The Adoption of Big Data and Analytics in Logistics Companies

According to research from BluJay Solutions, customer experience is set to become the driving force for supply chain innovation, and with that logistics companies must undergo a technological transformation to improve their use of big data and analytics.


With the onset of the ‘now economy’, customer expectations surrounding product
availability, delivery times, and communication between buyer and seller are continuing to grow, straining the logistics industry, and pushing for a greater need to use big data to become elastic in their service offering.

Value to the customer can come from improvements made through the exclusive use of internal data. Tracking vehicle data is one internal source that can help unlock this value. Through tracking shipments, product availability can be improved across both brick-and- mortar and e-commerce settings, giving customers improved choices. In addition, last-mile delivery tracking can allow adaptive delivery time estimates to be provided to customers, helping them effectively plan for the acceptance of goods.
Internal data though is limited in both its volume and nature.

For companies to truly harness the power of big data they should consider pulling data from a diverse network of sources. By factoring in local weather, geopolitical, and social commentary data, logistics companies can more accurately predict demand and react elastically to this. Consider perhaps issues surrounding the performance of refrigerated delivery trucks in different weather conditions. Through big data, combining internal tracking data of vehicles and external weather data, companies can implement route plans for vehicles that maximise efficiency whilst ensuring products do not go over threshold temperatures.


Logistic companies can also use an elastic service offering if they can predict the peaks and troughs of demand, based on external consumer data, helping to reduce unnecessary expenditure. This complex network of external data requires collaboration between partners if a true end-to-end data set is to be established. Without this, the adoption of big data by logistics companies could become a cumbersome and inaccurate endeavour. A true network of data will allow manufacturers to fully integrate with suppliers giving them information about shipping status, inventory, demand, and capacity.

If suppliers know the demand of a manufacturer over the next quarter, they can scale up and down production, and if logistics companies know the demand, they can plan accordingly to ensure they provide the necessary services.

For businesses to achieve the success they must assure that the data they collect, and use is accurate. External data may provide some organisations with uncertainty as they may not be able to assess its accuracy. Based on this the World Economic Forum’s Platform for Shaping the Future of Advanced Manufacturing and Production have devised a framework for organisations to benchmark themselves against in their adoption of advanced technology and data. This has opened the door for new partnerships to be formed for data sharing and collaboration across the supply chain.