A Logical Evaluation of Deep Learning Based Quick-Fix Mentality Impact on Personal and Professional Growth

When things get out of hand, people tend to take swift action to restore order. When it comes to organizational setups, a complete grasp of issues is necessary for gauging the importance of change, and then well considered corrective measures are required. The purpose of this research is to fill gaps in our understanding of the connection between a “quick fix” attitude and various results. In addition to exploring QFM's function in organizational growth and personal fulfillment, this research seeks to understand its impact on organizational behavior. In order to have a thorough grasp of quick-fix attitude, the material generated since 1983 in various publications worldwide was chosen and evaluated. A reasonable conclusion was reached by subjecting the literature to content analysis. In order to assess the efficacy of the suggested scheme, this exercise allowed the study to synthesize a comprehensive view of the subject based on a deep learning association called Elevated Learning for Quick-Fix Mentality Analysis (ELQFMA), which is cross-validated with the conventional learning scheme called Linear Regression Analysis (LRA). According to the results of this study, trust in organizational procedures, employee engagement, productivity, and commitment are all negatively impacted by adopting a mentality focused on fast fixes. Limiting the harm with a quick remedy is possible, but proposing it as a philosophy is difficult. Rather than embracing a mindset that values rapid fixes and habitually makes choices, this article advocates for a philosophy that recognizes the significance of due process.