Method and device for constructing multi-dimensional account book of responsibility accounting

Abstract

The present application provides a method and device for constructing a multidimensional account book of responsibility accounting, which belongs to the technical field of responsibility accounting of ERP enterprise management software. The method for constructing a multidimensional account book of responsibility accounting includes: constructing an internal data pool of responsibility accounting to realize the standardization of business data; keeping accounts based on the business data in the internal data pool of responsibility accounting to generate a basic account book; setting multidimensional account book rules; processing the data in the basic account book based on the multidimensional account book rules to generate multidimensional account book data. The method for constructing a multidimensional account book of responsibility accounting provided by the present application can efficiently and accurately construct a multidimensional account book of responsibility accounting in the case where the frequency of changes in the organizational structure of the enterprise is high and there is an internal settlement scenario.

Description

Technical Field

[0001] The present application belongs to the technical field of responsibility accounting of ERP enterprise management software, and specifically relates to a method and device for constructing a multi-dimensional account book of responsibility accounting. Background Art

[0002] When building a multidimensional account book based on corporate operating data, the relationship between corporate organizations will affect the determination of internal settlements. Business transactions between two organizations under the same parent organization are internal transactions, and the income and costs generated are considered internal settlements for the parent organization. If they are recorded in the account book according to the actual amount, it will lead to inflated income and costs. When the corporate organizational structure changes, the determination of internal settlements will also change. Therefore, how to correctly handle internal settlements affects the accuracy of multidimensional accounts.

[0003] The existing account book construction method is difficult to handle changes in organizational structure and the existence of internal settlement business. It is difficult to build a multi-dimensional account book of the entire organizational structure including internal settlement data, and it is impossible to simultaneously build a multi-dimensional account book before and after the organizational structure change. Summary of the invention

[0004] In order to solve at least one technical problem existing in the background technology, the present application provides a method for constructing a multi-dimensional account book of responsibility accounting, which can efficiently and accurately construct a multi-dimensional account book of responsibility accounting in the scenario where the organizational structure of the enterprise changes frequently and there is internal settlement.

[0005] The technical solution adopted in this application is:

[0006] The first embodiment of the present application provides a method for constructing a multi-dimensional account book of responsibility accounting, including:

[0007] Build an internal data pool for responsibility accounting to achieve standardization of business data;

[0008] Bookkeeping is performed based on the operating data in the responsibility accounting internal data pool to generate a basic account book;

[0009] Set up multi-dimensional ledger rules;

[0010] The data in the basic account book is processed based on the multi-dimensional account book rule to generate multi-dimensional account book data.

[0011] According to one embodiment of the present application, the construction of the responsibility accounting internal data pool includes:

[0012] The internal settlement documents maintained during internal settlement are added to the responsibility accounting internal data pool, the settlement parties are defined as "cost center / profit center, counterparty cost center / counterparty profit center", and the transaction information of the settlement parties is recorded.

[0013] According to an embodiment of the present application, the bookkeeping based on the operating data in the responsibility accounting internal data pool to generate a basic account book is specifically:

[0014] When recording accounts, the original accounting dimensions are retained and the accounting period is determined based on the business date;

[0015] Summarize the current period's debits, current period's credits, current year's debit accumulations, and current year's credit accumulations based on the accounting period;

[0016] The data including the aforementioned “cost center / profit center, counterparty cost center / counterparty profit center” are defined as internal settlement data;

[0017] The first common superior of the "cost center / profit center, counterparty cost center / counterparty profit center" is found, and the offset data of the common superior is generated.

[0018] According to an embodiment of the present application, the construction of the responsibility accounting internal data pool to achieve the standardization of business data is specifically as follows:

[0019] Define standard data format parameters of the responsibility accounting internal data pool;

[0020] Based on the standard data format parameters, homogeneous data and heterogeneous data in the business data are converted to identify cost centers, profit centers, accounting dimensions, and analysis dimensions.

[0021] According to an embodiment of the present application, the multi-dimensional account book rule includes accounting dimensions and account book value conditions for each of the accounting dimensions.

[0022] According to an embodiment of the present application, the processing of the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data is specifically:

[0023] Filtering the data in the basic account book based on the value conditions in the multi-dimensional account book rules;

[0024] The filtered data is aggregated according to the accounting dimensions.

[0025] According to an embodiment of the present application, the processing of the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data further includes:

[0026] Based on the enterprise organizational structure, summarize the data of each organizational node at the current level and its direct subordinates.

[0027] According to an embodiment of the present application, the processing of the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data further includes:

[0028] The beginning and ending amounts are calculated based on the beginning of the year, the occurrence of this period, and the cumulative occurrence of this year to generate the multi-dimensional account book data.

[0029] According to one embodiment of the present application, the method further includes:

[0030] The multi-dimensional account book data is transferred to a fixed version, and when the enterprise organizational structure changes, a new version of the multi-dimensional account book data is regenerated;

[0031] Compare and analyze the fixed version of multi-dimensional account book data and the new version of multi-dimensional account book data.

[0032] The second aspect of the present application provides a device for constructing a multi-dimensional account book of responsibility accounting, including:

[0033] The data pool construction module is suitable for building the internal data pool of responsibility accounting to achieve the standardization of business data;

[0034] A basic account book generation module, adapted to record accounts based on the operating data in the responsibility accounting internal data pool to generate a basic account book;

[0035] The rule setting module is suitable for setting multi-dimensional account book rules;

[0036] The multi-dimensional account book data generating module is adapted to process the data in the basic account book based on the multi-dimensional account book rules to generate multi-dimensional account book data.

[0037] Due to the adoption of the above technical solution, the beneficial effects achieved by this application include at least:

[0038] According to the method for constructing a multi-dimensional account book of responsibility accounting provided by the embodiment of the first aspect of the present application, first, an internal data pool of responsibility accounting is constructed to realize the standardization of operating data. This step aims to unify the business data of enterprises from different sources into a standard format to realize data standardization, which is not only conducive to data management and query, but also lays a good foundation for the subsequent construction of multi-dimensional account books. Standardized data can ensure that information of all dimensions is retained, thereby improving the quality and consistency of account book data; accounting is performed based on the operating data in the internal data pool of responsibility accounting to generate a basic account book. In this step, the basic account book can only record the beginning of the year and the current period. The three types of data, namely, the annual and annual cumulative data, can not only reduce the amount of data, but also quickly form the beginning and end data; setting multi-dimensional account book rules provides guiding principles for the next step of processing the data in the basic account book. The pre-set rules can automatically process a large amount of data, reduce the need for manual intervention, and improve work efficiency; finally, the data in the basic account book is processed based on the multi-dimensional account book rules to generate multi-dimensional account book data. In this step, irrelevant data is filtered out through rules, and only data related to the multi-dimensional account book is retained, and then aggregated as needed to make the data more centralized and useful. The generated multi-dimensional account book data can provide the enterprise management with a more detailed and comprehensive financial analysis perspective. In summary, the method for constructing a multi-dimensional account book of responsibility accounting provided in the first aspect of the embodiment of the present application can efficiently and accurately construct a multi-dimensional account book of responsibility accounting in the case where the frequency of changes in the organizational structure of the enterprise is high and there is an internal settlement scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0040] Figure 1 Schematic diagram of the process of constructing a multi-dimensional account book of responsibility accounting provided in the embodiment of the present application Figure 1 ;

[0041] Figure 2 Schematic diagram of the process of constructing a multi-dimensional account book of responsibility accounting provided in the embodiment of the present application Figure 2 ;

[0042] Figure 3 A schematic diagram of the structure of an apparatus for constructing a multi-dimensional account book for responsibility accounting provided in an embodiment of the present application.

[0043] in,

[0044] 110. Data pool construction module; 120. Basic account book generation module; 130. Rule setting module; 140. Multi-dimensional account book data generation module. DETAILED DESCRIPTION

[0045] In order to more clearly illustrate the overall concept of the present application, a detailed description is given below in an illustrative manner in conjunction with the accompanying drawings.

[0046] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present application is not limited by the specific embodiments disclosed below. It should be noted that the embodiments of the present application and the features in each embodiment may be combined with each other without conflict.

[0047] In the present application, unless otherwise clearly specified and limited, a first feature "above" or "below" a second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in an appropriate manner in any one or more embodiments or examples.

[0048] like Figure 1 As shown, the first aspect of the present application provides a method for constructing a multi-dimensional account book of responsibility accounting, comprising:

[0049] Step 100: Build an internal data pool for responsibility accounting to achieve standardization of business data.

[0050] Step 200: Bookkeeping is performed based on the operating data in the responsibility accounting internal data pool to generate a basic account book.

[0051] Step 300: Set multi-dimensional account book rules.

[0052] Step 400: Process the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data.

[0053] In step 100, the internal data pool refers to a database or data warehouse used within an organization to collect, organize, store and manage various types of operating data. In the context of responsibility accounting, the role of the internal data pool is particularly critical because it involves the standardization of data processing of various cost centers, profit centers and other related accounting dimensions within the enterprise. The internal data pool integrates data from different sources, including but not limited to financial data, business data, internal settlement data, etc., which are converted and stored on a unified platform for subsequent analysis and processing. In the internal data pool, it is possible to identify accounting dimensions such as cost centers, profit centers, and other accounting dimensions and analysis dimensions that users are concerned about, such as departments, projects, WBS, channels, customers, products, etc. This information is crucial for building multi-dimensional ledgers. By building an internal data pool for responsibility accounting, enterprises can manage their internal financial data more efficiently and accurately.

[0054] In step 200, operating data refers to various financial and non-financial information generated by the enterprise during its daily operations. Specifically, the operating data in the responsibility accounting internal data pool usually includes:

[0055] Cost center / profit center data: This is the cost and revenue information of each department or business unit within the enterprise. They are the responsibility centers within the enterprise and are responsible for cost control and revenue generation in their respective areas.

[0056] Accounting dimensions: including but not limited to departments, projects, work breakdown structures (WBS), channels, customers, products, etc. These dimensions help enterprises collect and analyze costs and benefits at different management levels.

[0057] Internal settlement data: When business transactions occur between different cost centers or profit centers within an enterprise, internal settlement data will be generated. These data reflect the income, costs and expenses of internal transactions.

[0058] Other operating data: may include various financial data such as inventory, fixed assets, accounts receivable, accounts payable, as well as non-financial indicators such as production volume, sales volume, etc.

[0059] The basic account book is a data set that summarizes and records the business activities of an enterprise according to specific rules and time periods. It is formed by the business data in the internal data pool of responsibility accounting after accounting processing, and is mainly used as the basic data source for the subsequent construction of multi-dimensional account books. The basic account book can only record the beginning balance, the amount of this period, and the cumulative amount of this year, which not only reduces the amount of data, but also can quickly form the beginning and end data.

[0060] In step 300, the multi-dimensional account book rules are set to select appropriate accounting dimensions and set corresponding account book value conditions according to the needs of the enterprise when generating the multi-dimensional account book. This ensures that the generated multi-dimensional account book data meets the management needs of the enterprise and can provide more detailed and targeted financial information.

[0061] Setting up multi-dimensional account book rules mainly includes the following aspects:

[0062] Determine the accounting dimensions:

[0063] Accounting dimensions refer to the different dimensions used to classify and summarize data in the account book, such as department, project, work breakdown structure (WBS), channel, customer, product, etc. These dimensions help companies analyze financial data from multiple perspectives.

[0064] Define the conditions for obtaining the value of the account book:

[0065] The value conditions define the specific values ​​of each accounting dimension, which determines which data should be included in the multidimensional ledger and which data should be excluded. For example, you can set it to include only data within a specific time period, or only consider certain types of transactions.

[0066] By setting up multi-dimensional bookkeeping rules, enterprises can analyze and display financial data from multiple angles and levels, so that management can obtain more refined information. Multi-dimensional bookkeeping rules can be flexibly configured according to the actual situation of the enterprise, meet the different needs of different management levels, and provide customized financial statements.

[0067] In step 400, multi-dimensional ledger data refers to comprehensive financial information generated by multi-dimensional analysis and aggregation of basic ledger data under the responsibility accounting framework. This data can provide a detailed view of the company's financial status from multiple perspectives, helping management to better understand the company's operating conditions and performance. Multi-dimensional ledger data allows companies to view and analyze financial data from different dimensions (such as departments, projects, product lines, etc.). Each dimension can be analyzed independently or in combination, providing a rich perspective. The generation of multi-dimensional ledger data enables companies to fully understand their financial status from multiple perspectives and levels.

[0068] According to the method for constructing a multi-dimensional account book of responsibility accounting provided by the embodiment of the first aspect of the present application, first, an internal data pool of responsibility accounting is constructed to realize the standardization of operating data. This step aims to unify the business data of enterprises from different sources into a standard format to realize data standardization, which is not only conducive to data management and query, but also lays a good foundation for the subsequent construction of multi-dimensional account books. Standardized data can ensure that information of all dimensions is retained, thereby improving the quality and consistency of account book data; accounting is performed based on the operating data in the internal data pool of responsibility accounting to generate a basic account book. In this step, the basic account book can only record the beginning of the year and the current period. The three types of data, namely, the annual and annual cumulative data, can not only reduce the amount of data, but also quickly form the beginning and end data; setting multi-dimensional account book rules provides guiding principles for the next step of processing the data in the basic account book. The pre-set rules can automatically process a large amount of data, reduce the need for manual intervention, and improve work efficiency; finally, the data in the basic account book is processed based on the multi-dimensional account book rules to generate multi-dimensional account book data. In this step, irrelevant data is filtered out through rules, and only data related to the multi-dimensional account book is retained, and then aggregated as needed to make the data more centralized and useful. The generated multi-dimensional account book data can provide the enterprise management with a more detailed and comprehensive financial analysis perspective. In summary, the method for constructing a multi-dimensional account book of responsibility accounting provided in the first aspect of the embodiment of the present application can efficiently and accurately construct a multi-dimensional account book of responsibility accounting in the case where the frequency of changes in the organizational structure of the enterprise is high and there is an internal settlement scenario.

[0069] In some embodiments of the present application, building a responsibility accounting internal data pool includes:

[0070] Add the internal settlement documents maintained during internal settlement to the internal data pool of responsibility accounting, define the settlement parties as "cost center / profit center, counterparty cost center / counterparty profit center", and record the transaction information of the settlement parties.

[0071] Specifically, during the internal settlement process, it is necessary to create internal settlement documents to record relevant information about settlement activities. The information of these internal settlement documents is added to the internal data pool of responsibility accounting to ensure that the settlement data is managed and used together with other operating data. In the data pool, the settlement parties are defined as "cost center / profit center" and "counterparty cost center / counterparty profit center", which means that one party of the settlement is a cost center or profit center, and the other party is the corresponding counterparty cost center or counterparty profit center. The transaction information of the settlement parties is recorded in the data pool, including but not limited to the transaction amount, transaction date, transaction type and other related data.

[0072] By adding the information in the internal settlement document to the internal data pool of responsibility accounting, the integrity and accuracy of the internal settlement data are ensured. This can avoid omissions or erroneous records and ensure the reliability and authenticity of financial data. The information in the internal settlement document is added to the data pool in a standard format, which realizes the standardized management of data. This helps with subsequent data processing and analysis, ensuring that all data follows a unified format and standard. By defining the settlement parties as "cost center / profit center, counterparty cost center / counterparty profit center", internal settlement data can be quickly identified and processed, improving the efficiency of internal settlement. This enables enterprises to complete the internal settlement process faster and update financial data in a timely manner. Recording the transaction information of the settlement parties helps to trace and audit internal settlement activities in the future. When necessary, these records can be used for verification to ensure the compliance and transparency of internal settlement activities. The standardization and accurate recording of internal settlement data provides a reliable foundation for the subsequent construction of multi-dimensional ledgers. When generating multi-dimensional ledgers, internal settlement data can be accurately identified and processed to ensure the accuracy and integrity of multi-dimensional ledgers.

[0073] like Figure 2 As shown, in some embodiments of the present application, accounting is performed based on the operating data in the internal data pool of responsibility accounting to generate a basic account book, specifically:

[0074] When recording accounts, the original accounting dimensions are retained and the accounting period is determined based on the business date;

[0075] Summarize the current period's debits, current period's credits, current year's debit accumulation, and current year's credit accumulation based on the accounting period;

[0076] Define the data including "cost center / profit center, counterparty cost center / counterparty profit center" as internal settlement data;

[0077] Find the first common superior of "cost center / profit center, counterparty cost center / counterparty profit center" and generate the offset data of the common superior.

[0078] Specifically, during the accounting process, the original accounting dimensions are retained to ensure that the dimension information of all original data is not lost. The accounting period is determined according to the date on which the business occurs, that is, the data is classified into the corresponding accounting period according to the actual date of the business. Summarizing the current period's debit occurrence, current period's credit occurrence, current year's cumulative debit occurrence, and current year's cumulative credit occurrence based on the accounting period means that according to the determined accounting period, the current period's debit occurrence and credit occurrence are summarized, and at the same time, the cumulative debit occurrence and cumulative credit occurrence so far this year are summarized. For data entries that contain both cost centers / profit centers and counterparty cost centers / counterparty profit centers, they are defined as internal settlement data, which represent transactions between different cost centers or profit centers within the enterprise. Find the first common superior of the cost center / profit center and the other party's cost center / profit center, and generate the offsetting data (negative number) of the common superior to ensure that internal transactions are correctly processed in the account book to avoid repeated calculations or inflated revenues and costs. For example, if there is: Profit center - Workshop 1, other party's profit center - Workshop 2, element - internal expenditure, debit amount - 100; when recording, find the first common superior of Workshop 1 and Workshop 2, Branch Factory, and generate the corresponding offsetting data for Branch Factory as follows: Profit center - Branch Factory 1, element - internal expenditure, debit amount - (-100).

[0079] According to the actual date of the transaction, the data is classified into the corresponding accounting period. For example, if a transaction occurs in September 2024, then the transaction will be recorded in the books of September 2024. In the determined accounting period, summarize the debit and credit amounts of the current period, as well as the cumulative debit and credit amounts of the current year to date. For example, if multiple debit and credit transactions occurred during September 2024, the amounts of these transactions need to be summarized. Generate common superior offset data to ensure that internal transactions do not lead to false increase of revenue and costs. For example, if the common superior of cost center A and cost center B is a workshop, then the offset data of the workshop needs to be generated to offset the internal transactions between A and B.

[0080] Retaining the original accounting dimensions ensures the integrity and traceability of the data, which is helpful for subsequent data analysis and decision support. By determining the accounting period based on the business date, the accuracy and timeliness of financial records are ensured, avoiding errors caused by time mismatches. By identifying internal settlement data and generating corresponding offset data, internal transactions are avoided from being double-counted in the books, ensuring the accuracy of internal settlements. Accurate internal settlement processing provides management with reliable financial information.

[0081] like Figure 2 As shown, in some embodiments of the present application, a responsibility accounting internal data pool is constructed to achieve standardization of operating data, specifically:

[0082] Define standard data format parameters for responsibility accounting internal data pool;

[0083] Based on standard data format parameters, homogeneous and heterogeneous data in business data are converted to identify cost centers, profit centers, accounting dimensions, and analysis dimensions.

[0084] Specifically, the conversion tool allows you to flexibly configure conversion rules. Design a set of standard data format parameters, including but not limited to the structure of the data table, field naming rules, data types, encoding rules, etc. These parameters need to cover all necessary information for cost centers, profit centers, accounting dimensions (such as departments, projects, WBS, etc.) and analysis dimensions (such as channels, customers, products, etc.). For data with the same structure, you can directly convert it according to the defined standard data format parameters to ensure data consistency and readability. For data with different structures, mapping and conversion are required to make it conform to the standard format, which involves data cleaning, format adjustment, field mapping, etc., to ensure that all data conforms to unified standards when entering the internal data pool. During the conversion process, identify the cost center, profit center, accounting dimension (such as department, project, WBS, etc.) and analysis dimension (such as channel, customer, product, etc.), and store this information in the data pool for subsequent analysis and use.

[0085] By defining standard data format parameters and converting data, the standardization of operating data is achieved, ensuring that all data follows a unified format for subsequent processing and analysis. Standardized data is consistent, which can avoid errors and confusion caused by inconsistent data formats and improve data quality. Standardized data is easier to analyze, especially for data on cost centers, profit centers, accounting dimensions, and analysis dimensions, which can be more accurately summarized and compared. Through flexible and configurable data conversion rules, it can adapt to different types of data sources and ensure that the data pool can accommodate diverse corporate operating data. Standardized data formats enable data from different sources to be better integrated to form a unified data pool, which is convenient for subsequent multi-dimensional account book construction and management.

[0086] In some embodiments of the present application, the multidimensional account book rules include accounting dimensions and account book value conditions for each accounting dimension. Accounting dimensions refer to different dimensions used to classify and summarize data in multidimensional account books. These dimensions can help enterprises analyze and display financial data from multiple perspectives, usually including but not limited to departments, projects, work breakdown structures (WBS), channels, customers, products, etc. Account book value conditions refer to specific value conditions set for each accounting dimension when generating a multidimensional account book. These conditions define which data should be included in the multidimensional account book and which data should be excluded.

[0087] First, you need to determine the accounting dimensions that need to be focused on in the multi-dimensional account book. These dimensions should be the key dimensions for enterprises to manage and analyze financial data, such as departments, projects, products, etc. For each accounting dimension, set specific value conditions. These conditions may include but are not limited to:

[0088] Time range: Defines the time period of the data, such as only including data from a specific month or quarter.

[0089] Category restrictions: Define categories of data, such as only including certain types of transactions or items.

[0090] Other filter conditions: For example, only include data from a specific department or project.

[0091] Assume that an enterprise wants to generate a multidimensional ledger containing departments and projects. The specific steps are as follows:

[0092] Define accounting dimensions: Determine that the accounting dimensions that need to be focused on in multi-dimensional ledgers are "department" and "project".

[0093] Set the value conditions: For the "Department" dimension, set the value conditions to include only the data of the Sales Department and the Production Department. For the "Project" dimension, set the value conditions to include only the data of specific projects (such as Project A and Project B).

[0094] Through the above steps, enterprises can ensure that the generated multi-dimensional ledger data is screened and summarized, and can accurately reflect the financial status of the enterprise in a specific dimension.

[0095] like Figure 2 As shown, in some embodiments of the present application, the data in the basic account book is processed based on the multi-dimensional account book rules to generate multi-dimensional account book data, specifically:

[0096] Filter the data in the basic account book based on the value conditions in the multi-dimensional account book rules;

[0097] Summarize the filtered data according to the accounting dimensions.

[0098] Specifically, the data in the basic account book is filtered based on the value conditions in the multi-dimensional account book rules. This step involves filtering the data that meets the rules from the basic account book according to the value conditions in the multi-dimensional account book rules. The specific steps are as follows:

[0099] Define value conditions: Determine which data should be included and which data should be excluded based on the value conditions in the multi-dimensional account book rules.

[0100] Data filtering: Select data entries that meet the value conditions from the basic account book. For example, if the multi-dimensional account book rules stipulate that only data from a specific department or a specific time period is included, only the data that meets the conditions will be retained.

[0101] The filtered data is aggregated according to the accounting dimensions. After the data filtering is completed, the filtered data is aggregated according to the accounting dimensions defined in the multi-dimensional account book rules. The specific steps are as follows:

[0102] Define accounting dimensions: Determine the accounting dimensions that require attention in multidimensional ledgers, such as departments, projects, WBS, etc.

[0103] Data aggregation: Aggregate the filtered data according to these dimensions. For example, if there are multiple dimensions (such as department, project, WBS, etc.) in the basic account book, and the multi-dimensional account book only focuses on certain specific dimensions (such as project and WBS), then the data with the same dimensions will be merged and aggregated.

[0104] By setting the value conditions, you can ensure that only data related to the multi-dimensional ledger is retained, and irrelevant data is excluded, thereby improving the accuracy and relevance of the data. Aggregating the screened data according to the accounting dimensions can generate more refined financial information. Through automated processing, the workload of manual screening and aggregation is reduced, and the efficiency of generating multi-dimensional ledger data is improved. Ensure the accuracy and consistency of multi-dimensional ledger data, and avoid data redundancy and errors.

[0105] Assume that an enterprise wants to generate a multidimensional ledger, focusing on the dimensions of departments and projects, and only including data for this quarter. The specific steps are as follows:

[0106] Define the value conditions: only include data from this quarter, and only include data from the sales department and the production department.

[0107] Data filtering: Filter out the data for this quarter from the basic account book and only keep the data for the sales department and production department.

[0108] Define accounting dimensions: focus on the dimensions of departments and projects.

[0109] Data aggregation: Aggregate the filtered data by department and project. For example, aggregate the data of all sales departments and production departments under the same project.

[0110] In some embodiments of the present application, processing the data in the basic account book based on the multi-dimensional account book rule to generate the multi-dimensional account book data further includes:

[0111] Based on the enterprise organizational structure, summarize the data of each organizational node at the current level and its direct subordinates.

[0112] Specifically, this step ensures that when aggregating data, not only the data at each organizational node level is considered, but also the data of its direct subordinates. The specific steps are as follows:

[0113] Organizational structure identification: Identify the organizational structure of the enterprise, including organizational nodes at all levels (such as departments, workshops, subsidiaries, etc.).

[0114] Data aggregation: Starting from the lowest level organizational node, data is aggregated upwards level by level. The data of each node includes not only the data of the current level, but also the data of its immediate subordinates.

[0115] Bottom-up aggregation: Ensure that the data of each organizational node is complete, including the data of all direct subordinates. For example, if there is a department A, which has two direct subordinate departments B and C, then the aggregated data of department A will include the data of department A itself as well as the data of departments B and C.

[0116] Assume that the company has the following organizational structure: head office -> department A -> department B and department C.

[0117] Define the value conditions: only include data from this quarter, and only include data from the sales department and the production department.

[0118] Data filtering: Filter out the data for this quarter from the basic account book and only keep the data for the sales department and production department.

[0119] Define accounting dimensions: focus on the dimensions of departments and projects.

[0120] Data aggregation: Aggregate the filtered data by department and project dimensions.

[0121] Aggregation based on organizational structure: The data of the head office is summarized including the data of department A; the data of department A is summarized including the data of department B and department C; the data of department B and department C are summarized separately.

[0122] By aggregating the data of each organizational node based on the corporate organizational structure, we ensure that the data at each level is complete, including not only the data at this level, but also the data of its direct subordinates. This can avoid data omissions and ensure the comprehensiveness and accuracy of the data. Data aggregation based on the corporate organizational structure enables managers at each level to obtain complete financial information within their jurisdiction, so as to better understand and manage the financial status within their scope of responsibility. Through a bottom-up aggregation method, data traceability is ensured. The data of each organizational node can be traced, which is convenient for future audits and reviews. The generated multi-dimensional account book data supports multi-level analysis, which can not only view the overall financial status of the entire enterprise, but also go deep into specific levels such as various departments and workshops to provide detailed financial information.

[0123] In some embodiments of the present application, processing the data in the basic account book based on the multi-dimensional account book rule to generate the multi-dimensional account book data further includes:

[0124] Calculate the beginning and ending amounts based on the beginning of the year, the current period's occurrences, and the current year's cumulative occurrences to generate multi-dimensional ledger data.

[0125] Specifically, the beginning balance refers to the account balance at the beginning of the year, which is the basic starting point of multi-dimensional account book data. The current period's amount refers to the debit and credit amounts that occurred during the current accounting period, and these amounts need to be recorded based on actual business conditions. The cumulative amount for the year refers to the cumulative total of all debit and credit amounts from the beginning of the year to the end of the current accounting period. The beginning balance is usually calculated based on the ending balance of the previous period. For example, if the ending balance of the previous period is X, then the beginning balance of this period is also X. If there is no ending balance of the previous period, the beginning balance is equal to the beginning balance. The ending balance is calculated based on the beginning balance, the current period's amount, and the cumulative amount for the year. The specific calculation formula is as follows:

[0126] If the direction of the element balance is debit, then the ending amount = the beginning balance + the cumulative debit amount of this period - the cumulative credit amount of this period.

[0127] If the direction of the element balance is credit, then the ending amount = the beginning balance + the cumulative amount of credit in this period - the cumulative amount of debit in this period.

[0128] Assume that an enterprise wants to generate a multi-dimensional account book, focusing on the dimensions of departments and projects, and needs to calculate the beginning and ending amounts. The specific steps are as follows:

[0129] Define the value conditions: only include data from this quarter, and only include data from the sales department and the production department.

[0130] Data filtering: Filter out the data for this quarter from the basic account book and only keep the data for the sales department and production department.

[0131] Define accounting dimensions: focus on the dimensions of departments and projects.

[0132] Data aggregation: Aggregate the filtered data by department and project dimensions.

[0133] Aggregation based on organizational structure: Starting from the lowest organizational node, data is aggregated upwards level by level. The data of each node includes not only the data of the current level, but also the data of its direct subordinates.

[0134] Calculate the beginning and ending amounts:

[0135] Assume that the balance at the beginning of the year is RMB 1 million, the cumulative debit amount for this period is RMB 500,000, and the cumulative credit amount for this period is RMB 300,000.

[0136] The amount at the end of the period = the balance at the beginning of the year + the cumulative amount of debits in this period - the cumulative amount of credits in this period = 100 + 500,000 - 300,000 = 1.2 million yuan.

[0137] The beginning balance = the ending balance of the previous period = 1 million yuan (if there is no previous period, the beginning balance is equal to the balance at the beginning of the year).

[0138] By calculating the beginning and ending amounts, the integrity of the multi-dimensional ledger data is ensured. This makes the financial information more comprehensive. By calculating the beginning and ending amounts based on the beginning of the year, the current period, and the cumulative occurrence of the current year, the accuracy and consistency of the data are ensured. This avoids possible errors in manual calculations and improves the reliability of the data. The generated multi-dimensional ledger data not only provides detailed financial information, but also can show the financial status at each point in time. By calculating the beginning and ending amounts, the coherence and consistency of the financial data are ensured, which facilitates subsequent audit and review work.

[0139] In some embodiments of the present application, the method further comprises:

[0140] Transfer multi-dimensional account book data to a fixed version, and regenerate a new version of multi-dimensional account book data when the enterprise organizational structure changes;

[0141] Compare and analyze the fixed version of multi-dimensional account book data and the new version of multi-dimensional account book data.

[0142] After generating the multi-dimensional account book data, the current multi-dimensional account book data is transferred to a fixed version. This means that the existing account book data is saved in an unchangeable state for subsequent comparative analysis. When the corporate organizational structure changes, new multi-dimensional account book data needs to be regenerated based on the new organizational structure. This is because changes in the organizational structure will affect the determination of internal settlement and the way data is aggregated.

[0143] The currently generated multi-dimensional account book data is transferred to a fixed version to ensure that the data will not be modified in the future. The purpose of this is to be able to compare and analyze the account book data with the new version after the organizational structure changes to understand the impact of the organizational structure changes on the financial situation.

[0144] When the organizational structure of an enterprise changes, new multi-dimensional account book data needs to be regenerated. The specific steps are as follows:

[0145] Identify organizational changes: First, identify the specific changes in the organizational structure, including the addition, merger, or splitting of departments or units.

[0146] Update the internal data pool: Update the data in the responsibility accounting internal data pool according to the new organizational structure to ensure that the information in the data pool matches the new organizational structure.

[0147] Regenerate multi-dimensional ledger data: Based on the updated internal data pool, regenerate multi-dimensional ledger data according to the new organizational structure. This includes re-filtering data, summarizing, and calculating the beginning and ending amounts.

[0148] By comparing the fixed version of the multi-dimensional ledger data with the new version of the multi-dimensional ledger data, the company can understand the impact of organizational structure changes on the financial situation. This helps management better understand the effect of organizational structure adjustments.

[0149] Specific steps of comparative analysis:

[0150] Data preparation: Ensure that the fixed version and the new version of the multi-dimensional ledger data are comparable at the time point, that is, select the same time period for comparison.

[0151] Variance analysis: Compare two versions of data and find out where the differences are. This can include changes in revenue, costs, expenses, etc.

[0152] Impact assessment: Based on the results of the variance analysis, the impact of organizational changes on the financial situation is assessed. For example, if significant changes are found in the revenue or costs of certain departments, further analysis can be conducted to determine the reasons.

[0153] Decision support: Based on the results of comparative analysis, management can better understand the actual effects of organizational structure changes and adjust strategies or optimize resource allocation accordingly.

[0154] Transferring multi-dimensional account book data to a fixed version ensures data retention and traceability, providing a basis for subsequent audits and historical data analysis. By comparing and analyzing the fixed version and the new version of multi-dimensional account book data, companies can intuitively understand the specific impact of organizational structure adjustments on financial conditions. By conducting regular comparative analysis, companies can continuously optimize their organizational structures and ensure that financial data can truly reflect the company's operating conditions. The results of the comparative analysis can provide detailed data support for management.

[0155] like Figure 3 As shown, the second embodiment of the present application provides a device for constructing a multi-dimensional account book of responsibility accounting, including:

[0156] The data pool construction module 110 is suitable for constructing the internal data pool of responsibility accounting to achieve the standardization of operating data;

[0157] A basic account book generation module 120 is adapted to perform accounting based on the operating data in the responsibility accounting internal data pool to generate a basic account book;

[0158] A rule setting module 130, adapted to set multi-dimensional account book rules;

[0159] The multi-dimensional account book data generating module 140 is adapted to process the data in the basic account book based on the multi-dimensional account book rules to generate multi-dimensional account book data.

[0160] The device for constructing a multidimensional account book of responsibility accounting provided by the second aspect embodiment of the present application can implement the method for constructing a multidimensional account book of responsibility accounting in any embodiment of the first aspect above, and thus can achieve any technical effect of the method for constructing a multidimensional account book of responsibility accounting above, which will not be repeated here.

[0161] Anything not described in this application can be achieved by adopting or drawing on existing technologies.

[0162] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0163] The above is only the embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for constructing a multi-dimensional account book of responsibility accounting, characterized in that: include: Build an internal data pool for responsibility accounting to achieve standardization of business data; Bookkeeping is performed based on the operating data in the responsibility accounting internal data pool to generate a basic account book; Set up multi-dimensional ledger rules; Processing the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data; in, The construction of the responsibility accounting internal data pool includes: Add the internal settlement documents maintained during internal settlement to the responsibility accounting internal data pool, define the settlement parties as "cost center / profit center, counterparty cost center / counterparty profit center", and record the transaction information of the settlement parties; The accounting is performed based on the operating data in the responsibility accounting internal data pool to generate a basic account book, specifically: When recording accounts, the original accounting dimensions are retained and the accounting period is determined based on the business date; Summarize the current period's debits, current period's credits, current year's debit accumulations, and current year's credit accumulations based on the accounting period; The data including the "cost center / profit center, counterparty cost center / counterparty profit center" is defined as internal settlement data; Find the first common superior of the "cost center / profit center, counterparty cost center / counterparty profit center", and generate the offset data of the common superior; The construction of the internal data pool of responsibility accounting to achieve the standardization of business data is as follows: Define standard data format parameters of the responsibility accounting internal data pool; Based on the standard data format parameters, convert homogeneous data and heterogeneous data in the operating data to identify cost centers, profit centers, accounting dimensions, and analysis dimensions; The multi-dimensional account book rules include accounting dimensions and account book value conditions of each of the accounting dimensions; The processing of the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data is specifically: Filtering the data in the basic account book based on the value conditions in the multi-dimensional account book rules; The filtered data is aggregated according to the accounting dimensions.

2. The method for constructing a multi-dimensional account book of responsibility accounting according to claim 1, characterized in that: The step of processing the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data further includes: Based on the enterprise organizational structure, summarize the data of each organizational node at the current level and its direct subordinates.

3. The method for constructing a multi-dimensional account book of responsibility accounting according to claim 2, characterized in that: The step of processing the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data further includes: The beginning and ending amounts are calculated based on the beginning of the year, the occurrence of this period, and the cumulative occurrence of this year to generate the multi-dimensional account book data.

4. The method for constructing a multi-dimensional account book of responsibility accounting according to claim 1, characterized in that: The method also includes: The multi-dimensional account book data is transferred to a fixed version, and when the enterprise organizational structure changes, a new version of the multi-dimensional account book data is regenerated; Compare and analyze the fixed version of multi-dimensional account book data and the new version of multi-dimensional account book data.

5. A device for constructing a multi-dimensional account book of responsibility accounting, characterized in that: include: The data pool construction module is suitable for building the internal data pool of responsibility accounting to achieve the standardization of business data; A basic account book generation module, adapted to record accounts based on the operating data in the responsibility accounting internal data pool to generate a basic account book; The rule setting module is suitable for setting multi-dimensional account book rules; A multi-dimensional account book data generation module, adapted to process the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data; in, The construction of the responsibility accounting internal data pool includes: Add the internal settlement documents maintained during internal settlement to the responsibility accounting internal data pool, define the settlement parties as "cost center / profit center, counterparty cost center / counterparty profit center", and record the transaction information of the settlement parties; The accounting is performed based on the operating data in the responsibility accounting internal data pool to generate a basic account book, specifically: When recording accounts, the original accounting dimensions are retained and the accounting period is determined based on the business date; Summarize the current period's debits, current period's credits, current year's debit accumulations, and current year's credit accumulations based on the accounting period; The data including the "cost center / profit center, counterparty cost center / counterparty profit center" is defined as internal settlement data; Find the first common superior of the "cost center / profit center, counterparty cost center / counterparty profit center", and generate the offset data of the common superior; The construction of the internal data pool of responsibility accounting to achieve the standardization of business data is as follows: Define standard data format parameters of the responsibility accounting internal data pool; Based on the standard data format parameters, convert homogeneous data and heterogeneous data in the operating data to identify cost centers, profit centers, accounting dimensions, and analysis dimensions; The multi-dimensional account book rules include accounting dimensions and account book value conditions of each of the accounting dimensions; The processing of the data in the basic account book based on the multi-dimensional account book rule to generate multi-dimensional account book data is specifically: Filtering the data in the basic account book based on the value conditions in the multi-dimensional account book rules; The filtered data is aggregated according to the accounting dimensions.

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