One of the most conspicuous skill shortages in IT today are people with data skills. This includes data management, analytics, and data storytelling capabilities.
In fact, the skill shortage for data scientists is so acute that the U.S. economy could be short as many as 250,000 data scientists by 2024, according to the McKinsey Global Institute.
One way that Dr. Tianbing Qian (TQ) has been tackling analytics challenges at Ports America is by crowdsourcing business problems with graduate students and faculty from leading universities.
TQ is SVP and CIO at Ports America. As a member of company’s executive leadership team, in addition to information technology, he also leads Ports America’s digital transformation and views advanced analytics as a cornerstone to company’s overall Digital Strategy. During the past year, TQ and his team have marshalled master’s and doctoral candidates as well as professors from leading universities such as Arizona State University to take on a number of complex business challenges for the largest terminal operator and stevedore that operates 42 ports and 80 locations in the U.S. through the use of advanced analytics.
For example, one of the projects being tackled by Ph.D. students and faculty members is tied to demand forecasting for how many trucks will come each day at terminals to pick up import containers.
“When container ships come, we offload thousands of containers from each vessel and store them into our container yard before they go via trucks/rails to retail stores or factories,” said TQ. Ports America is the largest independent container terminal operator in the U.S., handling approximately 12 million TEUs (twenty-foot equivalent units) of cargo each year at its nationwide facilities.
“Before BCO (beneficial cargo owners)/Shippers come to pick up the containers, the terminal needs to forecast how many containers each customer plans to pick up each day in order to determine the amount of labor they need to fulfill that demand. Forecasting demand accurately not only has a direct impact on bottom line, but also impacts the truck turnaround time at terminal – a key measure for customer satisfaction.”
To help forecast labor demand more accurately, doctoral candidates and university professors have developed sophisticated yet pragmatic algorithms which, to date, have significantly improved the forecast accuracy over existing rules.
“Our faculty strives to bring both rigor and relevance to their research projects. Experiential learning opportunities, such as the demand forecasting project at Ports America, are a perfect example of how we can leverage our corporate partners to create opportunities for our students,” said Professor Raghu Santanam, Chair of the Information Systems Department at Arizona State University. He and his colleagues are among a small team of researchers that improved the forecast accuracy for Ports America.
“We are in the process of implementing these algorithms at pilot terminal while looking at potentially applying the analytics to other locations,” said TQ.
Enhancing container visibility
Ports America and its team of academics also are looking into how data and analytics can be used to better forecast the availability of containers once they come off a cargo ship. When a cargo ship comes into a port, there are thousands of containers that are transferred off, and a number of factors, ranging from container position on vessel to yard work plan, can impact when it becomes available for pick-up.
“You need to be able to tell the BCOs and the shippers when the containers will be available for pick up,” said TQ. “It’s a complex problem to predict when the container will be available. It could be one day, or it might be three days.”
TQ likens the problem to when a customer calls a cable company for service and the customer is informed that a technician will arrive sometime between 9am and 4pm, which is a big spread.
“If you can narrow this down more closely for BCOs and shippers from three days to a half-day, this can lead to big improvements in customer’s warehouse planning, inventory replenishment, and outbound distribution,” TQ said.
Safety is extremely important as well in ports. Many pieces of heavy equipment are operating and moving within the container yard, posing dangers to shipyard workers. “The challenge for us now is – how we use data to improve safety management and to predict where the next accident is likely to occur?” said TQ. One of Ports America’s university analytics teams began exploring this challenge. “Part of what we’re looking for are insights that not only tell us what has happened, but what will likely to happen. Ports America already has industry-leading performance in safety and predictive safety is the natural next step to drive further improvement,” said TQ.
Although Ports America’s university analytical partnerships is still in its early stage, “We are seeing a lot of momentum and enthusiasm from both business and universities. Universities have an abundance of brain power and want to help solve real-world, leading edge problems. In the meantime, companies have a huge need for advanced analytics talent. There is a lot of potential here for value creation and win-win via university partnership on analytics collaboration,” said TQ.
Professor Santanam views the partnership with Ports America as an exemplar of how corporations and universities can come together to create experiential learning opportunities for students. “Such opportunities create a talented workforce that can create use-inspired solutions for their new employers from day one,” said Prof. Santanam.