Logistics industry trends for 2021 (Part 1)

Logistics industry trends for 2021 (Part 1)
Logistics are an indispensable tool for any business organization that wants to run efficiently consuming the least amount of resources possible and at the same time achieving the goals set at the right time. It’s a useful tool in any scenario and its presence keeps growing exponentially.

2020 was certainly a year brimming with major changes as we witnessed the massive increase of e-commerce. The Covid-19 pandemic brought stability to some trends that were on the rise and the industry has been forced to bet on digital transformation in order to accelerate the automation processes on logistics, so it's really important to get to know the industry trends as well as all the factors that can influence and sustain the growth in logistics this year.

Artificial Intelligence

The pressure to build more agile businesses it’s fully on, and AI is set to play a major role in the logistics sector opening new possibilities with its wide range of uses. With its complex data networks and information channels, the logistics sector is an ideal fit for AI regarding demand forecasting, supply planning, route optimization, and dynamic pricing. Artificial Intelligence can aid decisions related to capacity planning, forecasting, and network optimization, thereby streamlining operations and enhancing overall supply chain performance. AI is finding extensive use in dynamic route optimization, managing delivery time windows, optimize fuel consumption, and load capacity utilization, among many other activities in last-mile deliveries thereby propelling the digitization of supply chains. On the other hand, next-generation logistics entail fully-automated warehousing, which will come in hand with major breakthroughs in AI development.


The introduction of 5G makes will inevitably lead us to the full automation stage in warehousing. The integrated use of 5G and AI is right around the corner. With the existing communication tech, hardware chips embedded in many robotic devices are often underused due to problems such as latency and excessive energy consumption. The reliable transmission enabled by 5G will undoubtedly facilitate the use of intelligent robots. As a transport layer technology, 5G will provide a robust communication environment that allows the simultaneous access of massive numbers of devices, will enable smart terminal equipment like drones, robots, shuttles, wearable devices, and sorting equipment, to play a larger role in different modules of warehousing.


Blockchain has emerged in the last couple of years as a major solution for some of the problems and inefficiencies plaguing the logistics industry for decades. Traditionally, the data from transactions between parties is stored individually with no overview of all the activities, which constitutes a huge trust issue that makes collaboration a lot more difficult. Blockchain resolves these issues because all the data is shared by all the parties involved. Also, the technology creates an encrypted digital record that tracks goods at every stage of the supply chain. It makes any irregularity clearly visible, enabling companies to solve it quickly. And it can automate processes while also making it easier to verify goods - reducing paperwork and supporting end-to-end traceability.

Big Data & Machine Learning

The concept of big data goes well with the logistics business. It is expected that logistics companies can experience consistent growth due to the use of big data analytics on their operational activities. Data sets collected from various sources should be turned into something productive to help in decision-making.

Machine learning is a subset of AI that allows an algorithm, software or system to learn and adjust without being specifically programmed to do so. It typically uses data or observations to train a computer model wherein different patterns in the data (combined with actual and predicted outcomes) are analyzed and used to improve how the technology functions. Machine Learning (ML) models, based on algorithms, are great at analyzing trends, spotting anomalies, and deriving predictive insights within massive data sets.

These powerful functionalities make it an ideal solution to address some of the main challenges of the supply chain and logistics industry like poor planning, rising transportation costs, inefficient supplier relations management, inventory inconsistencies, and technical downtimes.


Robotics applied to logistics involves using robots and machines with smart systems to automate tasks like organization, transfers, delivery, and product retrieving in a warehouse. The difference between traditional machinery and industrial robots is that the latter are associated with artificial intelligence systems that allow them to handle more complex variables and react quickly and independently by means of algorithms. That is to say, compared with a robotic arm in a conventional production line, a smart logistics robot can learn new tasks and execute them to cover things that needed human assistance up until now. Industrial robots also help to support manual work, streamlining processes. Retail giants like Amazon and Walmart that have already deployed robots in their warehouses and fulfillment centers will only expand their deployments, especially in our current economic climate.

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