Enhancing Brahms model with multi-layered alerts filtration system for customer service improvement

Abstract

Human behaviour is deeply involved in every field of life in order to perform daily business activities which includes medical, education, industry, politics, sports and science etc. Improved educated behaviour is considered as a gateway to the successful life while irresponsible conduct leads to inefficiency and inconsistency. Quality assurance may be compromised, if the proper human behaviour is not observed while performing job activities in the work practice system. One of the major reasons for the developed countries to progress consistently is to follow the rules in the system across the board. Human behaviour is streamlined and improved gradually with the passage of time to get the best output and results eventually, business activities are flourished and problems of people are resolved. Companies devise plans and strategies to maximize their productivity and profitability, but results are not always encouraging. Regular inconsistent performances are a major cause of corporate failures which may turn into bankruptcy. Employees may make mistakes in the routine business activities including customer service department (CSD) which is a compromise on quality and productivity. It’s challenging and time consuming to address human errors while performing job activities in the work practice system. Employees need guidance and transparent monitoring system to address the possible risk of human mistakes in the workplace environment. Two case studies including Immigration Department and Graduate School of Management in a university are considered to observe human behavior scenarios using ethnography study. Multi-Layered Alert Filtration System (MLAFS) using Brahms Model (BM) has been designed for controlling job activities of employees in the CSD. It detects human errors and generate filtered alerts to employees at the time of the mistakes as necessary actions can be taken to streamline the work flow which improves an institutional efficiency and performance. In this research, we will study the process of human behaviour improvement at the customer service department by using BM and filtered alerts which would minimise human errors and enhance organisational performance. The mechanism for the filtration of alerts would ensure the quality and credibility of the system while concerned employees would be receiving the alerts and messages through mobile or SMS to correct their mistakes. Profit and loss figures could be changed easily by introducing MLAFS from small scale to large scale organisations where precision and great care is required while dealing with day to day business affairs. Damage caused by human mistakes could lead to failure and disastrous situations if it is not addressed properly for a long time. Clear communication for employees in the form of filtered alerts and messages could save organisations from further losses and damages.