Freight forwarders are the unsung heroes of global trade. Whenever there’s a new supply chain shock, they are the companies we rely on to react fastest, to problem-solve strategies for the world’s foremost brands and manufacturers and, ultimately, to maintain the flow of goods.
It’s a relentless 24/7/365 business and, with so much of a freight forwarder’s work determined by uncontrollable external factors, technology hasn’t always been viewed as an obvious answer to the problems they face. After all, there’s only so much that software can do when it comes to preventing ships from being late.
However, with the world’s supply chains growing ever more complex, amplifying the impact of any shocks, the future of freight forwarding now depends on the industry’s ability to identify areas where technology can make a difference – both to alleviate the burden on teams as well as improve decision-making in the event of the unexpected occurring.
The scalability problem
Freight forwarding is a counter-cyclical business. When demand for goods increases quickly, it creates a massive opportunity for these companies, providing they can rise to the challenge.
But with so much freight forwarding activity reliant on time-consuming manual processes – such as processing customs documents and matching shipping codes – companies generally have little choice but to hire in extra human capacity to meet the spikes in demand.
Hire too few people, and delays and backlogs will quickly occur; hire too many, and they’ll be saying goodbye to their margin. There’s also a global talent shortage for them to contend with, not to mention the problem of what to do with the extra resource once the supply chain volatility eases, and it becomes unsustainable to keep these people on in full-time roles.
At its core, it’s a question of scalability. The world’s supply chain infrastructure cannot scale quickly or effectively enough to meet market demand. So, is there a way that technology can offer a more sustainable long-term solution?
Greater visibility in the control center
Visibility into the real-time progress of cargo has been one of the major technology investment areas of the past few years. On a very practical level, this technology ensures that fewer containers go missing, while there have also been attempts to overlay additional data sets – such as weather forecasting – to boost visibility further and help predict where backlogs may occur.
The jury is still out on the effectiveness of predictive visibility. Decisions still have to be made before ships leave the port (after that it tends to be the captain’s responsibility as to what happens next). And most supply chain ‘shocks’ are so-called because they take everyone by surprise – the result of a complex, interconnected infrastructure that is always at the mercy of myriad external factors.
Freight forwarders don’t just need to see where a particular shipment is at any given moment. Instead, they need technology that will allow them to understand the implications of this information better and take action – for example, determining what updates to communicate to the rest of the supply chain or establishing when to get started on paperwork, rather than waiting until the container shows up in port.
Machine learning tools can play a role here, analysing historical data and real-time updates to provide freight forwarding teams with informed recommendations on what needs to happen next. It’s about turning visibility into actionable intelligence, rather than it serving merely an FYI.
Of course, unexpected external challenges – from terrible weather to ships stuck in canals – will always be a fact of life, but there is still huge potential to improve freight forwarding decision-making when such incidents occur.
The other aspect of shipping visibility that must be considered is the impact on team workloads. Real-time visibility into the progress of a specific container might make a freight forwarding employee better prepared, but it won’t necessarily make their work any less onerous.
That’s why the ultimate goal has to be developing technology tools that automate routine freight forwarding processes based upon real-time insight into shipping progress. For example, when a container is reaching the destination port, the technology will know exactly which forms need to be completed and can source and input all of the necessary information required.
It might sound complicated but, in fact, this level of automation is already firmly within our grasp and capable of cutting the admin burden placed upon freight forwarding staff from around two-thirds of their time to just 10%. That leaves far more time for these employees to focus on providing a more dynamic service and helping clients create strategic solutions to some of their most pressing supply chain challenges.
Freight forwarders that have this type of proactive dialogue with customers will make themselves far more valuable in the long-term – important given that they’re currently facing increased competition from all directions.
Automation and collaboration, hand-in-hand
Current global shipping practices are built upon rigid processes that date back centuries and cannot easily be displaced. However, with visibility, automation and actionable intelligence, freight forwarders will be able to scale up and down more quickly as demand fluctuates, while freeing up human experts to spend more time collaborating with clients on what needs to happen next.
They’ll also be able to lower the barriers to entering the profession – by using the technology to take care of the complex technical details often required in the paperwork. It will mean they can hire more knowledge workers based on their problem-solving or client service prowess rather than their understanding of regulatory nuance.
For decades, freight forwarders have relied upon their human workers to analyse hugely complex, rapidly evolving situations and make smart decisions for their clients. It’s time we gave them the tools to achieve a step-change in the quality of these decisions – for the benefit of the entire supply chain.
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