Data-driven budgeting method and system

Abstract

The invention discloses a budgeting method and a budgeting system based on data driving, belongs to the technical field of financial management of an ERP (Enterprise Resource Planning) system, realizes data driving of budgeting through a business data collection template library and multi-stage data auditing, forms a datamation central data resource pool, provides reliable input for subsequent automatic calculation, and improves the budgeting efficiency. A structured budget management rule base is utilized to dynamically maintain and manage the budget management rule and the budget calculation formula in a classified manner, and a plurality of corresponding sensitivity analysis factors are configured, so that the structuralization and configurability of budget compilation logic are realized; and the result confirmation flow of the service processing end avoids a redundant and complicated modification process, so that the processing efficiency of the budget result is greatly improved.

Description

Technical Field

[0001] This invention belongs to the field of financial management technology of ERP systems, specifically relating to a data-driven budget preparation method and system. Background Technology

[0002] Budget management, as a core tool for corporate financial control and strategic execution, directly impacts a company's resource allocation, performance evaluation, and decision-making effectiveness through its quality and efficiency. In traditional Enterprise Resource Planning (ERP) or financial management systems, budget preparation typically employs a "two-down, two-up" model centered on manual entry and hierarchical aggregation. Specifically, management first issues the budget framework and targets (first step). Each business department, based on historical data and experience, manually fills in detailed budget data in static spreadsheets or simple forms and submits it (first step). The finance department then manually aggregates and performs preliminary balancing, providing feedback on modifications or adjusted data to the business departments (second step). The business departments then revise and resubmit, and this cycle continues until the final draft is completed (second step).

[0003] However, when dealing with complex budget preparation, this model often relies on a set of pre-set and fixed budget management rules, which are essentially static. When key business drivers such as market environment, raw material prices, and project progress change, dynamic budget adjustments cannot be made. Any modification to any parameter in these budget management rules requires manual recalculation, verification, and multi-level approval. The process is rigid and the response is slow, resulting in the budget often becoming out of touch with actual business by the time it is approved. Financial forecasts based on historical extrapolation have a serious lack of flexibility in budget preparation and are difficult to adapt to dynamic business environments.

[0004] Furthermore, the existing budget management process is a cyclical process of "multiple downs and multiple ups" based on "two downs and two ups," involving a large number of cross-departmental and cross-level paper or electronic document transfers, meeting communications, and manual reviews. If errors are found or balancing adjustments are needed during the data entry, summarization, and verification process, the entire process often needs to be backed up layer by layer to the source department, and after modification, it has to go through the complete review chain again. This linear and serial process is not only time-consuming and labor-intensive, extending the budget cycle (usually for several months), but also easily introduces new data and human errors in repeated modifications, making the budget management process lengthy and complex, and the communication and coordination costs between various review nodes are high.

[0005] As mentioned above, how to provide a data-driven budgeting method and system that can flexibly configure rules, automate budget preparation, and efficiently generate budget results has become an urgent problem to be solved in this field. Summary of the Invention

[0006] The purpose of this invention is to provide a data-driven budgeting method and system to solve the aforementioned problems in the prior art.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a data-driven budgeting method, comprising: Acquire standardized business data of various budget types uploaded by the business processing terminal, and perform multi-level data review on the standardized business data. Store the standardized business data that has passed the multi-level data review into the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. The system acquires multiple budget management rules input from the budget management terminal, categorizes each budget management rule according to budget type, defines corresponding budget calculation formulas and sensitivity analysis factors for each categorized budget management rule, and establishes a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule library. The budget management rule base is used to calculate the budget results of standardized business data of various budget types in the central data resource pool to generate an initial budget result. The initial budget result is then sent to the finance department for confirmation. Based on the confirmation result, the budget result is generated and stored in the central data resource pool, thus completing the budget preparation.

[0008] In one possible design, standardized business data of various budget types uploaded by the business processing terminal is acquired, and the standardized business data undergoes multi-level data review. The standardized business data that passes the multi-level data review is then stored in a central data resource pool, including: Obtain business data collection document templates for each budget type and store the business data collection document templates for each budget type in the business data collection template library. The budget types include investment budget, cost and expense budget, and revenue budget. The business data collection document templates include business name field, business time field, structured field of business driver parameters, and structured field of budget preparation parameters. The system obtains data upload requests from the business processing terminal, identifies the budget type of the data upload requests, obtains the budget type identification result, and retrieves the corresponding budget type business data collection document template from the business data collection template library based on the budget type identification result as the current business data collection document template. The basic business data uploaded by the business processing terminal is collected using the current business data collection form template. The corresponding supplementary business data is obtained from the central data resource pool using the basic business data as the query condition. The basic business data and the supplementary business data are standardized, and the standardized basic business data and the supplementary business data are integrated into standardized business data. The standardized business data is submitted to the data review terminal, which then sends it to review nodes at all levels for sequential review. The data review process is recorded and the data review results are obtained. If the data audit result is "passed", the standardized business data that has passed the multi-level data audit will be stored in the central data resource pool, and the data audit process and the data audit result will be stored in the central data resource pool. The multi-level data audit includes data platform audit, business department audit and budget specialist audit. If the data review result is "not approved", the standardized business data that failed the multi-level data review will be returned to the business processing end for business data modification. The data review process and the data review result will be sent to the business processing end for visualization display. The modified standardized business data will be obtained and subjected to multi-level data review until the data review result is "approved".

[0009] In one possible design, multiple budget management rules input from the budget management terminal are obtained. These rules are then categorized according to budget type. For each categorized rule, a corresponding budget calculation formula and sensitivity analysis factor are defined. This process establishes a correlation between the budget management rules for each budget type and each budget calculation formula and sensitivity analysis factor, generating a budget management rule library, including: The system retrieves multiple budget management rules input from the budget management terminal, categorizes these rules according to budget type, and obtains investment budget management rules, cost and expense budget management rules, and revenue budget management rules. For the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, the budget calculation formula description, budget calculation target, and budget calculation conditions for the corresponding budget type are defined through the budget management terminal; Based on the description of the budget calculation formula, the budget calculation objectives, and the budget calculation conditions, budget calculation formulas corresponding to various budget types are generated for the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, respectively. Through the budget management terminal, multiple sensitivity analysis factors are defined for the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, respectively. The sensitivity analysis factors are used to characterize the budget impact variables that affect the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules. Obtain preset rule association mapping relationships, and based on the rule association mapping relationships, form associations between the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules and the corresponding budget calculation formulas and the corresponding sensitivity analysis factors to obtain various types of budget rule association relationships; The various types of budget rule relationships are categorized and stored to generate a budget management rule library.

[0010] In one possible design, the sensitivity analysis factors include business driver analysis factors, accounting item analysis factors, budget control item analysis factors, and budget preparation analysis factors; Accordingly, after defining multiple sensitivity analysis factors, the following are also included: For each sensitivity analysis factor, a sensitivity analysis control parameter is configured for budget sensitivity analysis. The sensitivity analysis control parameter includes the abbreviation of the sensitivity analysis factor, the unit of measurement of the sensitivity analysis factor, the decimal places of the sensitivity analysis factor, the upper and lower limit types of the sensitivity analysis factor, the limit range of the sensitivity analysis factor, and the adjustment step size of the sensitivity analysis factor. A sensitivity analysis control window is set for each sensitivity analysis control parameter, and the corresponding sensitivity analysis factor control instruction is obtained from the business processing terminal through the sensitivity analysis control window. The sensitivity analysis control window includes a sensitivity analysis control progress bar, a sensitivity analysis control button, and a sensitivity analysis control input box. Based on the sensitivity analysis factor regulation instructions, each of the sensitivity analysis factors is regulated to obtain the regulated sensitivity analysis factors. Based on the rule-based mapping relationship, various types of budget rule relationships are formed between the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules and the corresponding budget calculation formulas and the adjusted sensitivity analysis factors.

[0011] In one possible design, the budget management rule base is used to calculate budget results from standardized business data of various budget types in the central data resource pool to generate initial budget results, including: The standardized business data is extracted from the central data resource pool, and the corresponding budget management rules and budget calculation formulas are selected from the budget management rule base according to the budget type of the standardized business data. Based on the budget management rules and the budget calculation formula, the standardized business data is used to calculate the budget and obtain the initial budget result.

[0012] In one possible design, the initial budget result is sent to the finance department for confirmation. Upon receiving the finance department's confirmation, a budget result is generated and stored in the central data resource pool, thus completing budget preparation, including: Obtain a preset budget result comparison standard, send the initial budget result to the finance department, and compare the initial budget result with the budget result comparison standard through the business processing terminal to obtain the finance department confirmation result; If the financial department confirms that the initial budget result meets the budget result comparison standard, then the initial budget result is marked as a normal budget result, and the initial budget result marked as a normal budget result is used as the budget result and stored in the central data resource pool to complete the budget preparation. If the financial department confirms that the initial budget result does not meet the budget result comparison standard, the initial budget result is marked as an abnormal budget result. The initial budget result marked as an abnormal budget result is sent to the budget management department to issue a corresponding budget management warning message. The budget management warning message is recorded and displayed visually on the business processing department.

[0013] In one possible design, after the budget is prepared, it also includes: The budget preparation path of each budget result stored in the central data resource pool is recorded. The budget preparation path is associated with the budget result and then stored in the central data resource pool. The budget preparation path includes standardized business data, budget management rules, budget calculation formulas and sensitivity analysis factors corresponding to the budget result generation process.

[0014] Secondly, the present invention provides a data-driven budgeting system, comprising: A standardized business data storage unit is used to acquire standardized business data of various budget types uploaded by the business processing terminal, and to perform multi-level data review on the standardized business data. The standardized business data that has passed the multi-level data review is stored in the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. The budget management rule base construction unit is used to acquire multiple budget management rules input from the budget management terminal, classify each budget management rule according to budget type, define corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establish a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule base. The budget result generation unit is used to calculate the budget result by using the budget management rule base to perform standardized business data of various budget types in the central data resource pool, so as to generate an initial budget result, and send the initial budget result to the finance end for result confirmation. After obtaining the confirmation result from the finance end, the budget result is generated and stored in the central data resource pool based on the confirmation result from the finance end, thus completing the budget preparation.

[0015] Thirdly, the present invention provides an electronic device comprising a memory, a processor, and a transceiver connected in sequence and communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the data-driven budgeting method as described in the first aspect or any possible design of the first aspect.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the data-driven budgeting method described in the first aspect or any possible design of the first aspect.

[0017] Fifthly, the present invention provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform a data-driven budgeting method as described in the first aspect or any possible design of the first aspect.

[0018] Beneficial Effects: This invention provides a data-driven budgeting method, comprising: First, acquiring standardized business data of various budget types uploaded by the business processing terminal, and performing multi-level data review on the standardized business data, storing the standardized business data that has passed the multi-level data review into a central data resource pool, wherein the standardized business data includes business driver parameters and budgeting parameters; Second, acquiring multiple budget management rules input by the budget management terminal, classifying each budget management rule according to budget type, defining corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establishing associations between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule library; Finally, using the budget management rule library to calculate the budget results of the standardized business data of various budget types in the central data resource pool to generate initial budget results, sending the initial budget results to the finance terminal for confirmation, obtaining the finance terminal confirmation result, generating budget results based on the finance terminal confirmation result and storing them in the central data resource pool, thus completing budgeting. By using a business data collection template library and multi-level data review, data-driven budget preparation is achieved, forming a data-driven central data resource pool. This provides reliable input for subsequent automated calculations. Furthermore, by utilizing a structured budget management rule library, budget management rules and budget calculation formulas are dynamically maintained and managed by category, and multiple corresponding sensitivity analysis factors are configured, realizing the structured and configurable nature of budget preparation logic. Meanwhile, the result confirmation process at the business processing end avoids redundant and complicated modification processes, significantly improving the efficiency of budget result processing. Attached Figure Description

[0019] Figure 1 A flowchart illustrating the data-driven budgeting method provided in an embodiment of the present invention; Figure 2 A functional structure diagram of a data-driven budget preparation system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0021] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0022] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0023] Example: like Figure 1 As shown, the first aspect of this embodiment provides a data-driven budgeting method, which may include, but is not limited to, the following steps: S1. Obtain standardized business data of various budget types uploaded by the business processing terminal, and perform multi-level data review on the standardized business data. Store the standardized business data that has passed the multi-level data review into the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. In one possible implementation, step S1 involves acquiring standardized business data of various budget types uploaded by the business processing terminal, performing multi-level data review on the standardized business data, and storing the standardized business data that has passed the multi-level data review into the central data resource pool. This can be broken down into, but is not limited to, the following steps S11-S16, specifically including: S11. Obtain business data collection document templates for each budget type, and store the business data collection document templates for each budget type into the business data collection template library. The budget types include investment budget, cost and expense budget, and revenue budget. The business data collection document templates include business name field, business time field, structured field of business driver parameters, and structured field of budget preparation parameters. S12. Obtain the data upload request sent by the business processing terminal, identify the budget type of the data upload request, obtain the budget type identification result, and retrieve the corresponding budget type business data collection document template from the business data collection template library according to the budget type identification result as the current business data collection document template; S13. Collect basic business data uploaded by the business processing terminal using the current business data collection form template, obtain corresponding supplementary business data from the central data resource pool using the basic business data as query conditions, standardize the basic business data and the supplementary business data, and integrate the standardized basic business data and the supplementary business data into standardized business data. S14. Submit the standardized business data to the data review terminal, and send it to the review nodes at all levels through the data review terminal to conduct data review in sequence, record the data review process and obtain the data review results; S15. If the data audit result is "passed", the standardized business data that has passed the multi-level data audit will be stored in the central data resource pool, and the data audit process and the data audit result will be stored in the central data resource pool. The multi-level data audit includes data platform audit, business department audit and budget specialist audit. S16. If the data review result is "not approved", the standardized business data that failed the multi-level data review is returned to the business processing end for business data modification. The data review process and the data review result are sent to the business processing end for visualization display. The modified standardized business data is then obtained for multi-level data review until the data review result is "approved".

[0024] It should be noted that the budget preparation method provided in this embodiment constructs a business data collection template library by collecting business data collection document templates for various budget types. This achieves digitalization and standardization at the source of budget preparation, reduces manual input errors when retrieving data from the business system, and ensures improved data quality from the data source. The introduced online multi-level review process digitizes the review process, replacing offline transmission with online review. The approval trajectory is clearly traceable, the process cycle is significantly shortened, and process efficiency is greatly improved. Business personnel (business processing end) are reduced from filling out complex financial budget forms to filling out simple basic business data and confirming the corresponding supplementary business data obtained from the central data resource pool, thus reducing their workload. Through the business data collection template library and multi-level data review in this embodiment, true data-driven budget preparation is achieved, forming a unique, accurate, and traceable central data resource pool, providing reliable input for subsequent automated calculations.

[0025] S2. Obtain multiple budget management rules input from the budget management terminal, classify each budget management rule according to budget type, define corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establish a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule library; In one possible implementation, step S2 involves acquiring multiple budget management rules input from the budget management terminal, classifying each budget management rule according to its budget type, defining corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establishing associations between the budget management rules of various budget types and each budget calculation formula and sensitivity analysis factor to generate a budget management rule base. This can be broken down into, but is not limited to, the following steps S21-S26, specifically including: S21. Obtain multiple budget management rules input from the budget management terminal, classify and process each budget management rule according to the budget type, and obtain investment budget management rules, cost and expense budget management rules, and revenue budget management rules; S22. For the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, the budget calculation formula description, budget calculation target, and budget calculation conditions for the corresponding budget type are defined through the budget management terminal; S23. Based on the description of the budget calculation formula, the budget calculation objective, and the budget calculation conditions, generate budget calculation formulas corresponding to various budget types for the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, respectively; S24. Through the budget management terminal, define a number of corresponding sensitivity analysis factors for the investment budget management rules, the cost and expense budget management rules and the revenue budget management rules respectively, wherein the sensitivity analysis factors are used to characterize the budget impact variables that affect the investment budget management rules, the cost and expense budget management rules and the revenue budget management rules; S25. Obtain a preset rule association mapping relationship, and based on the rule association mapping relationship, form an association between the investment budget management rule, the cost and expense budget management rule, and the revenue budget management rule and the corresponding budget calculation formula and the corresponding sensitivity analysis factor to obtain various types of budget rule association relationships; S26. Classify and store the various types of budget rule relationships to generate a budget management rule library.

[0026] It should be noted that the budget preparation method provided in this embodiment, by constructing a structured budget management rule base, allows for the categorized maintenance and management of budget management rules and budget calculation formulas, and configures corresponding multiple sensitivity analysis factors, thus realizing the structured and configurable budget preparation logic. In specific implementation, the budget management rules and budget calculation formulas can be dynamically configured and adjusted at any time according to business changes, enabling the budget configuration method in this embodiment to have strong adaptability and dynamic adjustment capabilities; in addition, the generation of each budget data has clear budget management rules and budget calculation formulas as the basis, facilitating subsequent data flow backtracking (budget preparation path recording).

[0027] In one possible implementation, in step S24, the sensitivity analysis factors include business driver analysis factors, accounting subject analysis factors, budget control project analysis factors, and budget preparation analysis factors. Accordingly, after defining multiple sensitivity analysis factors, the following steps S241-S244 may also be included, but are not limited to: S241. Configure sensitivity analysis control parameters for each sensitivity analysis factor to perform budget sensitivity analysis, wherein the sensitivity analysis control parameters include the abbreviation of the sensitivity analysis factor, the unit of measurement of the sensitivity analysis factor, the decimal places of the sensitivity analysis factor, the upper and lower limit types of the sensitivity analysis factor, the limit range of the sensitivity analysis factor, and the adjustment step size of the sensitivity analysis factor. S242. Set a sensitivity analysis control window for each sensitivity analysis control parameter, and obtain the corresponding sensitivity analysis factor control instruction from the business processing terminal through the sensitivity analysis control window, wherein the sensitivity analysis control window includes a sensitivity analysis control progress bar, a sensitivity analysis control button and a sensitivity analysis control input box; S243. Based on the sensitivity analysis factor control instruction, each of the sensitivity analysis factors is controlled to obtain the controlled sensitivity analysis factors; S244. Based on the rule association mapping relationship, an association is formed between the investment budget management rule, the cost and expense budget management rule, and the revenue budget management rule and the corresponding budget calculation formula and each of the adjusted sensitivity analysis factors, to obtain various types of budget rule association relationships.

[0028] It should be noted that the budget preparation method in this embodiment provides a user interaction window and a sensitivity analysis control window, allowing users to dynamically adjust the various sensitivity analysis factors according to actual conditions and temporary changes, triggering real-time related budget calculations. Furthermore, the sensitivity analysis control window provides visual feedback, realizing the advancement of budgeting from static reports to dynamic decision-making simulations. Managers or decision-makers at the corresponding budget management end can intuitively and instantly observe the impact of changes in these sensitivity analysis factors (e.g., price, sales volume, cost) on the final budget results (e.g., profit, cash flow). More importantly, this controllable dynamic mechanism transforms multi-round, cross-departmental offline communication and trial calculations into real-time interactive simulations on the front-end interface, significantly shortening the decision-making cycle and greatly improving the efficiency of budget result generation. Moreover, the user end (business processing end) can perform horizontal comparative analysis of the generated budget results under the influence of different sensitivity analysis factors, helping to select the optimal budget preparation path.

[0029] In one possible implementation, step S2, using the budget management rule base to calculate budget results on standardized business data of various budget types in the central data resource pool to generate initial budget results, can be, but is not limited to, decomposed into the following steps S27-S28, specifically including: S27. Extract the standardized business data from the central data resource pool, and select the corresponding budget management rules and budget calculation formulas from the budget management rule base according to the budget type of the standardized business data; S28. Based on the budget management rules and the budget calculation formula, perform budget calculations on the standardized business data to obtain the initial budget result.

[0030] S3. Calculate the budget results using the budget management rule base on the standardized business data of various budget types in the central data resource pool to generate an initial budget result. Send the initial budget result to the finance department for confirmation. Obtain the confirmation result from the finance department. Based on the confirmation result from the finance department, generate the budget result and store it in the central data resource pool to complete the budget preparation.

[0031] In one possible implementation, step S3 involves sending the initial budget result to the finance department for confirmation, obtaining a confirmation result from the finance department, generating a budget result based on the confirmation result, and storing it in the central data resource pool to complete the budget preparation. This step can be broken down into, but is not limited to, the following steps S31-S33, specifically including: S31. Obtain a preset budget result comparison standard, send the initial budget result to the finance end, and compare the initial budget result with the budget result comparison standard through the business processing end to obtain the finance end confirmation result; S32. If the financial department confirms that the initial budget result meets the budget result comparison standard, then the initial budget result is marked as a normal budget result, and the initial budget result marked as a normal budget result is used as the budget result and stored in the central data resource pool to complete the budget preparation; S33. If the financial department confirms that the initial budget result does not meet the budget result comparison standard, the initial budget result is marked as an abnormal budget result, and the initial budget result marked as an abnormal budget result is sent to the budget management department to issue a corresponding budget management warning message. The budget management warning message is recorded, and the budget management warning message is visualized on the business processing department.

[0032] It should be noted that the budget preparation method provided in this embodiment realizes an automated confirmation process from the initial budget result to the final budget result through result feedback and confirmation at the business processing end. It eliminates the need for offline communication and rejection, avoids duplicate data submission and redundant processing, and achieves faster processing of budget results between ends in a more efficient manner, thus greatly improving the processing efficiency of budget results.

[0033] In one possible implementation, step S3, after the budget preparation is completed, may also include, but is not limited to, the following step S34, specifically including: S34. Record the budget preparation path of each budget result stored in the central data resource pool, and store the budget preparation path in the central data resource pool after associating the budget preparation path with the budget result. The budget preparation path includes standardized business data, budget management rules, budget calculation formulas and sensitivity analysis factors corresponding to the budget result generation process.

[0034] Specifically, in practical applications, the budget preparation path includes all relevant process data in the budget result generation process, including standardized business data, multi-level data review processes, multi-level data review results, budget management rules, budget calculation formulas, sensitivity analysis factors, sensitivity analysis control instructions, financial confirmation results, and all other data that contributes to and is related to the generation of budget results. This is to improve the completeness of the budget results, and storing this data facilitates possible in-depth analysis of the budget process, comparison of historical budget preparation, and data monitoring.

[0035] like Figure 2 As shown, the second aspect of this embodiment provides a hardware system for implementing the data-driven budgeting method described in the first aspect of the embodiment, including: A standardized business data storage unit is used to acquire standardized business data of various budget types uploaded by the business processing terminal, and to perform multi-level data review on the standardized business data. The standardized business data that has passed the multi-level data review is stored in the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. The budget management rule base construction unit is used to acquire multiple budget management rules input from the budget management terminal, classify each budget management rule according to budget type, define corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establish a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule base. The budget result generation unit is used to calculate the budget result by using the budget management rule base to perform standardized business data of various budget types in the central data resource pool, so as to generate an initial budget result, and send the initial budget result to the finance end for result confirmation. After obtaining the confirmation result from the finance end, the budget result is generated and stored in the central data resource pool based on the confirmation result from the finance end, thus completing the budget preparation.

[0036] The working process, working details and technical effects of the system provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0037] like Figure 3 As shown, the third aspect of this embodiment provides an electronic device, including: a memory, a processor, and a transceiver that are sequentially and communicatively connected, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the data-driven budgeting method as described in the first aspect of the embodiment.

[0038] For specific examples, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0039] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee transceiver (a low-power LAN protocol based on the IEEE 802.15.4 standard), a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0040] The working process, working details and technical effects of the electronic device provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0041] The fourth aspect of this embodiment provides a storage medium for storing instructions containing the data-driven budgeting method described in the first aspect of the embodiment. That is, the storage medium stores instructions that, when executed on a computer, perform the data-driven budgeting method as described in the first aspect of the embodiment.

[0042] The storage medium refers to a carrier for storing data, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or memory sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0043] The working process, working details and technical effects of the storage medium provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0044] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the data-driven budgeting method as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0045] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A data-driven budgeting method, characterized in that, include: Acquire standardized business data of various budget types uploaded by the business processing terminal, and perform multi-level data review on the standardized business data. Store the standardized business data that has passed the multi-level data review into the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. The system acquires multiple budget management rules input from the budget management terminal, categorizes each budget management rule according to budget type, defines corresponding budget calculation formulas and sensitivity analysis factors for each categorized budget management rule, and establishes a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule library. The budget management rule base is used to calculate the budget results of standardized business data of various budget types in the central data resource pool to generate an initial budget result. The initial budget result is then sent to the finance department for confirmation. Based on the confirmation result, the budget result is generated and stored in the central data resource pool, thus completing the budget preparation.

2. The data-driven budgeting method according to claim 1, characterized in that, Acquire standardized business data of various budget types uploaded by the business processing terminal, perform multi-level data review on the standardized business data, and store the standardized business data that has passed the multi-level data review into the central data resource pool, including: Obtain business data collection document templates for each budget type and store the business data collection document templates for each budget type in the business data collection template library. The budget types include investment budget, cost and expense budget, and revenue budget. The business data collection document templates include business name field, business time field, structured field of business driver parameters, and structured field of budget preparation parameters. The system obtains data upload requests from the business processing terminal, identifies the budget type of the data upload requests, obtains the budget type identification result, and retrieves the corresponding budget type business data collection document template from the business data collection template library based on the budget type identification result as the current business data collection document template. The basic business data uploaded by the business processing terminal is collected using the current business data collection form template. The corresponding supplementary business data is obtained from the central data resource pool using the basic business data as the query condition. The basic business data and the supplementary business data are standardized, and the standardized basic business data and the supplementary business data are integrated into standardized business data. The standardized business data is submitted to the data review terminal, which then sends it to review nodes at all levels for sequential review. The data review process is recorded and the data review results are obtained. If the data audit result is "passed", the standardized business data that has passed the multi-level data audit will be stored in the central data resource pool, and the data audit process and the data audit result will be stored in the central data resource pool. The multi-level data audit includes data platform audit, business department audit and budget specialist audit. If the data review result is "not approved", the standardized business data that failed the multi-level data review will be returned to the business processing end for business data modification. The data review process and the data review result will be sent to the business processing end for visualization display. The modified standardized business data will be obtained and subjected to multi-level data review until the data review result is "approved".

3. The data-driven budgeting method according to claim 1, characterized in that, The system acquires multiple budget management rules input from the budget management terminal, categorizes these rules according to budget type, defines corresponding budget calculation formulas and sensitivity analysis factors for each categorized rule, and establishes associations between the budget management rules for each budget type and each budget calculation formula and sensitivity analysis factor, thereby generating a budget management rule library, including: The system retrieves multiple budget management rules input from the budget management terminal, categorizes these rules according to budget type, and obtains investment budget management rules, cost and expense budget management rules, and revenue budget management rules. For the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, the budget calculation formula description, budget calculation target, and budget calculation conditions for the corresponding budget type are defined through the budget management terminal; Based on the description of the budget calculation formula, the budget calculation objectives, and the budget calculation conditions, budget calculation formulas corresponding to various budget types are generated for the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, respectively. Through the budget management terminal, multiple sensitivity analysis factors are defined for the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules, respectively. The sensitivity analysis factors are used to characterize the budget impact variables that affect the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules. Obtain preset rule association mapping relationships, and based on the rule association mapping relationships, form associations between the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules and the corresponding budget calculation formulas and the corresponding sensitivity analysis factors to obtain various types of budget rule association relationships; The various types of budget rule relationships are categorized and stored to generate a budget management rule library.

4. The data-driven budgeting method according to claim 3, characterized in that, The sensitivity analysis factors include business driver analysis factors, accounting subject analysis factors, budget control project analysis factors, and budget preparation analysis factors. Accordingly, after defining multiple sensitivity analysis factors, the following are also included: For each sensitivity analysis factor, a sensitivity analysis control parameter is configured for budget sensitivity analysis. The sensitivity analysis control parameter includes the abbreviation of the sensitivity analysis factor, the unit of measurement of the sensitivity analysis factor, the decimal places of the sensitivity analysis factor, the upper and lower limit types of the sensitivity analysis factor, the limit range of the sensitivity analysis factor, and the adjustment step size of the sensitivity analysis factor. A sensitivity analysis control window is set for each sensitivity analysis control parameter, and the corresponding sensitivity analysis factor control instruction is obtained from the business processing terminal through the sensitivity analysis control window. The sensitivity analysis control window includes a sensitivity analysis control progress bar, a sensitivity analysis control button, and a sensitivity analysis control input box. Based on the sensitivity analysis factor regulation instructions, each of the sensitivity analysis factors is regulated to obtain the regulated sensitivity analysis factors. Based on the rule-based mapping relationship, various types of budget rule relationships are formed between the investment budget management rules, the cost and expense budget management rules, and the revenue budget management rules and the corresponding budget calculation formulas and the adjusted sensitivity analysis factors.

5. The data-driven budgeting method according to claim 1, characterized in that, The budget management rule base is used to calculate budget results from standardized business data of various budget types in the central data resource pool to generate initial budget results, including: The standardized business data is extracted from the central data resource pool, and the corresponding budget management rules and budget calculation formulas are selected from the budget management rule base according to the budget type of the standardized business data. Based on the budget management rules and the budget calculation formula, the standardized business data is used to calculate the budget and obtain the initial budget result.

6. The data-driven budgeting method according to claim 5, characterized in that, The initial budget results are sent to the finance department for confirmation. Based on the finance department's confirmation, a budget result is generated and stored in the central data resource pool, completing the budget preparation process, including: Obtain a preset budget result comparison standard, send the initial budget result to the finance department, and compare the initial budget result with the budget result comparison standard through the business processing terminal to obtain the finance department confirmation result; If the financial department confirms that the initial budget result meets the budget result comparison standard, then the initial budget result is marked as a normal budget result, and the initial budget result marked as a normal budget result is used as the budget result and stored in the central data resource pool to complete the budget preparation. If the financial department confirms that the initial budget result does not meet the budget result comparison standard, the initial budget result is marked as an abnormal budget result. The initial budget result marked as an abnormal budget result is sent to the budget management department to issue a corresponding budget management warning message. The budget management warning message is recorded and displayed visually on the business processing department.

7. The data-driven budgeting method according to claim 1, characterized in that, After the budget is completed, it also includes: The budget preparation path of each budget result stored in the central data resource pool is recorded. The budget preparation path is associated with the budget result and then stored in the central data resource pool. The budget preparation path includes standardized business data, budget management rules, budget calculation formulas and sensitivity analysis factors corresponding to the budget result generation process.

8. A data-driven budgeting system, characterized in that, The method applied to the data-driven budgeting method as described in any one of claims 1 to 7 includes: A standardized business data storage unit is used to acquire standardized business data of various budget types uploaded by the business processing terminal, and to perform multi-level data review on the standardized business data. The standardized business data that has passed the multi-level data review is stored in the central data resource pool. The standardized business data includes business motivation parameters and budget preparation parameters. The budget management rule base construction unit is used to acquire multiple budget management rules input from the budget management terminal, classify each budget management rule according to budget type, define corresponding budget calculation formulas and sensitivity analysis factors for each classified budget management rule, and establish a correlation between the budget management rules of various budget types and each budget calculation formula and each sensitivity analysis factor to generate a budget management rule base. The budget result generation unit is used to calculate the budget result by using the budget management rule base to perform standardized business data of various budget types in the central data resource pool, so as to generate an initial budget result, and send the initial budget result to the finance end for result confirmation. After obtaining the confirmation result from the finance end, the budget result is generated and stored in the central data resource pool based on the confirmation result from the finance end, thus completing the budget preparation.

9. An electronic device, characterized in that, The system includes a memory, a processor, and a transceiver that are sequentially and communicatively connected. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the data-driven budgeting method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or the instructions are executed by the computer, they implement the data-driven budgeting method as described in any one of claims 1 to 7.

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