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Logistics & Transport Analytics

Drive digital transformation through advanced analytics with AI/ML. Increase operational efficiencies, increase customer experience and increase new innovative business products.


The logistics and transport industry is undergoing rapid changes and facing numerous challenges. These challenges include the need to reduce costs and improve supply chain efficiency. Problem statements such as route optimization, pick-up and drop-off site planning, fleet management, and traffic management have become critical for the industry.

In order to meet the growing expectations of today's consumers, it is essential for the logistics and transport industry to focus on reducing costs and improving visibility through spatially optimized supply chain solutions.

The GlobeOSS team is well-equipped to assist in this regard.

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Logistics & Transport Analytics
Use Cases


Route Optimization

Spatially optimizing driver routes is crucial in order to deliver a superior customer experience & greater profitability in parcel delivery. 

Identifying optimal routes whilst considering multiple variables such as road conditions, depot status, and driver & vehicle profile is challenging.


Customer Insights

Customer Insights. Know exactly what your customers want, when they want it. And make sure they get it.


Branches and location performance Insights


Customer Value Management




Customer Touchpoints analytics


Root Cause Analytis

Enable engineers to troubleshoot faster.


Customer Intelligence & Next Best Offer

Determine customer loyalty state, next best action, customer lifetime value using AI.

Churn Prediction

Next Best Offer

Automation of Real-time Customer Experience, contextual, digital engagement and customer value.


Predictive Asset Maintenance

Predict the future issues and maintenance. So that this can be proactively handled to maximised uptime.



Pick Up & Drop Off Site Planning

Logistics players are turning to networks of stores or self-serve lockers to serve as pick up & drop off points to reduce their failed delivery numbers.


Using spatial modelling enables supply chain firms to predict demand using new data streams (such as human mobility or ecommerce propensity) as well as to understand catchment areas.



Public Data and Internal Data combination. Hyper-target your campaigns at a deeper granularity


Fleet Management

Using Location Intelligence in the fleet management process allows your company to improve efficiency, reduce costs, and provide compliance with government regulations. Visualizing your fleets assets & optimizing their activity with data streams such as traffic, weather, & routing data can, if done properly, lead to double digit savings for your organization.


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Advanced Data Analytics

Cloud, On-Prem or Hybrid - helping our transport and logistics customers in digital operation, digital customer experience, digital business and digital security and fraud. 

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AI & Machine Learning

Unlock new possibilities and amplify our impact for society and transport and logistics businesses with AI/ML

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Geospatial Data Science

Analysing spatial data combined with analytics and AI/ML for positive transport and logistics business impact.

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Internet of Things (IOT)

With our expertise in data analytics and AI/ML, we will also enable transport and logistics enterprises to create sustainable IOT initiatives - edge, cloud and hybrid.

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Security analytics

Helping our transport and logistics customers in automating SOC, using many supporting tools like data analytics, SIEM, Threat Intelligence, SOAR and Endpoint security.

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