Maritime analytics involves leveraging data from ships and vessels to gain valuable business and operational insights. It helps monitor ship and cargo operations, detect anomalies and optimize performance. Maritime analytics solutions provide predictive analytics capabilities to predict equipment failures, reduce downtime and maintenance costs. It helps identify inefficiencies, spot trends and anomalies to reduce costs and risks. Maritime analytics is widely used in applications such as fleet management, vessel tracking and monitoring, weather routing, predictive maintenance and cargo optimization. The growing digitalization of vessels and incorporation of IoT sensors is enabling more data capture to drive analytics solutions.
The global maritime analytics market is estimated to be valued at US$ 1275.91 Bn in 2023 and is expected to exhibit a CAGR of 4.5% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics:
Increased demand for predictive maintenance is expected to drive the growth of the maritime analytics market over the forecast period. Maritime analytics enables equipment condition monitoring and predictive maintenance of critical components and assets onboard ships. It helps detect early signs of equipment failure or component degradation and schedule planned maintenance. This reduces downtime and unplanned maintenance costs. Another factor fueling the market growth is increasing adoption of big data and analytics solutions across maritime businesses. Maritime organizations are leveraging available operational data to gain insights, optimize processes and enhance safety and efficiency through big data analytics.
Segment Analysis
The global Maritime Analytics market is dominated by two segments – Asset tracking and Optimization (31%) and Security management (29%). The Asset tracking and Optimization segment tracks and monitors vessels, containers and cargo. It helps in route optimization, weather tracking, ETAs and ensuring safety and security of assets. This segment is dominating as maritime organisations are increasingly adopting analytics solutions to optimize fleet operations and reduce costs.
PEST Analysis
Political: Governments across major economies are implementing regulations around emission control, safety and security which is driving adoption of analytics solutions for compliance.
Economic: Fluctuations in trade volumes and fuel prices impact profitability of shipping lines, forcing them to leverage analytics for efficient operations and cost cutting.
Social: Rising consumer demand is increasing trade volumes globally. However, concerns around environment protection are also growing.
Technological: Advent of IoT, sensors and automation is enabling generation of huge maritime data. Analytics helps extract insights from this data to improve monitoring, planning and decision making.
Key Takeaways
The global Maritime Analytics market share is expected to witness high growth over the forecast period of 2023 to 2030. The global maritime analytics market is estimated to be valued at US$ 1275.91 Bn in 2023 and is expected to exhibit a CAGR of 4.5% over the forecast period 2023 to 2030.
Regional analysis comprises
The Asia Pacific region currently dominates the market due to high trade volumes and growing focus of governments and ports on utilizing digital technologies. China, India and Japan are major markets owing to large fleet sizes and trade infrastructure. Europe is another sizable market led by countries like Germany and UK.
Key players related content comprises
Key players operating in the maritime analytics market are exactEarth, Windward, Spark Cognition, BYTELKE, Ericsson, Cognite, shippeo, and AWS. exactEarth and Windward are leading players focusing on vessel tracking and security. Spark Cognition and BYTELKE offer AI-powered fleet optimization solutions. Ericsson provides analytics platforms for integrating operations across ports and logistics chains
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
