CN115953032A - Enterprise project execution risk assessment system based on data analysis - Google Patents
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Abstract
The invention relates to the field of risk analysis, and discloses an enterprise project execution risk assessment system based on data analysis, which is used for solving the problems that when an existing enterprise accepts a customized project, accepted project risks are judged by personnel experience, and accepted project risks cannot be scientifically and accurately analyzed and assessed by combining the operation condition of the enterprise, and comprises a processor, and a data acquisition module, a data analysis module, an early warning prompt module and a data storage module which are in communication connection with the processor; the invention determines the risk degree of the enterprise executing the customized project according to the matching degree of the customized project and all aspects of the enterprise, and then judges whether the customized project can be carried according to the risk degree, thereby solving the defect that the risk of the customized project can be judged only according to the personal experience in the past.
Description
Technical Field
The invention relates to the technical field of risk analysis, in particular to an enterprise project execution risk assessment system based on data analysis.
Background
With the rapid development of economy, the business of the client customized project is rapidly developed, the scale is gradually enlarged, the client customized project has the unique characteristics of strong innovation, multiple uncertain factors and the like besides the characteristics of a common project, and the risk of the client customized project in the implementation process is increased by the characteristics;
when the existing enterprises carry on customized projects of customers, the carried-on project risks are often judged by the experience of personnel, and the carried-on project risks cannot be scientifically and accurately analyzed and evaluated by combining the operation conditions of the enterprises;
in order to solve the above problems, a technical solution is now provided.
Disclosure of Invention
In order to overcome the above defects in the prior art, embodiments of the present invention provide an enterprise project execution risk assessment system based on data analysis, which determines a risk level of an enterprise executing a customized project according to a matching degree of the customized project and various aspects of the enterprise, and further determines whether the customized project can be accepted according to the risk level, thereby solving a problem that a customized project risk can only be determined according to human experience in the past, so as to solve the problem proposed in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
an enterprise project execution risk assessment system based on data analysis comprises a processor, and a data acquisition module, a data analysis module, an early warning prompt module and a data storage module which are in communication connection with the processor;
a processor for processing data from at least one module of an enterprise project execution risk assessment system;
the data acquisition module is used for acquiring project execution demand information customized by a client and state information of an enterprise, sending the acquired information to the data analysis module through the processor for data analysis, and sending the acquired information to the data storage module through the processor for data storage;
the data analysis module is used for carrying out risk assessment on the project customized by the customer after receiving the information sent by the data acquisition module, sending the generated rejection signal and the signal with higher risk to the early warning prompt module, and sending the project information with lower risk to the data storage module for storage;
the early warning prompting module is used for carrying out corresponding risk prompting after receiving the signals with larger risk and the rejection signals sent by the data analysis module and calling the items with smaller risk stored in the data storage module for sequential recommendation;
and the data storage module is used for storing the information acquired by the data acquisition module and the project risk assessment information analyzed by the data analysis module and sequencing the project risk assessment information in sequence according to the risk.
In a preferred embodiment, after receiving the information sent by the data acquisition module, the data analysis module calibrates the idle information of the enterprise for a construction period to Qg, the required information of the project for a construction period to Xg, the required information of the project work station to Xw, and the idle work station information of the enterprise to Qw, and if the required information of the project work station Xw is greater than the idle work station information Qw of the enterprise, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompt module through the processor, and the early warning prompt module performs early warning prompt; if the project station demand information Xw is less than or equal to the idle station information Qw of the enterprise, calculating a capacity evaluation coefficient Ca of the customized project of the client according to a formula, wherein the specific calculation formula is as follows:
In a preferred embodiment, the data analysis module further marks the project fund demand information and the enterprise fund information as Xm and Qm, respectively, obtains a fund evaluation coefficient Em according to a formula Qm/Xm, and if the fund evaluation coefficient Em is smaller than 1, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompting module through the processor, and the early warning prompting module performs early warning prompting.
In a preferred embodiment, when the capital evaluation coefficient Em and the capacity evaluation coefficient Ca are both greater than or equal to 1, the data analysis module calibrates the enterprise allocation promotion information to Qi, and calculates the risk evaluation coefficient R of the enterprise receiving the customized project according to the capacity evaluation coefficient Ca, the capital evaluation coefficient Em and the enterprise allocation promotion information Qi, and the specific calculation expression is as follows:
In a preferred embodiment, the data analysis module compares the risk evaluation coefficient R with a standard risk threshold, and if the risk evaluation coefficient R is greater than or equal to the standard risk threshold, the data analysis module generates a greater risk signal and sends the greater risk signal to the early warning module, and the early warning module performs early warning; and if the risk evaluation coefficient R is smaller than the standard risk threshold value, the data analysis module sends the item with lower risk to the data storage module through the processor for data storage.
In a preferred embodiment, the data analysis module sets the standard number of days as D0, and the total number of days of the project as D, and then the number of days evaluation coefficient is D = D0/D, and if the number of days evaluation coefficient D is less than 1, the standard risk threshold is corrected and then compared with the risk evaluation coefficient R, and the standard risk threshold is set as R0, and the corrected standard risk threshold is R0, and the calculation expression of R0 is as follows:
The enterprise project execution risk assessment system based on data analysis has the technical effects and advantages that:
the risk degree of the enterprise executing the customized project of the client is determined according to the matching degree of the customized project of the client and the enterprise, and whether the customized project of the client can be carried is judged according to the risk degree, so that the defect that the risk of the customized project can be judged only according to the personal experience in the past is overcome;
the invention also correspondingly adjusts the standard risk threshold according to the whole project planning time so as to improve the requirements on the project productivity, capital and the like, and consider the risk improvement problem caused by overlong days intervals.
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FIG. 1 is a schematic diagram of a system for performing risk assessment of an enterprise project based on data analysis according to the present invention.
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example 1
The enterprise project execution risk assessment system based on data analysis determines the risk degree of an enterprise executing a client customized project according to the matching degree of the client customized project and all aspects of the enterprise, and further judges whether the client customized project can be accepted or not according to the risk degree, so that the defect that the risk of the customized project can be judged only according to human experience in the past is overcome.
FIG. 1 is a schematic diagram of a system for risk assessment of enterprise project execution; the system comprises a processor, a data acquisition module, a data analysis module, an early warning prompt module and a data storage module, wherein the data acquisition module, the data analysis module, the early warning prompt module and the data storage module are in communication connection with the processor.
The processor may be configured to process data and/or information from at least one component of the enterprise project execution risk assessment system or an external data source (e.g., a cloud data center). In some embodiments, the processor may be local or remote. For example, the processor may access information and/or data from a data storage device, a terminal device, and/or a data collection device via a network. As another example, a processor may be directly connected to a data storage device, a terminal device, and/or a data collection device to access information and/or data. In some embodiments, the processor may be implemented on a cloud platform. For example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof.
The data acquisition module is used for acquiring project execution demand information customized by a client and state information of an enterprise, transmitting the acquired information to the data analysis module through the processor for data analysis, and transmitting the acquired information to the data storage module through the processor for data storage.
The project execution demand information comprises project construction period demand information, project station demand information and project fund demand information, the project construction period demand information refers to a completion period specified by the customized project of the client, the shorter the completion period is, the higher the risk of the project is, the project station demand information refers to the work position data required by the customized project of the client, the more stations are required, the higher the capacity required by the project is, and the higher the risk is; the project capital requirement information refers to the amount of capital cost required by the customer in the early stage of the customized project, and the higher the capital cost is, the higher the risk of the project is.
The state information of the enterprise comprises idle station information of the enterprise, capital information of the enterprise, idle information of a construction period of the enterprise and allocation increase and movement information of the enterprise, the idle station information of the enterprise refers to the number of idle stations of the enterprise in a certain time period, the capital information of the enterprise refers to the residual amount of capital of the enterprise, the idle information of the construction period of the enterprise refers to the number of idle days of the enterprise in the future, and the allocation increase and movement information of the enterprise refers to manual information of the stations which can be temporarily increased by the enterprise in a short time.
After receiving the information sent by the data acquisition module, the data analysis module compares project construction period required information with enterprise construction period idle information, compares project station required information with enterprise idle station information, and comprehensively judges whether the enterprise can meet the construction period requirement of the client customized project. If the project station demand information Xw is less than or equal to the idle station information Qw of the enterprise, comparing and judging the project construction period demand information and the enterprise construction period idle information, and calculating the capacity evaluation coefficient Ca of the customized project of the client according to a formula, wherein the specific calculation formula is as follows:
It should be noted that, as the capacity estimation coefficient Ca approaches 1, the less the spare capacity of the enterprise, the greater the risk of the customized project.
The data analysis module is also used for comparing project fund demand information with enterprise fund information, respectively marking the project fund demand information and the enterprise fund information as Xm and Qm, acquiring a fund evaluation coefficient Em according to a formula Qm/Xm, and if the fund evaluation coefficient Em is less than 1, indicating that enterprise fund cannot meet the customer customized project fund demand, and at the moment, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompt module through the processor, and the early warning prompt module carries out early warning prompt; if the capital evaluation coefficient Em is larger than or equal to 1, the capital requirement of the customized project of the customer can be met by the enterprise capital, and when the capital evaluation coefficient Em is larger, the capital of the enterprise is richer, and the risk of the corresponding enterprise taking over the customized project of the customer is smaller.
The data analysis module also marks the enterprise allocation increasing transfer information as Qi, calculates a risk evaluation coefficient R of the enterprise for receiving the customized project according to the capacity evaluation coefficient Ca, the fund evaluation coefficient Em and the enterprise allocation increasing transfer information Qi, and specifically calculates the following expression when the capacity evaluation coefficient Ca and the fund evaluation coefficient Em are both more than or equal to 1:
The data analysis module compares the risk evaluation coefficient R with a standard risk threshold, if the risk evaluation coefficient R is larger than or equal to the standard risk threshold, the risk of the enterprise executing the customized project of the client is higher, at the moment, the data analysis module generates a higher risk signal and sends the signal to the early warning prompt module, and the early warning prompt module carries out early warning prompt; if the risk evaluation coefficient R is smaller than the standard risk threshold, the risk of the enterprise executing the customized project of the client is smaller, and at the moment, the data analysis module sends the project with the smaller risk to the data storage module through the processor for data storage.
It should be noted that, in the present application, the customized projects of the client are all consistent with the enterprise, and there is no situation that the customized projects of the client are inconsistent with the enterprise type, so that the risk level of the enterprise executing the customized projects of the client can be determined according to the matching degree of the customized projects of the client and all aspects of the enterprise, and then whether the customized projects of the client can be accepted or not is determined according to the risk level, thereby solving the defect that the risk of the customized projects can only be determined according to human experience in the past.
The early warning prompt module carries out corresponding risk prompt after receiving the large risk signal and the rejection signal sent by the data analysis module, wherein the rejection signal can be used for carrying out early warning prompt by a red light signal, and the large risk signal is used for carrying out early warning prompt by a yellow light signal. Meanwhile, the early warning prompt module also calls the items with smaller risks stored in the data storage module to recommend in sequence, so that related staff in the later period can screen conveniently.
In an optional example, the early warning prompting module may be connected with a display screen for early warning display and recommendation.
The data storage module is used for storing the information acquired by the data acquisition module and the project risk assessment information analyzed by the data analysis module, and sequencing the project risk assessment information in sequence according to the risk size, so that the later-stage early warning prompt module can call the information in sequence to recommend and display the project.
Example 2
The difference between the embodiment 2 of the present invention and the above embodiments is that the risk degree of taking over the project is mainly determined by the matching degree of the customized project and various aspects of the enterprise in the above embodiments, wherein the standard risk threshold is set differently, which may cause a change in the evaluation result, while the setting of the standard risk threshold is often changed along with a change in the planning time, specifically, when the risk evaluation coefficients R are the same, the risk degree of the project with an excessively long planning time of the whole project is greater, and therefore, the standard risk threshold should be reduced.
Specifically, the data analysis module sets standard days as D0, the total days of the project as D, the day evaluation coefficient is D = D0/D, if the day evaluation coefficient D is greater than or equal to 1, it is indicated that the total days of the project do not exceed the standard days, at this time, the standard risk threshold is set according to a general standard, if the day evaluation coefficient D is less than 1, it is indicated that the total days of the project are too long, a certain risk influence is generated, at this time, the standard risk threshold needs to be correspondingly reduced, so as to improve requirements on the productivity, the fund and the like of the project. Specifically, if the standard risk threshold is R0 and the corrected standard risk threshold is R0, then:
The total number of days of the project refers to the time interval from the current time to the end of the project, the number of days is not equal to the number of days of project duration, the number of days is also related to the start time of the project, for example, if the project is started after five days, the project duration is five days, and the total number of days d of the project is ten days.
Therefore, when the risk evaluation is carried out on the customized project of the customer, the risk evaluation coefficient R of the project is determined, the whole days of the project are compared with the standard days to determine whether the standard risk threshold needs to be corrected or not, finally, the risk evaluation coefficient R is compared with the determined standard risk threshold, and whether the customized project of the customer can be accepted or not is judged according to the risk degree.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters and the threshold value in the formula are selected and set by the technical personnel in the field according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. The procedures or functions according to the embodiments of the present application are wholly or partially generated when the computer instructions or the computer program are loaded or executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the module units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
And finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (6)
1. An enterprise project execution risk assessment system based on data analysis, characterized by: the system comprises a processor, and a data acquisition module, a data analysis module, an early warning prompt module and a data storage module which are in communication connection with the processor;
a processor for processing data from at least one module of an enterprise project execution risk assessment system;
the data acquisition module is used for acquiring project execution demand information customized by a client and state information of an enterprise, transmitting the acquired information to the data analysis module through the processor for data analysis, and transmitting the acquired information to the data storage module through the processor for data storage;
the data analysis module is used for carrying out risk assessment on the project customized by the customer after receiving the information sent by the data acquisition module, sending the generated rejection signal and the signal with higher risk to the early warning prompt module, and sending the project information with lower risk to the data storage module for storage;
the early warning prompting module is used for carrying out corresponding risk prompting after receiving the signals with larger risk and the rejection signals sent by the data analysis module and calling the items with smaller risk stored in the data storage module for sequential recommendation;
and the data storage module is used for storing the information acquired by the data acquisition module and the project risk assessment information analyzed by the data analysis module and sequencing the project risk assessment information in sequence according to the risk.
2. The data analysis-based enterprise project execution risk assessment system of claim 1, wherein: after the data analysis module receives the information sent by the data acquisition module, the idle information of the enterprise in the construction period is marked as Qg, the required information of the project in the construction period is marked as Xg, the required information of the project station is marked as Xw, the idle station information of the enterprise is marked as Qw, if the required information of the project station Xw is greater than the idle station information Qw of the enterprise, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompt module through the processor, and the early warning prompt module carries out early warning prompt; if the project station demand information Xw is less than or equal to the idle station information Qw of the enterprise, calculating a capacity evaluation coefficient Ca of the customized project of the client according to a formula, wherein the specific calculation formula is as follows:
if the productivity evaluation coefficient Ca is smaller than 1, the client customized project cannot be completed, at the moment, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompt module through the processor, and the early warning prompt module carries out early warning prompt.
3. The data analysis-based enterprise project execution risk assessment system of claim 2, wherein: the data analysis module further marks project capital demand information and enterprise capital information as Xm and Qm respectively, acquires a capital evaluation coefficient Em according to a formula Qm/Xm, and if the capital evaluation coefficient Em is smaller than 1, the data analysis module generates a rejection signal and sends the rejection signal to the early warning prompt module through the processor, and the early warning prompt module carries out early warning prompt.
4. The system of claim 3, wherein the system is configured to perform risk assessment of an enterprise project based on data analysis, and further configured to: when the capital evaluation coefficient Em and the productivity evaluation coefficient Ca are both more than or equal to 1, the data analysis module marks the enterprise allocation transfer information as Qi, and calculates a risk evaluation coefficient R of the enterprise for accepting the customized project of the client according to the productivity evaluation coefficient Ca, the capital evaluation coefficient Em and the enterprise allocation transfer information Qi, and the specific calculation expression is as follows:
in the formula (I), the compound is shown in the specification,
、/>
、/>
and respectively assigning deployment information, capacity evaluation coefficients and fund evaluation coefficients to the enterprises.
5. The system of claim 4, wherein the system is configured to perform risk assessment of an enterprise project based on data analysis, and further configured to: the data analysis module compares the risk evaluation coefficient R with a standard risk threshold, if the risk evaluation coefficient R is greater than or equal to the standard risk threshold, the data analysis module generates a greater risk signal and sends the greater risk signal to the early warning prompt module, and the early warning prompt module carries out early warning prompt; and if the risk evaluation coefficient R is smaller than the standard risk threshold value, the data analysis module sends the item with lower risk to the data storage module through the processor for data storage.
6. The system of claim 5, wherein the system is configured to perform risk assessment of an enterprise project based on data analysis, and further configured to: the data analysis module sets standard days as D0, the whole days of the project as D, the evaluation coefficient of days is D = D0/D, if the evaluation coefficient of days D is less than 1, the standard risk threshold is corrected and then compared with the risk evaluation coefficient R, the standard risk threshold is set as R0, the corrected standard risk threshold is R0, and the calculation expression of R0 is as follows:
wherein d0< d, b is a preset correction coefficient.
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| CN114022273A (en) * | 2021-11-26 | 2022-02-08 | 江苏华博实业集团有限公司 | Financial risk management system and method for financing supply chain |
| CN114757590A (en) * | 2022-06-14 | 2022-07-15 | 江苏金恒信息科技股份有限公司 | Enterprise operation risk early warning and management and control system based on big data analysis |
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