Management method and device based on product flow direction, equipment, medium and product

Abstract

The invention provides a product flow direction-based management method and device, equipment, a medium and a product, and relates to the technical field of product management, and the method comprises the steps: carrying out the abnormality monitoring of the flow direction of a product according to the currently obtained code scanning information and / or inventory information, and a pre-configured abnormal flow direction judgment rule in a product flow process, and obtaining the abnormal flow direction of the product; obtaining an abnormal type of the product flow direction; according to an early warning rule, abnormal data corresponding to an abnormal type indicated by the early warning rule is extracted from storage data of a product whose flow direction is monitored to be abnormal, and according to the abnormal data, at least one of the following items is executed: early warning information is pushed to an early warning receiver, and the abnormal data is corrected based on an additional recording document fed back by the early warning receiver; wherein the additional recording document is related to the early warning information; and performing exception management and control on the dealers related to the exception data. Therefore, integration and deep analysis can be carried out on the product flow direction data, and compliance management of products is realized.

Description

Technical Field

[0001] The present application relates to the technical field of product management, and in particular to a management method, device, equipment, medium and product based on product flow. Background Art

[0002] Currently, many companies in the food industry are leveraging information technology to manage product flows. These systems, such as Enterprise Resource Planning (ERP), Warehouse Management Systems (WMS), Dealer Management Systems (DMS), and Point of Sales (POS), enable the initial digital recording of product information across procurement, warehousing, and sales processes. For example, much of this product flow management is enabled by traceability technology. Many food companies have established product traceability systems based on technologies such as QR codes and blockchain, in accordance with relevant standards and regulations. By scanning the QR code on product packaging, consumers can access basic product information, including production batches and test reports, enabling one-way traceability of product information from production to sales. However, most of these systems focus solely on simple data recording and querying, lacking in data integration and in-depth analysis, and thus fail to fully tap into the value of data for compliant product flow management. Summary of the Invention

[0003] The embodiments of the present application provide a management method, device, equipment, medium and product based on product flow, which solves the problem that the current management based on product flow only stays at the data recording and query level and cannot fully tap the value of data to achieve compliance management of product flow.

[0004] In a first aspect, to achieve the above-mentioned objectives, embodiments of the present application provide a product flow-based management method, comprising: During the product flow process, based on the currently acquired scan code information and / or inventory information and the pre-configured abnormal flow direction judgment rules, the product flow direction is monitored for abnormalities and the abnormal type of the product flow direction is obtained; According to the early warning rule, in the stored data of the product with abnormal flow direction, extract the abnormal data corresponding to the abnormal type indicated by the early warning rule, and perform at least one of the following according to the abnormal data: Pushing the warning information to the warning recipient, and correcting the abnormal data based on the supplementary recording document fed back by the warning recipient; wherein the supplementary recording document is related to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

[0005] The scanning information includes at least one of the scanning subject, scanning time, and scanning location, and also includes product information obtained by scanning; the abnormality type includes supply relationship abnormality and / or freshness abnormality; Based on the currently acquired scanned code information and pre-configured abnormal flow direction determination rules, the product flow direction is monitored for abnormalities and the abnormal type of the product flow direction is obtained, including at least one of the following: Comparing the code scanning subject with the target distributor in the product information to obtain a first comparison result, comparing the code scanning location with the sales area in the product information to obtain a second comparison result, and comparing the product type in the product information with the product types that the code scanning subject is allowed to sell to obtain a third comparison result, and if at least one of the first comparison result, the second comparison result, and the third comparison result satisfies the product supply relationship abnormality rule in the abnormal flow direction determination rule, determining that the abnormality type is a supply relationship abnormality; wherein the target distributor is a distributor that is allowed to sell the product corresponding to the product information; The first freshness of the product is determined based on a first time interval between the scanning time and the production date in the product information, and when the first freshness is lower than the freshness threshold in the abnormal flow direction determination rule, the abnormality type is determined to be a freshness abnormality.

[0006] Among them, the abnormal product supply relationship rules include at least one of the following: the scanning entity does not belong to the target dealer, the scanning location does not belong to the sales area of the target dealer, and the product type does not fall within the sales scope of the scanning entity.

[0007] The inventory information includes product type, product quantity, and product sales area; the abnormality type includes at least one of abnormal supply relationship, abnormal freshness, and abnormal inventory turnover days; Based on the currently acquired inventory information and pre-configured abnormal flow determination rules, the product flow is monitored for abnormalities and the abnormal type of product flow is obtained, including at least one of the following: Comparing the product type with the products that the dealer corresponding to the inventory information is allowed to sell, if the product type does not belong to the products that the dealer corresponding to the inventory information is allowed to sell, determining the abnormality type as a supply relationship abnormality according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; Comparing the product sales area corresponding to the product type with the location of the warehouse corresponding to the inventory information, if the product sales area does not include the location of the warehouse, determining the row type of the product as having an abnormal supply relationship according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; determining a second freshness of the product based on a second time interval between the acquisition date of the inventory information and the production date of the product, and determining that the abnormality type is a freshness abnormality when the second freshness is lower than a freshness threshold in the abnormal flow direction determination rule; The available days of the product in the inventory are determined based on the product quantity and the average monthly sales quantity of the product, and when the available days are outside the first turnover range in the abnormal flow determination rule, the abnormality type is determined to be a turnover days abnormality.

[0008] The warning rules include one or more of the following: warning period, warning push time, warning receiver, and abnormality type; According to the early warning rules, in the stored data of the product with abnormal flow direction, the abnormal data corresponding to the abnormal type indicated by the early warning rules is extracted, including: Determine the time period corresponding to the current warning cycle based on the warning cycle and the warning push time; The abnormal data is obtained from the stored data according to the abnormality type and the time period.

[0009] According to the abnormal data, the warning information is pushed to the warning recipient, and the abnormal data is corrected based on the supplementary document fed back by the warning recipient, including: Generate an abnormality detail table based on the abnormal data; At the warning push moment in the warning rule, sending the warning information to the warning recipient, wherein the warning information includes the abnormality details list; Receive the supplementary document feedback from the warning recipient; The abnormal flow document is supplemented according to the supplementary document, and the abnormal data is corrected based on the supplementary result.

[0010] Among them, the abnormal details table includes: one or more items of the inventory turnover days abnormal table, the freshness abnormal table and the supply relationship abnormal table; the supply relationship abnormal table includes one or more items of the inventory flow abnormal table, the inventory advance scan code table, the audit visit table, the off-site points table, the in and out warehouse table and the store inventory collection table.

[0011] Among them, the abnormal details table includes at least one of the following fields: abnormal flow operation dealer field, abnormal operation warehouse field, abnormal flow product field, abnormal flow product quantity field, abnormal flow product freshness field, abnormal flow product to which dealer field, abnormal flow product to which warehouse field.

[0012] According to the abnormal data, abnormal management and control is performed on the dealers related to the abnormal data, including: According to the abnormal data, the number of abnormally directed distributors, abnormally directed warehouses, and abnormally directed stores corresponding to the abnormal data is obtained; Determine the target warning dimension based on the mapping relationship between the quantity of the abnormally flowing products and the pre-configured quantity range and the warning dimension; According to the target warning dimension, the dealer is managed and controlled, wherein the management and control of the dealer includes product order control and / or dealer payment collection control.

[0013] The method further comprises: Obtaining real-time distribution data of the product in warehouses at all levels based on the scanned code information; obtaining product expiration dates based on the scanned code information and / or the inventory information; and obtaining warehouse turnover efficiency based on the inventory information; Calculate product turnover efficiency based on the warehouse turnover efficiency; A product supply scheduling plan is predicted based on the real-time distribution data, the product expiration date, the product turnover efficiency and the product production efficiency.

[0014] In a second aspect, to achieve the above-mentioned objectives, embodiments of the present application provide a product flow-based management device, comprising: The monitoring module is used to monitor the flow of products during their flow, based on the currently acquired scanned code information and / or inventory information, and pre-configured abnormal flow direction determination rules, to determine the abnormal type of product flow. A processing module is configured to extract, from the stored data of products detected to have abnormal flow according to the early warning rule, abnormal data corresponding to the abnormal type indicated by the early warning rule, and perform at least one of the following based on the abnormal data: Pushing the warning information to the warning recipient, and correcting the abnormal data based on the supplementary recording document fed back by the warning recipient; wherein the supplementary recording document is related to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

[0015] In the third aspect, in order to achieve the above-mentioned purpose, an embodiment of the present application provides a management device based on product flow, including a transceiver, a processor, a memory, and a program stored on the memory and runnable on the processor; the transceiver is used to send and receive data under the control of the processor, and when the processor executes the program, it implements the management method based on product flow as described in the first aspect.

[0016] In a fourth aspect, in order to achieve the above-mentioned purpose, an embodiment of the present application provides a readable storage medium on which a program or instruction is stored, and when the program or instruction is executed by a processor, the product flow-based management method as described in the first aspect is implemented.

[0017] In a fifth aspect, in order to achieve the above-mentioned purpose, an embodiment of the present application provides a computer program product, including computer instructions, which, when executed by a processor, implement the product flow-based management method as described in the first aspect.

[0018] The beneficial effects of the above technical solution of this application are as follows: In an embodiment of the present application, first, during the flow of products, based on the currently acquired scan code information and / or inventory information, and the pre-configured abnormal flow direction determination rules, the flow direction of the products is monitored for abnormalities, and the abnormal type of the product flow direction is obtained; secondly, based on the early warning rules, in the stored data of the products whose flow direction is abnormal, the abnormal data corresponding to the abnormal type indicated by the early warning rules is extracted, and based on the abnormal data, at least one of the following is performed: push the early warning information to the early warning recipient, and correct the abnormal data based on the supplementary document fed back by the early warning recipient; wherein the supplementary document is related to the early warning information; and perform abnormal management on the distributors related to the abnormal data. In this way, it is achieved that by fully analyzing and mining the data recorded during the product flow process, the abnormal situations existing in the product flow process can be obtained, and the corresponding distributors can be further managed to make up for the shortcomings of the current system in data integration and in-depth analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a product flow management method according to an embodiment of the present application; Figure 2 Schematic diagram of a product flow management device according to an embodiment of the present application; Figure 3 This is a schematic diagram of a product flow management device according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the technical problems, technical solutions and advantages to be solved by this application clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0021] It should be understood that references throughout this specification to "one embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic associated with the embodiment is included in at least one embodiment of the present application. Therefore, the appearances of "in one embodiment" or "in an embodiment" throughout this specification do not necessarily refer to the same embodiment. Furthermore, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0022] In the various embodiments of the present application, it should be understood that the size of the serial numbers of the following processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0023] Additionally, the terms "system" and "network" are often used interchangeably herein.

[0024] In the embodiments provided herein, it should be understood that "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information.

[0025] The embodiment of the present application provides a management method based on product flow, such as Figure 1 As shown, the method includes: Step 101: During product flow, based on currently acquired scanned code information and / or inventory information and pre-configured abnormal flow direction determination rules, monitor the product flow direction for abnormalities and determine the type of abnormal product flow direction. For example, the scanned code information may include information corresponding to the scan action in at least one of the following scenarios: outbound delivery, inbound delivery, inventory count, consumer scanning, and store scanning.

[0026] In step 101 above, firstly, the product flow process can refer to the entire product lifecycle, including, for example, factory warehousing, brand delivery, supplier warehousing and delivery, store warehousing and delivery, and consumer purchase. Secondly, during product delivery, the warehouse owner scans the product to record the product's flow through the scanning action and results. Thirdly, the warehouse management system also periodically (e.g., daily at dawn) conducts inventory of the products in the warehouse (e.g., by counting incoming and outgoing inventory data) to obtain inventory information. Fourth, the abnormal flow determination rules include, for example, one or more of the product supply relationship abnormality determination rules, freshness abnormality (or product expiration date abnormality) determination rules, and inventory turnover days abnormality (or product inventory turnover abnormality) determination rules. Among them, the product supply relationship abnormality refers to the inconsistency between the compliant supplier of the operating entity of the corresponding product and the distributor of the actual distributor of the product. Judging from the information, there are mainly several situations: (1) The operating entity does not have the sales authority for the corresponding product series, but has a scan record of the products in this product series (in simple terms, the operating entity scanned the product that it does not have the right to sell); (2) The operating entity has the sales authority for the product series, but the supplier with the sales authority for the product is inconsistent with the actual product distributor (in simple terms, the operating entity scanned the product that it has the right to sell). products for sale, but the sales area of the scanned products does not include the area where the operating entity is located); In addition, in the process of product circulation in the food industry, there are strict management rules for the circulation of product validity periods. Generally, near-expiry products and expired products cannot be sold on the market. Based on this, the embodiment of the present application proposes a rule for determining freshness anomalies, specifically: configuring the number of days from the production date of different products to today (the collection date, such as the warehouse entry and exit scanning date or the inventory count date), and setting the product freshness corresponding to different days. For example, the freshness is negatively correlated with the number of days from the production date to today. When the freshness is lower than the configured freshness threshold, the product freshness is determined to be abnormal; in addition, the inventory turnover days refers to the number of channel distributors in the warehouse, corresponding to the average monthly sales volume of the product, and the number of days available for the in-warehouse inventory of the products in the warehouse. According to the pre-configured rules for the turnover days of different products, the dimension of the number of days of abnormal turnover is defined. For example: slow turnover, high turnover, etc. In other words, the rule for determining abnormal inventory turnover days is to determine the turnover days of products in stock based on the product's inventory quantity and the average monthly sales volume of the product. It then determines whether the calculated turnover days are abnormal based on the pre-set normal turnover days range. For example, if the calculated turnover days are outside the normal turnover days range, the product's inventory turnover days are considered abnormal. Furthermore, corresponding to the abnormal flow direction determination rules, abnormality types include abnormal supply relationships, abnormal freshness, and abnormal inventory turnover days.

[0027] Step 102: Extract abnormal data corresponding to the abnormal type indicated by the early warning rule from the stored data of the product with abnormal flow according to the early warning rule, and perform at least one of the following according to the abnormal data: Pushing the warning information to the warning recipient, and correcting the abnormal data based on the supplementary recording document fed back by the warning recipient; wherein the supplementary recording document is related to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

[0028] In step 102 above, firstly, the early warning rules are pre-configured automatic early warning rules based on the actual needs of different business scenarios. For example, in market management and channel management scenarios, they primarily assess product flow and supply relationships; in inventory management scenarios, they primarily assess product freshness and inventory turnover efficiency. Specifically, the configurable parameters for the early warning rules include: data collection cycle (daily / weekly / monthly / custom), automatic push time, data recipient, and abnormal data collection dimensions (the dimensions of abnormal data required for each abnormal rule). Secondly, by pushing early warning information to the early warning recipient and correcting the abnormal data based on the supplementary documents provided by the early warning recipient in response to the early warning information, this automatically identifies data errors and their causes during the manual process of flow data collection, ensuring that the overall flow data is rigorous and accurate, facilitating subsequent product management through in-depth data mining. Thirdly, by implementing abnormality management on distributors associated with the abnormal data, the standardized flow of products can be ensured.

[0029] In an embodiment of the present application, first, during the flow of products, based on the currently acquired scan code information and / or inventory information, and the pre-configured abnormal flow direction determination rules, the flow direction of the products is monitored for abnormalities, and the abnormal type of the product flow direction is obtained; secondly, based on the early warning rules, in the stored data of the products whose flow direction is abnormal, the abnormal data corresponding to the abnormal type indicated by the early warning rules is extracted, and based on the abnormal data, at least one of the following is performed: push the early warning information to the early warning recipient, and correct the abnormal data based on the supplementary document fed back by the early warning recipient; wherein the supplementary document is related to the early warning information; perform abnormal management on the distributors related to the abnormal data. In this way, it is achieved that by fully analyzing and mining the data recorded during the product flow process, the abnormal situations existing in the product flow process can be obtained, and the corresponding distributors can be further managed to make up for the shortcomings of the current system in data integration and in-depth analysis, and ensure that products can flow in a standardized manner.

[0030] As an optional implementation, the code scanning information includes at least one of the scanning subject, scanning time, and scanning location, as well as product information obtained by scanning; the abnormality type includes supply relationship abnormality and / or freshness abnormality. Among them, product information includes, for example: one or more of: product name, product series, production date, manufacturer, target distributor, sales area, etc. Among them, the sales area is the area where the product corresponding to the product information is allowed to be sold. On this basis, step 101 includes at least one of the following: Compare the code scanning subject with the target distributor in the product information to obtain a first comparison result, and / or compare the code scanning location with the sales area in the product information to obtain a second comparison result, and compare the product type in the product information with the product type that the code scanning subject is allowed to sell to obtain a third comparison result, and if at least one of the first comparison result, the second comparison result, and the third comparison result satisfies the product supply relationship abnormality rule in the abnormal flow direction determination rule, determine that the abnormality type is a supply relationship abnormality; wherein the target distributor is a distributor that is allowed to sell the product corresponding to the product information. Exemplarily, the supply relationship abnormality rule includes at least one of the following: the code scanning subject does not belong to the target distributor, the code scanning location does not belong to the sales area of the target distributor, and the product type does not fall within the sales scope of the code scanning subject.

[0031] That is to say, this step is: on the one hand, the scanning subject (the scanning subject can be determined based on the scanning device) is compared one by one with the target distributor of the product. If the scanning subject does not belong to the target distributor, it is determined that the product cannot be sold by the scanning subject. Therefore, the abnormality type of the product is the product supply relationship abnormality, that is, the product meets the rule of the product supply relationship abnormality rule that the scanning subject does not belong to the target distributor. On the other hand, the scanning location (which can be obtained by positioning the pair of scanning devices) is compared with the sales area where the product is allowed to be sold. If the scanning location is not within the sales area, the product is a cross-regional circulation product, and the type of anomaly that exists in the product is a product supply relationship anomaly, that is, the product meets the rule of the product supply relationship anomaly that the scanning location does not belong to the sales area of the target distributor. On the other hand, on the basis that the scanning subject is the target distributor of the product, the product type is further compared with the product type that the scanning subject is allowed to sell. If the product type of the product does not belong to the product type sold by the scanning subject, the type of anomaly that exists in the product is a product supply relationship anomaly, that is, the product meets the rule of the product supply relationship anomaly that the product type does not belong to the sales scope of the scanning subject.

[0032] Based on the first time interval between the scan time and the production date in the product information, a first freshness of the product is determined. If the first freshness is lower than the freshness threshold in the abnormal flow determination rule, the abnormality type is determined to be a freshness abnormality. As previously mentioned, the first time interval is the product expiration date, and a preconfigured correspondence between the product expiration date and freshness is provided. Therefore, based on this correspondence, the first freshness corresponding to the first time interval can be determined, and then, based on a comparison of the first freshness with the freshness threshold, whether the product has a freshness abnormality can be determined.

[0033] That is, during operations such as sales shipment, delivery shipment, receipt, return shipment, and purchase shipment, inventory management personnel in the corresponding warehouses scan barcodes for shipment and entry. While scanning and collecting barcode information, the system (e.g., the subject implementing the product flow management method of this application) automatically determines the expiration date / freshness and product supply relationship of the scanned products. The system automatically records the corresponding information details.

[0034] As another optional implementation, the inventory information includes product type, product quantity, and product sales region; the abnormality type includes at least one of a supply relationship abnormality, a freshness abnormality, and an inventory turnover days abnormality; based on this, step 101 includes at least one of the following: Comparing the product type with the products that the dealer corresponding to the inventory information is allowed to sell, if the product type does not belong to the products that the dealer corresponding to the inventory information is allowed to sell, determining the abnormality type as a supply relationship abnormality according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; Comparing the product sales area corresponding to the product type with the location of the warehouse corresponding to the inventory information, if the product sales area does not include the location of the warehouse, determining the row type of the product as having an abnormal supply relationship according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; determining a second freshness of the product based on a second time interval between the acquisition date of the inventory information and the production date of the product, and determining that the abnormality type is a freshness abnormality when the second freshness is lower than a freshness threshold in the abnormal flow direction determination rule; The available days of the product in the inventory are determined based on the product quantity and the average monthly sales volume of the product. If the available days fall outside the first turnover range in the abnormal flow determination rules, the abnormality type is determined to be a turnover days abnormality. The average monthly sales volume of a product is the average sales volume of this type of product by the distributor corresponding to the warehouse over N consecutive months (total sales volume for N months / N), and the available days of the product are the ratio of the product quantity to the average monthly sales volume of the product. Furthermore, if the available days are less than the lower limit of the first turnover range, it indicates a relatively fast turnover; if the available days are greater than the upper limit of the first turnover range, it indicates a relatively slow turnover.

[0035] In the above two optional implementation methods, data such as product supply relationships, freshness, inventory turnover days, etc. can be automatically updated based on the inventory data automatically updated in various inventory entry and exit scenarios and daily by the system.

[0036] As an optional implementation, the warning rule includes one or more of a warning period, a warning push time, a warning recipient, and an anomaly type. Based on this, in step 102, according to the warning rule, from the stored data of the product with abnormal flow direction detected, abnormal data corresponding to the anomaly type indicated by the warning rule is extracted, including: According to the warning cycle and the warning push time, determine the time period corresponding to the current warning cycle; for example, if the warning cycle is one week and the warning push time is 7:00 a.m. every Monday, then the time period corresponding to the current warning cycle is 7:00 a.m. on two consecutive Mondays; According to the exception type and the time period, the exception data is obtained from the stored data. That is to say, when the warning push time is reached (continuing the above example, 7 o'clock on Monday), the exception data corresponding to the exception type that needs to be pushed is extracted from the stored data between two adjacent warning push times (including the data obtained by scanning the code for entering and leaving the warehouse and the periodically updated inventory information). For example, in the warning corresponding to the market management and channel management scenarios, the exception data corresponding to the supply relationship exception type is pushed; in the warning corresponding to the inventory management scenario, the exception data corresponding to the freshness exception and the turnover days exception type are pushed.

[0037] As an optional implementation, in step 102, based on the abnormal data, an early warning message is pushed to the early warning recipient, and the abnormal data is corrected based on the supplementary document fed back by the early warning recipient, including: Based on the abnormal data, an abnormality detail table is generated; illustratively, the abnormality detail table includes: one or more items from the inventory turnover days abnormality table, the freshness abnormality table, and the supply relationship abnormality table; the supply relationship abnormality table includes one or more items from the inventory flow abnormality table, the inventory advance scan table, the audit visit table, the off-site points table, the in-and-out table, and the store inventory collection table. In other words, different abnormality detail tables are set up for different abnormality types, among which, for the supply relationship abnormality type, specific detail tables corresponding to different scanning operation scenarios are also specifically set up. The scanning scenarios and warning scenarios corresponding to the above-mentioned supply relationship abnormality tables are shown in Table 1 below: Table 1 Warning scenario QR code scanning operation scenario Warning template scenario Abnormal inventory turnover days All inbound and outbound Inventory turnover days exception table Abnormal freshness All inbound and outbound Freshness Abnormality Table Abnormal product supply relationship Dealer Inventory Inventory flow abnormality table Inventory advance scan code table Abnormal product supply relationship Dealer / store visits Audit Visit Form Abnormal product supply relationship Consumer Points Off-site points table Abnormal product supply relationship All inbound and outbound In and out table Abnormal product supply relationship Store barcode collection Store inventory collection form Exemplarily, each of the above-mentioned exception details tables may include at least one of the following key data fields: abnormal flow operation dealer field, abnormal operation warehouse field, abnormal flow product field, abnormal flow product quantity field, abnormal flow product freshness field, abnormal flow product to which dealer field, abnormal flow product to which warehouse field.

[0038] Exemplarily, the other exception breakdown sheets except the off-site integration sheet may all include a region field, a provincial region field, and a city region field; among them, the inventory turnover days exception sheet may further include: a dealer field, a dealer code field, a warehouse code field, a warehouse name field, a product SKU field, a product name field, an inventory number field, a real-time turnover days (inventory number / average monthly sales volume * 30) field, a monthly average transfer goods field in the recent three months, and an inventory turnover dimension field; the freshness exception sheet may further include: a dealer field, a dealer code field, a warehouse code field, a warehouse name field, a product SKU field, a product name field, a freshness dimension field, an exception quantity field, a product inventory number field, and an abnormal inventory ratio field; the inventory count flow exception sheet includes: an inventory count dealer name field, an inventory count dealer 1P field, an inventory count warehouse code field, an inventory count warehouse name field, an abnormal flow SKU field, an abnormal flow product name field, an abnormal flow quantity field, an abnormal flow consignor code field, and an abnormal flow consignor name field; the inventory count early scanning sheet may further include: an inventory count dealer name field, an inventory count dealer 1P field, an inventory count warehouse code field, an inventory count warehouse name field (such as dealer warehouse), an inventory count warehouse type field, an inventory count warehouse code field, an inventory count warehouse name field (such as store warehouse), a store sales status (barcode) field, a current distribution status (barcode) field, a product SKU field, a product name field, and a product quantity field; the inspection visit sheet may further include: a visited warehouse type field, a visited warehouse name field, a visited warehouse code field, a visited warehouse consignor field, a visited warehouse consignor name field, an abnormal flow product SKU field, an abnormal flow product name field, an abnormal flow product quantity field, an abnormal consignor name field, and an abnormal consignor code field, etc.; the inbound and outbound sheet may further include: an operating warehouse name field, an operating warehouse code field, an operating warehouse consignor field, a transaction nature, an abnormal flow product SKU field, an abnormal flow product name field, an abnormal flow product quantity field, an abnormal consignor name field, and an abnormal consignor code field, etc.; the store inventory collection sheet may further include: a collected store name field, a collected store code field, a store supply consignor name field, an abnormal product series field, an abnormal flow product SKU field, an abnormal flow product name field, an abnormal flow product quantity field, an abnormal consignor name field, and an abnormal consignor code field, etc. The off-site integration sheet may include: an off-site integration dealer code field, an off-site integration dealer name field, an off-site integration product series field, an off-site integration product SKU field, an off-site integration product name field, an off-site integration product quantity field, and an off-site integration identity quantity field (the quantity of all provinces where the off-site integration products are scanned).

[0039] At the warning push moment in the warning rule, send the warning information to the warning recipient, where the warning information includes the exception breakdown sheet; Receive the supplementary document feedback from the warning recipient; for example, after receiving the abnormality details list, the warning recipient will self-check the cause of the abnormality. If the product flow is abnormal due to abnormal operation, the corresponding proof data can be submitted to eliminate the abnormal data.

[0040] The abnormal flow documents are re-entered based on the re-entry documents, and the abnormal data is corrected based on the re-entry results. For example, the alert recipient (such as a salesperson) performs re-entry of the relevant abnormal flow documents based on the received abnormal flow data table. After the corresponding inbound and outbound documents are re-entered, the system automatically corrects the abnormal product flow data.

[0041] As an optional implementation, in step 102, based on the abnormal data, abnormal management and control is performed on the dealers related to the abnormal data, including: According to the abnormal data, the number of abnormally directed distributors, abnormally directed warehouses, and abnormally directed stores corresponding to the abnormal data is obtained; The target warning dimension is determined based on the mapping relationship between the number of abnormal flow products and the pre-configured number range and the warning dimension; for example, the warning dimensions corresponding to different abnormal product quantities include high warning dimension, medium warning dimension and low warning dimension. For example, if the abnormal number is in the range of 10 to 30, the warning dimension is a low warning dimension; if the abnormal number is in the range of 30 to 60, the warning dimension is a medium warning dimension; if the abnormal number is above 60, the warning dimension is a high warning dimension.

[0042] The distributor is managed and controlled based on the target warning dimension. This management includes product order control and / or distributor payment collection control. The higher the warning dimension, the more non-compliant the distributor's product management is. To prevent abnormal product flows and reduce losses, the distributor will be managed and controlled, such as by limiting order quantities or shortening payment cycles.

[0043] That is to say, based on the existing abnormal flow data, the system automatically calculates the number of abnormal flow products corresponding to abnormal flow dealers, abnormal flow operation warehouses, and operation stores, and sets different warning dimensions (high, medium, and low) for dealers with a large number of abnormal flows. The corresponding warning data can be used for other product order control, dealer collection management and other related business management.

[0044] Furthermore, as an optional implementation, the method further includes: Based on the scanned code information, obtain the real-time distribution data of the product in warehouses at each level; based on the scanned code information and / or the inventory information, obtain the product expiration date; and based on the inventory information, obtain the warehouse turnover efficiency; wherein the turnover efficiency corresponds to the number of days the inventory is available.

[0045] According to the warehouse turnover efficiency, the product turnover efficiency is calculated; for example, the product turnover efficiency of warehouses at all levels is calculated according to different quarters / months.

[0046] A product supply scheduling plan is predicted based on the real-time distribution data, the product expiration date, the product turnover efficiency and the product production efficiency.

[0047] First, we can analyze the omnichannel flow of all products through: ① Real-time distribution data, product expiration dates, and warehouse turnover efficiency for products (by minimum SKU) at each warehouse level (factory, central warehouse, branch warehouse, distributor warehouse, and store warehouse); ② Product turnover efficiency statistics for each warehouse level by quarter / month; and ③ The production efficiency of finished products at the factory. Secondly, we can predict product supply and production schedules, with production forecasts for overseas factories on a quarterly basis and for domestic factories on a monthly basis. In other words, based on current warehouse inventory and supply conditions, we can estimate the corresponding production time and quantity for each product, ultimately achieving efficient supply chain management and reducing losses caused by inventory backlogs.

[0048] An example of the above optional implementation method may include: first, obtaining real-time distribution data (inventory quantity in each warehouse) and the expiration dates of inventory products at each level of warehouses; second, obtaining the inventory quantity of products with expiration dates within a normal range; third, determining the inventory turnover days based on the ratio of the inventory quantity of products with expiration dates within a normal range to the average monthly sales volume over the past six months; then, if the product turnover days are within a preset time range (pre-configured 55 to 60 days), production scheduling is based on the production quantity / sales quantity of the target month of the previous year (the month corresponding to the production scheduling plan). If the product turnover days are less than the minimum value of the preset time range, the scheduled production quantity should be greater than the production quantity / sales quantity of the target month of the previous year to compensate for the current inventory shortage; if the product turnover days are greater than the maximum value of the preset time range, the scheduled production quantity should be less than the production quantity / sales quantity of the target month of the previous year to avoid inventory backlogs. Of course, when scheduling, factors such as the current sales environment and sales performance of the preceding months can also be considered based on actual conditions.

[0049] The above-mentioned embodiment of the present application completes the real-time collection of product flow data at key nodes, and realizes product flow tracing, real-time abnormal analysis, data push, real-time prediction analysis, and support report data viewing in quasi-real time within a system. If there is an abnormal flow, the system can correct the relevant flow data so that the data truly and completely reflects the product flow. Specifically: First, it solves the problem that in the process of flow data collection, there will inevitably be data errors in the process of manual operation. Without the system to automatically identify the corresponding errors and the causes of the errors, the overall flow data will be imprecise or untrue. Second, it solves the problem that from product production to the hands of consumers, there are many different operating entities involved in the in-and-out operations. The in-and-out operations of different groups of people are not necessarily standard, and the in-and-out data are not necessarily collected comprehensively, which may lead to the problem of faults or missing in the middle links of product flow data. Third, it solves the problem that the work efficiency of manually checking a large amount of data is low, and the real-time performance is poor. It cannot realize immediate audit from the product management level, and the lag of the data may also cause inaccurate prediction data. Finally, the following beneficial effects are achieved: on the one hand, the product flow management data is coherent, and it is possible to analyze the inventory accuracy, inventory freshness, and inventory turnover efficiency of all nodes from the product perspective, thereby improving the management capabilities of the product. On the other hand, there is real-time analysis of product supply relationships at key nodes, and it supports active push of abnormal data, providing clues for abnormal flow management in real time, effectively improving channel inventory management capabilities, improving market management efficiency, and establishing a good manufacturer-merchant cooperation model; on the other hand, the embodiment of the present application is simple to configure, and supports push of multiple distribution scenarios, data ranges, and distribution times, which greatly facilitates users to use the flow management system and do a good job of product flow control. On the other hand, the embodiment of the present application uses computer computing power to realize big data analysis, improve supply chain forecasting capabilities, and improve supply scheduling efficiency, thereby supporting channel sales to the greatest extent.

[0050] The embodiment of the present application also provides a management device based on product flow, such as Figure 2 As shown, the device includes: The monitoring module 201 is used to monitor the flow of products during their flow, based on the currently acquired scanned code information and / or inventory information and pre-configured abnormal flow direction determination rules, to determine the abnormal type of the product flow direction; The processing module 202 is configured to extract, from the stored data of the product with abnormal flow, according to the early warning rule, abnormal data corresponding to the abnormal type indicated by the early warning rule, and perform at least one of the following based on the abnormal data: Pushing warning information to the warning recipient, and correcting the abnormal data based on the supplementary document fed back by the warning recipient according to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

[0051] The scanning information includes at least one of the scanning subject, scanning time, and scanning location, and also includes product information obtained by scanning; the abnormality type includes supply relationship abnormality and / or freshness abnormality; On this basis, the processing module 202 is used to monitor the flow direction of the product according to the currently acquired scanned code information and the pre-configured abnormal flow direction determination rules, and obtain the abnormal type of the product flow direction, and is specifically used to perform at least one of the following: Comparing the code scanning subject with the target distributor in the product information to obtain a first comparison result, and / or comparing the code scanning location with the sales area in the product information to obtain a second comparison result, and comparing the product type in the product information with the product type allowed to be sold by the code scanning subject to obtain a third comparison result, and if at least one of the first comparison result, the second comparison result, and the third comparison result satisfies the product supply relationship abnormality rule in the abnormal flow direction determination rule, determining that the abnormality type is a supply relationship abnormality; wherein the target distributor is a distributor allowed to sell the product corresponding to the product information; The first freshness of the product is determined based on a first time interval between the scanning time and the production date in the product information, and when the first freshness is lower than the freshness threshold in the abnormal flow direction determination rule, the abnormality type is determined to be a freshness abnormality.

[0052] Among them, the abnormal product supply relationship rules include at least one of the following: the scanning entity does not belong to the target dealer, the scanning location does not belong to the sales area of the target dealer, and the product type does not fall within the sales scope of the scanning entity.

[0053] The inventory information includes product type and product quantity; the abnormality type includes at least one of abnormal supply relationship, abnormal freshness and abnormal inventory turnover days; On this basis, the processing module 202 is used to monitor the product flow direction for abnormalities based on the currently acquired inventory information and the pre-configured abnormal flow direction determination rules, and to obtain the abnormal type of the product flow direction, specifically to perform at least one of the following: Comparing the product type with the products that the dealer corresponding to the inventory information is allowed to sell, if the product type does not belong to the products that the dealer corresponding to the inventory information is allowed to sell, determining the abnormality type as a supply relationship abnormality according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; determining a second freshness of the product based on a second time interval between the acquisition date of the inventory information and the production date of the product, and determining that the abnormality type is a freshness abnormality when the second freshness is lower than a freshness threshold in the abnormal flow direction determination rule; The available days of the product in the inventory are determined based on the product quantity and the average monthly sales quantity of the product, and when the available days are outside the first turnover range in the abnormal flow determination rule, the abnormality type is determined to be a turnover days abnormality.

[0054] The warning rules include one or more of the following: warning period, warning push time, warning receiver, and abnormality type; On this basis, the processing module 202 is used to extract abnormal data corresponding to the abnormal type indicated by the early warning rule from the stored data of the product with abnormal flow according to the early warning rule, specifically to: Determine the time period corresponding to the current warning cycle based on the warning cycle and the warning push time; The abnormal data is obtained from the stored data according to the abnormality type and the time period.

[0055] The processing module 202 is used to push the warning information to the warning recipient and correct the abnormal data based on the supplementary document fed back by the warning recipient, specifically to: Generate an abnormality detail table based on the abnormal data; At the warning push moment in the warning rule, sending the warning information to the warning recipient, wherein the warning information includes the abnormality details list; Receive the supplementary document feedback from the warning recipient; The abnormal flow document is supplemented according to the supplementary document, and the abnormal data is corrected based on the supplementary result.

[0056] Among them, the abnormal details table includes: one or more items of the inventory turnover days abnormal table, the freshness abnormal table and the supply relationship abnormal table; the supply relationship abnormal table includes one or more items of the inventory flow abnormal table, the inventory advance scan code table, the audit visit table, the off-site points table, the in and out warehouse table and the store inventory collection table.

[0057] Among them, the abnormal details table includes at least one of the following fields: abnormal flow operation dealer field, abnormal operation warehouse field, abnormal flow product field, abnormal flow product quantity field, abnormal flow product freshness field, abnormal flow product to which dealer field, abnormal flow product to which warehouse field.

[0058] The processing module 202, when used to perform abnormality management and control on the dealers related to the abnormal data based on the abnormal data, is specifically used to: According to the abnormal data, the number of abnormally directed distributors, abnormally directed warehouses, and abnormally directed stores corresponding to the abnormal data is obtained; Determine the target warning dimension based on the mapping relationship between the quantity of the abnormally flowing products and the pre-configured quantity range and the warning dimension; According to the target warning dimension, the dealer is managed and controlled, wherein the management and control of the dealer includes product order control and / or dealer payment collection control.

[0059] Wherein, the device further includes: an analysis module, configured to obtain real-time distribution data of the product in warehouses at various levels based on the scanned code information; obtain product expiration dates based on the scanned code information and / or the inventory information; and obtain warehouse turnover efficiency based on the inventory information; A statistics module, used for calculating product turnover efficiency based on the warehouse turnover efficiency; The forecasting module is used to forecast the product supply scheduling plan based on the real-time distribution data, the product expiration date, the product turnover efficiency and the product production efficiency.

[0060] It should be noted here that the above-mentioned product flow-based management device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned product flow-based management method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0061] An embodiment of the present application also provides a management device based on product flow, including a transceiver 310, a processor 300, a memory 320, and a program stored on the memory 320 and executable on the processor 300; wherein, when the processor 300 executes the program, the management method based on product flow as described above is implemented.

[0062] The transceiver 310 is configured to receive and send data under the control of the processor 300 .

[0063] Among them, Figure 3In the embodiment of the present invention, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits such as one or more processors represented by processor 300 and memory represented by memory 320. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore not further described herein. The bus interface provides an interface. The transceiver 310 can be multiple components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices over a transmission medium.

[0064] The processor 300 is responsible for managing the bus architecture and general processing, and the memory 320 can store data used by the processor 300 when performing operations.

[0065] The present application also provides a readable storage medium having a program stored thereon. When executed by a processor, the program implements the product flow-based management method described above and achieves the same technical effect. To avoid repetition, the details are not described here. The readable storage medium may be, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0066] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, hardware can also be used, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, disk, or CD) and includes a number of instructions for executing the methods described in each embodiment of this application.

[0067] Therefore, an embodiment of the present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the product flow-based management method as described above and can achieve the same technical effect. To avoid repetition, they will not be described here.

[0068] In embodiments of the present application, modules can be implemented in software so that they can be executed by various types of processors. For example, an identified executable code module can include one or more physical or logical blocks of computer instructions, for example, which can be constructed as objects, processes, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but can include different instructions stored in different locations, which, when logically combined together, constitute the module and achieve the specified purpose of the module.

[0069] In fact, executable code module can be a single instruction or many instructions, and can even be distributed on a plurality of different code segments, distributed in the middle of different programs, and distributed across a plurality of memory devices.Similarly, operating data can be identified in the module, and can be realized and organized in the data structure of any appropriate type according to any appropriate form.Described operating data can be collected as a single data set, or can be distributed in different locations (being included on different storage devices), and can only be present in a system or network as an electronic signal at least in part.

[0070] When a module can be implemented using software, given the current state of hardware technology, those skilled in the art can build corresponding hardware circuits to implement the corresponding functions of the software-implemented module without considering cost. The hardware circuits may include conventional very large-scale integration (VLSI) circuits or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules may also be implemented using programmable hardware devices, such as field programmable gate arrays, programmable array logic, or programmable logic devices.

[0071] The above exemplary embodiments are described with reference to the accompanying drawings. Many different forms and embodiments are possible without departing from the spirit and teachings of this application. Therefore, this application should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this application will be complete and impartial and will convey the scope of this application to those skilled in the art. In the drawings, component sizes and relative sizes may be exaggerated for clarity. The terminology used herein is for purposes of describing specific exemplary embodiments only and is not intended to be limiting. As used herein, unless the context clearly indicates otherwise, the singular forms "a," "an," and "the" are intended to encompass such plural forms. It will be further understood that the terms "comprising" and / or "including," when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not preclude the presence or addition of one or more other features, integers, steps, operations, components, elements, and / or groups thereof. Unless otherwise indicated, when stated, a range of values includes the upper and lower limits of that range and any subranges therebetween.

[0072] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles described in the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A management method based on product flow, characterized in that: include: During the product flow process, based on the currently acquired scan code information and / or inventory information and the pre-configured abnormal flow direction judgment rules, the product flow direction is monitored for abnormalities and the abnormal type of the product flow direction is obtained; According to the early warning rule, in the stored data of the product with abnormal flow direction, extract the abnormal data corresponding to the abnormal type indicated by the early warning rule, and perform at least one of the following according to the abnormal data: Pushing the warning information to the warning recipient, and correcting the abnormal data based on the supplementary recording document fed back by the warning recipient; wherein the supplementary recording document is related to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

2. The method according to claim 1, characterized in that The code scanning information includes at least one of the scanning subject, scanning time, and scanning location, and also includes product information obtained by scanning; the abnormality type includes supply relationship abnormality and / or freshness abnormality; Based on the currently acquired scanned code information and pre-configured abnormal flow direction determination rules, the product flow direction is monitored for abnormalities and the abnormal type of the product flow direction is obtained, including at least one of the following: Comparing the code scanning subject with the target distributor in the product information to obtain a first comparison result, and / or comparing the code scanning location with the sales area in the product information to obtain a second comparison result, and comparing the product type in the product information with the product type allowed to be sold by the code scanning subject to obtain a third comparison result, and if at least one of the first comparison result, the second comparison result, and the third comparison result satisfies the product supply relationship abnormality rule in the abnormal flow direction determination rule, determining that the abnormality type is a supply relationship abnormality; wherein the target distributor is a distributor allowed to sell the product corresponding to the product information; The first freshness of the product is determined based on a first time interval between the scanning time and the production date in the product information, and when the first freshness is lower than the freshness threshold in the abnormal flow direction determination rule, the abnormality type is determined to be a freshness abnormality.

3. The method according to claim 2, characterized in that The product supply relationship abnormality rules include at least one of the following: the scanning entity does not belong to the target dealer, the scanning location does not belong to the sales area of the target dealer, and the product type does not fall within the sales scope of the scanning entity.

4. The method according to claim 1, wherein The inventory information includes product type and product quantity; the abnormality type includes at least one of abnormal supply relationship, abnormal freshness and abnormal inventory turnover days; Based on the currently acquired inventory information and pre-configured abnormal flow determination rules, the product flow is monitored for abnormalities and the abnormal type of product flow is obtained, including at least one of the following: Comparing the product type with the products that the dealer corresponding to the inventory information is allowed to sell, if the product type does not belong to the products that the dealer corresponding to the inventory information is allowed to sell, determining the abnormality type as a supply relationship abnormality according to the product supply relationship abnormality rule in the abnormal flow direction determination rule; determining a second freshness of the product based on a second time interval between the acquisition date of the inventory information and the production date of the product, and determining that the abnormality type is a freshness abnormality when the second freshness is lower than a freshness threshold in the abnormal flow direction determination rule; The available days of the product in the inventory are determined based on the product quantity and the average monthly sales quantity of the product, and when the available days are outside the first turnover range in the abnormal flow determination rule, the abnormality type is determined to be a turnover days abnormality.

5. The method according to claim 1, wherein The warning rules include one or more of the following: warning period, warning push time, warning recipient, and abnormality type; According to the early warning rules, in the stored data of the product with abnormal flow direction, the abnormal data corresponding to the abnormal type indicated by the early warning rules is extracted, including: Determine the time period corresponding to the current warning cycle based on the warning cycle and the warning push time; The abnormal data is obtained from the stored data according to the abnormality type and the time period.

6. The method according to claim 1 or 5, characterized in that According to the abnormal data, push the warning information to the warning recipient, and correct the abnormal data based on the supplementary document fed back by the warning recipient, including: Generate an abnormality detail table based on the abnormal data; At the warning push moment in the warning rule, sending the warning information to the warning recipient, wherein the warning information includes the abnormality details list; Receive the supplementary document feedback from the warning recipient; The abnormal flow document is supplemented according to the supplementary document, and the abnormal data is corrected based on the supplementary result.

7. The method according to claim 6, characterized in that The abnormal details table includes: one or more items of the inventory turnover days abnormal table, the freshness abnormal table and the supply relationship abnormal table; the supply relationship abnormal table includes one or more items of the inventory flow abnormal table, the inventory advance scan code table, the audit visit table, the off-site points table, the in and out warehouse table and the store inventory collection table.

8. The method according to claim 6, characterized in that The abnormal details table includes at least one of the following fields: abnormal flow operation dealer field, abnormal operation warehouse field, abnormal flow product field, abnormal flow product quantity field, abnormal flow product freshness field, abnormal flow product dealer field, and abnormal flow product warehouse field.

9. The method according to claim 1, characterized in that Based on the abnormal data, abnormal management and control are performed on the dealers related to the abnormal data, including: According to the abnormal data, the number of abnormally directed distributors, abnormally directed warehouses, and abnormally directed stores corresponding to the abnormal data is obtained; Determine the target warning dimension based on the mapping relationship between the quantity of the abnormally flowing products and the pre-configured quantity range and the warning dimension; According to the target warning dimension, the dealer is managed and controlled, wherein the management and control of the dealer includes product order control and / or dealer payment collection control.

10. The method according to claim 1, characterized in that The method further comprises: Obtaining real-time distribution data of the product in warehouses at all levels based on the scanned code information; obtaining product expiration dates based on the scanned code information and / or the inventory information; and obtaining warehouse turnover efficiency based on the inventory information; Calculate product turnover efficiency based on the warehouse turnover efficiency; A product supply scheduling plan is predicted based on the real-time distribution data, the product expiration date, the product turnover efficiency and the product production efficiency.

11. A management device based on product flow, characterized in that: include: The monitoring module is used to monitor the flow of products during their flow, based on the currently acquired scanned code information and / or inventory information, and pre-configured abnormal flow direction determination rules, to determine the abnormal type of product flow. A processing module is configured to extract, from the stored data of products detected to have abnormal flow according to the early warning rule, abnormal data corresponding to the abnormal type indicated by the early warning rule, and perform at least one of the following based on the abnormal data: Pushing the warning information to the warning recipient, and correcting the abnormal data based on the supplementary recording document fed back by the warning recipient; wherein the supplementary recording document is related to the warning information; Conduct abnormal management and control on dealers related to the abnormal data.

12. A product flow management device comprising a transceiver, a processor, a memory, and a program stored in the memory and executable on the processor; characterized in that: The transceiver is used to send and receive data under the control of the processor, and the processor implements the product flow-based management method according to any one of claims 1 to 10 when executing the program.

13. A readable storage medium having a program or instruction stored thereon, characterized in that: When the program or instruction is executed by a processor, the product flow-based management method according to any one of claims 1 to 10 is implemented.

14. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implements the product flow-based management method according to any one of claims 1 to 10.

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