Source: supplychainbrain.com
According to a survey published by Dresner Advisory Services, over 50% of companies are using big-data analytics. A closer look reveals that the adoption rate varies significantly by industry, with financial services and telecommunications leading the way, followed by education and healthcare. But the top five includes no mention of logistics.
When one thinks about big data, logistics is rarely the first industry that comes to mind. Ironically, however, it’s likely to be the one that stands to benefit most from its adoption.
The use of predictive analysis to estimate and prevent bottlenecks in the supply chain is crucial, especially in an industry where punctuality, transparency, and privacy play key roles. And with more and more consumers opting for e-commerce, pretending to stay relevant without relying on big data is naive.
The Last-Mile Problem
The last mile of a package’s journey to the buyer is the most painful step for logistics companies. It’s also the most expensive, acocunting for over half of total shipping costs. Delays due to traffic jams, parking difficulties, bad weather, force majeure, and even more trivial challenges such as apartments without elevators, all contribute to adding up costs and negatively impacting customers’ experience.
Obstacles to a smooth delivery used to be impossible to predict. However, with the help of GPS systems in delivery vehicles and smartphones, sensors, scanners, and the internet of things (IoT), shippers can now monitor the whole journey. They can even proactively intervene — for example, informing the driver if a street is congested or inaccesible.
In the long run, logistic companies will discover patterns and recurring challenges, and come up with practical ways to overcome them. Say that the cost of fuel tends to increase in August. Big-data analysis can predict the increase and make sure that vehicles are completely refueled in July. UPS’ ORION algorithm is a state-of-the-art example, able to collect and analyze more than 1 billion data points per day on factors such as package weight, shape, and size. From there, it can cross-reference the data with historical delivery information to estimate capacity, package volumes, and customer demand. With the help of this scientific, data-driven approach, UPS claims to have saved $50 million annually, simply by decreasing each drivers’ mileage by one mile.
“Currently, there are different industries working simultaneously to solve the last-mile problem,” says Asparuh Koev, chief executive officer at Transmetrics. “I don’t see why, for example, I shouldn’t be able to track in real-time where is the plumber coming to fix the sink.”
But things aren’t that black and white, according to Pete Bandtock, billing workstream lead at DHL Global. “The last-mile problem isn’t a universal issue in logistics,” he says. “Think about ocean freight shipments. They’re often collected at the port by the consignee, or delivered in multiple massive containers to a consignee location.” Ergo, no last-mile problem.
“The issue is more acute in the B2C sector,” Bandtock continues, “and I do see significant investment in technology there, both in terms of routing algorithms and in customer messaging and visibility.”
Angel Mitev, senior vice president and practice lead for big data, transportation and logistics at Sciant, has a different opinion. “Although I agree that the biggest impact will be on B2C logistics,” he says, “we’re likely to also see an impact on B2B, especially with the arrival of autonomous trucks and vans. Crowdsourcing, drone deliveries, and real-time route optimization are other areas where the technology exists and has been tested. So there’s no doubt that the last mile will be an area where we’ll see major innovations in the very near future.”
Crowdsourcing and Robots
When it comes to optimizing last-mile delivery, the crowdsourcing model has proved to be extremely useful. A food delivery to the home is likely to be carried out by a local courier. At the same time, projects such as Uber Freight are taking logistics in a new direction. Amazon Flex allows the last mile to be managed by locals, who can make up to $25 an hour, while giving customers greater transparency and faster deliveries. This disruptive approach can revolutionize the current last-mile model by replacing professional carriers with randomly moving local drivers.
Bandtock has a contrary view. “While the growth of crowdsourced services is evident for consumers,” he says, “I don’t see it becoming particularly relevant for B2B logistics, since there’s only so much you can carry on a bike or a car.” He is similarly skeptical about UberFreight: “I don’t believe they will push much into the heavier freight space, as they have neither the footprint nor the capital to do it.”
Koev points out that road congestion dramatically impacts the quality of delivery. “Traffic is getting worse,” he says. “More people are living in bigger cities, so density is increasing. Crowdsourcing won’t magically solve the issue — it needs to be fixed at the infrastructure level.”
So it there no way out with current infrastructure? “Think about the subway,” Koev says. “It’s the the most-used type of transportation in major cities. Existing subways are designed to transport passengers, but they can transport parcels as well. It will just have to function differently.”
Another major trend in logistics is the use of non-human workers. Prime Air’s delivery system is designed to get packages to customers in 30 minutes or less using drones. Some 100,000 robots have replaced conveyors and human-operated machines in most Amazon warehouses. Kiva Systems, the company behind those robots, was acquired by Amazon in 2012 for $775 million, the latter’s second-largest acquisition at the time.
The benefits of warehouse automation go beyond staff cutting. The use of robots brings more accurate insights into how the loading and delivering of packages can be improved. And self-driving vehicles promise to take logistics to a whole new level. Already in use in controlled environments such as warehouses and yards, they’ll soon be seen in shared and public spaces, such as on highways and city streets, according to Markus Kückelhaus, vice president of innovation and trend research with DHL.
Bandtock doubts the logistics industry will be fully automated in the foreseeable future, if ever. “The commodity piece can be largely automated by a combination of big data and robotics,” he says. “However, the picture with more complex supply chains is more blurred.
“Think about the wine and spirits business,” he continues. “A supermarket chain will place major orders for massive quantities of certain drinks in anticipation of foreseeable events, such as the World Cup, Wimbledon, or royal wedding. Some of these events have a shorter notice period than the production period for the commodity involved. Niche logistics players need to reach across this supply chain and ensure that the champagne needed to toast the royal wedding, which started its production cycle three years ago, will be available in shops four weeks before the event, which was announced three months ago. The value-add of the logistician in this example is in relationships, not in data. “
Koev is similarly skeptical. “Human-free anything is not possible, period,” he says. “Even if humans don’t deliver the packages, they’ll have to maintain the systems. It’s a market problem, not a technology problem. In logistics, we operate in this paradox: we try to work with the infrastructure we have, even though the benefits of adoption are obvious. Transportation is very commoditized. Everyone’s doing the same thing, and it’s been like this for years.”
Mitev, on the other hand, predicts an almost completely automated industry. “The vanilla logistic services could be human-free,” he says. “Artificial intelligence, along with data-driven back-end systems directing fleets of autonomous vehicles and robots, will perform most of the delivery, loading, unloading and other menial tasks. Scheduling and route optimization, warehouse management, cargo and equipment localization, and inventory management will also become more and more automated. Customer relationship management and tailored logistics services will be the new battleground, where companies will be fighting to differentiate themselves, and where the human factor will remain critical.”
Time for a Shift
To get there, a significant industry shift is needed. Historically, logistics companies haven’t been big adopters of cloud-based technologies, which are essential to optimizing and digitizing last-mile delivery.
“With autonomous last-mile deliveries going mainstream,” Mitev says, “the industry is very likely going to witness a significant improvement in event-data collection. In this scenario, automated scheduling and dock management will become critical, as autonomous vehicles will have to be scheduled much more precisely than human-driven ones. Cloud-based and IoT-enabled dock management, together with event management platforms, will become the industry’s must-have.”
The acceleration of cloud-based system adoption is, therefore, crucial. The proper gathering and cleansing of data enable better forecasting of events and less uncertainty. Such goals can’t be reached with legacy, on-premise systems. Standardized cross-platform integrations, so crucial to creating seamless information chains, can be more easily achieved with cloud-based, micro-service, open-application programming interface (API) systems adoption. The International Air Transport Association’s e-air waybill is one example of open APIs, but according to Mitev, “What’s missing are standards for documents such as pick-up orders or cargo manifests.” Major upgrades, or even complete replacements of primary IT systems, are required, he adds.
“Standard APIs would be great,” says Koev, “but it’s a competitive market, and players usually don’t want to share. I’ve seen companies deliberately removing part of their data before passing on to the next company.”
Moreover, the technology only becomes valuable when it’s scalable, which smaller companies will find difficult to do. “So my two cents for who’s going to to push the market forward is on established players, rather than start-ups,” Koev says.
Big data will grow even bigger, with an increasing number of connected devices autonomously generating terabytes of new information. The abilility to access and process that intelligence will give logistics companies a substantial competitive edge, but the foundation for it needs to be built now. The race will be between the current big players, struggling with their journey toward digitalization, and new entrants who are joining a pre-digital industry.