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Top 10 Supply Chain and Logistics Technology Trends

14.02.2024

Cover photo for 10 Supply Chain and Logistics Technology Trends that will transform the industry with an illustration that dispalys a screen supported by a human with the imagery of logistics assets, dashboards and processes.

In the ever-evolving realm of technology, few sectors feel the impact as profoundly as logistics and supply chain management. With its abundance of manual processes and diverse data sources ripe for extracting insights, this industry stands to gain immensely from innovation and pioneering trends in Supply Chain and Logistics technology.

Recent years have ushered the logistics industry into a new era of innovation, driven by artificial intelligence, advanced analytics, and automation. Startups, introducing their trailblazing solutions, add to this momentum. However, these advancements bring not only opportunities but also heightened expectations. As both individuals and businesses demand faster, more cost-effective deliveries, logistics companies find themselves at a crossroads—adapt or fade away. This tug-of-war between technology and consumer preferences shapes the exciting future of logistics.

From advanced data analytics to digital twins to automation we have identified the 10 important logistics technologies and trends that will redraw the sector: 

AI Will Become an Essential Logistics Technology

Artificial intelligence (AI) has led to significant advances in various industries, including logistics, where its impact has been much more visible over the past years. The McKinsey report predicted that AI will be one of the most important logistics technologies reshaping the sector by 2030, outperforming humans in important but repetitive tasks, especially during the ongoing trade and logistics challenges

Integrating AI into logistics provides several important benefits:

  • It optimizes your data through natural language processing (NLP) and machine learning (ML), efficiently handling large databases and increasing operational accuracy across multiple environments.
  • AI-powered analytics surpasses manual analytics by leveraging computation power to take into account all the relevant data in the organization. This empowers logistics efficiency and reduces uncertainty while improving the working conditions of logistics professionals and keeping the costs at bay
  • The role of AI in demand forecasting is extremely important considering the e-commerce boom and ever-increasing amount of shipments transported through the logistics networks. AI taps into historical data, combines it with external factors such as holidays, and identifies past trends to forecast future demand, enabling optimal asset management, proactive capacity purchasing, and improved service levels.
  • Many new vehicles and robots leverage AI to improve the speed and working conditions of humans on the road and in the warehouse.
  • AI can empower strategic decision-making and simulate scenarios if implemented alongside the digital twin. This reduces risk, creates agility, and creates a reliable tool to experiment with your network and realize its full potential.

AI in logistics is reshaping the industry by enriching data, enhancing analytics, transforming forecasts, improving working conditions, and empowering tactical and strategic decision-making processes via powerful scenario planning.

Scenario Planning Will Be a Game Changer

Another logistics technology to follow is scenario planning which can prove to be a vital tool in managing uncertainties in the supply chain. It employs digital twin technology to simulate processes, anticipate issues, and propose solutions. For example, climate change-related disruptions affecting the shipping of goods, such as the draught in the Panama Canal, can be navigated through scenario planning. The technology can simulate the effect of such events on the transport networks by analyzing historical data, and propose alternative routes or transport modes to avoid disruptions.

Another example is DB Schenker Bulgaria which used AI-powered simulations to measure the efficiency and resilience of numerous network setups’. By comparing these, the company identified the best possible way to adjust the network infrastructure and the most optimal linehaul plan. This technology can also prepare organizations to experiment with the effect of different scenarios such as Black Friday peaks, hub addition/removal, route planning, and service level adjustment.

However, a major prerequisite for establishing a reliable scenario simulation is having centralized data management that represents an accurate single version of the truth for understanding past events and using this data to power up simulations.

Centralized Data Management Will Create Visibility

Data is the most important asset of any organization in the 21st century and the way you manage and control should be a priority for your logistics business. Data stored in different silos and across many disconnected TMS/ERP systems is fragmented and does not represent a single version of the truth. In a complex logistics environment, it becomes impossible to make informed and data-driven decisions without having access to full visibility across your operations.

Leveraging data lakes and data warehouses to centralize your data is a straightforward way of getting it under control since it can eliminate the silos, future-proof your business for scalability, and build a foundation for advanced analytics tools.

Data lakes swiftly store vast volumes of unstructured data, a goldmine for data scientists, though proper governance is paramount to avoid chaos. On the other hand, data warehouses are a better fit for organized data, that can support many operational activities such as inventory management, but adapting them could be intricate and costly. Both solutions eliminate data silos, catering to diverse units.

However, it is important to assess the current state of your business as well as the resources that you can spend on centralizing the data management. One thing is clear – if your organization wants to move forward with logistics technology implementations, a strategic approach towards data management and data quality is essential.

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Clean Data Will Empower Decision Making

Establishing centralized data management and defining how you store it should go hand in hand with stronger governance over the quality of your logistics data.

Errors such as retired employees listed as delivery contacts or inaccuracies in destination zip codes can lead to order delays and substantial financial losses for logistics service providers. Data cleansing, involving data quality correction, is pivotal in minimizing such discrepancies. In the current digital era it is crucial to avoid the “garbage in – garbage out” principle, especially when it comes to companies that want to follow data-driven conclusions. Here are some areas where your organization can focus on to improve your data:

  • Ensure that your data follows a consistent and standardized format.
  • Remove data duplication caused by multiple data sources or similar issues.
  • Address common syntax problems like data errors.
  • Leverage historical data and enrichment algorithms to fill in the gaps.

By fostering accurate and reliable data, logistics organizations can streamline their data analytics, and leverage it for precise demand forecasting and operational optimization algorithms.

Data Analytics Will Uncover Hidden Inefficiencies

Reliable data analytics is now crucial in logistics operations due to rising demands for efficiency. By leveraging centralized and clean data, logistics service providers can uncover hidden bottlenecks.

With access to detailed historical reporting on operational performance, organizations can detect trends and target inefficiencies on local, regional, and even global levels. Leveraging real-time analytics powered by Telematics and IoT can uncover another layer of operational excellence. On top of that, companies can set the right KPIs and measurements to handle volumes more effectively, leading to better growth and long-term success.

To implement it, companies can hire digital officers or work with logistics technology providers who have proven experience in working with sector-specific data. Given the amounts of data that companies have and an overall demand for efficient logistics, implementing analytics is no longer optional, but essential for survival in the competitive market. Going a step further and focusing on predictive analytics can enhance supply chain visibility, improve forecasting, optimize planning, and manage unexpected conditions.

Forecasting Will Predict Future Volumes (and Not Only)

Predicting the future is impossible. However, predicting future capacity demand in logistics is something that is already a reality. Implementing tailored forecasting models can improve safety stock management, increase fleet utilization, optimize operations to reduce costs, and enhance employee efficiency.

Short-range demand forecasts, which predict demand a few days or weeks ahead, have a significant impact on operational planning and cost reduction, particularly for companies with low-profit margins. To achieve effective fleet repositioning, selling surplus logistics assets, and dynamic pricing strategies, logistics companies should combine demand forecasting with augmented intelligence tools, creating a “human-in-the-loop AI” approach that combines AI recommendations with human decision-making.

Increasing Investment into Logistics Startups from VCs and Enterprises

As we see growing VC funding in logistics startups, major logistics companies are beginning to follow this path. Many of them have invested millions of dollars in new technologies developed by innovative startups or even acquired them altogether. This way, logistics companies can get the best of both worlds – leverage their capacities while driving R&D through their new partners. Giants like UPS see great benefits in sealing partnerships: the company made a minority investment in TuSimple, an autonomous driving company, to test self-driving tractor-trailers in Arizona, to see how this addition could potentially enrich the existing UPS networks. Maersk also it’s joining fellow shipping giants CMA CGM and MSC in investing capital in Traxens, an IoT, high-value data, and services platform for the supply chain industry. The e-commerce players are aiming to participate in this race as well with Shopify, a multi-channel commerce platform, acquiring a Massachusetts-based 6 River Systems, a provider of collaborative warehouse robotics solutions.

The race for innovation has also encouraged Singapore’s sovereign wealth fund Temasek to partner with transport giant Kuehne + Nagel to launch a $50 million venture fund for logistics and supply chain startups. According to the director of the fund, Marc Dragon, there is a high level of expectation from vendors that because of technology, there would be new powerful methods to approach supply chains.

There are also companies looking to expand their technological portfolio in-house. For example, C.H. Robinson Worldwide, the biggest freight broker in North American, announced it would double its technology spending to $1 billion in order to expand and develop its services to counter the competition from digital startups. Additionally, in what appears to be an effort to adapt quickly to digital innovations, Deutsche Post DHL Group announced in October 2019 that it plans to invest $2.2 billion in digital initiatives through 2025. With so many partnerships created over the past year, it will be interesting to see what kinds of solutions result from these investments.

Sustainability Powered by Technology

Sustainability is a trend that has been cutting across industries and logistics is no exception. Last-mile delivery, in particular, is traditionally very time- and energy-consuming, which is also why it presents many opportunities for fresh and smart approaches. To lessen the negative environmental impact, companies leverage a plethora of technologies, from actual electric vehicles to AI-based software that calculates the route with the lowest generated emissions. 

Amazon recently announced its “Climate Pledge”, a commitment to meet the goals of the Paris Agreements 10 years earlier. By doing so, the company hopes to encourage other businesses to join and aim to become net-zero carbon across their operations by 2040 and promote renewable energy. To do so, Amazon has contracted Rivian, an electric vehicle startup, to supply it with 100,000 electric vans.

Deutsche Post, the world’s largest courier company, has also committed $552 million to the production of light cargo electric vehicles and micro e-mobility units. Partnering with a Chinese manufacturer, the multinational partnership is set to result in the production of up to 100,000 street scooters per year.

Similar logistics technology trends can be seen across the entire shipping sector. Just recently, over 60 commercial groups, including Maersk, launched an initiative that aims to use ships and marine fuels with zero carbon emissions on the high seas by 2030. These efforts are fundamental not only due to their direct impact but because they inspire the whole industry to adopt a more sustainable mindset.

Autonomous Vehicles

Even though autonomous vehicles, be it trucks or drones, have become closely associated with the close future of logistics, we are still likely to see it in only its trial stage throughout the next year. Nevertheless, one of the most discussed logistics technology trends of recent time.

For example, UPS Ventures has made a minority investment in autonomous driving company TuSimple. Together, both companies are testing self-driving trucks on a route in Arizona to determine whether the vehicles can improve service and efficiency in the UPS network. This means that UPS and TuSimple join the ranks of other companies, including Daimler, Tesla, Starsky Robotics, Einride, and Embark, that have the aim to remove the drivers from freight haulers altogether.

But interestingly, companies are starting to see the potential of autonomous vehicles even in unexpected areas, such as fleet maintenance. Austrian Airlines is using drones that are deployed in hangars to perform standard maintenance tasks and document any potential damage outside of the aircraft. Doing this could not only cut down maintenance costs but also free up the workload of technicians. As more drones are being considered for small package delivery purposes, it wouldn’t be surprising to see more trial runs and pilot project approvals. In fact, Alphabet’s Wing, the first federally-approved delivery drone in the US, has made its first delivery while UPS became America’s first nationwide drone airline. It will be interesting to see how many other companies can take their lead on drone delivery.

Warehouse Robotics

It’s without a doubt that warehouse operations have undergone a significant shift in recent years – and with technology being progressively integrated, this is one of the logistics technology trends that is likely to continue. One of the obvious innovations is warehouse robotics, a fast-growing field. After all, according to the Global Customer Report 2019, there has been an 18% year-over-year increase in testing of warehouse robotics. Boston Dynamics’ mobile warehouse robot, Handle, is one great example: The company has developed a completely autonomous robot with a small footprint, long reach, and vision system which all enable it to unload trucks, build pallets, and move boxes throughout any warehouse facility.

Whether it’s wearable technology, driverless vehicles, or multifunctional robots, robotization can significantly improve the efficiency and speed of warehouse processes. Companies such as GreyOrange and Locus Robotics already incorporate robots that autonomously move around the warehouse. With machine-learning technologies and sensors ensuring extreme accuracy and easy traceability, the modern warehouse will start seeing the inclusion of many more autonomous robots.