or DC, Bedard said in a phone interview. In one case involving a multinational customer whose shipments missed their
scheduled U.S. arrivals about 20 percent of the time, APL
Logistics discovered that the customer’s ERP tables had not
been updated for 10 years and were generating inaccurate
information about the cargo’s status. Armed with this information, the customer redefined its key performance indicators (KPIs) to reflect more plausible supply chain scenarios.
It shaved $20 million to $30 million off its transport spend by
eliminating costly air freight that had been used as a backstop
in the event of a late or delayed shipment, Bedard said.
The increasing visibility into demand needs and supply
responses means that retail orders will become more precise
and specialized than ever before, Bedard said. Gone will be the
days of hit-or-miss ordering and deliveries because retailers
didn’t have sufficient clarity into their supply chains, he said.
A LONG JOURNEY
While progress is being made, it should be remembered that
ocean shipping is a hidebound business with a corporate culture often slow to change. While companies like Maersk are
aggressively pursuing big data and analytics, others are not as
engaged. The absence of digital uniformity creates roadblocks
to a mainstream uptake of big data, Kuznetsova said.
The complexities of operating in a worldwide industry have
been amplified by the recent surge in vessel-sharing agreements (VSAs), where financially hobbled liner companies
have commingled assets in an effort to rationalize capacity
while still delivering on service commitments. At this point,
big data and analytics are optimally deployed at a liner company like Honolulu-based Matson Inc., which largely serves
lanes between Hawaii and the U.S. mainland, because Matson
owns its own liner strings, according to Josh Brogan, vice
president at consultancy A. T. Kearney.
Still, Brogan said the deployment of robust analytical tools
could help carriers, forwarders, and customers cut through
even the clutter presented by VSAs. “Any time there’s complexity, there is an opportunity,” said Brogan, who worked in
the liner business and today consults with cargo owners.
Brogan said big data will be most useful in helping liner
companies model their responses to future events, whatever
they may be, with the overarching goal of improving asset
utilization. “‘How do we optimize our ships? How will next
year look for our customers? How do we recover from service failures?’ Those are the questions that big data can help
answer,” he said.
Kuznetsova said the liner industry is finally taking a serious look at why adoption of data tools has historically been
so poor. With the trade in terrible financial shape, “the time
is good” for liner executives to explore new and potentially
important advances in running their businesses, she said.
“We are just starting the journey” down the road toward big
data and analytics becoming mainstream, she said. Carriers
that embrace the road will pull ahead. Those that stay off the
path will continue to fall behind, she added.
