Logisina

Logisina is a term used in some contemporary logistics discourse to denote an integrated, data-driven approach to managing supply chain and transportation processes. It is not a formally defined standard; rather, it functions as a conceptual label for systems that fuse data from multiple sources to support adaptive decision making in real time.

In current practice, logisina descriptions appear in industry discussions, pilot projects, and theoretical papers that explore architectures for interoperable logistics information systems. There is no universally accepted taxonomy or specification, and usage varies by author or organization.

Core ideas associated with logisina include data integration across enterprise systems (ERP, WMS, TMS), IoT sensor streams, and external data such as weather or traffic feeds; real-time analytics and machine learning for forecasting and optimization; dynamic routing and transport mode selection; digital twin-like simulations for planning; and governance, security, and privacy considerations.

Potential benefits cited include improved forecasting accuracy, reduced cycle times, higher delivery reliability, and greater resilience to disruptions; efficiencies in inventory management; and better alignment of capacity with demand. Potential challenges include data quality and interoperability, integration costs, governance complexity, and the need for specialized expertise.

Related concepts include supply chain analytics, logistics optimization, digital twin in logistics, and Internet of Things applications in transportation. As a term, logisina remains informal and context-dependent, serving mainly as a shorthand for exploring advanced, data-centric logistics architectures.