CN110599041A - Enterprise target management method, cloud and system based on artificial intelligence technology - Google Patents
Enterprise target management method, cloud and system based on artificial intelligence technology Download PDFInfo
- Publication number
- CN110599041A CN110599041A CN201910872765.7A CN201910872765A CN110599041A CN 110599041 A CN110599041 A CN 110599041A CN 201910872765 A CN201910872765 A CN 201910872765A CN 110599041 A CN110599041 A CN 110599041A
- Authority
- CN
- China
- Prior art keywords
- data
- cloud
- user
- artificial intelligence
- analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an enterprise target management method, a cloud and a system based on an artificial intelligence technology, wherein the method comprises the following steps: receiving current user data uploaded by a client; evaluating the current user data by adopting a trained artificial intelligence typhoon algorithm model to obtain AI analysis results, wherein the AI analysis results comprise task risk state early warning, personnel KPI analysis reports and working capacity figures, and superior and inferior analysis and existing problems of each node on a company value chain; and receiving a user query request uploaded by the client, and pushing the AI analysis result to the client according to the query request for a user to check. The embodiment of the invention integrates the advantages of KPI + OKR + KSF, makes up the defects, adopts a self-developed deep learning Typhoon algorithm library, and combines artificial intelligence, cloud computing, big data analysis and mobile internet technology to provide intelligent suggestions for enterprise decision-making and help enterprise strategic targets land correctly and efficiently.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an enterprise target management method, a cloud and a system based on artificial intelligence technology.
Background
The traditional way of achieving enterprise target management landing generally adopts KPI, OKR and KSF, which is as follows:
the Key Performance Indicator (KPI) is a target type quantitative management indicator for measuring the process performance by setting, sampling, calculating and analyzing key parameters of the input end and the output end of the internal process of an organization, is a tool for decomposing the strategic target of an enterprise into operable working targets, and is the basis of enterprise performance management. KPI can make the department in charge of defining the main responsibility of the department, and based on this, define the performance measurement index of the personnel in the department. Establishing a clear and feasible KPI system is the key to good performance management. The key performance indicators are quantitative indicators for measuring the performance of the work of the workers, and are important components of the performance plan.
OKR (objectives and Key results), a set of management tools and methods for specifying and tracking objects and their completion, invented by Intel corporation. OKR are the main goals of specifying the "goals" of companies and teams and specifying the measurable "key outcomes" achieved by each goal. OKR may be shared throughout the organization so that teams may target specifically throughout the organization to help coordinate and concentrate energy.
KSF, key success factors (key success factors), is one of the information system development planning methods, proposed in 1970 by William Zani, professor Harvard university. Key Success Factors (KSF), which are commonly used concepts when discussing the relationship between industrial characteristics and enterprise strategies, are important requirements in the environment in combination with their own special capabilities to achieve good performance.
The defects of the three management modes are as follows:
KPI: focusing on the achievement of target indexes, the method has the advantages that the quantitative strategy deployment and the strategic resource management are simpler, and the defects that employees of the company easily deviate from the real targets of the company in the actual implementation process.
OKR: focusing on the achievement of the target process, the method has the advantages of easier tracking of target landing and implementation of strategic management, and the defect of dilution of the overall sense of corporate targets and strategies by project business.
KSF: focusing on the achievement of the target success factor, the advantage is that the underlying employee potential can be stimulated and talent management implemented, while the disadvantage is that the strategic driving force of the company is weakened.
Disclosure of Invention
The embodiment of the invention aims to provide an enterprise target management method, a cloud and a system based on an artificial intelligence technology, so as to integrate the advantages of KPI + OKR + KSF and make up the defects, and an intelligent suggestion is provided for enterprise decision by adopting a self-developed deep learning Typhoon algorithm library and combining artificial intelligence, cloud computing, big data analysis and a mobile internet technology, so that an enterprise strategic target can be accurately and efficiently landed.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides an enterprise target management method based on an artificial intelligence technology, including:
receiving current user data uploaded by a client;
evaluating the current user data by adopting a trained artificial intelligence typhoon algorithm model to obtain an AI analysis result, wherein the AI analysis result comprises risk state early warning of tasks, KPI analysis reports and working capacity portraits of personnel, and superior and inferior analysis and existing problems of each node on a company value chain;
and receiving a user query request uploaded by the client, and pushing the AI analysis result to the client according to the query request for a user to check.
As a specific implementation manner of the present application, the user data includes employee data, company data, task data, target data, and policy data, and the current user data is evaluated by using a trained artificial intelligence typhoon algorithm model to obtain an AI analysis result, which specifically includes:
adopting the artificial intelligent typhoon algorithm model to perform AI analysis on the employee data and the company data to obtain preliminary information, wherein the preliminary information comprises company industry, types and development stages;
obtaining a recommendation strategy according to the target data, the strategy data and the preliminary information;
distributing a value chain module according to the recommendation strategy so that a user executes task creation and task assignment operations under the value chain module;
receiving a task execution result uploaded by the client;
and analyzing based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
In a second aspect, an embodiment of the present invention further provides another enterprise target management method based on an artificial intelligence technology, including:
the method comprises the steps that a client receives current user data input by a user and uploads the current user data to a cloud;
the cloud end adopts a trained artificial intelligence typhoon algorithm model to evaluate the current user data so as to obtain an AI analysis result, wherein the AI analysis result comprises task risk state early warning, personnel KPI analysis report and working capability portrait, and superior and inferior analysis and existing problems of each node on a company value chain;
the client receives a query request input by a user and uploads the query request to the cloud;
and the cloud end pushes the AI analysis result to the client end according to the query request so as to be checked by a user.
As a specific embodiment of the present application, the method specifically includes:
the client receives and uploads employee data and company data input by a user to the cloud;
the cloud end adopts the artificial intelligent typhoon algorithm model to perform AI analysis on the employee data and the company data to obtain preliminary information, wherein the preliminary information comprises company industry, types and development stages;
the client receives and uploads target data and strategy data input by a user to the cloud;
the cloud end obtains a recommendation strategy according to the target data, the strategy data and the preliminary information;
the cloud end distributes a value chain module according to the recommendation strategy so that a user can execute task creation and task assignment operations under the value chain module;
the client receives updating operation of a user to obtain a task execution result, and uploads the task execution result to the cloud;
and the cloud end analyzes based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
Further, before the client receives the current user data input by the user, the method further includes:
and the client receives the classification operation of the user and divides the role of the staff into a target maker, a task creator and a task executor according to the classification operation.
In a third aspect, an embodiment of the present invention further provides a cloud, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, where the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method in the first aspect.
In a fourth aspect, an embodiment of the present invention further provides an enterprise target management system based on an artificial intelligence technology, including a cloud and a client that communicate with each other. Wherein the cloud is described in the third aspect.
Further, the client is used for receiving classification operation of the user and dividing the role of the staff into three types of target formulators, task creators and task executors according to the classification operation.
By implementing the embodiment of the invention, the advantages of KPI + OKR + KSF are fused, the defects of the KPI + OKR + KSF are overcome, a self-developed deep learning Typhoon algorithm library is adopted, artificial intelligence, cloud computing, big data analysis and mobile internet technology are combined, an intelligent suggestion is provided for enterprise decision making, and the strategic target of an enterprise can be effectively helped to land on the ground accurately and efficiently.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below.
FIG. 1 is a schematic diagram of an enterprise target management method based on artificial intelligence technology according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of an enterprise target management method based on artificial intelligence technology according to a first embodiment of the present invention;
FIG. 3 is a sub-flowchart of step S102 in FIG. 2;
FIG. 4 is a schematic flow chart diagram of an enterprise target management method based on artificial intelligence technology according to a second embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an enterprise target management system based on artificial intelligence technology according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of the cloud of FIG. 5;
FIG. 7 is a goal management interface diagram.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that, the embodiment of the present invention is intended to solve the foregoing problems, and to combine the advantages of KPI + OKR + KSF and make up for the disadvantages, which is an AI + new methodology. AI enabling to determine a logic path, and enabling the target to not lose shape through a graph; enabling AI to identify priority, and optimizing a whole-person struggling process; AI enables the creation of operation value, and the whole person is a heart and everyone is a manager.
Based on this, the solution provided by the embodiment of the invention is as follows: as shown in fig. 1, the collection of target, policy and task user behavior data is completed by managing target execution tool target rows, and the user behavior data is accumulated; and importing the user behavior data into the trained artificial intelligence typhoon algorithm model to finish the evaluation of the target execution process and the result.
Further, the technical features of the above solution are as follows:
1. an artificial intelligence algorithm is used: self-developed deep learning Typhoon algorithm library
2. Technology combining cloud computing, big data analysis and mobile internet
3. Fusing management knowledge and methodology of "goal → strategy → task
4. Adopts a hybrid cloud architecture and a Saas service mode
Further, the implementation method comprises the following steps:
the solidified relationship of manager/managed is eliminated among employees, and each employee is a manager. And the stylized strategic target implementation process makes the target fall on the ground by targeting, strategy determination and task allocation. The process strategy goal is followed until the task is completed. The value of each person is reflected in the process. And the quality, efficiency and effect of the task executed by the staff are obtained through an AI analysis method, and visual data are provided for a decision layer. The method comprises the following specific steps:
1. the roles of the employees are classified into 3 categories, which are:
the target maker: responsible for creating corporate targets, creating policies
The task creator: is responsible for distributing tasks
The task performer: is responsible for realizing the task and is responsible for the task creator
2. And importing employee data and company data according to roles, and performing desensitization treatment on part of the data in the database. The employee data includes at least one target maker.
3. According to the imported data, AI analysis obtains preliminary information, such as company industry, type, development stage, and the like.
4. The target maker creates a target, sets a specific quantization index and sets a weight.
5. A monthly target is set. Decomposing into month targets according to the created year targets.
6. The target maker creates a strategy and sets weight. Multiple strategies can be created under each target, and the AI automatically recommends part of the strategies for reference according to the information of the company and the type of the target.
7. A value chain module is assigned. Each strategy can be distributed with a plurality of modules, and the AI recommends part of the modules for reference according to the type of the strategy.
8. Tasks are created and assigned. And adding specific tasks under the value module, and setting weight. Tasks can be assigned to anyone.
9. And the staff updates the task progress. The staff update the tasks which are executed by the staff on the task bulletin board every day.
10. And checking the report. After each task is updated, a corresponding report is generated, so that the result of each task is clear to all people.
11. And (5) AI analysis report. The AI reports daily, reporting the effects of landing on the content company goals, the value of employees, systemic risks, etc.
Based on the foregoing description of the implementation method and the like of the embodiment of the present invention, please refer to fig. 2, which is a schematic flow chart of the enterprise target management method based on the artificial intelligence technology according to the first embodiment of the present invention. In this embodiment, the description is mainly performed by using the cloud as an execution subject. As shown, the method may include:
s101, receiving current user data uploaded by a client.
Specifically, in the foregoing implementation method, steps 1, 2, 4, 5, 6, and 8 may all be understood as user input data received by the client, and the client uploads the data to the cloud.
And S102, evaluating the current user data by adopting the trained artificial intelligence typhoon algorithm model to obtain an AI analysis result.
As can be seen from fig. 1, in the embodiment of the present invention, known data (e.g., user behavior data such as objects, policies, and tasks) may be used for training, so as to establish an artificial intelligence Typhoon algorithm-based library (which may also be understood as an artificial intelligence Typhoon algorithm model). When the cloud receives the current user data from the client, the current user data can be analyzed and evaluated by adopting an artificial intelligence typhoon algorithm model so as to obtain an AI analysis result. The AI analysis result comprises the risk state early warning of tasks, KPI analysis reports and working capability figures of personnel, and the advantages and disadvantages analysis of each node on a company value chain and existing problems.
S103, receiving a user query request uploaded by the client, and pushing the AI analysis result to the client according to the query request for a user to check.
Specifically, when a client needs to query an AI analysis result, a query request can be initiated to the cloud end through the client, and the cloud end pushes the AI analysis result to the client end according to the query request so as to be viewed by the user.
Further, as shown in fig. 3, step S102 specifically includes:
and S1021, performing AI analysis on the employee data and the company data by adopting the artificial intelligent typhoon algorithm model to obtain preliminary information.
Wherein the preliminary information includes company industry, type, and stage of development.
And S1022, obtaining a recommendation strategy according to the target data, the strategy data and the preliminary information.
S1023, a value chain module is distributed according to the recommendation strategy, so that a user can execute task creation and task assignment operation under the value chain module.
And S1024, receiving a task execution result uploaded by the client.
And S1025, analyzing based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
The enterprise target management method based on artificial intelligence of the embodiment of the invention integrates the advantages of KPI + OKR + KSF, makes up the defects, adopts a self-developed deep learning Typhoon algorithm library, combines artificial intelligence, cloud computing, big data analysis and mobile internet technology, provides intellectualized suggestions for enterprise decision making, and can effectively help enterprise strategic targets fall on the ground accurately and efficiently.
Fig. 4 is a schematic flowchart of an enterprise target management method based on artificial intelligence technology according to a second embodiment of the present invention. In this embodiment, the client and the cloud are mainly used as the execution subject for description. As shown, the method may include:
s201, the client receives classification operation of the user, and according to the classification operation, the role of the staff is divided into three categories, namely a target maker, a task creator and a task executor.
S202, the client receives current user data input by a user and uploads the current user data to a cloud.
And S203, the cloud end adopts the trained artificial intelligence typhoon algorithm model to evaluate the current user data so as to obtain an AI analysis result.
The AI analysis result comprises the risk state early warning of tasks, KPI analysis reports and working capability figures of personnel, and the advantages and disadvantages analysis of each node on a company value chain and existing problems.
And S204, the client receives a query request input by a user and uploads the query request to the cloud.
S205, the cloud end pushes the AI analysis result to the client end according to the query request so as to be checked by a user.
Further, the method specifically comprises the following steps:
the client receives and uploads employee data and company data input by a user to the cloud;
the cloud end carries out AI analysis on the employee data and the company data by adopting the artificial intelligent typhoon algorithm model to obtain preliminary information, wherein the preliminary information comprises company industry, types and development stages;
the client receives and uploads target data and strategy data input by a user to the cloud;
the cloud end obtains a recommendation strategy according to the target data, the strategy data and the preliminary information;
the cloud end distributes a value chain module according to the recommendation strategy so that a user can execute task creation and task assignment operation under the value chain module;
the client receives the updating operation of a user to obtain a task execution result, and uploads the task execution result to the cloud;
and the cloud end analyzes based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
It should be noted that, in the embodiment, please refer to the embodiment described in fig. 2 and fig. 3 for a specific process of related steps in this embodiment, which is not described herein again.
Based on the same inventive concept, the embodiment of the invention also provides an enterprise target management system based on the artificial intelligence technology. As shown in fig. 5, the system includes a client 100 and a cloud 200 in communication with each other, wherein the cloud 200 corresponds to the method embodiments described in fig. 2 and fig. 3.
Specifically, as shown in fig. 6, the cloud may include: one or more processors 101, one or more input devices 102, one or more output devices 103, and memory 104, the processors 101, input devices 102, output devices 103, and memory 104 being interconnected via a bus 105. The memory 104 is used for storing a computer program comprising program instructions, the processor 101 being configured for invoking the program instructions for performing the methods of the above-described method embodiment parts.
It should be understood that, in the embodiment of the present invention, the Processor 101 may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 102 may include a keyboard or the like, and the output device 103 may include a display (LCD or the like), a speaker, or the like.
The memory 104 may include read-only memory and random access memory, and provides instructions and data to the processor 101. A portion of the memory 104 may also include non-volatile random access memory. For example, the memory 104 may also store device type information.
In a specific implementation, the processor 101, the input device 102, and the output device 103 described in the embodiment of the present invention may execute the implementation manner described in the embodiment of the method for detecting an attack traffic of an industrial network provided in the embodiment of the present invention, which is not described herein again.
Further, the client 100 is configured to receive a classification operation of a user, and classify the role of the employee into three categories, namely, a target maker, a task creator, and a task performer according to the classification operation.
The enterprise target management system based on the artificial intelligence technology provided by the embodiment of the invention integrates the advantages of KPI + OKR + KSF, makes up the defects, adopts a self-developed deep learning Typhoon algorithm library, combines artificial intelligence, cloud computing, big data analysis and mobile internet technology, provides an intelligent suggestion for enterprise decision making, and can effectively help enterprise strategic targets fall on the ground correctly and efficiently.
Further, when an enterprise formulates an annual target, the SAAS system provides an accurate target strategy scheme for the enterprise according to basic data such as the industry where the enterprise is located and business models through an AI algorithm, helps the enterprise determine a strategic path, and correctly decomposes the target (a target management interface is shown in fig. 7). In the actual landing process of the strategy, the enterprise is helped to continue to be decomposed downwards around a chain for creating value, and a target landing management mode which is adopted by the traditional enterprise and is centered on an organization structure is avoided. In the whole system, all people are managers and all people can be called.
Further, through big data generated in the process of falling to the ground of a company target, the AI can provide relevant process early warning, analysis reports, optimization suggestions and the like for managers, and can provide the following steps: the risk state early warning of tasks, KPI analysis reports and working capability figures of personnel, the advantage and disadvantage analysis of each node on a company value chain, existing problems and the like.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. An enterprise target management method based on artificial intelligence technology is characterized by comprising the following steps:
receiving current user data uploaded by a client;
evaluating the current user data by adopting a trained artificial intelligence typhoon algorithm model to obtain an AI analysis result, wherein the AI analysis result comprises risk state early warning of tasks, KPI analysis reports and working capacity portraits of personnel, and superior and inferior analysis and existing problems of each node on a company value chain;
and receiving a user query request uploaded by the client, and pushing the AI analysis result to the client according to the query request for a user to check.
2. The artificial intelligence technology-based enterprise target management method of claim 1, wherein the user data comprises employee data, company data, task data, target data and strategy data, and the current user data is evaluated using a trained artificial intelligence typhoon algorithm model to obtain an AI analysis result, specifically comprising:
adopting the artificial intelligent typhoon algorithm model to perform AI analysis on the employee data and the company data to obtain preliminary information, wherein the preliminary information comprises company industry, types and development stages;
obtaining a recommendation strategy according to the target data, the strategy data and the preliminary information;
distributing a value chain module according to the recommendation strategy so that a user executes task creation and task assignment operations under the value chain module;
receiving a task execution result uploaded by the client;
and analyzing based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
3. An enterprise target management method based on artificial intelligence technology is characterized by comprising the following steps:
the method comprises the steps that a client receives current user data input by a user and uploads the current user data to a cloud;
the cloud end adopts a trained artificial intelligence typhoon algorithm model to evaluate the current user data so as to obtain an AI analysis result, wherein the AI analysis result comprises task risk state early warning, personnel KPI analysis report and working capability portrait, and superior and inferior analysis and existing problems of each node on a company value chain;
the client receives a query request input by a user and uploads the query request to the cloud;
and the cloud end pushes the AI analysis result to the client end according to the query request so as to be checked by a user.
4. The artificial intelligence technology-based enterprise target management method according to claim 3, wherein the method specifically comprises:
the client receives and uploads employee data and company data input by a user to the cloud;
the cloud end adopts the artificial intelligent typhoon algorithm model to perform AI analysis on the employee data and the company data to obtain preliminary information, wherein the preliminary information comprises company industry, types and development stages;
the client receives and uploads target data and strategy data input by a user to the cloud;
the cloud end obtains a recommendation strategy according to the target data, the strategy data and the preliminary information;
the cloud end distributes a value chain module according to the recommendation strategy so that a user can execute task creation and task assignment operations under the value chain module;
the client receives updating operation of a user to obtain a task execution result, and uploads the task execution result to the cloud;
and the cloud end analyzes based on the preliminary information, the target data, the strategy data, the recommendation strategy and the task execution result to obtain the AI analysis result.
5. An artificial intelligence technology based enterprise target management method according to claim 3 or 4, wherein before the client receives the current user data input by the user, the method further comprises:
and the client receives the classification operation of the user and divides the role of the staff into a target maker, a task creator and a task executor according to the classification operation.
6. Cloud comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is configured to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of claim 1 or 2.
7. An artificial intelligence technology-based enterprise target management system, comprising a cloud and a client which are in communication with each other, wherein the cloud is as claimed in claim 6.
8. The artificial intelligence technology-based enterprise target management system of claim 7, wherein the client is configured to receive a user's classification operation and classify employee roles into three categories, target formulator, task creator, and task performer, based on the classification operation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910872765.7A CN110599041A (en) | 2019-09-16 | 2019-09-16 | Enterprise target management method, cloud and system based on artificial intelligence technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910872765.7A CN110599041A (en) | 2019-09-16 | 2019-09-16 | Enterprise target management method, cloud and system based on artificial intelligence technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110599041A true CN110599041A (en) | 2019-12-20 |
Family
ID=68859905
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910872765.7A Pending CN110599041A (en) | 2019-09-16 | 2019-09-16 | Enterprise target management method, cloud and system based on artificial intelligence technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110599041A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112966973A (en) * | 2021-03-30 | 2021-06-15 | 建信金融科技有限责任公司 | System and method for managing targets and key results |
| CN113269513A (en) * | 2021-05-12 | 2021-08-17 | 北京创仕科锐信息技术有限公司 | Target management method and system |
| WO2024031191A1 (en) * | 2022-08-10 | 2024-02-15 | Mavryck Inc. | Systems and methods for project and program management using artificial intelligence |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105989442A (en) * | 2015-02-12 | 2016-10-05 | 伈思策管系统股份有限公司 | Computer software of enterprise value creation platform |
| CN106886885A (en) * | 2017-02-16 | 2017-06-23 | 运城学院 | A kind of Enterprise Comprehensive Management System |
| CN109658478A (en) * | 2017-10-10 | 2019-04-19 | 爱信诺征信有限公司 | It is a kind of that the method and system of enterprise's portrait are provided |
| CN109726905A (en) * | 2018-12-20 | 2019-05-07 | 北交金科金融信息服务有限公司 | A kind of method and system of enterprise value portrait evaluation |
| CN109947821A (en) * | 2019-03-14 | 2019-06-28 | 腾讯科技（深圳）有限公司 | Generation method, display methods, device, equipment and the storage medium of report information |
| CN110033191A (en) * | 2019-04-16 | 2019-07-19 | 北京殷塞信息技术有限公司 | A kind of analysis method and system of business artificial intelligence |
| CN110084493A (en) * | 2019-04-11 | 2019-08-02 | 企家有道网络技术(北京)有限公司 | Enterprise diagnosis, prediction technique and device, server based on artificial intelligence |
| CN110110960A (en) * | 2019-03-25 | 2019-08-09 | 深圳民太安智能科技有限公司 | A kind of commercial vehicle intelligence air control platform |
-
2019
- 2019-09-16 CN CN201910872765.7A patent/CN110599041A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105989442A (en) * | 2015-02-12 | 2016-10-05 | 伈思策管系统股份有限公司 | Computer software of enterprise value creation platform |
| CN106886885A (en) * | 2017-02-16 | 2017-06-23 | 运城学院 | A kind of Enterprise Comprehensive Management System |
| CN109658478A (en) * | 2017-10-10 | 2019-04-19 | 爱信诺征信有限公司 | It is a kind of that the method and system of enterprise's portrait are provided |
| CN109726905A (en) * | 2018-12-20 | 2019-05-07 | 北交金科金融信息服务有限公司 | A kind of method and system of enterprise value portrait evaluation |
| CN109947821A (en) * | 2019-03-14 | 2019-06-28 | 腾讯科技（深圳）有限公司 | Generation method, display methods, device, equipment and the storage medium of report information |
| CN110110960A (en) * | 2019-03-25 | 2019-08-09 | 深圳民太安智能科技有限公司 | A kind of commercial vehicle intelligence air control platform |
| CN110084493A (en) * | 2019-04-11 | 2019-08-02 | 企家有道网络技术(北京)有限公司 | Enterprise diagnosis, prediction technique and device, server based on artificial intelligence |
| CN110033191A (en) * | 2019-04-16 | 2019-07-19 | 北京殷塞信息技术有限公司 | A kind of analysis method and system of business artificial intelligence |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112966973A (en) * | 2021-03-30 | 2021-06-15 | 建信金融科技有限责任公司 | System and method for managing targets and key results |
| CN113269513A (en) * | 2021-05-12 | 2021-08-17 | 北京创仕科锐信息技术有限公司 | Target management method and system |
| WO2024031191A1 (en) * | 2022-08-10 | 2024-02-15 | Mavryck Inc. | Systems and methods for project and program management using artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Nguyen et al. | Synergistic effect of integrated project delivery, lean construction, and building information modeling on project performance measures: a quantitative and qualitative analysis | |
| US8782784B1 (en) | Framework for implementing security incident and event management in an enterprise | |
| Zahradníčková et al. | Scenarios as a strong support for strategic planning | |
| CN110599041A (en) | Enterprise target management method, cloud and system based on artificial intelligence technology | |
| Ellinas et al. | Toward project complexity evaluation: A structural perspective | |
| US8271319B2 (en) | Structured implementation of business adaptability changes | |
| Hu et al. | Research and application of capability maturity model for Chinese intelligent manufacturing | |
| Gohar et al. | Identifying and evaluating risks of construction projects in fuzzy environment: a case study in Iranian construction industry | |
| Zorrilla et al. | A reference framework for the implementation of data governance systems for industry 4.0 | |
| Yap et al. | Criticality of project knowledge and experience in the delivery of construction projects | |
| CN115545516A (en) | Performance data processing method, device and system based on process engine | |
| CN115471200A (en) | Cloud computing-based human resource data management system, method and device | |
| Al-Roumi et al. | Exploring the rate of adoption and implementation depth of building information modeling (BIM): A case of Kuwait | |
| Praynlin et al. | Performance analysis of software effort estimation models using neural networks | |
| Filip | Designing and building modern information systems; A series of decisions to be made | |
| CN117350640A (en) | Project progress management method and system | |
| CN116630082A (en) | Method and device for allocating production resources, electronic equipment and storage medium | |
| CN116777140A (en) | Enterprise business management method, device, equipment and medium | |
| Gorbunova et al. | State enterprises' financial stability coefficients | |
| Tundo et al. | An energy-aware approach to design self-adaptive ai-based applications on the edge | |
| Igwe et al. | Towards a framework of automated resource model for post contract cost control of construction projects | |
| CN113706101B (en) | Intelligent system architecture and method for power grid project management | |
| CN115204501A (en) | Enterprise evaluation method and device, computer equipment and storage medium | |
| CN113962664A (en) | Method, device, equipment and medium for human resource evaluation | |
| CN112712270B (en) | Information processing method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |