Order allocation method and device, electronic equipment and storage medium

Abstract

The invention discloses an order allocation method and device, electronic equipment and a storage medium, and relates to the technical field of medical instruments. The method comprises the steps that historical order data of multiple suppliers are acquired, and the historical order data comprise time information, product information and channel information; based on the historical order data, performance criteria corresponding to the suppliers are determined; wherein the performance benchmark comprises the product supply amount and represents the supply capacity of the supplier; and based on the performance benchmark, performing order allocation on the plurality of suppliers according to the current enterprise data, the enterprise data being determined based on the last allocated multi-dimensional order data of the plurality of suppliers. Therefore, the supplier historical order data is utilized to accurately evaluate the supply capability, reasonable resource allocation is realized, the defects of traditional static allocation are overcome, the response speed of a supply chain is improved, and the dependence on a single supplier and the risk dispersion are reduced through reasonable allocation.

Description

Technical Field

[0001] This application relates to the technical field of medical devices, and particularly to an order allocation method, device, electronic device, and storage medium. Background Art

[0002] In the cooperation relationship between a brand owner and suppliers, as the core of the production link, the production efficiency, cost control, quality control ability, and response speed of suppliers directly determine whether the brand owner can quickly and efficiently meet market demands. Due to differences in factors such as scale, technical strength, and production experience among suppliers, different levels and performance are formed.

[0003] However, traditional order allocation methods often follow static production capacity allocation principles, failing to fully consider the actual capabilities, historical performance, and market dynamic changes of suppliers, resulting in unreasonable resource allocation, overcapacity for some suppliers while some other suppliers are unable to meet order demands. This not only affects the overall efficiency of the supply chain but may also lead to unfair competition among suppliers, reducing the stability and sustainability of the supply chain. Summary of the Invention

[0004] Embodiments of this application provide an order allocation method, device, electronic device, and storage medium.

[0005] On the one hand, this application provides an order allocation method, including:

[0006] Obtain historical order data of multiple suppliers, where the historical order data includes time information, product information, and channel information;

[0007] Based on the historical order data, determine the performance benchmarks corresponding to multiple suppliers respectively; wherein, the performance benchmark includes the product supply quantity, which represents the supply ability of the supplier;

[0008] Based on the performance benchmarks, allocate the current planning data to multiple suppliers, and the planning data is determined based on the multi-dimensional order data of the multiple suppliers in the previous allocation.

[0009] On the one hand, this application provides an order allocation device, including:

[0010] An obtaining module, configured to obtain historical order data of multiple suppliers, where the historical order data includes time information, product information, and channel information;

[0011] A determining module, configured to determine the performance benchmarks corresponding to multiple suppliers respectively based on the historical order data; wherein, the performance benchmark includes the product supply quantity, which represents the supply ability of the supplier;

[0012] An allocation module for allocating current project data to multiple suppliers based on a performance benchmark, where the project data is determined based on the multi-dimensional order data allocated to the multiple suppliers last time.

[0013] In a possible embodiment, the determination module is configured to: statistically analyze historical order data based on supplier information, time information, product information, and channel information to obtain a statistical result; statistically analyze the statistical result based on supplier information, time information, and product information to obtain the product quantities produced by each of the multiple suppliers in each time period; perform a weighting process on the product quantities corresponding to each of the multiple suppliers to obtain the performance benchmarks corresponding to each of the multiple suppliers.

[0014] In a possible embodiment, the apparatus further includes: a summarization module for obtaining the multi-dimensional order data allocated to the multiple suppliers last time, where the multi-dimensional order data includes time information, channel information, product information, batch information, and regional information; summarizing the multi-dimensional order data according to the product dimension to obtain the current project data.

[0015] In a possible embodiment, the allocation module is configured to: determine the product supply quantities corresponding to each of the multiple suppliers based on the performance benchmark; compare the product planned quantity corresponding to the current project data with the sum of the corresponding product supply quantities of the multiple suppliers; if the product planned quantity is greater than the sum of the product supply quantities of the multiple suppliers, allocate orders to the multiple suppliers respectively according to the product supply quantities.

[0016] In a possible embodiment, the allocation module is configured to: determine the allocation priorities of the multiple suppliers based on the performance benchmark; determine the allocation order and allocation satisfaction corresponding to each of the multiple suppliers based on the allocation priorities, where the allocation satisfaction represents the ratio between the actual allocated quantity and the product supply quantity corresponding to the performance benchmark; allocate orders to the multiple suppliers based on the allocation order and allocation satisfaction.

[0017] In a possible embodiment, the allocation module is configured to: determine the allocation order corresponding to each of the multiple suppliers based on the allocation priorities; determine the allocation satisfaction corresponding to each of the multiple suppliers based on the current market supply and demand situation and the allocation priorities.

[0018] In a possible embodiment, the allocation module is configured to: determine the currently allocated supplier based on the allocation order; allocate orders to the currently allocated supplier according to the product supply quantity corresponding to the product of the allocation satisfaction and the corresponding performance benchmark; determine whether there are unallocated orders in the current project data; if so, allocate orders to the next supplier based on the allocation order and allocation satisfaction.

[0019] On the one hand, an embodiment of the present application provides an electronic device, which includes a processor and a memory. Among them, the memory stores program code, and when the program code is executed by the processor, the processor is caused to execute any one of the above order allocation methods.

[0020] On the one hand, a computer-readable storage medium provided by the present application includes program code, and when the storage medium runs on an electronic device, the program code is used to cause the electronic device to execute any one of the above order allocation methods.

[0021] The beneficial effects of the present application are as follows:

[0022] An embodiment of the present application provides an order allocation method, device, electronic device and storage medium. First, by analyzing the historical order data of suppliers (including time, product and channel information), the actual supply capacity and performance of suppliers are accurately evaluated, so as to achieve reasonable allocation of resources and avoid problems of resource waste and supply-demand imbalance caused by traditional static allocation methods. Secondly, the dynamic allocation mechanism can quickly respond to changes in market demand, shorten the order processing time, and improve the overall response speed of the supply chain. This data-driven decision support not only reduces the deviation of subjective judgment, but also provides brand parties with more comprehensive market insights through multi-dimensional data analysis. In addition, by setting performance benchmarks, the solution encourages suppliers to improve their own capabilities, promotes fair competition, reduces supplier dissatisfaction or withdrawal caused by unfair allocation, thereby enhancing the stability and sustainability of the supply chain. Reasonable order allocation also reduces the brand party's dependence on a single supplier and further disperses the supply chain risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0024] Figure 1 It is a schematic diagram of an application scenario in an embodiment of the present application;

[0025] Figure 2 It is a flowchart of the implementation of an order allocation method in an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of the structure of an order allocation device in an embodiment of the present application;

[0027] Figure 4 It is a schematic diagram of a hardware composition structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] To make the objectives, technical solutions, and advantages of this application clearer and more understandable, the following will clearly and completely describe the technical solutions in the embodiments of this application in combination with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application. Without conflict, the embodiments in this application and the features in the embodiments can be combined arbitrarily with each other. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0029] The terms "first", "second", etc. in the specification and claims of this application and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here.

[0030] The following briefly introduces the design concept of the embodiments of this application:

[0031] In the cooperative relationship between the brand side and the supplier, as the core of the production link, the production efficiency, cost control, quality control ability, and response speed of the supplier directly determine whether the brand side can quickly and efficiently meet market demand. Due to differences in factors such as scale, technical strength, and production experience among suppliers, different levels and performance are formed. However, the traditional order allocation method often based on static production capacity allocation principles fails to fully consider the actual capabilities, historical performance, and market dynamic changes of suppliers, resulting in unreasonable resource allocation, overcapacity for some suppliers while some other suppliers are unable to meet order requirements. This not only affects the overall efficiency of the supply chain but may also lead to unfair competition among suppliers, reducing the stability and sustainability of the supply chain.

[0032] In view of this, the embodiments of the present application provide an order allocation method, device, electronic device, and storage medium. The order allocation method includes: obtaining historical order data of multiple suppliers, where the historical order data includes time information, product information, and channel information; determining corresponding performance benchmarks for multiple suppliers based on the historical order data; where the performance benchmark includes the product supply quantity, which characterizes the supply capacity of the supplier; based on the performance benchmark, allocating the current planning data to multiple suppliers, and the planning data is determined based on the multi-dimensional order data allocated to the multiple suppliers last time. This technical solution optimizes supply chain management through a dynamic order allocation method. In this way, the supply capacity is accurately evaluated by using the historical order data of suppliers (covering time, product, and channel information), resource allocation is realized, and the deficiencies of traditional static allocation are solved. Secondly, the dynamic allocation mechanism quickly responds to market changes, shortens the order processing time, and improves the supply chain response speed. Data-driven decision-making reduces subjective biases, and multi-dimensional analysis provides a comprehensive market insight. In addition, the performance benchmark motivates suppliers to improve their capabilities, promotes fair competition, and enhances the stability and sustainability of the supply chain. Reasonable allocation reduces the dependence on a single supplier and disperses risks.

[0033] The preferred embodiments of the present application are described below with reference to the accompanying drawings of the specification. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present application, and are not used to limit the present application. And without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0034] As Figure 1 shown, it is a schematic diagram of an application scenario provided by the embodiments of the present application. In this application scenario schematic diagram, it includes a terminal device 101 and a server 102. Among them, the terminal device 101 communicates with the server 102 through a communication network.

[0035] The terminal device 101 is an electronic device used by a target object. This electronic device can be a personal computer, mobile phone, tablet computer, notebook, e-book reader, vehicle-mounted terminal, etc. In addition, a client related to order allocation can be installed on the terminal device 101. This client can be software (such as an APP, browser, etc.), or a web page, a small program, etc. The target object can use the above-mentioned client related to order allocation through the terminal device 101 to perform operations related to order allocation.

[0036] The server 102 can be an independent physical server, an edge device 102 in the field of cloud computing, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, cloud functions, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0037] There is no limit on the number of the above terminal devices 101 and / or servers 102.

[0038] It should be noted that the order allocation method in the embodiments of the present application can be executed independently by the terminal device 101 or the server 102, or jointly executed by the terminal device 101 and the server 102. For example, when executed independently by the server 102, the server 102 obtains the historical order data of multiple suppliers, and the historical order data includes time information, product information, and channel information; based on the historical order data, the performance benchmarks corresponding to multiple suppliers are determined; among them, the performance benchmark includes the product supply volume, which represents the supply capacity of the supplier; based on the performance benchmark, the current planning data is used to allocate orders to multiple suppliers, and the planning data is determined based on the multi-dimensional order data allocated to multiple suppliers last time.

[0039] Next, in combination with the above application scenarios, the order allocation method provided by the exemplary embodiments of the present application will be described with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown for the convenience of understanding the spirit and principle of the present application, and the embodiments of the present application are not limited in this regard.

[0040] Refer to Figure 2 , which is the implementation flowchart of an order allocation method provided by an embodiment of the present application. Here, the server is used as the execution subject for introduction, and the specific implementation process of the method is as follows:

[0041] S201, Obtain the historical order data of multiple suppliers, and the historical order data includes time information, product information, and channel information.

[0042] S202, Based on the historical order data, determine the performance benchmarks corresponding to multiple suppliers respectively; among them, the performance benchmark includes the product supply volume, which represents the supply capacity of the supplier.

[0043] S203, Based on the performance benchmark, allocate the current planning data to multiple suppliers, and the planning data is determined based on the multi-dimensional order data allocated to multiple suppliers last time.

[0044] In the embodiments of the present application, the time information includes year and quarter information, the product information includes brand, noodle type, and variety segmentation pool, and the channel information includes channel and age segment. When obtaining historical order data, it is mainly carried out by combining the historical cooperation data between the brand side and multiple suppliers. After obtaining the historical order data, statistics are carried out according to "supplier code + supplier name + year + quarter + brand + noodle type + channel + age segment + variety segmentation pool" to facilitate the further use of the historical order data in the future.

[0045] After obtaining the historical order data, based on the historical order data, determine the performance benchmarks corresponding to multiple suppliers, including: statistically analyzing the historical order data based on supplier information, time information, product information, and channel information to obtain a statistical result, where the supplier information includes supplier number and supplier name; statistically analyzing the statistical result based on supplier information, time information, and product information to obtain the product quantities produced by multiple suppliers in each time period; further, performing a weighting process on the product quantities corresponding to multiple suppliers to obtain the performance benchmarks corresponding to multiple suppliers. Among them, the weighting coefficient corresponding to the weighting process is determined according to the historical order data. If the historical performance benchmark of a certain supplier is relatively high, the weighting coefficient can be increased, and vice versa, it can be decreased.

[0046] For example, summarize and statistically analyze the historical order data of multiple suppliers obtained in step S201 based on "supplier code + supplier name + year + quarter + brand + noodle type + variety segmentation pool" to obtain the product supply quantity (number of product pieces) corresponding to this benchmark. If at this time, the statistical result shows that the product supply quantity corresponding to "Supplier A + 2022 + First Quarter + Brand A + Knitting + Segmentation Pool A" is 100, and the historical performance benchmark of Supplier A is excellent, then the weighting coefficient K can be set to 1.2, and multiplying 100 by the weighting coefficient 1.2 can obtain the performance benchmark of 120 for Supplier A under the benchmark of "Supplier A + 2022 + First Quarter + Brand A + Knitting + Segmentation Pool A", which also means that the knitting production capacity of Supplier A for Brand A in the first quarter of 2022 is 120 pieces.

[0047] For another example, the historical order data of multiple suppliers obtained in step S201 is summarized and statistically analyzed based on the benchmark of "supplier code + supplier name + year + quarter + brand + noodle type + variety sub - pool". It is statistically obtained that the product supply volume corresponding to "supplier B + 2022 + first quarter + brand A + knitting + sub - pool A" is 100, and the historical performance benchmark of supplier B ranks relatively low among multiple suppliers. Then, the weighting coefficient K can be set to 0.8, and 100 is multiplied by the weighting coefficient 0.8 to obtain the performance benchmark of 80 for supplier B under the benchmark of "supplier B + 2022 + first quarter + brand A + knitting + sub - pool A", which also means that the knitting production capacity of supplier B for brand A in the first quarter of 2022 is 80 pieces.

[0048] After obtaining the performance benchmarks corresponding to multiple suppliers respectively, and before allocating the current planning data to multiple suppliers based on the performance benchmarks, it further includes: obtaining the multi - dimensional order data allocated to multiple suppliers last time. The multi - dimensional order data includes time information, channel information, product information, batch information, and regional information, and further summarizes the multi - dimensional order data according to the product dimension to obtain the current planning data.

[0049] For example, referring to Table 1, it is an example table of planning data. In Table 1, Q1 represents the first quarter. According to the data in Table 1, the brand plans to produce 100,000 pieces of knitted products, 150,000 pieces of woolen knitted products, and 200,000 pieces of denim products in the first quarter of 2022.

[0050] Serial number Year Quarter Flour type Planned production volume of product / piece 1 2022 Q1 Knitting 100,000 2 2022 Q1 Wool knitting 150,000 3 2022 Q1 Denim 200,000

[0051] Table 1

[0052] Furthermore, allocating the current planning data based on the performance benchmarks corresponding to multiple suppliers respectively includes:

[0053] Based on the performance benchmarks, determining the product supply volumes corresponding to multiple suppliers respectively, and comparing the product planned volume corresponding to the current planning data with the sum of the corresponding multiple product supply volumes. If the product planned volume is greater than the sum of the multiple product supply volumes, then allocate orders to multiple suppliers respectively according to the multiple product supply volumes.

[0054] For example, in the first quarter of 2022, the brand plans to produce 100,000 knitted items. The supply volume corresponding to the performance benchmark of Supplier A is 20,000 items, the supply volume corresponding to the performance benchmark of Supplier B is 20,000 items, and the supply volume corresponding to the performance benchmark of Supplier C is 30,000 items. Among them, the sum of the supply volumes corresponding to Supplier A, Supplier B, and Supplier C is 20,000 + 20,000 + 30,000 = 70,000 items. At this time, the planned quantity of products in the brand's planning data is 100,000 items, which is greater than the sum of the supply volumes of each supplier, 70,000 items. Therefore, the order is directly allocated according to the supply volume corresponding to the performance benchmark of each supplier, that is, 20,000 orders are allocated to Supplier A, 20,000 orders are allocated to Supplier B, and 20,000 orders are allocated to Supplier C.

[0055] In one embodiment, if the planned quantity of products is less than, equal to, or greater than the sum of the supply volumes of multiple products, based on the performance benchmark, the current planning data is used to allocate orders to multiple suppliers, including:

[0056] First, based on the performance benchmark, determine the allocation priorities of multiple suppliers. The allocation priorities include 5 grade groups, namely the strategic group, the core group, the cultivation group, the qualified group, and the observation group. Each grade group contains four levels: A, B, C, and D. For example, the strategic group includes Strategic A, Strategic B, Strategic C, and Strategic D, the core group includes Core A, Core B, Core C, and Core D, the cultivation group includes Cultivation A, Cultivation B, Cultivation C, and Cultivation D, the qualified group includes Qualified A, Qualified B, Qualified C, and Qualified D, and the observation group includes Observation A, Observation B, Observation C, and Observation D. For each grade group, Level A > Level B > Level C > Level D.

[0057] Then, based on the assigned priorities, determine the assignment order and assignment satisfaction corresponding to each of the multiple suppliers, where the assignment satisfaction represents the ratio between the actual assigned quantity and the product supply quantity corresponding to the performance benchmark. Specifically, based on the assigned priorities, determine the assignment order corresponding to each of the multiple suppliers; based on the current market supply and demand situation and the assigned priorities, determine the assignment satisfaction corresponding to each of the multiple suppliers. For example, when the assigned priorities of the multiple suppliers include the strategic group, the core group, the cultivation group, the qualified group, and the observation group, the determined assignment order is: strategic group → core group → cultivation group → qualified group → observation group. If it is further determined that the current market supply and demand situation represents the peak season, the assignment satisfaction corresponding to the strategic group, the core group, the cultivation group, the qualified group, and the observation group can be determined as 100%, 90%, 80%, 70%, and 60% respectively; if it is determined that the current market supply and demand situation represents the off-season, the assignment satisfaction corresponding to the strategic group, the core group, the cultivation group, the qualified group, and the observation group can be determined as 100%, 80%, 60%, 50%, and 40% respectively, or other values, which are adjusted according to the actual situation. Among them, regardless of whether the current market supply and demand situation represents the off-season or the peak season, the assignment satisfaction of the strategic group is set to 100%.

[0058] Finally, based on the assignment order and the assignment satisfaction, perform order assignment for the multiple suppliers, which specifically includes: based on the assignment order, determine the currently assigned supplier; for the currently assigned supplier, perform order assignment according to the product supply quantity corresponding to the product of the assignment satisfaction and the corresponding performance benchmark; determine whether there are unassigned orders in the current planning data; if so, based on the assignment order and the assignment satisfaction, perform order assignment for the next supplier until the current planning data is completely assigned.

[0059] Next, a specific example is used to illustrate the order assignment method.

[0060] (1) The current planning data is as follows:

[0061] In 2022, Q1 quarter, knitted, 200,000 pieces 0; in 2022, Q1 quarter, woolen knitted, 300,000 pieces.

[0062] (2) The supplier performance benchmarks are as follows:

[0063] In 2022, Q1 quarter, knitting, Supplier No. 1, 10,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 2, 10,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 3, 10,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 4, 10,000 pieces... In 2022, Q1 quarter, knitting, Supplier No. 20, 10,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 21, 5,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 22, 5,000 pieces; In 2022, Q1 quarter, knitting, Supplier No. 23, 0; In 2022, Q1 quarter, wool knitting, Supplier No. 1, 10,000 pieces; In 2022, Q1 quarter, wool knitting, Supplier No. 2, 10,000 pieces; In 2022, Q1 quarter, wool knitting, Supplier No. 3, 10,000 pieces; In 2022, Q1 quarter, wool knitting, Supplier No. 4, 10,000 pieces... In 2022, Q1 quarter, wool knitting, Supplier No. 20, 10,000 pieces.

[0064] (3) The allocation priority groups of suppliers are as follows:

[0065] Supplier No. 1: Strategic; Supplier No. 2: Strategic; Supplier No. 3: Strategic; Supplier No. 4: Core A; Supplier No. 5: Core A; Supplier No. 6: Core A; Supplier No. 7: Core B; Supplier No. 8: Core B; Supplier No. 9: Core B; Supplier No. 10: Core C; Supplier No. 11: Core C; Supplier No. 12: Core C; Supplier No. 13: Core D; Supplier No. 14: Core D; Supplier No. 15: Core D; Supplier No. 16: Cultivation A; Supplier No. 17: Cultivation A; Supplier No. 18: Cultivation A; Supplier No. 19: Cultivation B; Supplier No. 20: Cultivation B; Supplier No. 21: Qualified A; Supplier No. 22: Qualified B; Supplier No. 23: Qualified C.

[0066] (4) Current market supply and demand situation: Peak season. Then, under the peak season rules, the allocation satisfaction degrees corresponding to each allocation priority are shown in the following table:

[0067]

[0068]

[0069] Table 2

[0070] (5) Specific allocation steps.

[0071] Step1: Use 100% of the current planned quantity to meet 100% of the strategic suppliers.

[0072] At this time, in 2022, Q1 quarter, knitting, 100% of the planned quantity is 20W * 100% = 20W;

[0073] For strategic suppliers, if the production capacity planning reaches 100% of the target, the corresponding suppliers that can be allocated are suppliers No. 1 - 20. Among them, suppliers No. 1 - 3 are strategic suppliers, and the total production capacity planning target is 30,000. Using 200,000 - 30,000 = 170,000. Therefore, suppliers No. 1, No. 2, and No. 3 each received an order allocation of 10,000 in knitting.

[0074] At this time, the remaining product planned quantity corresponding to the planning data is 170,000.

[0075] Step2: Use 80% of the current planning quantity to meet 80% of the core supplier pool. Among them, the core supplier pool: Core A > Core B > Cultivate A > Core C > Cultivate B.

[0076] For Core A, 80% of the current planning quantity = 200,000 * 80% = 160,000. Among them, subtract the 30,000 allocated to strategic suppliers in Step1, so there is still 130,000 left. Core A has three suppliers, namely suppliers No. 4, No. 5, and No. 6, and their production capacity planning has been completed at 80%, then (1 + 1 + 1) * 80% = 24,000. 130,000 > 24,000, so allocate the planning quantity to Core A to make it reach 80%; suppliers No. 4, No. 5, and No. 6 each received an order allocation of 8,000 in knitting.

[0077] At this time, the remaining planning quantity is 106,000.

[0078] For Core B, 80% of the current planning quantity = 200,000 * 80% = 160,000. Among them, subtract the 30,000 allocated to strategic suppliers in Step1 and the 24,000 of Core A, and there is still 106,000 left. Core B has three suppliers, namely suppliers No. 7, No. 8, and No. 9, and their production capacity planning has been completed at 80%, then (1 + 1 + 1) * 80% = 24,000. 104,000 > 24,000, so allocate the planning quantity to Core B to make it reach 80%, and suppliers No. 7, No. 8, and No. 9 each received an order allocation of 8,000 in knitting.

[0079] At this time, the remaining planning quantity is 104,000 - 24,000 = 80,000.

[0080] For Cultivate A, 80% of the current planning quantity = 200,000 * 80% = 160,000. Among them, subtract the 30,000 allocated to strategic suppliers in Step1, the 24,000 of Core A, and the 24,000 of Core B, and there is still 80,000 left. Cultivate A has three suppliers, namely suppliers No. 16, No. 17, and No. 18, and their production capacity planning has been completed at 80%, then (1 + 1 + 1) * 80% = 24,000. 80,000 > 24,000, so allocate the planning quantity to Cultivate A to make it reach 80%, and suppliers No. 16, No. 17, and No. 18 each received an order allocation of 8,000 in knitting.

[0081] At this time, the remaining planning quantity is 80,000 - 24,000 = 56,000.

[0082] Similarly, the tenth, eleventh, and twelfth suppliers of Core C can be calculated to receive order allocations of 8,000 each, with 32,000 remaining; the nineteenth and twentieth suppliers of Cultivated B receive order allocations of 8,000 each, with 16,000 remaining.

[0083] Finally, there is still a planned volume of 16,000 remaining. All suppliers of Core A, Core B, Cultivated A, Cultivated C, and Cultivated B have received an indicator of 8,000.

[0084] Step3: Use 100% of the current planned volume to satisfy 60% of the qualified supplier pool. Among them, the qualified supplier pool: Qualified A > Qualified B > Cultivated C > Qualified C

[0085] For Qualified A, 100% of the current planned volume = 200,000 - the order allocation in Step1 - the order allocation in Step2 = 200,000 - 30,000 - 112,000 = 58,000. There is one supplier, the twenty-first supplier, for Qualified A, and its production capacity planning completion rate is 60%, so the allocation should be: 10,000 * 60% = 6,000. Since 58,000 > 6,000, the twenty-first supplier receives an order allocation of 6,000, with 52,000 remaining.

[0086] For Qualified B, with 52,000 remaining in the current planned volume, there is one supplier, the twenty-second supplier, for Qualified B, and its production capacity planning completion rate is 60%, so the allocation should be: 10,000 * 60% = 6,000. Among them, since 52,000 > 6,000, the twenty-second supplier receives an order allocation of 8,000, with 46,000 remaining.

[0087] For Cultivated C, there is no cultivation currently.

[0088] For Qualified C, although there is Qualified C currently, since it was not the corresponding matching supplier in the same quarter last year, it is not allowed to be allocated. At this time, there is still 46,000 remaining.

[0089] Step4: Use 100% of the current planned volume to satisfy 100% of the core supplier pool. Among them, the core supplier pool: Core A > Core B > Cultivated A > Core C > Cultivated B.

[0090] For Core A, with a current planned volume of 46,000, there are three suppliers for Core A, namely the fourth, fifth, and sixth suppliers, and their production capacity planning completion rate is 80%, so (1 + 1 + 1) * 80% = 24,000; currently, the production capacity planning is to make it reach 100%, and it is still short of (1 + 1 + 1) * 20% = 6,000. Since 46,000 > 6,000, the planned volume is allocated to Core A to make it reach 100%. Therefore, the fourth, fifth, and sixth suppliers each receive an additional order allocation of 2,000 in knitting, and the planned volume still remains 40,000.

[0091] Core B, with a current planned volume of 40,000. There are three suppliers for Core B, namely Supplier No. 7, No. 8, and No. 9. Their production capacity planning has been completed by 80%, so (1 + 1 + 1) * 80% = 24,000; currently, the production capacity planning is to make it reach 100%, and the shortfall is (1 + 1 + 1) * 20% = 6,000. Since 40,000 > 6,000, the planned volume is allocated to Core B to make it reach 100%; therefore, Supplier No. 7, No. 8, and No. 9 each receive an additional order allocation of 2,000 in knitting. At this time, the remaining planned volume is 34,000.

[0092] Cultivation A, with a current planned volume of 34,000. There are three suppliers for Cultivation A, namely Supplier No. 16, No. 17, and No. 18. Their production capacity planning has been completed by 80%, so (1 + 1 + 1) * 80% = 24,000; currently, the production capacity planning is to make it reach 100%, and the shortfall is (1 + 1 + 1) * 20% = 6,000. Since 34,000 > 6,000, the planned volume is allocated to Cultivation A to make it reach 100%, so Supplier No. 16, No. 17, and No. 18 each receive an additional order allocation of 2,000 in knitting. At this time, the remaining planned volume is 28,000.

[0093] Core C, with a current planned volume of 28,000. There are three suppliers for Core C, namely Supplier No. 10, No. 11, and No. 12. Their production capacity planning has been completed by 80%, so (1 + 1 + 1) * 80% = 24,000; currently, the production capacity planning is to make it reach 100%, and the shortfall is (1 + 1 + 1) * 20% = 6,000. Since 28,000 > 6,000, the planned volume is allocated to Core C to make it reach 100%, so Supplier No. 16, No. 17, and No. 18 each receive an additional order allocation of 2,000 in knitting. At this time, the remaining planned volume is 28,000.

[0094] If the planned volume is not enough to be allocated to Core C at this time, assuming that although there is a planned volume of 28,000, but a target of 30,000 needs to be allocated, then the 28,000 is evenly allocated to all Core C suppliers, and each of the three Core C suppliers gets an order allocation of 28,000 / 3.

[0095] The subsequent rules are the same above until all the planned data are allocated or there are insufficient suppliers at the end.

[0096] Before performing the rule calculation for each step, a judgment needs to be made. In the previous step of allocation, whether the corresponding target value has been reached. If it has been reached, then it is normally allocated in the next step of allocation. If it has not been reached, then it needs to be allocated based on the current planned volume used and the previous allocation result.

[0097] For example, for the first allocation, 60% of the planned quantity is used to achieve an 80% achievement rate; the actual allocation result is that 60% of the planned quantity is used to achieve a 70% achievement rate; for the second time, 80% of the planned quantity is allocated to achieve a 90% achievement rate; then at this time of allocation, it is necessary to calculate the total amount of the difference at this time, which is 90% - 70% = 20%, and then allocate 20% of the currently remaining planned quantity to see if it is satisfied. If it is satisfied, then allocate; if not, then use proportional average allocation; at this time, count the suppliers allocated with 200,000 in the knitting category and the specific index numbers; type of fabric + supplier + number of pieces; then, for the logic of the remaining all variety sub - pools, allocate in the same way; type of fabric + supplier + number of pieces; finally, from the perspective of the supplier, conduct statistics on how many allocated indicators the supplier finally obtains; supplier + indicator (number of pieces); at this time, the result of the total production capacity planning allocation is obtained, supplier + indicator (number of pieces).

[0098] Through the above - mentioned method, the order allocation to each supplier is completed, which can accurately evaluate the actual supply capacity and performance of the suppliers, so as to achieve the reasonable allocation of resources and avoid the problems of resource waste and imbalance between supply and demand caused by the traditional static allocation method. Secondly, the dynamic allocation mechanism can quickly respond to changes in market demand, shorten the order processing time, and improve the overall response speed of the supply chain. This data - driven decision - making support not only reduces the deviation of subjective judgment, but also provides the brand side with more comprehensive market insights through multi - dimensional data analysis. In addition, through the setting of performance benchmarks, the scheme encourages suppliers to improve their own capabilities, promotes fair competition, reduces supplier dissatisfaction or withdrawal caused by unfair allocation, thereby enhancing the stability and sustainability of the supply chain. Reasonable order allocation also reduces the brand side's dependence on a single supplier and further disperses the supply chain risks.

[0099] Based on the same inventive concept, the embodiment of the present application also provides an order allocation device. As Figure 3 shown, it is a schematic structural diagram of the order allocation device 300, which may include:

[0100] An acquisition module 301, configured to acquire historical order data of multiple suppliers, where the historical order data includes time information, product information, and channel information;

[0101] A determination module 302, configured to determine the performance benchmarks respectively corresponding to multiple suppliers based on the historical order data; where the performance benchmark includes the product supply quantity, which represents the supply capacity of the supplier;

[0102] An allocation module 303, configured to allocate the current planned data to multiple suppliers based on the performance benchmarks, and the planned data is determined based on the multi - dimensional order data of the multiple suppliers in the previous allocation.

[0103] In a possible embodiment, the determination module 302 is configured to: statistically analyze the historical order data based on supplier information, time information, product information, and channel information to obtain a statistical result; statistically analyze the statistical result based on supplier information, time information, and product information to obtain the product quantities produced by multiple suppliers in each time period; perform a weighting process on the product quantities corresponding to multiple suppliers respectively to obtain the performance benchmarks corresponding to multiple suppliers respectively.

[0104] In a possible embodiment, the apparatus further includes: a summarization module, configured to obtain the multi-dimensional order data allocated to multiple suppliers last time, where the multi-dimensional order data includes time information, channel information, product information, batch information, and regional information; summarize the multi-dimensional order data according to the product dimension to obtain the current planning data.

[0105] In a possible embodiment, the allocation module 303 is configured to: determine the product supply quantities corresponding to multiple suppliers respectively based on the performance benchmarks; compare the product planned quantity corresponding to the current planning data with the sum of the corresponding multiple product supply quantities; if the product planned quantity is greater than the sum of the multiple product supply quantities, allocate orders to multiple suppliers respectively according to the multiple product supply quantities.

[0106] In a possible embodiment, the allocation module 303 is configured to: determine the allocation priorities of multiple suppliers respectively based on the performance benchmarks; determine the allocation order and allocation satisfaction degrees corresponding to multiple suppliers respectively based on the allocation priorities; where the allocation satisfaction degree represents the ratio between the actual allocation quantity and the product supply quantity corresponding to the performance benchmark; allocate orders to multiple suppliers based on the allocation order and allocation satisfaction degree.

[0107] In a possible embodiment, the allocation module 303 is configured to: determine the allocation order corresponding to multiple suppliers respectively based on the allocation priorities; determine the allocation satisfaction degrees corresponding to multiple suppliers respectively based on the current market supply and demand situation and the allocation priorities.

[0108] In a possible embodiment, the allocation module 303 is configured to: determine the currently allocated supplier based on the allocation order; allocate orders to the currently allocated supplier according to the product supply quantity corresponding to the product of the allocation satisfaction degree and the corresponding performance benchmark; determine whether there are unallocated orders in the current planning data; if so, allocate orders to the next supplier based on the allocation order and allocation satisfaction degree.

[0109] In some possible embodiments, the order allocation device according to the present application may at least include a processor and a memory. Among them, the memory stores program code, and when the program code is executed by the processor, the processor is caused to execute the steps in the order allocation method according to various exemplary embodiments of the present application described in this specification. For example, the processor may execute as Figure 2 shown in the steps.

[0110] Based on the same inventive concept, an electronic device is further provided in an embodiment of the present application. The electronic device may implement the functions of the foregoing order allocation method device. Refer to Figure 4 , the electronic device includes:

[0111] At least one processor 401, and a memory 402 connected to at least one processor 401. In the embodiment of the present application, the specific connection medium between the processor 401 and the memory 402 is not limited. Figure 4 In Figure 4 it is taken as an example that the processor 401 and the memory 402 are connected through a bus 400. The bus 400 is represented by a thick line in Figure 4 . The connection manners between other components are only for illustrative purposes and are not to be construed as limiting. The bus 400 may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation,

[0112] in Figure 3 it is only represented by a thick line, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 401 may also be referred to as a controller, and the name is not limited.

[0113] In the embodiment of the present application, the memory 402 stores instructions executable by at least one processor 401. By executing the instructions stored in the memory 402, at least one processor 401 may execute the order allocation method discussed above. The processor 401 may implement

[0114] In a possible design, the processor 401 may include one or more processing units. The processor 401 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communications. It can be understood that the above-mentioned modem processor may not be integrated into the processor 401 either. In some embodiments, the processor 401 and the memory 402 may be implemented on the same chip, and in some embodiments, they may also be separately implemented on independent chips.

[0115] The processor 401 may be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the order allocation method disclosed in combination with the embodiments of the present application may be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0116] As a non-volatile computer-readable storage medium, the memory 402 can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The memory 402 may include at least one type of storage medium, for example, it may include flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (RAM), a static random access memory (SRAM), a programmable read-only memory (PROM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 402 is any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 402 in the embodiments of the present application may also be a circuit or any other device capable of implementing a storage function, for storing program instructions and / or data.

[0117] By programming the design of the processor 401, the code corresponding to the order allocation method introduced in the foregoing embodiments can be solidified into the chip, so that the chip can execute when running Figure 2Steps of the order allocation method of the illustrated embodiment. How to design and program the processor 401 is a well-known technique to those skilled in the art and will not be elaborated here.

[0118] Based on the same inventive concept, an embodiment of the present application also provides a storage medium storing computer instructions, which, when running on a computer, cause the computer to execute the order allocation method discussed above.

[0119] In some possible implementation manners, each aspect of the order allocation method provided by the present application can also be implemented in the form of a program product, which includes program code. When the program product runs on a device, the program code is used to cause the control device to execute the steps in the order allocation method according to various exemplary embodiments of the present application described above in this specification.

[0120] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0122] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the steps specified in one process or a plurality of processes and / or blocks Figure 1 one process or a plurality of processes and / or blocks Figure 1 in one block or a plurality of blocks.

[0124] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. An order allocation method, characterized in that, Including: Obtain historical order data of multiple suppliers, where the historical order data includes time information, product information, and channel information; Based on the historical order data, determine the performance benchmarks corresponding to the multiple suppliers respectively; wherein, the performance benchmark includes the product supply volume, which represents the supply capacity of the supplier; Based on the performance benchmarks, allocate the current planning data to the multiple suppliers, and the planning data is determined based on the multi-dimensional order data allocated to the multiple suppliers last time.

2. The method according to claim 1, wherein The determining the performance benchmarks corresponding to the multiple suppliers respectively based on the historical order data includes: Statistically analyze the historical order data based on supplier information, time information, product information, and channel information to obtain a statistical result; Statistically analyze the statistical result based on the supplier information, the time information, and the product information to obtain the product quantities produced by the multiple suppliers in each time period respectively; Perform weighted processing on the product quantities corresponding to the multiple suppliers respectively to obtain the performance benchmarks corresponding to the multiple suppliers respectively.

3. The method according to claim 1, wherein Before allocating the current planning data to the multiple suppliers based on the performance benchmarks, it further includes: Obtain the multi-dimensional order data allocated to the multiple suppliers last time, where the multi-dimensional order data includes time information, channel information, product information, batch information, and regional information; Summarize the multi-dimensional order data according to the product dimension to obtain the current planning data.

4. The method according to claim 1, wherein The allocating the current planning data to the multiple suppliers based on the performance benchmarks includes: Based on the performance benchmarks, determine the product supply volumes corresponding to the multiple suppliers respectively; Compare the product planned volume corresponding to the current planning data with the sum of the corresponding multiple product supply volumes; If the product planned volume is greater than the sum of the multiple product supply volumes, allocate orders to the multiple suppliers respectively according to the multiple product supply volumes.

5. The method according to claim 1, wherein The allocating the current planning data to the multiple suppliers based on the performance benchmarks includes: Based on the performance benchmarks, determine the allocation priorities of the multiple suppliers; Based on the allocation priorities, determine the allocation order and allocation satisfaction degrees corresponding to the multiple suppliers respectively; wherein, the allocation satisfaction degree represents the ratio between the actual allocation quantity and the product supply volume corresponding to the performance benchmark; Allocate orders to the multiple suppliers based on the allocation order and the allocation satisfaction degree.

6. The method according to claim 5, wherein The determining the allocation order and allocation satisfaction degrees corresponding to the multiple suppliers respectively based on the allocation priorities includes: Based on the allocation priorities, determine the allocation order corresponding to the multiple suppliers respectively; Based on the current market supply and demand situation and the allocation priorities, determine the allocation satisfaction degrees corresponding to the multiple suppliers respectively.

7. The method according to claim 5, wherein The allocating orders to the multiple suppliers based on the allocation order and the allocation satisfaction degree includes: Based on the allocation order, determine the currently allocated supplier; For the current assigned supplier, perform order allocation according to the product supply quantity corresponding to the product supply quantity corresponding to the allocation satisfaction degree. Determine whether there is an unallocated order in the current planning data. If so, based on the allocation order and the allocation satisfaction degree, perform order allocation for the next supplier.

8. An order allocation device, characterized in that, Includes: An acquisition module for acquiring historical order data of multiple suppliers, the historical order data including time information, product information, and channel information. A determination module for determining the performance benchmarks corresponding to the multiple suppliers respectively based on the historical order data; wherein the performance benchmark includes the product supply quantity, which represents the supply capacity of the supplier. An allocation module for performing order allocation of the current planning data to the multiple suppliers based on the performance benchmark, and the planning data is determined based on the multi-dimensional order data allocated to the multiple suppliers last time.

9. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor executes any one of the methods described in claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Includes program code, and when the storage medium runs on an electronic device, the program code is used to cause the electronic device to execute any one of the methods described in claims 1 to 7.

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