How to harness vast volume of data and turn it into actionable insights that benefit customers and stakeholders?

The explosion of big data over the past few years has profoundly impacted all industries. With the proliferation of connected devices and gadgets used by consumers and businesses, we are generating and exchanging more data than ever before. The challenge for businesses across all sectors is how to harness this vast volume of data and turn it into actionable insights that benefit their customers and other stakeholders.

Despite the potential benefits, the logistics industry has been slow to fully embrace the big data revolution. While other industries have significantly progressed in leveraging data to drive better outcomes, the logistics industry has lagged. As an industry, we have been slow to adopt modern data management and analytics approaches.

At CEVA Logistics, we recognize the importance of harnessing big data to drive value for our customers. We believe that in order to be the logistics partner our customers and carriers deserve, we need to be able to use AI and machine learning to optimize our customers’ freight flows in real-time across the globe.

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Connecting the different parts of the company

The first main barrier to overcome is the industry’s data architecture. For many companies, data is still locked away in silos around individual transport modes (ocean, air, ground, etc.) These modes of transport often use different systems, with limited interoperability through a common data architecture. The logistics industry has traditionally focused on transporting items from point to point. While simple, it is a model that must change.

All around us, we are watching the industry evolve. Customers want more control and transparency for the entire journey of their shipment. Omnichannel distribution and virtual warehousing are beginning to disrupt traditional point-to-point logistics models. Sustainability is a major topic that is thankfully here to stay as we search for better ways to transport customer shipments.

To respond to these changes, we must revolutionize our approach to data. We must bring it all together and see it as one singular repository of valuable intelligence. To do this, companies will have to build an enterprise data architecture and be more open to sharing data with partners — with good data governance structures and framework, of course.

At CEVA, we are well underway with this process, and I’m confident in the roadmap that our Chief Data Officer, Karl Prag , and his team are implementing to lead our ambitious data, analytics and AI agenda. Their experience — and vision — in this field are impressive.

Creating value for the customer

With the right data in the right place, logistics companies can create immense value for their customers by offering a seamless and tailored experience.

Imagine a scenario where customers can prioritize preferences such as speed, cost, and environmental impact, all while being supported by smart algorithms that update their options in real-time. Similar to how we book our own travel arrangements, we can let customers tell us what’s important to them and then let our systems optimize the transport—from departure locations and transit times to transportation modes and solutions.

In addition, as sustainability becomes an increasingly important topic, logistics companies can leverage data and AI to make more eco-friendly decisions. By providing customers with CO2 emissions information and sustainable transportation options, logistics companies can help customers make more environmentally conscious choices during every minute and at every step of the shipment, reducing their carbon footprint significantly. A recent BCG study found that the impact of this kind of reactivity can lead to a significant reduction of all three key variables: speed, cost and CO2 emissions.

In short, by harnessing the power of data and technology, logistics companies can create a more customer-centric and sustainable industry.

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Responsive logistics

As big data in logistics evolves, the next stage of value creation is to use data to be more dynamic and to predict demand and disruption. Let’s call this “responsive logistics.” This will involve real-time tracking, AI and machine learning — all of which will enable logistics companies to truly implement concepts like virtual warehousing and pro-active disruption handling.

Here’s a simple example of responsive logistics in action. A delivery of critical components is planned to be sent to a customer’s factory (A), but the data shows that stock levels at factory A are satisfactory while the level at another factory (B) is running low. AI could be used to spot this need and automatically re-route the delivery to factory B. Being able to dynamically optimize deliveries in real time would offer significant value to the customer and give logistics companies like CEVA a competitive advantage, as we can tap into all types of transport and use our extensive network to support any customer need.

Of course, this would rely on the customer sharing their stock levels. For this to work, the logistics industry needs secure relationships built on trust, where data governance best practices are applied, and clear agreements are in place. At CEVA, we have long-lasting relationships with our customers because of our commitment to partnership and the co-creation of value in the global economy. The length of our average customer relationship is currently more than 20 years, so when it comes to data, we understand that we are only custodians of our partners’ data, not owners. That’s why we will only request data to securely use it in co-creating value with our clients—never to sell or exploit the data.

Bringing long-term value through seamless data networks

The logistics industry is now at an inflection point. Technology and data have been the future, but their implementation over the next 3-5 years will make all the difference between leaders and laggards. The market needs more control, flexibility and transparency over its shipments, and the data exists to provide this agility.

To create value, our industry must adopt and advance a mindset focused just as much on building seamless data networks as on physical distribution networks. We must build strong connections in our data sets that mirror the relationships between the real-world people who drive this industry forward.

Iterative innovation (‘faster horses’ as the saying goes) won’t be enough. We need visionary leadership about the use and value of data.

At CEVA, I’m excited about our plans and what they will do for our industry. As I write this, we are building the foundations for a more sustainable, responsive and efficient future, and we will never stop trying to find better ways to use data to serve our customers and the world.