Supplier qualification comprehensive evaluation system and method based on big data

Abstract

The invention relates to the technical field of supplier qualification evaluation, and discloses a supplier qualification comprehensive evaluation system and method based on big data, and the evaluation method comprises the following steps: S1, obtaining the basic information data of suppliers; s2, obtaining trial information data of a supplier; s3, acquiring weather information data; s4, analyzing the basic information data through an analysis module to obtain a basic evaluation index of the supplier; analyzing the trial information data and the weather information data in the trial period through an analysis module to obtain a comprehensive trial evaluation index of the supplier; and finally, analyzing the basic evaluation index and the comprehensive trial evaluation index to obtain a supplier comprehensive evaluation index. The suppliers are graded according to the comprehensive evaluation indexes of the suppliers; the evaluation result of the supplier can be more intuitively known, whether cooperation can be performed can be directly judged according to the rating result, interference of human subjective factors is reduced, and the evaluation result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of supplier qualification evaluation, and in particular to a supplier qualification comprehensive evaluation system and method based on big data. Background Art

[0002] Suppliers are companies or individuals that supply various required resources to the enterprise. These resources include but are not limited to raw materials, equipment, energy, and labor. When selecting suppliers, the enterprise procurement department will evaluate the qualifications of many suppliers in order to achieve the goal of selecting the best for cooperation.

[0003] The traditional method of evaluating supplier qualifications is to obtain basic information about suppliers through market surveys. The company's procurement department manually collects, organizes, and compares and analyzes the basic information to ultimately select better suppliers.

[0004] However, it is difficult to intuitively see the qualifications of suppliers through the data, and the manual collection, collation and analysis contain certain subjective factors. There may be problems with supplier information opacity, which is not conducive to unified management of suppliers. Summary of the invention

[0005] The purpose of the present invention is to provide a supplier qualification comprehensive evaluation system and method based on big data to solve the following technical problems: How to evaluate supplier qualifications.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A comprehensive evaluation method for supplier qualifications based on big data includes the following steps: S1: Obtain basic information data of suppliers through the market information module; S2: Obtain the trial information data of the supplier through the trial data module; S3: Obtain weather information data through the weather data module; S4: Analyze the basic information data through the analysis module to obtain the basic evaluation index of the supplier; then analyze the trial information data and weather information data during the trial period through the analysis module to obtain the supplier's comprehensive trial evaluation index; finally, analyze the basic evaluation index and the comprehensive trial evaluation index to obtain the supplier's comprehensive evaluation index; and rate the supplier based on the supplier's comprehensive evaluation index.

[0007] As a further solution of the present invention: by formula: ; Calculate the supplier's basic evaluation index ; in, The length of time the supplier has been in business, The quantity of the required product type; The quantity of the required product type that the supplier can provide; To research the number of customers of a supplier, ; For the Customer satisfaction; Preset constants for the first basis; Preset constants for the second basis; Preset constants for the third basis; is the first basic weight coefficient; is the second basic weight coefficient; is the third basic weight coefficient.

[0008] As a further solution of the present invention: by formula: ; Calculate the trial evaluation index for the day ; in, is the first judgment function, when hour, ;when hour, ; The total quantity of the product type of the supplier during the trial period. ; For the The actual supply of the product type; For the The actual daily demand for the product type; For the The basic preset tolerance values ​​for the types of goods; For the The commodity error adjustment coefficient for the commodity type on that day; The actual delivery time on that day; The preset delivery time for the day; It is the allowable error value of the basic preset time; is the time error adjustment coefficient for the day; For the The quality standards of the product types; is the preset target achievement rate; To serve as the basic trial assessment index; Preset constants for the first trial; Preset constants for the second trial; Preset constants for the third trial; is the first trial weight coefficient; is the second trial weight coefficient; is the weight coefficient of the third trial.

[0009] As a further solution of the present invention: by formula: ; Calculate the The error adjustment coefficient of the goods for the day ; in, is the second judgment function, when hour, ;when hour, ; For the The length of time between the order placement time of the same day and the preset deadline for the type of goods; is the time coefficient; Preset constants for the fourth trial.

[0010] As a further solution of the present invention: the trial evaluation index of the day is With the first preset value For comparison: when If the trial supplier on that day fully meets the standards, the trial will continue; when If the trial on that day is slightly below the standard, the trial will continue; when , the trial on that day seriously failed to meet the standards and the trial was stopped.

[0011] As a further solution of the present invention: by formula: ; Calculating the comprehensive trial evaluation index ; in, is the third judgment function, when hour, ;when hour, ; is the total number of days of actual trial. ; The number of days for the trial is preset; The number of days to reach the target; For the day trial evaluation index; is the first comprehensive preset constant; Preset constant for the second synthesis; is the first comprehensive weight coefficient; is the second comprehensive weight coefficient.

[0012] As a further solution of the present invention: by formula: ; Calculate the supplier comprehensive evaluation index ; Supplier comprehensive evaluation index With the second preset value For comparison: when When, the supplier is level three; when When the supplier is level 2; when When the supplier is first-level.

[0013] A supplier qualification comprehensive evaluation system based on big data, including: Market information module, used to obtain basic information data of suppliers; Trial data module, used to obtain trial information data of suppliers; Weather data module, used to obtain weather information data; The analysis module is used to analyze the basic information data to obtain the basic evaluation index of the supplier; the analysis module is then used to analyze the trial information data and weather information data during the trial period to obtain the supplier's comprehensive trial evaluation index; finally, the basic evaluation index and the comprehensive trial evaluation index are analyzed to obtain the supplier's comprehensive evaluation index; and the supplier is rated based on the supplier's comprehensive evaluation index.

[0014] Beneficial effects of the present invention: The present invention first obtains the basic information data of the supplier through the market information module; then obtains the trial information data of the supplier through the trial data module; then obtains the weather information data through the weather data module; finally, the basic information data is analyzed through the analysis module to obtain the basic evaluation index of the supplier; then, the trial information data and weather information data of the trial period are analyzed through the analysis module to obtain the comprehensive trial evaluation index of the supplier; finally, the basic evaluation index and the comprehensive trial evaluation index are analyzed to obtain the comprehensive evaluation index of the supplier; and the supplier is rated according to the comprehensive evaluation index of the supplier; the evaluation result of the supplier is more intuitively understood, and whether cooperation is possible can be directly judged according to the rating result, thereby reducing the interference of human subjective factors and making the evaluation result more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 A method flow chart of an embodiment of the present invention; Figure 2A system module framework diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, in one embodiment, a method for comprehensive evaluation of supplier qualifications based on big data is provided, comprising the following steps: S1: Obtain basic information data of suppliers through the market information module; S2: Obtain the trial information data of the supplier through the trial data module; S3: Obtain weather information data through the weather data module; S4: Analyze the basic information data through the analysis module to obtain the basic evaluation index of the supplier; then analyze the trial information data and weather information data of the trial period through the analysis module to obtain the comprehensive trial evaluation index of the supplier; finally, analyze the basic evaluation index and the comprehensive trial evaluation index to obtain the comprehensive evaluation index of the supplier; and rate the supplier according to the comprehensive evaluation index of the supplier; Through the above technical scheme, this embodiment first obtains the basic information data of the supplier through the market information module; then obtains the trial information data of the supplier through the trial data module; then obtains the weather information data through the weather data module; finally, the basic information data is analyzed through the analysis module to obtain the basic evaluation index of the supplier; then the trial information data and weather information data of the trial period are analyzed through the analysis module to obtain the comprehensive trial evaluation index of the supplier; finally, the basic evaluation index and the comprehensive trial evaluation index are analyzed to obtain the comprehensive evaluation index of the supplier; and the supplier is rated according to the comprehensive evaluation index of the supplier; the evaluation results of the supplier can be understood more intuitively, and whether cooperation is possible can be directly judged according to the rating results, which reduces the interference of human subjective factors and makes the evaluation results more accurate.

[0019] As an implementation mode of the present invention, the basic information data includes operating time, product types and customer satisfaction; the trial information data includes the supply quantity of each product type, the order time of each product type, the delivery time of the product and the quality standard of each product type.

[0020] As an implementation mode of the present invention, by formula: ; Calculate the supplier's basic evaluation index ; in, The length of time the supplier has been in business, The quantity of the required product type; The quantity of the required product type that the supplier can provide; To research the number of customers of a supplier, ; For the Customer satisfaction; Preset constants for the first basis; Preset constants for the second basis; Preset constants for the third basis; is the first basic weight coefficient; is the second basic weight coefficient; is the third basic weight coefficient; Through the above technical solution, the operating time of the supplier in this embodiment The larger the value, the more reliable the supplier is. Therefore, the basic evaluation index of the supplier is The bigger; It is the ratio of the number of goods types that suppliers can provide in the required goods type to the number of required goods types. The larger the ratio of the number of goods types that suppliers can provide in the required goods type to the number of required goods types, the more goods types the supplier can provide. Therefore, the basic evaluation index of the supplier is The bigger; To investigate the average satisfaction of the suppliers' customers, the average satisfaction The larger the value, the better the service the supplier can provide. Therefore, the basic evaluation index of the supplier is The bigger; It should be noted that the first basic preset constant , the second basic preset constant , the third basic preset constant , the first basic weight coefficient , the second basic weight coefficient and the third basic weight coefficient It is a preset value obtained based on experience and will not be described in detail here.

[0021] As an implementation mode of the present invention, by formula: ; Calculate the trial evaluation index for the day ; in, is the first judgment function, when hour, ;when hour, ; The total quantity of the product type of the supplier during the trial period. ; For the The actual supply of the product type; For the The actual daily demand for the product type; For the The basic preset tolerance values ​​for the types of goods; For the The commodity error adjustment coefficient for the commodity type on that day; The actual delivery time on that day; The preset delivery time for the day; It is the allowable error value of the basic preset time; is the time error adjustment coefficient of the day; For the The quality standards of the product types; is the preset target achievement rate; To serve as the basic trial assessment index; Preset constants for the first trial; Preset constants for the second trial; Preset constants for the third trial; is the first trial weight coefficient; is the second trial weight coefficient; is the third trial weight coefficient; Through the above technical solution, this embodiment For the The absolute value of the difference between the actual supply of a product type and the actual demand on that day; For the The preset tolerance value for the day for each type of product; For the The absolute value of the difference between the actual supply of the commodity type and the actual demand on that day is The difference between the preset tolerance values ​​of the commodity types on the day; in the formula In the first judgment function In Reference ;when , explain The absolute value of the difference between the actual supply and the actual demand for the day for the commodity type is The actual supply of the product type is within the preset allowable error range on that day, which means that the actual supply of the supplier matches the actual demand on that day. ;when , explain The absolute value of the difference between the actual supply of the commodity type and the actual demand on that day exceeds The preset tolerance value for the day for the type of goods, which means that the actual supply of the supplier does not match the actual demand on the day. ; and The absolute value of the difference between the actual supply of the commodity type and the actual demand on that day is The larger the difference between the preset tolerance values ​​of the same day for the same product type, the worse the supplier's service level is. The smaller; for The absolute value of the difference between the actual supply and the actual demand of the commodity type for which the actual supply does not match the actual demand on the day is equal to the absolute value of the difference between the actual supply and the actual demand on the day of the commodity type. The accumulated value of the difference between the preset tolerance values ​​of the commodity types on that day; The absolute value of the difference between the actual supply and the actual demand of the commodity type for which the actual supply does not match the actual demand on the day is equal to the absolute value of the difference between the actual supply and the actual demand on the day of the commodity type. The cumulative value of the difference between the preset tolerance values ​​of the commodity type on the day The larger the value, the worse the service level of the supplier. Therefore, the trial evaluation index of the day is The smaller; The absolute value of the difference between the actual delivery time of the day and the preset delivery time of the day; The allowable error value for the preset time of the day; The absolute value of the difference between the actual delivery time of the day and the preset delivery time of the day and the allowable error value of the preset time of the day; in the formula In the first judgment function In Reference ;when , it means that the absolute value of the difference between the actual delivery time and the preset delivery time of the day is within the allowable error range of the preset time of the day, so it means that the actual delivery time of the supplier matches the preset delivery time of the day. ;when , it means that the absolute value of the difference between the actual delivery time and the preset delivery time of the day exceeds the allowable error value of the preset time of the day, so it means that the actual delivery time of the supplier does not match the preset delivery time of the day. ; The greater the difference between the absolute value of the difference between the actual delivery time of the day and the preset delivery time of the day and the allowable error value of the preset time of the day, the worse the service level of the supplier, and therefore the trial evaluation index of the day The smaller; For the The compliance rate of the product types on the day; The preset target achievement rate and The difference in the compliance rate of the two types of goods on the same day; in the formula In the first judgment function In Reference ;when , explain The compliance rate of the product type on that day is not lower than the preset compliance rate, indicating that the supplier's product quality meets the requirements. ;when , explain The compliance rate of the product type on that day is lower than the preset compliance rate; this indicates that the supplier's product quality is poor. ; for The preset compliance rate of quality price difference in the first product type and the The cumulative value of the difference in the compliance rate of the commodity types on the same day; The preset compliance rate of quality price difference in the first product type and the The cumulative value of the difference in the compliance rate of the commodity type on the day The larger the value, the worse the quality of the supplier's goods. Therefore, the trial evaluation index of the day is The smaller the time error adjustment coefficient of the day According to the weather settings, each type of weather corresponds to an adjustment coefficient ; The corresponding adjustment coefficient of each weather is the default value; It should be noted that Basic preset tolerance values ​​for the product types , Basic preset time allowable error value , preset target achievement rate , Basic Trial Evaluation Index , First try preset constants , Second trial preset constant 、The third trial preset constant , first trial weight coefficient , Second trial weight coefficient and the third trial weight coefficient It is a preset value obtained based on experience and will not be described in detail here.

[0022] As an implementation mode of the present invention, by formula: ; Calculate the The error adjustment coefficient of the goods for the day ; in, is the second judgment function, when hour, ;when hour, ; For the The length of time between the order placement time of the same day and the preset deadline for the type of goods; is the time coefficient; Preset constants for the fourth trial; Through the above technical solution, the time coefficient of this embodiment Determined based on the order time of the day and the preset deadline. If the order time of the day is earlier than the preset deadline, ; ; In the formula In the second judgment function In Reference ;when hour, , ; Orders placed earlier on the same day The default tolerance for this commodity type is The basic preset tolerance value for the type of goods; when the order time on the same day is later than the preset deadline, , , , ; If the order time is later than the preset deadline, the duration The longer, the The larger the preset tolerance value for a particular commodity type is on that day; It should be noted that the fourth trial preset constant It is a preset value obtained based on experience and will not be described in detail here.

[0023] As an embodiment of the present invention, the trial evaluation index of the day is With the first preset value For comparison: when If the trial supplier on that day fully meets the standards, the trial will continue; when If the trial on that day is slightly below the standard, the trial will continue; when , if the trial on that day seriously fails to meet the standards, the trial will be stopped; Through the above technical solution, this embodiment converts the trial evaluation index of the day into With the first preset value For comparison: When When the test result is less than 100%, it means that the test result is slightly below the standard and the test result will continue. , indicating that the trial on that day seriously failed to meet the standards and the trial was stopped; It should be noted that the first preset value It is a preset value obtained based on experience and will not be described in detail here.

[0024] As an implementation mode of the present invention, by formula: ; Calculating the comprehensive trial evaluation index ; in, is the third judgment function, when hour, ;when hour, ; is the total number of days of actual trial. ; The number of days for the trial is preset; The number of days to reach the target; For the day trial evaluation index; is the first comprehensive preset constant; Preset constant for the second synthesis; is the first comprehensive weight coefficient; is the second comprehensive weight coefficient; Through the above technical solution, this embodiment is the difference between the actual total trial days and the preset trial days; in the formula In the third judgment function In Reference ;when , it means that the actual total trial days are less than the preset trial days; it means that the trial on that day is seriously not up to standard, so ; Comprehensive trial evaluation index ;when , it means that the actual total trial days exceed the preset trial days, which means that there is no serious failure to meet the trial standards on that day. ; Comprehensive trial evaluation index ; The ratio of the number of days meeting the target to the total number of days actually on trial is the ratio of the number of days meeting the target to the total number of days actually on trial. The larger the comprehensive trial evaluation index The bigger; is the average trial evaluation index of the total number of actual trial days; the average trial evaluation index of the total number of actual trial days The larger the comprehensive trial evaluation index The bigger; It should be noted that the preset trial days , the first comprehensive preset constant , the second comprehensive preset constant , the first comprehensive weight coefficient and the second comprehensive weight coefficient It is a preset value obtained based on experience and will not be described in detail here.

[0025] As an implementation mode of the present invention, by formula: ; Calculate the supplier comprehensive evaluation index ; Supplier comprehensive evaluation index With the second preset value For comparison: when When, the supplier is level three; when When the supplier is level 2; when When the supplier is first-level.

[0026] Through the above technical solution, the comprehensive trial evaluation index of this embodiment The larger the supplier's comprehensive evaluation index is, the The larger the supplier's basic evaluation index The larger the supplier comprehensive evaluation index The bigger; when hour, ; The supplier is level 3; Cannot cooperate; When When the supplier is at level 2, it becomes a candidate; when When the supplier is first-level, cooperation is possible; It should be noted that the second preset value It is a preset value obtained based on experience and will not be described in detail here.

[0027] See also Figure 2 As shown, a supplier qualification comprehensive evaluation system based on big data includes: Market information module, used to obtain basic information data of suppliers; Trial data module, used to obtain trial information data of suppliers; Weather data module, used to obtain weather information data; The analysis module is used to analyze the basic information data to obtain the basic evaluation index of the supplier; the analysis module is then used to analyze the trial information data and weather information data during the trial period to obtain the supplier's comprehensive trial evaluation index; finally, the basic evaluation index and the comprehensive trial evaluation index are analyzed to obtain the supplier's comprehensive evaluation index; and the supplier is rated based on the supplier's comprehensive evaluation index.

[0028] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A comprehensive evaluation method for supplier qualifications based on big data, characterized in that: The following steps are involved: S1: Obtain basic information data of suppliers through the market information module; S2: Obtain the trial information data of the supplier through the trial data module; S3: Obtain weather information data through the weather data module; S4: Analyze the basic information data through the analysis module to obtain the basic evaluation index of the supplier; then analyze the trial information data and weather information data during the trial period through the analysis module to obtain the supplier's comprehensive trial evaluation index; finally, analyze the basic evaluation index and the comprehensive trial evaluation index to obtain the supplier's comprehensive evaluation index; and rate the supplier based on the supplier's comprehensive evaluation index.

2. According to the method for comprehensive evaluation of supplier qualifications based on big data according to claim 1, it is characterized in that: By formula: ； Calculate the supplier's basic evaluation index ; in, The length of time the supplier has been in business, The quantity of the required product type; The quantity of the required product type that the supplier can provide; To research the number of customers of a supplier for market research, ; For the Customer satisfaction; Preset constants for the first basis; Preset constants for the second basis; Preset constants for the third basis; is the first basic weight coefficient; is the second basic weight coefficient; is the third basic weight coefficient.

3. According to the method for comprehensive evaluation of supplier qualifications based on big data in claim 2, it is characterized in that: By formula: ； Calculate the trial evaluation index for the day ; in, is the first judgment function, when hour, ;when hour, ; The total quantity of the product type of the supplier during the trial period. ; For the The actual supply of the product type; For the The actual daily demand for the product type; For the The basic preset tolerance values ​​for the types of goods; For the The commodity error adjustment coefficient for the commodity type on that day; The actual delivery time on that day; The preset delivery time for the day; It is the allowable error value of the basic preset time; is the time error adjustment coefficient of the day; For the The quality standards of the product types; is the preset target achievement rate; To serve as the basic trial assessment index; Preset constants for the first trial; Preset constants for the second trial; Preset constants for the third trial; is the first trial weight coefficient; is the second trial weight coefficient; is the weight coefficient of the third trial.

4. According to the method for comprehensive evaluation of supplier qualifications based on big data in claim 3, it is characterized in that: By formula: ； Calculate the The error adjustment coefficient of the goods for the day ; in, is the second judgment function, when hour, ;when hour, ; For the The length of time between the order placement time of the same day and the preset deadline for the type of goods; is the time coefficient; Preset constants for the fourth trial.

5. According to the method for comprehensive evaluation of supplier qualifications based on big data according to claim 4, it is characterized in that: The trial evaluation index of the day With the first preset value For comparison: when If the trial supplier on that day fully meets the standards, the trial will continue; when If the trial on that day is slightly below the standard, the trial will continue; when , the trial on that day seriously failed to meet the standards and the trial was stopped.

6. According to claim 5, a comprehensive evaluation method for supplier qualifications based on big data is characterized in that: By formula: ； Calculating the comprehensive trial evaluation index ; in, is the third judgment function, when hour, ;when hour, ; is the total number of days of actual trial. ; The number of days for the trial is preset; The number of days to reach the target; For the day trial evaluation index; is the first comprehensive preset constant; Preset constant for the second synthesis; is the first comprehensive weight coefficient; is the second comprehensive weight coefficient.

7. The method for comprehensive evaluation of supplier qualifications based on big data according to claim 6 is characterized in that: By formula: ； Calculate the supplier comprehensive evaluation index ; Supplier comprehensive evaluation index With the second preset value For comparison: when When, the supplier is level three; when When the supplier is level 2; when When the supplier is first-level.

8. A supplier qualification comprehensive evaluation system based on big data, applicable to a supplier qualification comprehensive evaluation method based on big data as described in any one of claims 1 to 7, characterized in that: include: Market information module, used to obtain basic information data of suppliers; Trial data module, used to obtain trial information data of suppliers; Weather data module, used to obtain weather information data; The analysis module is used to analyze basic information data and obtain the basic evaluation index of suppliers; The trial information data and weather information data of the trial period are then analyzed through the analysis module to obtain the supplier's comprehensive trial evaluation index; finally, the basic evaluation index and the comprehensive trial evaluation index are analyzed to obtain the supplier's comprehensive evaluation index; and the supplier is rated based on the supplier's comprehensive evaluation index.

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