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Introduction

Employee performance tracking is a critical aspect of human resource management in organizations. Traditionally, performance tracking has been done manually, which can be time-consuming and prone to errors. With the advancements in technology, automated systems for employee performance tracking have become increasingly popular. These systems offer benefits such as real-time monitoring, data analysis, and performance evaluation.

This thesis aims to design a system for automated employee performance tracking that can streamline the performance tracking process and provide valuable insights for decision-making. The system will utilize technologies such as data analytics, machine learning, and artificial intelligence to effectively monitor and evaluate employee performance.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Overview of employee performance tracking
2.2 Traditional vs automated performance tracking systems
2.3 Benefits of automated employee performance tracking
2.4 Challenges of implementing automated systems
2.5 Technologies used in automated performance tracking
2.6 Best practices in employee performance tracking
2.7 Case studies of organizations using automated systems
2.8 Regulatory considerations in performance tracking
2.9 Future trends in employee performance tracking
2.10 Gaps in current literature

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Sampling techniques
3.4 Data analysis methods
3.5 Ethical considerations
3.6 Pilot study
3.7 Project timeline
3.8 Budget allocation

Chapter 4: Discussion of Findings
4.1 Overview of data collected
4.2 Analysis of employee performance metrics
4.3 Comparison of manual vs automated tracking
4.4 Impact of the system on organizational performance
4.5 Recommendations for implementation
4.6 Limitations of the study
4.7 Future research directions

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Conclusion
5.3 Implications for practice
5.4 Contributions to the field
5.5 Recommendations for future research

Thesis Overview

Designing a system for automated employee performance tracking is a crucial step towards enhancing the efficiency and effectiveness of HR processes in organizations. This thesis aims to address the limitations of manual performance tracking systems by developing an automated system that leverages technology to monitor, analyze, and evaluate employee performance in real time.

Chapter 1 provides an introduction to the topic, highlighting the background of the study, problem statement, objectives, scope, and significance of the study. It also outlines the structure of the thesis and defines key terms used throughout the document.

Chapter 2 presents a comprehensive literature review on employee performance tracking, comparing traditional and automated systems, discussing the benefits and challenges of automated tracking, exploring technologies used, and examining best practices and case studies in the field.

Chapter 3 details the research methodology, including the research design, data collection methods, sampling techniques, data analysis methods, ethical considerations, pilot study, project timeline, and budget allocation.

Chapter 4 delves into a thorough discussion of the findings, analyzing employee performance metrics, comparing manual and automated tracking systems, assessing the impact of the system on organizational performance, providing recommendations for implementation, and outlining limitations and future research directions.

Chapter 5 concludes the thesis by summarizing key findings, drawing conclusions, discussing implications for practice, highlighting contributions to the field, and offering recommendations for future research. Through this thesis, we aim to contribute to the body of knowledge in automated employee performance tracking and provide valuable insights for organizations seeking to improve their HR processes.

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