Managing some operational activities such as handling transportation quotation requests received via e-mail can be a challenging and time-consuming task, especially if you are trying to make strategic resource decisions in a rapidly changing business environment.
Traditional supply chain management can no longer offer companies the flexibility they need given the characteristics of today's ecosystem, which is characterized by volatility, disruptions and unpredictability. For this reason, most companies have begun to automate logistics and supply chain processes with the help of technologies such as Artificial Intelligence, Machine Learning and others.
By digitalizing the process and leveraging Machine Learning algorithms and other automation technologies, you can greatly streamline operations and free up time and resources for other activities. It is therefore possible to use automations in the supply chain to make strategic resource decisions and effectively manage the demand for transportation quotes, ultimately aiding the digitalization process and competitiveness in an increasingly interconnected world.
The leading technologies needed to enhance supply chain automation software are Artificial Intelligence (AI) and Machine Learning: if workers now waste 20% to 30% of their work week handling documents or document-based information, the use of automated intelligent algorithms can optimize business processes, improve accuracy and response time, achieve significant operational efficiency gains and major cost reductions.
For example, shipping companies need to streamline back-office activities for creating draft bills of lading, shipping quotations, and cargo manifests.
However, they often experience process slowdowns due to the length of time it takes to handle spot quotations, Packing List information collection and related data entry errors, complications in container tracking. These problems can be overcome by choosing innovative and scalable technology solutions.
Why digitalize and automate the supply chain?
The growing amount of supply chain data requires more digital and automated tools.
New technologies are demonstrating the importance of data collection, automated processing and analysis in supply chain optimization as they help increase efficiency and reduce costs.
With the generation of huge amounts of data at all stages of the supply chain, from planning to final delivery, only technology tools are capable of processing such quantities from various sources without wasting valuable time and information.
For this reason, more and more companies are increasing the amount of digital tools in their operations that enable them to make informed changes for supply chain optimization at any time.
In addition, digitalization and supply chain automation can bring a number of benefits to companies, including cost savings and strategic decision making.
Using Machine Learning algorithms and other automation technologies, companies can optimize back office activities and reduce the risk of disruptions, ultimately helping to reduce costs and improve efficiency. The use of data analytics and other digital tools can therefore help companies better understand their supply chain operations, enabling them to identify opportunities for improvement and make more informed decisions. Overall, the digitalization process can help companies better manage their supply chains and remain competitive in an increasingly interconnected world.
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Back-office tasks automated with AI and Machine Learning
In the logistics world, it can happen that employees spend valuable time reading paper documents or emails in order to extract the information they need to perform operational tasks, such as generating trade quotations.
This is clearly a repetitive and low value-added activity: if a C-level manager is tasked with making strategic resource decisions, he or she needs to direct them toward less time-consuming and more profitable tasks.
This is where automation comes in!
For example, as part of the digitalization process, automated email quote creation with artificial intelligence and machine learning can be a valuable tool for companies that want to streamline their operations and stay ahead of the curve.
Automated email quotes using Artificial Intelligence and Machine Learning can help companies speed up the time it takes to create quotes and make strategic resource decisions. These advanced technologies help companies streamline back office activities in ways that reduce costs and the risk of disruption, ultimately helping to reduce costs and improve efficiency.
The use of data analytics and other digital tools can also enable companies to better understand their operations and thus identify opportunities for improvement. In this way, automation can help companies better manage processes and remain attractive in an increasingly competitive market
Anyway, there are many use cases for digitization and process automation in supply chain and logistics. These use cases can range from the area of logistics corridors and trade hubs, trade facilitation, consumer contact and interaction points, circular services, supplier relations, digital platforms and marketplaces, supply chain monitoring, risk management, the financial side of trade and supply chain to decision-making processes.
Let us therefore see a specific case of the operation of supply chain automations based on AI and Machine Learning.
Automating spot quotation management, packing list reading and container tracking
Supply chain automation can therefore support companies in automated data entry operations in ERP or WMS from logistics documents, or help the transportation industry automate and standardize the extraction of information needed for creating quotations with Artificial Intelligence technology. This enables significant operational efficiency gains.
Thus, it is clear that digitalization in transportation meets the need to streamline back-office activities for the creation of draft bills of lading, shipping quotations and freight manifests, and also enables cost cutting, reduced operational time and streamlined processes.
Let's look at a real-world case study that shows in practice how digitization can help the transportation industry achieve significant operational efficiency gains and major cost reductions. Let's take a number of activities that are usually connected: spot quotation management, packing list reading, and container tracking.
“In accomplishing these tasks, transportation companies experience process slowdowns due to long lead times in spot quotation management, packing list information collection and related data entry errors, complications in container tracking. These blockages can be overcome with an innovative and scalable technology solution.”
When the sales department receives spot quotation requests from customers, Wenda's Intelligent Document Processing with AI reads the emails automatically, performs a data analysis and, in dialogue with the management system, sends the quotation to the customer. Once the customer accepts the quotation, shipment tracking can be activated; data can be automatically extracted from a packing list or bill of lading and then used to track the shipment via container tracking to the point of delivery.
With Wenda's Container Tracking, it is possible to track a container automatically simply by starting with a document where the container number is located (Packing List, bill of lading, etc.). Automatic container tracking can be enabled by starting with a one-time configuration, then, enabling and activating the document from which we want to take the information-in this case, a packing list.
Once the document type is recognized and the container number is identified, Wenda's intelligent algorithms automatically read all the information found within the document-in this case, including the container number.
Whenever a packing list is received, the system will read everything by itself, detecting the number of containers and automatically triggering tracking.
You can view tracking details by verifying all milestones of the tracked container, follow its path on the map, and receive real-time information and notifications, along with all container and shipping or transport company data, closing the loop on a high value-added digitalization process.
