Technology is opening a realm of possibilities for capitalizing on big data in logistics and the use cases – as well as the benefits – continue to roll in. Here are some of the ways in which logistics enterprises can win from a data-driven approach.

Flexible route and capacity planning

Data is unlocking new efficiencies across many different organisations and logistics is no exception. According to DHL, wide adoption and use of big data in logistics will remould the industry through “previously unimaginable levels” of optimisation; a fine showing of praise from one of the industry’s biggest players.

Starting with a driver’s journey, one role for big data analytics in logistics lies within dynamic route planning - a way of accommodating updates to weather, traffic and orders. In this instance, data gleaned from sensors within a truck, a weather report or similar is used to give advice to drivers on their best possible route.

A similar approach is used for capacity planning, where an operator can use predictive analytics for a look into their availability of assets and personnel to allocate resources where they’re most needed. Such measures prevent the same trucks heading in similar directions and ensure a better, more efficient operation.

Accountability and performance optimisation

The use of data-collecting sensors within vehicles has been huge for the logistics industry, not least due to its intilling of transparency around organisations.

It’s now possible to track the whereabouts of every vehicle to provide updates over a likely time of delivery. For the overachievers, this information can even be used to prove their reliability in the securing of new contracts.

The end goal should be for data to create a more open logistics industry where a group’s all-round performance is put beyond doubt. Again, for the most efficient groups - regardless of their size - it could prove a great signal of worth.