What’s next in logistics?

what's next in logistics

As we move forward, technology and logistics are not only improving; they're coming together in a seamless blend of efficiency and innovation.

The true essence of innovation lies in recognising our strengths and limitations. While machines excel in consistency and precision, humans bring irreplaceable value to dynamic and unpredictable scenarios. This synergy is crucial, especially in areas where autonomous technology, like self-driving vehicles, faces challenges.

Watch the short video to get an idea of Sentispec's take on this topic:

 

So what trends are we envisioning for the next five years within tech and within logistics, whether it's AI, computer vision or anything else? 

It's very clear that there are very many manual operations in logistics. But we need to rethink which parts of this operation is suitable for human operation and which parts are not. So if you look at what humans are really bad at – high volume, high precision, repetitive tasks, like reading barcodes – we're not very good at that. A computer is really good at that.

If you look at what humans are good at, it's making almost intuition based, complex decisions in dynamic environments. Computers are really bad at that, which is also why self-driving cars have trouble. 

Parts of it can be automated. There are things that are predictable and those you want to take away from the human and give to the machine. You always want the human to be in control.

We need to fundamentally rethink who should be doing what, who's good at what, and start moving those things around. At the moment, the vast majority of work is still manual. And we want to change that. And that's what we're seeing generally across the industry.

Start with the business case

I'd say those who are successful are the ones who start with the business case. Ask yourself, What is the business case for doing this? When it comes to volume estimation the business case writes itself. Whereas when you look at for example congestion monitoring of a warehouse floor by looking at how the fork lifts and the people move – that is very hard to do a business case for. If you start with a business case, it typically ends well.

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