A method and system applied to freight aviation cost accounting

Abstract

The application discloses a method and system applied to freight aviation cost accounting, obtains a plurality of service data by carrying out data preprocessing on main data and associated data of a to-be-processed freight flight; determines corresponding supplier agreement data based on a processing dimension corresponding to each piece of service data. Based on matched service data and supplier agreement data under the same processing dimension, an initial cost accrual calculation result is calculated. Then, a difference result between the initial cost accrual calculation result and supplier opening account data under a target granularity is calculated; the initial cost accrual calculation result is optimized according to the difference result, and a target cost accrual calculation result corresponding to the freight flight is obtained. The application can change the condition of relying on supplier opening account data for financial data management. In addition, the difference between the cost accrual calculation result and the supplier opening account data is audited, and further optimization is carried out, so that the accuracy of freight aviation cost accounting is improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and more specifically to a method and system for calculating costs in air freight. Background Technology

[0002] Cargo airlines primarily operate by providing cargo transportation, handling, and transshipment services. From cargo collection to final delivery to the consignee, the process is highly complex, utilizing aircraft as the main mode of transport, with ground handling services providing support. Costs throughout the transportation process revolve around flight operations. Compared to other transportation industries, air transport involves a greater variety of service providers and incurs more substantial costs. Cargo airlines require comprehensive and precise control over all cost expenditures to ensure smooth operation.

[0003] However, existing air cargo cost accounting mainly relies on supplier billing data, which has a certain lag and is prone to inaccurate air cargo cost accounting. Summary of the Invention

[0004] In view of the above, this application provides the following technical solution:

[0005] A method for calculating air freight costs includes:

[0006] Acquire the master data and associated data of the cargo flights to be processed, wherein the associated data includes at least fuel data, route data and ground service data;

[0007] The master data and associated data are preprocessed to obtain several service data items;

[0008] Based on the processing dimension corresponding to each of the service data, determine the supplier agreement data corresponding to the processing dimension;

[0009] Based on matching service data and supplier agreement data under the same processing dimension, the initial cost accrual calculation result is obtained;

[0010] The difference between the supplier billing at the target granularity and the initial cost accrual calculation result is calculated.

[0011] The initial cost accrual calculation result is optimized based on the difference results to obtain the target cost accrual calculation result.

[0012] Preferably, the difference between the supplier billing and initial cost accrual calculation results at the target granularity includes:

[0013] Upon receiving a bill audit instruction, the existing pre-audit results for the bill are deleted.

[0014] The billing details of the suppliers to be audited, as well as the master data, related data, and service data of the corresponding cargo flights for processing dimensions, are pre-audited to obtain the pre-audit results.

[0015] Based on the first pre-audit sub-result and the initial cost accrual calculation result, cost difference data at different levels of granularity are determined. The pre-audit result includes the first pre-audit sub-result and the second pre-audit sub-result. In the initial accrual calculation result, there is accrual calculation data corresponding to the first pre-audit sub-result, and in the initial accrual calculation result, there is no accrual calculation data corresponding to the second pre-audit sub-result.

[0016] From the cost difference data, extract the cost difference data corresponding to the first pre-audit sub-result of supplier billing under the target granularity, where the target granularity includes the smallest granularity among the current different levels of granularity;

[0017] Based on the cost difference data corresponding to the second pre-audit sub-result and the first pre-audit sub-result of supplier billing at the target granularity, the difference between supplier billing and the initial cost accrual calculation result is determined.

[0018] Preferably, the method further includes:

[0019] Collect target data, which includes general information, cargo aircraft information of cargo airlines, and information of suppliers providing services for cargo transportation;

[0020] Based on a specific data table format, the data sub-items corresponding to each target data are stored to obtain an initial data table, wherein the specific data table format includes sub-tables of target data of different types, and a data sub-item storage area corresponding to each sub-table;

[0021] The operation items of the initial data table are determined, and the initial data table is encapsulated based on the operation items to obtain the target data table, so that data can be queried based on the target data table to obtain the master data and related data corresponding to the cargo flight to be processed, as well as the supplier agreement data.

[0022] Preferably, the data preprocessing of the master data and associated data to obtain several service data items includes:

[0023] In response to the presence of unapproved flags in the master data and associated data, the master data and associated data are verified according to specific judgment logic;

[0024] The verified data is processed based on flight information to perform flight matching, data aggregation, and data completion, resulting in several service data entries.

[0025] Preferably, the processing dimension includes a flight dimension, wherein determining the supplier agreement data corresponding to the processing dimension based on the processing dimension corresponding to each piece of service data includes:

[0026] Determine the supplier agreement screening criteria corresponding to the flight dimension;

[0027] Obtain the basic rules for agreement fees that match the supplier agreement screening criteria;

[0028] Each of the aforementioned basic rules for fee calculation is matched, and the supplier agreement data of the successfully matched basic rules for fee calculation is obtained, so that the corresponding cost accrual sub-result under the flight dimension is calculated based on the supplier agreement data.

[0029] Preferably, the processing dimension includes a time dimension, wherein determining the supplier agreement data corresponding to the processing dimension based on the processing dimension corresponding to each service data item includes:

[0030] Obtain valid cargo processing data that matches the time dimension from each of the service data entries;

[0031] For each piece of valid cargo processing data, determine the matching protocol rules;

[0032] Based on the aforementioned agreement rules, the corresponding supplier agreement data is determined so that, based on the supplier agreement data and the valid cargo processing data, the cost accrual sub-result corresponding to the flight cargo processing data can be calculated.

[0033] Preferably, the calculation of the initial cost accrual result based on matching service data and supplier agreement data under the same processing dimension includes:

[0034] Based on the matching service data and supplier agreement data under the same processing dimension, determine the cost accrual sub-results that match each processing dimension;

[0035] Based on different aggregation granularities, the cost accrual sub-results are aggregated to obtain the initial cost accrual calculation results.

[0036] Preferably, the difference between the supplier billing and initial cost accrual calculation results at the target granularity includes:

[0037] Based on the supplier's billing and the calculation results of the initial cost accrual, cost difference data at different levels of granularity are determined;

[0038] From the cost difference data, extract the difference results between supplier billing and cost accrual at the target granularity, where the target granularity includes the smallest granularity among the current different levels of granularity.

[0039] A system for calculating air freight costs includes:

[0040] The data acquisition unit is used to acquire the master data and related data of the cargo flight to be processed. The related data includes at least aviation fuel data, route data and ground service data.

[0041] The data preprocessing unit is used to preprocess the master data and related data to obtain several service data items.

[0042] The protocol data acquisition unit is used to determine the supplier protocol data corresponding to the processing dimension based on the processing dimension corresponding to each piece of service data.

[0043] The cost calculation unit is used to calculate the initial cost accrual result based on matching service data and supplier agreement data under the same processing dimension.

[0044] The difference calculation unit is used to calculate the difference between the supplier's billing at the target granularity and the initial cost accrual calculation result;

[0045] The target cost acquisition unit is used to optimize the initial cost accrual calculation result based on the difference result to obtain the target cost accrual calculation result.

[0046] An electronic device, comprising a processor and a memory;

[0047] The processor is used to execute programs stored in the memory;

[0048] The memory is used to store a program that implements the steps of a method for calculating air freight costs as described above.

[0049] A storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for calculating air freight costs as described in any of the preceding claims.

[0050] As can be seen from the above technical solution, this application discloses a method and system for cargo air freight cost accounting. By preprocessing the master data and related data of the cargo flight to be accounted for, several service data points corresponding to the cargo flight are obtained. Since each service data point corresponds to a different processing dimension, supplier agreement data corresponding to that processing dimension is determined based on that processing dimension. Based on the matching service data and supplier agreement data under the same dimension, an initial cost accrual calculation result is calculated. Then, the difference between the initial cost accrual calculation result and the supplier billing at the target granularity is calculated. The initial cost accrual calculation result is optimized based on the difference result to obtain the target cost accrual calculation result corresponding to the cargo flight.

[0051] This application pre-calculates cargo flight costs through supplier agreements, changing the reliance on supplier billing data for financial data management. Furthermore, it audits discrepancies between the calculated cost accrual results and the supplier's billing data, using the audit findings to further optimize the cost accrual calculations and improve the accuracy of cargo aviation cost accounting. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0053] Figure 1 A flowchart illustrating a method for calculating air freight costs, provided as an embodiment of this application;

[0054] Figure 2 A schematic diagram of the structure of a system for calculating air freight costs provided in this application embodiment;

[0055] Figure 3 This is a schematic diagram of the structure of an electronic device used for cargo air freight cost accounting, provided as an embodiment of this application. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] See Figure 1 It illustrates a flowchart of a method for calculating air freight costs according to an embodiment of this application, which may include:

[0058] Step S110: Obtain the master data and related data of the cargo flights to be processed.

[0059] The master data and associated data corresponding to the cargo flights for which costs are to be calculated can be obtained from the cargo airline's data management system. The master data mainly includes basic information such as transport order number, flight type, flight load, and aircraft registration number. The associated information may include fuel data, route data, and ground service data.

[0060] The fuel data corresponds to the fuel cost incurred during cargo transportation, while the route data corresponds to the route cost. This route data can be determined by obtaining the navigation data of the actual cargo flight. However, if navigation data is unavailable or outdated, the flight route information preset by the data management system can be used as the actual flight route data for subsequent route cost calculations. If there is a delay in updating the actual route data, the corresponding preset route data can be queried, updated to reflect the actual route data, and the route cost can be recalculated. Therefore, the master data and related data of the cargo flights to be processed can be queried, modified, and deleted during the processing to ensure the accuracy of the data for the cargo flights.

[0061] Step S120: Perform data preprocessing on the master data and associated data to obtain several service data entries.

[0062] Specifically, data preprocessing is used to classify data in master data and related data to obtain service data that is easy to calculate according to service type.

[0063] For example, based on flight departure and arrival times, aircraft numbers, landing and departure flights from the same airport can be paired, parking times can be calculated, and these data can be summarized into the flight service data of the service data, facilitating the subsequent calculation of related fees. Alternatively, based on the ground service data of cargo flights, the data can be classified according to the service type or the provider of the ground service to obtain multiple service data entries.

[0064] Step S130: Based on the processing dimension corresponding to each service data, determine the supplier agreement data corresponding to the processing dimension.

[0065] Step S140: Based on the matching service data and supplier agreement data under the same processing dimension, calculate the initial cost accrual calculation result.

[0066] Specifically, based on the processing dimension corresponding to each piece of service data, the supplier agreement data corresponding to that processing dimension is determined. The processing dimension described in this embodiment can divide all service data into dimensions. For example, when the processing dimension represents time, the service data can be divided according to time. If this embodiment requires calculating data within the previous month, the service data that can be calculated is determined based on the processing dimension corresponding to each piece of service data. Alternatively, if the processing dimension represents a service type, the service data can be divided according to the service type to determine the service agreement corresponding to the service data under that processing dimension. In practical application scenarios, the processing dimension is not limited to the two mentioned above, and no single limitation is made in this step.

[0067] Additionally, the supplier agreement data can be stored in the cargo airline's data management system. When matching the service data with supplier agreements, the matching can be performed based on specific supplier agreement filtering criteria. The data management system stores all supplier agreements, and agreements with identical content may correspond to different suppliers. Therefore, the filtering order or criteria need to be clearly defined during matching. For example, the supplier providing the service in the current service data can be identified first, and then the supplier agreement for that supplier can be determined from the data management system. If a supplier has multiple supplier agreements, the service data can be matched again according to service type to determine the supplier agreement that corresponds to the price calculation, ensuring the accuracy of the final calculated cost.

[0068] When calculating costs, service data under the same processing dimension and the corresponding supplier agreement data are calculated. The calculation results corresponding to all service data are further processed to obtain the initial cost accrual calculation results corresponding to the cargo aviation to be processed.

[0069] Step S150: Calculate the difference between the supplier billing at the target granularity and the initial cost accrual calculation result.

[0070] To ensure the accuracy of the initial cost accrual calculation results, this embodiment compares the initial cost accrual calculation results with the supplier billing information to determine whether there are differences at different granular levels. The differences are then compared between the supplier billing at the target granularity and the corresponding initial cost accrual calculation results. Specifically, supplier billing can be checked against each piece of service data one by one to identify discrepancies and their corresponding cost accrual calculation results, thus determining the discrepancies. It should be noted that the differences between supplier billing and the initial cost accrual calculation results in this embodiment represent the differences between the two. These differences can include the discrepancies between the pre-approval data corresponding to the supplier billing and its corresponding initial cost accrual calculation results, as well as related costs and expenses included in the supplier billing data but not calculated or considered in the initial accrual calculation process. These will be explained in detail in subsequent embodiments.

[0071] Step S160: Optimize the initial cost accrual calculation results based on the difference results to obtain the target cost accrual calculation results.

[0072] Based on the aforementioned discrepancy results, the initial cost accrual calculation results are optimized to obtain the target cost accrual calculation results. Optimization can involve modifying the data in the initial cost accrual calculation results that differ from the actual discrepancy results to achieve the same processing result as the invoice data provided by the supplier. Alternatively, the initial cost accrual calculation process can be optimized based on the discrepancy results. For example, if the discrepancy analysis indicates a mismatch in the supplier agreement, the cost accrual calculation result can be optimized by optimizing the agreement matching process. Furthermore, it can involve adding expense items included in the supplier's invoice data obtained after auditing the supplier's invoice data, but not included in the initial cost accrual calculation process, to complete the optimization of the initial cost accrual calculation results. Specifically, the optimization of the initial cost accrual calculation results can be analyzed based on the substantive data content included in the actual discrepancy results.

[0073] This embodiment of the application preprocesses the master data and associated data of the cargo flight to be processed, obtaining several service data corresponding to the cargo flight. Since each service data corresponds to a different processing dimension, supplier agreement data corresponding to the processing dimension is determined based on the processing dimension of each service data. Based on the matching service data and supplier agreement data under the same dimension, the initial cost accrual calculation result is calculated. Then, the difference between the initial cost accrual calculation result and the supplier billing at the target granularity is calculated; the initial cost accrual calculation result is optimized based on the difference result to obtain the target cost accrual calculation result corresponding to the cargo flight.

[0074] This application embodiment calculates cargo flight cost data in advance through supplier agreements, changing the reliance on supplier billing data for financial data management and providing a relatively quicker cost accrual calculation result. Furthermore, it audits the discrepancies between the calculated cost accrual result and the supplier's billing data, further optimizing the cost accrual calculation based on the audit results, thereby improving the accuracy of cargo air freight cost accounting.

[0075] Next, this application will further describe the method applied to cargo air freight cost accounting.

[0076] The implementation basis of this application embodiment is a data management module or data management system that stores data on all cargo flights, suppliers, supplier agreements, etc., so that relevant data can be matched and retrieved through the data management system, and further calculated and audited. Specifically, the steps to create a data management system may include:

[0077] Collect target data, which may include general information, cargo aircraft information under cargo airlines, and supplier information for cargo transportation services. Store the data sub-items corresponding to each target data item based on a specific data table format to obtain an initial data table. The specific data table format includes sub-tables for different types of target data and storage areas for data sub-items corresponding to each sub-table. Determine the operation items for the initial data table and encapsulate it based on the operation items to obtain a target data table. This allows for data querying based on the target data table to obtain master data and related data corresponding to the cargo flights to be processed, as well as supplier agreement data.

[0078] Different types of target data correspond to different data table formats. Each data table format includes sub-tables that categorize the data items within the target data. All collected target data is categorized and stored according to the data table format to obtain the initial data table. Each data category's corresponding data table can be stored using a specific data table name to facilitate quick and accurate data retrieval later. Data types can be categorized according to the various executing entities in cargo transportation, resulting in corresponding classification data tables. For example, data can be divided into data corresponding to cargo transport flights and the service providers for those flights, stored according to specific data table formats. Further, the data items within the cargo transport flight data are categorized and stored, resulting in multiple sub-tables for each data table. For instance, each cargo transport flight data can be categorized into data items such as flight type, flight time, route data, fuel data, cargo handling, cargo order number, service content, service time, and the corresponding service provider. After categorization, the specific numerical data is then associated with the corresponding data name to obtain the initial data table. Supplier-related data can be first categorized into data tables by supplier, and then supplier agreement data under the same supplier can be stored as sub-tables.

[0079] The initial data table and its sub-tables classify and store the collected target data. However, for data with high real-time requirements, such as supplier agreements, aviation fuel data, route data, and service data, there may be operations that need to be modified or deleted. In this case, operation items need to be created in the initial data table and its sub-tables. The data corresponding to the operation items can be stored and displayed in a linked manner so that it is clear that operations such as querying, modifying, and deleting can be performed.

[0080] Based on the above classification and storage of target data, a target data table is obtained. Data can be queried from the data table according to the data items to obtain the master data, related data and corresponding supplier agreements of the cargo flights to be processed, and then cost calculation is performed based on the above data.

[0081] First, before cost calculation, the master data and associated data need to be preprocessed to obtain several service data entries. Specifically, in response to the presence of unverified flags in the master data and associated data, the master data and associated data are verified according to specific judgment logic to obtain verified data. The verified data is then processed based on flight information for flight pairing, data aggregation, and data completion to obtain several service data entries.

[0082] Before processing cargo flight data, its status needs to be verified to prevent duplicate calculations and inaccurate final cost results. Specifically, data marked as "unverified" is identified as target calculation data and further validated. During data collection and storage, data requiring calculation is marked with a calculation identifier. When retrieving valid calculation data later, data with the calculation identifier is directly extracted for cost calculation, improving efficiency and reducing invalid calculations in the cost calculation process.

[0083] Data marked with an unverified flag is further validated. Precise judgment logic is set for flight operation data in master data and related data, including but not limited to judgment of flight validity and judgment of information such as flight nature, special vehicle use, aircraft type, outbound and return trips. This enables the data system to perform self-checks on cargo flight data and ensures the accuracy of the cargo flight data information to be processed.

[0084] Furthermore, the verified data undergoes flight pairing, data aggregation, and data completion processing based on flight information to obtain several service data entries. Specifically, based on flight information such as departure time, arrival time, and aircraft number in the verified master data and associated data, landing and departure flights at the same airport are paired, and parking time is calculated to facilitate the calculation of related fees. The master data and associated data for cargo flights include service data. Based on parameters such as flight date, flight number, aircraft number, and aircraft type, flights to which service data is not yet determined are searched in the data management system, and the corresponding service data is aggregated to those flights so that the fee calculation process can include the service data aggregating to those flights. Additionally, after pairing and aggregating the above cargo flight data, there may still be missing data or service items, or data that has not been mentioned, leading to omissions in cost calculation. In such cases, it is necessary to pair and search the above cargo flight data entry by entry, and then fill in the missing data into the service data.

[0085] After the above process, several service data points can be obtained for each cargo flight to be processed. These service data points may include service type and service value data. The service value data is then assigned to the service type according to the service type list, so that the supplier agreement can be matched with the service type and the service value data corresponding to the service type can be calculated.

[0086] Furthermore, based on the processing dimension corresponding to each piece of service data, a supplier agreement corresponding to that processing dimension is determined. The processing dimension may include at least a flight dimension and a time dimension. Different processing dimensions have different screening criteria for supplier agreements, resulting in different final cost calculation results.

[0087] When the processing dimension corresponding to the service data is the time dimension, since cargo handling fees are usually calculated once within a specified period, a time dimension can be set to perform a calculation on the service data corresponding to cargo flights within this time range. First, obtain valid cargo handling data that matches the time dimension. Second, for each valid cargo handling data, determine the matching agreement rules. Based on the agreement rules, determine the corresponding supplier agreement data so that, based on the supplier agreement data and the valid cargo handling data, calculate the cost accrual sub-result corresponding to the flight cargo handling. For example, based on the price in the agreement and the cargo handling data (including weight or number of services), calculate the fee, which can be used as the cost accrual result.

[0088] When the processing dimension corresponding to service data is the flight dimension, cost calculation is performed at the flight level. For a single piece of service data, the supplier agreement screening criteria corresponding to the flight dimension are first determined. Different supplier agreement screening criteria have matching basic rules, which may include factors such as agreement effective time, whether it can be used for accrual, the service type corresponding to the agreement (service type), whether the agreement type is a general agreement or the agreement occurrence location is consistent with the flight occurrence location, etc., to ensure the correctness and calculability of the supplier agreements obtained by matching flight information at this processing dimension.

[0089] During the supplier agreement matching process, a single service data point may match multiple supplier agreements within the same dimension. In such cases, it's necessary to further prioritize these agreements. This can be achieved by counting the number of criteria each supplier agreement meets, with the agreement meeting the most criteria having higher priority. If multiple agreements have the same number of criteria, their effective dates are used to determine priority, with later effective dates resulting in higher priority. Based on this prioritization, each service type in the service data is guaranteed to have a unique corresponding supplier agreement.

[0090] The supplier agreement includes pricing rules for various service types. Based on the service type and service value data in each service data entry, calculations are performed to obtain the corresponding cost accrual sub-result for each service data entry. Then, the cost accrual sub-results calculated from the matching service data and supplier agreement data under the same processing dimension are combined to obtain the initial cost accrual calculation result for the cargo flight to be processed.

[0091] To ensure the accuracy of the final cost accrual calculation results, this embodiment of the application reviews the initial cost accrual calculation results, calculates the difference between the supplier billing at the target granularity and the initial cost accrual calculation results, and optimizes the initial cost accrual calculation results based on the difference results to obtain the target cost accrual calculation results. The target granularity can mainly include service type, supplier, cost accrual calculation results, and time range. Specifically, the initial cost accrual calculation results and supplier billing data can be matched based on flight number, flight date, service type, supplier, and location information to obtain the finest granularity of flight cost difference data.

[0092] Furthermore, in one embodiment of this application, the difference between the supplier billing and initial cost accrual calculation results at the target granularity includes:

[0093] Upon receiving a bill audit instruction, the existing pre-audit results for the bill are deleted.

[0094] The billing details of the suppliers to be audited, as well as the master data, related data, and service data of the corresponding cargo flights for processing dimensions, are pre-audited to obtain the pre-audit results.

[0095] Based on the first pre-audit sub-result and the initial cost accrual calculation result, cost difference data at different levels of granularity are determined. The pre-audit result includes the first pre-audit sub-result and the second pre-audit sub-result. In the initial accrual calculation result, there is accrual calculation data corresponding to the first pre-audit sub-result, and in the initial accrual calculation result, there is no accrual calculation data corresponding to the second pre-audit sub-result.

[0096] From the cost difference data, extract the cost difference data corresponding to the first pre-audit sub-result of supplier billing under the target granularity, where the target granularity includes the smallest granularity among the current different levels of granularity;

[0097] Based on the cost difference data corresponding to the second pre-audit sub-result and the first pre-audit sub-result of supplier billing at the target granularity, the difference between supplier billing and the initial cost accrual calculation result is determined.

[0098] Specifically, since each cargo flight review is conducted under different processing dimensions and target granularities, it is necessary to delete the existing pre-review results of invoices and the corresponding review data before conducting the review. After deletion, the invoice details of the supplier's invoice to be reviewed (i.e., the invoice details of the supplier's billing) as well as the flight master data, related data, and service data of the corresponding processing dimensions are pre-reviewed to obtain the pre-review results.

[0099] During the review of supplier billing data, the data also records detailed billing information for each supplier's next flight and expense items. Different granularities can be used to pre-review the supplier billing data, yielding preliminary review results. The purpose of this preliminary review is to obtain accurate supplier billing data. Then, the preliminary review results are compared with the current initial cost accrual calculation results. This comparison includes two dimensions of preliminary review sub-results: a first preliminary review sub-result and a second preliminary review sub-result. The initial cost accrual calculation results contain accrual calculation data corresponding to the first preliminary review sub-result, but do not contain accrual calculation data corresponding to the second preliminary review sub-result. Since the first preliminary review sub-result has a corresponding initial cost accrual calculation result, the difference between the two can be directly calculated. However, the second preliminary review sub-result does not have a corresponding initial cost accrual calculation result, meaning that the expense items corresponding to the second preliminary review sub-result may not have been considered in the cost accrual calculation process. Therefore, this portion of the expense corresponding to the second preliminary review sub-result needs to be included in the final target cost accrual calculation result. In this embodiment, based on the cost difference data corresponding to the second pre-audit sub-result and the first pre-audit sub-result of supplier billing at the target granularity, the difference between supplier billing and the initial cost accrual calculation result is determined. This allows for the addition of data on dimensions of costs that were not calculated or considered but actually incurred during the correction of the initial accrual calculation result, making the final cost accrual calculation result more accurate.

[0100] It should be noted that the initial cost accrual calculation can be performed according to different calculation dimensions. Therefore, when matching the pre-audit results corresponding to supplier invoicing with the initial cost accrual calculation results, matching can also be performed according to this dimension. Furthermore, matching can be performed at a finer granularity under the corresponding dimension, such as matching according to the target granularity. Similarly, the optimization process based on discrepancies can also be processed according to the corresponding dimension or target granularity. In practical application scenarios, this optimization process can also be referred to as cleanup and carry-forward in some application scenarios.

[0101] For example, cost accrual data, supplier billing data, and clearing and carry-over data can be matched based on flight number, flight date, expense item, supplier, and location information to obtain the most granular flight-level cost variance data. Furthermore, different granular cost variance data can be obtained by summarizing the flight-level cost variance data. The summarization granularity mainly includes: expense category, supplier, expense item, and time range. Specifically, expense category-level summarization is based on the actual year the expense occurred and the expense category, obtaining all expenses within the year and summarizing them according to different expense categories. For cost accrual data and supplier billing data, the actual expense date is usually based on the flight date, and expense categories can be obtained from the accrual details and billing details. Expense categories are mainly divided into eight categories: fuel costs, ground service fees, takeoff and landing parking fees, en-route fees, approach control fees, civil aviation construction fund, aircraft maintenance fees, and meal fees. Supplier-level summarization is based on expense category-level expense summarization and can further obtain the expense summarization for each supplier under a specific expense category in a specific year. By using year and expense category as search criteria and summarizing data by supplier code, the system clearly identifies the supplier's cost accrual amount, supplier billing amount, clearing and carry-forward amount, and any discrepancies. Expense item-level summaries build upon supplier-level expense summaries, allowing for further viewing of detailed expense item-level summaries. This fine-grained expense summary clarifies the cost accrual and supplier billing status of expense items under a specific expense category in a given month, and summarizes the clearing and carry-forward amount at the expense item level. Based on year, expense category, and supplier code, corresponding detailed accrual expense data and supplier billing details can be obtained. By summarizing data within the expense occurrence period, the final cost accrual amount and supplier billing amount are obtained. The expense occurrence period refers to the first day of the month and the last day of the month in which the expense actually occurred. Through these fine-grained summaries, the system clearly demonstrates the discrepancy between the initial cost accrual results and the actual supplier billing data, accurately pinpointing the source of the discrepancy. This facilitates analysis and clearing of discrepancies by financial personnel to obtain the target cost accrual calculation result. Finance personnel can use the expense clearing and carry-forward function to clear the discrepancies between cost accruals and supplier billing, and optimize cost estimation results in a timely manner, which will improve the accuracy of cost accounting.

[0102] In addition, embodiments of this application can also generate flight cost difference data using a view approach. This involves comparing a data table generated from the initial cost accrual calculation results with a cost billing data table corresponding to the supplier's billing data to obtain a cost difference data view. If the initial cost accrual calculation results or the supplier's billing data change, the cost difference data view can respond in real-time to updates to the different data, providing a more accurate and real-time display of the cost difference data.

[0103] Based on the aforementioned discrepancy data, and taking supplier billing data as the standard, the initial cost accrual calculation results are optimized. This optimization may involve modifying the sub-cost accrual calculation results that contain discrepancies in the initial cost accrual calculation results, or analyzing the discrepancies to optimize the steps in obtaining the initial cost accrual calculation results. Alternatively, supplier billing data not included in the initial cost accrual calculation results may be added to achieve the goal of optimizing the initial cost accrual calculation results and ultimately obtaining the target cost accrual calculation results used for financial management.

[0104] This application embodiment systematically stores and manages master data and related data of cargo flights, as well as supplier information and service agreements related to suppliers. By matching cargo flight data with supplier agreements based on different processing dimensions, it obtains supplier agreements that have calculation conditions with the cargo flight service data. Cost accrual calculations are then performed based on the provisions of the supplier agreements, yielding initial cost accrual calculation results for the cargo flights under the corresponding processing dimensions. This eliminates reliance solely on supplier invoices for cost data, enabling more convenient and timely access to financial data for further business planning. Furthermore, to ensure the accuracy of the initial cost accrual calculation results in subsequent applications, the differences between supplier invoices and the initial cost accrual calculation results are compared. The differences obtained from the comparison are used to further optimize the initial cost accrual calculation results, resulting in more accurate target cost accrual calculation results.

[0105] Below is a practical application example of the method for cost accounting in air cargo provided in this application. Air cargo airlines mainly provide cargo transportation, handling, and transshipment services. From the receipt of goods to the final delivery of goods to the consignee, a complex process is required. During this process, air and ground services provided by one or more suppliers are generated, and cargo costs are incurred based on these services. Businesses need to keep track of the ratio of cost expenditures to revenue in a timely manner. However, in actual cost accounting, there is a certain difference in the time of acquisition between the cost invoices provided by suppliers and the revenue data of the same period. This requires air cargo airlines to use a data management system to process the data and obtain the cost accrual calculation results at the same time dimension, so as to facilitate management with the revenue data of the same period and further make decisions on business planning, etc.

[0106] Cargo airlines need to structure their enterprise data management system, classifying and storing information such as flight data, suppliers, and supplier service agreements to improve the system's orderliness and facilitate subsequent cost accounting. Additionally, acquiring data for cargo flights requiring cost accounting involves obtaining operational data during the cargo transport process for each flight based on cargo orders. This operational data is then preprocessed to obtain several service data entries corresponding to each cargo flight. These service data are then matched against corresponding supplier agreement data within their respective processing dimensions. The pricing rules specified in the supplier agreement data are used to calculate and record the cost accrual sub-results for each service data entry for each cargo flight, generating an initial invoice containing the cost accrual sub-results for each service data entry for each cargo flight. This initial invoice also stores the sum of all cost accrual sub-results, i.e., the initial cost accrual calculation result.

[0107] In addition, cargo airlines can refer to cost invoices provided by suppliers when calculating costs, and compare these cost invoices with the initial cost accrual calculation results based on data at different target granularities to obtain discrepancy data. This discrepancy data can include differences in the cost accrual calculation sub-results for the same service data, differences in supplier agreement data for the same service data, and supplier billing data not included in the initial cost accrual calculation results. Based on this discrepancy data, optimization and modifications can be made to obtain more accurate target cost accrual calculation results.

[0108] The system for cargo aviation cost accounting provided in the embodiments of this application is described below. The system for cargo aviation cost accounting described below can be referred to in correspondence with the method for cargo aviation cost accounting described above.

[0109] like Figure 2 As shown in the figure, this application provides a schematic diagram of a system for calculating air freight costs. The device may include:

[0110] The data acquisition unit 100 is used to acquire the master data and related data of the cargo flight to be processed. The related data includes at least aviation fuel data, route data and ground service data.

[0111] Data preprocessing unit 200 is used to preprocess the master data and associated data to obtain several service data items;

[0112] The protocol data acquisition unit 300 is used to determine the supplier protocol data corresponding to the processing dimension based on the processing dimension corresponding to each piece of service data;

[0113] Cost calculation unit 400 is used to calculate the initial cost accrual calculation result based on matching service data and supplier agreement data under the same processing dimension.

[0114] The difference calculation unit 500 is used to calculate the difference between the supplier's billing at the target granularity and the initial cost accrual calculation result.

[0115] The target cost acquisition unit 600 is used to optimize the initial cost accrual calculation result based on the difference result to obtain the target cost accrual calculation result.

[0116] This embodiment of the application preprocesses the master data and associated data of the cargo flight to be processed, obtaining several service data corresponding to the cargo flight. Since each service data corresponds to a different processing dimension, supplier agreement data corresponding to the processing dimension is determined based on the processing dimension of each service data. Based on the matching service data and supplier agreement data under the same dimension, the initial cost accrual calculation result is calculated. Then, the difference between the initial cost accrual calculation result and the supplier billing at the target granularity is calculated; the initial cost accrual calculation result is optimized based on the difference result to obtain the target cost accrual calculation result corresponding to the cargo flight.

[0117] This application embodiment calculates cargo flight cost data in advance through supplier agreements, changing the reliance on supplier billing data for financial data management and providing a relatively quicker cost accrual calculation result. Furthermore, it audits the discrepancies between the calculated cost accrual result and the supplier's billing data, further optimizing the cost accrual calculation based on the audit results, thereby improving the accuracy of cargo air freight cost accounting.

[0118] Preferably, the difference calculation unit is specifically used for:

[0119] Upon receiving a bill audit instruction, the existing pre-audit results for the bill are deleted.

[0120] The billing details of the suppliers to be audited, as well as the master data, related data, and service data of the corresponding cargo flights for processing dimensions, are pre-audited to obtain the pre-audit results.

[0121] Based on the first pre-audit sub-result and the initial cost accrual calculation result, cost difference data at different levels of granularity are determined. The pre-audit result includes the first pre-audit sub-result and the second pre-audit sub-result. In the initial accrual calculation result, there is accrual calculation data corresponding to the first pre-audit sub-result, and in the initial accrual calculation result, there is no accrual calculation data corresponding to the second pre-audit sub-result.

[0122] From the cost difference data, extract the cost difference data corresponding to the first pre-audit sub-result of supplier billing under the target granularity, where the target granularity includes the smallest granularity among the current different levels of granularity;

[0123] Based on the cost difference data corresponding to the second pre-audit sub-result and the first pre-audit sub-result of supplier billing at the target granularity, the difference between supplier billing and the initial cost accrual calculation result is determined.

[0124] Preferably, the device further includes:

[0125] The target data acquisition unit is used to collect target data, which includes general information, cargo aircraft information of cargo airlines, and supplier information for providing services for cargo transportation.

[0126] A data storage unit is used to store data sub-items corresponding to each target data according to a specific data table format to obtain an initial data table, wherein the specific data table format includes sub-tables of target data of different types, and a data sub-item storage area corresponding to each sub-table;

[0127] The target data table acquisition unit is used to determine the operation items of the initial data table and encapsulate the initial data table based on the operation items to obtain the target data table, so that data query can be performed based on the target data table to obtain the master data and related data corresponding to the cargo flight to be processed, as well as the supplier agreement data.

[0128] Preferably, the data preprocessing unit 200 includes:

[0129] The data verification subunit is used to verify the main data and related data according to specific judgment logic in response to the presence of unverified tags in the main data and related data.

[0130] The service data acquisition subunit is used to perform flight matching, data aggregation, and data completion processing on the verified data based on flight information to obtain several service data entries.

[0131] Preferably, the processing dimension includes a flight dimension, wherein the protocol data acquisition unit 300 includes:

[0132] The protocol filtering subunit is used to determine the supplier protocol filtering conditions corresponding to the flight dimension;

[0133] The protocol rule acquisition subunit is used to obtain the basic protocol fee rules that match the supplier protocol screening criteria;

[0134] The first sub-unit for obtaining supplier agreement data is used to match each of the aforementioned agreement fee basic rules and obtain the supplier agreement data of the successfully matched agreement fee basic rules, so as to calculate the corresponding cost accrual sub-result under the flight dimension based on the supplier agreement data.

[0135] Preferably, the processing dimension includes a time dimension, wherein determining the supplier agreement data corresponding to the processing dimension based on the processing dimension corresponding to each service data item includes:

[0136] The effective data acquisition subunit is used to acquire effective cargo processing data that matches the time dimension in each piece of service data.

[0137] The protocol rule determination subunit is used to determine the matching protocol rule for each piece of valid cargo processing data.

[0138] The second sub-unit for acquiring supplier agreement data is used to determine the corresponding supplier agreement data based on the agreement rules, so as to calculate the cost accrual sub-result corresponding to flight cargo processing based on the supplier agreement data and the valid cargo processing data.

[0139] Preferably, the cost calculation unit 400 includes:

[0140] The cost accrual sub-result calculation sub-unit is used to determine the cost accrual sub-result that matches each processing dimension based on the matching service data and supplier agreement data under the same processing dimension.

[0141] The cost accrual sub-results aggregation sub-unit is used to aggregate the cost accrual sub-results based on different aggregation granularities to obtain the initial cost accrual calculation results.

[0142] The system for cargo aviation cost accounting provided in this application embodiment can be applied to electronic devices used for cargo aviation cost accounting. Figure 3 A schematic diagram of an electronic device used in cargo air freight cost accounting is shown, with reference to... Figure 3 The structure of an electronic device used for cargo air cost accounting may include: at least one processor 10, at least one memory 20, at least one communication bus 30 and at least one communication interface 40;

[0143] In this embodiment, the number of processor 10, memory 20, communication bus 30 and communication interface 40 is at least one, and processor 10, memory 20 and communication bus 30 communicate with each other through communication interface 40.

[0144] The processor 10 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0145] The memory 20 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device;

[0146] The memory stores a program, which the processor can call. The program is used to implement the various processing steps in the aforementioned method for calculating air freight costs.

[0147] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0148] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0149] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0150] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for use in freight air cost accounting, characterized in that, The method comprises: acquiring main data and associated data of a cargo flight to be processed, the associated data at least including fuel data, route data and ground service data; performing data preprocessing on the main data and the associated data to obtain a plurality of pieces of service data; determining supplier agreement data corresponding to a processing dimension corresponding to each piece of service data based on the processing dimension; calculating an initial cost calculation result based on matching service data and supplier agreement data under the same processing dimension; calculating a difference result between a supplier account under a target granularity and the initial cost calculation result; optimizing the initial cost calculation result according to the difference result to obtain a target cost calculation result; wherein the calculation of the difference result between the supplier account under the target granularity and the initial cost calculation result comprises: in response to receiving a bill auditing instruction, deleting an existing bill pre-audit result; pre-auditing bill detail data of a supplier account to be audited and main data and associated data of a cargo flight corresponding to the processing dimension to obtain a pre-audit result; determining cost difference data of different hierarchical granularities based on a first pre-audit sub-result and the initial cost calculation result, the pre-audit result comprising a first pre-audit sub-result and a second pre-audit sub-result, there being calculation data corresponding to the first pre-audit sub-result in the initial cost calculation result, and there being no calculation data corresponding to the second pre-audit sub-result in the initial cost calculation result; in the cost difference data, extracting cost difference data corresponding to the first pre-audit sub-result of the supplier account under the target granularity, the target granularity including the smallest granularity in the current different hierarchical granularities; determining a difference result between the supplier account and the initial cost calculation result based on the second pre-audit sub-result and the cost difference data corresponding to the first pre-audit sub-result of the supplier account under the target granularity.

2. The method of claim 1, wherein, The method further comprises: collecting target data, the target data including general information, cargo aircraft information of a cargo airline and supplier information providing services for cargo transportation; storing data sub-items corresponding to each target data based on a specific data table format to obtain an initial data table, wherein the specific data table format includes sub-tables of different types of target data and data sub-item storage areas corresponding to each sub-table; determining operation items of the initial data table, and packaging the initial data table based on the operation items to obtain a target data table, so that data query based on the target data table obtains main data and associated data corresponding to a cargo flight to be processed, and supplier agreement data.

3. The method of claim 1, wherein, The data preprocessing on the main data and the associated data to obtain a plurality of pieces of service data comprises: in response to the main data and the associated data having an unverified mark, verifying the main data and the associated data according to specific judgment logic; performing flight pairing, data attachment and data completion processing on the verified data based on flight information to obtain a plurality of pieces of service data.

4. The method of claim 1, wherein, The processing dimension includes a flight dimension, wherein the determining of the supplier agreement data corresponding to the processing dimension based on the processing dimension corresponding to each piece of service data comprises: determining a supplier agreement screening condition corresponding to the flight dimension; obtaining an agreement cost basis rule matched with the supplier agreement screening condition; matching each piece of the agreement cost basis rule, and obtaining supplier agreement data of the agreement cost basis rule matched successfully, so that a corresponding cost accrual sub-result under the flight dimension is calculated based on the supplier agreement data.

5. The method of claim 1, wherein, The processing dimension includes a time dimension, wherein the determining of the supplier agreement data corresponding to the processing dimension based on the processing dimension corresponding to each piece of service data comprises: obtaining valid cargo processing data matched with the time dimension in each piece of the service data; determining a matched agreement rule for each piece of the valid cargo processing data; determining corresponding supplier agreement data based on the agreement rule, so that a cost accrual sub-result corresponding to the flight cargo processing data is calculated based on the supplier agreement data and the valid cargo processing data.

6. The method of claim 1, wherein, The calculating of the initial cost accrual calculation result based on the matched service data and supplier agreement data under the same processing dimension comprises: determining a cost accrual sub-result matched with each processing dimension based on the matched service data and supplier agreement data under the same processing dimension; based on different summary granularities, the cost accrual sub-results are summarized to obtain the initial cost accrual calculation result.

7. A system for use in freight airline cost accounting, the system comprising: comprise: a data acquisition unit configured to acquire main data and associated data of a cargo flight to be processed, the associated data at least including fuel data, route data, and ground service data; a data preprocessing unit configured to perform data preprocessing on the main data and the associated data to obtain a plurality of pieces of service data; an agreement data acquisition unit configured to determine supplier agreement data corresponding to a processing dimension based on the processing dimension corresponding to each piece of the service data; a cost calculation unit configured to calculate an initial cost accrual calculation result based on matched service data and supplier agreement data under the same processing dimension; a difference calculation unit configured to calculate a difference result of a supplier account under a target granularity and the initial cost accrual calculation result; a target cost acquisition unit configured to optimize the initial cost accrual calculation result according to the difference result to obtain a target cost accrual calculation result; wherein the difference calculation unit calculates the difference result of the supplier account under the target granularity and the initial cost accrual calculation result, and is specifically configured to: In response to receiving the bill auditing instruction, deleting the existing bill pre-audit result; pre-auditing the bill detail data of the supplier account to be audited and the main data of the corresponding processing dimension of the freight flight and the associated data, service data to obtain a pre-audit result; based on the first pre-audit sub-result and the initial cost accrual calculation result, determining cost difference data of different hierarchical granularities, the pre-audit result including a first pre-audit sub-result and a second pre-audit sub-result, there being accrual calculation data corresponding to the first pre-audit sub-result in the initial cost accrual calculation result, and there being no accrual calculation data corresponding to the second pre-audit sub-result in the initial cost accrual calculation result; in the cost difference data, extracting the cost difference data corresponding to the first pre-audit sub-result of the supplier account under the target granularity, the target granularity including the smallest granularity in the current different hierarchical granularities; based on the second pre-audit sub-result and the cost difference data corresponding to the first pre-audit sub-result of the supplier account under the target granularity, determining the difference result of the supplier account and the initial cost accrual calculation result.

8. An electronic device, comprising: comprise a processor and a memory; The processor is configured to execute a program stored in the memory. The memory is configured to store a program, and the program is configured to implement each step of the method for air cargo cost accounting according to any one of claims 1-6.

9. A storage medium, characterized by The storage medium has a computer program stored thereon, and the computer program is executed by the processor to implement each step of the method for air cargo cost accounting according to any one of claims 1-6.

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