CN118313678A - Intelligent enterprise decision method and system based on large model - Google Patents
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Abstract
The invention discloses an intelligent enterprise decision-making method and system based on a large model, which relate to the field of enterprise decision-making management, can objectively measure the accuracy of enterprise decision making by evaluating decision-making accuracy parameters, help enterprises identify potential decision-making problems, timely adjust and optimize the decision-making, ensure that the decision-making meets business requirements and expected targets, help objectively evaluate the accuracy of the decision-making, provide reference basis for subsequent decision-making, help enterprises know the effect of the decision-making on a business level by analyzing the influence of decision-making implementation, including sales rate change rate, profit rate change rate and customer satisfaction degree score, help enterprises optimize decision-making schemes, improve business performance and customer satisfaction degree, realize long-term sustainable development, and help enterprise managers to comprehensively understand potential risks brought by the decision-making by evaluating risk information including technical investment proportion and employee job departure rate after the decision-making implementation.
Description
Technical Field
The invention relates to the field of enterprise decision management, in particular to an intelligent enterprise decision method and system based on a large model.
Background
With the rapid development of the internet and information technology, enterprises face massive data and information, the traditional analysis and decision-making method cannot meet the deep mining and utilization requirements of the data, intelligent enterprise decision-making methods based on large models are generated so as to analyze the data more efficiently and accurately and assist decision-making, the enterprises need to make decisions more quickly and accurately when facing increasingly complex and changeable market environments and competitive pressures, and the application of the intelligent enterprise decision-making methods and systems can help enterprise managers to analyze and solve problems more scientifically and improve decision-making efficiency and quality.
The existing intelligent enterprise decision method and system based on the large model may have the following problems: 1. the existing inadequately analyzed designated enterprise decision system cannot sufficiently evaluate the accuracy of decisions, so that the accuracy of various decisions made by enterprises cannot be effectively guaranteed, the decision results are inaccurate, bad business influence is generated, the enterprise cannot accurately evaluate the influence on the business after decision implementation due to lack of sufficient analysis on business influence evaluation, such as sales change rate, profit rate change rate and customer satisfaction degree score, and the business results after enterprise decision implementation cannot meet expectations.
2. A few designated enterprise decision methods are used for insufficiently analyzing risk information after decision implementation, so that enterprises are difficult to effectively evaluate risks, including technical investment proportion and employee withdrawal rate, the enterprises face risks which cannot be effectively controlled, adverse effects are generated on service stability, and the enterprise cannot comprehensively evaluate the comprehensive effects after decision implementation due to the lack of comprehensive effect analysis of full analysis, so that whether various decisions meet the enterprise development requirements cannot be judged.
Disclosure of Invention
The invention aims to provide an intelligent enterprise decision method and system based on a large model, which solve the problems in the background technology.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention provides an intelligent enterprise decision method based on a large model, which comprises the following steps: step one, enterprise decision analysis: according to a successfully trained appointed model, guiding an appointed enterprise to make various decisions, analyzing decision accuracy parameters corresponding to various decisions of the appointed enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy evaluation coefficients corresponding to various decisions of the appointed enterprise, so that whether various decision accuracy of the appointed enterprise based on the appointed model meets application requirements of the appointed enterprise is analyzed.
Step two, evaluating business influence: when the accuracy of a certain decision made by a designated enterprise based on a designated model meets the application requirements of the designated enterprise, various decisions meeting the application requirements of the designated enterprise are recorded as compliance decisions, the influence on the service after the implementation of the compliance decisions made by the designated enterprise is analyzed, the influence comprises the corresponding sales change rate and profit margin change rate after the implementation of the compliance decisions and the customer satisfaction degree score, and further the corresponding service influence evaluation coefficient of the designated enterprise after the implementation of the compliance decisions is calculated.
Step three, risk assessment: and acquiring corresponding risk information of the appointed enterprise after implementing each compliance decision, wherein the risk information comprises a technical investment proportion and an employee departure rate, and further calculating to obtain a corresponding risk assessment coefficient of the appointed enterprise after implementing each compliance decision.
Step four, comprehensive influence analysis: and according to the business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions and the risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, further analyzing to obtain the comprehensive evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, and further analyzing whether the implementation of the compliance decisions of the appointed enterprises meets the enterprise development requirements or not.
Step five, early warning prompting: and when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirements of the appointed enterprise, carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the development requirements of the enterprise.
Preferably, the calculation obtains decision accuracy evaluation coefficients corresponding to various decisions of a specified enterprise, and the specific calculation process is as follows: substituting the accuracy, precision and recall rate corresponding to various decisions of a designated enterprise into a calculation formulaThe decision accuracy evaluation coefficients alpha i corresponding to various decisions of a designated enterprise are obtained, i is a number corresponding to various decisions, i=1, 2, … …, n, i is any integer greater than 2, wherein A i、Bi、Ci respectively represents the accuracy, precision and recall rate corresponding to the ith decision of the designated enterprise, A ', B ', C ' respectively represent the set standard accuracy, standard precision and standard recall rate, and eta 1、η2、η3 respectively represent the weight factor corresponding to the set accuracy, the weight factor corresponding to the precision and the weight factor corresponding to the recall rate.
Preferably, the analysis indicates whether the accuracy of various decisions made by the enterprise based on the specified model meets the application requirements of the specified enterprise, and the specific analysis process is as follows: comparing the decision accuracy evaluation coefficients corresponding to various decisions of the designated enterprises with a set decision accuracy evaluation coefficient threshold, if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is larger than or equal to the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises, and if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is smaller than the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models does not meet the application requirements of the designated enterprises, so as to analyze whether the various decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises.
Preferably, the analysis designates the influence of each compliance decision made by the enterprise on the business, and the specific analysis process is as follows: a1, acquiring sales data before and after implementation of each compliance decision from a sales system and transaction records of a designated enterprise, respectively marking sales before and after implementation of each compliance decision as M i'、Mi '', wherein i is a number corresponding to each compliance decision, i=1, 2, … …, n and i are any integers greater than 2, and calculating a formula by using the sales dataObtaining corresponding sales change rate M i after implementation of each compliance decision;
A2, acquiring financial data before and after decision implementation from financial reports, accounting records and management systems of specified enterprises, wherein the financial data comprises business income, sales cost and operation cost, so as to obtain net profits and revenue corresponding to each compliance decision implementation, calculating the ratio of the net profits and revenue corresponding to each compliance decision implementation, obtaining profit rates corresponding to each compliance decision implementation, respectively marking the profit rates as R 'and R', and calculating the profit rates according to a calculation formula Obtaining a corresponding profit margin change rate R i after implementation of each compliance decision;
a3, sending a questionnaire through design, so as to collect and obtain satisfaction scores of clients for implementation of all compliance decisions, and carrying out mean value calculation on the collected satisfaction scores corresponding to all compliance decisions, so as to obtain the corresponding client satisfaction scores after implementation of all compliance decisions.
Preferably, the calculating obtains the corresponding business impact evaluation coefficient of the appointed enterprise after implementing the compliance decision, and the specific calculating process is as follows: substituting the sales change rate, profit margin change rate and customer satisfaction score corresponding to the compliance decision implementation into a calculation formulaObtaining corresponding business influence evaluation coefficients beta i of the appointed enterprises after the implementation of the compliance decisions, wherein M i、Ri、Qi respectively represents sales volume change rate, profit margin change rate and customer satisfaction degree score corresponding to the appointed enterprises after the implementation of the ith compliance decision, M ', R ' and Q ' respectively represent set standard sales volume change rate, standard profit margin change rate and standard customer satisfaction degree score,、、The weight factors corresponding to the set sales rate change rate, the weight factors corresponding to the profit rate change rate and the weight factors corresponding to the customer satisfaction degree scores are respectively adopted.
Preferably, the calculation obtains a risk assessment coefficient corresponding to the specified enterprise after implementing each compliance decision, and the specific calculation process is as follows: by the calculation formula: The risk assessment coefficients psi i corresponding to the specified enterprises after implementing the compliance decisions are obtained, i is the number corresponding to the compliance decisions, i=1, 2, … …, n, i is any integer greater than 2, wherein E i、Fi respectively represents the technical investment proportion and employee departure rate corresponding to the specified enterprises after implementing the i-th compliance decisions, E 'and F' are respectively set standard technical investment proportion and standard employee departure rate, and mu 1、μ2 is a weight factor corresponding to the set technical investment proportion and a weight factor corresponding to the employee departure rate.
Preferably, the analysis obtains a comprehensive evaluation coefficient corresponding to the specified enterprise after implementation of each compliance decision, and the specific analysis process is as follows: business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried out, and risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried outAnd obtaining a comprehensive evaluation coefficient x i corresponding to the specified enterprise after the implementation of each compliance decision, wherein beta i、Ψi represents a business impact evaluation coefficient and a risk evaluation coefficient corresponding to the specified enterprise after the implementation of the ith compliance decision, and pi 1、π2 is a weight factor corresponding to the set business impact evaluation coefficient and a weight factor corresponding to the risk evaluation coefficient respectively.
Preferably, the analysis specifies whether each compliance decision implementation of the enterprise meets the enterprise development requirements, and the specific analysis process is as follows: comparing the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision with a set comprehensive evaluation coefficient threshold, judging that the implementation of the compliance decision of the specified enterprise does not meet the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is greater than or equal to the set comprehensive evaluation coefficient threshold, and judging that the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is less than the set comprehensive evaluation coefficient threshold, so as to analyze whether the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement.
The present invention provides in a second aspect an intelligent enterprise decision system based on a large model, comprising: the system comprises an enterprise decision analysis module, a business influence evaluation module, a risk evaluation module, a comprehensive influence analysis module and an early warning terminal.
The enterprise decision analysis module is used for guiding various decisions made by the designated enterprise according to the successfully trained designated model, analyzing decision accuracy parameters corresponding to various decisions of the designated enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy assessment coefficients corresponding to various decisions made by the designated enterprise, so that whether various decision accuracy made by the designated enterprise based on the designated model meets the application requirements of the designated enterprise is analyzed.
And the business impact assessment module is used for marking various decisions meeting the application requirements of the appointed enterprise as various compliance decisions when the accuracy of certain decisions made by the appointed enterprise based on the appointed model meets the application requirements of the appointed enterprise, analyzing the impact of various compliance decisions made by the appointed enterprise on the business, wherein the impact comprises corresponding sales rate change rate and profit margin change rate after various decisions are implemented and customer satisfaction degree scoring, and further analyzing and obtaining corresponding business impact assessment coefficients of the appointed enterprise after various decisions are implemented.
The risk assessment module is used for acquiring corresponding risk information of the appointed enterprise after various decisions are implemented in real time, wherein the risk information comprises market share changes of competitors and financial condition indexes of suppliers, and further analyzing and obtaining corresponding risk assessment coefficients of the appointed enterprise after various decisions are implemented.
The comprehensive influence analysis module is used for analyzing and obtaining the comprehensive evaluation coefficients corresponding to the designated enterprises after various decisions are implemented according to the business influence evaluation coefficients corresponding to the designated enterprises after various decisions are implemented and the risk evaluation coefficients corresponding to the designated enterprises after various decisions are implemented, so that whether various decision implementations of the designated enterprises meet the enterprise development requirements or not is analyzed.
And the early warning terminal is used for carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the enterprise development requirement when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirement of the appointed enterprise.
The invention has the beneficial effects that: 1. according to the intelligent enterprise decision-making method and system based on the large model, the decision-making accuracy parameters are evaluated, the accuracy of enterprise decision making can be objectively measured, potential decision-making problems can be recognized by enterprises, timely adjustment and optimization are facilitated, decision-making is guaranteed to meet business requirements and expected targets, the accuracy of decision-making is facilitated to be objectively evaluated, reference is provided for subsequent decision-making, influences on business after decision-making implementation are analyzed, the sales rate change rate, profit rate change rate and customer satisfaction degree score are included, the effect of enterprises on a business level is facilitated to be known, the enterprise optimization decision-making scheme can be facilitated, business performance and customer satisfaction degree are improved, and long-term sustainable development is achieved.
2. According to the embodiment of the invention, through evaluating the risk information which possibly exists after the decision is implemented, such as the technical investment proportion and the employee departure rate, the enterprise manager is helped to comprehensively know the potential risk brought by the decision, the risk management measures are adopted in advance, the robustness of the enterprise in the decision execution process is guaranteed, through comprehensively evaluating the coefficient and combining the business influence evaluation and the risk evaluation, the effect and the risk of the decision can be comprehensively considered, the enterprise is helped to make a more comprehensive and balanced decision, the enterprise is helped to find a balance point, and the positive business influence and the risk control can be brought after the decision is implemented.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the steps of the present invention.
FIG. 2 is a schematic diagram of the system structure of 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.
Referring to fig. 1, the present invention provides an intelligent enterprise decision method based on a large model, which includes: step one, enterprise decision analysis: according to a successfully trained appointed model, guiding an appointed enterprise to make various decisions, analyzing decision accuracy parameters corresponding to various decisions of the appointed enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy evaluation coefficients corresponding to various decisions of the appointed enterprise, so that whether various decision accuracy of the appointed enterprise based on the appointed model meets application requirements of the appointed enterprise is analyzed.
It should be noted that, according to the expected targets and results, various decisions made by the designated enterprises are evaluated, the situations after the various decisions are implemented are recorded, the results of the various decisions are marked as success or failure, the number of the successful decisions is counted, and according to the total number of the various decisions, the number of the successful decisions is divided by the total number of the decisions, so that the accuracy corresponding to the various decisions of the designated enterprises is obtained;
Determining whether the decision meets the expected standard, for example, judging whether the decision meets the expected or not according to a preset target or standard, evaluating each decision made by the appointed enterprise, judging whether the decision meets the expected or not, counting the number of the decisions meeting the expected, dividing the number of the decisions expected by the symbol by the total number of the decisions, and obtaining the corresponding accuracy of various decisions of the appointed enterprise;
Determining the standard or definition of correct decisions, for example, judging whether the decisions are correct or not according to the actual results, evaluating each decision made by the appointed enterprise, judging whether the decisions are correct decisions according to the defined correct standard, counting the number of the correct decisions, dividing the number of the correct decisions by the total number of the decisions, and obtaining recall rates corresponding to various decisions of the appointed enterprise.
In a specific embodiment, the calculation obtains the decision accuracy evaluation coefficients corresponding to various decisions of the designated enterprise, and the specific calculation process is as follows: substituting the accuracy, precision and recall rate corresponding to various decisions of a designated enterprise into a calculation formulaThe decision accuracy evaluation coefficients alpha i corresponding to various decisions of a designated enterprise are obtained, i is a number corresponding to various decisions, i=1, 2, … …, n, i is any integer greater than 2, wherein A i、Bi、Ci respectively represents the accuracy, precision and recall rate corresponding to the ith decision of the designated enterprise, A ', B ', C ' respectively represent the set standard accuracy, standard precision and standard recall rate, and eta 1、η2、η3 respectively represent the weight factor corresponding to the set accuracy, the weight factor corresponding to the precision and the weight factor corresponding to the recall rate.
Note that η 1、η2、η3 has values greater than 0 and less than 1.
It should be further noted that, according to decision scenes and business targets corresponding to the designated enterprises, actual data and historical performances, determining expected accuracy, precision and recall targets, and comparing and referencing by combining industry standards and competitor performances, and finally, making reasonable trade-off and adjustment according to actual conditions and resource conditions, so as to ensure that the standard accuracy, standard precision and standard recall set by the designated enterprises meet the actual demands of the enterprises;
Setting a weight vector W= [ W1, W2, W3], wherein W1, W2, W3 respectively represent weights corresponding to accuracy, precision and recall, setting a comprehensive evaluation index K, and calculating according to the weight vector W, wherein the comprehensive evaluation index is specifically expressed as Tp, tn, fp, fn represents a real example, a true negative example, a false positive example and a false negative example respectively, and uses a gradient descent method to optimize an objective function K, and under the condition of given training data and verification data sets, the value of a weight vector W is adjusted to optimize a comprehensive evaluation index K, so that the setting of a weight factor corresponding to the optimal accuracy, a weight factor corresponding to the precision and a weight factor corresponding to the recall rate is determined.
In a specific embodiment, the analysis indicates whether the accuracy of various decisions made by the enterprise based on the specified model meets the application requirements of the specified enterprise, and the specific analysis process is as follows: comparing the decision accuracy evaluation coefficients corresponding to various decisions of the designated enterprises with a set decision accuracy evaluation coefficient threshold, if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is larger than or equal to the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises, and if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is smaller than the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models does not meet the application requirements of the designated enterprises, so as to analyze whether the various decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises.
Step two, evaluating business influence: when the accuracy of a certain decision made by a designated enterprise based on a designated model meets the application requirements of the designated enterprise, various decisions meeting the application requirements of the designated enterprise are recorded as compliance decisions, the influence on the service after the implementation of the compliance decisions made by the designated enterprise is analyzed, the influence comprises the corresponding sales change rate and profit margin change rate after the implementation of the compliance decisions and the customer satisfaction degree score, and further the corresponding service influence evaluation coefficient of the designated enterprise after the implementation of the compliance decisions is calculated.
In a specific embodiment, the analysis specifies the impact of compliance decisions made by the enterprise on the business, and the specific analysis process is as follows: a1, acquiring sales data before and after implementation of each compliance decision from a sales system and transaction records of a designated enterprise, respectively marking sales before and after implementation of each compliance decision as M i'、Mi '', wherein i is a number corresponding to each compliance decision, i=1, 2, … …, n and i are any integers greater than 2, and calculating a formula by using the sales dataObtaining corresponding sales change rate M i after implementation of each compliance decision;
A2, acquiring financial data before and after decision implementation from financial reports, accounting records and management systems of specified enterprises, wherein the financial data comprises business income, sales cost and operation cost, so as to obtain net profits and revenue corresponding to each compliance decision implementation, calculating the ratio of the net profits and revenue corresponding to each compliance decision implementation, obtaining profit rates corresponding to each compliance decision implementation, respectively marking the profit rates as R 'and R', and calculating the profit rates according to a calculation formula Obtaining a corresponding profit margin change rate R i after implementation of each compliance decision;
a3, sending a questionnaire through design, so as to collect and obtain satisfaction scores of clients for implementation of all compliance decisions, and carrying out mean value calculation on the collected satisfaction scores corresponding to all compliance decisions, so as to obtain the corresponding client satisfaction scores after implementation of all compliance decisions.
Note that M i is 0 or more and r i is 0 or more.
In a specific embodiment, the calculating obtains the corresponding business impact evaluation coefficient of the designated enterprise after implementing each compliance decision, and the specific calculating process is as follows: substituting the sales change rate, profit margin change rate and customer satisfaction score corresponding to the compliance decision implementation into a calculation formulaObtaining corresponding business influence evaluation coefficients beta i of the appointed enterprises after the implementation of the compliance decisions, wherein M i、Ri、Qi respectively represents sales volume change rate, profit margin change rate and customer satisfaction degree score corresponding to the appointed enterprises after the implementation of the ith compliance decision, M ', R ' and Q ' respectively represent set standard sales volume change rate, standard profit margin change rate and standard customer satisfaction degree score,、、The weight factors corresponding to the set sales rate change rate, the weight factors corresponding to the profit rate change rate and the weight factors corresponding to the customer satisfaction degree scores are respectively adopted.
It should be noted that the number of the substrates,、、The values of (2) are all more than 0 and less than 1.
It should be further noted that, according to the goals and expectations of the appointed enterprises in sales increase, profit margin improvement and customer satisfaction, analyzing industry standards and competitor performances, making reasonable reference values, setting sales rate change, profit margin change and customer satisfaction score according to the own conditions and resource limitation of the appointed enterprises, and finally, through internal evaluation and verification, adjusting and optimizing according to actual conditions, so as to obtain standard sales rate change, standard profit margin change and standard customer satisfaction score which are suitable for the appointed enterprises' goals and market environments;
And finally, verifying through data simulation and actual performance to obtain a final sales volume change rate corresponding weight factor, a profit rate change rate corresponding weight factor and a customer satisfaction degree scoring corresponding weight factor.
Step three, risk assessment: and acquiring corresponding risk information of the appointed enterprise after implementing each compliance decision, wherein the risk information comprises a technical investment proportion and an employee departure rate, and further calculating to obtain a corresponding risk assessment coefficient of the appointed enterprise after implementing each compliance decision.
It should be noted that, by querying financial reports corresponding to various decision implementations of the designated enterprises, and checking project budget and expense approval records of the designated enterprises, total expenses of the designated enterprises are obtained, and total expenses for technical investment including research and development expenses, technical equipment acquisition expenses, technical personnel training expenses and the like are counted when various decision implementations are performed, so as to obtain technical investment expenses, and the technical investment is pointed out to be in the total expenses of the designated enterprises, so as to obtain corresponding technical investment proportions after various decision implementations;
Obtaining an off-job data report from a designated enterprise personnel department, wherein the report comprises specific information of off-job staff and off-job date, counting the number of staff corresponding to each decision before and after implementation and the number of on-job staff corresponding to each decision during implementation, and dividing the number of off-job staff by the average number of on-job staff to obtain corresponding staff off-job rates after each decision is implemented.
In a specific embodiment, the calculation obtains the risk assessment coefficient corresponding to the specified enterprise after implementing each compliance decision, and the specific calculation process is as follows: by calculation formulaThe risk assessment coefficients psi i corresponding to the specified enterprises after implementing the compliance decisions are obtained, i is the number corresponding to the compliance decisions, i=1, 2, … …, n, i is any integer greater than 2, wherein E i、Fi respectively represents the technical investment proportion and employee departure rate corresponding to the specified enterprises after implementing the i-th compliance decisions, E 'and F' are respectively set standard technical investment proportion and standard employee departure rate, and mu 1、μ2 is a weight factor corresponding to the set technical investment proportion and a weight factor corresponding to the employee departure rate.
Note that, the values of μ 1、μ2 are all greater than 0 and less than 1.
The method is characterized in that the importance and influence factors of the technical investment proportion are determined according to the strategic planning of enterprises and the technical development requirements, the conditions of the technical investment proportion of industry standards and competitors are considered, the enterprise scale and the development stage are combined, and finally, the set standard technical investment proportion and standard employee departure rate are obtained through human resource analysis and employee feedback;
and finally, verifying through actual business influence simulation and data analysis, thereby obtaining a weight factor corresponding to the set technical investment proportion and a weight factor corresponding to the employee departure rate.
Step four, comprehensive influence analysis: and according to the business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions and the risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, further analyzing to obtain the comprehensive evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, and further analyzing whether the implementation of the compliance decisions of the appointed enterprises meets the enterprise development requirements or not.
In a specific embodiment, the analysis obtains the comprehensive evaluation coefficients corresponding to the specified enterprise after implementation of each compliance decision, and the specific analysis process is as follows: business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried out, and risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried outAnd obtaining a comprehensive evaluation coefficient x i corresponding to the specified enterprise after the implementation of each compliance decision, wherein beta i、Ψi represents a business impact evaluation coefficient and a risk evaluation coefficient corresponding to the specified enterprise after the implementation of the ith compliance decision, and pi 1、π2 is a weight factor corresponding to the set business impact evaluation coefficient and a weight factor corresponding to the risk evaluation coefficient respectively.
It should be noted that pi 1、π2 has a value of more than 0 and less than 1.
In a specific embodiment, the analysis specifies whether each compliance decision implementation of the enterprise meets the enterprise development requirements, and the specific analysis process is as follows: comparing the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision with a set comprehensive evaluation coefficient threshold, judging that the implementation of the compliance decision of the specified enterprise does not meet the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is greater than or equal to the set comprehensive evaluation coefficient threshold, and judging that the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is less than the set comprehensive evaluation coefficient threshold, so as to analyze whether the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement.
It should be further noted that, through communication with the business department and the risk management team corresponding to the designated enterprise, the business impact assessment coefficient and the weight preference of the risk assessment coefficient are obtained, according to the strategic target and the risk bearing capacity corresponding to the designated enterprise, the weighting and investigation of the assessment coefficient weight are performed, and finally, through the risk simulation analysis and the business impact prediction, the verification is performed, so as to obtain the weight factor corresponding to the business impact assessment coefficient and the weight factor corresponding to the risk assessment coefficient.
According to the embodiment of the invention, through evaluating the risk information which possibly exists after the decision is implemented, such as the technical investment proportion and the employee departure rate, the enterprise manager is helped to comprehensively know the potential risk brought by the decision, the risk management measures are adopted in advance, the robustness of the enterprise in the decision execution process is guaranteed, through comprehensively evaluating the coefficient and combining the business influence evaluation and the risk evaluation, the effect and the risk of the decision can be comprehensively considered, the enterprise is helped to make a more comprehensive and balanced decision, the enterprise is helped to find a balance point, and the positive business influence and the risk control can be brought after the decision is implemented.
Step five, early warning prompting: and when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirements of the appointed enterprise, carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the development requirements of the enterprise.
Referring to fig. 2, an intelligent enterprise decision system based on a large model includes the following modules: the system comprises an enterprise decision analysis module, a business influence evaluation module, a risk evaluation module, a comprehensive influence analysis module and an early warning terminal.
The enterprise decision analysis module is used for guiding various decisions made by the designated enterprise according to the successfully trained designated model, analyzing decision accuracy parameters corresponding to various decisions of the designated enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy assessment coefficients corresponding to various decisions made by the designated enterprise, so that whether various decision accuracy made by the designated enterprise based on the designated model meets the application requirements of the designated enterprise is analyzed.
And the business impact assessment module is used for marking various decisions meeting the application requirements of the appointed enterprise as various compliance decisions when the accuracy of certain decisions made by the appointed enterprise based on the appointed model meets the application requirements of the appointed enterprise, analyzing the impact of various compliance decisions made by the appointed enterprise on the business, wherein the impact comprises corresponding sales rate change rate and profit margin change rate after various decisions are implemented and customer satisfaction degree scoring, and further analyzing and obtaining corresponding business impact assessment coefficients of the appointed enterprise after various decisions are implemented.
The risk assessment module is used for acquiring corresponding risk information of the appointed enterprise after various decisions are implemented in real time, wherein the risk information comprises market share changes of competitors and financial condition indexes of suppliers, and further analyzing and obtaining corresponding risk assessment coefficients of the appointed enterprise after various decisions are implemented.
The comprehensive influence analysis module is used for analyzing and obtaining the comprehensive evaluation coefficients corresponding to the designated enterprises after various decisions are implemented according to the business influence evaluation coefficients corresponding to the designated enterprises after various decisions are implemented and the risk evaluation coefficients corresponding to the designated enterprises after various decisions are implemented, so that whether various decision implementations of the designated enterprises meet the enterprise development requirements or not is analyzed.
And the early warning terminal is used for carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the enterprise development requirement when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirement of the appointed enterprise.
According to the intelligent enterprise decision-making method and system based on the large model, the decision-making accuracy parameters are evaluated, the accuracy of enterprise decision making can be objectively measured, potential decision-making problems can be recognized by enterprises, timely adjustment and optimization are facilitated, decision-making is guaranteed to meet business requirements and expected targets, the accuracy of decision-making is facilitated to be objectively evaluated, reference is provided for subsequent decision-making, influences on business after decision-making implementation are analyzed, the sales rate change rate, profit rate change rate and customer satisfaction degree score are included, the effect of enterprises on a business level is facilitated to be known, the enterprise optimization decision-making scheme can be facilitated, business performance and customer satisfaction degree are improved, and long-term sustainable development is achieved.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of the invention or beyond the scope of the invention as defined in the description.
Claims (9)
1. An intelligent enterprise decision method based on a large model is characterized by comprising the following steps:
Step one, enterprise decision analysis: according to a successfully trained appointed model, guiding an appointed enterprise to make various decisions, analyzing decision accuracy parameters corresponding to various decisions of the appointed enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy evaluation coefficients corresponding to various decisions of the appointed enterprise, so that whether the accuracy of various decisions made by the appointed enterprise based on the appointed model meets application requirements of the appointed enterprise is analyzed;
Step two, evaluating business influence: when the accuracy of a certain decision made by a designated enterprise based on a designated model meets the application requirements of the designated enterprise, marking various decisions meeting the application requirements of the designated enterprise as compliance decisions, analyzing the influence on the service after the implementation of the compliance decisions made by the designated enterprise, wherein the influence comprises the sales change rate and profit rate change rate corresponding to the implementation of the compliance decisions and the customer satisfaction degree score, and further calculating to obtain the service influence evaluation coefficient corresponding to the designated enterprise after the implementation of the compliance decisions;
Step three, risk assessment: acquiring corresponding risk information of the appointed enterprise after implementing each compliance decision, wherein the risk information comprises a technical investment proportion and an employee departure rate, and further calculating to obtain a corresponding risk assessment coefficient of the appointed enterprise after implementing each compliance decision;
Step four, comprehensive influence analysis: according to the business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions and the risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, further analyzing to obtain the comprehensive evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions, and further analyzing whether the implementation of the compliance decisions of the appointed enterprises meets the enterprise development requirements or not;
step five, early warning prompting: and when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirements of the appointed enterprise, carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the development requirements of the enterprise.
2. The intelligent enterprise decision-making method based on the large model as claimed in claim 1, wherein the calculation is to obtain decision accuracy evaluation coefficients corresponding to various decisions of the designated enterprise, and the specific calculation process is as follows:
Substituting the accuracy, precision and recall rate corresponding to various decisions of a designated enterprise into a calculation formula The decision accuracy evaluation coefficients alpha j and j corresponding to various decisions of a designated enterprise are obtained, j is a number corresponding to each compliance decision, j=1, 2, … …, m and j are any integer greater than 2, wherein A j、Bj、Cj respectively represents the accuracy, the precision and the recall rate corresponding to the j-th decision of the designated enterprise, A ', B ', C ' respectively represent the set standard accuracy, standard precision and standard recall rate, and eta 1、η2、η3 respectively represent the weight factor corresponding to the set accuracy, the weight factor corresponding to the precision and the weight factor corresponding to the recall rate.
3. The intelligent enterprise decision-making method based on large model as claimed in claim 2, wherein the analysis of whether the accuracy of various decisions made by the designated enterprise based on the designated model meets the application requirements of the designated enterprise is as follows:
Comparing the decision accuracy evaluation coefficients corresponding to various decisions of the designated enterprises with a set decision accuracy evaluation coefficient threshold, if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is larger than or equal to the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises, and if the decision accuracy evaluation coefficient corresponding to a certain decision of the designated enterprises is smaller than the set decision accuracy evaluation coefficient threshold, judging that the decision accuracy of the designated enterprises based on the designated models does not meet the application requirements of the designated enterprises, so as to analyze whether the various decision accuracy of the designated enterprises based on the designated models meets the application requirements of the designated enterprises.
4. The intelligent enterprise decision method based on large model as claimed in claim 1, wherein the analysis designates the influence of each compliance decision made by the enterprise on the business, and the specific analysis process is as follows:
A1, acquiring sales data before and after implementation of each compliance decision from a sales system and transaction records of a designated enterprise, respectively marking sales before and after implementation of each compliance decision as M i'、Mi '', wherein i is a number corresponding to each compliance decision, i=1, 2, … …, n and i are any integers greater than 2, and calculating a formula by using the sales data Obtaining corresponding sales change rate M i after implementation of each compliance decision;
A2, acquiring financial data before and after decision implementation from financial reports, accounting records and management systems of specified enterprises, wherein the financial data comprises business income, sales cost and operation cost, so as to obtain net profits and revenue corresponding to each compliance decision implementation, calculating the ratio of the net profits and revenue corresponding to each compliance decision implementation, obtaining profit rates corresponding to each compliance decision implementation, respectively marking the profit rates as R 'and R', and calculating the profit rates according to a calculation formula Obtaining a corresponding profit margin change rate R i after implementation of each compliance decision;
a3, sending a questionnaire through design, so as to collect and obtain satisfaction scores of clients for implementation of all compliance decisions, and carrying out mean value calculation on the collected satisfaction scores corresponding to all compliance decisions, so as to obtain the corresponding client satisfaction scores after implementation of all compliance decisions.
5. The intelligent enterprise decision-making method based on the large model as claimed in claim 4, wherein the calculation is to obtain the business impact evaluation coefficient corresponding to the specified enterprise after each compliance decision is implemented, and the specific calculation process is as follows:
Substituting the sales change rate, profit margin change rate and customer satisfaction score corresponding to the compliance decision implementation into a calculation formula Obtaining corresponding business influence evaluation coefficients beta i of the appointed enterprises after the implementation of the compliance decisions, wherein M i、Ri、Qi respectively represents sales volume change rate, profit margin change rate and customer satisfaction degree score corresponding to the appointed enterprises after the implementation of the ith compliance decision, M ', R ' and Q ' respectively represent set standard sales volume change rate, standard profit margin change rate and standard customer satisfaction degree score,、、The weight factors corresponding to the set sales rate change rate, the weight factors corresponding to the profit rate change rate and the weight factors corresponding to the customer satisfaction degree scores are respectively adopted.
6. The intelligent enterprise decision-making method based on the large model as claimed in claim 1, wherein the calculation results in risk assessment coefficients corresponding to the specified enterprise after implementing each compliance decision, and the specific calculation process is as follows: The risk assessment coefficients psi i corresponding to the specified enterprises after implementing the compliance decisions are obtained, i is the number corresponding to the compliance decisions, i=1, 2, … …, n, i is any integer greater than 2, wherein E i、Fi respectively represents the technical investment proportion and employee departure rate corresponding to the specified enterprises after implementing the i-th compliance decisions, E 'and F' are respectively set standard technical investment proportion and standard employee departure rate, and mu 1、μ2 is a weight factor corresponding to the set technical investment proportion and a weight factor corresponding to the employee departure rate.
7. The intelligent enterprise decision-making method based on the large model as claimed in claim 6, wherein the analysis obtains the comprehensive evaluation coefficients corresponding to the specified enterprise after the implementation of the compliance decision, and the specific analysis process is as follows:
business influence evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried out, and risk evaluation coefficients corresponding to the appointed enterprises after the implementation of the compliance decisions are carried out And obtaining a comprehensive evaluation coefficient x i corresponding to the specified enterprise after the implementation of each compliance decision, wherein beta i、Ψi represents a business impact evaluation coefficient and a risk evaluation coefficient corresponding to the specified enterprise after the implementation of the ith compliance decision, and pi 1、π2 is a weight factor corresponding to the set business impact evaluation coefficient and a weight factor corresponding to the risk evaluation coefficient respectively.
8. The intelligent enterprise decision making method based on large model as claimed in claim 7, wherein the analysis specifies whether each compliance decision implementation of the enterprise meets the enterprise development requirement, and the specific analysis process is as follows:
Comparing the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision with a set comprehensive evaluation coefficient threshold, judging that the implementation of the compliance decision of the specified enterprise does not meet the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is greater than or equal to the set comprehensive evaluation coefficient threshold, and judging that the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement if the comprehensive evaluation coefficient corresponding to the specified enterprise after the implementation of the compliance decision is less than the set comprehensive evaluation coefficient threshold, so as to analyze whether the implementation of the compliance decision of the specified enterprise meets the enterprise development requirement.
9. A large model based intelligent enterprise decision system for performing the large model based intelligent enterprise decision method of any one of claims 1-8, comprising the following modules:
The enterprise decision analysis module is used for guiding various decisions made by the designated enterprise according to the successfully trained designated model, analyzing decision accuracy parameters corresponding to various decisions of the designated enterprise, wherein the decision accuracy parameters comprise accuracy, precision and recall rate, and further calculating to obtain decision accuracy assessment coefficients corresponding to various decisions made by the designated enterprise, so that whether various decision accuracy made by the designated enterprise based on the designated model meets the application requirements of the designated enterprise is analyzed;
The business impact assessment module is used for marking various decisions meeting the application requirements of the appointed enterprise as various compliance decisions when certain decision accuracy of the appointed enterprise based on the appointed model meets the application requirements of the appointed enterprise, analyzing the impact of various compliance decisions made by the appointed enterprise on the business, wherein the impact comprises sales change rate and profit margin change rate corresponding to various decisions after implementation and customer satisfaction degree scoring, and further analyzing and obtaining business impact assessment coefficients corresponding to the appointed enterprise after various decisions are implemented;
The risk assessment module is used for acquiring corresponding risk information of the appointed enterprise after various decisions are implemented in real time, wherein the risk information comprises market share changes of competitors and financial condition indexes of suppliers, and further analyzing and obtaining corresponding risk assessment coefficients of the appointed enterprise after various decisions are implemented;
The comprehensive influence analysis module is used for analyzing and obtaining the comprehensive evaluation coefficients corresponding to the designated enterprises after various decisions are implemented according to the business influence evaluation coefficients corresponding to the designated enterprises after various decisions are implemented and the risk evaluation coefficients corresponding to the designated enterprises after various decisions are implemented, so that whether various decision implementations of the designated enterprises meet the enterprise development requirements or not is analyzed;
And the early warning terminal is used for carrying out early warning prompt when the implementation of a certain compliance decision of the appointed enterprise does not meet the enterprise development requirement when the accuracy of a certain decision made by the appointed enterprise based on the appointed model does not meet the application requirement of the appointed enterprise.
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