The Ocean Freight Industry is Ripe for Predictive Analytics

The ocean freight industry is navigating uncertain waters, as major changes in technology and the competitive landscape continue to make waves. To complicate things, manual processes and a high number price exception requests get in the way of a quick response, resulting in lost opportunities, and eventually, lost customers.

To add to this, in just the last year, buyouts, mergers and failures have reduced the number of major carriers. Nothing says “industry in flux” better than Hanjin Shipping going out of business in the largest container shipping bankruptcy in 30 years, or the three Japanese carriers joining forces to become ONEShipping.

While this consolidation is to be expected of a maturing industry, some experts consider what’s happening in the ocean freight industry to be cannibalization rather than consolidation. As a result, the biggest companies continue to grow by merging with smaller competitors, leaving a few major players to control a disproportionate share of the market – much like the airline industry a decade ago.

The ocean freight industry has also been losing money in recent years. In the third quarter of 2016 alone, losses reached $1 billion. This exacerbates already existing hurdles shippers are facing, including overcapacity and pricing errors.

But there is hope. Ships are getting bigger and technology is advancing as shipping enters the world of eCommerce. The digital revolution of shipping is producing more data than ever before, and this data can be leveraged to help ocean freight companies better understand their customers and pricing.

Yet none of that will matter if the industry doesn’t move away from old ways of thinking and start running shipping like a business and not just an operation to be maintained. That means developing new and better ways of making decisions, and focusing not only on operational decisions, but on commercial ones as well. And it means an end to the race to the bottom on pricing – a race in which there are no winners.

What if you could unleash your digital capabilities to automate a large portion of your pricing decisions and enable your Pricing Teams to focus on what truly matters: unique customer situations that require their expertise and experience?

Never before has the ocean freight industry been presented with such a clear opportunity to leverage predictive analytics and data-driven insights. Some shippers are finally grasping the potential for predictive analytics to transform pricing into an opportunity to grow both volume and profits at the same time.

Fortunately, this new focus on driving profitable growth is occurring at a time when, as I mentioned, there is more data available than ever. For example, providers like Xeneta offer price benchmarking and rate data analysis for ocean freight rates, insight that was simply unavailable just a year ago in many markets.

With this wealth of data at their fingertips, ocean freight companies would be foolish not to leverage the power of predictive analytics. And they would be even more foolish to ignore history – in their industry (e.g., Hanjin) and others.

The retail electricity business, for example, focused for a long time entirely on operational efficiency. Eventually, deregulation of the electrical market required retail electricity companies to start focusing not only on what it takes to successfully manage the costs of their operation, and begin focusing on what it takes to successfully run a commercial business. Suddenly, they were faced with not only controlling their own costs, but determining market strategy and pricing their products and services in a competitive retail market. It was a disaster.

That’s because they based their decisions on gut feeling and “the way things had always been done”  (something shippers also have relied upon for too long), and not on data and facts. For retail electricity providers, predictive analytics was no longer an option but rather a necessity. And it wasn’t until they approached their commercial decisions with the same level of analysis and data-based decision making that they approached their operational decisions that they saw positive growth and success.

The lesson is simple: If your costs and revenue are not aligned, you will not have profitable growth. You will go out of business. This was true for the retail electricity industry and the airline industry and it will prove to be true for the ocean freight industry.

Ocean freight companies must use predictive analytics to capture the maximum amount of demand at the highest profit point. They shouldn’t choose between profitability and market share, but rather strive for both.

In my next blog, we’ll explore how data-driven analytics are making profit and revenue management possible for ocean freight companies.  Want to learn more about how we can help you unleash your digital capabilities? Contact us at for more information.