CN117541406A

CN117541406A - Service early warning method, device, computer equipment and storage medium

Info

Publication number: CN117541406A
Application number: CN202311731757.3A
Authority: CN
Inventors: 王宇
Original assignee: China Life Insurance Co ltd
Current assignee: China Life Insurance Co ltd
Priority date: 2023-12-15
Filing date: 2023-12-15
Publication date: 2024-02-09

Abstract

The application relates to a business early warning method, a business early warning device, computer equipment and a storage medium. Obtaining business data in a preset statistical period based on each unit of business data of business in each unit statistical period when the business progress statistical condition is met, determining business progress information of the business based on the preset statistical period, the business data and a corresponding business data target value, generating business early warning information based on the business progress information and the target business progress information when the business progress information does not meet the preset business progress condition, and sending the business early warning information to an executing mechanism corresponding to the business. Compared with the traditional mode of checking and early warning under the manual line, the method and the device have the advantages that the service progress information of the service is determined based on the statistical period, the service data and the corresponding service data target value, and when the service progress information does not meet the service progress condition, the corresponding service early warning information is sent to the corresponding actuating mechanism of the service, so that the accuracy of service early warning is improved.

Description

Service early warning method, device, computer equipment and storage medium

Technical Field

The present invention relates to the technical field of financial insurance business, and in particular, to a business early warning method, apparatus, computer device, storage medium and computer program product.

Background

In the processing process of the financial insurance service, each service personnel can generate a large amount of service data, and in order to ensure the normal operation of the financial insurance service, a corresponding service target needs to be set for the financial insurance service so as to promote the relevant service personnel to actively execute the corresponding financial insurance service. At present, a mode of reminding and early warning the business progress of a financial insurance business is generally to realize business early warning by carrying out progress comparison on the line of related business personnel after displaying business progress data in a public manner. However, early warning is carried out in an off-line comparison mode, so that the condition of index observation omission is easily caused, and the accuracy of service early warning is not high.

Therefore, the current business early warning method for the financial insurance business has the defect of low accuracy.

Disclosure of Invention

Based on the foregoing, it is necessary to provide a service early warning method, apparatus, computer device, computer readable storage medium and computer program product capable of improving early warning accuracy.

In a first aspect, the present application provides a service early warning method, where the method includes:

when the condition of satisfying the business progress statistics is detected, determining the business to be counted and the corresponding unit statistics period;

obtaining service data in a preset statistic period according to at least one unit service data of the service in at least one unit statistic period;

acquiring a business data target value preset by the business in the preset statistical period, and determining business progress information of the business according to the preset statistical period, the business data and the business data target value;

and if the business progress information does not meet the preset business progress condition, generating business early warning information according to the business progress information and the target business progress information, acquiring an executing mechanism corresponding to the business, and sending the business early warning information to the executing mechanism.

In one embodiment, the method further comprises:

acquiring a total target value of service data in a preset time period preset by an execution mechanism of the service; the service data total target value is determined based on historical service data of the executing mechanism;

And determining at least one preset statistical period according to the preset time period, and storing service data target values corresponding to the preset statistical periods according to the service data total target value.

In one embodiment, the determining the traffic to be counted and the corresponding unit counting period includes:

determining the data type of the service;

and determining a unit statistical period corresponding to the service according to the data type.

In one embodiment, the data type includes at least one of business resource data and business personnel data; the determining the unit statistical period corresponding to the service according to the data type comprises the following steps:

if the data type is business resource data, determining the unit statistical period as a first unit statistical period;

if the data type is business personnel data, determining the unit statistical period as a second unit statistical period;

wherein the first unit statistical period is smaller than the second unit statistical period.

In one embodiment, the determining the service progress information of the service according to the preset statistical period, the service data and the service data target value includes:

Determining cycle starting time and cycle ending time according to the preset statistical period, and acquiring recording time corresponding to the service data;

obtaining sequence time progress information corresponding to the service according to the recording time, the cycle starting time and the cycle ending time;

obtaining task progress information corresponding to the service according to the service data and the service data target value;

and obtaining the business progress information of the business according to the time sequence progress information and the task progress information.

After the service progress information of the service is determined, the method further comprises the following steps:

and if the numerical value of the task progress is detected to be smaller than the numerical value of the time sequence progress, determining that the business progress information does not meet the preset business progress condition.

acquiring the same-ratio business data corresponding to the same-ratio preset statistical period corresponding to the preset statistical period;

and determining the business progress information of the business according to the ratio of the business data to the same-ratio business data.

if the ratio of the service data to the same-ratio service data is smaller than one, determining that the service progress information does not meet a preset service progress condition.

In one embodiment, the actuators are stored in a preset mechanism relationship table, the mechanism relationship table including dependencies between the plurality of actuators;

acquiring the business progress information of each peer of executing mechanism corresponding to the executing mechanism;

and sequencing the business progress information and the business progress information of each peer, and if the ranking of the business progress information is detected to be in a preset ranking range, determining that the business progress information does not meet a preset business progress condition.

In a second aspect, the present application provides a service early warning device, where the device includes:

the detection module is used for determining the business to be counted and the corresponding unit counting period when the business progress counting condition is detected to be met;

the acquisition module is used for acquiring service data in a preset statistic period according to at least one unit service data of the service in at least one unit statistic period;

The determining module is used for obtaining a service data target value preset by the service in the preset statistical period and determining service progress information of the service according to the preset statistical period, the service data and the service data target value;

and the early warning module is used for generating service early warning information according to the service progress information and the target service progress information if the service progress information does not meet the preset service progress condition, acquiring an executing mechanism corresponding to the service, and sending the service early warning information to the executing mechanism.

In a third aspect, the present application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when the processor executes the computer program.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method described above.

In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of the method described above.

According to the business early warning method, the business early warning device, the computer equipment, the storage medium and the computer program product, business data in a preset statistical period are obtained based on at least one unit business data of business in at least one unit statistical period when business progress statistical conditions are met, business progress information of the business is determined based on the preset statistical period, the business data and corresponding business data target values, and when the business progress information does not meet the preset business progress conditions, business early warning information is generated based on the business progress information and the target business progress information and is sent to an executing mechanism corresponding to the business. Compared with the traditional mode of checking and early warning under the manual line, the method and the device have the advantages that the service data of the service are counted according to the preset counting period, the service progress information of the service is determined based on the period, the service data and the corresponding service data target value, and when the service progress information does not meet the service progress condition, the corresponding service early warning information is sent to the corresponding actuating mechanism of the service, so that the accuracy of service early warning is improved.

Drawings

FIG. 1 is an application environment diagram of a business early warning method in one embodiment;

FIG. 2 is a flow chart of a business early warning method in one embodiment;

FIG. 3 is an interface diagram of business pre-warning in one embodiment;

FIG. 4 is a schematic diagram of an interface of an early warning device in one embodiment;

FIG. 5 is a schematic diagram of the structure of the early warning information in one embodiment;

FIG. 6 is a flow chart of early warning detection in one embodiment;

FIG. 7 is a schematic diagram of a flow of early warning pushing in an embodiment;

FIG. 8 is a schematic diagram of an interface for traffic alert information in one embodiment;

FIG. 9 is a schematic diagram of a structure of service data in one embodiment;

FIG. 10 is a schematic diagram of the structure of index data in one embodiment;

FIG. 11 is a schematic diagram of a business objective in one embodiment;

FIG. 12 is a schematic diagram showing a business progress determination step in one embodiment;

FIG. 13 is a timing diagram of a traffic alert method in one embodiment;

FIG. 14 is a block diagram of a business alert device in one embodiment;

fig. 15 is an internal structural view of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The service early warning method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal communicates with the server through a network. The data storage system may store data that the server needs to process. The data storage system may be integrated on a server, or may be placed on a cloud or other network server, where the data storage system includes a database and an ODS (Operational Data Store, operation data storage) data warehouse, etc. The terminal is also called as a front end of the data billboard, and can be used for displaying corresponding service data, providing a corresponding service setting page and an early warning information display page for a user, setting corresponding service progress statistics conditions in the terminal by the user, and sending the service progress statistics conditions to the server, and summarizing and sending the service data generated by the service to the server, wherein the server is used for storing the corresponding service data. The server is also called a data billboard access terminal, and can acquire corresponding service data from the data storage system and judge whether the service progress condition is met when the service progress statistics condition is detected to be met, and send corresponding service early warning information to the terminal when the service progress condition is not met, so that the terminal can display the corresponding service early warning information. The terminal may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, which may be smart watches, smart bracelets, headsets, etc. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.

In one embodiment, as shown in fig. 2, a service early warning method is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps:

step S202, when the condition of the business progress statistics is detected to be met, the business to be counted and the corresponding unit statistics period are determined.

The service may be a service in a financial field, and before the service is executed, a target to be achieved by the service in a period of time may be preset, so as to implement a staged operation plan of the service. The objective to be achieved by the service may be that the service data of the service needs to reach a preset value within a period of time. In the service execution process, the server can continuously detect the completion condition of the service, for example, the server can continuously detect whether the service progress statistics condition is met currently, and when the service progress statistics condition is detected to be met, the server can determine the service to be counted based on the service progress statistics condition met currently. The service progress statistics conditions may have a plurality of conditions, and each condition may correspond to a different service.

After the server determines the service to be counted based on the service progress statistics condition, the unit statistics period of the service to be counted can also be determined. The unit statistical period represents the minimum statistical period of the service, and a plurality of unit statistical periods can form a complete statistical period.

The service may be executed by a corresponding executing mechanism, where each executing mechanism has a service execution preference and an operation rhythm corresponding to the executing mechanism, and the service data target value corresponding to the service to be counted may correspond to the executing mechanism. The server may store in advance business data target values set for business execution preferences and operation rhythms of different actuators. The business data target value represents a target to be achieved by the execution mechanism for executing the numerical value of the business in a preset time period, and the business data target value is also called a staged operation target. Specifically, the user may upload the set staged business data target value to the server in a table form based on the operation rhythm of the current executing mechanism, and the server parses the table file into the business data target value of each executing mechanism row by row and stores the business data target value in the database.

Step S204, obtaining the business data in the preset statistic period according to at least one unit business data of the business in at least one unit statistic period.

When the service is executed, corresponding service data, such as resource values for the user to transact the service transaction, etc., can be generated. When the server counts the service to be counted, the unit counting period of the service can be determined, and at least one unit service data of at least one unit counting period in a preset counting period is obtained, so that the server can obtain the service data in the preset counting period according to the at least one unit service data.

The data types of the services can be various, and for different types of services, the server can collect the data based on different unit statistical periods. Specifically, the terminal may upload the service data of each service to the ODS data repository in the server for storage, the server may start the progress calculation task at regular time, and obtain each unit service data of each unit statistics period corresponding to each service from the unified ODS data repository, and the server may synchronize each unit service data to the database of the system and execute the task progress calculation task.

Step S206, obtaining a business data target value preset by the business in a preset statistical period, and determining business progress information of the business according to the preset statistical period, the business data and the business data target value.

After obtaining the service data in the preset statistical period, the server can calculate the service progress information. The server may obtain, in advance, a service data target value preset by the service in a preset statistical period, where the service data target value may be a target value that needs to be reached by service data of the service in the preset statistical period. The server may determine service progress information of the service based on the preset statistical period, service data, and service data target value. The server may determine the business progress information of the business through various algorithms based on the preset statistical period, the business data and the business data target value, including but not limited to determining the business progress information through algorithms such as time-of-sequence progress, comparison progress and progress ranking.

Step S208, if the business progress information does not meet the preset business progress condition, generating business early warning information according to the business progress information and the target business progress information, acquiring an execution mechanism corresponding to the business, and sending the business early warning information to the execution mechanism.

After determining the service progress information of the service, the server may compare the service progress information with a preset service progress condition. The business progress condition may include various forms, such as, but not limited to, numerical, percentage, and ranking range thresholds. If the business progress information does not meet the corresponding business progress conditions, the server can generate business early warning information according to the business progress information and the target business progress information, acquire an execution mechanism corresponding to the business, and send the business early warning information to the corresponding execution mechanism, so that a corresponding user can see the displayed business early warning information in a terminal of the execution mechanism, and take corresponding measures to process the business early warning information.

Specifically, the service early warning information may be displayed on an interface as shown in fig. 3, and fig. 3 is a schematic diagram of the interface of the service early warning in one embodiment. The page shown in fig. 3 may be a service management page corresponding to the executing mechanism. In some embodiments, the services include resource services and personnel services, wherein personnel services represent personnel information owned by an actuator, also referred to as team services. The server may display information such as team data, team data statistics, business data statistics, early warning data, etc. in the page shown in fig. 3. The team data comprises executive conditions of personnel business of an executive mechanism, business data can display business progress information of each business, and the server can display a team data statistical chart representing personnel variation conditions and a business data statistical chart representing business data variation conditions in a chart form. Wherein personnel changes include personnel increasing manpower, personnel releasing manpower, and the like. And the server can also display the business early warning information which does not meet the preset business progress condition.

The server can start early warning detection and early warning pushing tasks at regular time, the early warning detection task can determine an executing mechanism triggering service early warning information and a corresponding service data target value through the steps, the server sends the service early warning information to an IM ((Instant Messaging, real-time communication system) system of the executing mechanism through the early warning pushing task to realize notification to a user, and after the user receives the notification, the user can visually analyze the system or check detailed service progress information.

The server may define an early warning rule in advance, that is, a pushing rule of the service early warning information. As shown in fig. 4, fig. 4 is an interface schematic diagram of the early warning device in one embodiment. The user can set the early warning rule in the page as shown in fig. 4. For example, the decision maker self-defines the data early warning rule based on the business operation rhythm of the execution mechanism, wherein the business data target value of the execution mechanism of each business can correspond to the operation preference and habit of the execution mechanism so as to realize personalized assessment. Specifically, the rules that the page of the early warning setting can be configured include, but are not limited to, early warning type, early warning index, early warning time, early warning mechanism, early warning rule, early warning frequency, whether to push through IM, push target configuration item, and the like. The early warning index can be set to be any data index of the visual analysis system, such as corresponding type business data and the like; the calculation mode supports definition modes such as the same ratio, the time sequence progress, the ranking and the like. The method comprises the steps of determining whether early warning is needed or not in a mode of calculating the same-ratio data of the service, determining whether early warning is needed or not in a sequence time progress mode by comparing time progress and the progress of the service data, and determining whether early warning is needed or not in a ranking mode by calculating the ranking of the service progress in each execution mechanism.

The related information of the service early warning can be stored in a database of the server, and the related information comprises rule information, specific forms of the service early warning information and the like. Specifically, as shown in fig. 5, fig. 5 is a schematic structural diagram of early warning information in an embodiment. The early warning related information can be stored in an ER diagram mode, and comprises early warning indexes, early warning rules, early warning results, early warning messages and other entities. The early warning index defines the name, index name and index code of a database table which needs to be subjected to early warning index, is used for providing an optional index list for a user, and is used for positioning a program to a corresponding system index value. Wherein different metrics represent different types of traffic.

The early warning rules define organization codes, start-stop time, push targets, early warning types, calculation rules and the like for the early warning to take effect. The actuating mechanism can be correspondingly provided with a corresponding lower-level actuating mechanism, and the mechanism code indicates that the current mechanism and all lower-level mechanisms thereof need to be subjected to early warning detection according to the rule; the calculation rule is stored in json format, and the calculation mode and the corresponding threshold value are recorded, for example, the calculation mode is ranking, the threshold value lower bound is 5, and the upper bound is 10, and the calculation rule is triggering early warning operation of ranking 5-10 in all lower mechanisms of the same upper mechanism; the push target field is multiple options, and can select the positions of an organization management layer, an upper-level organization management layer, a provincial level operator and the like. Each pre-warning rule is associated with a pre-warning indicator.

When the server needs to push the service early warning information, a push message can be generated for each user needing to be pushed at a specified time point according to the push rules and the push targets in the early warning rules. The early warning message defines the push time, the number of the pushed person and the push status. Each early warning message is associated with a corresponding early warning result, the different types of services can be stored in different data tables, and the server can obtain all the services which are corresponding to the execution mechanism and need to be early warned by associating two data tables with different service types, so that the pushing program can push the early warning information to the target user according to the association results of the two tables.

In some embodiments, the server may start the service progress detection task at regular time, as shown in fig. 6, and fig. 6 is a schematic flow chart of early warning detection in one embodiment. The task is started every day in a timing manner through the dispatching platform, the server can receive the called information through the application program interface and trigger early warning detection, and after receiving the request, the server can inquire early warning rules which are effective in all current time periods from the database, namely, the server detects which services are still in the effective period and which services are configured with the early warning rules which are still effective in the current time period. The server can circularly traverse all the early warning rules and traverse index data of a corresponding executing mechanism in the database based on index codes configured by each early warning rule, wherein the index codes represent the types of the services and the index data represent the data of the services. And the server judges whether the index of the current executing mechanism reaches the condition of triggering early warning based on the calculation rule, namely whether the condition of the business progress is met, if not, all the executing mechanisms reaching the condition of triggering early warning and corresponding business data, namely index values, are recorded, and the index values are written into an early warning result table to form business early warning information.

In addition, the server can push the early warning information according to the set rule. As shown in fig. 7, fig. 7 is a schematic flow chart of early warning pushing in an embodiment. The scheduling platform can be connected with the server, the scheduling platform starts tasks every day at regular time, and the starting time of the pushing tasks can be set to be after the early warning detection tasks are received by the server, and the early warning information pushing tasks are started after the server receives the request of the scheduling platform. The server can query all message records to be pushed on the same day from the database, the message records can be execution mechanisms needing to be pushed, the server can traverse all message records, and the corresponding early warning results are associated to generate early warning message, namely service early warning information. The early warning message comprises an early warning mechanism, an early warning index, an index definition, an early warning time range, an early warning threshold value and a current index value. Wherein the index represents a service, and the index value represents a numerical value of service data.

In addition, in order to optimize the pushing efficiency and avoid pushing a large amount of messages to each user, the server may further aggregate the messages of the same user into a data table, for example, cluster the service early warning information of the same user to form a table picture, as shown in fig. 8, and fig. 8 is an interface schematic diagram of the service early warning information in an embodiment. When the server determines that a certain user has a plurality of service early warning information, the corresponding plurality of service early warning information can be integrated into a form picture to be pushed. The service early warning information can represent early warning information of a certain user in the executing mechanism, the server can push the service early warning information into the IM system through an IM system interface of the corresponding executing mechanism, and after the IM system receives the service early warning information, the service early warning information can be sent to the corresponding user according to a user identifier in the service early warning information, such as a user work number, so that targeted service early warning notification is realized.

In the service early warning method, when the service progress statistics condition is met, service data in a preset statistics period is obtained based on at least one unit service data of a service in at least one unit statistics period, service progress information of the service is determined based on the preset statistics period, the service data and a corresponding service data target value, and when the service progress information does not meet the preset service progress condition, service early warning information is generated based on the service progress information and the target service progress information and is sent to an executing mechanism corresponding to the service. Compared with the traditional mode of checking and early warning under the manual line, the method and the device have the advantages that the service data of the service are counted according to the preset counting period, the service progress information of the service is determined based on the period, the service data and the corresponding service data target value, and when the service progress information does not meet the service progress condition, the corresponding service early warning information is sent to the corresponding actuating mechanism of the service, so that the accuracy of service early warning is improved.

In one embodiment, further comprising: acquiring a total target value of service data in a preset time period preset for an execution mechanism of the service; the total target value of the service data is determined based on the historical service data of the executing mechanism; and determining at least one preset statistical period according to the preset time period, and storing service data target values corresponding to the preset statistical periods according to the total target value of the service data.

In this embodiment, the service data target value of the preset statistics period may be obtained by segmentation. The preset time period may be a time period greater than a time span of a preset statistical period, and the server may acquire a total target value of service data within the preset time period, which is preset for an actuator of the service. Wherein the total target value of the service data can be determined according to the historical service data of the executing mechanism. For example, the difference between the value of the total target of traffic data at the later time period and the value of the historical traffic data may be less than a preset value threshold.

The server may determine at least one preset statistical period according to the preset time period, and store the service data target value corresponding to each preset statistical period according to the total service data target value. For example, when the number of preset statistical periods is two, the service data target value of each preset statistical period may be the total service data target value divided by two. Specifically, assuming that the preset time period is two months, the server can determine that the preset statistical period is one month through segmentation, and the server determines the business progress information in the preset time period by combining the business data of the two preset statistical periods. The unit statistics periods of the service data included in the preset statistics periods may be different due to different unit statistics periods corresponding to different types of services.

According to the embodiment, the server can determine the business data target value of each preset statistical period by dividing the preset time period into at least one preset statistical period, and can determine the business data progress in the preset time period by collecting the business data of at least one preset statistical period, so that the accuracy of business progress early warning is improved.

In one embodiment, determining the traffic to be counted and the corresponding unit counting period thereof includes: determining the data type of the service; and determining a unit statistical period corresponding to the service according to the data type.

In this embodiment, services of different data types may correspond to different unit statistic periods. When the server detects the progress of the service, the data type of the service can be determined, and the unit statistical period corresponding to the service is determined according to the data type. Wherein, the data type may include at least one of service resource data and service personnel data. The business resource data represents data of virtual resources generated by executing the business, and the business personnel data represents variation data of business personnel in the executing mechanism. In one embodiment, if the server detects that the data type is service resource data, the server may determine that the unit statistic period is the first unit statistic period. If the server detects that the data type is business personnel data, the server can determine that the unit statistical period is a second unit statistical period. Wherein the first unit statistical period is smaller than the second unit statistical period.

Specifically, for the service resource data, the unit statistics period of the service resource data can be hours, that is, the server can count the progress of the service resource data per hour; for business personnel data, the unit statistical period can be a day, i.e. the server can count the business personnel data every day. The data of the unit statistical period can be summarized to form service data in a preset statistical period and a preset time period. The unit statistical period may be stored in a regular form in a database. Wherein the database comprises a multi-layer structure. As shown in fig. 9, fig. 9 is a schematic diagram of a structure for storing service data in one embodiment. The structure and data flow of the service early warning information are composed of an original data layer, a summary data layer and an assessment data layer.

The early warning rule management module in the assessment early warning layer can be used for defining early warning rules; the early warning pushing module can open the instant communication system of the executing mechanism, when a certain mechanism triggers early warning, the server automatically sends a message to the management layer of the corresponding mechanism through the instant communication system, and active notification is realized, so that the management layer is helped to timely learn about the business management problem. The early warning display module can display early warning data of an executing mechanism and a subordinate mechanism to which a current user belongs in the visual analysis system, and the user can check detailed early warning information comprising index values, business data target values, budget completion rates, difference gaps, comparison data, early warning pushing time, pushing times and the like by clicking early warning items.

The service resource summary of the summary data layer may include a service resource value table of each execution mechanism, including service resource values of total service resource value, first-year traffic, first-year standard of long-term service, decade and above standard of three-year, short-term service, health service, comprehensive persistence rate, and the like. The server can store data for two years by taking a day as a time unit, and the server can update the stored business resource data according to the incremental business resource data every hour, so that the effectiveness is ensured. The team summary may include a team data table of each actuator, where the team data table includes information about service personnel, and the team data table may include data for measuring development of the team, such as, for example, a certification man power, a comprehensive lifting man power, an effective man power, a star man power, a personnel augmentation man power, and a decompaction man power. The server may store data in days for two years and update daily.

The data summarizing processing module can summarize through a plurality of processing links according to the effectiveness of data updating and the type of data. For example, for the service data with the unit statistics period of days, which is the day-level update, the server can start the data processing task in the early morning every day, and calculate the accumulated service resources and team data which are cut off to the time of the previous day; for the service data with the unit statistics period of hours, which is the hour-level update, the server can start the data processing task at regular time every hour, calculate the increment service resource data which is up to the previous hour, and accumulate and update the increment service resource data into the service resource data of the current day.

The policy data module of the original data layer can store a full amount of service resource data table for summarizing and processing service resources and partial service personnel data, such as comprehensive lifting manpower, effective manpower and the like. The mechanism information module stores a mechanism information table, wherein the mechanism information table records all levels of provinces, cities, counties, network points and job sites and the hierarchical relation thereof, and the summarizing program of the server can summarize the statistical data of the business data of each level of mechanism layer by layer according to the data of the table. The business personnel information module can store a business personnel information table, records the information of the organization attribution, the jurisdictional relation, the recommendation relation, the job time, the job status and the like of the business personnel, and is used for summarizing and processing part of team indexes.

The service data may be stored in a table form in a server, as shown in fig. 10, and fig. 10 is a schematic structural diagram of index data in an embodiment. Including a business resource data table and a team data table. The service resource data table is used for storing various service resource data of each organization, and two fields of time dimension and service date are designed for supporting the early warning function of flexibly defining the time range. The service date indicates what day of service data is counted by the data, and the database stores data of each day in two years to support the calculation of the same ratio. The time dimension represents the time span of the data statistics, supporting day, week, month, season, year and custom periods. If the time period is a month, the statistics of the data is to summarize the service resource data within a month before the service date, and the rest is the same. The organization codes represent the effective execution mechanisms of the data, and index data are summarized up layer by layer according to organization architecture trees of organization relations in the calculation flow, so that the index data of each level of the job site, the network point, the district, the city and the province are counted.

The team data table may be used to store team data of each actuator, i.e., business person data of each actuator, and its design concept is the same as that of the business resource data table. The business data target value may be obtained by including a combination result of the business resource data table and the team data table, and may be stored in a table form. Specifically, as shown in fig. 11, fig. 11 is a schematic structural diagram of a business object in one embodiment. The business data target table may store staged business data target values tailored by the respective actuators. The time dimension corresponds to the time dimension of the service resource data table and the team data table, and represents the current preset statistical period. The start time and the deadline define the currently preset service validation period. In order to support the business data target value to be flexibly disassembled into multi-stage sub-targets according to the experience preference and habit of the execution mechanism, a server can introduce a superior target coding field for recording the master-slave relation of the business data target value; each target field is a specific target value of the corresponding service data. The system associates the target table with the business resource data table and the team data table every day, thereby calculating the business data target achievement status of each executing mechanism.

Through the embodiment, the server can count the service data according to different data types and different unit counting periods, and further the server acquires and early warns the service progress information by collecting the service data of different unit counting periods, so that the accuracy of service early warning is improved.

In one embodiment, determining the business progress information of the business according to the preset statistical period, the business data and the business data target value comprises: according to a preset statistical period, determining a period starting time and a period ending time, and acquiring a recording time corresponding to service data; obtaining sequence time progress information corresponding to the service according to the recording time, the cycle starting time and the cycle ending time; obtaining task progress information corresponding to the service according to the service data and the service data target value; and obtaining the business progress information of the business according to the time sequence progress information and the task progress information.

In this embodiment, the server may determine the service progress information in various manners. For example, the server may determine the period start time and the period end time according to the preset statistical period, and obtain the recording time corresponding to the service data. The server obtains the time sequence progress information corresponding to the service according to the recording time, the cycle starting time and the cycle ending time, and obtains the task progress information corresponding to the service according to the service data and the service data target value, so that the server can obtain the service progress information of the service according to the time sequence progress information and the task progress information. That is, the server can determine the business progress information through the comparison of the time sequence progress. In one embodiment, when the server detects that the value of the task progress is smaller than the value of the time-of-sequence progress, the server may determine that the service progress information does not meet the preset service progress condition.

Specifically, the embodiment provides a manner of determining a business progress based on a time-of-sequence progress. The server may calculate the time-sequential progress information of the service at the current point in time. The time schedule information may be specifically expressed as: sequence time progress information= (current time-operation target start time)/(operation target end time-operation target start time); the operation target starting time represents the starting time of the current preset statistical period, and the operation target ending time represents the ending time of the current preset statistical period. The server may also calculate current task progress information, specifically expressed as: task progress = index value/target value. Wherein the index value represents a value of the traffic data and the target value represents a value of the traffic data target value. If the server detects that the task progress information is smaller than the sequence time progress information, the server determines that the service does not meet the service progress condition.

Specifically, as shown in fig. 12, fig. 12 is a schematic diagram of a business progress determining step in an embodiment. Each executive mechanism can formulate a period of assessment target according to the business data target of the annual upper-level genre and the self business rhythm. For example, taking february and march as preset time periods, the server determines a total target value of service data corresponding to the preset time periods and splits the total target value into assessment targets of a plurality of time periods, and when the server detects that the progress of the service data in the february and march time periods is smaller than the time-ordered progress of the whole time periods of february and march at the current time point, the server can determine that service early warning is required, and timely inform a management decision layer corresponding to an executing mechanism to remind the executing mechanism to follow up service execution conditions. In addition, besides the time schedule, the server can also perform early warning judgment by setting modes such as the same-ratio negative increase and the completion rate ranking for the time period.

Through the embodiment, the server can determine whether service early warning is needed or not by detecting the time schedule and the task schedule, so that the accuracy of the service early warning is improved.

In one embodiment, determining the business progress information of the business according to the preset statistical period, the business data and the business data target value comprises: obtaining the same-ratio business data corresponding to the same-ratio preset statistical period and corresponding to the preset statistical period; and determining the service progress information of the service according to the ratio of the service data to the same-ratio service data.

In this embodiment, the server may also determine whether the service progress condition is satisfied by calculating a homonymy growth condition. For example, the server may obtain the same-ratio service data corresponding to the same-ratio preset statistical period corresponding to the preset statistical period. Wherein, the same comparison preset statistical period represents the preset statistical period of the same time and time span of the last year. The same-ratio service data represents service data of the same period of time in the last year. The server can determine the business progress information of the business according to the ratio of the business data to the same-ratio business data. Specifically, the method can be expressed as: homonymy = current date index value/last year index value 100%. In one embodiment, if the server detects that the ratio of the service data to the same-ratio service data is less than one, the server may determine that the service progress information does not meet a preset service progress condition, and service early warning is required.

Through the embodiment, the server can determine whether service early warning is needed or not by calculating the same-ratio parameters, so that the accuracy of the service early warning is improved.

In one embodiment, after determining the business progress information of the business, the method further comprises: acquiring business progress information of each peer of executing mechanism corresponding to the executing mechanism; and sequencing the business progress information and the business progress information of each peer, and if the ranking of the business progress information is detected to be in the preset ranking range, determining that the business progress information does not meet the preset business progress condition.

In this embodiment, the executing mechanisms may be stored in a preset mechanism relationship table, and the mechanism relationship table may include the subordinate relationships among the plurality of executing mechanisms. The server may determine the execution mechanisms that do not satisfy the business progress condition based on the business data ranking of each execution mechanism. For example, the server may obtain each peer service progress information of each peer execution mechanism corresponding to the execution mechanism, and sort the service progress information and each peer service progress information. Wherein the same-level executing mechanism represents the executing mechanism which belongs to the same upper-level executing mechanism as the executing mechanism. If the server detects that the ranking of the business progress information is within the preset ranking range, the server determines that the business progress information does not meet the preset business progress condition.

Specifically, the server may select certain service data and obtain service progress information of the service data in each execution mechanism, and rank the service progress information of each execution mechanism in a reverse order, and if the ranking is greater than the configured lower threshold and less than the upper threshold, the server considers that the condition of achieving the ranking early warning of the rate is reached. For example, if the server sets the threshold lower bound to be 5 and the threshold upper bound to be 10, the calculation rule is that 5-10 of all lower-level mechanisms of the same upper-level mechanism are not satisfied with the preset business progress condition. And a push target field is also arranged in the mechanism information and the early warning rule and used for pushing targets of the business early warning information, and the push target field comprises a mechanism management layer, an upper mechanism management layer, a provincial operator and the like. The mechanism management layer is expressed and pushed to staff of all management layers of the current mechanism; the upper-level organization management layer represents staff of an upper-level organization manager for finding the current organization according to the organization architecture tree; the provincial level operator represents the data billboard operator of the provincial level organization to which the current organization belongs. The server can generate an early warning message for each user and write the early warning message into the database, so that the server pushes business early warning information based on preset early warning information pushing rules.

According to the embodiment, the server can determine the execution mechanism needing service early warning by calculating the completion rate ranking of the execution mechanism, so that the accuracy of the service early warning is improved.

In one embodiment, as shown in fig. 13, fig. 13 is a timing diagram of a traffic early warning method in one embodiment. In this embodiment, the steps of inputting the service data target value, calculating the service data, executing the early warning, and the like are performed. When entering the business data target value, the user can upload the formulated staged business data target value to the server in a form of a table according to the operation rhythm of the current executing mechanism, and the server analyzes the table into the operation target of each mechanism row by row and stores the operation target in the database.

When the service data is calculated, the server can start the calculation task at regular time, wherein the service resource data index calculation task is started once per hour, and the team index calculation task is started once per day. The server acquires target data in all statistical periods from a unified ODS data warehouse, and synchronizes the target data into a database of the system uniformly, and then performs an index calculation task. When the service resource data calculation task runs for the first time on the day, the server firstly generates a data record with service time of the day for each mechanism in each time dimension, and then updates the data record of the day according to the latest service resource data every hour, so that the timeliness of the data is ensured. The team index calculation task operation logic is the same as the first operation logic of the business resource data on the same day. The server may also calculate the target completion, for example, the server may traverse the business data target values that are validated at the current point in time for each of the actuators, correlate the business data target values with two index tables according to the institution codes, the time dimension, and calculate the completion rate of the target. And finally storing the whole result into a database.

When the early warning is executed, the server can start early warning detection and early warning pushing tasks at regular time, the early warning detection tasks can find all mechanisms triggering early warning and business data of the mechanisms, and then early warning information is sent to the IM system through the early warning pushing tasks, so that notification to a user is achieved. After the user receives the notification, the detailed operation condition can be checked through the visual analysis system.

Through the embodiment, the server can count the service data of the service according to the preset counting period, determine the service progress information of the service based on the period, the service data and the corresponding service data target value, and send corresponding service early warning information to the corresponding execution mechanism of the service when the service progress information does not meet the service progress condition, so that the accuracy of service early warning is improved. In addition, the technical scheme aims at the industry attribute and the unique operation rhythm of the financial insurance business re-marketing, and by constructing the assessment early warning function in the visual analysis system of the financial insurance business data, the opening and fusion of business data, operation targets and assessment rules are effectively realized, so that a management decision layer of an executing mechanism can flexibly customize the performance operation targets and the assessment early warning rules according to the unique operation rhythm of the mechanism, and the completion condition of relevant important indexes of business assessment can be timely and intuitively known. The data visual analysis system is provided with the capability of actively finding business management problems, the boosting management efficiency is improved, and a data-driven management system is realized.

It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a service early warning device for realizing the service early warning method. The implementation scheme of the solution to the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitation in the embodiments of one or more service early warning devices provided below may refer to the limitation of the service early warning method hereinabove, and will not be repeated here.

In one embodiment, as shown in fig. 14, there is provided a service early warning apparatus, including: the system comprises a detection module 500, an acquisition module 502, a determination module 504 and an early warning module 506, wherein:

the detection module 500 is configured to determine a service to be counted and a corresponding unit counting period thereof when the service progress statistics condition is detected to be satisfied.

The obtaining module 502 is configured to obtain service data in a preset statistic period according to at least one unit service data of the service in at least one unit statistic period.

The determining module 504 is configured to obtain a service data target value preset by the service in a preset statistics period, and determine service progress information of the service according to the preset statistics period, the service data, and the service data target value.

And the early warning module 506 is configured to generate service early warning information according to the service progress information and the target service progress information if the service progress information does not meet the preset service progress condition, acquire an execution mechanism corresponding to the service, and send the service early warning information to the execution mechanism.

In one embodiment, the apparatus further comprises: the segmentation module is used for acquiring a total target value of the business data in a preset time period, which is preset by an execution mechanism of the business; the total target value of the service data is determined based on the historical service data of the executing mechanism; and determining at least one preset statistical period according to the preset time period, and storing service data target values corresponding to the preset statistical periods according to the total target value of the service data.

In one embodiment, the detection module 500 is configured to determine a data type of the service; and determining a unit statistical period corresponding to the service according to the data type.

In one embodiment, the detecting module 500 is configured to determine that the unit statistics period is a first unit statistics period if the data type is service resource data; if the data type is business personnel data, determining the unit statistical period as a second unit statistical period; wherein the first unit statistical period is smaller than the second unit statistical period.

In one embodiment, the determining module 504 is configured to determine a period start time and a period end time according to a preset statistical period, and obtain a recording time corresponding to the service data; obtaining sequence time progress information corresponding to the service according to the recording time, the cycle starting time and the cycle ending time; obtaining task progress information corresponding to the service according to the service data and the service data target value; and obtaining the business progress information of the business according to the time sequence progress information and the task progress information.

In one embodiment, the apparatus further comprises: and the first judging module is used for determining that the business progress information does not meet the preset business progress condition if the numerical value of the task progress is detected to be smaller than the numerical value of the time sequence progress.

In one embodiment, the determining module 504 is configured to obtain the same-ratio service data corresponding to the same-ratio preset statistical period corresponding to the preset statistical period; and determining the service progress information of the service according to the ratio of the service data to the same-ratio service data.

In one embodiment, the apparatus further comprises: and the second judging module is used for determining that the service progress information does not meet the preset service progress condition if the ratio of the service data to the same-ratio service data is smaller than one.

In one embodiment, the apparatus further comprises: the third judging module is used for acquiring the business progress information of each peer of executing mechanism corresponding to the executing mechanism; and sequencing the business progress information and the business progress information of each peer, and if the ranking of the business progress information is detected to be in the preset ranking range, determining that the business progress information does not meet the preset business progress condition.

All or part of the modules in the service early warning device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 15. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing business data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a business pre-warning method.

It will be appreciated by those skilled in the art that the structure shown in fig. 15 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application is applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, where the memory stores a computer program, and the processor implements the service early warning method described above when executing the computer program.

In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the business pre-warning method described above.

In one embodiment, a computer program product is provided, comprising a computer program that when executed by a processor implements the business pre-warning method described above.

It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A business pre-warning method, characterized in that the method comprises:

2. The method according to claim 1, wherein the method further comprises:

3. The method of claim 1, wherein the determining the traffic to be counted and the corresponding unit counting period thereof comprises:

determining the data type of the service;

4. A method according to claim 3, wherein the data type comprises at least one of business resource data and business personnel data; the determining the unit statistical period corresponding to the service according to the data type comprises the following steps:

5. The method of claim 1, wherein the determining the business progress information of the business according to the preset statistical period, the business data and the business data target value comprises:

obtaining business progress information of the business according to the time sequence progress information and the task progress information;

6. The method of claim 1, wherein the determining the business progress information of the business according to the preset statistical period, the business data and the business data target value comprises:

determining service progress information of the service according to the ratio of the service data to the same-ratio service data;

7. The method of any one of claims 1 to 6, wherein the actuators are stored in a preset mechanism relationship table, the mechanism relationship table comprising dependencies between a plurality of actuators;

8. A business pre-warning device, characterized in that the device comprises:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.