Data-driven organizations in the logistics industry are the younger siblings of fully-grown digital twins

(© Yassay - Pixabay)

Speak to anyone in logistics and they’ll tell you the same thing. Global supply chains continue to be pulled, stretched and yanked to near breaking point as the global economy readjusts in the wake of pandemic lockdowns.

Stung by the experiences of the last couple of years, those looking to insulate themselves and their customers from future disruption are turning to technology to make the supply chain more resilient and better able to cope with the ups and downs of international trade.

The message from the boardroom is clear. Business leaders want to be able to make rapid decisions that support both their customers and employees based on real-time data and accurate information. They want to be able to predict what’s going to happen and take decisions based on intelligent modelling rather than be on the back foot having to respond to events and incidents.

In other words, they want to create a data-driven operation (DDO) capable of delivering greater visibility and new levels of operational efficiency.

It’s a view discussed by Leif Eriksen, Research Vice President, Future of Operations at global market intelligence firm, IDC, who insists that decades of ongoing innovation have erased the technology barriers that have prevented firms from becoming truly data-driven organizations.

The logistics industry is becoming a data-driven operation 

In a recent article, he describes how as a young engineer in 1984 working in a production facility he was tasked with “finding ways to improve the production process” using data trapped in "green screen terminal" minicomputers at a time when the PC was “just coming of age.”

Fast forward to today and things couldn’t be more different. Eriksen wrote: 

The list of technologies available to support the data-driven journey today which weren't widely available even 20 years ago includes cloud technology, ubiquitous wireless technology, mobile computers, AI/ML, and AR/VR.

We have also seen substantial innovation in new sensor technologies and there are very few parameters, if any, that we can no longer cost-effectively measure. 

The availability of technology, though, is only half of the story. That’s because the reason this technology exists is to collect data. Lots of data. And in the world of logistics, that means connecting sensors to assets such as vans, lorries, containers, refrigerated units, warehouses and depots to establish the exact whereabouts of everything in the supply chain.

Samsara’s cloud-based platform doesn’t just gather data from individual vehicles — such as tyre pressures and exhaust emissions — it also gathers information from whole fleets. And when information is gathered from all these places and assets, it doesn’t just provide oversight of a vehicle – or even a fleet of vehicles – but of a whole supply chain ecosystem instead.

Digital twins are born out of data-driven organizations 

Which begs the question. At what point does a DDO become a digital twin? At what point does a DDO become a digital model or replica that mirrors their business and the supply chain? It may not be as advanced as some high-flying examples — such as Roll Royce’s virtual replicas of its aero engines — but the discussions coming out of the logistics industry definitely share a familial resemblance to a digital twin, even if it is in its embryonic state.

For instance, live data flowing from connected sensors means fleet managers can monitor engine wear and tear so that pre-emptive maintenance can be carried out even before a vehicle is due for a trip to the garage.

Real-time monitoring of fuel use can highlight problems in fuel efficiency and identify whether that’s down to the driver or the vehicle. GPS tracking means fleet managers always know the exact location of every vehicle and driver. If vehicles are hauling refrigerated payloads where the temperature is critical to meet food standards, for example, this information can be gathered and relayed in real-time.

And when it comes to safety, live footage from onboard cameras can not only keep a record of what’s happening on the road, but safety systems augmented with artificial intelligence (AI) can also help prevent accidents.

In essence, the data gathered from all the sensors and monitoring systems — and relayed in real-time via the cloud — starts to build a picture of how a business operates. The more data it gathers, the sharper in focus the picture becomes.

Adopting a digital twin revolves around meaningful data

Crucially, the image or model created is not static, but constantly changing depending on the stresses, strain and performance of the supply chain ecosystem.

Of course, you can’t simply go out and buy a digital twin off the shelf. But by gathering data, firms can start to lay the foundations of their own digital twin.

For instance, US-based oil and gas contractor, Delta Constructors, operates 12 permanent sites and hundreds of vehicles and assets across Alaska, North Dakota, and other southern states. After it began its shift to becoming a DDO operation, it’s now able to manage its infrastructure, fleet, and sites all from a single pane of glass.

And they’re not alone. A recent report by Samara found that technology is helping leaders operate efficiently through uncertain times. In particular, it notes that organizations are leveraging sensor-derived data to “optimize efficiency through smarter, faster decision-making.”

It may not be a digital twin in the sense of Rolls Royce’s shining example, but it definitely bears all the hallmarks of a DDO. And if DDOs are the precursor to digital twins, then surely, it’s only a matter of time.