CN117610897A - Supply chain service management system and method based on data analysis - Google Patents
Supply chain service management system and method based on data analysis Download PDFInfo
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Abstract
The invention discloses a supply chain service management system and method based on data analysis, and relates to the technical field of supply chain data management.
Description
Technical Field
The invention relates to the technical field of supply chain data management, in particular to a supply chain service management system and method based on data analysis.
Background
The supply chain is an integration of key business processes and relations from an original material provider to enterprises on the whole chain of an end user, which provides convenience for supply chain service management work, enables the end user to quickly receive accurate supply goods and helps to realize intelligent management of supply chain services;
when the information flow on the supply chain is transmitted from a client to an original provider end, the information cannot be effectively shared, so that the information distortion is more and more serious, the client demand information received by the node is more and more fluctuated, a long whip effect is formed, instability of commodity production and supply is increased, negative interference is caused to commodity supply, and in the prior art, a hierarchical management mode is adopted for a retailer: the information of different demand orders is transmitted to retailers of different levels in a scattered manner, so that fluctuation of demand information received by the nodes is relieved, abnormal phenomena with large fluctuation of transmitted information in the commodity supply process can not be found and early-warned in time, and information verification and adjustment can not be timely reminded to be performed so as to further reduce the interference of long whip effect.
Therefore, a supply chain service management system and method based on data analysis are urgently needed to solve the above technical problems.
Disclosure of Invention
The invention aims to provide a supply chain service management system and method based on data analysis, which are used for solving the problems in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions: a data analysis based supply chain service management system, comprising: the system comprises a supply chain data acquisition module, a database, an effect interference analysis module, an information balance analysis module and a supply chain service management module;
the output end of the supply chain data acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the effect interference analysis module and the information balance analysis module, the output end of the effect interference analysis module is connected with the input end of the information balance analysis module, and the output end of the information balance analysis module is connected with the input end of the supply chain service management module;
collecting supply chain information and information receiving historical data of supply chain nodes during article supply through the supply chain data collecting module, and transmitting all collected data to the database;
storing all the collected data through the database;
analyzing the information receiving interfered degree of the supply chain node through the effect interference analysis module;
establishing an information unbalance early warning prediction model through the information balance analysis module, and analyzing the unbalance condition of the information received by the supply chain;
and carrying out supply chain link point receiving information service management according to the unbalance condition through the supply chain service management module.
Further, the supply chain data acquisition module comprises a node data acquisition unit and an order receiving data acquisition unit;
the output ends of the node data acquisition unit and the order receiving data acquisition unit are connected with the input end of the database;
the node data acquisition unit is used for acquiring the number of supply chain nodes and the grading information of retailers in the process of supplying the articles for a plurality of times, wherein the supply chain nodes change along with the number of the suppliers, for example: if the number of suppliers is 3, the corresponding supply chain node is: consumer, retailer, distributor, manufacturer, primary supplier, secondary supplier, tertiary supplier, then supply chain node number is 7, primary supplier is the direct supplier of manufacturer, secondary supplier is the supplier of primary supplier, tertiary supplier is the supplier of secondary supplier, the hierarchical information of retailer refers to the information of the level number of retailers at the time of article supply, the level number is equal to the retailer number, for example: the number of retailers is 3 when a certain article is supplied, the number of the grades of the retailers is 3, the grading condition of the retailers is not counted in the number of the supply chain nodes, namely, the number of the supply chain nodes is not changed along with the grading condition of the retailers no matter the retailers are graded;
and acquiring the information of the quantity of the demand orders in the previous node transmission information received by different supply chain link points in the process of supplying the articles through the order receiving data acquisition unit.
Further, the effect interference analysis module comprises a received information calling unit and an interference analysis unit;
the input end of the received information calling unit is connected with the output end of the database, and the output end of the received information calling unit is connected with the input end of the interference analysis unit;
the receiving information calling unit is used for calling the quantity information of the demand orders transmitted by the last node and received by different supply chain nodes to the interference analysis unit;
the interference analysis unit is used for analyzing the interference degree of the receiving of the demand information for different numbers of the supply chain nodes and the classification condition of retailers.
Further, the information balance analysis module comprises a sample data retrieval unit, an early warning prediction model establishment unit and an information balance pre-judgment unit;
the input end of the sample data calling unit is connected with the output ends of the interference analysis unit and the database, the output end of the sample data calling unit is connected with the input end of the early warning prediction model building unit, and the output end of the early warning prediction model building unit is connected with the input end of the information balance pre-judging unit;
the sample data calling unit is used for calling the number of supply chain nodes, the grading information of retailers and the interference degree of the receiving of the demand information, combining the called data to generate sample data, and transmitting the sample data to the early warning prediction model building unit;
an information unbalance early warning prediction model is built according to sample data through the early warning prediction model building unit;
substituting the number of supply chain nodes and retailer grading data which are currently supplied with the articles into an information unbalance early warning prediction model by the information balance pre-judging unit, predicting the interference degree of receiving the demand information when the corresponding articles are supplied, setting an interference degree threshold value, comparing the predicted interference degree with the threshold value, and pre-judging the problem that the information unbalance exists in the corresponding article supply if the predicted interference degree exceeds the threshold value.
Further, the supply chain service management module comprises an information unbalance early warning unit and an information checking and reminding unit;
the input end of the information unbalance early-warning unit is connected with the output end of the information balance pre-judging unit, and the output end of the information unbalance early-warning unit is connected with the input end of the information checking reminding unit;
if the information unbalance pre-warning unit pre-judges that the article supply has the problem of information unbalance, an information unbalance pre-warning signal is sent to the information checking and reminding unit;
and reminding the information verification reminding unit to verify the quantity information of the article demand orders received by all the supply chain link points.
A supply chain service management method based on data analysis, comprising the steps of:
s1: collecting supply chain information and information receiving historical data of supply chain nodes when articles are supplied;
s2: analyzing the information receiving interfered degree of the supply chain node;
s3: establishing an information unbalance early warning prediction model, and analyzing unbalance conditions of information received by a supply chain;
s4: supply link point receive information service management is performed according to the imbalance condition.
Further, in step S1: the collection of the number of the supply chain nodes in the previous k-time article supply process is L= { L 1 ，L 2 ，…，L k Number of retailer classes in corresponding secondary item supply processThe quantity set is h= { H 1 ，H 2 ，…，H k And acquiring the information of the quantity of the demand orders in the previous node transfer information received by different supply chain link points in the process of supplying the articles.
Further, in step S2: the method comprises the steps of calling the number of retailers in the prior random primary article supply process to be b, dividing a supply chain in the corresponding secondary article supply process into b supply chains, wherein each supply chain comprises a retailer, and acquiring a set of the number of demand orders in the transmission information of the last node received by a supply chain node in one supply chain at random to be G= { G 1 ，G 2 ，…，G m In the corresponding secondary article supply process, m+1 supply chain nodes are used for calculating the interference degree W of supply chain node demand information receiving of random one supply chain according to the following formula e ：
；
Wherein G is i Representing the quantity of demand orders received by the ith supply chain node in one supply chain from the transmission information of the last node, and calculating the interference degree of the demand information reception of the supply chain nodes of the b supply chains in the same way to obtain the total interference degree value R of the demand information reception in the corresponding secondary article supply process j ，The total value set of the interference degree of the receiving of the demand information in the k-time article supply process is R= { R 1 ，R 2 ，…，R k }；
When the prior goods are supplied by a big data technology, the quantity of demand orders in the information received by different nodes on a supply chain is collected, the interference degree of the demand information received by the supply chain nodes during goods supply is analyzed by analyzing the quantity change and difference conditions of the demand orders in the information received by the different nodes, the greater the difference is, the greater the demand information received by the nodes is judged, namely the interference degree is, the interference degree of the demand information received by the nodes is analyzed, the interference degree of the demand information received by the nodes corresponding to the classification conditions of different supply chains in historical data is used as training sample data of an information unbalance early warning prediction model, the interference degree of the demand information received under the different conditions is analyzed, the classification conditions of retailers are comprehensively considered, the different retailers are located in the different supply chains, the different supply chains refer to the supply chains which are changed only by retailers, the interference degree analysis of the demand information received by the supply chains is performed, and the accuracy and the referenceability of training sample data are improved.
Further, in step S3: generating sample data { (L) 1 ，H 1 ，R 1 ），（L 2 ，H 2 ，R 2 ），…，（L k ，H k ，R k ) Fitting the sample data, and establishing an information unbalance early warning prediction model:wherein->、And->Representing a fitting coefficient, x representing a first argument referring to the number of supply chain nodes, y representing a second argument referring to the number of retailer levels, z representing a dependent variable referring to the extent of interference with demand information reception, calculated according to the following formula, respectively、/>And->：
；
；
；
Wherein L is j Indicating the number of supply chain nodes in the prior jth article supply process, H j The number of the levels of retailers in the conventional jth article supply process is represented, the number of supply chain nodes when the article supply is currently carried out is obtained to be n, the number of the levels of the retailers is f, and n and f are substituted into the information unbalance early warning prediction model: let x=n, y=f, the predicted interference degree of the receiving of the demand information when the current article is supplied is:setting the interference degree threshold as F, and comparingAnd F: if->The problem that the demand information received by the node is unbalanced in the current article supply process is prejudged.
Further, in step S4: if the problem that the demand information received by the article supply existing node is unbalanced is prejudged, an information unbalance early warning signal is sent to remind that the quantity information of the article demand orders received by all the supply chain link points is checked;
the method comprises the steps of considering different numbers of supply chain nodes, namely, different supply chain nodes caused by different levels of suppliers, describing multiple times of transmission processes of demand information when the nodes are transmitted one by one, enabling the probability of information change to be higher, considering the fact that the retailers are different in classification, enabling orders to be scattered, namely, the number of demand orders in the transmission information is smaller in base number, enabling the probability of information change to be lower, establishing an information unbalance early warning prediction model according to the number of the supply chain nodes, the classification data of the retailers and the interference degree of the demand information received by the nodes under the corresponding conditions, predicting the interference degree of the demand information receiving under the different preconditions, predicting the fluctuation condition of the demand information in advance, helping to timely find and early warn the abnormal phenomenon that the transmission information in the commodity supply process fluctuates greatly, timely reminding and verifying the rationality of the demand information transmitted on the supply chain so as to reasonably adjust the demand information, and effectively reducing the interference of long whip effect on the supply chain service.
Compared with the prior art, the invention has the beneficial effects that:
when the prior goods are supplied by a big data technology, the quantity of demand orders in the information received by different nodes on a supply chain is collected, the interference degree of the demand information received by the supply chain node during the goods supply is analyzed by analyzing the quantity change and difference condition of the demand orders in the information received by different nodes, the interference degree is analyzed by taking the interference degree of the demand information received by different supply chain nodes and the corresponding classification condition of different retailers in historical data as training sample data of an information unbalance early warning prediction model to analyze the interference degree of the demand information received under different conditions, the classification condition of retailers is comprehensively considered, different retailers are in different supply chains, the different supply chains refer to supply chains only changed by retailers, and the interference degree analysis of the demand information received by a plurality of supply chains is performed, so that the accuracy and the referenceability of the training sample data are improved;
in consideration of different numbers of supply chain nodes, namely different supply chain nodes caused by different levels of suppliers, in addition, in consideration of different classification conditions of retailers, an information unbalance early warning prediction model is built by combining the number of the supply chain nodes, the classification data of retailers and the interference degree of demand information received by the nodes under the corresponding conditions, the interference degree of demand information receiving under different preconditions is predicted, fluctuation conditions of the demand information are predicted in advance, abnormal phenomena of large fluctuation of transmission information in the commodity supply process are helped to be found and early warned in time, rationality of the demand information transmitted on the supply chain is reminded and verified in time to reasonably adjust the demand information, and interference of long whip effect on supply chain service is effectively reduced.
Drawings
FIG. 1 is a schematic diagram of a supply chain service management system based on data analysis according to the present invention;
fig. 2 is a flow chart of a supply chain service management method based on data analysis according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1-2, the present invention provides the following technical solutions: a data analysis based supply chain service management system, comprising: the system comprises a supply chain data acquisition module, a database, an effect interference analysis module, an information balance analysis module and a supply chain service management module; the method comprises the steps that supply chain information and information receiving historical data of supply chain nodes during article supply are collected through a supply chain data collection module, and all collected data are transmitted to a database; storing all the acquired data by a database; analyzing the information receiving interfered degree of the supply chain node through an effect interference analysis module; an information unbalance early warning prediction model is established through an information balance analysis module, and unbalance conditions of information received by a supply chain are analyzed; and carrying out information service management on the supply chain link point receiving information service according to the unbalance condition through a supply chain service management module.
The supply chain data acquisition module comprises a node data acquisition unit and an order receiving data acquisition unit; the node data acquisition unit is used for acquiring the number of supply chain nodes and the grading information of retailers in the process of supplying the articles for a plurality of times; the order receiving data acquisition unit is used for acquiring the information of the quantity of the demand orders in the previous node transmission information received by different supply chain link points in the process of supplying the articles.
The effect interference analysis module comprises a received information calling unit and an interference analysis unit; the method comprises the steps that a receiving information calling unit is used for calling the quantity information of the demand orders transmitted by a last node and received by different supply chain nodes to an interference analysis unit; the interference degree of the receiving of the demand information is analyzed by the interference analysis unit for different numbers of supply chain nodes and retailer classification conditions.
The information balance analysis module comprises a sample data retrieval unit, an early warning prediction model establishment unit and an information balance prejudgment unit; the method comprises the steps of calling the number of supply chain nodes, the grading information of retailers and the interference degree of demand information reception through a sample data calling unit, combining the called data to generate sample data, and transmitting the sample data to an early warning prediction model building unit; an information unbalance early warning prediction model is established according to the sample data through an early warning prediction model establishing unit; substituting the number of supply chain nodes and retailer grading data which are currently supplied with the articles into an information unbalance early warning prediction model through an information balance pre-judging unit, predicting the interference degree of receiving the demand information when corresponding to the articles are supplied, setting an interference degree threshold value, comparing the predicted interference degree with the threshold value, and pre-judging the problem that the information unbalance exists in the corresponding articles if the predicted interference degree exceeds the threshold value.
The supply chain service management module comprises an information unbalance early warning unit and an information checking and reminding unit; if the information unbalance pre-warning unit pre-judges that the article supply has the problem of information unbalance, an information unbalance pre-warning signal is sent to the information checking and reminding unit; and reminding the information verification reminding unit to verify the quantity information of the article demand orders received by all the supply chain link points.
A supply chain service management method based on data analysis, comprising the steps of:
s1: collecting supply chain information and information receiving historical data of supply chain nodes when supplying articles, wherein the number set of the supply chain nodes in the previous k article supply processes is L= { L 1 ，L 2 ，…L k Number of retailer classes in corresponding secondary item supply processThe quantity set is h= { H 1 ，H 2 ，…，H k Collecting the quantity information of the demand orders in the previous node transmission information received by different supply chain link points in the process of supplying the articles;
s2: analyzing the information receiving interference degree of the supply chain nodes, invoking the level number of retailers as b in the prior random one-time article supply process, dividing the supply chain in the corresponding one-time article supply process into b supply chains, wherein each supply chain comprises a retailer, and acquiring the number set of demand orders in the information transmitted by the last node received by the supply chain nodes in one supply chain at random as G= { G 1 ，G 2 ，…，G m In total, m+1 supply chain nodes in the corresponding secondary article supply process according to the formulaCalculating the interference degree W of supply chain node demand information reception of random supply chain e Wherein G is i Representing the quantity of demand orders received by the ith supply chain node in one supply chain from the transmission information of the last node, and calculating the interference degree of the demand information reception of the supply chain nodes of the b supply chains in the same way to obtain the total interference degree value R of the demand information reception in the corresponding secondary article supply process j ，The total value set of the interference degree of the receiving of the demand information in the k-time article supply process is R= { R 1 ，R 2 ，…，R k }；
S3: an information unbalance early warning prediction model is built, unbalance conditions of information received by a supply chain are analyzed, and sample data { (L) is generated 1 ，H 1 ，R 1 ），（L 2 ，H 2 ，R 2 ），…，（L k ，H k ，R k ) Fitting the sample data, and establishing an information unbalance early warning prediction model:wherein，/>、/>And->Representing a fitting coefficient, x representing a first argument referring to the number of supply chain nodes, y representing a second argument referring to the number of retailer levels, z representing a dependent variable referring to the extent to which demand information is received disturbed, according to the formula->、Andrespectively calculating to obtain->、/>And->Wherein L is j Indicating the number of supply chain nodes in the prior jth article supply process, H j The number of the levels of retailers in the conventional jth article supply process is represented, the number of supply chain nodes when the article supply is currently carried out is obtained to be n, the number of the levels of the retailers is f, and n and f are substituted into the information unbalance early warning prediction model: let x=n, y=f, the predicted interference degree of the receiving of the demand information when the current article is supplied is: />Setting the interference degree threshold as F, comparing +.>And F: if->The method comprises the steps of pre-judging that the problem of unbalance of demand information received by a node exists in the current article supply process;
s4: if the problem that the demand information received by the article supply existing node is unbalanced is predicted, an information unbalance early warning signal is sent to remind that the quantity information of the article demand orders received by all the supply chain link points is checked.
Example 1: the method comprises the steps of obtaining that in the previous random primary article supply process, the number of retailers is 3, dividing a supply chain in the corresponding secondary article supply process into 3 supply chains, and obtaining that the number of corresponding supply chain nodes is 5, wherein the number of the 3 supply chain nodes is respectively: first: consumer, retailer 1, distributor, manufacturer, and supplier; second: consumer, retailer 2, distributor, manufacturer, and supplier; third,: consumer, retailer 3, distributor, manufacturer, supplier, obtains the number of demand orders in the last node transfer information received by the supply chain node in the first supply chain as g= { G 1 ，G 2 ，G 3 ，G 4 The interference degree W of the supply chain node demand information receiving of the first supply chain is calculated by the method of (200, 250, 260, 300) 1 Approximately 35.6, obtaining the quantity of the received demand orders of the three supply chains, and calculating to obtain the interfered degrees of the demand information receiving of the supply chain nodes of the three supply chains, wherein the interfered degrees are respectively as follows: 35.6, 10.2 and 23.2, the total value of the interfered degree corresponding to the receiving of the demand information in the secondary article supply process is 69.
Example 2: the collection of the number of the supply chain nodes in the previous 5-time article supply process is L= { L 1 ，L 2 ，L 3 ，L 4 ，L 5 The number of retailer levels in the corresponding secondary item supply process is set to h= { H = {5,6,8,5,7} 1 ，H 2 ，H 3 ，H 4 ，H 5 The total value set of the interfered degree of the receiving of the demand information in the prior 5-time article supply process is R= { R } = {3,1,3,5,2} 1 ，R 2 ，R 3 ，R 4 ，R 5 }={69，102.5，75.2，12.2 90.6, generates sample data { (L) 1 ，H 1 ，R 1 ），（L 2 ，H 2 ，R 2 ），（L 3 ，H 3 ，R 3 ），（L 4 ，H 4 ，R 4 ），（L 5 ，H 5 ，R 5 ) Fitting the sample data, and establishing an information unbalance early warning prediction model:obtaining that the number of supply chain nodes is 7 when the current article is supplied, the number of retailers is 1, letting x=7 and y=1, predicting that the interference degree of receiving the demand information when the current article is supplied is 118.7, and setting the threshold of the interference degree to be F=70 and 118.7>70, prejudging that the problem of unbalance of the demand information received by the node exists in the current article supply process: the fluctuation of demand information received by the nodes is large, the interference of long whip effect on information reception is large, an information unbalance early warning signal is sent, and the quantity information of the demand orders of the articles received by all the supply chain link points is reminded to be checked.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A supply chain service management system based on data analysis, comprising: the system comprises a supply chain data acquisition module, a database, an effect interference analysis module, an information balance analysis module and a supply chain service management module;
the output end of the supply chain data acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the effect interference analysis module and the information balance analysis module, the output end of the effect interference analysis module is connected with the input end of the information balance analysis module, and the output end of the information balance analysis module is connected with the input end of the supply chain service management module;
collecting supply chain information and information receiving historical data of supply chain nodes during article supply through the supply chain data collecting module, and transmitting all collected data to the database;
storing all the collected data through the database;
analyzing the information receiving interfered degree of the supply chain node through the effect interference analysis module;
establishing an information unbalance early warning prediction model through the information balance analysis module, and analyzing the unbalance condition of the information received by the supply chain;
and carrying out supply chain link point receiving information service management according to the unbalance condition through the supply chain service management module.
2. A data analysis based supply chain service management system as claimed in claim 1, wherein: the supply chain data acquisition module comprises a node data acquisition unit and an order receiving data acquisition unit;
the output ends of the node data acquisition unit and the order receiving data acquisition unit are connected with the input end of the database;
the node data acquisition unit is used for acquiring the number of supply chain nodes and the grading information of retailers in the process of supplying the articles for a plurality of times;
and acquiring the information of the quantity of the demand orders in the previous node transmission information received by different supply chain link points in the process of supplying the articles through the order receiving data acquisition unit.
3. A data analysis based supply chain service management system as claimed in claim 2, wherein: the effect interference analysis module comprises a received information calling unit and an interference analysis unit;
the input end of the received information calling unit is connected with the output end of the database, and the output end of the received information calling unit is connected with the input end of the interference analysis unit;
the receiving information calling unit is used for calling the quantity information of the demand orders transmitted by the last node and received by different supply chain nodes to the interference analysis unit;
the interference analysis unit is used for analyzing the interference degree of the receiving of the demand information for different numbers of the supply chain nodes and the classification condition of retailers.
4. A data analysis based supply chain service management system as claimed in claim 3, wherein: the information balance analysis module comprises a sample data retrieval unit, an early warning prediction model establishment unit and an information balance pre-judgment unit;
the input end of the sample data calling unit is connected with the output ends of the interference analysis unit and the database, the output end of the sample data calling unit is connected with the input end of the early warning prediction model building unit, and the output end of the early warning prediction model building unit is connected with the input end of the information balance pre-judging unit;
the sample data calling unit is used for calling the number of supply chain nodes, the grading information of retailers and the interference degree of the receiving of the demand information, combining the called data to generate sample data, and transmitting the sample data to the early warning prediction model building unit;
an information unbalance early warning prediction model is built according to sample data through the early warning prediction model building unit;
substituting the number of supply chain nodes and retailer grading data which are currently supplied with the articles into an information unbalance early warning prediction model by the information balance pre-judging unit, predicting the interference degree of receiving the demand information when the corresponding articles are supplied, setting an interference degree threshold value, comparing the predicted interference degree with the threshold value, and pre-judging the problem that the information unbalance exists in the corresponding article supply if the predicted interference degree exceeds the threshold value.
5. The data analysis based supply chain service management system of claim 4, wherein: the supply chain service management module comprises an information unbalance early warning unit and an information checking and reminding unit;
the input end of the information unbalance early-warning unit is connected with the output end of the information balance pre-judging unit, and the output end of the information unbalance early-warning unit is connected with the input end of the information checking reminding unit;
if the information unbalance pre-warning unit pre-judges that the article supply has the problem of information unbalance, an information unbalance pre-warning signal is sent to the information checking and reminding unit;
and reminding the information verification reminding unit to verify the quantity information of the article demand orders received by all the supply chain link points.
6. A supply chain service management method based on data analysis is characterized in that: the method comprises the following steps:
s1: collecting supply chain information and information receiving historical data of supply chain nodes when articles are supplied;
s2: analyzing the information receiving interfered degree of the supply chain node;
s3: establishing an information unbalance early warning prediction model, and analyzing unbalance conditions of information received by a supply chain;
s4: supply link point receive information service management is performed according to the imbalance condition.
7. The data analysis-based supply chain service management method of claim 6, wherein: in step S1: the collection of the number of the supply chain nodes in the previous k-time article supply process is L= { L 1 ，L 2 ，…L k The retailer level number set in the corresponding secondary item supply process is h= { H 1 ，H 2 ，…，H k The previous process of supplying articles is collectedThe last node received by a different supply link point communicates demand order quantity information in the information.
8. The data analysis-based supply chain service management method of claim 7, wherein: in step S2: the method comprises the steps of calling the number of retailers in the prior random primary article supply process to be b, dividing a supply chain in the corresponding secondary article supply process into b supply chains, wherein each supply chain comprises a retailer, and acquiring a set of the number of demand orders in the transmission information of the last node received by a supply chain node in one supply chain at random to be G= { G 1 ，G 2 ，…，G m In the corresponding secondary article supply process, m+1 supply chain nodes are used for calculating the interference degree W of supply chain node demand information receiving of random one supply chain according to the following formula e ：
；
Wherein G is i Representing the quantity of demand orders received by the ith supply chain node in one supply chain from the transmission information of the last node, and calculating the interference degree of the demand information reception of the supply chain nodes of the b supply chains in the same way to obtain the total interference degree value R of the demand information reception in the corresponding secondary article supply process j ，The total value set of the interference degree of the receiving of the demand information in the k-time article supply process is R= { R 1 ，R 2 ，…，R k }。
9. The data analysis-based supply chain service management method of claim 8, wherein: in step S3: generating sample data { (L) 1 ，H 1 ，R 1 ），（L 2 ，H 2 ，R 2 ），…，（L k ，H k ，R k ) Fitting the sample data, and establishing an information unbalance early warning prediction model:wherein->、/>And->Representing a fitting coefficient, x representing a first argument referring to the number of supply chain nodes, y representing a second argument referring to the number of retailer levels, z representing a dependent variable referring to the extent of interference in reception of demand information, and calculating +.>、/>And->：
；
；
；
Wherein L is j Indicating the number of supply chain nodes in the prior jth article supply process, H j Representing the number of retailer levels in the past jth article supply process, and acquiring the supply when the article is currently suppliedThe number of chain nodes is n, the number of retailers is f, and n and f are substituted into the information unbalance early warning prediction model: let x=n, y=f, the predicted interference degree of the receiving of the demand information when the current article is supplied is:setting the interference degree threshold as F, and comparingAnd F: if->The problem that the demand information received by the node is unbalanced in the current article supply process is prejudged.
10. The data analysis-based supply chain service management method according to claim 9, wherein: in step S4: if the problem that the demand information received by the article supply existing node is unbalanced is predicted, an information unbalance early warning signal is sent to remind that the quantity information of the article demand orders received by all the supply chain link points is checked.
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