RPA promotes logistics to an intelligent era丨10 scenarios for the application of RPA in the logistics industry
With the continuous growth of China's national economy, the logistics industry has developed into a huge pillar industry group. However, on the whole, the scale of logistics enterprises is limited, the level of service and the degree of information construction still need to be improved.
The logistics business process is cumbersome, and there is a lack of effective support of information technology in important links such as order processing, expense entry, and business accounting, which often requires a lot of manpower and time. Problems such as low efficiency in processing business documents, untimely information feedback, and high error rates also restrict the development of logistics enterprises and affect the improvement of service levels.
How to use digital information technology to break through the development bottleneck and transform to high efficiency and intelligence has become a top priority for traditional logistics enterprises.
In recent years, technologies such as big data, Internet of Things, and RPA have developed rapidly, providing new solutions for the transformation and upgrading of logistics enterprises.
On the basis of fully sorting out business processes, RPA robots can replace humans to complete large-scale, repeatable tasks based on clear rules, improve process automation, reduce labor and time costs, and enhance corporate competitiveness.
Advantages of RPA (UB Store) applied to the logistics industry:
1. Optimize business processes: RPA can reduce manual data input from internal systems to B2B portals and automate business processes.
2. Reduce labor costs: RPA can free employees from boring and repetitive tasks, which not only improves efficiency, but also alleviates the shortage of manpower during peak business periods, thereby reducing labor costs.
3. Improve business quality: Even the most attentive employees will inevitably make mistakes. As long as the RPA robot is set correctly, it can execute tasks completely according to the script, effectively avoiding human errors and improving business quality and accuracy.
4. The operation is simple and easy to use: RPA is non-invasive and can integrate various legacy systems without development. The operation is simple and even ordinary employees can quickly get started.
Top 10 scenarios for the application of RPA in the logistics industry
Scenario 1: The automatic shipping
logistics operator needs to manually inquire in the ERP according to the established conditions, then export and make the logistics order, send it to the logistics supplier by mail or enter it in the order system provided by the logistics supplier. Many manual operations, large amount of data, high frequency and error-prone.
The RPA robot can query the goods to be shipped from the ERP according to a predetermined time period and automatically generate logistics orders. The waybill or order is then generated in the logistics provider's system. Logistics operators only need to pay attention to abnormal situations and adjust logistics orders, which greatly reduces workload while ensuring data accuracy.
Scenario 2: Logistics status update
After the goods are shipped, supply chain managers need to log in to the external system or website of the logistics provider, query the logistics status information according to the logistics order number, and then manually update it to their logistics platform. The workload is large and the operation is very cumbersome.
The RPA robot will regularly and automatically check the logistics status update on the logistics provider’s external website or system according to the number of the logistics order, and copy the latest information to the designated system. The workload is greatly reduced and data can be updated actively in time, which improves the customer experience.
Scenario 3: Logistics bidding The
customer service staff of the logistics supplier needs to log in to Party A's external bidding system or website frequently, perform project accounting based on the project bidding information, and then manually submit the relevant bidding documents and make a quotation. The workload is large, the operation is very cumbersome and sometimes it is difficult to make a normal submission before the deadline for the bidding, and sometimes the quotation error will cause other consequences.
RPA will regularly and automatically check the latest logistics project bidding on Party A’s external bidding website or system, and then perform project accounting according to the pre-set business logic, and submit relevant information and quotations. The manual workload is greatly reduced, and there will be no quotation errors.
Scenario 4: The booking process has
more than 50 fields in the booking receipt, and it takes more than 5 minutes for the customer service operator to enter a single order. Since there are many sources of booking receipts, the format cannot be unified, so it is difficult to implement system import. In addition, each ticket must be checked repeatedly to avoid data errors. The workload is very large, and it is often necessary to work overtime to complete the booking data entry during peak seasons.
RPA will automatically scan and digitize booking documents in multiple formats through computer vision, and then automatically enter them. When abnormal conditions occur, manual inspection and verification are introduced. The operator's input workload is greatly reduced, and at the same time, it can also be dealt with by increasing the resources of small craftsmen during peak seasons.
Scenario 5: Order processing
RPA robots can replace employees to complete manual operations during order processing, and automatically search and process customer orders in the database. It not only reduces the workload of employees, improves work efficiency, but also hardly makes mistakes, greatly saving processing time.
Scenario 6: Cargo tracking
RPA can automatically extract detailed shipping information from received emails, record the shipping status in the dispatch system, and provide customers with accurate shipping schedules to better track logistics information.
Scenario 7: Inventory monitoring
Logistics inventory generally requires manufacturers and suppliers to monitor and maintain regularly to ensure that there are enough goods to meet customer needs. RPA robots can monitor inventory levels in real time. When the inventory is low, RPA can promptly notify relevant personnel to replenish and purchase in time, and provide real-time reports to optimize inventory requirements.
Scenario 8: Transportation management
can integrate the company's original transportation management system through RPA, solving the problems of regular follow-up and multi-system interaction during transportation. RPA can alleviate the boring and redundant manual tasks of transportation analysts, allowing them to focus on more meaningful work. In addition, RPA can also track and obtain information on the carrier's website to make shipment arrangements.
Scenario 9: Report generation
RPA combines the functions of machine learning (ML) and natural language processing (NLP) in AI technology to replace manual tasks that are automatically executed. For example, creating shipping orders, entering document information into a database, downloading reports, and entering valuable information into a CRM or ERP system. Expandable and flexible RPA robots can be easily integrated on different systems, process data across systems, reduce the workload of personnel, and avoid human errors.
Scenario 10: Invoicing processing
RPA robots can automatically post sales invoices and purchase orders to the accounting system without manual intervention, making the invoicing process faster and more effective, reducing customer waiting time, and improving payment efficiency. In addition, RPA can also check the bills, notify the relevant person in charge of the identified inconsistencies in time, and notify the accountants and customers via email after the payment is completed.
RPA (UB Store) technology provides automated tools for logistics front-line operators, which can help them automatically capture and enter data, or automate data processing according to established business rules, reducing workload while ensuring data availability accuracy. Staff no longer need to work overtime to do mechanical repetitive work, which improves process efficiency, improves customer satisfaction, and provides customers with more professional services.