The logistics sector has seen a large increase in investment in innovation and has become an area in which traditional players are increasingly confronted with new players and new competitive dynamics. This determines the need to consolidate the supply chain around the end-customer to provide him with an experience that meets his expectations, ensuring price transparency, the possibility to track the purchase and adequate digital service.
More and more often we hear about logistics in association with concepts such as Big data, IoT, self-driving trucks, digital twin, drones and robots, all tools that contribute to the growth of competitiveness of the major players in the industry.
Logistics and innovation, technologies
The McKinsey Global Institute has made research on the evolution of logistics, analyzing how much the role of Artificial Intelligence applications will impact the industry by 2030. The research highlighted 10 technologies that can revolutionize the operation and management of the warehouse:
- Multi shuttle system: automatic systems that do not require the intervention of operators in the arrangement of goods
- Analytics tools: algorithms that support operators in performance analysis and forecasting
- Optical recognition: sensors used to scan and recognize objects
- Conveyor belt connections: connections between multiple belts that analyze various item flows
- Management system: software that analyzes the data flows of the warehouse
- Smart storage: advanced solutions for storing and retrieving goods in the warehouse
- 3D printing: autonomous realization of tools with different materials
- Swarm AGV Robots: vehicles that move goods, following software commands
- Smart glasses: augmented reality glasses that allow you to receive more information on certain products
- Picking robots: robotic arms capable of imitating human movements.
The software developed in this area and the technological innovations adopted by some companies have become the differentiation key that contributes to the creation of brand loyalty, internal business efficiency and sustainable profit growth. In contrast, companies stuck on traditional approaches and turning their backs on digitization risk falling behind new market entrants.
Logistics and innovation, use cases
For example, the implementation of automation in the logistics industry is a relevant technology driver, capable of streamlining processes in areas as diverse as managing the collection of data on consumer and market preferences, automated order processing, warehouse workflows and deliveries. But, more than anything else, automation in logistics implies transparency. This is the only way to monitor the data flows that feed the supply chain at every point in real-time, eliminating the risk of human error and, consequently, making the entire system more efficient.
Another example of innovation in this area involves the use of SaaS models and digital platforms. These make it possible to direct customers to services that interact seamlessly with each other and operate using the same data sources.
Moreover, by using tools of this type, customers do not need to access different services because they will be able to perform all functions through a single software. Each element that is customized for a specific business is automatically applied to all related solutions. In this way, a digital platform enables logistics providers to equip their customers with solutions that meet their needs through a subscription. Customers gain by reducing costs and time spent on manually setting up their IT infrastructure, while the provider increases its customer base and places the pivot of its logistics services structure on them.
Often Saas and digital platforms also play a key role in the support they can provide for the analysis of large amounts of data. Having a lot of data coming from heterogeneous sources and used in different areas implies the need to have a data-driven approach, but above all to have a tool able to order, group, map and process data to introduce innovation in the entire logistics process. Only in this way can data become a powerful input that can generate added value to the logistics service offered.
These applications represent concrete examples of the direction in which the logistics sector is heading. In this perspective, it becomes necessary to adapt the existing technology architecture to the market and exploit innovation to extract from data and processes the added value that the customer needs and will be able to recognize.