Financial cost control and benefit evaluation intelligent device

Abstract

The invention relates to the technical field of cost control and benefit evaluation, in particular to a financial cost control and benefit evaluation intelligent device, which comprises a server and a control evaluation system, and is characterized in that the control evaluation system is electrically connected with the server; the control evaluation system comprises a data acquisition module, a database establishment module, a cost analysis module, an importance evaluation module, a monitoring and early warning module and an assistant processing module. Through the data acquisition module, the cost analysis module, the importance evaluation module, the monitoring and early warning module and the assistant processing module, the financial cost data is monitored in real time by using the monitoring and early warning module, when the financial cost data is abnormally changed, abnormal data is found in time and early warning is given to workers, so that the financial cost data is timely monitored. And then the worker is helped to process the abnormal data in time through the auxiliary processing module, so that the processing efficiency of the worker on the abnormal data is improved, and unnecessary loss and risk are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of cost control and benefit evaluation, and in particular to an intelligent device for financial cost control and benefit evaluation. Background Art

[0002] Cost control refers to controlling the various costs incurred by enterprises in the production and operation process through reasonable means and methods to achieve the purpose of reducing costs and improving benefits. Its core lies in the reasonable arrangement and utilization of resources, striving to obtain the maximum benefit at the minimum cost. Benefit evaluation refers to the evaluation and analysis of the investment and operating activities of the enterprise to determine its contribution to the enterprise's benefits. It helps enterprises understand and evaluate the risks and returns of various investments and operating activities, and provides a basis for decision-making.

[0003] Generally speaking, staff need to monitor financial cost data in real time and take timely measures to adjust it when abnormal financial cost data occurs. However, the existing intelligent devices are difficult to summarize and monitor in real time because financial cost data is usually scattered in different departments and systems. As a result, staff are unable to observe abnormal financial cost data in time, thereby delaying processing time and causing unnecessary losses and risks.

[0004] In summary, how to solve the problem that staff cannot observe financial cost data in time, thus causing unnecessary losses and risks, has become a technical problem that technicians in this field need to solve urgently. Therefore, it is necessary to propose an intelligent device for financial cost control and benefit evaluation. Summary of the invention

[0005] To solve the above problems, the present invention provides an intelligent device for financial cost control and benefit evaluation, which uses a data acquisition module, a cost analysis module, a importance evaluation module, a monitoring and early warning module and an assisting processing module to monitor the financial cost data in real time. When the financial cost data undergoes abnormal changes, the abnormal data is discovered in time and an early warning is issued to the staff. Subsequently, the assisting processing module is used to help the staff process the abnormal data in time, thereby improving the staff's efficiency in processing abnormal data and reducing unnecessary losses and risks.

[0006] In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: the intelligent device for financial cost control and benefit evaluation includes a server and a control evaluation system, and the control evaluation system is electrically connected to the server.

[0007] The control and evaluation system includes:

[0008] The data collection module is used to collect historical data related to finance and benefits. The historical data includes financial cost data, benefit data and historical cost control plans.

[0009] The database establishment module is used to pre-process the financial cost data, benefit data and historical cost control plan collected by the data collection module and establish a database.

[0010] The cost analysis module is used to analyze financial cost data from different dimensions. Financial cost data includes raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data.

[0011] The importance assessment module is used to arrange the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data from large to small according to their influence on the benefit data.

[0012] The monitoring and early warning module is used to monitor the changes in raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data in real time.

[0013] The monitoring and early warning module includes a time series model, which monitors abnormal values ​​in raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data and issues early warning signals.

[0014] The assisting processing module is used to generate 5 alternative plans for staff to choose from based on the abnormal values ​​in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data monitored in the monitoring and early warning module, combined with the historical cost control plan in the database establishment module.

[0015] The technical principles of the above scheme are as follows:

[0016] The financial cost data, benefit data and historical cost control schemes are collected through the data collection module; the data collected by the data collection module are preprocessed and a database is established through the database establishment module; the financial cost data are analyzed from multiple dimensions through the cost analysis module to understand the composition and change trend of the financial cost data; the importance assessment module is used to assess which data in the financial cost data has the greatest impact on the benefit data, helping staff to focus on these data with great impact; through the monitoring and early warning module, the time series model is used to monitor the changes in financial cost data in real time and monitor abnormal values. Once an abnormality is detected, an early warning will be issued to the staff immediately; based on the monitoring results of the monitoring and early warning module and the historical cost control schemes in the database, the cost control schemes are automatically screened through the assistance processing module for reference and selection by the staff.

[0017] The above scheme has the following beneficial effects:

[0018] 1. The present invention monitors the changes in financial cost data in real time through the monitoring and early warning module, and immediately issues an early warning when an abnormality is detected. The device can significantly reduce the time for staff to discover and handle cost anomalies, thereby reducing unnecessary losses and risks.

[0019] 2. The present invention can automatically screen cost control plans for staff to refer to and select through the assisting processing module, providing strong support for staff decision-making, thereby helping to improve decision-making efficiency and accuracy.

[0020] 3. The present invention analyzes financial cost data from multiple dimensions through a cost analysis module, which helps enterprises to have a more comprehensive understanding of the cost composition and changing trends, thereby formulating more effective cost control strategies.

[0021] 4. The present invention uses an importance assessment module to assess the importance of financial cost data, so that staff can give priority to cost factors that have the greatest impact on benefits, thereby optimizing resource allocation and improving resource utilization efficiency.

[0022] Further, the performance data includes product sales, profit margins, market share, return on investment, and customer satisfaction.

[0023] Beneficial effects: By integrating and analyzing product sales, profit margins and other efficiency data, smart devices can more accurately assess the profitability and market performance of enterprises, thereby providing more accurate decision-making support for cost control and efficiency improvement. Data such as market share and return on investment reflect the competitive position of enterprises in the market and the efficiency of capital utilization. Based on these data, smart devices can help enterprises optimize resource allocation, such as adjusting sales strategies, increasing R&D investment or optimizing production processes, to improve overall efficiency.

[0024] Furthermore, preprocessing includes data cleaning, data deduplication and data standardization of financial cost data, benefit data and historical cost control plans.

[0025] Beneficial effects: Data cleaning can effectively remove noise, missing values ​​and outliers in the data, ensure the accuracy and reliability of the data, and provide a solid foundation for subsequent analysis and decision-making. Data deduplication can avoid duplicate data in the data set, thereby improving the quality and accuracy of the data and ensuring the accuracy and reliability of subsequent analysis. Data standardization can ensure that data from different sources adopt a unified format and standard, making it easier to compare and integrate data between different systems, thereby improving data consistency.

[0026] Further, the different dimensions include time dimension, location dimension, product dimension and department dimension.

[0027] Beneficial effects: By analyzing the financial cost data at different time points, the trend of cost changes can be identified, which helps to predict future cost trends. For costs that are greatly affected by seasonal factors, seasonal adjustments can be made through time dimension analysis to make the financial cost data more stable and comparable. By analyzing the financial cost data of different locations, cost differences between regions can be identified, which helps to formulate targeted cost control strategies. According to the analysis results of the location dimension, the allocation of production, sales and other resources can be optimized to improve resource utilization efficiency. By analyzing the financial cost data of different products, high-cost or inefficient products can be identified, and then optimization measures can be taken to reduce product costs. Combining product costs and market demand, more reasonable product pricing strategies can be formulated to improve product competitiveness. By analyzing the financial cost data of different departments, real-time monitoring and early warning of department costs can be achieved, and cost control problems can be discovered and solved in a timely manner.

[0028] Furthermore, outlier monitoring rules are formulated in the time series model, and whether there are anomalies in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data is determined based on the outlier monitoring rules.

[0029] Beneficial effects: Time series models can capture trends and patterns in financial cost data over time. When outliers appear in financial cost data, it often means that there are potential problems or abnormal situations. Through outlier monitoring, staff can discover these problems in a timely manner and take appropriate measures to intervene and correct them, thereby preventing the problem from further deteriorating or causing greater losses. Outlier monitoring rules can not only help companies identify anomalies in data, but also provide information and context about outliers.

[0030] Furthermore, outlier monitoring rules are formulated based on error values, probability values, statistics, and thresholds.

[0031] Beneficial effects: Outliers will cause the error value in the time series model to increase. By comparing the difference between the model error value and the actual observed value, outliers that deviate from the normal range can be identified, which is beneficial to the analysis of financial cost data by the time series model. Probability values ​​are used to measure the possibility of an event. For outlier monitoring, the probability that a data point belongs to a normal distribution can be calculated. By comparing the relationship between data points and statistics, outliers can be identified. The threshold is a boundary used to determine whether a data point is an outlier. By setting a reasonable threshold, normal values ​​and outliers in the data set can be distinguished.

[0032] Furthermore, the control and evaluation system also includes a prediction module, which is used to simulate and regulate the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data respectively, and through the simulation and regulation, predict the direction of change of product sales, profit margin, market share, return on investment and customer satisfaction data.

[0033] Beneficial effects: The prediction module can simulate and regulate the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data respectively. Through the simulation and regulation of different data, the data change direction of product sales, profit margin, market share, return on investment and customer satisfaction can be predicted, which is conducive to improving the scientificity and accuracy of staff decision-making.

[0034] Furthermore, the assistance processing module is also used to put forward control suggestions for raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data based on the data change direction of product sales, profit margin, market share, return on investment and customer satisfaction predicted by the prediction module.

[0035] Beneficial effects: By precisely controlling various data, staff can allocate resources more effectively, thereby improving resource utilization efficiency. Decisions based on forecast results are more scientific, avoiding blind decisions and waste of resources, and helping the company achieve sustainable development.

[0036] Furthermore, the regulatory suggestions include regulating raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data in three directions: reducing, maintaining and increasing.

[0037] Beneficial effects: By simulating and predicting the control of raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data, enterprises can optimize production processes, improve production efficiency, and increase benefits while controlling costs.

[0038] Furthermore, the control and evaluation system also includes a display module, which includes a display screen. The display screen is fixedly connected to one side of the server and is electrically connected to the server. The display module is used to display the data results processed by the cost analysis module, the importance assessment module, the monitoring and early warning module, the auxiliary processing module and the prediction module on the display screen in the form of charts.

[0039] Beneficial effects: Displaying data in the form of charts makes complex data analysis results intuitive and easy to understand. Staff can quickly grasp the key information and trends of the data without having to deeply understand complex data models and algorithms. Intuitive data display helps staff make quick judgments, reduce hesitation and uncertainty in the decision-making process, and improve decision-making efficiency.

[0040] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is an axonometric diagram of the intelligent device for financial cost control and benefit evaluation of the present invention.

[0042] Figure 2 It is a structural block diagram of the control and evaluation system in the intelligent device for financial cost control and benefit evaluation of the present invention.

[0043] The reference numerals in the drawings of the specification include: 1. server; 2. display screen. DETAILED DESCRIPTION

[0044] The following is further described in detail through specific implementation methods:

[0045] Embodiment 1:

[0046] As attached Figure 1-Figure 2 As shown: the intelligent device for financial cost control and benefit evaluation includes a server 1 and a control evaluation system, and the control evaluation system is electrically connected to the server 1.

[0047] The control and evaluation system includes: data collection module, database establishment module, cost analysis module, importance evaluation module, monitoring and early warning module and assistance processing module.

[0048] The data acquisition module is mainly used to collect financial cost data and benefit data. The database establishment module is mainly used to clean, deduplicate and standardize the financial cost data and benefit data collected by the data acquisition module and the historical cost control plan, and then establish a database. The cost analysis module is used to obtain financial cost data from the database and perform cost analysis on the obtained financial cost data. The cost analysis module can analyze from multiple dimensions during the analysis. The importance assessment module is used to arrange the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data included in the financial cost data from large to small according to their influence on the benefit data. The monitoring and early warning module is used to monitor the financial cost data in real time and to promptly warn the staff when abnormal values ​​appear in the financial cost data. The assistance processing module is used to provide solutions to the staff for reference based on the historical cost control plan.

[0049] The following is a detailed explanation of the functions of each module:

[0050] The data collection module is used to collect historical data related to finance and benefits. The historical data includes financial cost data, benefit data and historical cost control plans. The benefit data includes product sales, profit margins, market shares, return on investment and customer satisfaction.

[0051] Specifically, the staff needs to collect financial cost data, benefit data and historical cost control plans through the data collection module. For example, in an enterprise, the staff can obtain financial cost data, benefit data and historical cost control plans through the enterprise's financial system and document management system, government statistics and industry reports. After the above data information is collected through the data collection module, it can provide a basis for financial cost control and benefit evaluation.

[0052] The database establishment module is used to pre-process the financial cost data, benefit data and historical cost control plan collected by the data collection module and establish a database. The pre-processing includes data cleaning, data deduplication and data standardization of the financial cost data, benefit data and historical cost control plan.

[0053] Specifically, the staff can use the database establishment module to clean, deduplicate and standardize the data collected by the data acquisition module, identify erroneous data by checking missing values ​​and invalid values ​​in the data collected by the data acquisition module, and eliminate duplicate data in the data, thereby reducing data redundancy, and finally unify data in different formats into a standard format set in advance by the staff, which is facilitating subsequent data analysis and application.

[0054] After data cleaning, data deduplication and data standardization are performed on the data collected in the data acquisition module, a database can be established.

[0055] The cost analysis module is used to analyze financial cost data from different dimensions, including raw material cost data, production cost data, marketing cost data and human resource cost data. The different dimensions include time dimension, location dimension, product dimension and department dimension.

[0056] Specifically, after the database is established, the cost analysis module can analyze the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data. The analysis can be performed through the time dimension, location dimension, product dimension and department dimension. The analysis shows that the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data will change under the influence of time, location, product and department, and the dimensions that have the greatest impact on the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data are determined. For example, the sales volume of an iced drink in summer is much greater than that in winter. At this time, the analysis of the time dimension has a greater impact on the production and manufacturing cost data. Analyzing the financial cost data through the cost analysis module will help enterprises better understand their own advantages, thereby improving the efficiency and accuracy of decision-making.

[0057] The importance assessment module is used to arrange the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data from large to small according to their influence on the benefit data.

[0058] Specifically, by evaluating raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data, the importance assessment module can evaluate the different impacts of raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data on benefit data, which is beneficial for staff to optimize the allocation of cost resources and improve the utilization efficiency of cost resources.

[0059] The monitoring and early warning module is used to monitor the changes in raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data in real time.

[0060] The monitoring and early warning module includes a time series model, which monitors the abnormal values ​​in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data and issues early warning signals; the time series model has an abnormal value monitoring rule, which is used to determine whether the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data are abnormal. The abnormal value monitoring rule is formulated based on error value, probability value, statistic and threshold.

[0061] Specifically, a time series model is selected according to the data collected by the data collection module. In this embodiment, the time series model selects an ARIMA model, and the ARIMA model is trained using the data collected by the data collection module.

[0062] Anomaly monitoring rules are formulated based on error values, probability values, statistics, and thresholds. For example, an error range can be set in the anomaly monitoring rule. When the error of the actual data exceeds this range, the data is considered abnormal. At this time, the monitoring and early warning module will issue an early warning to the staff. Real-time monitoring of financial cost data by the monitoring and early warning module can significantly reduce the processing time of staff when abnormal data is discovered, reduce unnecessary losses, and avoid risks.

[0063] The assisting processing module is used to generate 5 alternative plans for staff to choose from based on the abnormal values ​​in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data monitored in the monitoring and early warning module, combined with the historical cost control plan in the database establishment module.

[0064] Specifically, after the monitoring and early warning module monitors the abnormal values ​​in the financial cost data and issues early warnings to the staff, the assistance processing module will select the cost control plan based on the abnormal values ​​in the raw material cost data, production and manufacturing cost data, marketing cost data, and human resource cost data, combined with the historical cost control plans in the database. For example, there are 10 plans in the historical cost control plan. The assistance processing module will generate 5 alternative plans from these 10 cost control plans according to the correlation with the abnormal data for the staff to refer to and choose. The cost control plans selected by the assistance processing module provide reference for the staff, help the staff improve the efficiency and accuracy of decision-making, and provide support for the staff's decision-making.

[0065] Embodiment 2:

[0066] The difference from the above embodiment is that the control and evaluation system also includes a prediction module, which is used to simulate and control the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data, and predict the data change direction of product sales, profit margin, market share, return on investment and customer satisfaction through simulation and control. The auxiliary processing module is also used to propose control suggestions for raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data based on the data change direction of product sales, profit margin, market share, return on investment and customer satisfaction predicted by the prediction module. The control suggestions include regulating the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data from three directions: reducing, keeping unchanged and increasing.

[0067] Specifically, the prediction module is used to simulate and regulate the raw material cost data, production and manufacturing cost data, marketing cost data, and human resource cost data, and the direction of data changes in product sales, profit margins, market share, return on investment, and customer satisfaction are predicted during the simulation and regulation process. For example, by simulating a reduction of 1 million in raw material costs, it is predicted that the profit margin will increase by 10%. At this time, the assistance processing module will prompt the staff that the profit margin will increase when the raw material cost is reduced, thereby helping the staff to make the decision to reduce the raw material cost. Through the simulation and prediction of the control strategy by the prediction module, the staff can more accurately evaluate the impact of different decisions on the benefit data, so as to make more informed decisions. The assistance processing module makes regulation suggestions based on the prediction results, which can ensure that the company's resources are more reasonably allocated and utilized, thereby improving overall business performance.

[0068] Embodiment 3:

[0069] The difference from the above embodiment is that the control and evaluation system also includes a display module, which includes a display screen 2. The display screen 2 is fixedly connected to one side of the server 1 by screws. The display screen 2 is electrically connected to the server 1. The display module is used to display the data results processed by the cost analysis module, the importance assessment module, the monitoring and early warning module, the auxiliary processing module and the prediction module on the display screen 2 in the form of charts.

[0070] Specifically, by displaying the data results processed by the cost analysis module, importance assessment module, monitoring and early warning module, assistance processing module and prediction module on the display screen 2 in the form of charts, the staff can more intuitively understand the distribution and change trend of the data, so that it is easier to find the rules and anomalies in the data. The data results on the display screen 2 can provide strong data support for the staff, helping them to make more wise and accurate decisions. For example, by viewing the data results of the cost analysis module, decision makers can understand the cost structure and change trend of the enterprise, so as to formulate a more reasonable cost control strategy.

[0071] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. Intelligent device for financial cost control and benefit evaluation, characterized in that: It comprises a server (1) and a control and evaluation system, wherein the control and evaluation system is electrically connected to the server (1); The control and evaluation system includes: Data collection module, used to collect historical data related to finance and benefits, including financial cost data, benefit data and historical cost control plans; A database establishment module is used to pre-process the financial cost data, benefit data and historical cost control scheme collected by the data collection module and establish a database; Cost analysis module, used to analyze financial cost data from different dimensions; Financial cost data include raw material cost data, production cost data, marketing cost data and human resource cost data; Importance evaluation module, used to arrange raw material cost data, manufacturing cost data, marketing cost data and human resource cost data from largest to smallest according to their influence on benefit data; Monitoring and early warning module, used to monitor the changes of raw material cost data, production cost data, marketing cost data and human resource cost data in real time; The monitoring and early warning module includes a time series model; the time series model is used to monitor abnormal values ​​in raw material cost data, production and manufacturing cost data, marketing cost data, and human resource cost data and issue early warning signals; The assisting processing module is used to generate 5 alternative plans for staff to choose from based on the abnormal values ​​in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data monitored in the monitoring and early warning module, combined with the historical cost control plan in the database establishment module.

2. The intelligent device for financial cost control and benefit evaluation according to claim 1, characterized in that: Performance data includes product sales, profit margins, market share, return on investment, and customer satisfaction.

3. The intelligent device for financial cost control and benefit evaluation according to claim 2 is characterized in that: Preprocessing includes data cleaning, data deduplication and data standardization of financial cost data, benefit data and historical cost control plans.

4. The intelligent device for financial cost control and benefit evaluation according to claim 3 is characterized in that: The different dimensions include time dimension, location dimension, product dimension and department dimension.

5. The intelligent device for financial cost control and benefit evaluation according to claim 4 is characterized in that: Outlier monitoring rules are formulated in the time series model, and the outlier monitoring rules are used to determine whether there are anomalies in the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data.

6. The intelligent device for financial cost control and benefit evaluation according to claim 5 is characterized in that: Outlier monitoring rules are formulated based on error values, probability values, statistics, and thresholds.

7. The intelligent device for financial cost control and benefit evaluation according to claim 6 is characterized in that: The control and evaluation system also includes a prediction module; The prediction module is used to simulate and regulate the raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data respectively, and through simulation and regulation, predict the direction of data changes in product sales, profit margins, market share, return on investment and customer satisfaction.

8. The intelligent device for financial cost control and benefit evaluation according to claim 7 is characterized in that: The assistance processing module is also used to put forward suggestions for regulating raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data based on the data change direction of product sales, profit margin, market share, return on investment and customer satisfaction predicted by the forecasting module.

9. The intelligent device for financial cost control and benefit evaluation according to claim 8, characterized in that: The regulation suggestions include regulation of raw material cost data, production and manufacturing cost data, marketing cost data and human resource cost data in three directions: reduction, unchanged and increase.

10. The intelligent device for financial cost control and benefit evaluation according to claim 9, characterized in that: The control and evaluation system also includes a display module, which includes a display screen (2), the display screen (2) is fixedly connected to one side of the server (1), and the display screen (2) is electrically connected to the server (1); The display module is used to display the data results processed by the cost analysis module, the importance assessment module, the monitoring and early warning module, the auxiliary processing module and the prediction module on the display screen (2) in the form of charts.

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