An Advanced IoT-Based Tool for Effective Employee Performance Evaluation in the Banking Sector

Abstract

Nowadays, high-quality service becomes pivotal to ensure higher customer satisfaction for banking sectors. Through developmental methods, it helps them align their employees and resources to meet their strategic objectives. The challenge is that there is no automatic, strong and intelligent way, which helped the bank sectors to assess employee’s performance after receiving training while keeping scores. In this paper, we design and implement an effective tool based on IoT for assessing employees’ performance by applying the right evaluation metrics. Besides, we aim at determining the necessary information so that the manager has clear strategy that improves performance expectations and keeps it high. We develop also an evaluation model that can take incoming performance data of deployed sensors with work environments, performing data analysis of various employers and determine their performance while customizing the multi-criteria decision-making. The experimental results show that IoT-based tool generates remarkably higher performance than existing tools in the literature for nearly all training programs and all decision-making managers.