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Covid-19 has dealt the whole of global society a punishing blow, but if there’s one industry that’s always been tasked with uniting that society, it’s transport and logistics.

It’s an industry that’s had to rise to the challenge of the pandemic, redoubling its efforts in connecting goods with people like never before, fighting hard against the distances that have held communities apart. Keeping everything as connected as possible, and keeping supply chains open to maintain those connections, has been the primary challenge.

As the world begins to return to something resembling normal, it’s become apparent that the logistics industry as a whole may have been missing an opportunity—since even before Covid-19—to own a much greater stake in its own supply chains. Not just to keep them open, but to entirely reimagine how supply chains work now and could work in the future.

The missed opportunity lies in data. While the logistics industry is of course more than familiar with using data—even to the extent of regularly utilizing AI and machine learning—to bolster the work of its people, that’s barely scratching the surface of the possible.

So far, logistics firms have mostly been using data to build forecasting models and event management algorithms that work absolutely fine; they’re built on the data of things that happened in years gone by, and can fairly accurately figure out what’s going to happen next.

As long as everything works in the way it’s expected to.

As long as, say, a global epidemic doesn’t come along and scatter expectations to the winds.

But that’s exactly what happened, and so it’s important to reflect on what uncertainty really means in logistics, and how things could be done better.

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