In a transportation and logistics context, location intelligence refers to technologies that aggregate supply chain data and apply machine learning to provide insights into the whereabouts and movements of assets, products and human resources. 

The Basics

Location data is familiar to just about anyone who uses a smartphone. Location intelligence is the process of creating meaningful insights into the whereabouts and movements of assets, products and workers. Location intelligence is only possible when you combine location data and technology with internal and external data sources — such as Internet of Things (IoT) devices, carrier, vessel, air cargo and rail data, internal enterprise systems and external logistics systems. This intelligence is then used to optimize business processes — including transport planning, the inbound and outbound flow of materials and products, ETA predictions, the movement of physical assets and human resources within facilities, and all the way to last-mile deliveries. Location technology provides a layer of data that unifies enterprise data silos. Real-time location data and insights are key to building a “resilient” supply chain and managing supply chains from end to end.

The Future

It’s not here quite yet, but the world of business has embarked on a journey toward predictive supply chains. Location data, technology and software are going to play a key role in bringing that vision into reality. Enhanced visibility will contribute directly to supply chain predictability.

Although there has been some progress on this front, most supply chain managers have limited insight into the locations of assets and goods. End-to-end visibility is a struggle because location data is only available when shipments pass through certain staging points. For example, manufacturers will record when goods leave a factory but the location of those shipments is unknown until they arrive at the next supply chain gateway. Without access to consistent real-time information, manufacturers, distributors and retailers often don’t find out about delivery problems until shipments, often worth millions of dollars, fail to turn up. With the application of location technology and real-time visibility, systems can predict delays before they occur and companies can proactively mitigate their effects.

Similarly, companies today are challenged to provide accurate estimated times of arrival (ETAs) for multi-modal shipments, and often opt to buffer their ETAs by building in extra time to compensate for potential delays. With precise, end-to-end tracking and accurate data, shippers and logistics service providers will be able to create leaner and more cost-efficient shipment flows, along with ETAs that reflect the ground truth of asset and product locations. With location intelligence, companies will be able to optimize and automate workflow and decision support across different stakeholders. 

For example, supply chain leaders can optimize operations within facilities such as warehouses, yards and distribution centers. With real-time visibility into the location, movement and productivity of workforces, zones and machines, users can make proactive decisions that reduce costs and boost service levels. 

As sustainability becomes a greater focus for manufacturers and service providers, location intelligence can provide a clearer understanding of a supply chain’s transportation carbon footprint. Understanding this carbon footprint enables operators to optimize accordingly to achieve sustainability goals.

The results: smarter supply chains informed by the visibility of assets, the ability to react in real time and the availability of insights to optimize processes and improve operational efficiencies. By replacing isolated data with end-to-end visibility, location intelligence will contribute to the development of predictive supply chains — yielding operations characterized by collaboration, responsiveness, risk mitigation, agility and optimization.

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