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Abstract The Internet era has raised the demand for skilled workers in businesses and for economic expansion. Businesses find it difficult to expand when trained personnel are shortages. Evaluating and managing exceptionally gifted persons have become more difficult due to technological developments, which have slowed down technological progress and business expansion. The study suggests a technique to quantify how firms develop and employ talent to address this issue. An algorithm called the fuzzy optimized talent cultivation engine (FOTCE) is introduced to evaluate the effectiveness of talent development. The algorithm combines an adaptive neuro-Fuzzy Inference System with Adaptive Hybrid Particle Swarm Optimization. By considering factors including work-life balance, training, involvement, job performance, and satisfaction, the suggested FOTCE algorithm hopes to improve talent strategies and boost organizational competitiveness. The FOTCE algorithm assesses talent development on three levels: overall efficacy, major categories (such as job satisfaction and involvement), and individual indicators within each category. Fuzzy logic handles subjective viewpoints and unclear data in the study, allowing for a more comprehensive assessment. The technique uses fuzzy math to show different levels of employee retention by giving different factors different weights. The results show that the FOTCE technique helps evaluate and upgrade talent development programs and provides valuable insights for better people management when tested with accurate HR data from a company. The findings demonstrate that the suggested FOTCE algorithm outperformed state-of-the-art models like IAA-NRM (83% retention rate) and FAHP (87% retention rate) by a wide margin. Comparatively, FAHP had an EEI of 83% and DEA had 86%. The EEI for this organization achieved 95%. In addition, the FOTCE model showed a higher Talent Development Efficiency Score (TCDES) of 93%, proving that it boosts organizational competitiveness and employee happiness. |
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