Three technologies shaping the future of the logistics industry
The logistics industry is transforming to make way for the demands of the future. Continually looking for improvements to reduce travel times and increase efficiencies overall, technological advancements play a vital role in this transformation.
Discover three technologies shaping distribution methods with their aim to promote growth and improve efficiencies.
1. Internet of Things (IoT)
The Internet of Things (IoT) are physical objects that are connected to the internet and can monitor, report on, send and receive data.
Standardization is important to define specifications for the ability of computer systems or software to collect and use such data. Standards can define best practice use of the technology and present opportunities in new areas and markets. For example, IEEE 1547.3:2007 gives guidelines for monitoring, information exchange and control of distributed resources interconnected with electric power systems and TS 102 689:2.1.1 describes machine-to-machine (M2M) service requirements aimed at an efficient end-to-end delivery of M2M services.
While the IoT doesn't just serve the logistics industry, it has had a major impact on the ability to track products throughout their distribution cycle, improve supply chain monitoring and even driver safety.
Inventory and goods tracking
From raw materials, to storage containers, to the final product, IoT devices can identify the location of goods at any stage. This technology can provide accurate information to assist with managing the movement of goods, meeting deadlines and tracking deliveries. It can also play a vital role in monitoring conditions including temperature and light exposure for sensitive items that require specific storage conditions.
Supply chain monitoring
Overall, the ability to monitor products throughout their movement in a supply chain can provide clearer tracking visibility, identify risks or issues and improve communication between all stakeholders. The IoT can assist with efficient supply chain monitoring and improve quality, risk, product and movement management.
Driver safety
The IoT enables a connection between devices in order to gather and communicate data. It can obtain data such as driving behaviour, road conditions or even the need for infrastructure maintenance. Utilizing this technology can enhance driver safety, where predictions are used to make decisions that prioritize driver safety.
2. Artificial and augmented intelligence
Artificial intelligence (AI) can pave the way for a logistics company to address and improve the most important objectives - achieving high volumes with lower margins on strict deadlines. AI can optimize functions across a business, even an entire network.
A standardized approach defines best practices in order to implement these technologies. For example, DIN SPEC 92001-1:2019 establishes life cycle processes and quality requirements of AI modules.
As artificial intelligence can make drastic changes within the logistics industry, the International Organization for Standardization (ISO) are currently developing a range of Standards to assist in its implementation including framework for artificial intelligence (AI) systems using machine learning (ML), process management framework for Big data analytics, assessment of the robustness of neural networks and risk management.
With AI becoming more accessible and more importantly affordable, the logistics industry has embraced this technology to automate warehousing tasks, predict demands and improve back office operations. Alongside AI has also risen augmented intelligence - utilizing human expertise alongside AI - which is now making its mark on the industry.
Warehousing tasks and operations
AI is transforming warehousing tasks, including inventory processing, moving products, sorting items and packing products for deliveries. It can even improve the use of space in a warehouse. Soon we can come to expect that as AI evolves, it can even improve organizing products and stock as well as automate quality control efforts.
Predictive demand
AI technology can improve the accuracy of demand predictions while taking into consideration a variety of factors to enhance logistics demand forecasting. Improving predicting demands can assist with meeting strict deadlines and save in areas of delivery, maintenance and leasing costs. Staying on top of demand can also improve customer experience and satisfaction.
Back office operations
Back office operations should not be overlooked when implementing AI technology within a business. Areas including compliance, accounting and human resources can use the automation of tedious and repetitive tasks while benefiting from data accuracy and security to improve overall efficiencies.
Augmented intelligence
Alongside artificial intelligence is the increased popularity of augmented intelligence. Rather than a standalone approach of machine learning, augmented intelligence has been designed to combine the insights and recommendations from AI and include the human aspect into the decision-making process. This sees an employee making the final decisions based on the accumulated knowledge.