Predicting the future with real time data

“When I'm not working for Maersk, every activity I do is data driven, by accident or by design. Be it fly fishing, riding a motorbike or a road bike – I track every aspect of my fitness, my food intake, my energy output. I continually analyze my surroundings when on the motorcycle or when fishing. The opportunities that compiled data can provide you with are just too appealing not to use them,” Holly says. For the past ten months, she has been CDO at Maersk.

Eating, breathing and living data 24-7, Holly is building the bridge “byte-by-byte” between present and future, providing new ground for businesses wanting to dive into integrated logistics.

“For integrated logistics data is the key. It is one of the best assets we have, and for our customers, it's really not any more just about the containers and the ships, but all about optimizing the end-to-end logistics,” Landry explains.

There’s data that helps you improve precision, reliability, durability and then there is data that can lead to new business opportunities. In between, we use synthetic data to understand what data will help!

But generating and collecting data takes time – valuable time. To address that hurdle we look to experience gained in other industries, as Maersk looks to leapfrog the advancements already out – like with synthetic data.

The world of synthetic data has been inhabited by the gaming industry, aviation and many others but logistics companies have been slow to adopt the new ways and the possibilities data brings.

“Basically, we can "re-present” or simulate large amounts of data based on smaller amounts of real data. Through this we can generate features and meet specific needs or conditions which otherwise would not be available in real-world data.” Holly explains.

The processing of huge amounts of real-time data is all about using the present to predict the future. Data is to be looked at as a living thing that changes constantly. The events and scenarios of the future do not look like the events we know from the past.

 
“The future is now and we cannot always rely on past information to predict the future. We extrapolate the future scenarios based on data from the present”, Holly says when asked why one cannot base simulations for the future on past data. For example, historical models didn’t tell us about the great toilet paper global shortage for a global pandemic – but we could see in real-time the event unfolding. For the next pandemic, we don’t know when that will be but we know an enormous shift of paper goods manufacturing and distribution will occur.

Data provides logistics clients with endless possibilities to reduce waste, enter new markets, proactively manage unforeseen events and basically a better ability to turn what might have been problematic situations in the old days to new opportunities. By getting trustworthy input on what is going on in global trade, which markets are underserved, which shortages are building up in the market etc. companies will be able to respond effectively to their customers' needs.

“If you're trying to launch a new product or a new promotion in a specific region we can provide, `hey, here's what's worked before´. And then more importantly, `here's what would probably work in the future´” - Holly says and then continues “..and that is going to make all the difference.”