An administrative management method and system based on big data

Abstract

The application relates to the technical field of administration, and particularly discloses an administration method and system based on big data, which comprises the following steps: step S1: determining the post of an employee to be evaluated, and obtaining historical project data of the post; step S2: setting an evaluation period, extracting all work projects of the employee in the period, calculating the similarity by comparing historical project information, and screening similar projects; step S3: obtaining the working years and project periods of historical employees who have executed similar projects, combining the working years of the employee to be evaluated, generating a period distribution curve, and determining a maximum value point period; and step S4: quantifying the performance of the employee according to the comparison between the evaluation period length and the maximum value point period; the application is driven by data, objectively evaluates the efficiency of the employee, and is particularly suitable for performance management of project-based enterprises.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of administrative management, and particularly relates to an administrative management method and system based on big data. BACKGROUND

[0002] The administrative management of an enterprise is a comprehensive management field, covering multiple aspects, including office management, human resource management, asset management, and logistics management, etc.; wherein the human resource management includes recruitment configuration, training development, and performance management, etc.

[0003] In the existing performance evaluation system, the main method adopted is based on human scoring. This traditional method exposes many drawbacks in the actual operation process. First of all, subjective factors dominate in it. The personal emotions, biases, and personal cognitive levels of the evaluators will have a great influence on the scoring results. For example, when the evaluator and the evaluated person have a close relationship, the score may be high; on the contrary, if there are some contradictions or misunderstandings between the two, the score may be low. This human subjective judgment makes the performance evaluation results lack objectivity and fairness, and cannot truly reflect the work performance of the employees.

[0004] Secondly, the lack of unified standards is also a major problem faced by the existing performance evaluation. Different evaluators may have great differences in the evaluation standards for the same work. For example, for the communication ability of an employee, some evaluators may pay more attention to the fluency of expression, while others pay more attention to the logic and appeal of the content. This leads to the fact that each evaluator scores according to his own standards in the scoring process, making the scoring results lack consistency and comparability.

[0005] In addition, the lack of reference basis for performance scoring is also a prominent problem. Since there are no clear and specific quantitative indicators and objective facts as support, the evaluators often have to score based on vague impressions and subjective feelings. This makes the scoring results lack persuasiveness, and the employees also have difficulty in understanding and accepting the evaluation results, and cannot obtain valuable feedback and improvement direction from them.

[0006] Finally, this human scoring method also has the problem of low scoring efficiency. In the case of a large enterprise with a large number of employees, relying on manual scoring one by one requires a lot of time and effort. The evaluators need to carefully consider and evaluate each indicator of each employee, which not only increases the workload, but also easily leads to a long and tedious evaluation process. At the same time, due to the limited attention and energy of humans, in the long scoring process, the evaluators may experience fatigue and inattention, further affecting the accuracy and efficiency of the scoring. SUMMARY

[0007] The application aims to provide an administrative management method and system based on big data, and solve the above technical problems.

[0008] The application aims to provide an administrative management method and system based on big data, and solve the above technical problems.

[0009] An administrative management method based on big data comprises the following steps:

[0010] Step S1: obtaining a post of a to-be-evaluated employee in an enterprise, wherein the to-be-evaluated employee is an employee of the enterprise who needs to be evaluated; and obtaining historical project information of the post in the enterprise;

[0011] Step S2: setting an evaluation period, obtaining all work projects of the to-be-evaluated employee in the evaluation period; obtaining a similarity according to the historical project information; and screening similar projects according to the similarity;

[0012] Step S3: obtaining a historical employee who executes the similar projects, obtaining a historical working time of the historical employee when executing the similar projects, and obtaining a project period of the similar projects; obtaining an entry time of the to-be-evaluated employee and a current project period, obtaining a cycle distribution curve, and obtaining a maximum value point period;

[0013] Step S4: obtaining a time length of the evaluation period, and obtaining a performance score of the to-be-evaluated employee according to the maximum value point period.

[0014] As a further scheme of the application, the process of obtaining the historical project information comprises:

[0015] obtaining all historical projects of the post in the enterprise, dividing the historical projects into a plurality of project stages, obtaining project elements, core capabilities and project outputs of each project stage, and obtaining the historical project information.

[0016] As a further scheme of the application, the process of obtaining the similarity comprises:

[0017] obtaining all project stages of the work projects, denoted as a current project stage, and obtaining project elements, core capabilities and project outputs of the current project stage, denoted as current project elements, current core capabilities and current project outputs, respectively;

[0018] obtaining a text similarity of the current project elements and the project elements of the historical projects based on a natural language processing technology, denoted as a task overlap degree To, obtaining a text similarity of the current core capabilities and the core capabilities of the historical projects, denoted as a skill matching degree Sm, and obtaining a text similarity of the current project outputs and the project outputs of the historical projects, denoted as an output similarity Os;

[0019] then the similarity is obtained wherein To i represents the task overlap degree of the project element of the i-th project stage of the historical project and the current project element, Sm i represents the skill matching degree of the core competence of the i-th project stage of the i-th historical project and the current core competence, Os i represents the output similarity of the project output of the i-th project stage of the historical project and the current project output, n represents the total number of project stages, and w1, w2 and w3 are weight coefficients, each being 0.4, 0.35 and 0.25 respectively.

[0020] As a further scheme of the present application: the process of screening similar projects according to the similarity includes screening historical projects whose similarity exceeds a preset similarity threshold, which are recorded as similar projects.

[0021] As a further scheme of the present application: the time consumed by the employee to be evaluated for completing the work project is recorded as a current project cycle, and the service length is the total length of time during which the employee to be evaluated has engaged in the post.

[0022] As a further scheme of the present application: the process of establishing the cycle distribution curve includes:

[0023] screening all similar projects whose service length is consistent with the service length of the employee to be evaluated, which are recorded as historical analysis projects; obtaining the project cycles of all historical analysis projects to obtain a project cycle set, obtaining the maximum value in the project cycle set, which is recorded as Y max , and obtaining the minimum value in the project cycle set, which is recorded as Y min ; obtaining the cycle range [Y min , Y max ] of all historical analysis projects, and dividing the cycle range into a plurality of cycle intervals;

[0024] According to the project cycles of the historical analysis projects, the historical analysis projects are divided into corresponding cycle intervals, and then the number of all historical analysis projects in each cycle interval is obtained; each cycle interval is numbered, and a coordinate system is established with the number as the horizontal coordinate and the number as the vertical coordinate; each numbered cycle interval and its number are converted into a coordinate point at the corresponding position in the coordinate system, and a smooth curve is used to connect the coordinate points to obtain a cycle distribution curve.

[0025] As a further scheme of the present application: the maximum value point of the cycle distribution curve is obtained, and the horizontal coordinate corresponding to the maximum value point is recorded as the maximum value point cycle tmax.

[0026] As a further scheme of the present application: the performance score of the employee to be evaluated is wherein m is the total number of work projects in the evaluation period, tmax x represents the maximum point period of the xth work project, t x represents the current project period of the xth work project, K is a preset correction coefficient and K>0, P max is the full score of the performance score, T is the length of the evaluation period.

[0027] As a further scheme of the present application: an administrative management system based on big data, comprising:

[0028] The acquisition module: obtains the post of the employee to be evaluated in the enterprise, the employee to be evaluated is the enterprise employee who needs to be evaluated; obtain the historical project information of the post in the enterprise;

[0029] The analysis module: set the evaluation period, obtain all work projects of the employee to be evaluated in the evaluation period; according to the historical project information, obtain the similarity, and filter out similar projects according to the similarity;

[0030] Obtain the historical employee who executes the similar project, obtain the historical working years of the historical employee when executing the similar project, and obtain the project period of the similar project; obtain the entry years and the current project period of the employee to be evaluated, obtain the cycle distribution curve, and obtain the maximum point period;

[0031] The scoring module: obtain the length of the evaluation period, and obtain the performance score of the employee to be evaluated according to the maximum point period.

[0032] The beneficial effects of the present application are:

[0033] The administrative management method and system based on big data significantly improve the objectivity, accuracy and efficiency of enterprise performance evaluation through data-driven and intelligent analysis; the natural language processing (NLP) technology is used to calculate the project similarity (task overlap, skill matching degree and output similarity) to avoid emotional bias of artificial scoring; the project cycle of historical employees in the same position is taken as a reference (maximum value point cycle) to eliminate the influence of individual cognitive differences of evaluators. A three-dimensional evaluation model is formed by comprehensively considering multi-dimensional data such as project elements (collaboration departments, error cost), core capabilities (tool skills) and outputs (report types); the contribution of different dimensions is dynamically adjusted by presetting a weight coefficient (such as a task overlap weight of 0.4) to adapt to different post characteristics. The whole process from data collection (historical project information) to score generation (formalized calculation) is automated to reduce manual intervention time; the project cycle distribution law is intuitively displayed to assist managers in identifying the optimal work efficiency interval; the employee execution efficiency is directly reflected by comparing the current project cycle with the historical maximum value cycle; the preset correction coefficient K can adjust the scoring sensitivity according to the complexity of different positions to enhance the fairness of evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0034] The application will be further described below in conjunction with the drawings.

[0035] Figure 1 is a process schematic diagram of an administrative management method based on big data. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0037] Please refer to Figure 1 The application is an administrative management method based on big data, which comprises the following steps:

[0038] Step S1: obtaining the post of a to-be-evaluated employee in an enterprise, wherein the to-be-evaluated employee is an employee of the enterprise who needs to be evaluated; obtaining all historical projects of the post in the enterprise, dividing the historical projects into a plurality of project stages, obtaining project elements, core capabilities and project outputs of each project stage, and obtaining historical project information;

[0039] As a preferred embodiment of the present application, the project elements include collaborative departments, project size and error cost, the error cost includes loss amount; the project output includes market analysis report, user research report, the use tools include Excel, Python, SQL, consumer behavior and statistics; the project elements are obtained based on the project proposal;

[0040] It can be understood that obtaining the complete profile of the historical project of the same post (such as collaborative departments, error cost, tool skills, etc.) provides a reference for subsequent similarity calculation and efficiency comparison; through unified project stage division (such as time or milestone node) and element extraction (such as core ability, output), the ambiguity of post responsibility description is eliminated; the employee performance evaluation is converted from subjective experience judgment to objective data comparison, which improves the credibility and fairness of the evaluation;

[0041] As a preferred embodiment of the present application, the division process of the project stage includes:

[0042] When the historical project is divided based on time, the historical project is divided according to a preset time interval threshold to obtain a plurality of project stages;

[0043] When the historical project is divided based on project content, according to the actual situation of the project, a plurality of milestone nodes are selected during the execution of the historical project to obtain a plurality of project stages, and the project stages include a start-up stage, a planning stage, an execution stage and a closing stage;

[0044] It can be understood that based on historical project data, objective criteria are established to avoid subjective randomness of evaluation, complex projects are divided into quantifiable stages (start-up, execution, closing, etc.), and key dimensions (elements, abilities, outputs) are extracted for standardized comparison; by accumulating historical project information, an internal project knowledge base of the enterprise is formed;

[0045] Step S2: Set an evaluation period, and obtain all work projects of the employee to be evaluated within the evaluation period; obtain the similarity of each historical project and the work project according to the historical project information; and filter out the historical projects with a similarity exceeding a preset similarity threshold, which are recorded as similar projects;

[0046] As a preferred embodiment of the present application, the similarity obtaining process includes:

[0047] Obtain all project stages of the work project, recorded as current project stages, and obtain project elements, core abilities and project outputs of the current project stages, and recorded as current project elements, current core abilities and current project outputs respectively;

[0048] Based on natural language processing technology, the text similarity of the current project element and the project element of the historical project is obtained, denoted as task overlap To, the text similarity of the current core competence and the core competence of the historical project is obtained, denoted as skill matching degree Sm, and the text similarity of the current project output and the project output of the historical project is obtained, denoted as output similarity Os;

[0049] Then the similarity is obtained Wherein To i represents the task overlap of the project element of the i-th project stage of the historical project and the current project element, Sm i represents the skill matching degree of the core competence of the i-th project stage of the i-th historical project and the current core competence, Os i represents the output similarity of the project output of the i-th project stage of the historical project and the current project output, n represents the total number of project stages, w1, w2 and w3 are weight coefficients, which are 0.4, 0.35 and 0.25 respectively;

[0050] It can be understood that the historical project highly similar to the current work is found, the deviation of cross-project comparison (such as R&D and market projects being incomparable) is eliminated; comparable projects are flexibly grabbed according to the evaluation period (such as quarterly / annual), and the business changes of enterprises are adapted; more than 80% of the comparison time is reduced by replacing manual matching with automatic screening;

[0051] Step S3: obtaining historical employees who execute the similar projects, obtaining historical working years of the historical employees when executing the similar projects, and obtaining project periods of the similar projects;

[0052] The entry year of the employee to be evaluated is obtained, and the time consumed by the employee to be evaluated to complete the work project is obtained, denoted as the current project period, and the entry year is the total duration of the employee to be evaluated in the post;

[0053] According to the historical working years and the project periods of the similar projects and the entry year, a cycle distribution curve is established; the maximum point of the cycle distribution curve is obtained, and the abscissa corresponding to the maximum point is obtained, denoted as the maximum point period tmax;

[0054] As a preferred embodiment of the present application, the historical working years are the entry years of the historical employees when executing the similar projects, and the project periods are the total durations consumed by the similar projects from start to end;

[0055] As a preferred embodiment of the present application, the establishment process of the cycle distribution curve comprises:

[0056] Screening all similar projects with the same working years as the entering years of the employee to be evaluated as historical analysis projects max , and obtaining the maximum value in the project cycle set as Y min ; obtaining the minimum value in the project cycle set as Y min ; obtaining the cycle range [Y max , Y x ] of all historical analysis projects, and dividing the cycle range into several cycle intervals;

[0057] According to the project cycle of the historical analysis projects, the historical analysis projects are divided into corresponding cycle intervals, and the number of all historical analysis projects in each cycle interval is obtained; each cycle interval is numbered, and a coordinate system is established with the number as the horizontal coordinate and the number as the vertical coordinate; each numbered cycle interval and the number thereof are converted into coordinate points at corresponding positions in the coordinate system, and a cycle distribution curve is obtained by connecting the coordinate points with a smooth curve;

[0058] As a preferred embodiment of the present application, the process of obtaining the maximum value point comprises:

[0059] Obtaining extreme value points on the cycle distribution curve, and obtaining the vertical coordinate values corresponding to each extreme value point; the extreme value point with the maximum vertical coordinate value is recorded as the maximum value point;

[0060] It can be understood that the year-efficiency probability distribution model is constructed by the execution cycle data of historical employees on similar projects, the optimal efficiency interval (maximum value point cycle tmax) is identified, it is assumed that the project cycle of employees with the same working years obeys normal distribution, the maximum value point corresponds to the highest probability efficiency value (i.e. reasonable cycle that most people can reach), and the historical data with the same entering years as the employee to be evaluated is screened to ensure the fairness of comparison (e.g. 3-year experienced employees are not compared with new employees);

[0061] Step S4: obtaining the duration T of the evaluation cycle, and obtaining the performance score of the employee to be evaluated according to the maximum value point cycle , wherein m is the total number of working projects in the evaluation cycle, tmax x represents the maximum value point cycle of the xth working project, t x represents the current project cycle of the xth working project, K is a preset correction coefficient and K>0, P max is the full score of the performance score;

[0062] It should be noted that reflects the average gap between the current cycle and the historical optimal cycle (a negative value indicates that the efficiency is better than the historical benchmark); Reflect the density of the work project of the personnel to be evaluated, avoid the evaluation deviation of more work and more mistakes, the more the completed projects, the greater the value; Map the score to the interval [0, P max ] interval, ensure that the score distribution is reasonable.

[0063] An administrative management system based on big data, comprising:

[0064] The acquisition module: obtains the post of the employee to be evaluated in the enterprise, the employee to be evaluated is the enterprise employee who needs to be performance evaluated; obtain the historical project information of the post in the enterprise;

[0065] The analysis module: set the evaluation period, obtain all work projects of the employee to be evaluated in the evaluation period; according to the historical project information, obtain the similarity, and filter out the similar projects according to the similarity;

[0066] Obtain the historical employee who executes the similar project, obtain the historical working years of the historical employee when executing the similar project, and obtain the project cycle of the similar project; obtain the entry years of the employee to be evaluated and the current project cycle, obtain the cycle distribution curve, and obtain the maximum value point cycle;

[0067] The scoring module: obtain the duration of the evaluation period, and obtain the performance score of the employee to be evaluated according to the maximum value point cycle.

[0068] The above has carried out the detailed description to one embodiment of the application, but the content described is only the preferred embodiment of the application, and cannot be considered as used for limiting the implementation range of the application. Any equivalent change and improvement made according to the application scope should still belong to the patent coverage range of the application.

Claims

1. A big data-based administrative management method, characterized in that, Includes the following steps: Step S1: Obtain the employee's position in the company, where the employee is the one whose performance needs to be evaluated; obtain the historical project information of the position within the company. Step S2: Set an evaluation period, obtain all work items of the employee to be evaluated within the evaluation period; obtain similarity based on the historical project information, and filter out similar projects based on the similarity; Step S3: Obtain historical employees who performed similar projects, obtain the historical years of service of the historical employees when performing similar projects, and obtain the project cycle of the similar projects; obtain the years of service and current project cycle of the employee to be evaluated, obtain the cycle distribution curve, and obtain the cycle of the maximum point; Step S4: Obtain the duration of the evaluation period and obtain the performance score of the employee to be evaluated based on the maximum value period; In step S3, the process of establishing the periodic distribution curve includes: Filter out all similar projects whose historical work experience matches the stated entry year, and denot them as historical analysis projects; obtain the project cycle of all historical analysis projects to obtain a project cycle set, and obtain the maximum value in the project cycle set, denoted as Y. max And obtain the minimum value in the set of project cycles, denoted as Y. min ; Obtain the period range [Y] of all historical analysis projects min Y max The periodic range is divided into several periodic intervals. Based on the project cycle of the historical analysis projects, the historical analysis projects are divided into corresponding cycle intervals, and the number of all historical analysis projects in each cycle interval is obtained; each cycle interval is numbered, and a coordinate system is established with the number as the horizontal axis and the number as the vertical axis; the cycle intervals and their numbers are converted into coordinate points at corresponding positions in the coordinate system, and the coordinate points are connected by a smooth curve to obtain the cycle distribution curve. Obtain the maximum point of the periodic distribution curve, and obtain the x-coordinate corresponding to the maximum point, denoted as the period tmax of the maximum point; In step S4, the performance score of the employee to be evaluated. ,in , m is the total number of work items within the evaluation period, tmax x Let t represent the period of the maximum point of the x-th work item. x P represents the current project cycle of the x-th work item, K is a preset correction coefficient and K > 0, and P max The full score for performance evaluation is given by T, and the duration of the evaluation period is given by T.

2. The administrative management method based on big data according to claim 1, characterized in that, In step S1, the process of obtaining historical project information includes: Obtain all historical projects for the aforementioned positions within the enterprise, divide these historical projects into several project phases, and obtain the project elements, core capabilities, and project deliverables for each project phase to obtain historical project information.

3. The administrative management method based on big data according to claim 2, characterized in that, In step S2, the process of obtaining the similarity includes: Obtain all project phases of the work project and denote them as the current project phase. Also obtain the project elements, core capabilities, and project deliverables of the current project phase and denote them as the current project elements, current core capabilities, and current project deliverables, respectively. Based on natural language processing technology, the text similarity between the current project element and the project element of the historical project is obtained, denoted as task overlap To; the text similarity between the current core capability and the core capability of the historical project is obtained, denoted as skill matching Sm; and the text similarity between the current project output and the project output of the historical project is obtained, denoted as output similarity Os. Then the similarity is obtained. To i Sm represents the task overlap between the project elements of the i-th project phase in the historical project and the current project element. i Os represents the skill matching degree between the core competencies of the i-th historical project and the current core competencies in the i-th project phase. i The output similarity between the project output of the i-th project stage in the history project and the output of the current project is represented by n, where n represents the total number of project stages, and w1, w2, and w3 are weighting coefficients with values ​​of 0.4, 0.35, and 0.25, respectively.

4. The administrative management method based on big data according to claim 3, characterized in that, In step S2, the process of filtering out similar items based on the similarity includes filtering out historical items whose similarity exceeds a preset similarity threshold and recording them as similar items.

5. The administrative management method based on big data according to claim 1, characterized in that, In step S3, the time consumed by the employee to be evaluated to complete the work project is obtained and recorded as the current project cycle, and the years of service are the total length of time the employee to be evaluated has worked in the position.

6. An administrative management system based on big data, characterized in that, include: Data collection module: Obtains the job position of the employee to be evaluated in the company, where the employee to be evaluated is the company employee whose performance needs to be evaluated; Obtain historical project information for the aforementioned positions within the company; Analysis module: Sets an evaluation period, obtains all work projects of the employee to be evaluated within the evaluation period; obtains similarity based on the historical project information, and filters out similar projects based on the similarity; Obtain historical employees who performed similar projects, obtain the historical years of service of the historical employees when performing similar projects, and obtain the project cycle of the similar projects; obtain the years of service and current project cycle of the employee to be evaluated, obtain the cycle distribution curve, and obtain the cycle of the maximum point; Scoring module: Obtain the duration of the evaluation period and obtain the performance score of the employee to be evaluated based on the maximum value period; The process of establishing the periodic distribution curve includes: Filter out all similar projects whose historical work experience matches the stated entry year, and denot them as historical analysis projects; obtain the project cycle of all historical analysis projects to obtain a project cycle set, and obtain the maximum value in the project cycle set, denoted as Y. max And obtain the minimum value in the set of project cycles, denoted as Y. min ; Obtain the period range [Y] of all historical analysis projects min Y max The periodic range is divided into several periodic intervals. Based on the project cycle of the historical analysis projects, the historical analysis projects are divided into corresponding cycle intervals, and the number of all historical analysis projects in each cycle interval is obtained; each cycle interval is numbered, and a coordinate system is established with the number as the horizontal axis and the number as the vertical axis; the cycle intervals and their numbers are converted into coordinate points at corresponding positions in the coordinate system, and the coordinate points are connected by a smooth curve to obtain the cycle distribution curve. Obtain the maximum point of the periodic distribution curve, and obtain the abscissa corresponding to the maximum point, denoted as the period tmax of the maximum point; The performance rating of the employee to be evaluated ,in , m is the total number of work items within the evaluation period, tmax x Let t represent the period of the maximum point of the x-th work item. x P represents the current project cycle of the x-th work item, K is a preset correction coefficient and K > 0, and P max The full score for performance evaluation is given by T, and the duration of the evaluation period is given by T.

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