Enterprise condition analysis method based on enterprise key index dynamic identification

Abstract

The invention discloses an enterprise condition analysis method based on dynamic identification of enterprise key indexes, which belongs to the technical field of enterprise index analysis and comprises the key steps of constructing an enterprise index library, constructing an index criticality evaluation model, scoring index criticality, screening key indexes and the like. Therefore, dynamic identification of enterprise key indexes is realized. According to the method, the key of each index of each enterprise is dynamically analyzed and evaluated from factors such as enterprise internal factors, target influence factors and abnormal factors, and the indexes of each enterprise are comprehensively scored in combination with a dynamic weight adjustment mechanism, so that the most important top index of each enterprise in the current stage is dynamically screened; therefore, the personalized and real-time monitoring and supervision requirements of the supervision mechanism on the enterprise can be better met.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise indicator analysis, and in particular relates to an enterprise situation analysis method based on dynamic identification of enterprise key indicators. Background Art

[0002] Key enterprise indicators are a set of selected indicators that an enterprise uses to measure its operating status, performance or achievement of strategic goals. These indicators are critical to the enterprise's decision-making and can provide deep insights into the health of the business.

[0003] In the current digital economy era, the evaluation and monitoring of key enterprise indicators are facing unprecedented challenges. Traditional evaluation systems are often based on static templates and expert experience, which are difficult to keep up with the rapid changes in the market environment and the dynamic adjustment of corporate strategies, resulting in limited timeliness and accuracy of evaluation results. For example, in traditional regulatory methods, regulators usually use fixed regulatory indicators to monitor the operating conditions and risk situations of enterprises. However, different enterprises have unique characteristics and needs, and enterprises at different stages also have different operational problems. Fixed regulatory indicators cannot accurately reflect the individual situation of enterprises. Summary of the invention

[0004] The purpose of the present invention is to provide an enterprise situation analysis method based on dynamic identification of key enterprise indicators, so as to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for analyzing enterprise conditions based on dynamic identification of key enterprise indicators, the method comprising:

[0007] Step 1: Build an enterprise indicator database: collect internal and external data related to the enterprise, clean and organize it, and build an enterprise indicator database;

[0008] Step 2: Construct an indicator criticality evaluation model: Based on the enterprise data in the enterprise indicator database, construct an indicator evaluation model V that combines the internal factor score, the target influencing factor score, and the abnormal factor score;

[0009] Step 3: Indicator criticality scoring: Based on the constructed indicator evaluation model and according to changes in the market and operating environment, assign corresponding weights to each enterprise indicator to perform criticality scoring on each enterprise indicator;

[0010] Step 4: Key indicator screening: Based on the criticality scores of each enterprise indicator, screen out the top-ranked key indicators and apply them to the enterprise's decision-making process.

[0011] Furthermore, the method for constructing the enterprise indicator database in step 1 is:

[0012] Collect internal and external data of the enterprise, including financial, operational, market and other data, to form an initial data set;

[0013] Clean the data, eliminate noise and missing values, and standardize the data to obtain the processed data set;

[0014] Select potential indicators according to enterprise goals and plans, thereby constructing a list of potential indicators, and classify each indicator to obtain a classified enterprise indicator database;

[0015] Regularly update and maintain the enterprise indicator database by adding new indicators and deleting indicators that are no longer applicable.

[0016] Furthermore, the method for constructing the indicator evaluation model in step 2 is:

[0017] Set a detection cycle, and obtain the intrinsic factor score value X, the target influencing factor score value B, and the abnormal factor score value R within the detection cycle;

[0018] Thus, the indicator evaluation model V is constructed through the formula V = α*X + β*B + δ*R;

[0019] Among them, α, β and δ are preset weight coefficients of each score value.

[0020] Furthermore, the method for obtaining the intrinsic factor score value X is:

[0021] At each detection cycle, all possible values ​​x1, x2, ..., x of each enterprise indicator are listed from the enterprise indicator database. n , and based on historical data and sample data, the probability P(x i );

[0022] At the same time, in this detection cycle, the indicator value k of each enterprise indicator is obtained every day j , so that through the formula Obtain the fluctuation coefficient σ of the enterprise indicator within the detection period;

[0023] Then through the formula Obtain the intrinsic factor score X of each enterprise indicator;

[0024] Among them, n is the total number of possible values, m is the total number of days in the detection period, and k j The index value k obtained on the jth day j .

[0025] Furthermore, the method for obtaining the target influencing factor score value B is:

[0026] Obtain the degree of fit between the enterprise indicator and the strategic goal during the detection period B r 、Contribution B g , and the performance value B under this indicator h 、Customer satisfaction B c ;

[0027] So through the formula Obtain the target influencing factor score B;

[0028] Among them, B in is the number of employees joining the company during the testing period, B out is the number of employees who left during the detection period, B th The default performance value.

[0029] Furthermore, the method for obtaining the abnormal factor score value R is:

[0030] Get the time-varying curve K(t) of each enterprise indicator value within the detection period, and get the number of positive reviews Q for the enterprise indicator within the detection period. g And the number of negative reviews Q b ;

[0031] By formula Obtain the abnormal factor score R;

[0032] Among them, γ1 and γ2 are preset coefficients, K0(t) is the time-varying curve of the standard enterprise index value set during the detection period, and K K is the average value of each enterprise indicator in the same historical detection period, t a is the start time of the detection cycle, t b The end time of the detection cycle.

[0033] Furthermore, the method for performing critical scoring on each enterprise indicator in step 3 is:

[0034] Obtain the indicator data of each enterprise and bring it into the corresponding indicator evaluation model V, so as to obtain the critical score G corresponding to each enterprise indicator through the formula GF=V*μ;

[0035] Among them, μ is the corresponding weight assigned to each enterprise indicator.

[0036] Furthermore, the method of assigning the corresponding weights to the enterprise indicators in step 3 is:

[0037] Define corresponding fuzzy sets for each enterprise indicator according to changes in the market and operating environment;

[0038] Based on empirical data and historical operating data, a fuzzy relationship matrix between various enterprise indicators is constructed;

[0039] The membership degree of each enterprise index is calculated using fuzzy mathematics method, and the comprehensive evaluation result is obtained through synthetic fuzzy matrix algorithm;

[0040] The obtained fuzzy comprehensive evaluation results are transformed into clear results, thus obtaining the weights of each enterprise indicator.

[0041] Beneficial effects of the present invention:

[0042] The present invention realizes the dynamic identification of key indicators of enterprises by constructing enterprise indicator library, constructing indicator key evaluation model, indicator key scoring, dynamic weight adjustment and key indicator screening and application. It not only improves the timeliness, objectivity and pertinence of enterprise key indicator evaluation, but also provides strong support for the intelligent operation of enterprises and the intelligent supervision of regulatory agencies.

[0043] The present invention dynamically analyzes and evaluates the criticality of each indicator of each enterprise based on the indicator data of the enterprise's historical years and different time dimensions, and from the perspectives of enterprise internal factors, target influencing factors, abnormal factors, etc., combines the dynamic weight adjustment mechanism to comprehensively score the indicators of each enterprise, and dynamically screens the most important top indicators of each enterprise at the current stage, so as to better meet the regulatory authorities' needs for personalized, real-time monitoring and supervision of enterprises.

[0044] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0046] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] In one embodiment, a method for analyzing enterprise conditions based on dynamic identification of key enterprise indicators is disclosed, such as Figure 1 As shown, the analysis method includes:

[0049] Step 1: Build an enterprise indicator database: collect internal and external data related to the enterprise, clean and organize it, and build an enterprise indicator database;

[0050] Step 2: Construct an indicator criticality evaluation model: Based on the enterprise data in the enterprise indicator database, construct an indicator evaluation model V that combines the internal factor score, the target influencing factor score, and the abnormal factor score;

[0051] Step 3: Indicator criticality scoring: Based on the constructed indicator evaluation model and according to changes in the market and operating environment, assign corresponding weights to each enterprise indicator to perform criticality scoring on each enterprise indicator;

[0052] Step 4: Key indicator screening: Based on the criticality scores of each enterprise indicator, screen out the top-ranked key indicators and apply them to the enterprise's decision-making process.

[0053] Through the above technical solution, this application first collects internal and external data related to the enterprise, cleans and organizes it, builds an enterprise indicator database, and then builds an indicator evaluation model that combines the internal factor score, the target influencing factor score and the abnormal factor score based on the enterprise data in the enterprise indicator database. Based on the constructed indicator evaluation model, and according to the changes in the market and operating environment, the corresponding weights of each enterprise indicator are assigned to each enterprise indicator to perform a critical score for each enterprise indicator. Finally, according to the critical scores of each enterprise indicator obtained, the top-ranked key indicators are screened out and applied to the decision-making process of the enterprise, so as to achieve a dynamic evaluation of the key indicators of the enterprise. In this way, the indicator data of the enterprise in different time dimensions over the years can be used to dynamically analyze and evaluate the criticality of each indicator of each enterprise from the perspective of internal factors, target influencing factors and abnormal factors of the enterprise. Combined with the dynamic weight adjustment mechanism, each enterprise indicator is comprehensively scored, and the most important top indicators of each enterprise at the current stage are dynamically screened to better meet the regulatory agency's personalized, real-time monitoring and supervision needs of enterprises.

[0054] As an implementation mode of the present invention, the method for constructing the enterprise indicator database in step 1 is:

[0055] Collect internal and external data of the enterprise, including financial, operational, market and other data, to form an initial data set;

[0056] Clean the data, eliminate noise and missing values, and standardize the data to obtain the processed data set;

[0057] Select potential indicators according to enterprise goals and plans, thereby constructing a list of potential indicators, and classify each indicator to obtain a classified enterprise indicator database;

[0058] Regularly update and maintain the enterprise indicator database by adding new indicators and deleting indicators that are no longer applicable.

[0059] Through the above technical solution, this embodiment provides a specific method for establishing an enterprise indicator database. First, internal and external data of the enterprise, including financial, operational, market and other data, are collected to establish a data foundation, thereby forming an initial data set. Then, the data is cleaned, noise and missing values ​​are eliminated, and the data is standardized to ensure dimensional consistency, so as to obtain a processed data set. Then, potential indicators are selected according to the enterprise goals and strategic plans, so as to construct a potential indicator list, and the indicators are classified according to types, such as financial, operational, market, etc., to obtain a classified enterprise indicator database, which is convenient for managing and analyzing indicators. Finally, the enterprise indicator database is regularly updated, new indicators are added, and indicators that are no longer applicable are deleted to regularly update and maintain the enterprise indicator database to maintain the timeliness and accuracy of the indicator library. In this way, not only is the use of subsequent data convenient, but also the quality and availability of data can be ensured.

[0060] As an implementation of the present invention, the method for constructing the indicator criticality evaluation model in step 2 is:

[0061] Set a detection cycle, and obtain the intrinsic factor score value X, the target influencing factor score value B, and the abnormal factor score value R within the detection cycle;

[0062] Thus, the indicator evaluation model V is constructed through the formula V = α*X + β*B + δ*R;

[0063] Among them, α, β and δ are the preset weight coefficients of each score value;

[0064] The method for obtaining the internal factor score value X is as follows: every detection period, all possible values ​​x1, x2, ..., x2 of each enterprise indicator are listed from the enterprise indicator database. n , and based on historical data and sample data, the probability P(x i );

[0065] At the same time, in this detection cycle, the indicator value k of each enterprise indicator is obtained every day j , so that through the formula Obtain the fluctuation coefficient σ of the enterprise indicator within the detection period;

[0066] Then through the formula Obtain the intrinsic factor score X of each enterprise indicator;

[0067] Among them, n is the total number of possible values, m is the total number of days in the detection period, and k j The index value k obtained on the jth day j ;

[0068] The method for obtaining the target influencing factor score B is to obtain the degree of fit B between the enterprise indicator and the strategic goal during the detection period. r 、Contribution B g , and the performance value B under this indicator h 、Customer satisfaction B c ;

[0069] So through the formula Obtain the target influencing factor score B;

[0070] Among them, B in is the number of employees joining the company during the testing period, B out is the number of employees who left during the detection period, B th is the preset performance value;

[0071] The method for obtaining the abnormal factor score R is to obtain the time-varying curve K(t) of each enterprise indicator value within the detection period, and at the same time obtain the number of favorable comments Q of the enterprise indicator within the detection period. g And the number of negative reviews Q g ;

[0072] By formula Obtain the abnormal factor score R;

[0073] Among them, γ1 and γ2 are preset coefficients, K0(t) is the time-varying curve of the standard enterprise index value set during the detection period, and K K is the average value of each enterprise indicator in the same historical detection period, t a is the start time of the detection cycle, t b The end time of the detection cycle.

[0074] Through the above technical solution, this embodiment provides a specific method for constructing an indicator criticality evaluation model. Since the evaluation of enterprise indicators is closely related to factors such as enterprise internal factors, target influencing factors and abnormal factors, the internal factor score value X is first obtained, and every time a detection cycle, all possible values ​​x1, x2, ..., x of each enterprise indicator are listed from the enterprise indicator database. n , and based on historical data and sample data, the probability P(x i); At the same time, in this detection cycle, the index value k of each enterprise index is obtained every day j , so that through the formula The fluctuation coefficient σ of the enterprise indicator within the detection period is obtained; then the formula Obtain the intrinsic factor score X of each enterprise indicator; formula Indicates the amount of information about the company's indicators. Indicators with large amounts of information can provide more details about the company's situation and help to understand the company's operations more comprehensively. For example, financial indicators have a large amount of information, which means that the indicator can provide rich information and help the company better understand its financial situation and identify potential problems and opportunities. The formula It indicates the fluctuation of the indicator value. Obviously, the larger the value is, the more unstable it is. Therefore, when the value of the internal factor score X is larger, the corresponding key indicator score is higher. Then obtain the degree of fit between the enterprise indicator and the strategic goal during the detection period B r 、Contribution B g , and the performance value B under this indicator h 、Customer satisfaction B c , so that through the formula The target influencing factor score B is obtained; from the formula, it can be seen that when the enterprise indicator is consistent with the strategic goal during the detection period, B r 、Contribution B g The higher the value, the higher the customer satisfaction or the larger the performance value, the higher the corresponding key indicator score. Similarly, when the personnel change is smaller, that is, the difference between the incoming and outgoing employees is larger, it can also indicate that the corresponding key indicator score is higher. Therefore, when the target influencing factor score B is larger, it indicates that the corresponding key indicator score is higher. Finally, the time change curve K(t) of each enterprise indicator value within the detection period is obtained, and the number of positive comments Q of the enterprise indicator within the detection period is obtained. g And the number of negative reviews Q b , through the formula The abnormal factor score R is obtained; the formula It is expressed as the difference between the obtained enterprise index value and the preset standard enterprise index value, and the formula It indicates the difference between the enterprise index evaluation value within the detection period and the historical evaluation value. The formula It represents the ratio of the number of favorable comments to the number of unfavorable comments. It can be seen from the formula that the larger its value is, the stronger the criticality of the indicator is. Therefore, the larger the value of the abnormal factor score R is, the higher the score of the corresponding critical indicator is. Therefore, the formula V = α*X + β*B + δ*R is used for comprehensive analysis to construct an indicator evaluation model. Through the internal factor scoring method, the intrinsic characteristics of the indicator can be quantified to ensure that the evaluation results fully reflect the value and reliability of the indicator, reduce the subjectivity of human judgment, and improve the objectivity and accuracy of the evaluation. The target factor scoring method can ensure that the evaluation results are closely centered on the enterprise goals, improve the pertinence and practicality of the evaluation, and support enterprises to accurately identify key indicators and optimize resource allocation by quantifying the contribution of indicators to the goals. The abnormal factor scoring method can monitor the abnormal fluctuations of indicators in real time, help enterprises plan ahead, reduce potential risks, identify abnormal changes in the market, and support enterprises to adjust strategies in time and seize favorable opportunities. Therefore, this embodiment can combine factors such as enterprise internal factors, target influencing factors, and abnormal factors to more accurately construct an indicator evaluation model, which is convenient for judging subsequent indicators of each enterprise.

[0075] As an implementation mode of the present invention, the method for performing critical scoring on each enterprise indicator in step 3 is:

[0076] Obtain the indicator data of each enterprise and bring it into the corresponding indicator evaluation model V, so as to obtain the critical score G corresponding to each enterprise indicator through the formula GF=V*μ;

[0077] Among them, μ is the corresponding weight assigned to each enterprise indicator, and the method of assigning the corresponding weight to each enterprise indicator is: according to the changes in the market and operating environment, define the corresponding fuzzy set for each enterprise indicator;

[0078] Based on empirical data and historical operating data, a fuzzy relationship matrix between various enterprise indicators is constructed;

[0079] The membership degree of each enterprise index is calculated using fuzzy mathematics method, and the comprehensive evaluation result is obtained through synthetic fuzzy matrix algorithm;

[0080] The obtained fuzzy comprehensive evaluation results are transformed into clear results, thus obtaining the weights of each enterprise indicator.

[0081] Through the above technical solution, this embodiment provides a method for critical scoring of each enterprise indicator, which is to first use the hierarchical analysis method or fuzzy mathematics method to assign corresponding weights to each enterprise indicator according to changes in the market and operating environment, and then bring the corresponding indicator data into the corresponding indicator evaluation model V, so as to obtain the critical score G corresponding to each enterprise indicator through the formula GF=V*μ. This method allows enterprises to automatically adjust the weights in indicator evaluation according to changes in the market and operating environment, ensure the timeliness and accuracy of the evaluation results, and enable enterprises to respond quickly to market changes.

[0082] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for analyzing enterprise situation based on dynamic identification of key enterprise indicators, characterized in that: The analysis method comprises: Step 1: Build an enterprise indicator database: collect internal and external data related to the enterprise, clean and organize it, and build an enterprise indicator database; Step 2: Construct an indicator criticality evaluation model: Based on the enterprise data in the enterprise indicator database, construct an indicator evaluation model V that combines the internal factor score, the target influencing factor score, and the abnormal factor score; Step 3: Indicator criticality scoring: Based on the constructed indicator evaluation model and according to changes in the market and operating environment, assign corresponding weights to each enterprise indicator to perform criticality scoring on each enterprise indicator; Step 4: Key indicator screening: Based on the criticality scores of each enterprise indicator, screen out the top-ranked key indicators and apply them to the enterprise's decision-making process.

2. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 1 is characterized in that: The method for constructing the enterprise indicator database in step 1 is: Collect internal and external data of the enterprise, including financial, operational, market and other data, to form an initial data set; Clean the data, eliminate noise and missing values, and standardize the data to obtain the processed data set; Select potential indicators according to enterprise goals and plans, thereby constructing a list of potential indicators, and classify each indicator to obtain a classified enterprise indicator database; Regularly update and maintain the enterprise indicator database by adding new indicators and deleting indicators that are no longer applicable.

3. The enterprise situation analysis method based on dynamic identification of key enterprise indicators according to claim 1 is characterized in that: The method for constructing the indicator evaluation model in step 2 is: Set a detection cycle, and obtain the intrinsic factor score value X, the target influencing factor score value B, and the abnormal factor score value R within the detection cycle; Thus, the indicator evaluation model V is constructed through the formula V = α*X + β*B + δ*R; Among them, α, β and δ are preset weight coefficients of each score value.

4. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 3 is characterized in that: The method for obtaining the intrinsic factor score value X is: At each detection cycle, all possible values ​​x1, x2, ..., x of each enterprise indicator are listed from the enterprise indicator database. n , and based on historical data and sample data, the probability P(x i ); At the same time, in this detection cycle, the indicator value k of each enterprise indicator is obtained every day j , so that through the formula Obtain the fluctuation coefficient σ of the enterprise indicator within the detection period; Then through the formula Obtain the intrinsic factor score X of each enterprise indicator; Among them, n is the total number of possible values, m is the total number of days in the detection period, and k j The index value k obtained on the jth day j .

5. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 3 is characterized in that: The method for obtaining the target influencing factor score value B is: Obtain the degree of fit between the enterprise indicator and the strategic goal during the detection period B r 、Contribution B g , and the performance value B under this indicator h 、Customer satisfaction B c ; So through the formula Obtain the target influencing factor score B; Among them, B in is the number of employees who joined the company during the testing period, B out is the number of employees who left during the detection period, B th The default performance value.

6. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 3 is characterized in that: The method for obtaining the abnormal factor score value R is: Get the time-varying curve K(t) of each enterprise indicator value within the detection period, and get the number of positive reviews Q for the enterprise indicator within the detection period. g And the number of negative reviews Q b ; By formula Obtain the abnormal factor score R; Among them, γ1 and γ2 are preset coefficients, K0(t) is the time-varying curve of the standard enterprise index value set during the detection period, and K K is the average value of each enterprise indicator in the same historical detection period, t a is the start time of the detection cycle, t b The end time of the detection cycle.

7. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 1 is characterized in that: The method for performing critical scoring on each enterprise indicator in step 3 is as follows: Obtain the indicator data of each enterprise and bring it into the corresponding indicator evaluation model V, so as to obtain the critical score G corresponding to each enterprise indicator through the formula GF=V*μ; Among them, μ is the corresponding weight assigned to each enterprise indicator.

8. The enterprise situation analysis method based on dynamic identification of enterprise key indicators according to claim 7 is characterized in that: The method of assigning the corresponding weights to each enterprise indicator in step 3 is: Define corresponding fuzzy sets for each enterprise indicator according to changes in the market and operating environment; Based on empirical data and historical operating data, a fuzzy relationship matrix between various enterprise indicators is constructed; The membership degree of each enterprise index is calculated using fuzzy mathematics method, and the comprehensive evaluation result is obtained through synthetic fuzzy matrix algorithm; The obtained fuzzy comprehensive evaluation results are transformed into clear results, thus obtaining the weights of each enterprise indicator.

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