CN113506050A

CN113506050A - Staff performance evaluation method and device, electronic equipment and readable storage medium

Info

Publication number: CN113506050A
Application number: CN202111058848.6A
Authority: CN
Inventors: 张明洋; 袁建华; 徐世超; 徐浩; 梁志婷; 陈爽
Original assignee: Beijing Minglue Zhaohui Technology Co Ltd
Current assignee: Beijing Minglue Zhaohui Technology Co Ltd
Priority date: 2021-09-10
Filing date: 2021-09-10
Publication date: 2021-10-15

Abstract

The application provides an assessment method, an assessment device, electronic equipment and a readable storage medium for staff performance, wherein the assessment method comprises the following steps: acquiring business information of an employee to be evaluated; determining at least one target business process monitoring index matched with the employee to be evaluated from a preset business process monitoring index system based on the business information of the employee to be evaluated; performing service stage labeling processing on the service information to obtain labeled service text information; and inputting the text information of the marking service into a preset performance evaluation model, and determining a performance evaluation result of the employee to be evaluated. According to the method and the system, the performance of different employees can be evaluated in a targeted manner according to different business scenes, and the accuracy of performance evaluation is improved.

Description

Staff performance evaluation method and device, electronic equipment and readable storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for evaluating employee performance, an electronic device, and a readable storage medium.

Background

With the development of the technology, in order to ensure the effective operation of the industry, the work of each employee in the enterprise needs to be evaluated, and the work completion degree of the employee is determined according to the performance evaluation of the employee, so that a favorable reference is provided for the subsequent work adjustment.

At the present stage, the performance assessment of the staff can be performed through a performance assessment model, the performance assessment model of the staff at present is generally referred by industry experience, then simply modified into the evaluation staff dimension, generally comprising the working attitude, the working capability, the value view and the like, in the process of performance and assessment of employees through the performance model, it is difficult to accurately quantify each index, and at the same time, in a performance model, the same evaluation rule is generally adopted to evaluate the employee in the same evaluation dimension, however, due to the different work contents of different employees, the mode of evaluating the performance of different employees in the same evaluation dimension by adopting the same evaluation rule has the problem of inaccurate evaluation, therefore, how to accurately evaluate the performance of each employee becomes a problem that needs to be solved urgently.

Disclosure of Invention

In view of this, the present application aims to provide a method and an apparatus for evaluating employee performance, an electronic device, and a readable storage medium, which can evaluate the performance of different employees in a targeted manner according to different business scenarios, thereby improving the accuracy of performance evaluation.

In a first aspect, an embodiment of the present application provides an employee performance evaluation method, where the evaluation method includes:

acquiring business information of an employee to be evaluated;

determining at least one target business process monitoring index matched with the employee to be evaluated from a preset business process monitoring index system based on the business information of the employee to be evaluated; the preset service process monitoring index system is determined based on service processes of different service scenes;

performing service stage labeling processing on the service information to obtain labeled service text information;

and inputting the text information of the marking service into a preset performance evaluation model, and determining a performance evaluation result of the employee to be evaluated.

In a possible embodiment, the preset business process monitoring index system is determined by the following steps:

determining a plurality of service stages respectively corresponding to different service scenes according to service flows of the different service scenes;

determining service process monitoring indexes corresponding to different service stages according to the different service stages corresponding to each service scene;

and determining a business process monitoring index system according to business process monitoring indexes corresponding to different business stages included in each business scene.

In one possible implementation, the performance assessment model is constructed according to the following steps:

constructing the performance evaluation model based on each preset evaluation index and the weight of each preset evaluation index; the preset evaluation index comprises a business process evaluation index and a reference item evaluation index.

In a possible implementation manner, the business process evaluation index includes a conversation use amount and a monitoring service duration ratio corresponding to each business process monitoring index; wherein, each business process monitoring index corresponds to a plurality of monitoring words and operation keywords.

In a possible implementation manner, the reference item evaluation index includes a usage amount of a preset service attitude class keyword; wherein, the service attitude class key words are determined according to historical formation data and key words of excellent employees.

In one possible implementation, the service information is obtained by:

acquiring work voice information of the employee to be evaluated;

carrying out validity processing on the working voice information to obtain valid voice information;

and performing text conversion processing on the effective voice information to obtain the service information.

In one possible embodiment, the evaluation method further comprises:

receiving business information of at least one employee;

and adjusting and updating the preset business process monitoring index system by performing order analysis and cluster analysis on the business information of at least one employee.

In a possible implementation manner, the inputting the text information of the annotation service into a preset performance evaluation model to determine a performance evaluation result of the employee to be evaluated includes:

obtaining a service evaluation score according to at least one evaluation service keyword under each target service process monitoring index provided in the labeling service text information and the evaluation service duration of each target service process monitoring index;

obtaining a service evaluation score based on at least one evaluation service keyword included in the labeling service text information;

and determining a performance evaluation result of the employee to be evaluated based on the business evaluation score and the service evaluation score.

In a possible implementation manner, the obtaining a service evaluation score according to at least one evaluation service keyword under each target service process monitoring index proposed in the labeled service text information and the evaluation service duration of each target service process monitoring index includes:

determining a first business sub-evaluation score according to at least one evaluation business keyword under each target business process monitoring index and a plurality of monitoring business keywords under the target business process monitoring index;

determining a second business sub-evaluation score according to the evaluation service duration of each target business process monitoring index and the monitoring service duration ratio of each target business process monitoring index;

determining the business evaluation score based on the first business sub-evaluation score and the second business sub-evaluation score.

In one possible embodiment, the first business sub-valuation score is determined by:

for each target business process monitoring index, determining at least one target business keyword matched with any one of a plurality of monitoring business keywords under the target business process monitoring index in at least one evaluation business keyword under the target business process monitoring index and the occurrence frequency of each target business keyword;

and determining a first business sub-evaluation score based on the at least one target business keyword under each target business process monitoring index and the occurrence frequency of each target business keyword.

In one possible embodiment, the second business sub-valuation score is determined by:

determining the service evaluation service duration ratio corresponding to each target business process monitoring index according to the evaluation service duration of each target business process monitoring index;

and determining a second business sub-evaluation score according to a matching result between the evaluation business service time length ratio of each target business process monitoring index and the corresponding monitoring service time length ratio.

In a possible implementation manner, the obtaining a service evaluation score based on at least one evaluation service keyword included in the annotation service text information includes:

determining at least one target evaluation keyword matched with a plurality of preset service attitude class keywords in the preset performance evaluation model and the occurrence frequency of each target evaluation keyword in the at least one evaluation service keyword;

determining the service evaluation score based on the at least one target evaluation keyword and the number of occurrences of each target evaluation keyword.

In a second aspect, the present application further provides an employee performance evaluation apparatus, where the apparatus includes:

the information acquisition module is used for acquiring the service information of the employee to be evaluated;

the index matching module is used for determining at least one target business process monitoring index matched with the employee to be evaluated from a preset business process monitoring index system based on the business information of the employee to be evaluated; the preset service process monitoring index system is determined based on service processes of different service scenes;

the information marking module is used for marking the service information in a service stage to obtain marked service text information;

and the performance evaluation module is used for inputting the marking service text information into a preset performance evaluation model and determining the performance evaluation result of the employee to be evaluated.

In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method for assessing employee performance according to any one of the first aspect.

In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to execute the steps of the method for evaluating employee performance according to any one of the first aspect.

The employee performance evaluation method, the employee performance evaluation device, the electronic device and the readable storage medium, which are provided by the embodiment of the application, are used for acquiring the business information of the employee to be evaluated, determining at least one target business process monitoring index matched with the business scene where the employee to be evaluated is located from a preset business process monitoring index system according to the business information of the employee to be evaluated, marking the business information according to the at least one target business process monitoring index to obtain marked business text information, inputting the marked business text information into a preset performance evaluation model to obtain the performance evaluation result of the employee to be evaluated, in the embodiment of the application, the business information of the employee to be evaluated is acquired through an intelligent device worn by the employee to be evaluated, the offline performance evaluation of the employee to be evaluated is completed according to the business information, and meanwhile, according to different business scenes, the performance of different employees is evaluated in a targeted manner, the accuracy of performance evaluation is improved, the off-line performance evaluation is digitalized, the evaluation result is fairer, and the quality of off-line business service can be improved better.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

FIG. 1 is a flow chart of a method for employee performance provided by an embodiment of the present application;

FIG. 2 is a flow chart of another employee performance method provided by an embodiment of the present application;

fig. 3 is a schematic structural diagram of an employee performance evaluation device according to an embodiment of the present disclosure;

fig. 4 is a second schematic structural diagram of an employee performance evaluation device according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.

First, an application scenario to which the present application is applicable will be described. The method and the device can be applied to the technical field of data processing.

Research shows that performance evaluation models of employees generally refer to each other according to industry experience at present, then are simply modified into evaluation employee dimensions, generally comprise working attitudes, working capacities, value views and the like, are generally large and extensive concept descriptions, are difficult to accurately quantify in the actual execution process, and perform performance evaluation according to the large and extensive performance evaluation model indexes, wherein the first problem is that no data support can be brought, the first problem is that scoring is basically performed according to subjective evaluation of managers or surrounding employees, and then corresponding evaluation results are formed, and a common evaluation mode is that: self-rating-round rating (his rating) -manager rating, etc., with results presented by way of scoring or rating recognition.

In addition, in another performance evaluation mode, a human management team firstly defines the dimensionality of a performance evaluation model of the staff according to the requirements of a company, wherein the dimensionality comprises working attitude, working performance, working capacity, product innovation capacity, service capacity, cross-team cooperation capacity, value view and the like, a manager performs scoring or grade identification according to the performance of the staff, firstly, the identification of the model is not necessarily suitable for different posts, particularly, the business content and form difference between different industries is large, and the situation that the unified performance evaluation model is suitable for different industries or different posts is difficult to achieve. Secondly, the administrator also has complete perceptual knowledge of the scoring or rating of the employee, and the assessment of the rest items has very strong subjectivity except that the performance can be quantified, and may bring large deviation to the assessment result. Due to the deviation of the evaluation result, information interference may be brought to the selection, use, breeding and remaining of later-period employees, even excellent employees leave the duties, and the labor cost of enterprises is increased. And quantifiable performance is a very important evaluation index for the evaluation of front-line staff, but the quantifiable performance has a large number of influence indexes, such as market environment, client objects, the number of clients, working time periods, and even weather reasons, which may influence the working performance. Therefore, the performance evaluation, the evaluation of particularly excellent staff and the mining of potential staff are true evaluation of multiple dimensions, and are more scientific and credible.

Further, the above-described evaluation method has the following problems: the performance assessment model does not necessarily fit all business scenarios, and the performance assessment models for different business scenarios should be different. The real specific dimensionality of a first-line employee performance evaluation model of an actual business scene cannot be accurately defined; the existing performance evaluation model cannot be objectively, directly and quantifiably evaluated. Resulting in less accurate performance assessment.

Based on the above, the embodiment of the application provides an employee performance evaluation method to improve the accuracy of performance evaluation, so that the online performance evaluation is digitalized, the evaluation result is fairer, and the quality of offline business service can be better improved.

Referring to fig. 1, fig. 1 is a flowchart illustrating an employee performance method according to an embodiment of the present disclosure. As shown in fig. 1, an employee performance method provided by an embodiment of the present application includes:

s101, acquiring service information of the staff to be evaluated.

S102, determining at least one target business process monitoring index matched with the employee to be evaluated from a preset business process monitoring index system based on the business information of the employee to be evaluated; the preset business process monitoring index system is determined based on the service processes of different business scenes.

S103, performing service stage labeling processing on the service information to obtain labeled service text information.

And S104, inputting the marking service text information into a preset performance evaluation model, and determining a performance evaluation result of the employee to be evaluated.

According to the staff performance method provided by the embodiment of the application, the offline performance of different staff can be evaluated in a targeted manner according to different business scenes, the accuracy of performance evaluation is improved, the online performance evaluation is enabled to be digitalized, the evaluation result is fairer, and the quality of offline business service can be better improved.

The following describes exemplary steps in an embodiment of the present application:

s101, acquiring service information of the staff to be evaluated.

In the embodiment of the application, the business information of the staff in the working process can be acquired through the intelligent audio acquisition equipment worn or worn by the staff in the working process.

Here, in the embodiment of the present application, performance evaluation is performed on employees in one work cycle, so when acquiring business information of an employee to be evaluated, it is necessary to acquire the business information in the cycle in which evaluation needs to be performed in real time, and it is necessary to acquire the business information in the cycle in which evaluation needs to be performed.

The service information may be generated based on voice information of an employee to be evaluated in a work cycle (a time period cycle or a work phase cycle), and is obtained after validity processing needs to be performed on the voice information, and in a possible implementation, the service information may be obtained through the following steps:

a 1: and acquiring the work voice information of the employee to be evaluated.

In the embodiment of the application, the working voice information of the staff to be evaluated is acquired through the voice acquisition equipment worn by the staff to be evaluated in one working period.

Here, the work voice information of the employee to be evaluated includes a voice of the employee to be evaluated during the work process, for example, a service conversation voice between the employee to be evaluated and the customer, a product introduction voice of the employee to be evaluated when introducing a relevant product to the customer, and the like.

It should be noted that, in the present application example, all the obtained work voice information of the staff to be evaluated is protected by privacy, and is authorized to be collected by the staff to be evaluated, for example, the staff to be evaluated may wear the voice collecting device only during the working time, and when the voice collecting device starts to perform voice collection on the staff to be evaluated, a prompt (an indicator lamp of the voice collecting device flashes, or a voice broadcast "starts voice collection") may be sent to the staff to be evaluated to prompt the staff to be evaluated to perform the voice collection process.

Furthermore, the voice acquisition time period of the voice acquisition equipment can be set as the working time period of the staff to be evaluated, and when the staff to be evaluated is determined to be off duty, the staff to be evaluated can not wear the voice acquisition equipment any more or can directly control the voice acquisition equipment to shut down, and the voice information of the staff to be evaluated is not collected any more.

a 2: and carrying out validity processing on the working voice information to obtain valid voice information.

In the embodiment of the application, after the work voice information of the employee to be evaluated is acquired, the acquired work information needs to be subjected to validity processing, and useless voice segments are deleted/filtered out, so that the processing time is saved, and the work efficiency is further improved.

The validity processing may include operations such as deleting silent segments from working voice information, and the specific operation may be deleting/filtering segments without sound for a long time, so as to eliminate interference of invalid voice information on subsequent voice recognition processing.

a 3: and performing text conversion processing on the effective voice information to obtain the service information.

In the embodiment of the application, the text conversion processing is performed on the effective voice information after the effective processing, so as to obtain the corresponding service information. And further carrying out service correlation screening processing on the service information, and deleting a great amount of repeated text information irrelevant to the service so as to eliminate the interference of invalid text information on subsequent performance evaluation processing.

In another practical embodiment, the voice information in the working period may be subjected to text processing to obtain unprocessed service text information, and the unprocessed service text information is input into a text recognition model preset in advance, and the text recognition model performs text validity processing such as paragraph space deletion, merging, character elimination and the like on the unprocessed service text information to obtain the service information.

Here, according to the voice service habit of the employee to be evaluated, the working process information of the employee to be evaluated and the business scenario information of the employee to be evaluated can be obtained from the business information, and these pieces of information are all key factors when the employee to be evaluated is evaluated subsequently.

In a possible implementation manner, when the business information of the employee to be evaluated is acquired, in addition to the work voice information of the employee to be evaluated in the working process, the position information of the employee to be evaluated, the state information of the device, and the like can be acquired. The position information can show the work place where the employee to be evaluated is located, and the work state (whether the employee leaves the post, the work position is inconsistent with the action content and the like) of the employee to be evaluated can be determined according to the specific work place.

In the embodiment of the application, when the work voice information of the employee to be evaluated is acquired, the employee information (employee ID, affiliated department information and the like) of the employee to be evaluated is determined at the same time, so that the acquired business information is associated with the employee information, and corresponding business information is extracted correspondingly according to the employee information when the corresponding employee to be evaluated is evaluated subsequently.

In a possible implementation manner, the business scene of the employee to be evaluated can be directly determined according to the employee information of the employee to be evaluated, so that corresponding monitoring indexes can be obtained according to different business scenes in the following, and performance evaluation can be performed on the employee to be evaluated in a targeted manner.

In the embodiment of the application, according to the service information of the employee to be evaluated, which is obtained in step S101, at least one target service process monitoring index matched with the employee to be evaluated is determined from a preset service process monitoring index system, so that performance evaluation is performed on the employee to be evaluated in different dimensions according to each target service process monitoring index.

The preset business process monitoring index system is determined based on the service processes of different business scenes and is a system containing at least one target business process monitoring index in different business scenes.

In the embodiment of the application, at least one target business process monitoring index matched with the staff to be evaluated is determined according to the business scene where the staff to be evaluated is located, when a business process monitoring index system is preset, at least one target business process monitoring index corresponding to each business scene is specified, the business scene where the staff to be evaluated is located is determined, and at least one target business process monitoring index matched with the staff to be evaluated can be determined.

Specifically, in the embodiment of the application, a business scene where a person to be evaluated is located can be obtained by performing semantic analysis on business information, and at least one target business process monitoring index is determined according to the business scene.

For example, during the work process of the employee to be evaluated, the collected work voice includes "you are good, ask what commodity you need to see", "XX commodity has a function of YY", and the like, and it can be known through voice analysis that the employee to be evaluated is in an offline sales scene.

In another possible implementation manner, while the business information of the employee to be evaluated is acquired, the employee information (employee ID, age, department, etc.) of the employee may be acquired to directly determine the business scenario in which the employee to be evaluated is located.

b 1: and determining a plurality of service stages respectively corresponding to different service scenes according to the service flows of the different service scenes.

In the embodiment of the present application, because different service flows or service phases are different in different service scenarios and different service requirements exist, different service phases may exist in different service scenarios, and therefore, a plurality of corresponding service phases in each service scenario need to be specifically determined according to the service flows in different service scenarios.

For example, in a car rental service scenario, the car rental service scenario is specifically divided into a car taking scenario and a car receiving scenario, and further subdivided, and for the car taking scenario, there are 4 service stages: ice breaking communication, car inspection flow, handover completion and identification; for a car pickup scene, there are 6 service phases: icebreaking communication, car-checking flow, expense description, completion of handover, disagreement answering and farewell; for the offline sales scenario, the 6 service phases of the service flow are corresponded: welcome, product recommendation, product introduction, associated sales, singing, and guest sending.

b 2: and determining the service process monitoring indexes corresponding to different service stages according to the different service stages corresponding to each service scene.

In the embodiment of the present application, according to the different service phases corresponding to each service scenario determined in step b1, service flow monitoring indexes corresponding to the different service phases are determined.

Here, for a business scenario, one business phase corresponds to one business process monitoring index, and it is necessary to evaluate the staff to be evaluated in each business phase to determine the performance of the staff to be evaluated in each business phase, and further determine the performance of the staff to be evaluated in the whole evaluation period.

For the above scenario example, there are 4 business process monitoring indexes for the car taking scenario: the method comprises the following steps of (1) performing ice breaking communication monitoring indexes, car inspection process monitoring indexes, finishing handover monitoring indexes and farewell monitoring indexes; aiming at a car receiving scene, 6 service process monitoring indexes exist: the system comprises an icebreaking communication monitoring index, a vehicle inspection process monitoring index, a charge description monitoring index, a completion handover monitoring index, an objection answer monitoring index and a notice monitoring index; aiming at the scene of offline sales, 6 business process monitoring indexes corresponding to the service processes are as follows: welcome monitoring indexes, product recommendation monitoring indexes, product introduction monitoring indexes, related sales monitoring indexes, singing and receiving monitoring indexes and guest sending monitoring indexes.

b 3: and determining a business process monitoring index system according to business process monitoring indexes corresponding to different business stages included in each business scene.

In the embodiment of the application, a business process monitoring index system containing the business process monitoring indexes of each business scene is determined according to the determined business process monitoring indexes corresponding to different business stages of each business scene.

In a possible implementation manner, as a service scene develops or a service requirement changes (a new service phase, a new product, or the like is added), a service flow monitoring index corresponding to each service scene may be updated, and a service flow monitoring index system is updated according to the update of the service flow monitoring index of each service scene, specifically, the service flow monitoring index system may be updated through the following steps:

c 1: and receiving business information of at least one employee.

In the embodiment of the application, the voice acquisition equipment worn by any employee is extracted, and the business information of any employee in the working process is acquired.

Here, the obtained service information may be subjected to validity processing, where the validity processing includes: deleting silent segments of the received voice information of the staff, recognizing the voice, and performing semantic understanding analysis to form effective text information; the service information may also be unprocessed service information (i.e., original voice information generated by a front-line employee in the working process), and validity processing may be performed on the unprocessed service information, where a specific processing process is consistent with the processing process of steps a1-a3, and is not described again.

c 2: and adjusting and updating the preset business process monitoring index system by performing order analysis and cluster analysis on the business information of at least one employee.

In this embodiment of the application, according to the business information of at least one employee obtained in step c1, performing singleton analysis and cluster analysis on the business information of multiple employees obtained within a period of time, thereby determining a change condition of a business process monitoring index in different business scenes according to an analysis result, and adjusting and updating a preset business process monitoring index system.

Here, the adjusting and updating of the business process monitoring index system includes at least one of the following operations: the method comprises the steps of adding a new service process monitoring index, deleting the service process monitoring index, adjusting the sequence of the service process monitoring index and the like, wherein the new service process monitoring index is changed due to service requirements in a service scene, and the more service stages mentioned in the service process can be determined by performing singleton analysis and cluster analysis on the service information of any employee, and at the moment, the service stage is required to be determined as a service process monitoring index and added to the corresponding service scene in a service process monitoring index system; for the reason that the service requirement is changed in the service scene when the service process monitoring index is deleted, the service stage which does not appear in the service process is determined by performing singleton analysis and cluster analysis on the service information of any employee, and at this time, the service stage needs to be deleted from the corresponding service scene in the service process monitoring index system, so as to improve the subsequent performance evaluation efficiency; for adjusting the sequence of the service process monitoring index, due to the change of the service requirement in the service scene, it may be that the order analysis and the cluster analysis are performed on the service information of any employee, although each service phase still exists, the sequence of the service phase is changed, because the sequence of the service process monitoring index corresponding to each service scene in the service process monitoring index system is corresponding to the actual service process, after the sequence of the service phase is determined to be changed, the sequence of the corresponding service phase in the service process monitoring index system also needs to be correspondingly updated.

For example, taking a newly added service flow monitoring index as an example, by analyzing a large amount of form data and comparing the form data with a keyword library of an originally defined service stage, it is found that a large amount of requirement query words or phrases such as keywords "what you need to point", "what can help you", "what you need", "what you want" and the like appear, by judgment and identification, the influence of requirement query on form is considered to be very important, and the requirement query can be added as a service flow monitoring index for performance assessment, so that a service flow monitoring index system can be more perfect.

In the embodiment of the application, the obtained service information is subjected to service stage labeling processing, a service information segment corresponding to each service stage is identified in the service information, and segmented labeling of the service stages is performed in the service information, so that labeled service text information is obtained, wherein labeled content in the labeled service text information corresponds to the service stage in the target service process monitoring index.

When the service phase is labeled, semantic recognition needs to be performed on information included in the service information, a keyword in each piece of voice information included in the service information is extracted, a service phase to which the piece of voice information belongs can be determined according to the keyword, and then a target service flow monitoring index corresponding to the piece of voice information is determined.

In a specific implementation process, business analysis can be performed according to historical work voices of a plurality of employees at different business stages under different business scenes, singleness analysis and clustering analysis are performed on the historical work voices of the plurality of employees at the same time, so that at least one business keyword at each business stage is obtained, when the business information of the employee to be evaluated is labeled, the keyword extracted from the business information of the employee to be evaluated can be matched with the at least one business keyword at each business stage, the business stage to which the employee belongs is determined according to a matching result, and then the business stage is labeled in the business information, so that labeled business text information is obtained.

For example, for an offline sales scenario, the first service stage is "welcome", and in this service stage, it can be known from analysis of historical service information that the keyword in the "welcome" stage is "hello", "welcome", and the like, and when the keyword of a certain piece of service sub-information in the service information of the staff to be evaluated is "hello", please, it can be determined that this piece of service sub-information belongs to the "welcome" stage, and the service stage is labeled in the service information, and labeled as the "welcome" stage.

It should be noted that when labeling the service phase, the service sub-information included in the service information may be labeled one by one, or a plurality of pieces of service sub-information belonging to the same service phase may be labeled uniformly according to the work sequence of the staff to be evaluated, because the staff to be evaluated works online, the work process is continuous, and considering the simplicity and readability of the labeled service text information, the unified service labeling is preferentially selected for the plurality of pieces of service sub-information belonging to the same service phase, the service information segment corresponding to each service phase is determined, and the labeled service text information is obtained by performing the segmented labeling of the service phase in the service information.

In the embodiment of the application, before performance evaluation is performed according to the marked business information of the employee to be evaluated, the working integrity of the employee to be evaluated can be evaluated according to the business stage marked in the marked business information, and if the fact that the work of the employee to be evaluated is incomplete is determined, the fact that the work of the employee to be evaluated is unqualified can be directly determined.

Specifically, the determination method of the work integrity of the employee to be evaluated may be to analyze a plurality of business phases marked in the marked business information, determine whether all business phases in the corresponding business scene are included, and determine that the work of the employee to be evaluated is incomplete if all business phases are not included.

In the embodiment of the application, the text information of the annotation service acquired in step S103 is input into a preset performance evaluation model, and the work of the employee to be evaluated is evaluated according to the preset performance evaluation model, so as to obtain a performance evaluation result of the employee to be evaluated.

Here, the evaluation result for the employee to be evaluated may be a specific evaluation score of the employee to be evaluated, and may also be a performance level (excellent, good, qualified, and unqualified) of the employee to be evaluated, or the like.

It should be noted that, the performance level of the employee to be evaluated is also determined based on the performance evaluation score of the employee, and the evaluation score may be divided into a plurality of score intervals, each score interval corresponding to one performance level, for example, taking the performance evaluation score as 100, the performance level corresponding to more than 90 is excellent, the performance level corresponding to 75 or more and less than 90 is good, the performance level corresponding to 60 or more and less than 75 is qualified, and the performance level corresponding to less than 60 is unqualified.

In the embodiment of the present application, for the performance evaluation model, two processes are divided: the process of constructing the performance evaluation model and the process of using the performance evaluation model will be described below in detail from the construction of the performance evaluation model and the use of the two processes, respectively:

the construction process of the performance evaluation model comprises the following steps:

d 1: and constructing the performance evaluation model based on the preset evaluation indexes and the weight of each preset evaluation index.

In the implementation of the application, the preset evaluation index includes a business process evaluation index and a reference item evaluation index. Specifically, the business process evaluation index includes a ratio of the number of phone usage to the monitoring service duration corresponding to each business process monitoring index, and each business process monitoring index may correspond to a plurality of monitoring phone keywords, and the number of phone usage is obtained by counting the number of occurrences of the monitoring phone keywords in the business information; the reference item evaluation index comprises the usage amount of a preset service attitude class keyword, and the service attitude class keyword is determined by performing keyword clustering analysis according to the business information corresponding to historical form data and the business information corresponding to excellent employees.

In a specific implementation process, aiming at the use amount of the dialect in the service process evaluation index, a corresponding monitoring dialect keyword needs to be set for each service process monitoring index, and aiming at each service process monitoring index, the acquisition mode of the monitoring dialect keyword can be to acquire historical service information of a plurality of employees within a period of time, and perform cluster analysis and form analysis on historical service information data to obtain the monitoring dialect keyword under each service process monitoring index; and the method can also be preset in advance by managers according to business service requirements and actual working scenes of all front-line working sites.

For example, if the occurrence frequency of the speech keywords such as "hello", "welcome", "please" and the like in the welcome reception stage in the online sales scene is relatively high, the keywords can be defined as the monitoring speech keywords in the welcome reception stage; aiming at a product introduction and reception stage in an offline sales scene, product trade name (SKU) data can be input in advance to serve as a monitoring tactical keyword, meanwhile, manual correction and input are carried out according to working voice information acquired by offline voice acquisition equipment, and aiming at the same SKU, data input is carried out on different offline SKU or SKU functional keywords, so that the accuracy and the integrity of the monitoring tactical keyword are ensured. Such as: the 'watermelon frost throat-moistening tablet' can be used for monitoring the key words 'watermelon frost' and 'throat-moistening tablet' in an extensible way.

In a specific implementation process, aiming at the monitoring service duration ratio in the service process evaluation index, the service duration ratio of each employee in each service stage is determined according to the service information of each employee in a period of time, the more reasonable service duration ratio of each service stage is determined through cluster analysis and list formation analysis, specifically, the service stage and the corresponding completion time length in the sale scene under the line are calculated, for example, the start time point T1 of product introduction, the end time point T2 of product introduction and T2-T1 are the duration of the product introduction stage, the ratio of the duration in the consumed duration of the whole sale service process is calculated, and the corresponding list formation result is compared and analyzed through the duration ratio judgment of the different service stages. A reasonable time allocation for each service phase to complete may be determined. That is to say, by analyzing the service information corresponding to a large amount of form data and counting the duration of each service phase, the most elegant time distribution dimension (monitoring service duration ratio) can be obtained, such as: in the monitoring service duration ratio, the period of demand inquiry and product introduction reception should be 60% of the whole sales service process.

In a specific implementation process, specific service attitude class keywords can be determined through cluster analysis and order analysis according to the service attitude class keywords extracted from the business information of the staff within a period of time aiming at the reference item evaluation indexes. Specifically, by combining the speech keywords in the business information corresponding to the single data and the business information corresponding to the excellent employees and performing cluster analysis, it is found that the frequency of occurrence of the speech keywords has a large influence on the single data, for example, by performing keyword cluster analysis on the business information corresponding to the single data, it is found that "can", "do not well" or "help you" and the like are found, the frequency of the speech keywords occurring in the single employees is high, and the speech keywords can be determined as the service attitude class keywords.

It is to be noted that the reference item evaluation index is an evaluation of the service attitude of the employee to be evaluated, and is not strictly divided according to the business phase, and the extraction and evaluation of the jargon key word can be performed for the service phase of the whole employee to be evaluated.

In a possible implementation manner, when any business scenario cannot be strictly divided according to business phases and cannot be evaluated by completely referring to a business process evaluation index and a reference item evaluation index, a performance evaluation model tag library can be formed by setting a large number of conversational keywords with model tags. For example, "this product is used as such", "it can bring … to you", "is good for … …", "is good for", these words are labeled as "product introduction"; the label of the language keywords such as "what you need", "what question", "what you like", "what you want to be the main point", etc. is set as "demand query". And analyzing the business information of the employee to be evaluated according to the set label of the conversational keyword to finish the performance evaluation of the employee to be evaluated.

Here, when the service information subjected to the validation processing is compared and analyzed with a standard performance evaluation model tag library, the dimension related to the performance evaluation model is automatically generated, and may be a presentation form of a radar map (a network map, a spider map, a star map, or a spider web map) or another list presentation form.

The generated tag library can also be updated according to a certain updating period and an evaluation requirement.

In the embodiment of the present application, the setting manner of the weight of each preset evaluation index in the performance evaluation model may be determined by historical business information of an employee with a higher historical yield or an employee with an excellent work evaluation in a period of time. Specifically, business ranking analysis is carried out on all employees based on performance evaluation results, statistical analysis is carried out on different employee performance evaluation results of different performance distribution sections, evaluation indexes with higher values in the performance evaluation results of high-performance employees are defined as values with higher weights, meanwhile, the evaluation indexes are compared and analyzed with capability indexes of low-performance employees, secondary correction is carried out, and therefore the weights of all preset evaluation indexes are determined.

Here, the setting of the weights of the different preset evaluation indexes may also be updated according to a preset update time period, the preset evaluation indexes with high business help and high business performance are enhanced, and the preset evaluation indexes with low business help are correspondingly weakened, so as to obtain the more accurate weight of each preset evaluation index in real time.

(II) usage procedure of performance evaluation model

Referring to fig. 2, fig. 2 is a flowchart illustrating another employee performance method according to an embodiment of the present disclosure. As shown in fig. 2, the step "inputting the text information of the annotation service into a preset performance evaluation model to determine the performance evaluation result of the employee to be evaluated" includes:

s201, obtaining a service evaluation score according to at least one evaluation service keyword under each target service process monitoring index provided in the labeling service text information and the evaluation service duration of each target service process monitoring index.

In the embodiment of the application, keyword extraction is performed on the labeled service text information corresponding to the employee to be evaluated, at least one evaluation service keyword of the employee to be evaluated under each target service flow monitoring index is determined, evaluation service duration of the employee to be evaluated under each target service flow monitoring index is determined according to time information correspondingly obtained when the service information of the employee to be evaluated is obtained, and a service evaluation score of the employee to be evaluated under each service flow evaluation index is determined according to the at least one evaluation service keyword and the evaluation service duration of each target service flow monitoring index.

Specifically, step S201 includes:

e 1: and determining a first business sub-evaluation score according to at least one evaluation business keyword under each target business process monitoring index and a plurality of monitoring business keywords under the target business process monitoring index.

In the embodiment of the application, a first business sub-evaluation score in a business use dimension is calculated according to at least one evaluation business keyword under each target business process monitoring index and a plurality of preset monitoring business keywords under the target business process monitoring index.

Specifically, in one possible implementation, the first business sub-valuation score is determined by:

f 1: and aiming at each target business process monitoring index, determining at least one target business keyword matched with any one of a plurality of monitoring word operation keywords under the target business process monitoring index in at least one evaluation business keyword under the target business process monitoring index, and the occurrence frequency of each target business keyword.

In the embodiment of the present application, it is necessary to calculate the respective usage amount of the target business process according to each target business process monitoring index, and therefore, it is necessary to evaluate a business keyword for each target business process monitoring index to match with a plurality of monitored business keywords under the target business process monitoring index, determine at least one target business keyword hitting the monitored business keyword, and simultaneously count the occurrence frequency of each target business keyword.

Here, for the matching of the evaluation business keyword and the monitoring technology keyword, the evaluation business keyword and the monitoring technology keyword may be completely identical, or the evaluation business keyword and the monitoring technology keyword are semantically identical.

f 2: and determining a first business sub-evaluation score based on the at least one target business keyword under each target business process monitoring index and the occurrence frequency of each target business keyword.

In this embodiment of the application, according to the at least one target business keyword and the occurrence number of each target business keyword under each target business process monitoring index obtained in step f1, performing statistical analysis on the target keywords under all target business process monitoring indexes to determine a first business sub-evaluation score.

Here, for each target business process monitoring index, the index business evaluation score under the target business process monitoring index may be determined by the occurrence number of the target business keyword, specifically, the occurrence number of the target business keyword may be directly determined as the index business evaluation score under the target business process monitoring index, for example, under the target business process monitoring index, the total number of occurrences of a plurality of target business keywords is 10, and then the index business evaluation score under the target business process monitoring index is 10; the total number of times of occurrence of the target business keywords under the target business process monitoring index is counted, and then the index business evaluation score under the target business process monitoring index is determined by multiplying the counted number by a corresponding coefficient, and for the above example, the total number of times of occurrence of the target business keywords is 10 and the counted number of times of occurrence of the target business keywords is multiplied by a corresponding coefficient of 10%, and the index business evaluation score under the target business process monitoring index is determined to be 1.

Here, after the index service evaluation score under each target service process monitoring index is calculated, the index service evaluation scores under each target service process monitoring index may be directly added to obtain a first service sub-evaluation score, or the index service evaluation scores may be weighted and summed according to the weight of each target service process monitoring index to obtain the first service sub-evaluation score.

The setting of the weight of the monitoring index of each target business process is consistent with the setting of the weight of the pre-estimated evaluation index, and is not repeated herein.

e 2: and determining a second business sub-evaluation score according to the evaluation service duration of each target business process monitoring index and the monitoring service duration ratio of each target business process monitoring index.

In the embodiment of the application, a second business sub-evaluation score under the monitoring service duration ratio is determined according to the evaluation service duration of the staff to be evaluated in each target business process monitoring index and the preset monitoring service duration ratio of each target business process monitoring index.

Specifically, in one possible implementation, the second business sub-valuation score is determined by:

g 1: and determining the service evaluation service duration ratio corresponding to each target business process monitoring index according to the evaluation service duration of each target business process monitoring index.

In the embodiment of the application, the service duration of the staff to be evaluated under each target business process monitoring index is determined, and the business evaluation service duration ratio of the staff to be evaluated under each target business process monitoring index is determined according to the total service duration of the staff to be evaluated.

g 2: and determining a second business sub-evaluation score according to a matching result between the evaluation business service time length ratio of each target business process monitoring index and the corresponding monitoring service time length ratio.

In the embodiment of the application, according to the comparison between the evaluation service duration ratio and the monitoring service duration ratio of each target service process monitoring index, whether the work allocation of the staff to be evaluated which comes online is reasonable can be determined, and therefore the second business sub-evaluation score is determined under the dimension of the monitoring service duration ratio.

For example, in the monitoring service duration ratio, the duration ratio of the demand inquiry and product introduction reception phase should be 60% of the whole sales process (complete service flow), and if the duration ratio of the demand inquiry and product introduction reception phase of a certain employee is only 10%, and a large amount of time is distributed in the welcome phase, the second business sub-evaluation score of the monitoring service duration ratio is low.

Specifically, the setting of the second business sub-evaluation score may be set according to requirements, for example, a mapping relationship between a difference interval between the evaluation business service time length ratio and the monitoring service time length ratio and the second business sub-evaluation score is defined, so as to determine the second business sub-evaluation score.

e 3: determining the business evaluation score based on the first business sub-evaluation score and the second business sub-evaluation score.

In the embodiment of the application, the first business sub-evaluation score and the second business sub-evaluation score can be directly added to obtain the business evaluation score; or performing weighted summation according to a first weight corresponding to the first service sub-evaluation score and a second weight corresponding to the second service sub-evaluation score to determine the service evaluation score.

The setting of the first weight and the second weight may be set according to the evaluation requirement, for example, when the employee is evaluated, the usage amount of the business keyword of the employee or the reasonability of the service duration ratio is considered, so as to set the first weight and the second weight, and similarly, the first weight and the second weight may also be updated in time according to the requirement.

S202, obtaining a service evaluation score based on at least one evaluation service keyword included in the annotation service text information.

In the embodiment of the application, the service evaluation score is calculated according to the matching relationship between at least one evaluation keyword and a preset service attitude class keyword included in the labeling service text information of the employee to be evaluated.

Specifically, step S202 includes:

h 1: and determining at least one target evaluation keyword matched with a plurality of preset service attitude class keywords in the preset performance evaluation model and the occurrence frequency of each target evaluation keyword in the at least one evaluation service keyword.

In the embodiment of the application, it is required to determine that at least one evaluation service keyword included in the annotation service text information matches with a plurality of preset service attitude class keywords, determine at least one target evaluation keyword hitting the preset service attitude class keywords, and simultaneously count the occurrence frequency of each target evaluation keyword.

Here, for matching the evaluation service keyword with the service attitude class keyword, the evaluation service keyword may be completely consistent with the service attitude class keyword, or the evaluation service keyword may be substantially semantically consistent with the service attitude class keyword.

h 2: determining the service evaluation score based on the at least one target evaluation keyword and the number of occurrences of each target evaluation keyword.

In the present embodiment, according to the at least one target evaluation keyword obtained in step h1 and the occurrence frequency of each target evaluation keyword, statistical analysis is performed on all target evaluation keywords to determine a service evaluation score.

For example, the service attitude keywords of 'hello' and 'yaho' are counted, and a reference item evaluation index score in the performance evaluation model is defined to be higher when the frequency of occurrence of an employee is higher.

Here, the service evaluation score may be determined by the number of occurrences of the target evaluation keyword, and specifically, the number of occurrences of the target evaluation keyword may be directly determined as the service evaluation score; the service evaluation score can also be calculated conveniently, and the service evaluation score is determined by multiplying the total times of the occurrence of the target evaluation keywords by corresponding coefficients after the total times of the occurrence of the target evaluation keywords are counted.

S203, determining a performance evaluation result of the employee to be evaluated based on the business evaluation score and the service evaluation score.

In the present embodiment, after the service evaluation score determined in step S201 and the service evaluation score determined in step S202 are obtained, a performance evaluation result of the employee to be evaluated is determined.

Specifically, taking the performance evaluation result of the employee to be evaluated as the performance score as an example, the performance score can be obtained by directly adding the business evaluation score and the service evaluation score, and the performance score of the employee to be evaluated is determined; and weighting the business evaluation score and the service evaluation score according to corresponding weights to determine the performance score of the employee to be evaluated.

The setting of the weights corresponding to the service evaluation score and the service evaluation score is consistent with the setting of the weight of the pre-estimated evaluation index, and is not repeated here.

The employee performance evaluation method provided by the embodiment of the application comprises the steps of obtaining business information of an employee to be evaluated, determining at least one target business process monitoring index matched with a business scene where the employee to be evaluated is located from a preset business process monitoring index system according to the business information of the employee to be evaluated, marking the business information according to the at least one target business process monitoring index to obtain marked business text information, inputting the marked business text information into a preset performance evaluation model to obtain a performance evaluation result of the employee to be evaluated, collecting the business information of the employee to be evaluated through intelligent equipment worn by the employee to be evaluated, and evaluating offline performances of different employees in a targeted manner, so that the accuracy of performance evaluation is improved, the offline performance evaluation is realized in a datamation manner, and the evaluation result is more fair, the quality of the service under the line can be better improved.

Based on the same inventive concept, the embodiment of the present application further provides an employee performance evaluation device corresponding to the employee performance evaluation method, and as the principle of the device in the embodiment of the present application for solving the problem is similar to the employee performance evaluation method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and repeated details are omitted.

Referring to fig. 3 and 4, fig. 3 is a schematic structural diagram of an employee performance evaluation device according to an embodiment of the present disclosure, and fig. 4 is a second schematic structural diagram of an employee performance evaluation device according to an embodiment of the present disclosure. As shown in fig. 3, the evaluation device 300 includes:

the information acquisition module 310 is used for acquiring the service information of the employee to be evaluated;

the index matching module 320 is configured to determine, based on the business information of the employee to be evaluated, at least one target business process monitoring index matched with the employee to be evaluated from a preset business process monitoring index system; the preset service process monitoring index system is determined based on service processes of different service scenes;

the information labeling module 330 is configured to perform labeling processing on the service information at a service stage to obtain labeled service text information;

and the performance evaluation module 340 is configured to input the text information of the annotation service into a preset performance evaluation model, and determine a performance evaluation result of the employee to be evaluated.

In one possible implementation, as shown in fig. 4, the evaluation apparatus 300 further includes a system determination module 350, and the system determination module 350 is configured to:

In a possible implementation, as shown in fig. 4, the evaluation apparatus 300 further includes a model building module 360, and the model building module 360 is configured to:

In one possible implementation, as shown in fig. 4, the evaluation apparatus 300 further includes a hierarchy updating module 370, where the hierarchy updating module 370 is configured to:

receiving business information of at least one employee;

In a possible implementation manner, the information obtaining module 310 is configured to obtain the service information by:

acquiring work voice information of the employee to be evaluated;

In a possible implementation manner, when the performance evaluation module 340 is used for inputting the annotation service text information into a preset performance evaluation model to determine a performance evaluation result of the employee to be evaluated, the performance evaluation module 340 is used for:

In a possible implementation manner, when the performance evaluation module 340 is configured to obtain a service evaluation score according to at least one evaluation service keyword under each target service process monitoring indicator set forth in the annotation service text information and the evaluation service duration of each target service process monitoring indicator, the performance evaluation module 340 is configured to:

In one possible implementation, the performance assessment module 340 is configured to determine the first business sub-assessment score by:

In one possible implementation, the performance assessment module 340 is configured to determine the second business sub-assessment score by:

In one possible implementation, when the performance evaluation module 340 is configured to obtain a service evaluation score based on at least one evaluation service keyword included in the annotation service text information, the performance evaluation module 340 is configured to:

The employee performance evaluation device provided by the embodiment of the application obtains the business information of an employee to be evaluated, determines at least one target business process monitoring index matched with a business scene where the employee to be evaluated is located from a preset business process monitoring index system according to the business information of the employee to be evaluated, marks the business information according to the at least one target business process monitoring index to obtain marked business text information, inputs the marked business text information into a preset performance evaluation model to obtain a performance evaluation result of the employee to be evaluated, in the embodiment of the application, the business information of the employee to be evaluated is collected through an intelligent device worn by the employee to be evaluated, the offline performance evaluation of the employee to be evaluated is completed according to the business information, meanwhile, the performance of different employees can be evaluated in a targeted manner according to different business scenes, the accuracy of performance evaluation is improved, the off-line performance assessment is digitalized, the assessment result is fairer, and the quality of off-line business service can be better improved.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 5, the electronic device 500 includes a processor 510, a memory 520, and a bus 530.

The memory 520 stores machine-readable instructions executable by the processor 510, when the electronic device 500 runs, the processor 510 and the memory 520 communicate through the bus 530, and when the machine-readable instructions are executed by the processor 510, the steps of the method for evaluating employee performance in the method embodiments shown in fig. 1 and fig. 2 may be performed.

The embodiment of the present application 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 steps of the employee performance evaluation method in the method embodiments shown in fig. 1 and fig. 2 may be executed.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An assessment method of employee performance, the assessment method comprising:

acquiring business information of an employee to be evaluated;

2. The evaluation method according to claim 1, wherein the predetermined business process monitoring index system is determined by:

3. The assessment method of claim 1, wherein said performance assessment model is constructed according to the following steps:

4. The evaluation method according to claim 3, wherein the business process evaluation index includes a ratio of a telephone usage amount and a monitoring service duration corresponding to each business process monitoring index; wherein, each business process monitoring index corresponds to a plurality of monitoring words and operation keywords.

5. The evaluation method according to claim 3, wherein the reference item evaluation index includes usage amount of a preset service attitude class keyword; wherein, the service attitude class key words are determined according to historical formation data and key words of excellent employees.

6. The evaluation method according to claim 1, wherein the service information is obtained by:

acquiring work voice information of the employee to be evaluated;

7. The evaluation method according to claim 1, further comprising:

receiving business information of at least one employee;

8. The assessment method according to claim 1, wherein the inputting of the annotation service text information into a preset performance assessment model to determine the performance assessment result of the employee to be assessed comprises:

9. The evaluation method according to claim 8, wherein the obtaining a service evaluation score according to at least one evaluation service keyword under each target service process monitoring index proposed in the annotation service text message and the evaluation service duration of each target service process monitoring index comprises:

10. The evaluation method of claim 9, wherein the first business sub-evaluation score is determined by:

11. The evaluation method of claim 9, wherein the second business sub-evaluation score is determined by:

12. The evaluation method according to claim 8, wherein said deriving a service evaluation score based on at least one evaluation service keyword included in the annotation service text message comprises:

13. An assessment device for employee performance, said assessment device comprising:

14. An electronic device, comprising: memory, processor and computer program stored in the memory and executable on the processor, characterized in that the processor is adapted to implement the method of assessment of employee performance as claimed in any one of claims 1 to 12 when executing the computer program stored in the memory.

15. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of assessing the performance of an employee as claimed in any one of claims 1 to 12.