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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. However, one should not forget, that with all the recent AI hype come a lot of misconceptions about the capabilities of the technology. You can read more about what AI in Logistics is and what it isn’t here.

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.

Big Data Analytics Will Uncover Hidden Inefficiencies

Reliable big data 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.

Data-Driven Optimization Will Redefine Logistics Planning

Focusing on logistics optimization is critical for exceeding customer expectations and ensuring smooth operations within logistics networks. It’s not just about avoiding problems – it’s about carefully refining strategies to build a network that can handle the challenges and fluctuations of modern business.

However, logistics optimization could be extremely challenging as it includes many important variables to consider –  inventory management, warehousing, transportation, and distribution, adding a layer of complexity to calculate the optimal way of operating the network.

Logistics planners must adopt a dual approach of long-term vision and short-term agility to plan optimally. Long-term planning should focus on adapting to market dynamics, reducing operational costs, enhancing customer service, and staying competitive. This involves designing a network with strategically located facilities to minimize transportation costs and transit times. Meanwhile, short-term planning involves breaking down long-term objectives into actionable priorities, utilizing logistics technologies like real-time data analytics and AI-powered forecasting to address bottlenecks and optimize resource allocation on the fly.

Through this blend of foresight and adaptability, logistics optimization becomes a cornerstone for efficient operations and superior customer satisfaction.

Customer Service Will Catalyze the Change

Regarding customer satisfaction – industry leaders predict that thirty-minute deliveries will become a standard expectation for shoppers thus building your business around the promise of swift, yet affordable deliveries becomes paramount.

Collaborative efforts among retailers, logistics providers, and other industry players, supported by data-driven solutions, are key to optimizing processes and enhancing the B2B2C customer experience. However, if your company wants to ensure that you are meeting a base level of customer service, we advice to focus on these 2 things:

  • Ensure precise delivery windows and be transparent: Provide delivery time estimates with a flexible timeframe, such as between 14:00 and 15:00 instead of specifying 14:00 precisely, allowing drivers greater flexibility. Implementing visible tracking mechanisms boosts transparency, efficiency, and customer satisfaction.

  • Prepare for unforeseen events: Establish contingency plans to address disruptions. Strategies like dual sourcing and direct distribution from warehouses and local stores enhance operational flexibility.

Prioritizing customer service in logistics is critical, but thanks to the latest logistics technologies, focusing on meeting expectations regarding timeliness, reliability, pricing, and flexibility can be as smooth as ever.

Logistics Automation Will Enhance the Workforce

Optimizing logistics processes while simultaneously providing clients with high-quality service is not an easy feat. There are too many variables to consider for a human brain when planning for optimal shipping/delivery. Manual planning processes, especially with multiple transportation legs and unpredictable demand, prove time-intensive.

To address these hurdles, leveraging AI and smart scheduling offers a solution for optimizing fleet management. Logistics automation platforms integrate diverse data sources to devise efficient routing plans and reduce delays. That can save time for the logistics professionals to focus on what matters – providing an exceptional quality of service. However, to leverage automation to the fullest, business leaders must closely monitor the innovation curve and upskill their workforce to stay competitive.

The best benefits lie in the synergy between humans and technology—those who embrace the available tools alongside investing in training their workforce will succeed in transforming their business to be as efficient as possible.

Sustainable Logistics Will Reduce Industry’s Carbon Footprint

The doo news is that Logistics efficiency and sustainability are closely intertwined. Elevating one inherently boosts the other. Sustainability initiatives are transforming the logistics industry, introducing eco-friendly strategies that reduce environmental impact. Central to this shift is the savvy use of logistics technology, which streamlines route planning, minimizes empty kilometers, and drives increased utilization.

2024 represents a crucial moment for sustainability in the sector, driven by pressing environmental concerns, notably in Europe where transport-related greenhouse gas emissions account for over 27% of the carbon footprint. With ambitious climate targets set for 2040, the Transport and Logistics sector is under pressure to prioritize sustainability.

Fortunately, logistics technology and alternative fuel vehicles leading the way towards a future where logistics operations are more environmentally friendly and efficient.