<![CDATA[Employee satisfaction is a crucial factor in the workplace that affects motivation, performance, and overall well-being. Dissatisfaction can lead to high turnover and organizational disruption. Enhancing satisfaction is essential for maintaining productivity and retention. However, gathering accurate data is challenging due to employee hesitancy. Career websites offer a platform for anonymous reviews; however, analyzing vast amounts of textual data can be overwhelming. Moreover, management needs to identify which aspects require priority for improvement. This study proposes a data analytics approach using sentiment analysis and topic modelling to assess employee satisfaction and identify contributing aspects. The method was applied to 9,000 publicly available reviews of Accenture on Glassdoor. The proposed method can provide insights into the positive or negative perceptions of employees towards the company and categorize them based on common topics. Opportunity mapping was then applied to highlight the areas requiring improvement. This study provides insights into employee opinions and identifies aspects that are satisfactory, lacking, or highly satisfying. This approach offers a valuable framework for organizations seeking to enhance employee satisfaction based on comprehensive data analysis.]]>
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