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Cargo gateways such as the Port of Long Beach and the Port of Los Angeles continue to face congestion that raises questions of what software and data can do to help manage the situation. The issue has experts in the logistics sector, such as the Association for Supply Chain Management, XPO Logistics, and academicians at Florida International University thinking about ways to unknot the problem that binds the supply chain.

It is a conundrum that escalates as time passes -- the longer ships must wait to be unloaded, the backlog builds up in the supply chain. Scarcity of staff to get cargo moving has meant some warehouses remain packed rather than passing from container ships to road or rail transports. Labor shortages are only part of the issue as changes necessary in response to the pandemic brought their own restrictions. Furthermore, consumer buying patterns shifted with the onset of the pandemic, increasing demand for goods shipped directly to home.

The digitalization of supply chains was already underway, says Craig Austin, assistant teaching professor in the department of marketing and logistics at Florida International University. Much of that has been directed at trying to better understand and anticipate the wants of the customer to better draw them in through marketing. Companies needed to apply that knowledge more deeply, he says, using analytics to share information.

However, the systems of different stakeholders, including suppliers of commodities and packaged goods down to the end consumer, were not integrated and did not communicate with each other. “There was only so much information you could share,” Austin says. “What the pandemic did -- and it did it cruelly -- it brought everything into clear focus.”

The pandemic led to surges in demand while capacity remains limited, says Yoav Amiel, senior vice president of technology, XPO Logistics, a truck brokerage and transportation solutions provider. That increases the need for scalability and flexibility in companies to respond to fluctuating needs. “We have a huge data set that we collect from everyone, from shippers and carriers, and the moment you apply machine learning to that you could come up with insights and optimize,” he says.

Platforms and solutions, such as those offered by XPO Logistics, can increase visibility of goods in the supply chain allowing companies to react to changes in the market. Amiel says when his company builds technology, it invests largely in data science and machine learning, the freight marketplace, and integration and automation. “We’re in the transportation business and as a result, we’re in the data business,” he says.

Demand for more e-commerce, especially in the early stages of the pandemic with challenges in transportation, created limited capacity, Amiel says. “Leveraging data, understanding and predicting demand, is a key enabler from technology-based companies to tackle that challenge,” he says. “With machine learning, we are able to predict where the demand will happen and prepare accordingly.” As the winter holiday nears, Amiel sees the potential for such systems to be crucial for spotting capacity gaps. “The ability for technology-based transportation companies to predict that by having enough data and the right algorithms will be a driver in the overall ability to address it,” he says.

Black Swan Event

The pandemic caught many companies flatfooted, Austin says, revealing their mitigation strategies and profitability goals were dashed. “None of them really planned for a black swan event,” he says. “The black swan in this case was China.” With so much manufacturing in China, supply networks that were thought to be robust and transparent were left scrambling.

A focus on connectivity among vendors and different parts of the supply chain emerged in the pandemic, along with recognizing vulnerability of systems, Austin says. Logisticians have always known there would be disruptions within the supply chain, he says, and prepared for circumstances such as hurricanes.

The pandemic also drove pent-up demand for goods for more than a year and a half. The impact of the pandemic also made some companies question their reliance on overseas suppliers that might become inaccessible in future pandemics. More and more companies in the supply chain are using AI, machine learning, robots, drones, and exploring autonomous trucks to be more efficient, but the risks of more pandemic outbreaks still loom large. “Until enough of us get vaccinated, we’re going to have these issues within supply chains,” Austin says.

This is not the first calamity to strike the logistics sector, yet the nature of the situation is new territory. “The supply chain has always been a bit tumultuous, but never have we seen the different types and the volume of disruption that we’ve had within the last 18 months. Never in history,” says Douglas Kent, executive vice president of strategy and alliances at the Association for Supply Chain Management, which offers certification programs, training tools, and other resources to supply chain professionals.

“About 40% of the imports coming into the US come through Long Beach,” he says. There have been unanticipated escalations in demand, a traditional type of supply conundrum, due to e-commerce purchases driven by the pandemic. There is a supply side situation, Kent says, which has to do with infrastructure, IT, and workforce availability.

On the IT side there are track and tracing capabilities that he says are necessary to supply chain management. “You have things that assist in terms of productivity for customs clearance.” There are needs to reschedule activities because of the disruptions on the demand and supply sides.

Increasing and elevating infrastructure, having access for workforce development at the port and the transfer to other modes, as well as the enabling technology all have roles to play in addressing the issues at hand, he says. “The other pieces of the puzzle have to get fixed as well. Rail shortages are occurring. We have truck driver shortages, which is a massive focus right now -- let’s not forget fulfillment centers and warehouses. There’s a massive concern that these entry-level, focus jobs are not [being filled],” he says.

There has been a buildup of issues that contributed to the current situation, though the events surrounding the pandemic served as a catalyst for the backlog and delays. “Everything gets layered in,” Kent says. “We’ve been beleaguered with all of these events.”

Before the seaport backlog in California, massive container ship Ever Given ran aground in March and blocked up the Suez Canal for six days. Ports in China faced shutdowns for its exports because of the pandemic, Kent says. “That’s why nothing is where it should be. Everything is costing so much more.”

This leads to new planning, demand shifts, supply shifts, and attempts to reroute, Kent says. “Companies are now trying to de-risk things by putting cargo that would normally go on one ship splitting it out to multiple ships just hoping that one of them will arrive on time,” he says.

That is difficult to keep track of systemically, Kent says, because so much change goes on all the time. This drives the use of other resources such as internet of things connectivity and augmented reality to get a better handle on the tumult. “We have to do that with technology,” he says. “This is not somebody banging stuff out on a spreadsheet in a backroom.”

The cascading issues of backlogs in the supply can go beyond delays in personal shipments of consumer goods that were ordered. Even after cargo gets removed from ships, there can be delays getting those goods on rail or road, Kent says. This can be exacerbated by panic buying by consumers, as was seen in the early weeks of the pandemic. “When consumers get scared of shortage, they over-consume,” he says.

Forecasting Conundrum

The question then becomes whether there was an organic rise in demand or if harried consumers drove up demand themselves. If manufacturers misread such inflated demand, it can lead to overproduction in response that leaves a glut. “It’s problematic for retailers trying to forecast demand,” Kent says. The issue can also affect wholesalers, distributors, and raw component suppliers. “Companies got to try and figure that out.”

Availability of technology is not the barrier to managing these issues, he says. Availability of data is the problem. With the different players and stakeholders in the supply chain ecosystem, including container providers, shipment schedulers, makers of inventory, there is a massive load of data, Kent says.

Even if a sort of traffic control tower platform was established to see those interactions, accurate real-time data is still required. “All of the players within the ecosystem have to provide relevant data to support the decision process,” he says.

The difficulty, however, is the disparity in the data from different stakeholders. Technology adoption varies by organization, as does their validation and accuracy of data they might provide. While some companies tied to this sector may have accelerated their digital adoption in response to the pandemic, Kent says it might take a few years to get staff trained and different companies coordinated on this front.

The supply chain is dealing with a general shortage of workforce along with a limited technical workforce talent pool, Kent says, where technology can outpace the capacity to train workers. Key roles such as data scientists are hard to find and expensive, he says.

There is hope, Kent says, as leadership within organizations recognize the importance of managing the supply chain through a disruption. Investments in technology have also accelerated, he says. “Right now, it’s a matter of orchestrating different players and building a strategy where we can understand that these types of capabilities within the supply chain directly related to enterprise risk strategy.”

轉貼自: InformationWeek

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