E ISSN: 2583-049X
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International Journal of Advanced Multidisciplinary Research and Studies

Volume 3, Issue 1, 2023

A Proposed Framework for Integrating Employee Retention Systems with Operational Productivity Metrics



Author(s): Abiola Falemi, Rasheed Akhigbe, Olatunde Taiwo Akin-Oluyomi

Abstract:

Employee retention and operational productivity are two critical dimensions that determine the long-term success and competitiveness of modern organizations. However, in many enterprises, these functions are treated as isolated systems, leading to fragmented decision-making and misaligned strategic outcomes. This study proposes a framework for integrating employee retention systems with operational productivity metrics, offering a unified approach to workforce sustainability and performance optimization. The proposed framework establishes dynamic linkages between human capital analytics, performance management systems, and organizational process efficiency. It positions employee retention not merely as a human resource function but as a strategic enabler of operational excellence and continuous improvement. The framework consists of four interconnected layers: (1) retention analytics and employee engagement diagnostics, (2) alignment of job satisfaction indicators with productivity metrics, (3) data-driven decision support for workforce planning, and (4) continuous feedback and performance improvement loops. By embedding data analytics and predictive modeling tools, the framework facilitates real-time monitoring of turnover risk, workload distribution, and performance efficiency. It also integrates qualitative feedback from engagement surveys and exits interviews into quantitative operational dashboards, allowing organizations to correlate employee experience data with productivity outcomes. The model underscores the importance of digital transformation tools such as HR analytics platforms, enterprise resource planning (ERP) systems, and AI-enabled performance trackers to automate insights and foster evidence-based interventions. Through the convergence of human and operational data streams, managers can identify root causes of attrition, optimize team structures, and design incentive mechanisms that directly enhance productivity. This study contributes theoretically by expanding the discourse on the symbiotic relationship between workforce retention and operational performance. Practically, it provides a replicable blueprint for organizations seeking to reduce turnover costs, improve productivity indices, and enhance workforce morale. The integrated framework thus bridges the traditional divide between HR strategy and operations management, supporting sustainable business growth and resilience in dynamic environments.


Keywords: Employee Retention, Operational Productivity, HR Analytics, Workforce Optimization, Performance Management, Data Integration, Organizational Efficiency, Predictive Modeling

Pages: 1704-1724

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