research and practical applications in the field of performance evaluation and salesforce management. Based on the final score calculated using the MAUT method, the salesperson rank from best to lowest is as follows: Sales 7 is ranked top with a value of 0.646, indicating the best overall performance. Sales 3 followed in second place with a value of 0.6125, followed by Sales 9 with a value of 0.5604 in third position.