An evaluation of the relationship between performance management and increased efficiency in the Department of Education (Ilembe District)

Abstract

This research case study was conducted in the iLembe District; Department of Education. The study investigates how an Employee Performance Management and Development System (EPMDS) is implemented in the Department. The aim of the study was to improve employee’s performance and increase efficiency. The study revealed that there are challenges associated with the implementation of Employee Performance Management and Development System as an appraisal system within the Department of Education (iLembe District). The findings of the study showed that there was no proper training on EPMDS due to limited resources and unavailability of qualified practitioners. Hence, there was inconsistency in the implementation of EPMDS as an appraisal system which resulted in a lack of morale and demotivation in employees’ performance. Another contributing factor to employees lack of motivation was that the department was failing to pay performance bonuses to employees with good performance due to unavailability of funds. Furthermore, employees were not provided with performance outcomes. The study provides new strategies that will assist to improve performance within the District office. Therefore, the study recommends that Human Resource Development should identify and provide new necessary skills, competencies and proper training to District employees. The study further suggests that managers should liaise and provide performance feedback. The study suggests that the department should allocate funds and pay performance bonus to deserving employees. The research employed in this study is the triangulation method. A sample of 100 respondents was drawn from a population of 800 employees in the iLembe District; Department of Education. A non-probability sampling known as purposive sampling was utilised to generate qualitative data and probability sampling was employed to generate quantitative data.