Identify the Causes of Voluntary Attrition for Highly Valued Technology Employees
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Growing competition and increased IT job opportunities have imposed organizations to reduce the attrition of their highly-valued employees. Retaining employees will help organizations save money and time spent recruiting and training new employees. In this study, I sought to identify major causes of attrition for highly valued employees in IT companies in the United States. Highly valued employees were defined as those with five or more years of experience working in the IT industry, including a minimum of three years as a subject matter expert (SME) in a computer programming language, and those who were promoted at their previous companies. Phenomenology is a qualitative design within the overall qualitative methodology. I used a phenomenological design to identify major causes of attrition for this studied population. I collected data via semistructured individual interviews with six participants who voluntarily agreed to participate in this study. The six participants identified for this study met the defined criteria of highly valued employees. Herzberg's motivational theory is used as the conceptual framework for this study. Data gathered from the interview process were analyzed in three steps. Step one focused on developing and applying codes. In step two, themes were created based on coding. During step three, all the gathered data was interpreted, and themes were created to conclude with the findings of the study. Four causes of attrition were identified from data analysis. The findings of this study could lead to an increase in retention rates of highly valued employees due to a better understanding of causes triggering these employees to look for opportunities outside their company. Retention strategies were developed around the findings of this study to motivate and increase job satisfaction of highly valued employees. For further studies, the recommendation is to conduct research at IT companies outside the United States to validate if these findings apply to all global IT companies.