We could consider logistics digital transformation as the process of implementing specific technology and digitization, in the whole set of processes that make up the industry, starting with the way logistics companies communicate with their customers, through the planning of their operations and deliveries, and of course the way they manage their internal processes.
Logistics digital transformation, like digitization in any other area or sector, has as its main objective to improve efficiency, reduce costs and increase customer satisfaction, which, by the way, with the rise of online sales, has been one of the main drivers of logistics digital transformation. Customer expectation for fast and reliable delivery has increased the pressure on logistics companies that have had to adapt and provide high quality delivery services.
Technologies applied to the logistics chain.
In order to adapt to this demand, logistics companies have adopted a number of digital technologies and solutions. Some examples include:
1.- Supply chain management (SCM) systems.
These digital systems allow logistics companies to plan and coordinate the flow of materials and products along the supply chain, from suppliers to end customers, with models or types of management unthinkable without the use of technology such as, for example:
Digital twins. A digital twin is a product of the logistics digital transformation and consists of a digital representation of a process or a complete facility as a real warehouse. It is used to simulate and analyze the performance and efficiency of the process or warehouse in situations different from the real ones. It allows for inventory changes, product location changes, or workflow changes to make informed decisions on how to optimize process or warehouse performance and efficiency, without making physical changes.
Warehouse as a Service. As an alternative to owning or renting your own warehouse space, it is really interesting for companies that need temporary storage space or do not have the capacity or resources to manage a warehouse of their own. Thanks to the digital logistics transformation, companies with excess resources in their warehouse and well digitized can put this excess at the service of other companies, and get an economic return for it.
VMI (Vendor Managed Inventory), is a way of managing inventory in which the supplier is responsible for maintaining the right level of inventory for the client company. It requires good communication and collaboration between the client company and the supplier, since its efficiency is based on the accuracy and transparency that the client company maintains in the digital exchange of information about its demand and consumption pattern.
2.- Delivery tracking and tracing systems.
These systems have brought a number of advantages thanks to the digital logistics transformation, some of which include:
Increased productivity: these systems enable better tracking and monitoring of shipments in real time, and facilitate more efficient decision-making to reduce delivery times.
Improved transparency: by providing detailed, real-time information on shipment location and delivery status, they enable both companies and customers to have a transparent view of the delivery process.
Collaborative efficiency: these systems facilitate integration and collaboration with different stakeholders in the delivery process, such as suppliers and carriers. This gives greater flexibility and adaptability to logistics management.
Cost reduction: the digital logistics transformation, by enabling increased productivity, improved transparency and enhanced collaboration, i.e. the integration of other links in the chain, has reduced costs by improving efficiency in elements such as the planning of delivery routes, while increasing their accuracy and reliability.
3.- Technologies with great potential.
We refer to technologies such as Big Data, Artificial Intelligence, Machine Learning, Natural Language Processing, Blockchain and Cloud Computing.
Big Data: technology that enables massive data storage and analysis, which can improve efficiency and decision-making in the logistics industry as well.
Artificial Intelligence: which enables machines to perform tasks that would normally require human intelligence, such as natural language processing and machine learning.
Natural Language Processing: is a technology that allows machines to understand, interpret and process human language effectively. Imagine the use we could make of this new machine capability within an EMS system. We will be able to directly tell our WMS system things like "calculate me an ABC/XYZ of the thousand best-selling references comparing sales with profit margin and show it to me in a simple graph", without having to use specific commands or a complicated user interface.
Machine Learning: a type of artificial intelligence that allows machines to learn and improve themselves based on data or past experience. This technology is applied in WMS systems providing a number of advantages such as having the ability to analyze past demand to establish improvements in inventory layout, or that it is the WMS system itself that, using data on the performance and efficiency of workers, identifies areas for improvement or optimizes the use of space based on location patterns.
Blockchain: a technology that enables the creation of ultra-secure, decentralized databases shared among multiple stakeholders. It is a technology with enormous potential for document management at an international level where it is expected to greatly reduce processing times.
Cloud computing or data processing in the cloud: this allows companies to adjust their use of IT resources according to their needs, access to permanently updated high quality applications, such as a WMS system, without having to invest in expensive software, as they pay only for the use they make of the contracted resources.
Automation and robots.
Process automation is one of the major revolutions of the digital logistics transformation. Apart from its undeniable spectacularity and the image of technification that it brings to a company, having robots in logistics has other advantages such as greater speed and accuracy in repetitive and monotonous tasks, increased efficiency in processes and the corresponding reduction of waste, rework and costs, and greater reliability and speed without errors in the processes.
Logistics digital transformation, like digitization in any other area or sector, has as its main objective to improve efficiency, reduce costs and increase customer satisfaction, which, by the way, with the rise of online sales, has been one of the main drivers of logistics digital transformation. Customer expectation for fast and reliable delivery has increased the pressure on logistics companies that have had to adapt and provide high quality delivery services.
Technologies applied to the logistics chain.
In order to adapt to this demand, logistics companies have adopted a number of digital technologies and solutions. Some examples include:
1.- Supply chain management (SCM) systems.
These digital systems allow logistics companies to plan and coordinate the flow of materials and products along the supply chain, from suppliers to end customers, with models or types of management unthinkable without the use of technology such as, for example:
Digital twins. A digital twin is a product of the logistics digital transformation and consists of a digital representation of a process or a complete facility as a real warehouse. It is used to simulate and analyze the performance and efficiency of the process or warehouse in situations different from the real ones. It allows for inventory changes, product location changes, or workflow changes to make informed decisions on how to optimize process or warehouse performance and efficiency, without making physical changes.
Warehouse as a Service. As an alternative to owning or renting your own warehouse space, it is really interesting for companies that need temporary storage space or do not have the capacity or resources to manage a warehouse of their own. Thanks to the digital logistics transformation, companies with excess resources in their warehouse and well digitized can put this excess at the service of other companies, and get an economic return for it.
VMI (Vendor Managed Inventory), is a way of managing inventory in which the supplier is responsible for maintaining the right level of inventory for the client company. It requires good communication and collaboration between the client company and the supplier, since its efficiency is based on the accuracy and transparency that the client company maintains in the digital exchange of information about its demand and consumption pattern.
2.- Delivery tracking and tracing systems.
These systems have brought a number of advantages thanks to the digital logistics transformation, some of which include:
Increased productivity: these systems enable better tracking and monitoring of shipments in real time, and facilitate more efficient decision-making to reduce delivery times.
Improved transparency: by providing detailed, real-time information on shipment location and delivery status, they enable both companies and customers to have a transparent view of the delivery process.
Collaborative efficiency: these systems facilitate integration and collaboration with different stakeholders in the delivery process, such as suppliers and carriers. This gives greater flexibility and adaptability to logistics management.
Cost reduction: the digital logistics transformation, by enabling increased productivity, improved transparency and enhanced collaboration, i.e. the integration of other links in the chain, has reduced costs by improving efficiency in elements such as the planning of delivery routes, while increasing their accuracy and reliability.
3.- Technologies with great potential.
We refer to technologies such as Big Data, Artificial Intelligence, Machine Learning, Natural Language Processing, Blockchain and Cloud Computing.
Big Data: technology that enables massive data storage and analysis, which can improve efficiency and decision-making in the logistics industry as well.
Artificial Intelligence: which enables machines to perform tasks that would normally require human intelligence, such as natural language processing and machine learning.
Natural Language Processing: is a technology that allows machines to understand, interpret and process human language effectively. Imagine the use we could make of this new machine capability within an EMS system. We will be able to directly tell our WMS system things like "calculate me an ABC/XYZ of the thousand best-selling references comparing sales with profit margin and show it to me in a simple graph", without having to use specific commands or a complicated user interface.
Machine Learning: a type of artificial intelligence that allows machines to learn and improve themselves based on data or past experience. This technology is applied in WMS systems providing a number of advantages such as having the ability to analyze past demand to establish improvements in inventory layout, or that it is the WMS system itself that, using data on the performance and efficiency of workers, identifies areas for improvement or optimizes the use of space based on location patterns.
Blockchain: a technology that enables the creation of ultra-secure, decentralized databases shared among multiple stakeholders. It is a technology with enormous potential for document management at an international level where it is expected to greatly reduce processing times.
Cloud computing or data processing in the cloud: this allows companies to adjust their use of IT resources according to their needs, access to permanently updated high quality applications, such as a WMS system, without having to invest in expensive software, as they pay only for the use they make of the contracted resources.
Automation and robots.
Process automation is one of the major revolutions of the digital logistics transformation. Apart from its undeniable spectacularity and the image of technification that it brings to a company, having robots in logistics has other advantages such as greater speed and accuracy in repetitive and monotonous tasks, increased efficiency in processes and the corresponding reduction of waste, rework and costs, and greater reliability and speed without errors in the processes.