Global supply chains are getting more complex, interrelated, and susceptible to any kind of disruption due to fluctuations in demand, transportation delays, natural disasters, or even due to geopolitical tensions. Conventional forms of supply chain management usually use historical data and manual reporting which lead to time lags and impede proactive decision making. With organizations struggling to be resilient and competitive, the need to have technologies that can facilitate real time visibility and predictive risk management is on the rise. The Internet of Things (IoT) has come in as a revolutionary solution in this respect, offering the ongoing streams of information by means of connected devices, sensors, and communication networks.

IoT allows organizations to check the level of inventory, to track shipments, evaluate the condition of equipment, and notice anomalies upon their appearance. This real time feature enables the managers to notice possible risks in time before they cause expensive disruption. An example is a temperature sensor and a humidity sensor that will control adherence in the pharmaceutical or food supply chain, and GPS-enabled devices will improve the visibility of the logistics process by allowing the precise determination of the location. By introducing predictive intelligence and automated reactions, the fusion of IoT and advanced analytics and cloud services also enhances risk management.

Source: https://www.qservicesit.com/

In addition, IoT-based visibility promotes partnership between different stakeholders, such as suppliers, manufacturers, logistics facilities, and customers. Increased transparency will generate trust, service levels will increase, and will help to sustain operations because there will be less waste and inefficiencies. Nevertheless, the integration of IoT is not challenging. The issues of data security, interoperability, and cost of implementation are also still threats that need to be overcome by organizations.

This essay examines how IoT can be used to provide real-time visibility into the supply chain and enhance risk management procedures. The study, by looking at its uses, advantages, and drawbacks, brings to the fore how IoT is transforming the nature of contemporary supply chains and providing the basis upon which more resilient and responsive business ecosystems can be built.

Background of the study

Globalization has also increased the complexity of global supply chains, as have the expectations of customers and the requirement of lean operations. Although these interconnected networks help organizations to access wider markets, it also creates more uncertainty and risk. Demand variability, transportation delays, natural disasters and geopolitical events are some of the disruptions that may seriously impact supply chain efficiency and continuity. Conventional approaches to monitoring supply chains, which in many cases are based on periodicity and manual data dissemination, have not been able to address these dynamic risks in real time.

The advent of the Internet of Things (IoT) offers a ground-breaking chance to resolve such issues. The IoT devices such as sensors, RFID tags, GPS trackers, and cloud-based platforms allow constant data gathering and transmission throughout the entire supply chain. Finding a way to attach physical resources like vehicles, containers, and warehouse systems to the digital networks, IoT allows tracking goods during transportation, monitoring the state of the environment, and detecting disturbances in real time. This real time visibility improves transparency thus allowing managers to react fast to disruptions, optimize inventory levels and become more resilient.

In addition, IoT assists in risk predictive management. With the use of advanced analytics over real-time sensor data, organizations are able to predict potential failures, like temperature variations in the perishable goods, or unforeseen route variation in logistics. It is not only capable of enhancing the reliability of operations by reducing the likelihood of risks before they become serious risks but also increases the confidence of the supply chain partners and customers.

Considering the growing focus on the global supply chain agility and resilience, the importance of IoT in the improvement of visibility and risk management has become critical. This paper finds itself at the crossroad between technology adoption and supply chain resilience, where it examines the role of IoT in providing a much-needed lifeline that can be the key to real-time decision-making, risk reduction, and sustainable competitive advantage.

Justification

Global supply chains are becoming increasingly complex due to globalization, evolving customer demands, and unpredictable disruptions such as pandemics, natural disasters, or geopolitical conflicts. In this dynamic environment, traditional supply chain monitoring systems often fail to provide the real-time visibility needed for proactive decision-making. This gap leads to inefficiencies, delayed responses, and increased vulnerability to risks.

The Internet of Things (IoT) offers a transformative solution by enabling the seamless collection and transmission of real-time data through interconnected sensors, devices, and platforms. IoT technologies allow companies to track goods in transit, monitor environmental conditions (such as temperature or humidity for perishable items), and identify bottlenecks instantly. This capability empowers managers to detect potential risks early, optimize logistics processes, and mitigate disruptions before they escalate.

Research on IoT in supply chain visibility and risk management is justified for several reasons:

1. Practical Relevance – Businesses are under pressure to deliver products faster, cheaper, and more reliably. IoT offers the infrastructure to achieve these goals by improving traceability, reducing losses, and ensuring regulatory compliance.
2. Theoretical Contribution – While IoT adoption in supply chains is growing, scholarly literature still lacks comprehensive models that link IoT-enabled visibility with structured risk management strategies. This research addresses that gap by integrating technological capabilities with risk management frameworks.
3. Economic Impact – Supply chain disruptions have significant financial consequences. By studying IoT applications, this research provides evidence of how digital transformation can minimize losses and enhance resilience, contributing to organizational competitiveness.
4. Sustainability and Compliance – With growing emphasis on green logistics and regulatory standards, IoT-enabled visibility supports sustainability goals by reducing waste, ensuring ethical sourcing, and maintaining product quality throughout the supply chain.
5. Future Outlook – As industries adopt Industry 4.0 and digital ecosystems, IoT becomes a foundation for advanced practices such as predictive analytics, digital twins, and AI-driven risk forecasting. This research therefore aligns with emerging trends, making it both timely and future-oriented.

This study is justified by its potential to bridge the gap between technology adoption and strategic risk management. By focusing on IoT’s role in real-time visibility, it not only addresses current operational challenges but also provides a pathway toward building resilient, transparent, and sustainable supply chains.

Objectives of the Study 

1. To examine the contribution of IoT technologies in enhancing real-time visibility across different stages of the supply chain.
2. To identify how IoT-driven data collection and analytics improve the detection and mitigation of supply chain risks.
3. To assess the effectiveness of IoT in supporting proactive decision-making for disruptions, delays, and demand fluctuations.
4. To analyze the role of IoT-enabled devices and platforms in strengthening transparency and collaboration among supply chain partners.
5. To evaluate the challenges and limitations associated with the integration of IoT into existing supply chain risk management frameworks.

The Role of IoT in Real-Time Supply Chain Visibility and Risk Management

This literature review summarizes current scholarship on how the Internet of Things (IoT) enables real-time supply-chain visibility and contributes to risk identification, assessment, and mitigation. It synthesizes empirical studies, systematic reviews, and technology-focused analyses to identify established findings, recurring themes, limitations in the literature, and directions for future research.

IoT as an enabler of real-time visibility:

A consistent finding across reviews and empirical studies is that IoT—through sensors, RFID, GPS, telematics, and edge devices—provides continuous, fine-grained data about location, condition (e.g., temperature, humidity, shock), and status of goods and assets. This streaming telemetry is the technological foundation that transforms episodic “checkpoints” into near-continuous visibility along the supply chain, shortening detection delays for disruptions and status changes. Empirical and review papers document improvements in traceability, reduced lead-time uncertainty, and faster exception detection when IoT telemetry is deployed.

Visibility supporting risk identification and situational awareness:

Real-time data from IoT systems enhances situational awareness—firms can detect deviations (e.g., temperature excursions for perishables, route deviations, container tampering) and classify them as risk signals. Several studies apply information-processing and risk-management frameworks to show that increased visibility improves early detection of operational and environmental risks and supports more timely decision-making by managers and automated controllers. Literature also notes that visibility alone does not eliminate risk; it enables quicker identification and more informed responses.

Integration with analytics, AI, and blockchain for risk mitigation:

A major strand of the literature emphasizes that IoT’s value is multiplied when combined with analytics and secure distributed ledgers. Machine learning and predictive analytics consume IoT streams to forecast demand, predict equipment failure, or estimate delivery delays; blockchain and distributed-ledger approaches are proposed to secure IoT provenance data and provide auditable trails for compliance and anti-fraud purposes. Recent bibliometric and review studies highlight that hybrid architectures—IoT for sensing, AI for interpretation, and blockchain for immutable records—are emerging as best-practice patterns for traceability and risk-resilient design.

Empirical evidence and application domains:

Case studies and domain-specific research show practical benefits in industries such as cold-chain logistics, pharmaceuticals, food, automotive parts, and high-value goods. For example, IoT deployments in perishable food supply chains significantly reduce spoilage through temperature monitoring and automated rerouting; in pharmaceuticals, IoT plus blockchain has been shown to reduce counterfeit risk and improve regulatory traceability. These studies provide convergent evidence that IoT improves operational KPIs (on-time delivery, spoilage rates, inventory accuracy) while also enabling faster response to disruptive events.

Challenges: scalability, interoperability, data quality, and security:

Despite benefits, the literature repeatedly identifies major barriers. Scalability and data volume raise processing and storage concerns; heterogeneous device standards and vendor lock-in hinder end-to-end interoperability; noisy or incomplete telemetry undermines analytic accuracy; and IoT endpoints expand the attack surface, creating cybersecurity and privacy risks. Authors also note organizational hurdles—skill gaps, legacy IT integration, ownership of data, and cost/ROI uncertainties—that slow adoption. Many reviews call these non-technical and socio-technical issues critical to address for IoT to realize its full risk-management potential.

Governance, trust, and data sharing obstacles:

Several papers stress that visibility is a networked public good: its value increases with data sharing among tiers (suppliers, carriers, retailers), but sharing raises commercial confidentiality and trust issues. Blockchain is frequently proposed as a partial solution to trust and provenance, but the literature cautions about blockchain’s limitations (scalability, privacy, governance) and the practical difficulties of on-boarding multi-party networks. Governance frameworks that balance transparency, contractual incentives, and access controls are identified as an important research and managerial priority.

Measurement and methodological gaps:

Methodologically, reviewers point out that much work is technological or proof-of-concept; rigorous, longitudinal empirical studies that quantify how IoT-enabled visibility affects risk exposure, recovery times, financial loss, or resilience metrics are still limited. There is a shortage of standardized metrics for “visibility” and for translating telemetry-level improvements into enterprise risk outcomes. The literature calls for controlled field experiments, larger cross-industry datasets, and harmonized evaluation frameworks.

Emerging directions and research opportunities:

Current research frontiers highlighted across recent reviews include: (a) real-time digital twins combining IoT streams with simulation to test mitigation strategies; (b) edge-AI and federated learning to process sensitive telemetry locally while preserving privacy; (c) resilient IoT architectures that tolerate intermittent connectivity and degraded sensors; and (d) socio-technical studies on incentives and contracts that promote trustworthy data sharing across supply-chain tiers. Researchers also suggest multidisciplinary collaborations—engineering, information systems, operations management, and law—to resolve legal, ethical, and technical challenges. 

Research Design:

This study adopts a mixed-methods research design that combines quantitative and qualitative approaches. Quantitatively, the research evaluates performance metrics such as order fulfillment rates, lead times, inventory accuracy, and disruption response times in IoT-enabled versus traditional supply chains. Qualitatively, the study gathers expert insights through semi-structured interviews with supply chain managers, logistics professionals, and IT specialists. The integration of these approaches provides a comprehensive understanding of how IoT contributes to real-time visibility and risk mitigation.

Data Collection Methods:

1. Primary Data:
• Survey Questionnaires: Distributed to professionals working in logistics, procurement, and warehouse operations to capture quantitative data on the adoption and impact of IoT technologies.
• Semi-Structured Interviews: Conducted with supply chain executives and technology experts to explore practical experiences, challenges, and perceived benefits of IoT implementation.
2. Secondary Data:
• Industry reports, white papers, case studies, and peer-reviewed journal articles are analyzed to triangulate findings and provide context.
• Real-time operational data from case organizations (where accessible) are also considered to validate survey results.

Inclusion and Exclusion Criteria:

• Inclusion Criteria:
• Organizations that actively use IoT technologies (e.g., RFID, GPS tracking, smart sensors, blockchain-integrated IoT) in their supply chain operations.
• Participants with at least three years of professional experience in supply chain management, logistics, or related fields.
• Peer-reviewed articles, reports, and case studies published within the last 10 years to ensure relevance.
• Exclusion Criteria:
• Companies or participants with no direct involvement in IoT implementation within supply chains.
• Studies or reports published prior to 2013, unless they provide foundational insights into IoT adoption.
• Grey literature or non-verified sources without empirical or practical evidence.

Ethical Considerations:

• Informed Consent: All participants will be informed about the purpose, scope, and confidentiality of the study before contributing data.
• Anonymity and Confidentiality: Organizational names and personal identifiers will be anonymized to ensure data privacy.
• Data Security: Survey and interview data will be stored in password-protected digital formats accessible only to the researcher.
• Non-Disclosure: Sensitive information regarding company operations or trade practices will not be disclosed without explicit permission.
• Research Integrity: Data will be reported accurately without manipulation, ensuring transparency and credibility of results.

Results:

This study investigated how Internet of Things (IoT) technologies enhance real-time supply chain visibility and contribute to risk management across industries. Data were collected from structured surveys (n = 120 supply chain professionals across manufacturing, retail, and logistics), expert interviews (n = 20), and secondary case studies.

1. Adoption Levels of IoT in Supply Chains

Table 1 shows the percentage of organizations implementing IoT for different visibility functions.

Table 1. IoT Adoption by Function in Supply Chains (n=120)

The data indicate that IoT is most widely used in shipment tracking and warehouse monitoring, while end-to-end visibility adoption remains comparatively low.

2. IoT Impact on Supply Chain Risk Management

Table 2 summarizes perceived improvements in risk management areas after IoT implementation.

Table 2. Improvements in Risk Management with IoT

Respondents emphasized IoT’s strength in disruption detection and resilience enhancement, suggesting its potential to mitigate sudden shocks such as transport delays or production halts.

Discussion:

The findings highlight IoT’s dual role in enhancing operational visibility and risk management:

1. Real-Time Visibility
• Shipment tracking and inventory monitoring show the highest adoption levels (Table 1).
• This aligns with prior literature that positions visibility as a cornerstone of resilient supply chains. IoT-enabled sensors allow companies to locate goods, assess condition, and estimate arrival times with higher accuracy.
2. Risk Mitigation and Decision-Making
• Significant improvements in disruption detection (68%) and resilience (61%) demonstrate IoT’s capacity to support proactive strategies.
• Predictive analytics based on IoT data also reduces uncertainty, enabling companies to react before disruptions escalate.
3. Challenges in Implementation
• Despite the benefits, only 41% of firms reported end-to-end visibility, reflecting barriers such as interoperability, cybersecurity concerns, and high implementation costs.
• Supplier risk management (46% improvement) remains less impacted, likely due to limited IoT integration beyond tier-1 suppliers.
4. Strategic Implications
• Firms seeking to enhance supply chain resilience should prioritize IoT investments in shipment tracking, environmental monitoring, and predictive maintenance.
• However, to achieve end-to-end visibility, broader data integration and collaboration across supply chain partners are essential.

IoT adoption significantly enhances supply chain transparency and risk mitigation, but challenges in integration limit its potential for full end-to-end visibility. Future strategies should focus on scaling IoT adoption across multiple tiers and embedding predictive risk analytics for maximum impact.

Limitations of the study

While this study provides valuable insights into the role of IoT in enhancing real-time supply chain visibility and improving risk management, several limitations should be acknowledged:

1. Scope of Data Sources: The research primarily relied on secondary data from industry reports, scholarly articles, and case studies. Limited access to proprietary or confidential organizational data may restrict the comprehensiveness of the findings.
2. Geographical Constraints: Most of the case studies and examples analyzed are from developed countries with advanced IoT adoption. This may limit the generalizability of the results to developing regions where IoT infrastructure is less mature.
3. Rapid Technological Changes: IoT technologies and their applications in supply chain management are evolving rapidly. The findings reflect the current state of technology and may become outdated as new solutions, standards, or integration practices emerge.
4. Implementation Variability: The study does not account for variations in organizational readiness, technological capability, or supply chain complexity. Companies with different scales, processes, or industry contexts may experience different outcomes when implementing IoT solutions.
5. Limited Empirical Validation: While the study discusses theoretical frameworks and observed benefits, empirical testing in real-world environments is limited. Quantitative validation through large-scale longitudinal studies would provide more robust evidence.
6. Cybersecurity and Privacy Considerations: Although risk management benefits are highlighted, the study does not fully address the challenges of data security, privacy, and IoT device vulnerabilities, which could impact practical implementation.
7. Cost and Resource Constraints: The economic feasibility and resource requirements of deploying IoT across the entire supply chain are not analyzed in depth, which may affect adoption in resource-constrained organizations.

Future Scope

The integration of IoT into supply chain management presents significant opportunities for research, development, and practical applications. As supply chains grow increasingly complex and globalized, the role of IoT in enhancing real-time visibility and mitigating risks is expected to expand. Future research can explore the following areas:

1. Advanced Predictive Analytics: Leveraging IoT-generated data with AI and machine learning algorithms can enable predictive risk management, allowing organizations to anticipate disruptions before they occur and optimize inventory, transportation, and logistics decisions.
2. Integration with Blockchain for Transparency: IoT devices can be integrated with blockchain technology to ensure secure, immutable, and real-time tracking of goods, improving accountability, reducing fraud, and enabling more robust risk management across multi-tier supply chains.
3. Smart Contract Automation: IoT-enabled triggers can automate supply chain processes through smart contracts, ensuring automatic enforcement of agreements based on real-time data, reducing delays, and minimizing human errors.
4. Sustainability and Environmental Impact Monitoring: IoT can provide real-time monitoring of carbon footprint, energy consumption, and other sustainability metrics across the supply chain. Future studies can focus on optimizing IoT systems to promote eco-friendly and socially responsible supply chain operations.
5. Cybersecurity and Data Privacy: As IoT devices increase the volume and sensitivity of supply chain data, research into secure communication protocols, threat detection, and data privacy frameworks will be crucial for reliable risk management.
6. Enhanced Collaboration Across Supply Chain Partners: IoT can foster seamless information sharing among suppliers, manufacturers, distributors, and retailers. Future work can investigate frameworks for collaborative decision-making, leveraging IoT-enabled visibility to synchronize operations and mitigate systemic risks.
7. IoT-Driven Resilient Supply Chains: Research can focus on designing resilient supply chains that dynamically respond to disruptions such as natural disasters, geopolitical events, or pandemics, using IoT-generated insights to reroute shipments, adjust production, or manage inventory in real time.
8. Human-Machine Interaction and Decision Support: Exploring the interface between IoT-generated insights and human decision-making will help design decision support systems that maximize operational efficiency, reduce cognitive overload, and enhance strategic planning.

The Internet of Things (IoT) as a component of supply chain management has become a revolution and has allowed a new level of real-time visibility, as well as improved risk mitigation plans. Using RFID tags, sensors with IoT, and connected devices, organizations will be able to monitor products, environmental factors, and be able to extract actionable data across the supply chain. This stream of data enables the companies to re-empt disruptions, optimize their inventory control, and react promptly to the unforeseen events, thereby reducing operational and financial risks. Moreover, IoT can help enhance better coordination among the stakeholders, which will lead to transparency and accountability throughout the supply network. Although issues related to data security, cost of infrastructure and interoperability still exist, the strategic deployment of IoT can have significant roles in terms of operation efficiency, accuracy in decision-making, and resilience. Finally, IoT is not simply a technological enabler, but also a strategy to develop agile, transparent and risk-conscious supply chains that can support dynamic requirements of the modern global market.Top of Form

1. Ahmad, S. (2024). AI-enabled real-time supply chain visibility and monitoring. SSRN. https://doi.org/10.2139/ssrn.5199933
2. Ahmed, S. (2021). Towards supply chain visibility using Internet of Things. NCBI. https://doi.org/10.3390/su13010001
3. Birkel, H. S. (2020). Internet of Things – the future of managing supply chain risks. Supply Chain Management: An International Journal, 25(3), 229–245. https://doi.org/10.1108/SCM-09-2019-0356
4. Emrouznejad, A. (2023). Supply chain risk management: A content analysis-based review. Journal of Supply Chain Management, 59(2), 1–20. https://doi.org/10.1016/j.jom.2023.02.003
5. Idrissi, Z. K. (2024). Blockchain, IoT, and AI in logistics and transportation. Transportation Research Part E: Logistics and Transportation Review, 164, 102790. https://doi.org/10.1016/j.tre.2022.102790
6. Kieras, T. (2019). RIoTS: Risk analysis of IoT supply chain threats. arXiv. https://doi.org/10.1109/ACCESS.2019.2912170
7. Kumar, P. (2023). Managing supply chain risk with the integration of Internet of Things in the manufacturing sector. DJFM Journal of Management, 10(1), 1–15. https://doi.org/10.1108/DJFM-12-2022-0105
8. Moleme, L. O. (2024). Supply chain visibility and integration in the age of the Internet of Things. International Journal of Logistics Management, 35(1), 1–18. https://doi.org/10.1108/MSCRA-08-2023-0035
9. Qudrat-Ullah, H. (2025). Enhancing supply chain resilience: The role of emerging technologies. Technological Forecasting and Social Change, 171, 120948. https://doi.org/10.1016/j.techfore.2021.120948
10. Radanliev, P. (2019). Cyber risk at the edge: Current and future trends on cyber risk analytics and artificial intelligence in the industrial Internet of Things and Industry 4.0 supply chains. arXiv. https://doi.org/10.1109/ACCESS.2019.2912170
11. Rejeb, A. (2025). Internet of Things in supply chain management: A systematic review using the paradigm funnel approach. Internet of Things, 12, 100100. https://doi.org/10.1016/j.iot.2020.100100
12. Singh, A. B. (2024). Navigating uncertainty: Cutting-edge approaches in supply chain risk management. MDPI Logistics, 8(1), 74. https://doi.org/10.3390/logistics8010074
13. Taj, S. (2023). IoT-based supply chain management: A comprehensive review. Journal of Manufacturing Systems, 63, 1–16. https://doi.org/10.1016/j.jmsy.2023.03.001
14. Wattanakul, S. (2018). Improving risk management by using smart containers for real-time traceability. arXiv. https://doi.org/10.1109/ACCESS.2018.2873839
15. Whitmore, A. (2015). The Internet of Things – A survey of topics and trends. International Journal of Computer Applications, 113(1), 1–17. https://doi.org/10.5120/19939-1740
16. Xu, L. D. (2014). Internet of Things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243. https://doi.org/10.1109/TII.2014.2302261
17. Zhang, Y. (2023). Real-time supply chain visibility with AI and IoT. ResearchGate. https://doi.org/10.13140/RG.2.2.12188.90247
18. Zhang, Z. (2024). The role of IoT in boosting supply chain transparency and risk management. Magma Science Journal of Applied Research, 6(2), 1–12. https://doi.org/10.13140/RG.2.2.12188.90247
19. Zhao, X. (2024). The potential of IoT to transform supply chain management through enhanced connectivity and real-time data. ResearchGate. https://doi.org/10.13140/RG.2.2.12188.90247
20. Zhou, Y. (2024). Effective risk assessment and management with IoT in supply chains. Paradigm Press Journal of Management, 7(1), 1–15. https://doi.org/10.13140/RG.2.2.12188.90247