Creating a Data-Driven Asset Tracking Model for Reducing Device Loss in Enterprise IT Operations
Abstract
Device loss within enterprise IT environments poses significant financial, operational, and security risks, particularly as organizations expand their digital footprints across hybrid workplaces and distributed infrastructures. This review examines the development of a data-driven asset tracking model designed to minimize loss, enhance asset visibility, and strengthen lifecycle governance across enterprise IT operations. The study synthesizes existing literature on automated tracking technologies?such as RFID, IoT sensors, barcode systems, and real-time location systems (RTLS)?alongside data analytics methods applied in predictive asset monitoring. Emphasis is placed on how organizations can leverage centralized asset repositories, anomaly-detection algorithms, and machine-learning-based forecasting to proactively identify loss patterns, optimize inventory accuracy, and improve compliance with security and audit requirements. The paper further evaluates integration challenges, implementation barriers, data architecture constraints, and the role of organizational policies in enabling effective asset protection. Recommendations are provided for designing a scalable framework that incorporates advanced analytics, continuous monitoring, and closed-loop feedback mechanisms. This review aims to guide IT leaders, system administrators, and enterprise risk managers in adopting intelligent asset management strategies that reduce device loss and support efficient operational governance.
Keywords
Asset Tracking, Enterprise IT Operations, Data-Driven Decision Making, Predictive Analytics, Device Loss Prevention, IT Asset Management (ITAM).
Citations
IRE Journals:
Taiwo Oyewole, Odunayo Mercy Babatope, Winner Mayo, Jolly I. Ogbole "Creating a Data-Driven Asset Tracking Model for Reducing Device Loss in Enterprise IT Operations" Iconic Research And Engineering Journals Volume 1 Issue 8 2018 Page 211-227 https://doi.org/10.64388/IREV1I8-1713056
IEEE:
Taiwo Oyewole, Odunayo Mercy Babatope, Winner Mayo, Jolly I. Ogbole
"Creating a Data-Driven Asset Tracking Model for Reducing Device Loss in Enterprise IT Operations" Iconic Research And Engineering Journals, 1(8) https://doi.org/10.64388/IREV1I8-1713056
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