Modern logistics - how breakthroughs in network connectivity will change the world

Since the early 1990s, the advent of the internet has led to an accelerated use of technology in logistics. This has included such developments as barcode scanning and GPS tracking of shipments, as well as more recent innovations such as robots and artificial intelligence. These advancements have allowed for increased productivity and decreased costs and errors in the field. In this digital transformation age, logistic technologies are undergoing major changes in order to keep up with the pace of the modern economy. Companies must be prepared to adapt to emerging technologies if they wish to remain competitive in a globalized world.

About the author

John Crittenden

Technical Analyst, Product Perfect

Former physician, now technical author, with an emphasis on bio-tech and medical advancements.

One of the many unanticipated downstream impacts of the COVID-19 pandemic has been how it revealed a level of unprecedented fragility and weakness in the global supply chain. According to Raj Subbiah, Head of Product at Uber Freight,

Our CEO, Ron Lior says that ‘The logistics industry was built for a world that we no longer live in.’ Every company that deals with the movement of goods is a logistics company and has to up its level of expertise in the logistics space. We’re very good at just-in-time logistics. We’re not very good at just-in-case logistics. Our resilience needs to be better so we can ensure a consistent customer experience. Technology is the perfect solution for solving these challenges.
Raj Subbiah, Head of Product at Uber Freight

Modularity has heretofore characterized the use of technology in logistics. Scanning barcodes at the POS informs real-time inventory levels- the “how many”. RFID technology adds the “where”. Distribution centers sporting automated conveyor belts, robotic arms, autonomous wheeled drones, and even aerial drones- for those hard to reach places- are steadily taking over the “where to”. Why? Warehousing constitutes about 30% of logistics costs. Seasoned professionals are wary of haste in converting “Why?” to “Why not?” The product life cycle (PLC) of these innovations suggests that inflection is nigh upon us. However, knowledge of the media driven “hype cycle” and Amara’s Law suggests that reflection be given its due.

Roy Amara, former director of the Institute for the Future 1 , articulates his eponymous law, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run”.

That is wisdom. PLC analysis may be expanded to include the Technology Acceptance Model (TAM), the Spiral Life Cycle Model, and their hybrid, the Spiral Cost Implementation Model (SCIM). That may be useful.

In this case, caution must not become intransigence. A storm of innovation is rapidly approaching. It promises coalescence of the modules described above. It promises that the lonely but efficient postmodern warehouse floor described above is inevitable. As a subject itself to the hype cycle, it is already entrenched as no less than the backbone of the Fourth Industrial Revolution. It is the Internet of Things (IoT). Sensors marry servos in the intimacy of the Fog, and the world will never be the same again.

The use of low latency processing at the edge of the Cloud (the Fog) to integrate sensor data and generate a servo response promises to redefine more than logistics. It is the centerpiece of smart factories, smart logistics, smart homes, smart farms, smart energy grids, and smart maintenance. It has applications in wearables, healthcare, fleet management, hospitality, and traffic management. Job security is an understandable concern. The bad news is that as previous Industrial Revolutions displaced myriads of blue-collar workers, this one is likely to displace many white-collar workers. The good news is that ultimately those so displaced will likely only be required only to develop an appropriate new set of skills. What skillset that may be is as of now unclear. This technology has already been proven superior to human logisticians in complex upstream procurement scenarios- and that’s no bullwhip.

There is, however, a bit of concern that with a dash of AI and a big helping of data, humans may be relegated to mere bystanders. Some specific areas in which increasing technology has application in logistics include:

Shipment tracking systems

Increased use of technology

The widespread adoption of smartphones and the internet has made it easier for companies and customers alike to track their shipments in real-time. Shipping companies now use GPS technology, barcodes, and QR codes to accurately track and monitor shipments.

Integration with other systems

Shipment tracking systems are increasingly being integrated with other systems such as transportation management systems, enterprise resource planning (ERP) systems, and customer relationship management (CRM) systems. This integration provides a more comprehensive view of the entire business process.

Big data analytics

Shipping companies are leveraging big data analytics to improve the accuracy of their shipment tracking systems. This allows them to gain insights into patterns, trends, and performance metrics to improve their operations and better meet customer needs.

Cloud-based solutions

Many shipment tracking systems have moved to the cloud, allowing for easy access and scalability. This also eliminates the need for companies to obtain proprietary software, with the option to do away with expensive hardware. The Cloud can provide IaaS.

Increased focus on user experience

With the rise of e-commerce and customer expectations for a seamless shipping experience, shipment tracking systems have become more user-friendly, with simpler interfaces and enhanced features such as push notifications and real-time updates.

Internet of things (IoT)

The Internet of Things (IoT) is transforming the logistics industry in both directions. Procurement processes informed by the IoT are superior to the best human efforts. Downstream logisticsbenefit by enabling real-time tracking and monitoring of shipments and improving operational efficiency.  Companies like Maersk are using remote container management systems which employ internal sensors to gather and broadcast real-time data from temperature, humidity and CO2 levels .Some ways in which IoT is changing logistics include:

Real-time tracking and monitoring

IoT devices and sensors attached to shipments can provide real-time information on the location, temperature, humidity, and other environmental factors of the shipment. This allows companies to quickly respond to any potential issues and ensure that the shipment arrives in good condition.

Predictive maintenance

IoT sensors can monitor the condition of vehicles and equipment in real-time, allowing companies to predict and prevent potential malfunctions and breakdowns.

Improved route optimization

IoT devices and sensors can collect data on traffic, road conditions, and weather, allowing logistics companies to optimize routes and reduce delivery times.

Inventory management

IoT devices and sensors can track inventory levels and alert companies when stock levels are low, allowing them to quickly reorder supplies and avoid stock shortages. These systems are much less likely to develop the bullwhip effect.

Enhanced security

IoT devices and sensors can provide real-time updates on the location of shipments and allow companies to monitor their progress, reducing the risk of theft and loss.

Global Internet of Things (IoT) in logistics market

Automation and drones

The drones are already here, Gather AI is a startup using drones in warehouses to scan inventory. According to Phystech Ventures, VCs have poured $5 billion into 129 drone startups in the last two years. Amazon has already began drone deliveries in California and Texas, with the launch of Amazon Prime Air. Amazon plans on delivering packages with a max payload of 5lb, which accounts for 85 percent of shipments. Automation and drones utilized in the following areas:

  1. Warehouse Operations
    Automated storage and retrieval systems, conveyor systems, and robots are used to handle, sort, and store packages, reducing the need for manual labor and increasing efficiency.
  2. Inventory Management
    Automated systems are used to track and manage inventory levels, reducing the risk of stock shortages and overstocking.
  3. Delivery Operations
    Autonomous vehicles, such as drones and self-driving trucks, are used to deliver packages, reducing the need for manual labor and increasing delivery speed.
  4. Supply Chain Optimization
    Automated systems are used to analyze data and optimize supply chain processes, such as route planning and inventory management, resulting in cost savings and improved customer service.
  5. Customer Service
    Automated chatbots and virtual assistants are used to provide customers with real-time updates on their shipments and answer their questions, reducing the need for manual customer service.
  6. Inventory Management
    Drones equipped with sensors and cameras can quickly and accurately scan warehouse shelves and provide real-time data on inventory levels, reducing the need for manual counts and helping to prevent stock shortages.
  7. Delivery
    Drones can be used to deliver small items within a warehouse, reducing the need for manual labor and increasing delivery speed.
  8. Safety Inspections
    Drones equipped with cameras and sensors can be used to inspect hard-to-reach areas of a warehouse, reducing the need for manual inspections and minimizing the risk of injury.
  9. Surveillance
    Drones equipped with cameras can be used to monitor warehouse operations and detect potential security breaches.
  10. Package handling
    Drones can be used to handle and sort packages, reducing the need for manual labor and increasing efficiency.

Artificial Intelligence

Artificial Intelligence (AI) has brought a new level of efficiency and effectiveness to the logistics industry. The integration of AI has revolutionized various processes and operations, including route optimization, inventory management, and predictive maintenance. AI algorithms are used to analyze data, optimize delivery routes, and reduce costs, resulting in faster and more cost-effective deliveries. AI-powered systems are also used to track and manage inventory levels, preventing stock shortages and overstocking. Predictive maintenance is another area where AI has had a significant impact, as it allows companies to proactively identify and resolve potential issues with vehicles and equipment before they result in downtime or increased costs. As AI continues to evolve, it is likely that new applications and uses will emerge, further transforming the logistics industry and enabling companies to operate more efficiently and effectively.

FedEx is using AI for delivery optimization and robotic delivery navigation. Amazon is using AI to power its search bar.

Improved GPS alone has been a game-changer

Modern GPS technology has greatly transformed the logistics industry by providing real-time tracking, improved route optimization, enhanced fleet management, and increased safety. In 2018, GPS technology company, Trimble, announced the release of its next-generation GPS module, the Trimble BD990-PRO. This module was designed to provide "sub-centimeter" accuracy in tracking vehicle location, making it possible to track the exact position of a vehicle within a few meters. In 2019, another similar firm, Omnitracs released its OneView platform, which included GPS tracking and routing optimization features that leverage real-time data and pin-point accuracy to optimize routes and provide drivers with the most efficient routes to their destination. (This already existed, but now it’s way more precise.) By doing so, logistics companies can reduce delivery times and improve customer satisfaction. With GPS, companies can now track and monitor shipments and deliveries in real-time, allowing them to manage their operations more effectively and respond to any potential issues more quickly. GPS data is also used to optimize delivery routes, reducing transit times and costs, and improving delivery speed. Furthermore, GPS technology helps enhance fleet management by providing real-time information about the movements of vehicles, enabling companies to optimize their operations, reduce costs, and improve delivery speed. Additionally, GPS tracking systems enhance safety by providing real-time information about the locations of vehicles and drivers, helping to avoid accidents and ensure that drivers follow safe driving practices. Overall, modern GPS technology has become an indispensable tool for companies in the logistics industry, helping them to operate more efficiently and effectively.

AI invades logistics: bots are at the wheel

Here they come! Like zombies climbing the wall in Brad Pitt’s 2013 movie, World War Z.

zombies climbing scene in Brad Pitt’s 2013 movie, World War Z
forgive the humor, just a reference to a zombie movie once in a while.

The incorporation of AI technology has made its way into the logistics industry and has been transforming the sector ever since. Among the many AI-driven tools, the emergence of intelligent bots has caused quite a stir. With their increasing deployment, logistics companies have become more efficient, streamlined, and cost-effective.

The intelligent bots, at the forefront of this change, are essentially software programs that automate time-consuming and repetitive tasks such as route planning, delivery tracking, and inventory management. The utilization of these bots has led to a substantial reduction in operational costs and an increase in efficiency, making them indispensable for logistics companies.

One of the most significant benefits of using bots in logistics is their capability to analyze massive amounts of data. By applying machine learning algorithms, these bots can effectively sift through complex data and provide crucial insights that help make informed decisions. This has been particularly beneficial in optimizing supply chain management, where logistics companies can leverage the insights generated by the bots to enhance efficiency and reduce costs.

Furthermore, bots are also suitable for mundane tasks such as inventory management. By utilizing bots to monitor stock levels, logistics companies can monitor inventory levels in real-time, avoid stockouts, and prevent any significant problem that may arise in the industry. Bots can also anticipate when inventory levels will be low, allowing logistics companies to make informed decisions on when to order more stock.

Another area where bots have had a significant impact is in route planning. With the aid of AI technology, bots can analyze various data points such as traffic, road conditions, and weather to generate the most efficient delivery route. This technology has been particularly useful in urban areas, where traffic congestion is a considerable issue. By optimizing delivery routes, logistics companies can reduce delivery times and enhance customer satisfaction.

Conceptual diagram showing that some applications of AI in logistics are automated warehouses, autonomous technology, analytics, back office work, and more.
AI applications in logistics

Cost basis: hard to calculate but absolutely required

In this movement of logistics, the bean counters can’t be forgotten. Cost calculation plagues and bewilders managers and CFOs perpetually. And for good reason. One of the biggest challenges facing logistics companies is the identification and consolidation of supply chain failures - those failures of course cost money every time. It’s hard because supply chain failures occur at any possible critical point of failure or weakness in the supply chain, from manufacturing and production to transportation and delivery. The problem is further exacerbated by the fact that there are so many layers. These layers include the raw material layer, which involves sourcing and acquiring materials that meet quality and quantity standards; the manufacturing layer, which transforms raw materials into finished goods; the transportation layer, which moves goods from the manufacturing site to the point of distribution via various modes of transportation; the warehousing and storage layer, which manages inventory levels and optimizes storage conditions; and the distribution layer, which delivers goods to the end customer via direct-to-consumer delivery or delivery to retail stores or distribution centers. Each layer is essential in ensuring the smooth and efficient flow of goods through the supply chain, and disruptions or inefficiencies at any point can have significant impacts on the overall supply chain process. Within each of those layers are the cost basis and cost models. Each model can be fine-tuned and reworked. This is both great news, and terrifying news at the same time, because someone has to do that work, and it’s not simple.

But if you break it into 2 key groups, you have:

  1. Direct Cost
  2. Indirect Cost

Each is portrayed in the visual below.

custom visualization showing the downstream impacts of direct and indirect cost calculations
the calculation and impact of direct and indirect cost allocations in logistics

From here to eternity...

Shipment tracking systems, the Internet of Things (IoT), automation, drones, and GPS technology have all had a significant impact on the logistics industry. The IoT has allowed for the integration of data from various devices and systems, providing companies with a more comprehensive view of their operations. Automation has improved operational efficiency and reduced costs. Drones have provided a new means of delivery, allowing for faster and more efficient deliveries in certain situations. Safety and regulatory concerns, particularly with respect to the potential for interference with commercial and general aviation, must be addressed. Upstream procurement is one of several areas in which the IoT and associated technology are clearly superior to human logisticians. There remains vast unrealized potential for companies to operate more efficiently, to reduce costs, and to improve customer service.

The ultimate potential of the IoT and associated technologies is not clear, but it seems likely that Amara’s law applies here. The long term potential of these technologies in logistics and other areas may be easily underestimated. There is an almost romantic image of the human logistics operator leaning back in his chair monitoring a sophisticated dashboard. They occasionally lean forward to twist a dial or push a button.  One is reminded of the airline pilot monitoring his aircraft while the autopilot is engaged.

That aviator may be “hand-flying” the aircraft on an instrument approach, but in actuality the autopilot is feeding him input to a fairly easy video game. He or she is not allowed to fly such an approach using the “raw data” alone. Not with revenue paying souls in the back. No human being can integrate the data  from aircraft position sensors and ground based transmitters like the onboard computer. The flight director does the real work. Similarly, how is our human logistician supposed to be able to keep up with the AI driven, self-monitoring, and big data analyzing virtual computer infrastructure that is being described here?  

In responding to global logistics scenarios, decisions- be they optimizations, projections, or directions- are input in fractions of a second to a dynamic network. The resulting perturbations are detected. New decisions are made and input . This may take place one hundred times in one second. So, what exactly is our operator doing? Let us program carefully, for logistics may be out of our hands as soon as we implement the program...

Key Takeaways

Logistics tech projects and organizations can cross the chasm. Here are a few notes we’d prescribe:

  1. Autonomous vehicles and self-driving trucks will keep growing at a rate that outpaces the cost to produce them.
  2. The financial incentives to move to electric trucking will grow, and both Democratic and Republican leaders will endorse the move broadly speaking.
  3. Predictive maintenance will allow IoT sensors [the logistics companies  that manufacture them] to predict more precisely when machinery and equipment will require maintenance, and even automatically call their own technicians to come out and schedule repairs proactively. This small but powerful adjustment will prevent downtime and protect production.
  4. Robotic warehouse automation will grow. Our hardware robots will be the default now for all new warehouse operations plans and build-outs, including material handling, inventory management, and order fulfillment.
  5. Using real-time data, AI algorithms can (right now) optimize routes and schedules for delivery trucks, reducing fuel costs and improving delivery times.
  6. Logistics companies will continue to use AI and hardware advancements to better forecast demand and adjust inventory levels more precisely.
  7. IoT sensors capabilities will expand to allow Wifi, Bluetooth, GPS, and private hardware networks to track shipments in near real-time. It will allow “god-mode” like panels at every shipping company that show where everything is, all the time, all at once.

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