Development of an Analytical Information System for an Outsourcing Company Using the Bradford Absence Factor

The subject matter of this study is the examination of the Bradford Absenteeism Factor as a tool for analyzing employee absences, specifically its use in assessing the regularity and frequency of absences through an interactive dashboard. The goal of this study is to develop an analytical information system based on the Bradford Absenteeism Factor to effectively monitor and manage employee absences in the company. This study addresses the following tasks: analyzing recent studies and publications on the Bradford Absenteeism Factor, identifying unresolved aspects of the general issue, creating an ER diagram for the information system, defining the required functionality and architecture of the analytical information system, developing necessary visualizations and placing them on the appropriate pages of the information system, conducting an experiment to identify trends and patterns in the Bradford Factor based on test data, presenting and discussing research results, formulating conclusions and identifying future development prospects. Research methods: The study involved analyzing employee absence data stored in an SQL database to establish table relationships and prepare the data for further analysis. Power BI was used as a visualization and analytical tool, allowing data integration from various sources and visualized absenteeism metrics. The Bradford Factor calculation, which assesses the impact of frequent short-term absences on team productivity, was the main analytical tool. Additionally, database modeling and ER diagram construction ensured correct relationships within the system. Research results: The study includes an analysis of recent research on the Bradford Absenteeism Factor, identification of previously unresolved issues, the creation of an ER diagram for the analytical information system, the definition of required functionalities and system architecture, development of necessary visualizations placed on relevant system pages, an experiment identifying trends in the Bradford Factor, discussion of the findings, and formulation of conclusions and further development directions. Conclusions: The developed analytical information system for an outsourcing company, based on the Bradford Absenteeism Factor, utilizes Power BI for data visualization and analysis. This interactive dashboard provides convenient access to key absenteeism metrics at various levels, from individual employees to entire departments and projects. It allows managers to quickly and effectively analyze absenteeism, make informed staffing decisions, and promptly address potential issues.

Authors

Publication Details

Journal
Innovative technologies and scientific solutions for industries
Published
2024-12-11
DOI
https://doi.org/10.30837/2522-9818.2024.4.125
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of an Analytical Information System for an Outsourcing Company Using the Bradford Absence Factor

Dmytro Sytnikov, Oleksandr Shulha
Innovative technologies and scientific solutions for industries
Risk and Safety Analysis
article

Development of an Analytical Information System for an Outsourcing Company Using the Bradford Absence Factor

Dmytro Sytnikov, Oleksandr Shulha
article en

Abstract

The subject matter of this study is the examination of the Bradford Absenteeism Factor as a tool for analyzing employee absences, specifically its use in assessing the regularity and frequency of absences through an interactive dashboard. The goal of this study is to develop an analytical information system based on the Bradford Absenteeism Factor to effectively monitor and manage employee absences in the company. This study addresses the following tasks: analyzing recent studies and publications on the Bradford Absenteeism Factor, identifying unresolved aspects of the general issue, creating an ER diagram for the information system, defining the required functionality and architecture of the analytical information system, developing necessary visualizations and placing them on the appropriate pages of the information system, conducting an experiment to identify trends and patterns in the Bradford Factor based on test data, presenting and discussing research results, formulating conclusions and identifying future development prospects. Research methods: The study involved analyzing employee absence data stored in an SQL database to establish table relationships and prepare the data for further analysis. Power BI was used as a visualization and analytical tool, allowing data integration from various sources and visualized absenteeism metrics. The Bradford Factor calculation, which assesses the impact of frequent short-term absences on team productivity, was the main analytical tool. Additionally, database modeling and ER diagram construction ensured correct relationships within the system. Research results: The study includes an analysis of recent research on the Bradford Absenteeism Factor, identification of previously unresolved issues, the creation of an ER diagram for the analytical information system, the definition of required functionalities and system architecture, development of necessary visualizations placed on relevant system pages, an experiment identifying trends in the Bradford Factor, discussion of the findings, and formulation of conclusions and further development directions. Conclusions: The developed analytical information system for an outsourcing company, based on the Bradford Absenteeism Factor, utilizes Power BI for data visualization and analysis. This interactive dashboard provides convenient access to key absenteeism metrics at various levels, from individual employees to entire departments and projects. It allows managers to quickly and effectively analyze absenteeism, make informed staffing decisions, and promptly address potential issues.

Innovative technologies and scientific solutions for industries(4(30))
Decent work and economic growth
Openalex Percentile: Top 77%
Risk and Safety Analysis
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