CN113505163B - Organization target analysis method, system and storage medium based on big data mining - Google Patents
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Abstract
The invention provides a big data mining-based organization target analysis method, which comprises the following steps: collecting multi-source organization data of the industry where the service object is located, and integrating and establishing a target big data directory; acquiring service data of a service object, and performing standard structured processing on the service data to obtain standard target data and establish an organization target library; constructing a target index library matrix based on standard target data, comparing the targets, scheduling the importance sequence of the targets, constructing a target importance initial matrix, and calculating to obtain the weight of the targets; and obtaining the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and calculating by combining the score value to obtain an analysis value result of the organization target. The big data target benchmarking method based on the data directory solves the problems of systematicness and operability in benchmarking management practice; by establishing a target library of each post of each department of organization, the big data whole-person benchmarking can be realized by using the data platform.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method, a system and a storage medium for analyzing an organization target based on big data mining.
Background
At present, the mainstream business management system in the market is mainly switched into office application from the perspective of instant messaging, and plays an important auxiliary role in the aspects of process approval, file transmission, examination condition management and the like, but is still careless in the aspects of organizing some core applications in the field of target management, such as business data management, process system management, major project management, leadership decision support and the like. The importance of target management, whether government or enterprise, has risen to an unprecedented level.
Traditional object management methods focus on the entire team doing things around the same object. Firstly, an organization or department with better performance than the performance of the family is found out for comparison to obtain better performance, so that the family continuously surpasses the benchmarks and pursues superiority; the organization needs to make annual strategic and personal annual goals every year, and in the actual execution of the organization, most people only see the final result of finance, but do not find the target pole which the organization wants to learn, and cannot realize the whole-member benchmarking of big data, and cannot really fall to the target pole.
Therefore, a scheme is needed to be provided so as to solve the problems of systematicness and operability in benchmarking practice and realize large data whole-person benchmarking.
Disclosure of Invention
The invention aims to solve the problems pointed out in the background technology, establish a target library of each post of each department of organization, and develop the whole-member benchmarking of big data by using a data platform.
The embodiment of the invention is realized by the following technical scheme: the organization target analysis method based on big data mining comprises the following steps:
s1, collecting multi-source organization data of an industry where a service object is located, and integrating and establishing a target big data directory;
s2, acquiring service data of a service object, and performing standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library;
s3, constructing a target index library matrix based on the standard target data, after pairwise comparison is carried out between the targets, scheduling the importance sequence of the targets, constructing a target importance initial matrix, and calculating to obtain the weight of the targets;
and S4, obtaining the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation.
According to a preferred embodiment, step S2 is preceded by:
analyzing and sorting according to the data and the theme list acquired by the target big data directory and the main data and the transaction data;
and formulating a target working data standard according to an analysis result obtained by analysis and sorting, wherein the target working data standard comprises a plurality of types of data subject domains, and the data subject domains collectively reflect all business contents related to working target management.
According to a preferred embodiment, the acquiring the service data of the service object in step S2 further includes: and acquiring the service data of the service object by a data exchange technology.
According to a preferred embodiment, the step S2 of performing standard structuring on the business data according to the standard model of the target management object further includes:
and analyzing the acquired data, and obtaining a data analysis result by combining a label library of the industry data and various intelligent algorithm interfaces, wherein the data analysis result comprises data label elements and data element relation data.
According to a preferred embodiment, the organization target library stores standard target data using XML data packets.
According to a preferred embodiment, the target metric library matrix comprises two dimensions of target type and belonging organizational structure.
According to a preferred embodiment, the weight of the target is calculated in step S3 using the following formula:
in the above formula,ai/ajfinger included from the target-finger library matrixnAn objectkIn the randomly selected targetKiAndKjthe importance of the comparison is such that,i，j∈{1，2，3，…n-1，n}。
according to a preferred embodiment, the analysis value of the organization target calculated in combination with the score value using the calculated weight of the target in step S4 is formulated as:
in the above formula, the first and second carbon atoms are,TSrefers to the result of the analysis of the value,TS k finger targetkThe value of the score of (a) is,W k finger targetkThe weight of (c).
The invention also provides an organization target analysis system based on big data mining, which is applied to the method, and comprises the following steps:
the organization data acquisition module is used for acquiring multi-source organization data of the industry where the service object is located and integrating and establishing a target big data directory;
the service data acquisition module is used for acquiring service data of the service object and carrying out standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library;
the weight design module is used for constructing a target index library matrix based on the standard target data, after pairwise comparison is carried out between targets, the importance sequence of each target is arranged, a target importance initial matrix is constructed, and the weight of the target is obtained through calculation;
and the analysis module is used for acquiring the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation.
The invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method as described above.
The technical scheme of the embodiment of the invention at least has the following advantages and beneficial effects: the big data target benchmarking method based on the data directory solves the problems of systematicness and operability in benchmarking management practice; by establishing a target library of each post of each department of organization, the big data whole-person benchmarking can be realized by using the data platform.
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Fig. 1 is a schematic flowchart of a method for analyzing an organization target based on big data mining according to embodiment 1 of the present invention;
fig. 2 is a block diagram of a structure of an organization target analysis system based on big data mining according to embodiment 1 of the present invention;
fig. 3 is a schematic diagram of a structured data relationship provided in embodiment 1 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a method for analyzing an organization target based on big data mining according to an embodiment of the present invention.
The applicant researches and discovers that currently, a mainstream business management system in the market is mainly switched into office application from the perspective of instant messaging, and plays an important auxiliary role in aspects of process approval, file transmission, examination condition management and the like, but the mainstream business management system is not careful in aspects of core applications in the field of organizing target management, such as business data management, process system management, major project management, leader decision support and the like. The importance of target management, whether government or enterprise, has risen to an unprecedented level.
Traditional object management methods focus on the entire team doing things around the same object. Firstly, an organization or department with better performance than the performance of the family is found out for comparison to obtain better performance, so that the family continuously surpasses the benchmarks and pursues superiority; the organization needs to make annual strategic and personal annual goals every year, and in the actual execution of the organization, most people only see the final result of finance, but do not find the target pole which the organization wants to learn, and cannot realize the whole-member benchmarking of big data, and cannot really fall to the target pole. Therefore, the method and the system provide a scheme so as to solve the problems of systematicness and operability in benchmarking practice and realize large data whole-person benchmarking. The specific scheme is as follows:
the organization target analysis method based on big data mining comprises the following steps:
s1, acquiring all target data of an organization of an industry where a service object is located by a multi-dimensional mechanism of the industry, integrating multi-source organization data to obtain target big data related to the service object, and establishing a target big data catalog; in an implementation manner of this embodiment, the target big data includes a primary classification, a secondary classification, and a topic, where the primary classification includes: post, goal, performance, and business; the secondary classification corresponding to the target comprises: business objectives, party business objectives, key work, other objectives, enterprise operations, product research and development, sales business, production objectives, and the like; the theme corresponding to the position comprises: management, finance, administration, human resources, marketing, technology, production, etc., and the other subjects under the secondary classification are not repeated herein.
Further, according to the data and the theme list collected by the target big data directory, analyzing and sorting are carried out according to the main data and the transaction data; in one implementation of this embodiment, the main data refers to a customer, a supplier, a device account, and the like, and the transaction data refers to various transaction-type data generated by a specific business operation, such as detection data, transaction data, and the like. Formulating a target working data standard according to an analysis result obtained by analysis and sorting, wherein the target working data standard is defined by a standard of a target management object model; the target work data standard comprises various data subject fields such as organization, task, target, index, performance, process management, project management and system, and the data subject fields collectively reflect all business contents related to work target management, such as government, education, real estate, energy, medical, finance and IT industry fields.
It should be noted that the purpose of establishing the standard definition of the target management object model is to achieve interconnection and intercommunication of the work management systems, that is, data can be transmitted between the systems and can be accurately understood; so that each user can obtain timely, complete and accurate data.
In addition, in this embodiment, the method further includes the following steps: and (3) summarizing and sorting according to the characteristics of the organized target data to obtain a target data theme matrix, wherein the theme T consists of 8 types of post organization structures, personnel, targets, tasks, projects, business data, behavior data, files and the like.
After the target big data directory is created through the step S1, the method further proceeds to the step S2,
and S2, acquiring service data of the service object through a data exchange technology, and carrying out standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library. Wherein, the standard structuralization processing of the service data according to the target management object standard model further comprises: analyzing the collected data, and combining a label library of industry data and various intelligent algorithm interfaces, for example: obtaining a data analysis result by a semantic database, an image database, a fingerprint database and the like, wherein the data analysis result comprises data label elements and data element relation data to form a structured data relation diagram, and the structured data relation diagram is shown in fig. 3; furthermore, the organization target library stores standard target data by adopting XML data packets.
After the establishment of the organization target library in step S2, the process proceeds to step S3,
s3, constructing a target index library matrix based on the standard target data, wherein the target index library matrix comprises two dimensions of a target type and an organization structure to which the target type belongs; further, in the present embodiment, the target index library matrix is composed ofK1、K2……Kn is in totalnEach object is formed, and further, after pairwise comparison is performed between each object, the objects are combinednThe targets are arranged in sequence; in the present embodiment, the targetKiAndKj(i，j∈{1，2，3，…n-1，n}) of the relative importance is notedai/aj(ai/aj∈{1，2，3，4，5，6，7，8，9，1/2，1/3，1/4，1/5，1/6，1/7，1/8，1/9})，KiAndKjcomparing and considering that the more important the former is, the higher the score is, otherwise, the lower the score is, scheduling the importance sequence of each target according to the score, constructing a target importance initial matrix, and calculating to obtain the weight of the target; in this embodiment, the weight of the target is calculated using the following formula:
in the above formula,ai/ajfinger included from the target-finger library matrixnAn objectkIn the randomly selected targetKiAndKjthe importance of the comparison is such that,i，j∈{1，2，3，…n-1，n}。
after the weight of the target is calculated in step S3, step S4 is further performed,
and S4, obtaining the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation. The target score value is obtained by comprehensively calculating the achievement condition of the target history and assisting the weighted product of the target weight coefficient; the result formula of calculating the analysis value of the tissue target in this embodiment is expressed as:
in the above formula, the first and second carbon atoms are,TSrefers to the result of the analysis of the value,TS k finger targetkThe value of the score of (a) is,W k finger targetkThe weight of (c).
Referring to fig. 2, an embodiment of the present invention further provides an organization target analysis system based on big data mining, which is applied to the method described above, and includes:
the organization data acquisition module is used for acquiring multi-source organization data of the industry where the service object is located and integrating and establishing a target big data directory;
the service data acquisition module is used for acquiring service data of the service object and carrying out standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library;
the weight design module is used for constructing a target index library matrix based on the standard target data, after pairwise comparison is carried out between targets, the importance sequence of each target is arranged, a target importance initial matrix is constructed, and the weight of the target is obtained through calculation;
and the analysis module is used for acquiring the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the method described above.
In conclusion, the big data target benchmarking method based on the data directory solves the problems of systematicness and operability in benchmarking management practice; by establishing a target library of each post of each department of organization, the big data whole-person benchmarking can be realized by using the data platform.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The organization target analysis method based on big data mining is characterized by comprising the following steps:
s1, collecting multi-source organization data of an industry where a service object is located, and integrating and establishing a target big data directory;
s2, acquiring service data of a service object, and performing standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library;
s3, constructing a target index library matrix based on the standard target data, after pairwise comparison is carried out between the targets, scheduling the importance sequence of the targets, constructing a target importance initial matrix, and calculating to obtain the weight of the targets;
and S4, obtaining the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation.
2. The big data mining-based organizational target analysis method of claim 1, wherein step S2 is preceded by:
analyzing and sorting according to the data and the theme list acquired by the target big data directory and according to the main data and the transaction data, wherein the transaction data refers to various transaction type data generated by specific business operation;
and formulating a target working data standard according to an analysis result obtained by analysis and sorting, wherein the target working data standard comprises a plurality of types of data subject domains, and the data subject domains collectively reflect all business contents related to working target management.
3. The big data mining-based organizational target analysis method according to claim 1, wherein the collecting business data of the service object in step S2 further comprises: and acquiring the service data of the service object by a data exchange technology.
4. The big data mining-based organizational target analysis method according to claim 1, wherein the step S2 of standard structuring the business data according to the target management object standard model further comprises:
and analyzing the acquired data, and obtaining a data analysis result by combining a label library of the industry data and various intelligent algorithm interfaces, wherein the data analysis result comprises data label elements and data element relation data.
5. The big data mining-based organizational target analysis method of claim 1, wherein the organizational target repository stores standard target data using XML data packets.
6. The big data mining-based organizational target analysis method of claim 1, wherein the target metrics library matrix includes two dimensions of target type and the organizational structure to which it belongs.
7. The method for analyzing organizational targets based on big data mining according to claim 2, wherein the weight of the target is calculated in step S3 using the following formulaWi：
In the above formula, the first and second carbon atoms are,ai/ajfinger included from the target-finger library matrixnAn objectkIn the randomly selected targetKiAndKjthe importance of the comparison is such that,i，j∈{1，2，3，…n-1，n}。
8. the method for analyzing organizational targets based on big data mining according to claim 7, wherein the weights of the calculated targets are used in step S4, and the analysis value result formula of the organizational target calculated in combination with the score value is expressed as:
in the above formula, the first and second carbon atoms are,TSrefers to the result of the analysis of the value,TS k finger targetkThe value of the score of (a) is,W k finger targetkThe weight of (c).
9. The organization target analysis system based on big data mining, applied to the method of any one of claims 1 to 8, characterized by comprising:
the organization data acquisition module is used for acquiring multi-source organization data of the industry where the service object is located and integrating and establishing a target big data directory;
the service data acquisition module is used for acquiring service data of the service object and carrying out standard structuralization processing on the service data according to a target management object standard model to obtain standard target data and establish an organization target library;
the weight design module is used for constructing a target index library matrix based on the standard target data, after pairwise comparison is carried out between targets, the importance sequence of each target is arranged, a target importance initial matrix is constructed, and the weight of the target is obtained through calculation;
and the analysis module is used for acquiring the score value of the target based on the target big data directory, obtaining the weight of the target by utilizing calculation, and obtaining an analysis value result of the organization target by combining the score value calculation.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
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