A method, system, medium and product for order management suitable for suppliers

Abstract

The application relates to the technical field of order data management, in particular to an order management method, system, medium and product suitable for a supplier, the method comprising the following steps: obtaining to-be-processed order information, and determining a processing operation of the to-be-processed order information; generating an operation guide based on the processing operation and the to-be-processed order information, and jumping from a current interface to a processing interface based on the processing operation; identifying an interface layout feature of the processing interface, and feeding back the operation guide to a preset prompt area in the processing interface based on the interface layout feature; in the process that a to-be-processed supplier executes the processing operation, operation behavior is detected in real time and is matched and verified with the operation guide, when it is detected that the operation behavior deviates from the operation guide, a real-time pop-up window is triggered to remind and feedback deviation correction suggestions, and the to-be-processed supplier is guided to process the to-be-processed order information in compliance with regulations. The application facilitates improvement of order processing efficiency and compliance.

Description

Technical Field

[0001] This application relates to the field of order data management technology, and in particular to an order management method, system, medium and product suitable for suppliers. Background Technology

[0002] In supply chain trade, the efficiency and compliance of order processing on the supplier side directly affect the overall operational efficiency of the supply chain and are also a key link in ensuring the stability of cooperation between suppliers and buyers. Currently, existing technologies have formed a standard implementation method for order information management on the supplier side. That is, the supplier obtains order information to be processed in batches or individually from the buyer's interface. After manually identifying the order type, supply requirements, and other core information, the supplier is redirected from the current order list interface to a fixed order processing interface according to the processing operation selected by the supplier. At the same time, standardized general operation instructions are displayed at the top or sidebar of the processing interface to guide the supplier to complete the order processing operation.

[0003] However, the operational guidelines generated by conventional methods are generally standardized content, and the displayed guidelines are disconnected from the actual operation of order information. When performing operations such as editing and reviewing, suppliers may need to frequently switch their focus between the displayed guidelines and the actual operation content, which significantly increases the processing time for a single order. At the same time, conventional methods can only display guidelines statically on the processing interface and cannot provide dynamic guidance based on the supplier's operation progress. Suppliers are prone to repeating operations due to misunderstandings of the guidelines and confusion about the operation steps, which further reduces the overall efficiency of order processing and makes it difficult to adapt to the actual needs of modern supply chain trade for efficient order processing. Summary of the Invention

[0004] To improve order processing efficiency and compliance, this application provides an order management method, system, medium, and product suitable for suppliers.

[0005] Firstly, this application provides an order management method suitable for suppliers, employing the following technical solution: An order management method applicable to suppliers includes: Obtain the order information to be processed and determine the processing operation for the order information to be processed; Based on the processing operation and the order information to be processed, an operation guide is generated, and the user is redirected from the current interface to the processing interface based on the processing operation. Identify the interface layout features of the processing interface, and based on the interface layout features, feed back the operation guidance to the preset prompt area in the processing interface; During the processing of the pending supplier, the operation behavior is detected in real time and matched with the operation guide. When the operation behavior deviates from the operation guide, a real-time pop-up reminder is triggered and a deviation correction suggestion is provided to guide the pending supplier to process the pending order information in compliance with regulations.

[0006] By adopting the above technical solution, the operation guide generated based on the processing operation and pending order information is tailored to the specific order processing needs. Simultaneously, by recognizing the layout features of the processing interface, the guide is accurately fed back to the preset prompt area, ensuring that the guide display matches the actual operation area within the processing interface. This avoids suppliers frequently switching their gaze to view the guide, significantly reducing the processing time for a single order. The precise display of the operation guide reduces the understanding cost for suppliers, minimizing invalid operations caused by misunderstandings. Furthermore, when an operation deviates from the guide, not only is a real-time pop-up reminder triggered, but also deviation correction suggestions are simultaneously fed back, providing suppliers with a clear direction for operational correction and avoiding invalid operations through repeated self-checking and attempts, further improving the overall efficiency of order processing.

[0007] In one possible implementation, when the number of pending order information exceeds a preset processing threshold, the method further includes: Identify the order initiation time in each pending order information, and sort all pending order information according to the chronological order of each order initiation time to generate a pending order list; Generate a pending quantity indicator based on the pending quantity of all pending orders; The pending list is folded to generate a folded list entry control, and the folded list entry control and the pending quantity prompt are superimposed on the order management function box. When the pending supplier triggers the folded list entry, the pending order list is expanded.

[0008] By adopting the above technical solution, the excess pending order information is sorted according to the order initiation time to generate a pending order list. This allows suppliers to clearly understand the order of order processing, avoiding omissions or errors caused by disordered orders. At the same time, a pending order quantity indicator is generated based on the excess pending order data. The collapsible list entry control and this indicator are superimposed on the order management function box to achieve a compact display of excess order information. This avoids the redundancy of interface information caused by the pending order list occupying a large area of ​​the operation interface. Moreover, the order list is only expanded when the supplier triggers the collapsible list entry control, which not only ensures the complete presentation of excess order information, but also avoids the interference of a static expanded list on the daily operation interface, reducing the distraction caused by interface information interference, and further improving the overall order processing efficiency in the scenario of excess pending orders.

[0009] In one possible implementation, the method further includes: Based on the order initiation time in each pending order information, determine the order dwell time for each pending order information, and determine the order stagnation value corresponding to each pending order information based on the order dwell time; Identify the number of pending review nodes in each pending order information from the process details in each pending order information, determine the historical review efficiency of each pending review node based on historical review information, and determine the order review value corresponding to each pending order information based on the historical review efficiency of each pending review node. Identify the order identifier in each pending order information, and identify the associated data of each pending order information from the pending order list based on each order identifier. Determine the order association value of each pending order information based on each associated data. The associated data includes the number of associated orders of the associated order information and the association initiation time of each associated order information. The order identifier of the pending order information is related to the associated order identifier of the corresponding associated order information. Based on the order stagnation value, the order review value, and the order association value of each pending order information, the order processing level of each pending order information is determined; Orders with a processing level higher than the preset processing level are identified as target orders to be processed, and dynamic pop-up information is generated based on the current operation interface information and the target orders to be processed.

[0010] By adopting the above technical solution, the order dwell time is determined based on the order initiation time and the order stagnation value is matched. The order review value is calculated by combining the number of pending review nodes and historical review efficiency. At the same time, the order association value is determined by relying on the order identifier association data. The order processing characteristics are quantified from three dimensions: stagnation, review, and association. This makes the priority determination of pending orders more data-supported and avoids the subjective arbitrariness of manual judgment. The order processing level of each pending order information is determined comprehensively based on multi-dimensional quantitative indicators, realizing the scientific and accurate division of order processing priorities. This allows pending suppliers to quickly identify high-priority target orders. When the processing level of a target pending order information is higher than the preset level, a dynamic pop-up message is generated based on the current operation interface information. This can provide targeted reminders for high-priority orders without interfering with the normal operation of pending suppliers, avoiding processing delays due to neglect of high-priority orders and ensuring the timeliness of important order processing.

[0011] In one possible implementation, generating the dynamic pop-up information based on the current user interface information and the target pending order information includes: Obtain the real-time order stagnation value and real-time order association value of the target pending order information, and generate a real-time growth factor based on the real-time order stagnation value and the real-time order association value; Obtain the historical operation process of the supplier to be processed within the historical analysis period, and determine the reminder interface area from the current operation interface information based on the historical operation process; An order reminder identifier is generated based on the order information to be processed. A dynamic pop-up message is generated based on the real-time growth factor and the order reminder identifier. The dynamic pop-up message is then fed back to the reminder interface area. The real-time growth factor is related to the display size of the dynamic pop-up message.

[0012] By adopting the above technical solution, a real-time growth factor is generated based on the real-time stagnation value and correlation value of the target pending orders. This links the display size of the dynamic pop-up information to the real-time urgency of the order. Suppliers pending orders can intuitively perceive the order priority through the pop-up size, quickly determining the processing priority without having to view cumbersome data. The alertable interface area is determined based on the supplier's historical operation process, ensuring that the dynamic pop-up is accurately displayed in an area that matches the supplier's operating habits, avoiding operational interference caused by the pop-up appearing in the core operation area. The real-time growth factor associated with the order characteristics, the alertable area that matches the operating habits, and the order reminder icon are combined to generate a dynamic pop-up and provide accurate feedback. This facilitates the personalized and dynamic display of reminder information while ensuring the effectiveness and user-friendliness of the reminder.

[0013] In one possible implementation, determining the alertable interface area from the current operation interface information based on the historical operation flow includes: Identify the operation information identifier of the current operation interface information, and determine the operation level based on the operation information identifier; When the operation level is higher than the preset operation level threshold, the predicted operation trajectory of the supplier to be processed is determined based on the historical operation process. Based on the real-time growth factor and the predicted operation trajectory, the area of ​​the interface that can be alerted is determined from the current operation interface information.

[0014] By adopting the above technical solution, the operation level is determined by identifying the operation information identifiers in the current operation interface. This facilitates the quantitative judgment of the importance and interference sensitivity of the current operation of the supplier to be processed, making the selection of the interface area objective. When the operation level is higher than the preset operation level threshold, the operation trajectory of the supplier to be processed is further predicted based on the historical operation process. This makes it easier to avoid core operation areas and key operation paths in advance, and avoid the reminder pop-up from obstructing and interfering with the high-level and high-importance operation of the supplier to be processed. By combining real-time growth factors and predicted operation trajectories to determine the interface area that can be reminded, the reminder location and operation behavior are intelligently adapted. This ensures that the reminders for high-priority orders can be effectively delivered, and also minimizes the impact on the normal operation of the supplier to be processed.

[0015] In one possible implementation, the method further includes: Identify the full-process operation data corresponding to the order information to be processed, including the node editing time, node viewing count, and historical error rate of each review node corresponding to the order information to be processed; Based on the weighting of each dimension of data in the entire process operation data, the password security level corresponding to the supplier to be processed is determined. When a remote login from the supplier to be processed is detected, the corresponding password generation rule is matched based on the password security level. The target review node is determined based on the node editing time, node viewing count, and historical error rate of each review node, and the target operation performance data corresponding to the target review node is determined from the full-process operation data. Based on the password generation rules and the target operation performance data, a unique verification password is generated and pushed to the terminal of the supplier to be processed to complete the login verification.

[0016] By adopting the above technical solution, and collecting full-process operation data such as node editing time, node viewing frequency, and historical error rate of the order to be processed at each review node, it is convenient to objectively quantify the operation habits and stability of the supplier to be processed. This allows the determination of password security level to be supported by real business data, avoiding overly general or subjective security level classification. The password security level is determined based on the weight ratio of operation data in each dimension, which facilitates differentiated security control that matches the operation risk of the supplier to be processed, improving the accuracy of account security protection. When a login from another location is detected, the corresponding password generation rule is adaptively matched according to the password security level, and a unique verification password is generated by combining the target operation performance data of the target review node. This deeply binds the verification password to the actual operation behavior of the supplier to be processed, effectively preventing security risks such as illegal theft and brute-force attacks.

[0017] Secondly, this application provides a management system, which adopts the following technical solution: A management system comprising: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the order management method applicable to the supplier described above.

[0018] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and execute the order management method applicable to the supplier described above.

[0019] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the above-described order management method applicable to suppliers.

[0020] In summary, this application includes at least one of the following beneficial technical effects: Operational instructions generated based on processing operations and pending order information are tailored to the specific processing needs of each order. Simultaneously, by recognizing layout features of the processing interface, the instructions are precisely reflected in preset prompt areas, ensuring the guidance display matches the actual operation area within the processing interface. This avoids suppliers frequently switching their gaze to view the instructions, significantly reducing the processing time for a single order. The precise display of operational instructions lowers the understanding cost for suppliers, reducing ineffective operations caused by misunderstandings. Furthermore, when an operational behavior deviates from the instructions, not only is a real-time pop-up alert triggered, but also deviation correction suggestions are simultaneously provided, offering suppliers a clear direction for operational correction and preventing ineffective operations through repeated self-checking and attempts, further improving the overall efficiency of order processing.

[0021] Real-time growth factors are generated based on the real-time stagnation and correlation values ​​of target pending orders. This links the display size of dynamic pop-up information to the real-time urgency of the order. Suppliers pending orders can intuitively perceive order priority through the pop-up size, quickly determining processing priority without having to view cumbersome data. The alertable interface area is determined based on the supplier's historical operation process, ensuring that the dynamic pop-up is accurately displayed in an area that matches the supplier's operating habits, avoiding operational interference caused by pop-ups appearing in core operation areas. By combining real-time growth factors related to order characteristics, alertable areas that match operating habits, and order reminder icons, dynamic pop-ups are generated and provide accurate feedback. This facilitates personalized and dynamic display of reminder information while ensuring the effectiveness and user-friendliness of the reminders. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating an order management method applicable to suppliers, as described in an embodiment of this application. Figure 2 This is a schematic diagram of an order details interface in an embodiment of this application; Figure 3 This is a schematic diagram of a dynamic pop-up information generation process in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a management system according to an embodiment of this application. Detailed Implementation

[0023] The following is in conjunction with the appendix Figures 1 to 4 This application will be described in further detail.

[0024] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0027] Specifically, this application provides an order management method suitable for suppliers, executed by a management system. This management system can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this.

[0028] refer to Figure 1 , Figure 1 This is a flowchart illustrating an order management method applicable to suppliers, as described in an embodiment of this application. The method includes steps S110-S140, wherein: Step S110: Obtain the order information to be processed and determine the processing operation for the order information to be processed.

[0029] Specifically, pending order information can be uploaded to the management system after the relevant stores place orders through their store-side devices. Relevant suppliers can view this information through their supply-side devices. Both store-side and supply-side devices use the same supply chain software. Pending order information includes the ordering store, requesting employee, order number, order type, order details, and order process details. Order details include product name, unit, quantity, and amount. Processing operations that can be performed on pending order information include, but are not limited to, editing, rejecting, and approving. Figure 2 As shown, the edit operation allows users to edit the order content of the pending order information, the reject operation represents the rejection of the purchase request corresponding to the pending order information, and the operation represents the approval of the purchase request corresponding to the pending order information. The processing operation for pending order information can be determined based on the proactive triggering of relevant suppliers. Alternatively, the management system can intelligently recommend processing operations based on the characteristic attributes of the pending order information and preset operation matching rules, displaying the recommended processing operations as candidate operations on the operation interface of the supplier's equipment for supplier confirmation and selection. The management system can also automatically match the corresponding processing operation for pending order information that meets preset automatic processing conditions by combining data such as the urgency, order type, and historical processing records of the pending orders. After authorization by the relevant supplier, the operation is executed, achieving intelligent determination and efficient matching of processing operations.

[0030] Step S120: Generate operation instructions based on the processing operation and the order information to be processed, and jump from the current interface to the processing interface based on the processing operation.

[0031] Specifically, the management system generates a customized operation guide based on the processing operation selected by the relevant supplier, combined with the order type, order content, and process details of the order information to be processed. This guide includes the execution steps, operational constraints, and key operation node prompts. For example, when the processing operation is "edit," the corresponding operation guide might include limits on product quantity adjustments, rules for adding free gifts, and guidelines for filling in remarks. Simultaneously, the management system triggers an interface jump command based on the selected processing operation, redirecting the current order list or order details preview interface to the customized processing interface matching that operation. Selecting "edit" redirects to the order details - edit interface, while selecting "reject" or "accept" loads the corresponding operation confirmation interaction area on the current order details interface, achieving precise matching and rapid redirection of the processing interface.

[0032] Step S130: Identify the interface layout features of the processing interface, and based on the interface layout features, provide operation guidance to the preset prompt area in the processing interface.

[0033] Specifically, the actual rendering parameters of the current processing interface (such as the screen resolution and interface scaling ratio of the supplier's terminal device) can be read, and then the pre-stored layout template parameters can be calibrated in real time based on the pixel coordinate system (such as calibrating the horizontal coordinate of 100px in the template to the actual pixel value adapted to the resolution when the screen resolution is 1920×1080). Finally, the calibrated interface layout features can be extracted. The interface layout features include, but are not limited to, the actual position of each functional module, the coordinates of the operation field, and the preset prompt area. Preset prompt areas can be pre-defined by relevant staff based on the interface layout characteristics of each processing interface and uploaded to the management system. When providing operation guidance to the preset prompt areas, the prompt areas must meet the principles of "not obscuring core operation controls, fitting the corresponding operation steps, and conforming to conventional visual habits." That is, the operation guidance is broken down into multiple operation steps, and a preset prompt area is assigned to each operation step based on preset matching rules. The preset matching rules can be as follows: when the operation step is adjusting the quantity of goods, the corresponding matching rule is to be adjacent to the operation field and not obscure the input box, for example, a floating prompt area to the right of the quantity input box; when the operation step is filling in remarks, the corresponding matching rule is to fit the operation area and have strong visual continuity, for example, a text prompt area below the remarks input box; when the operation step is selecting the reason for rejection, the corresponding matching rule is to prioritize displaying it above the operation field and conform to reading habits, for example, a text prompt area above the reason for rejection drop-down box; when the operation step is confirming submission, the corresponding matching rule is to not obscure the button and to allow for quick visual focus, for example, an icon prompt area to the right of the confirmation button. The specific content of the preset matching rules is not specifically limited in this application embodiment. They can be set by relevant personnel according to actual needs and uploaded to the management system in advance.

[0034] Step S140: During the processing operation performed by the supplier to be processed, the operation behavior is monitored in real time and matched with the operation guide. When the operation behavior deviates from the operation guide, a real-time pop-up reminder is triggered and feedback on deviation correction suggestions is provided to guide the supplier to process the order information to be processed in compliance with regulations.

[0035] Specifically, by collecting the operational instructions, coordinates, data entry, and execution sequence of operational nodes from the suppliers to be processed within the processing interface, the system can monitor the entire process of processing operations performed by the relevant suppliers. Simultaneously, it retrieves the operational guidelines matching the current processing operation and performs structured parsing to extract verification benchmark information such as operational constraints, operational step specifications, data entry limits, and node execution requirements for each operational step. This establishes an operational guide verification library. The verification benchmark information includes upper and lower limits for product quantity adjustments, character limits for remarks, mandatory requirements for selecting rejection reasons, the execution order of operational steps, and trigger conditions for each function button. Suppliers to be processed are those relevant to whom the pending order information processing operation needs to be performed.

[0036] When any dimension of real-time operation behavior data is detected to be inconsistent with the verification benchmark information in the operation guide verification library, it is determined that the current operation behavior deviates from the operation guide. At this time, a real-time pop-up reminder mechanism will be triggered immediately. The pop-up reminder will pop up precisely next to the current operation area on the processing interface. The pop-up display position follows the principle of not obscuring the current operation controls and being able to quickly capture the visual focus, so as to avoid the pop-up interfering with the supplier's subsequent correction operations. Simultaneously, based on the deviation type of the operation, corresponding precise correction suggestions will be retrieved from the preset deviation correction suggestion library, and these suggestions will be displayed in conjunction with pop-up reminders. The deviation correction suggestion library is pre-set and uploaded to the management system by relevant staff based on operation guidelines for different processing operations and common operation deviation types. Deviation correction suggestions for different deviation types include, but are not limited to: when the detected quantity adjustment value of the goods exceeds the original purchase quantity, the pop-up can display: "The current entered quantity exceeds the purchase limit," and the correction suggestion can be: "Enter the value no greater than XX (original purchase quantity)"; when the detected remark character count exceeds 50 characters, the pop-up can display: "The remark character count exceeds the limit," and the correction suggestion can be: "Reduce it to within 50 characters"; when the detected rejection submission button is triggered without selecting a rejection reason, the pop-up can display: "The rejection reason is required," and the correction suggestion can be: "Select the corresponding rejection reason from the drop-down list before submitting"; when the detected entered goods amount is not a preset value or is negative, the pop-up can display: "The goods amount entered is abnormal," and the correction suggestion can be: "Enter a positive value that matches the goods specifications," etc.

[0037] In this embodiment, the operation guide generated based on the processing operation and the order information to be processed is tailored to the specific order processing needs. Simultaneously, by recognizing the layout features of the processing interface, the guide is accurately fed back to a preset prompt area, ensuring that the guide display matches the actual operation area within the processing interface. This avoids suppliers frequently switching their gaze to view the guide, significantly reducing the processing time for a single order. The precise display of the operation guide reduces the understanding cost for suppliers, minimizing invalid operations caused by misunderstandings. Furthermore, when an operation deviates from the guide, not only is a real-time pop-up reminder triggered, but also a deviation correction suggestion is simultaneously fed back, providing suppliers with a clear direction for operational correction and avoiding invalid operations resulting from suppliers' self-verification and repeated attempts, further improving the overall efficiency of order processing.

[0038] Furthermore, when the number of pending order information exceeds a preset processing threshold, the method provided in this application embodiment further includes: Identify the order initiation time in each pending order information, and sort all pending order information according to the chronological order of each order initiation time to generate a pending order list; generate a pending quantity prompt icon based on the pending quantity of all pending order information; collapse the pending list and generate a collapsed list entry control, and overlay the collapsed list entry control and pending quantity prompt icon onto the order management function box; when a pending supplier triggers the collapsed list entry, expand the pending order list.

[0039] Specifically, the preset processing threshold can be three or four. The specific values ​​are not limited in this embodiment and can be set in advance by relevant personnel according to actual needs. When the number of pending order information exceeds the preset processing threshold, it indicates that there may be an accumulation of multiple pending order information on the order management interface. In order to maintain the cleanliness of the order management interface, the multiple pending order information can be collapsed. The specific folding process is as follows: Based on a preset feature recognition algorithm, the system can identify the corresponding order initiation time from each pending order information. Specifically, this is the timestamp when the store-side device submits the pending order information in the supply chain software and uploads it to the management system. The management system sorts all pending order information according to the order initiation time, using a first-initiated-first-sort rule (ascending order). The system then reads the sorted pending order list and counts the total number of pending orders to obtain the pending quantity. A corresponding pending quantity indicator is generated to remind suppliers of specific tasks. The pending data indicator is typically red. When multiple pending orders are included, a red dot with a number will be displayed in the order management function box. The red dot disappears once all pending orders have been processed.

[0040] The management system can invoke preset list folding rules to structurally fold the sorted list of orders to be processed. The preset list folding rules include: Folding logic: Only retain the basic index information of the orders to be processed, such as the order number and sorting number, hide the order details fields, and generate a lightweight folded list of data; Storage rules: The collapsed list data is temporarily stored in the front-end cache to avoid frequent calls to the back-end database and improve the response speed of subsequent expansion operations; Exception handling: If the number of pending orders is too large (e.g., N>100), the collapsible list will be automatically split into two sub-collapsible lists: "Initiated in the last 24 hours" and "Initiated 24 hours ago", for easier subsequent hierarchical display.

[0041] Based on the collapsed list data, a standardized collapsed list entry control is generated. It can be a button-type entry with the text "List of Orders to be Processed" and a collapsed / expanded status icon on the right. The collapsed list entry can cover the entire order management function box, that is, the list of orders to be processed can be expanded no matter where the supplier triggers the order management function box.

[0042] Based on the excess pending order data, a pending quantity indicator is generated. The collapsible list entry control and this indicator are overlaid on the order management function box to achieve a compact display of excess order information. This avoids the redundancy of interface information caused by the pending order list occupying a large area of ​​the operation interface. Moreover, the order list is only expanded when the pending supplier triggers the collapsible list entry control. This ensures the complete presentation of excess order information and avoids the interference of a static expanded list on the daily operation interface, reducing the distraction caused by interface information interference.

[0043] Furthermore, to prevent high-priority orders from being overlooked and to ensure the timeliness of processing important orders, the method provided in this application embodiment also includes: Based on the order initiation time in each pending order information, determine the order dwell time for each pending order information, and determine the corresponding order stagnation value for each pending order information based on the order dwell time; identify the number of pending review nodes in each pending order information from the process details in each pending order information, and determine the historical review efficiency of each pending review node based on historical review information, and determine the corresponding order review value for each pending order information based on the historical review efficiency of each pending review node; identify the order identifier in each pending order information, and identify the associated data of each pending order information from the pending order list based on each order identifier, and determine the order association value for each pending order information based on each associated data, including the number of associated orders and the associated initiation time of each associated order information, and the order identifier of the pending order information is related to the associated order identifier of the corresponding associated order information; determine the order processing level for each pending order information based on the order stagnation value, order review value, and order association value; identify pending order information with an order processing level higher than the preset processing level as target pending order information, and generate dynamic pop-up information based on the current operation interface information and the target pending order information.

[0044] Specifically, the order dwell time of pending order information refers to the time difference between the order initiation time and the current statistical time. It is used to reflect the idle time of pending order information that has not been processed. It can be calculated based on the time difference between the current statistical time and the order initiation time of each pending order information. Then, the order stagnation value corresponding to each pending order information is determined based on the preset order stagnation value mapping relationship. The preset order stagnation value mapping relationship is the correspondence between order dwell time and order stagnation value. The longer the dwell time, the higher the corresponding order stagnation value. The specific content of the preset order stagnation value mapping relationship is not specifically limited in this application embodiment.

[0045] The pending order information contains multiple review nodes in its process details. The number of nodes to be reviewed is the total number of nodes that need to be reviewed for the pending order information, extracted from the order process details. This includes nodes such as price review, inventory review, and shipping review. Historical review information includes the average processing time of each pending node within a historical time period, i.e., historical review efficiency, which can be extracted from historical review information based on a preset feature recognition algorithm. The order review value corresponding to the pending order information is a value generated by quantifying the number of pending nodes and the historical review efficiency of each node. This can be quantified and normalized to obtain the order review value for each pending order information. The specific quantification and normalization method is not specifically limited in this embodiment; the more pending nodes and the lower the historical review efficiency of each node, the higher the corresponding order review value.

[0046] The order identifier in the pending order information can serve as a unique identification code for the pending order. By traversing the pending order list based on the order identifier, associated data can be identified. This associated data includes related order information that is linked to the pending order information, as well as the associated initiation time of each related order. The identifier matching degree between the order identifier of the pending order information and the corresponding associated order identifier is higher than a preset identifier matching degree threshold. The specific preset identifier matching degree threshold is not limited in this embodiment. When determining the order association value of the pending order information, it is necessary to first analyze the initiation interval between each associated initiation time and the order initiation time of the pending order information. Then, the number of associated orders and the initiation interval between each associated order information and the pending order information are quantified and normalized to obtain the order association value. A higher number of associated orders and a smaller initiation interval correspond to a higher order association value.

[0047] Based on the above method, the order stagnation value, order review value, and order association value of each pending order can be obtained. By quantifying these values, a processing score can be obtained for each pending order. Then, based on a preset processing level mapping relationship, the order processing level of each pending order is determined. This preset mapping relationship corresponds to the processing score and the order processing level; a higher processing score corresponds to a higher order processing level. Specific details are not limited in this embodiment. When the order processing level of any pending order is higher than the preset processing level, a dynamic pop-up window generation mechanism can be triggered to generate a dynamic pop-up message for that pending order, reminding the supplier to promptly identify and process the pending order to ensure the timeliness of processing important or urgent orders.

[0048] Furthermore, to ensure the effectiveness and user-friendliness of the reminder, the method provided in this application embodiment generates dynamic pop-up information based on the current operation interface information and the target pending order information, specifically including steps S310-S330, such as... Figure 3 As shown, where: Step S310: Obtain the real-time order stagnation value and real-time order association value of the target pending order information, and generate a real-time growth factor based on the real-time order stagnation value and real-time order association value.

[0049] Specifically, the real-time growth factor of the target order information to be processed can be determined based on a preset growth factor mapping relationship. The preset growth factor mapping relationship is the correspondence between the parameter combination of the real-time order stagnation value and the real-time order association value and the real-time growth factor. The larger the real-time order stagnation value and the real-time order association value, the larger the corresponding real-time growth factor. The specific content of the preset growth factor mapping relationship is not specifically limited in this embodiment. Since the order stagnation value and the order association value change in real time, the generated growth factor also changes in real time.

[0050] Step S320: Obtain the historical operation process of the supplier to be processed within the historical analysis period, and determine the area of ​​the interface that can be reminded from the current operation interface information based on the historical operation process.

[0051] Specifically, the historical analysis period is a time preceding the current moment. The analysis duration for this period can be three minutes or five minutes, and the specific duration is not limited in this embodiment. The historical operation flow refers to the triggering behaviors of the supplier to be processed on the supply software during the historical analysis period. By analyzing the historical operation flow, the alertable interface areas where the supplier to be processed did not generate any triggering behaviors during the historical analysis period can be determined from the current operation interface information. Furthermore, to minimize the impact on the normal operation of the supplier to be processed, when determining the alertable interface areas from the current operation interface information based on the historical operation flow, the specific steps can be as follows: Identify the operation information identifier in the current operation interface and determine the operation level based on the operation information identifier; when the operation level is higher than the preset operation level threshold, determine the predicted operation trajectory of the supplier to be processed based on the historical operation process; determine the interface area that can be alerted from the current operation interface information based on the real-time growth factor and the predicted operation trajectory.

[0052] Specifically, operation information identifiers can be identified from the current operation interface information based on a preset feature recognition algorithm. The operation information identifiers are used to characterize the actual operation behavior type of the supplier to be processed in the current operation interface information. For example, the operation of modifying the purchase quantity in the order details-edit interface, the operation of modifying the amount in the order details-edit interface, the operation of selecting the rejection reason in the order details interface, the operation of filtering and viewing orders in the order list interface, and the operation of clicking the order management function box on the homepage. Different operation information identifiers correspond to different operation levels, which can be determined according to preset operation level allocation rules. The preset operation level allocation rules are the correspondence between different operation information identifiers and their corresponding operation levels. The specific content is not specifically limited in this application embodiment and can be set in advance by relevant personnel according to actual needs.

[0053] After determining the operation level, it can be compared with a preset operation level threshold. When the operation level is higher than the preset threshold, it indicates that the supplier to be processed has a higher requirement for the smoothness of the operation process at the current moment. That is, at the current moment, it is necessary to minimize the interference of external pop-up reminders on the core operation being performed to ensure the continuity and accuracy of order processing. Therefore, it is necessary to analyze historical operation processes to determine the predicted operation trajectory of the supplier to be processed in the future, and avoid this predicted operation trajectory when determining the area of ​​the interface that can be reminded, not just the area that has not been triggered in the past. Specifically, when determining the predicted operation trajectory of the supplier to be processed based on historical operation processes, it can be as follows: Based on a preset feature recognition algorithm and by organizing historical operation processes according to preset data dimensions, an operation dataset is obtained. The preset data dimensions include the operation interface type dimension (e.g., order details - edit interface, order list interface, homepage), operation behavior type dimension (e.g., quantity modification, amount modification, rejection reason selection), operation space coordinate dimension (e.g., (250,180), (320,260)), continuous operation sequence dimension (e.g., quantity modification - remarks filling - submit button click), operation dwell time dimension, and operation transition probability dimension (e.g., after quantity modification, there is an 85% probability of performing remarks filling). The system is grouped according to both the user interface type and the user action type. High-frequency sequences and transition probabilities are extracted. High-frequency sequences are the order of operations with a frequency greater than or equal to a preset percentage (e.g., modifying purchase quantity - filling in remarks - submitting). Transition probabilities are the percentage of times operation B is executed after operation A (e.g., filling in remarks occurs 85% of the time after modifying purchase quantity). Based on the extracted high-frequency sequences and transition probabilities, a preset operation trajectory model is trained to predict the processing operations that the supplier might perform in the next three or five minutes. The trigger positions of these predicted processing operations within the current user interface are then identified, and predicted operation trajectories are generated based on each trigger position. Since the real-time generation factor is related to the size of the dynamic pop-up information, the alertable interface area needs to be determined from the current user interface information by combining the real-time growth factor and the predicted operation trajectory.

[0054] First, the overall coverage area of ​​the predicted operation trajectory can be identified in the current operation interface. Then, other areas in the current operation interface besides the overall coverage area are identified as candidate alert areas. Next, the shrinkage value is determined based on the trajectory complexity of the predicted operation trajectory and the real-time growth factor. The trajectory complexity can be determined by calculating the path curvature of the predicted operation trajectory; higher trajectory complexity corresponds to a higher shrinkage value. Finally, based on the shrinkage value, the edge of the candidate alert area is shrunk inwards to prevent the pop-up edge from obscuring the predicted operation trajectory. The shrinkage value corresponding to the trajectory complexity and the real-time growth factor can be determined according to a preset shrinkage mapping relationship. This preset shrinkage mapping relationship is the correspondence between the parameter combination of trajectory complexity and the real-time growth factor and the shrinkage value. Specific details are not limited in this embodiment.

[0055] Based on historical operation processes, the operation trajectory of suppliers to be processed is further predicted, which makes it easier to avoid core operation areas and key operation paths in advance. This avoids the obstruction and interference of reminder pop-ups on high-level and high-importance operations of suppliers to be processed. By combining real-time growth factors and predicted operation trajectories to determine the area of ​​the interface that can be reminded, the reminder location and operation behavior are intelligently adapted. This ensures that reminders for high-priority orders can be effectively delivered, while minimizing the impact on the normal operation of suppliers to be processed.

[0056] Step S330: Generate an order reminder icon based on the order information to be processed, generate dynamic pop-up information based on the real-time growth factor and the order reminder icon, and feed the dynamic pop-up information back to the reminder interface area. The display size of the real-time growth factor and the dynamic pop-up information are related.

[0057] Specifically, a preset feature recognition algorithm can be used to identify core order fields from the order information to be processed, and an order reminder identifier can be generated based on these core fields. These core fields can include the order number, the store of the order, and the reason for the order priority (e.g., the order dwell time exceeds 8 hours). The specific core fields are not specifically limited in this embodiment. Then, a preset real-time growth factor-popup specification mapping rule is used to determine the corresponding popup specification. This rule specifies the display size, color scheme, font style, and display duration for different real-time growth factor values. The specific details are not specifically limited in this embodiment and can be set in advance according to actual needs. The structured information of the order reminder identifier is then filled into the visual template corresponding to the matched popup specification to ensure that the layout of the displayed content is adapted.

[0058] In this embodiment of the application, a real-time growth factor is generated based on the real-time stagnation value and correlation value of the target pending order. This links the display size of the dynamic pop-up information to the real-time urgency of the order. The pending supplier can intuitively perceive the order priority through the pop-up size and quickly determine the processing priority without having to look at cumbersome data. The alertable interface area is determined based on the pending supplier's historical operation process, so that the dynamic pop-up is accurately displayed in the area that matches the pending supplier's operating habits, avoiding operation interference caused by the pop-up appearing in the core operation area. The real-time growth factor associated with the order characteristics, the alertable area that matches the operating habits, and the order reminder icon are combined to generate a dynamic pop-up and provide accurate feedback. This facilitates the personalized and dynamic display of reminder information while ensuring the effectiveness and user-friendliness of the reminder.

[0059] Furthermore, to prevent security risks such as unauthorized use and brute-force attacks, the method provided in this application embodiment also includes: The system identifies the full-process operation data corresponding to the pending order information. This data includes the node editing time, node viewing count, and historical error rate for each review node. Based on the weighting of each dimension in the full-process operation data, the system determines the password security level for the pending supplier. When a pending supplier logs in from a different location, the system matches the corresponding password generation rule based on the password security level. The system identifies the target review node based on the node editing time, node viewing count, and historical error rate for each review node, and determines the target operation performance data for that node from the full-process operation data. Based on the password generation rule and the target operation performance data, a unique verification password is generated and pushed to the pending supplier's terminal to complete the login verification.

[0060] Specifically, the historical operation records corresponding to the order information to be processed can be analyzed to identify the full-process operation data corresponding to the order information to be processed. The full-process operation data includes the node editing time, node viewing number, and node historical error rate of each review node during the flow of the order information to be processed. The node editing time is used to characterize the time spent by the supplier to perform editing, modification, and data entry operations at the corresponding review node. The node viewing number is used to characterize the frequency of the supplier to view and verify each review node. The node historical error rate is used to characterize the probability of the supplier to encounter data entry errors, process misoperation, submission anomalies, etc. when performing operations at the corresponding review node. Next, a weighted calculation can be performed based on the preset weight ratios of each dimension of the data in the entire process operation data to determine the password security level of the supplier to be processed. Among them, the node editing time, the number of times the node is viewed, and the historical error rate of the node can all be configured with corresponding weight coefficients. The weight ratios can be set in advance according to actual security needs and supplier operation risk levels. The password security level is used to characterize the degree of account security risk and verification strength requirements of the supplier to be processed. The specific weight configuration method and password security level division rules are not specifically limited in this application embodiment, and can be set by relevant personnel according to actual security strategies.

[0061] When the system detects that a supplier is performing a login operation from a different location, it matches the corresponding password generation rule from a preset password security level-password generation rule mapping library based on the determined password security level. The password generation rule is used to limit the length, character combination type, arrangement, and dynamic change logic of the verification password. Different password security levels correspond to different levels of password generation rule complexity; the higher the password security level, the higher the complexity of the matched password generation rule. The specific mapping relationship and details of the password generation rule are not specifically limited in this embodiment. Simultaneously, a comprehensive score is calculated based on the node editing time, node viewing count, and historical error rate of each review node. The review node with the highest comprehensive score is selected as the target review node from all review nodes. Furthermore, the frequency of operational errors, the number of repeated operations, the difference between the operation completion time and the baseline time, and the frequency of key information modifications corresponding to the target review node are extracted from the full-process operation data as target operation performance data. Finally, based on the matched password generation rules and the target operation performance data corresponding to the target audit node, character combination, sequence mapping and encryption calculation are performed to generate a unique verification password that is only applicable to the current supplier to be processed. The unique verification password is then pushed to the supplier's pre-bound supply-side device. After the supplier enters the unique verification password and passes the verification, the identity verification process for remote login is completed.

[0062] When a login from a different location is detected, the system adaptively matches the corresponding password generation rules based on the password security level and generates a unique verification password by combining the target operation performance data of the target audit node. This deeply binds the verification password to the actual operation behavior of the supplier to be processed, effectively preventing security risks such as unauthorized theft and brute-force attacks.

[0063] This application provides a management system, such as... Figure 4 As shown, Figure 4 The management system 400 shown includes a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, for example, via a bus 402. Optionally, the management system 400 may also include a transceiver 404. It should be noted that in practical applications, the transceiver 404 is not limited to one type, and the structure of this management system 400 does not constitute a limitation on the embodiments of this application.

[0064] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0065] Bus 402 may include a pathway for transmitting information between the aforementioned components. Bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 402 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0066] The memory 403 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0067] The memory 403 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the content shown in the foregoing method embodiments.

[0068] The management system includes, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Tablet PCs), PMPs (Portable Multimedia Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. It can also include servers. Figure 4 The management system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0069] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0070] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0071] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0072] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. An order management method suitable for suppliers, characterized in that, include: Obtain the order information to be processed and determine the processing operation for the order information to be processed; Based on the processing operation and the order information to be processed, an operation guide is generated, and the user is redirected from the current interface to the processing interface based on the processing operation. Identify the interface layout features of the processing interface, and based on the interface layout features, feed back the operation guidance to the preset prompt area in the processing interface; During the processing of the pending supplier, the operation behavior is detected in real time and matched with the operation guide. When the operation behavior deviates from the operation guide, a real-time pop-up reminder is triggered and a deviation correction suggestion is provided to guide the pending supplier to process the pending order information in compliance with regulations.

2. The order management method applicable to suppliers according to claim 1, characterized in that, When the number of pending orders exceeds a preset processing threshold, the process further includes: Identify the order initiation time in each pending order information, and sort all pending order information according to the chronological order of each order initiation time to generate a pending order list; Generate a pending quantity indicator based on the pending quantity of all pending orders; The pending list is folded to generate a folded list entry control. The folded list entry control and the pending quantity indicator are overlaid on the order management function box. When the pending supplier triggers the folded list entry, the pending order list is expanded.

3. The order management method applicable to suppliers according to claim 2, characterized in that, Also includes: Based on the order initiation time in each pending order information, determine the order dwell time for each pending order information, and determine the order stagnation value corresponding to each pending order information based on the order dwell time; Identify the number of pending review nodes in each pending order information from the process details in each pending order information, determine the historical review efficiency of each pending review node based on historical review information, and determine the order review value corresponding to each pending order information based on the historical review efficiency of each pending review node. Identify the order identifier in each pending order information, and identify the associated data of each pending order information from the pending order list based on each order identifier. Determine the order association value of each pending order information based on each associated data. The associated data includes the number of associated orders of the associated order information and the association initiation time of each associated order information. The order identifier of the pending order information is related to the associated order identifier of the corresponding associated order information. Based on the order stagnation value, the order review value, and the order association value of each pending order information, the order processing level of each pending order information is determined; Orders with a processing level higher than the preset processing level are identified as target orders to be processed, and dynamic pop-up information is generated based on the current operation interface information and the target orders to be processed.

4. The order management method for suppliers according to claim 3, characterized in that, The generation of dynamic pop-up information based on the current user interface information and the target pending order information includes: Obtain the real-time order stagnation value and real-time order association value of the target pending order information, and generate a real-time growth factor based on the real-time order stagnation value and the real-time order association value; Obtain the historical operation process of the supplier to be processed within the historical analysis period, and determine the reminder interface area from the current operation interface information based on the historical operation process; An order reminder identifier is generated based on the order information to be processed. A dynamic pop-up message is generated based on the real-time growth factor and the order reminder identifier. The dynamic pop-up message is then fed back to the reminder interface area. The real-time growth factor is related to the display size of the dynamic pop-up message.

5. The order management method for suppliers according to claim 4, characterized in that, The step of determining the area of ​​the interface that can be alerted from the current operation interface information based on the historical operation process includes: Identify the operation information identifier of the current operation interface information, and determine the operation level based on the operation information identifier; When the operation level is higher than the preset operation level threshold, the predicted operation trajectory of the supplier to be processed is determined based on the historical operation process. Based on the real-time growth factor and the predicted operation trajectory, the area of ​​the interface that can be alerted is determined from the current operation interface information.

6. The order management method applicable to suppliers according to claim 1, characterized in that, Also includes: Identify the full-process operation data corresponding to the order information to be processed, including the node editing time, node viewing count, and historical error rate of each review node corresponding to the order information to be processed; Based on the weight ratio of each dimension of data in the entire process operation data, the password security level corresponding to the supplier to be processed is determined. When a remote login from the supplier to be processed is detected, the corresponding password generation rule is matched based on the password security level; The target review node is determined based on the node editing time, node viewing count, and historical error rate of each review node, and the target operation performance data corresponding to the target review node is determined from the full-process operation data. Based on the password generation rules and the target operation performance data, a unique verification password is generated and pushed to the terminal of the supplier to be processed to complete the login verification.

7. A management system, characterized in that, The management system includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform an order management method suitable for a supplier according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, include: The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-6, which is suitable for a supplier's order management method.

9. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the steps of an order management method suitable for a supplier as described in any one of claims 1-6.

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