Logistics, the business of moving goods and material to be in the right place at the right time — and at the right cost — is one of the world’s oldest industries. Outstanding logistics networks enabled the expansion of the Greek Empire, and one can argue that stretching its logistics network too far contributed heavily to its decline. The legacy of that strong logistics network, however, remains, and Greece is still a world leader in the maritime movement of goods.
Fast forward a couple thousand years and our expectations have accelerated on all fronts: product life cycles have dramatically shortened.
Consumers expect significantly improved electronic devices every 12 months (or less), and a lack of inventory or an inability to provide two-day global shipping can quickly lead to short-term lost business or even long-term client loss due to platform switching decisions (think Android vs. iOS).
“Fast Fashion” has completely disrupted the traditional apparel business which used to rely on predictable, 12-month planning/manufacturing/delivery cycles. Retailers and manufacturers that get a product to market faster and cheaper — and then quickly move on to the next wave — are the ones that are succeeding while traditional integrated brands lose market share.
It is no coincidence that these trends are emerging at the same time that the global shipping industry is facing tremendous margin pressure.
Every player in the logistics network is looking for better visibility. And in order to better understand the complexity and breadth of the challenge, it is helpful to understand how the industry classifies the many actors involved in the process.
First-Party Logistics companies (1PL’s), the “consignees,” are those that manufacture or buy goods. Ultimately 1PL’s want to know that those goods and materials will be in the right place at the right time. Failure to do so can mean empty shelves or factory lines sitting idle. Examples of 1PL’s include retailers, such as Wal-Mart and Target, as well as manufacturers, such as Intel.
Second-Party Logistics companies (2PL’s), the “consignors”, are those that own the means of transportation (ships, trains, planes, trucks, cargo containers). They are also deeply interested in delivering on time, but they also have the added challenge of managing a complex pool of assets that are constantly in motion where resource utilization has a direct correlation to the bottom line. In the case of the top ten global shipping lines, the assets (ships, containers) are in the millions. Examples of 2PL’s include FedEx, UPS, Maersk, and Union Pacific.
Third-Party Logistics companies (3PL’s), are companies that contract or outsource logistics services. They may own and operate truck fleets, warehouses, and distribution centers. Examples of 3PL’s include DHL, Kuene + Nagel, and C.H. Robinson.
Fourth-Party Logistics (4PL’s) and Fifth-Party Logistics (5PL’s) are relatively new entrants into the space, and they include all of the service providers that provide general industry (technology, research, etc.) support as well as those that seek to build two-sided markets for Logistics. In many ways, they are the evangelists pushing the dream of automated freight forwarding and “Logistics-as-a-Service.”
In many ways, the 3PL’s and freight forwarders are stuck in the middle and often at the mercy of the 2PL’s while trying to schedule and coordinate the handoffs from factory to port to distribution center and ultimately to the customer. They are also on the front lines in dealing with those unfortunate extra costs known as demurrage and drayage (think of them as “late fees” for rented ships/containers and trucks). And let’s not forget the safety and labor-related issues, such as the number of continuous hours worked or hours worked in total per week.
All the parties in the supply chain benefit from better visibility, increased utilization, better on-time performance and reduced costs. So why hasn’t it happened? Because, quite frankly, up until recently, it has simply been too expensive to do so.
Today, however, a confluence of several key technological trends have emerged that dramatically change the cost dynamic:
- The Internet of Things (“IoT”), which in itself includes a series of tech advances that include low-cost sensors, decreased global data communication costs and major improvements to battery life.
- Machine Learning (“ML”) and Big Data, that can continuously examine massively large data sets of seemingly unrelated information and then be used to make valuable predictions and recommendations.
- The Public Cloud, which has dramatically reduced the cost of computing, moving it from CapEx to Opex, and providing on-demand access to virtually unlimited computing capacity to run those ML models.
Why does this matter?
Let’s take a look at a couple real-world scenarios on how this actually plays out:
One of the top 3 shipping lines, an owner of more than 2 million cargo containers, has publicly acknowledged that it annually wastes upwards of $1B (yes, one billion!) “shipping air” — or moving empty containers around the world — because they lack adequate visibility into where their assets are and when they will return. That company is not alone, as this problem affects virtually every shipping line that doesn’t track their assets.
Let’s look another case that impacts the entire logistics industry:
Every year in September, Apple holds a press event to announce its new version of the iPhone, which leads to a buying frenzy both directly and via Apple’s retail distribution partners. Behind the scenes, Apple’s component and contract manufacturing partners in Asia have been busy assembling products and getting them ready for global shipment.
The ramifications of this are massive. Virtually all port and logistics capacity in Shenzhen / Hong Kong are tied up for months before and after the launch. Smaller customers and shippers regularly have a tough time moving any product out of that region. Delivery times can double (or worse), which impacts many companies trying to stock up for holiday buying season.
Do companies try to avoid the rush by shipping their products by mid-summer to stock their warehouses and distribution centers? Will their products be ready in time? Can they afford to tie up all that working capital in inventory? Or do they take their chances on the shipping spot market — paying through the nose while hoping and praying that their shipments will arrive on time?
Consignors are working towards their most profitable time of year, but there is much to lose if they fail to deliver on-time. Proverbially that rolls downhill for the consignees. All parties are seeking better visibility and more predictable results.
So what can be done? Enter IoT and Machine Learning.
For 2nd-party logistics providers:
2PL’s have the opportunity to equip all of their assets with sensors and GPS trackers. This includes (but is not limited to) the following:
- Ships (partially tracked by AIS)
- Aircraft (partially tracked by ADS-B and ACARS)
- Rail (locomotives and railcars/wagons)
- Trucking (cabs/tractors, trailers, and chassis)
- Ports (gateways, portals, gantries, and geo-fenced zones)
- Intermodal shipping containers
Many use cases can simply be addressed through tracking time-based location. However, by adding additional sensors for temperature, humidity, vibration, light, door open/close, etc., there are much more quality, safety, authenticity, and security use cases that become possible.
In addition to being able to offer new, sensor-based services to their clients, 2PL’s have much to gain in terms of better asset utilization and management. Knowing where the assets are at any moment in time, combined with predictive models that know when assets will be returned are the keys to driving utilization. For a 2PL, higher utilization directly correlates to higher revenue and margins.
For the 4PL/5PL or Service Provider:
Thinking at a higher level, however, there are much larger opportunities for industry service providers that want to provide a macro view of shipping and logistics. This is where 4PL’s and 5PL’s see their chances to make a material impact on the global shipping market.
As a service provider (or as an incredibly forward-thinking 2PL), imagine what would be possible if you were able to ingest all of that real-time geospatial/temporal and sensor data and combine it with real-time and historical weather data, news, organized labor/strike info, your company’s or client’s ERP-based shipment info, and even social media feeds into a massive data lake on which you can run your machine learning algorithms.
You would then have the ability to publish a real-time, predictive index for the movement of all public goods and assets worldwide. You bet that there will be significant market interest in a service provider that can demonstrate looking backward with 90+% accuracy and forward with 80+% accuracy. In fact, there are companies who have built precisely this type of platform and service (I used to work for one).
Priming the Pump and a Path Forward
Ok, so you’re thinking this sounds great, and you’re wondering why aren’t these services broadly available? The short answer is still tied up in the hard realities of the ultra-low-margin global logistics market. GPS trackers have come way down in cost, but perhaps not far enough yet for all twenty million intermodal shipping containers. In fact, as of 2016, it’s been conservatively estimated that less than 5% of all containers are currently tracked, and the majority of those that are tracked are so-called “Reefers,” or refrigerated containers, that have access to power with battery backup.
Not unlike what the Public Cloud has already done for IT infrastructure, forward-thinking service providers need to find a way to shift the hardware tracking cost model from CapEx to OpEx. At scale and over time, the hardware costs will continue to fall, but even at $20/unit, it’s still a lot of CapEx if you have to buy millions of them. Good luck trying to explain that to a finicky venture capital or private equity firm though.
At the same time, this problem screams for an industry-wide consortium or alliance whose sole focus is the better interchange of these types of data in a secure manner. Everybody benefits from better visibility. Some more than others. As the global shipping market consolidates into the hands of a few brave (some would say foolish) companies, each with large market share, but with few seeing any profit growth in an already low-margin business, it could be a while yet before the vision of a truly automated logistics market becomes possible.
These industry-wide challenges are tough to solve and require commitment on behalf of both individual companies and the overall market to address. They also require a broad set of technology and domain skills to implement. With a unique mix of team experience in IoT, Cloud, Machine Learning, and Logistics, along with a set of industry-leading partners for devices, systems, and global communications, CTP is well-positioned to help all parties — from the 1PL to the 5PL — in defining their strategies and in developing/deploying automated logistics solutions that deliver breakthrough operational results.