With thin margins, high customer expectations and disparate IT systems around the globe, all data – big and small and of various types – is critical to enable transformation of transportation and logistics companies.

While some supply chain companies have used analytics to design logistics and facility networks to streamline their operations, most efforts have been generally narrow and mostly done in piecemeal. Big data was considered ubiquitous with few ways to connect the dots. Today, however, big data analytics is coming of age.

Supply chain managers and distribution experts are starting to embrace big data to provide better customer service, more effective fulfilment, faster responses to supply chain problems, and increased end-to-end efficiency.

“What is new is the speed at which we can help identify business areas ripe for leveraging data,” said Shaun Connolly, International Program Director for Transport, Logistics, Postal, and Supply Chain at Teradata, an international provider of powerful, enterprise big data analytics and services. “The transportation industry is at a turning point.”

That’s because international trade demands transparency, flexibility, and precise decision making.

“Many – I might even say most – transportation and logistics companies still need to integrate and leverage traditional structured data, while others are ready to exploit all data to their advantage,” Connolly said. “Additionally, there is an organizational change that needs to happen, where people rely on analytics and data along with their experience. Quite a challenge, actually and a dramatic change in the way business and IT work together.”

For transportation companies that have been slower at adapting big data analytics, this leaves just one option: get onboard and become data driven. “Otherwise they will be out of business in the next few years,” Connolly emphasized.

Connolly likes to use the quote from American industrialist Henry Ford: “If I would’ve asked people what they wanted, they would’ve said faster horses.”

“Most of the time, people in the business can tell you what they want, but they can’t tell you what they need (an analytic, continuously running against the data, to predict and alert when a customer is likely to churn),” Connolly remarked.

A number of solution providers such as SAP, Accenture, Kewill, Oracle, IBM, and Teradata are involved in game-changing technology that enables clients to have a full view of customer interactions, from customer service calls, website visits, invoicing payment behaviors or services purchased to volume and lanes shipped. “Big data solutions can integrate financial data with operations and commercial data to deliver carton-level or container-level profitability,” Connolly said.

“The output of integrating the enterprise data, allocating cost and revenue for every activity, creates billions of rows of data, enabling our customers to make precise decisions regarding pricing, cost-cutting, capacity, etc.,” Connolly emphasized.

UPS Model

UPS (United Parcel Service) has been implementing big data solutions to his processes since the early 1990s. According to its website, UPS now tracks data on 16.3 million packages per day for 8.8 million customers, with an average of 39.5 million tracking requests from customers per day. The company stores more than 16 petabytes of data.

“In the old days, UPS was trucking company,” commented Jack Levis, senior director of process management, UPS. “Today we are a technology company that has trucks.”

By employing big data software, UPS has created innovative analytic and predictive tools that are available to shippers today.

Its ORION (On-Road Integration Optimization and Navigation) tool shortens UPS truck drivers’ routes and saves the company millions of dollars on fuel.

“We are now deploying ORION on about 42% of our drivers in the United States,” reported Levis. “This is making it possible for us to reduce about 8 miles (13km) per driver.” Once fully deployed by the end of 2016, Levis predicts ORION will save the company US$300-US$400 million per year.

Another tool, UPS My Choice, alerts shippers about incoming shipments to give them the flexibility to reschedule, redirect, or authorize shipment release online so that UPS can leave packages according to their instructions. “Requests can be executed while a package is in flight or drivers or on the road,” Levis said.

UPS’s latest innovation is its package flow technologies, a suite of software and hardware predictive tools, created to optimize the delivery of multiple services to customers (air, ground and international) out of a single delivery vehicle.

“Here we created a virtual network that mimics the physical network that allows us to change the virtual network as well,” Levis said. “We did this so if there is a problem, say, in Chicago, we can reroute around it; or if a customer needs special planning, we can accommodate them.”

The technology employs a smart label that not only allows customers to track and trace their shipments, but allows instructions to be communicated regarding loading and sorting requirements while en route.

Today UPS spends over US$1 billion a year on technology. “Obviously, analytics is part of our DNA. A lot of companies seek us as a business process issue,” Levis said.

Ocean Response

Ocean shipping has long been a black hole for data. “Ocean statistics are still very much old school in terms of batches of information,” said Sandra Moran, a spokesperson for INTTRA.

INTTRA, the world’s largest web portal for ocean containerized freight, connects 54 steamship container companies with some 55,000 clients worldwide. Some 22,000 users access the portal every day.

“As a result, we process 23% of containers that are shipped worldwide,” Moran said.

Steamship lines have predominately used data to analyze the physical location of their ships and fuel consumption. “With many shipments being as long as 30 to 35 days, the ability to accurately predict when a ship will come into port is not great,” Moran commented. “Shippers are looking to optimize and squeeze out every last element of savings from their supply chains, so tolerance for this lack of information is declining.”

But now INTTRA is starting to use real time data like vessel position so that carriers can better predict date of arrival. “We are just beginning to test other data sources,” she added. This includes the impact of factors impacting ocean shipping: weather, port strikes, and other potential disruptions.

“Logistics managers can start thinking about alternate routings or the impact conditions outside of the control of the shipping line will have on their business,” Moran explained.

Currently, INTTRA works with 109 software partners to leverage its platform to transmit information electronically to and from steamship lines. INTTRA is purchasing AIS (automated information system) vessel tracking to aggregate information with shipping data to create these alerts.

“We also are in partnership with the next event in the chain: Bringing into our environment rail data to provide end-to-end supply chain data,” Moran added.

Analytics will provide more history and more actual performance results so that shippers can anticipate what can happen in the future. As a result, 3PLs will be better capable of serving the shipper who can put that same data into practice to get to the next level of supply chain excellence.

“If a company can take their average inventory down by a day or two, or three, they are in a situation where they don’t have to hold as much inventory,” Moran explained. “That can be worth millions of dollars of savings to their bottom line.”

In other words, the big data can help companies absorb the unpredictable characteristics of global trade, and try to find ways to take out slack in the system.

“There are real opportunities for companies that do this,” she said.

By Karen E Thuermer

Correspondent | Washington