CN112085412B - Resource optimization distribution system and distribution method - Google Patents
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Abstract
The application discloses a resource optimization distribution system, which comprises a background server for data storage, operation and output, wherein the background server is also in communication connection with a plurality of PC ends and mobile ends which are mutually communicated, and the background server comprises: the system comprises a database module, a data item, a storage module and a data calling and dispatching module, and a calculation comparison module. The application also provides a distribution method based on the distribution system, which is used for realizing automatic distribution of the resource data, collecting, comparing and analyzing the task situation after execution, revising the existing data in a feedback way, realizing cyclic optimization processing of the resource data, and solving the problems of low data processing efficiency, low reliability, incapability of serving human resource data management and the like in the prior art.
Description
Technical Field
The application relates to the field of digital information data processing systems, in particular to the field of digital systems for human resource management, and specifically relates to a resource optimal allocation system and an allocation method.
Background
The resource management mainly includes human resource management, infrastructure management, work environment management, financial resource management, supplier and partner management, knowledge information and technical resource management, and the like, and is mainly applied to a method for improving the overall efficiency in organization management. The management of resources is an intangible resource capable of converting potential productivity into actual productivity, and in human production activities, four resources are actually existing in the management of substances, manpower, financial resources and the like. The management resource has intangible and potential characteristics, and becomes a resource because the economic organization can reasonably and fully utilize the existing people, property and things through strengthening management under the condition of not increasing the first three tangible resources, thereby increasing the yield, the production value and the profit and obtaining better economic benefit.
It is a dynamic resource that works only when combined with labor and material resources to form a production business. This is because, after the combination of the material resources and the human resources, how much money can be provided for society, not only the combination of workers and production data on the material form, but also whether the productivity can be reasonably organized, the productivity level can be improved, and the relationship between people in production can be correctly processed.
In the existing human resource management process, a plurality of methods and auxiliary tools are often adopted, and because human resources have the characteristics of dynamic properties, difficult quantization and standardization, a plurality of data are required to be collected for reference, so that a manager can obtain corresponding index data to adjust a management mode conveniently. However, in the prior art, a platform system based on big data technology exists, but the platform system is only a primary data statistics tool, simple result feedback is performed, and effective analysis and self-sustaining management cannot be performed.
For enterprises focusing on flow management, the key points of timely circulation and feedback type information for determining working efficiency and management efficiency are how to utilize the existing mobile digital resource allocation and management, which is a problem to be solved by the current data circulation intensive enterprises.
Disclosure of Invention
In order to solve the problems that the existing enterprises taking data circulation feedback as main work and management content are not digitized enough in the aspects of data information processing, circulation, feedback and optimization, and the datamation optimization of resources cannot be realized, so that the distribution and circulation of the resource data are unreasonable and not efficient. The application provides a resource optimization distribution system for realizing classified storage of data, which realizes data optimization and distribution of all resources by a brand-new resource optimization distribution method, improves the utilization rate of the resource data and ensures timeliness and high efficiency of resource data acquisition, distribution and execution. Meanwhile, the application also provides a step of secondary checking and verifying of the resource data, and the authenticity and the credibility of the resource data are ensured. The acquired trusted data is compared with industry data or target data preset by the system, so that the working saturation of each link of the whole process is mastered, a priority data list is automatically generated, and the resource scientific optimization is fed back and serviced, so that the maximum value utilization of the effective resource is achieved.
In order to achieve the above purpose, the technical scheme adopted by the application is as follows:
a resource-optimized distribution system comprising a background server for data storage, computation and output, the background server further being communicatively connected with a plurality of PC-terminals and mobile-terminals in communication with each other, the background server comprising:
the database module comprises a plurality of data units, wherein the data units are preset by a system and comprise standard task data and planning task data capable of being changed in a self-defined mode; the standard task data is preset by the system, and can be directly read, identified and distributed according to a system preset mechanism. The planning task data refer to data content which can be set, modified and deleted by human definition according to actual conditions, and the standard task data and the planning task data are controlled by a dispatching instruction once being recorded and stored in a database module.
The data item consists of a plurality of preset and unchangeable execution items, and any one of the execution items has an associated mapping relation with at least one piece of standard task data and/or planning task data; an execution item is the smallest constituent unit that constitutes a unit of data including standard task data or planning task data. Any one data unit is associated with at least one execution item in the data items, and one execution item at least corresponds to one data unit to form the standard task data or the planning task data.
The storage module consists of an input unit and an execution data unit; the input unit is used for storing one or more pieces of discrete data input through any PC end; the discrete data is the starting point for triggering the data flow to realize the allocation of the system to the resource data. Any two pieces of discrete data are not mutually associated, and any piece of discrete data is independently input and triggers brand new data dispatch, circulation, execution and feedback. The execution data unit is used for storing at least one or more pieces of execution data, and the execution data is formed by standard task data or planning task data after being executed by any mobile terminal login account; that is, all execution items contained in the data unit are initial null values, and the execution data is correspondingly formed after the execution is completed. The discrete data, the plurality of execution items associated with the data units and the execution data have a one-to-one correspondence relationship, but one discrete data can respectively correspond to the plurality of data units and the execution data, and any one data unit has and only one execution data corresponds to the same.
The data calling and dispatching module comprises a data domain unit and a time sequence unit, wherein the data domain unit and the time sequence unit are used for limiting any login and retrieval task through a mobile terminal, and the data calling and dispatching module is used for calling and dispatching any data information in the database module, the data item and the storage module according to preset logic of a system by combining the matching degree of the data domain unit and the time sequence unit. The data domain unit refers to an attribute relationship preset in a background server and used for discriminating the data unit and the account number of the login mobile terminal, only the data unit with the same attribute can be received by the corresponding account number, and the user cannot dispatch the data unit. The time sequence unit refers to: the account relation mapping table is preset in the background server and used for judging the account relation mapping table corresponding to the data unit aiming at any attribute at any moment.
And the calculation comparison module is used for calculating any data information called in the data calling and dispatching module according to logic preset by the system and appointing and outputting the data information. The data information mentioned here refers to all data information related to the present system in a broad sense, and does not refer to specific data stored in a specific module in a narrow sense.
Preferably, the execution item in the data item forms a mapping relation with one or more data units in the database module through the tag data. The data unit is a data set composed of a plurality of execution items, the data unit is distinguished among the data units through tag data, the tag data is an identification code for reflecting the unique identity of the data unit, the representation mode can be realized through decimal coding of not lower than four digits, of course, as a person skilled in the art should understand that if the data to be identified is larger than four digits, the bit increment identification can be performed, the identification efficiency is not reduced, and therefore, the specific tag data setting can be realized in a self-defining way. If the secret information possibly exists in the related data unit, the label data can be produced in the existing encryption mode for encrypting and identifying the identity of the data unit so as to improve the confidentiality.
Further preferably, any one of said execution items contains at least one tag data identifiable by one or more of said data units. The mapping relations between the data units and the execution items are one-to-many, namely, the same execution item can establish the mapping relation with a plurality of data units; similarly, one data unit may correspond to a plurality of execution items; however, since the execution item is the smallest data unit that constitutes the data unit, one execution item may contain a plurality of tags belonging to a data communication mapping relationship with a plurality of data units at the same time; however, any one data unit has and can only have one tag data to realize that a mapping relation is established with one or more execution items with the same tag data.
The application also provides a resource optimal allocation method, which is realized based on the resource optimal allocation system and specifically comprises the following steps:
step ST01, logging in task data by a PC end, logging in a distribution system by the PC end, reading and/or logging in the task data after authority verification, and storing the task data in a logging unit to form corresponding discrete data with data types;
step ST02, the data calling and dispatching module matches the corresponding data units in the database module by reading the data types of any one of the discrete data;
step ST03, the data unit matches at least one execution item with a mapping relation according to the tag data to form a data unit of a task to be dispatched;
step ST04, the calculation comparison module respectively compares the data unit of the task to be dispatched in step ST03 with the data domain unit and the time sequence unit to determine a unique executable account or a plurality of accounts which can be sequentially executed, and feeds back the result to the data calling and dispatching module to make dispatching;
in step ST05, the account logs in the mobile terminal, and obtains the task distributed in step ST04 and the data unit information corresponding to the task, performs offline execution and completion, and evaluates the task completion according to the system preset standard by the mobile terminal to obtain the self-evaluation result data a, thereby generating the execution data and the execution task list.
Meanwhile, in order to further improve the authenticity and the credibility of the data, the method further comprises the steps of ST06, logging in the mobile terminal by the three-party account, obtaining the task list data generated in the step ST05, and checking the task list data one by one to obtain checking result data B; comparing the self-evaluation result data A with the check result data B through a calculation comparison module and outputting the following results:
if A is more than B, taking the check result data B as an output result;
if A < B, the self-evaluation result data A is taken as an output result.
In order to further master the whole flow data and acquire the actual management efficiency and efficiency effectiveness, the method further comprises a step ST07, wherein the output result of the step ST06 is compared with a corresponding industry average value, positive and negative values are output for representing the saturation, and a saturation list is formed.
In order to further improve the optimality of the resources so as to achieve the purpose of technical service for existing resource control and management, the method further comprises a step ST08 of comparing the output result of the step ST06 with a corresponding preset target value, outputting a preset target completion degree and an optimization list, and feeding back the optimization list to the database module.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a block diagram of a distribution system architecture of the present application;
FIG. 2 is a flow chart of the distribution method of the present application;
FIG. 3 is a schematic diagram of a data stream according to the present application;
FIG. 4 is a histogram of saturation and completion;
fig. 5 is a schematic diagram of a mapping relationship between tag data and execution items.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
In the description of the present application, it should be noted that, if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate an azimuth or a positional relationship based on that shown in the drawings, or an azimuth or a positional relationship in which a product of the application is conventionally put in use, it is merely for convenience of describing the present application and simplifying the description, and it is not indicated or implied that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like in the description of the present application, if any, are used for distinguishing between the descriptions and not necessarily for indicating or implying a relative importance.
Furthermore, the terms "horizontal," "vertical," and the like in the description of the present application, if any, do not denote a requirement that the component be absolutely horizontal or overhang, but rather may be slightly inclined. As "horizontal" merely means that its direction is more horizontal than "vertical", and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present application, it should also be noted that, unless explicitly stated and limited otherwise, the terms "disposed," "mounted," "connected," and "connected" should be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1:
the embodiment takes the data management of all aspects of the hotel management process in the hotel management enterprise as an example to describe the resource optimization distribution system provided by the application in detail, is shown in the accompanying drawings 1-5 of the specification, and comprises a background server for data storage, operation and output, wherein the background server is also in communication connection with a plurality of PC ends and mobile ends which are mutually communicated, the PC ends and the mobile ends can log in and register in an account number of the distribution system, and the reading and distribution of system resources are realized through the authority corresponding to the account number, which is consistent with the authority distribution of the existing resource system, and belongs to the known technology of the conventional software industry.
The background server comprises:
the database module comprises a plurality of data units, wherein the data units are preset by a system and comprise standard task data and planning task data capable of being changed in a self-defined mode; the standard task data is preset by the system, and can be directly read, identified and distributed according to a system preset mechanism. The planning task data refer to data content which can be set, modified and deleted by human definition according to actual conditions, and the standard task data and the planning task data are controlled by a dispatching instruction once being recorded and stored in a database module.
The data item consists of a plurality of preset and unchangeable execution items, and any one of the execution items has an associated mapping relation with at least one piece of standard task data and/or planning task data; an execution item is the smallest constituent unit that constitutes a unit of data including standard task data or planning task data. Any one data unit is associated with at least one execution item in the data items, and one execution item at least corresponds to one data unit to form the standard task data or the planning task data.
The storage module consists of an input unit and an execution data unit; the input unit is used for storing one or more pieces of discrete data input through any PC end; the discrete data is the starting point for triggering the data flow to realize the allocation of the system to the resource data. Any two pieces of discrete data are not mutually associated, and any piece of discrete data is independently input and triggers brand new data dispatch, circulation, execution and feedback. The execution data unit is used for storing at least one or more pieces of execution data, and the execution data is formed by standard task data or planning task data after being executed by any mobile terminal login account; that is, all execution items contained in the data unit are initial null values, and the execution data is correspondingly formed after the execution is completed. The discrete data, the plurality of execution items associated with the data units and the execution data have a one-to-one correspondence relationship, but one discrete data can respectively correspond to the plurality of data units and the execution data, and any one data unit has and only one execution data corresponds to the same.
The data calling and dispatching module comprises a data domain unit and a time sequence unit, wherein the data domain unit and the time sequence unit are used for limiting any login and retrieval task through a mobile terminal, and the data calling and dispatching module is used for calling and dispatching any data information in the database module, the data item and the storage module according to preset logic of a system by combining the matching degree of the data domain unit and the time sequence unit. The data domain unit refers to an attribute relationship preset in a background server and used for discriminating the data unit and the account number of the login mobile terminal, only the data unit with the same attribute can be received by the corresponding account number, and the user cannot dispatch the data unit. The time sequence unit refers to: the account relation mapping table is preset in the background server and used for judging the account relation mapping table corresponding to the data unit aiming at any attribute at any moment.
And the calculation comparison module is used for calculating any data information called in the data calling and dispatching module according to logic preset by the system and appointing and outputting the data information. The data information mentioned here refers to all data information related to the present system in a broad sense, and does not refer to specific data stored in a specific module in a narrow sense.
And the execution items in the data items form a mapping relation with one or more data units in the database module through the tag data. The data unit is a data set composed of a plurality of execution items, the data unit is distinguished among the data units through tag data, the tag data is an identification code for reflecting the unique identity of the data unit, the representation mode can be realized through decimal coding of not lower than four digits, of course, as a person skilled in the art should understand that if the data to be identified is larger than four digits, the bit increment identification can be performed, the identification efficiency is not reduced, and therefore, the specific tag data setting can be realized in a self-defining way. If the secret information possibly exists in the related data unit, the label data can be produced in the existing encryption mode for encrypting and identifying the identity of the data unit so as to improve the confidentiality.
Any of the execution terms contains at least one tag data identifiable by one or more of the data units. The mapping relations between the data units and the execution items are one-to-many, namely, the same execution item can establish the mapping relation with a plurality of data units; similarly, one data unit may correspond to a plurality of execution items; however, since the execution item is the smallest data unit that constitutes the data unit, one execution item may contain a plurality of tags belonging to a data communication mapping relationship with a plurality of data units at the same time; however, any one data unit has and can only have one tag data to realize that a mapping relation is established with one or more execution items with the same tag data.
In this embodiment, the hotel check-in link in the operation management is used as an information trigger node, check-in information is recorded through the PC end login account, and is stored in the recording unit of the background server, and is sequentially recorded as discrete data 1, discrete data 2, and discrete data 3 … … discrete data n according to the recording order. When the background server receives discrete data n (n=1, 2, 3, 4, 5 … …) input from the foreground PC end, if the discrete data 1 is received, activating a data calling and dispatching module, wherein the data calling and dispatching module respectively matches the data field unit and the time sequence unit by acquiring the attribute of the discrete data 1, and the attribute of the discrete data 1 realizing triggering in the embodiment is the check-in information, an account number irrelevant to the check-in information can be eliminated by matching the discrete data with the data field unit, or an account number set M with the check-in information attribute is associated; further, matching the discrete data 1 input time with the time sequence unit, and obtaining an account number set N matched with the corresponding time sequence unit at the moment, and determining an account number or an account number set obtained by M N as a target account number or an account number set to be distributed by the data calling and distributing module.
And after any account number in the target account number or the target account number set logs in the mobile terminal, the distributed task can be checked and acquired, and the task content comprises standard task data or planning task data. And the target account login user takes the standard task or the planned task, then executes the standard task or the planned task according to the task time, the requirements and the detail content, and carries out online evaluation according to the actual execution content and the evaluation standard preset by the system, the system automatically inputs the evaluation content logged in by the target account and records the evaluation content as self-evaluation result data A, and execution data is formed and stored in an execution data unit/storage module.
The system also provides a three-party account, logs in the three-party account, and invokes the executed task list in the execution data unit through the data invoking and dispatching module to perform offline verification and input verification result data B.
The calculation comparison module outputs the following results by comparing the self-evaluation result data A with the check result data B:
when the self-evaluation result data A is higher than the check result data B, taking the check result data B as a final system adoption value;
when the self-evaluation result data A is lower than the check result data B, the regional self-evaluation result data A is the final adoption value of the system. This section takes hotel check-out node management as an example: when any PC terminal inputs the information of the room return, discrete data 2 is generated, a data calling and dispatching module is triggered to call a second data unit, and the second data unit is collected and passes through tag data, as shown by tag data 0155 or tag data 0013 shown in fig. 5, a mapping relation is established, so that execution items of the same tag data are all included in the same data unit mapping, and distributed to corresponding account numbers for execution. In the data dispatch process of the node, the data field unit is post information, such as cleaning post, the time sequence unit corresponds to a specific duty account corresponding to a duty schedule contained in the post information, and a second data unit containing a plurality of execution items is dispatched to the corresponding duty account; the plurality of execution items comprise room sanitary equipment replacement, bedding replacement, room electric appliance counting and the like, and the content covered by the specific execution items is specifically set according to practical application. Noteworthy are: since the actual content of the task may include subjective judgment content, any execution item needs to be objectified and dataized for the quantifiability of all flow nodes; and discarding the content depending on subjective discrimination, and evaluating in a range selection or judgment mode if the content is not easy to discard, so as to realize quantization of different working contents from other dimensions.
After quantitative comparison, the checking result data B of the three-party account is a neutral reference standard, so that the distortion of the finally imported execution data caused by subjective deviation of personnel corresponding to the post is avoided, and the credibility and objectivity of the data are improved. The current state can be kept continuously by comparing the final adopted value with the industry average value preset in the background server, obtaining the saturation condition shown in fig. 4, and deriving a saturation list to visually reflect the conditions of insufficient execution, disqualification or disqualification and the like of the management content and the management content exceeding the industry average level in the whole working flow all-node management at present. The final adopted value of the corresponding data is compared with the preset target value in the background server in a memorial mode, a list which reaches the preset target and does not reach the preset target can be intuitively obtained, and an optimization list for feeding back the follow-up workflow for improvement is formed for further optimizing standard task data and/or planning task data.
The foregoing is directed to a system for intelligent matching, serving, executing, and feedback of any content importable by a system provided by the present embodiments. The circulation efficiency of the information of each post can be greatly improved through the circulation of system data, and the actual efficiency of work is improved; meanwhile, the working data conditions and the completion conditions of the whole post and the whole process can be completely controlled, the real advantages and the short plates can be clearly known at a glance, the typical technical service management is realized, and the datamation service work is realized; objectifying subjective content, converting objective content into data, and intelligentizing data content. The resource optimization arrangement, distribution and statistics are realized, and the resource advantages are combined with the actual application to exert the maximum economic effect and the optimal cost investment.
As an alternative to the present embodiment, a layered cloud server may be employed instead of the existing backend server; the database module, the data item and the storage module are arranged on an execution layer at the top layer; the data calling and dispatching module and the calculation comparison module are arranged in a calculation layer and used for calling and processing data; and placing the output data sets such as the saturation list, the optimization list and the like which are calculated to be output after calculation in a feedback layer. Specifically, the data flow diagram shown in fig. 3 is shown.
Example 2:
the resource optimizing and distributing method shown in fig. 2-5 in combination with the description is realized based on the resource optimizing and distributing system provided in the embodiment 1, and specifically comprises the following steps:
step ST01, logging in task data by a PC end, logging in a distribution system by the PC end, reading and/or logging in the task data after authority verification, and storing the task data in a logging unit to form corresponding discrete data with data types;
step ST02, the data calling and dispatching module matches the corresponding data units in the database module by reading the data types of any one of the discrete data;
step ST03, the data unit matches at least one execution item with a mapping relation according to the tag data to form a data unit of a task to be dispatched;
step ST04, the calculation comparison module respectively compares the data unit of the task to be dispatched in step ST03 with the data domain unit and the time sequence unit to determine a unique executable account or a plurality of accounts which can be sequentially executed, and feeds back the result to the data calling and dispatching module to make dispatching;
in step ST05, the account logs in the mobile terminal, and obtains the task distributed in step ST04 and the data unit information corresponding to the task, performs offline execution and completion, and evaluates the task completion according to the system preset standard by the mobile terminal to obtain the self-evaluation result data a, thereby generating the execution data and the execution task list.
Meanwhile, in order to further improve the authenticity and the credibility of the data, the method further comprises the steps of ST06, logging in the mobile terminal by the three-party account, obtaining the task list data generated in the step ST05, and checking the task list data one by one to obtain checking result data B; comparing the self-evaluation result data A with the check result data B through a calculation comparison module and outputting the following results:
if A is more than B, taking the check result data B as an output result;
if A < B, the self-evaluation result data A is taken as an output result.
In order to further master the whole flow data and acquire the actual management efficiency and efficiency effectiveness, the method further comprises a step ST07, wherein the output result of the step ST06 is compared with a corresponding industry average value, positive and negative values are output for representing the saturation, and a saturation list is formed. As shown in FIG. 4, a bar graph represents an output result A/B of a plurality of execution items after evaluation after execution, a solid line in the middle represents an industry average line, part of the execution items are higher than the industry average line or lower than the industry average line, and the whole execution items are saturation curves, and after optimized distribution by the distribution method described in the embodiment, the saturation data can be directly derived through the system to guide or improve the existing defects.
In this embodiment, to further improve the optimality of resources so as to achieve the purpose of technical service for existing resource control and management, the method further includes step ST08 of comparing the output result of step ST06 with a corresponding preset target value, outputting a preset target completion degree and an optimization list, and feeding back the optimization list to the database module. The preset targets are shown as the highest and lowest target lines a and B horizontally arranged in fig. 4, and the optimal list and completion degree can be obtained as compared with each execution item. Noteworthy are: because the method is applicable to practically any situation, the fullness or the lack of data does not affect the realization of the method; for example, when the resources to which the method is applied are in a start-up phase, the actual target line may be significantly lower than the industry average line.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (6)
1. A resource-optimized distribution system comprising a background server for data storage, computation and export, characterized in that: the background server is also in communication connection with a plurality of PC ends and mobile ends which are communicated with each other, and comprises:
the database module comprises a plurality of data units, wherein the data units are preset by a system and comprise standard task data and planning task data capable of being changed in a self-defined mode;
the data item consists of a plurality of preset and unchangeable execution items, and any one of the execution items has an associated mapping relation with at least one piece of standard task data and/or planning task data;
the storage module consists of an input unit and an execution data unit; the input unit is used for storing one or more pieces of discrete data input through any PC end; the execution data unit is used for storing at least one or more pieces of execution data, and the execution data is formed by standard task data or planning task data after being executed by any mobile terminal login account;
the data calling and dispatching module comprises a data domain unit and a time sequence unit, wherein the data domain unit and the time sequence unit are used for limiting any login and acquisition task through a mobile terminal, and the data calling and dispatching module is used for calling and dispatching any data information in the database module, the data item and the storage module according to a system preset logic by combining the matching degree of the data domain unit and the time sequence unit;
and the calculation comparison module is used for calculating any data information called in the data calling and dispatching module according to logic preset by the system and appointing and outputting the data information.
2. A resource optimizing distribution system as claimed in claim 1, wherein: and the execution items in the data items form a mapping relation with one or more data units in the database module through the tag data.
3. A resource optimizing allocation system according to claim 2, wherein: any of the execution terms contains at least one tag data identifiable by one or more of the data units.
4. A resource optimization allocation method is characterized in that: a resource-optimized allocation system according to claim 3, comprising the steps of:
step ST01, logging in task data by a PC end, logging in a distribution system by the PC end, reading and/or logging in the task data after authority verification, and storing the task data in a logging unit to form corresponding discrete data with data types;
step ST02, the data calling and dispatching module matches the corresponding data units in the database module by reading the data types of any one of the discrete data;
step ST03, the data unit matches at least one execution item with a mapping relation according to the tag data to form a data unit of a task to be dispatched;
step ST04, the calculation comparison module respectively compares the data unit of the task to be dispatched in step ST03 with the data domain unit and the time sequence unit to determine a unique executable account or a plurality of accounts which can be sequentially executed, and feeds back the result to the data calling and dispatching module to make dispatching;
step ST05, logging in a mobile terminal by an account, acquiring the task distributed in step ST04 and obtaining data unit information corresponding to the task, performing off-line execution and completion, and evaluating the task completion condition according to a system preset standard by the mobile terminal to obtain self-evaluation result data A, and generating execution data and an execution task list; step ST06, obtaining the task list data generated in step ST05, checking the task list data one by one, obtaining checking result data B; comparing the self-evaluation result data A with the check result data B through a calculation comparison module and outputting the following results:
if A is more than B, taking the check result data B as an output result;
if A < B, the self-evaluation result data A is taken as an output result.
5. The resource optimization allocation method according to claim 4, wherein: the method also comprises a step ST07, wherein the output result of the step ST06 is compared with a corresponding industry average value, and positive and negative values are output for representing the saturation and forming a saturation list; the saturation list refers to: and the corresponding execution data obtained after any data unit is executed is compared with the industry field average data corresponding to the data to obtain more or less visual data with evaluation significance.
6. The resource optimization allocation method according to claim 5, wherein: and step ST08 is also included, the output result of step ST06 is compared with a corresponding preset target value, a preset target completion degree and an optimization list are output, and the optimization list is fed back to the database module.
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