How big data is helping transform the logistics industry

By some estimates, e-commerce now makes up more than half of all retail sales, indicating that it's clearly something no business can afford to be without if it wants to be successful.

But despite the huge range of innovations that have helped improve the sector over recent years, the final part of the process – the process of physically getting goods from a business into the hands of the consumer – has remained largely unchanged. Although offerings like click-and-collect give consumers more choice, for many people, it's still a matter of sitting around waiting for a courier to show up.

And for the logistics industry itself, it's this part of the process – the so-called 'last mile' between local distribution centres and the customer's home, where the challenges lie, as this is typically the slowest and least cost-effective part of their operations.

However, this is starting to change as more organisations adopt big data analytics and the Internet of Things to give them more insight into where they can make improvements.

Speaking at a supply chain conference recently, Matthias Winkenbach, director of the Massachusetts Institute of Technology’s (MIT's) Megacity Logistics Lab, said these innovations can be a powerful resource for the sector, if businesses are able to effectively harness them.

The Wall Street Journal reports that one of the big challenges is that, while companies have large amounts of data available to them, they often don't know want to do with it, or even understand what it is telling them. But the team at the MIT Megacity Logistics Lab is looking to change this, working with companies such as Anheuser-Busch and Brazilian e-commerce firm B2W to examine what lessons can be learned from last-mile analytics.

For instance, Dr Winkenbach noted that while data-collecting tools can be used to track the progress of delivery vehicles and identify patterns in delivery times in order to better inform route planning, they can also provide "transactional data" that gives a clearer picture of what happens between a delivery truck and a customer's doorstep.

He explained many shippers want to know why some drop-offs take longer than others, a question that was hard to answer in the past as there was very little data available other than that provided from the truck itself.

But advanced geospatial information reveals that longer drop-offs tend to occur in the most densely populated parts of a city, where many people live in high-rise apartments. Mr Winkenbach said this indicates delivery workers are struggling to park, walking farther after parking, and climbing stairs when they get there.

It can also help logistics providers get a better picture of consumer behaviour, such as pinpointing customers who are typically not at home during delivery hours. This is not a factor that is usually factored into route planning, but can greatly impact the efficiency of operations.

The WSJ notes this is all information that can be used to help create more efficient routes, inform training programmes and determine the most suitable delivery vehicles. For example, the data may prove that multiple short-route deliveries on smaller vehicles, including bicycles, makes more sense than bulk deliveries in large trucks.

The results of this should be more effective delivery routes that not only save money for logistics firms, but allow consumers to get their goods faster, thereby improving customer satisfaction from both buyers and retailers.

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