Information processing system and index calculation method

Abstract

This information processing system comprises: an auxiliary storage device 1300 as a storage unit for storing a data set 400 that is related to calculation of a prescribed index, and has included therein, in association with one another, data of an input value necessary for computing the prescribed index, at least one structure of an expression for computing the prescribed index, and data of an output value which is a computing result of the prescribed index; and a CPU 1100 as a processing unit capable of outputting, on the basis of the data set, information related to the input value, the expression, or the output value, which are each associated with the prescribed index. With this configuration, the information processing system can manage the reliability of the index.

Description

Information processing system and index calculation method

[0001] The present invention relates to an information processing system and an index calculation method.

[0002] Japanese Patent Laid-Open Publication No. 2023-57944 (Patent Document 1) describes a technology for efficiently managing data. This publication states, "We provide an information processing device, information processing method, and information processing program that simplify input work when creating forms, application documents, etc." and "In a low-code development web server device (2), an action setting unit (28) sets a save area definition that indicates a save area to be saved within an area on a display screen, a control setting unit (24) sets a control definition that indicates controls that are at least display items or operation buttons to be placed within the save area set by the save area setting unit, a dynamic restoration target setting unit (26) sets, among the controls, controls whose values ​​are dynamically updated and displayed the next time the screen is displayed or thereafter as dynamic restoration target control definitions, and a storage control unit (27) associates the save area definition, the control definition, and the dynamic restoration target control definition as child elements of the save area definition, and stores the save area definition, the control definition, and the dynamic restoration target control definition in a hierarchical structure in a storage unit."

[0003] JP 2023-57944 A

[0004] There are cases where calculations are performed using input data to obtain a target value. In such cases, it has been difficult to verify the calculated value. For example, when using data calculated from multiple data, it is difficult to confirm how the value was calculated. However, when calculating management indicators or indicators of greenhouse gas (GHG) emissions, multiple calculation methods may exist for the same indicator. For example, if the type and quantity of underlying data are sufficient, the value of the indicator can be calculated accurately. However, even if the type and quantity of underlying data are sufficient, the value of the indicator can only be obtained as an approximate value with a certain degree of accuracy. Furthermore, even for the same indicator, regulations required for the calculation method may differ depending on the user. As such, even for the same indicator, the value and reliability may differ depending on the calculation process. Therefore, there is a need to be able to trace back the calculation process of the indicator, that is, to realize traceability for the calculation process of the indicator so that the reliability of the indicator can be managed. Patent Document 1 does not take the above-mentioned issues into consideration.

[0005] Therefore, an object of the present invention is to manage the reliability of the index.

[0006] To achieve the above object, one representative information processing system of the present invention is characterized by comprising: a storage unit that stores a dataset related to the calculation of a predetermined index, the dataset storing input value data required to calculate the predetermined index, at least one or more formula structures for calculating the predetermined index, and output value data resulting from the calculation of the predetermined index, in association with each other; and a processing unit that is capable of outputting information related to the input values, the formula, or the output value based on the dataset. Also, one representative index calculation method of the present invention is characterized by comprising the steps of: an information processing system referencing a dataset related to the calculation of a predetermined index, the dataset storing input value data required to calculate the predetermined index, at least one or more formula structures for calculating the predetermined index, and output value data resulting from the calculation of the predetermined index, and acquiring the input values; executing a process indicated by the formula; setting intermediate and / or final results of the execution of the process as output values; and associating and saving the acquired input value results, the execution result of the process, and the output value as the intermediate and / or final result.

[0007] According to the present invention, it is possible to manage the reliability of the index. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0008] 1. Explanatory diagram of an information processing system according to a first embodiment. Configuration diagram of an information processing system. Configuration diagram of a computer operable as an information processing system. Specific examples of data stored in a database. Specific diagram of data input / output. Specific example of a dataset. Flowchart showing the processing procedure of an information processing system. 1. Explanatory diagram of a process when reusing existing calculation results. 2. Explanatory diagram of a process when reusing existing calculation results. 3. Specific example of a data input screen. Flowchart of input control. Specific example of display of input values. 4. Explanatory diagram of comparison of identical indicators. Flowchart showing comparison processing of identical indicators. 5. Specific example of display of multiple indicators. Flowchart showing the processing procedure for displaying multiple indicators. 6. Explanatory diagram of displaying company information. Flowchart showing the processing procedure for displaying structure. 7. Explanatory diagram of data tracing. Flowchart showing the processing procedure for data tracing and displaying. 8. Explanatory diagram of tracing energy flow. 9. Explanatory diagram of displaying dataset usage statistics. 10. Explanatory diagram of an example of calculating and displaying monetization usage information from the usage amount of a dataset. 11. Specific example of a dataset related to calculating equipment consumption units. Flowchart of calculation processing for GX indicators.

[0009] Hereinafter, an embodiment will be described with reference to the drawings.

[0010] 1 is an explanatory diagram of an information processing system according to a first embodiment. The information processing system 500 is a system that calculates an index. The information processing system 500 uses a data set 400a when calculating the index.

[0011] Dataset 400a is a dataset related to the calculation of an index, and associates input value data required to calculate the index, at least one or more formula structures for calculating the index, and output value data that is the calculation result of the index. As an example, dataset 400a specifies three pieces of data A1 to A3 as inputs. The dataset also specifies B1 and B2 in the formula structure. B1 is a function of inputs A1 and A2. B2 is a function of B1 and A3. The dataset 400a also specifies that B2 is used for output C1. This C1 is the value of the index to be calculated using dataset 400a.

[0012] The information processing system 500 calculates an index based on the data set 400a. Specifically, the information processing system 500 obtains inputs A1 to A3 from the database 800, performs calculations according to formulas B1 to B2, and obtains C1. The information processing system 500 manages the values ​​of the inputs A1 to A2, formulas B1 to B3, and the value of the output C1 in association with each other. That is, the information processing system 500 can output the calculation results as data set 400b, which is data set 400a to which values ​​have been added. In this way, the information processing system 500 does not only output the calculation results of the index, but also manages the input values ​​and formulas used in the calculation of the index in association with each other, and outputs them together with the calculation results of the index. This enables traceability of the calculation process of the index, verification of the index, and management of its reliability. In other words, the information processing system 500 can support data traceability. Here, it is desirable to describe the inputs, formulas, and outputs in the data sets 400a and 400b in a format that is easily readable by humans. This is because it is assumed that the formula will be read directly by a human during verification. In this example, the formula is written in infix notation. It is also preferable to restrict the input value to ensure reproducibility. For example, if the latest value is set to be used as the input value, it will be difficult to confirm what point in time the data was used during subsequent verification. For this reason, it is preferable to set the type of input value, such as specifying a time, to make reproduction and verification easier.

[0013] 2 is a configuration diagram of an information processing system 500. The information processing system 500 is communicatively connected to a user terminal 600 and is capable of sending and receiving communication packets 700 to and from the user terminal 600. The user terminal 600 has a user instruction input function 610. The user instruction input function 610 accepts user operations and transmits instructions indicated by the operations to the information processing system 500. The instructions include storing a dataset 400 related to index calculation, executing index calculation, and outputting calculation results and intermediate progress.

[0014] The information processing system 500 has a dataset 400 for calculating indices, a dataset 440 for linking with an existing system API (Application Programming Interface), a function 100 for converting into calculation processing based on a mathematical formula, an input value state management function 200, a formula executable state management function 210, an output state management function 220, a DBMS (database management system) 230, and a usage management function 300.

[0015] As already explained, the data set 400 relating to the calculation of the index includes input information 410, which is information relating to the input, formula information 420, which is information relating to the formula, and output information 430, which is information relating to the output.

[0016] The dataset 440 for existing system API integration has correspondence information 441 from information search parameters to input information, and correspondence information 442 between output information and data structure for integration API. The correspondence information 441 from information search parameters to input information is data indicating the correspondence relationship between identification information of data that can be obtained from the outside and identification information that uniquely identifies data within the dataset 400. One example of data that can be obtained from the outside is data that can be obtained from the database 800. The correspondence information 442 between output information and data structure for integration API is data indicating the correspondence relationship between identification information that uniquely identifies data within the dataset 400 and the data format used by the output destination of the index.

[0017] The function 100 for converting to calculation processing based on a mathematical formula is a function for converting formula information 420 into a notation suitable for program processing. For example, it performs a process for converting formula information 420 written in infix notation into reverse Polish notation. The input value state management function 200 manages whether each input value indicated in the input information 410 of the dataset 400 is in a state where it can be obtained from the database 800. Furthermore, when calculating an index using a certain method, the input value state management function 200 can calculate the ratio of input values ​​that can be obtained as an achievement ratio.

[0018] The formula executable state management function 210 manages whether or not calculation is executable for each formula indicated in the formula information 420 of the data set 400. The formula executable state management function 210 can also calculate the ratio of how many of the formulas included in the data set are calculable as an achievement ratio.

[0019] The output state management function 220 is a function that executes calculations of formulas and manages the state of the final output and intermediate output. The final output is the output of the indicators indicated in the output information 430 of the dataset 400. The intermediate output is the output of acquired input values ​​and intermediate calculation progress, etc. The output state management function 220 can calculate the ratio of how much of the final output or intermediate output can be output as the achievement ratio. The DBMS 230 is software that manages access to the database 800.

[0020] The usage management function 300 is a function related to the use of indicators calculated based on a dataset 400. The usage management function 300 has an input / formula / output snapshot saving function 310 and a usage statistics / monetization information calculation function 320. The input / formula / output snapshot saving function 310 is a function that saves values ​​obtained for inputs, calculation results of formulas, values ​​of output indicators, and progress in association with the dataset 400. This snapshot corresponds to the dataset 400b in FIG. 1. The usage statistics / monetization information calculation function 320 is a function that manages the usage history of the output indicator values ​​and snapshots, and calculates the value of the output indicator values ​​and snapshots based on the usage history.

[0021] 3 is a configuration diagram of a computer that can operate as the information processing system 500. The computer 1000 has a CPU (Central Processing Unit) 1100, a memory 1200, an auxiliary storage device 1300, a communication device 1400, an input device 1500, and an output device 1600.

[0022] The CPU 1100 loads and executes a program in a memory that is a main storage device, thereby causing the computer 1000 to operate as an information processing system 500. The CPU 1100 also operates as a process that realizes a function 100 that converts data into calculation processing based on a mathematical formula, an input value state management function 200, a formula executable state management function 210, an output state management function 220, a DBMS 230, and a usage management function 300.

[0023] The auxiliary storage device 1300 is, for example, a hard disk drive. The auxiliary storage device 1300 stores the data set 400 and the data set 440. The auxiliary storage device 1300 can also store snapshots acquired by the usage management function 300 and other arbitrary data.

[0024] The communication device 1400 is a communication interface that communicates with the user terminal 600 and the database 800. The input device 1500 is a keyboard and a pointing device. The output device 1600 is a display or the like.

[0025] FIG. 4 shows a specific example of data stored in the database 800. The database 800 stores master data such as company information 810, product name 811, production equipment 812, factory structure 813, unit system 814, raw material, part, and work-in-progress product name 815, and business name 816. These master data identify the object itself and manage associated information. The interrelationships between data are managed using parent-child relationships and from-to relationships. For example, a product structure can be represented using a parent-child relationship in which the product name 811 is the parent and the raw material, part, and work-in-progress product name 815 is the child. Furthermore, the from-to relationships can be used to represent energy flow, manufacturing process flow, and business procedure flow. Annual unit constant definitions can also be represented using group relationships.

[0026] The database 800 stores, as performance data, energy prices 817, order information 818 as events, order information 819 as time-series periodic information, and energy performance 820 as a time series. This performance data is accumulated as periodic events or periodic data. For example, order information 818 is data that manages orders generated during a certain period as individual events, and order information 819 is data that manages the cumulative trend of orders for each period. This performance data can be compared with statistical forecast data or simulation forecast data. For example, a production plan can be formulated as a schedule based on orders that have been generated. Future orders can be predicted from the order information 819, which is performance data, and production can be predicted from the predicted orders. Furthermore, future fluctuations in energy performance can be predicted from the energy performance 820, which is performance data. The various predicted data can then be compared with data obtained subsequently as performance.

[0027] FIG. 5 is an explanatory diagram of data input / output. Data input / output is performed in the following steps (1) to (3). (1) The input value status management function 200 of the information processing system 400 sends an instruction to the DBMS 441 to acquire the desired input value using the "list of identifiers having the amount of information required to narrow down the information," "information 441 corresponding to information search parameters to input information," and "data search query taking into account the data table address + narrowing down conditions using values." (2) The information acquired by the DBMS 230 is converted using the "information 441 corresponding to information search parameters to input information" and "data search query taking into account the data table address + narrowing down conditions using values," and the input value status management function 200 receives the converted information as a "list of results." (3) The output state management function 220 uses the output value information, such as the "list of information amounts for narrowing down the output destination," "output information and data structure correspondence information 442 for the linked API," and "narrowing conditions using a data search query + value that takes into account the address of the data table," to send an instruction to the DBMS 230 to store the target output value in the database 800. In this way, the DBMS 230 retrieves information from the database 800 and stores the information based on instructions from the input value state management function 200 and the output state management function 220.

[0028] The correspondence information 441 and correspondence information 442 held by the information processing system 500 indicate the correspondence relationship between the identification information of data in the database 800 and the identification information that uniquely identifies the data within the dataset 400. By referencing the correspondence information 441 and correspondence information 442, the information processing system 500 can convert the name of the data used by the dataset 400 into the identification information of the data used by the database 800. The identification information of the data used by the database 800 corresponds to the address of the data table. Therefore, the DBMS can access the data in the database 800 using a narrowing-down condition that uses a "data search query + value that takes into account the address of the data table." The names of the data used by the dataset 400 can be used as a "list of identifiers with an amount of information that narrows down information" and a "list of an amount of information that narrows down output destinations," and are stored in the auxiliary storage device 1300.

[0029] Conventional relational databases link data using relations (table addresses). In this configuration, data is retrieved on the assumption that the system design is already known. Therefore, if the correspondence between data is undetermined or has changed, data cannot be retrieved, and flexible design changes cannot be accommodated. In contrast, the system disclosed in the embodiment manages reserved words that can uniquely identify the type of data managed in the database, and by combining these words, it is possible to ensure the uniqueness of the meaning and data source for the data in the entire data set.

[0030] FIG. 6 is a specific example of a dataset. Data set 400 shown in FIG. 6 is an example of a dataset for calculating management indicators. Data set 400 shown in FIG. 6 specifies "sales forecast" and "total variable costs" as input values. Also, it specifies "variable cost ratio" and "break-even sales" as output values. Furthermore, among the contents of processing performed using the input values, it specifies "total variable costs / sales forecast" as the formula for calculating the "variable cost ratio," and it specifies "total fixed costs / (1-variable cost ratio)" and "total fixed costs / marginal profit rate" as the formula for calculating the "break-even sales."

[0031] 6 , the data set 400 indicates the type of input value data, the details of the processing performed using the input value, and the type of output value data. When data of a specified type is obtained as an input value, the information processing system 500 executes processing using the data to obtain an output value. Furthermore, the information processing system 500 manages the value of the data used as the input value, the details of the processing performed, and the value of the output value obtained as a result of the processing, in association with each other.

[0032] In the dataset 400 of FIG. 6 , one row is assigned to each data type for input values, output values, and expressions. This makes the dataset 400 easy for humans to read directly. Furthermore, when data specified as an input value is obtained, the "status" included in the row for that input value is set to "FIX," and the value used as the input value is stored as "value." Similarly, rows for expressions and output can also have "status" and "value." In this way, the dataset 400 can store processing results and progress statuses within itself. The dataset 400 that stores the processing results and progress statuses is managed as a snapshot separately from the original dataset 400.

[0033] The input values ​​can also be the results of calculations using a formula. Of the input values, input values ​​obtained from an external source are called primary data. Input values ​​calculated from primary data are called secondary data. Secondary data is not limited to data calculated directly from primary data; data calculated from secondary data is also considered a type of secondary data, since it is calculated indirectly from primary data. Output values ​​may include data of the same type, but with different input values ​​or formulas. In Figure 6, there are two rows for "break-even sales" that use different formulas for calculation.

[0034] A digital signature may be generated from a data set 400 that stores processing results and progress status, and attached to the data set 400. In Fig. 6, the body is digitally signed, and a signature hash, which is a verifiable code, is embedded in the header. Information regarding which items correspond to which regulations and which items are primary data is also embedded in the body.

[0035] 7 is a flowchart showing the processing procedure of the information processing system. The information processing system 500 sequentially executes the following steps S101 to S108. Step S101: The information processing system 500 reads the correspondence information 441 from the information search parameters to the input information, and executes a process of converting data obtainable from the database 800 into identification information data used in the data set 400. Then, the process proceeds to step S102. Step S102: The information processing system 500 reads the data set 400. Then, the process proceeds to step S103. Step S103: The information processing system 500 performs processing using the input value state management function 200. This process determines whether all input information, which is data to be used as input values, is present. Then, the process proceeds to step S104.

[0036] Step S104: The information processing system 500 determines whether all of the input information is satisfied. If all of the input information is satisfied (Step S104: Yes), the process proceeds to Step S106. If there is any input information that is not satisfied (Step S104: No), the process proceeds to Step S105. Step S105: The information processing system 500 regards the unsatisfied input information as a missing item, outputs the ratio of the missing item to the total input information as a missing ratio, and ends the process. Step S106: The information processing system 500 starts the formula executable state management function 210, and proceeds to Step S107.

[0037] In step S107, the information processing system 500 executes a process to check the status of the input and intermediate results using the formula executable state management function 210. Then, the process proceeds to step S108. In step S108, the information processing system 500 interprets the formula using the formula-based calculation conversion function 100, and then proceeds to step S109. In step S109, the information processing system 500 performs calculations using the output state management function 220 and writes the results in the output information 430. The written output information 430 may also be used as input as secondary data. Therefore, steps S107 to S109 are repeated until all output information that can be calculated from the obtained input information has been written. Then, the process proceeds to step S110.

[0038] Step S110: The information processing system 500 reads and executes the correspondence information 442. As a result, the output value is output as data in a format suitable for the output destination. Then, the process proceeds to step S111. Step S111: The information processing system 500 executes the input / formula / output snapshot saving function 310. As a result, data associating the used input value, the processing content and result of the formula, and the calculated output value is accumulated as a snapshot.

[0039] In Figure 7, calculations start when all input information is met, but it may be configured so that calculations start within the range that can be calculated from the input information when some input information is obtained. In this case, the calculation progress can be output along with the missing items and the missing ratio.

[0040] 7 shows a process for performing calculations using data managed by database 800. If the same type of data is subsequently required, the process of FIG. 7 may be performed again, or existing calculation results may be referenced and reused. In this way, reusing existing calculation results can increase the value of the existing calculation results.

[0041] 8 and 9 are explanatory diagrams of the process when reusing existing calculation results. In the process of FIG. 8, the user terminal 600 and the information processing system 500 sequentially execute the following steps S201 to S204. Step S201: The user terminal 600 obtains the identification of the desired output from the user instruction input function 610. Then, the process proceeds to step S202. Step S202: The input / formula / output snapshot saving function 310 of the information processing system 500 searches past calculation history. Then, the process proceeds to step S203. Step S203: The information processing system 500 creates the result as a communication packet 700 and transmits it to the user terminal 600. Then, the process proceeds to step S204. Step S204: The information processing system 500 displays a ranking of data used as reference destinations on the user terminal 600.

[0042] In the process of FIG. 9, the user terminal 600 and the information processing system 500 sequentially execute the following steps S301 to S305. Step S301: The user terminal 600 obtains the identification of the desired output from the user instruction input function 610. Then, the process proceeds to step S302. Step S302: The input / formula / output snapshot saving function 310 of the information processing system 500 searches past calculation history. Then, the process proceeds to step S303. Step S303: The information processing system 500 creates the result as a communication packet 700 and transmits it to the user terminal 600. Then, the process proceeds to step S304. Step S304: The user terminal 600 receives, via the user instruction input function 610, information selected for data that has the same desired output but differs in at least one of the input and the calculation formula. Then, the process proceeds to step S305. Step S305: The usage statistics / monetization information calculation function 320 of the information processing system 500 outputs the information to the database 800, and the process ends.

[0043] Below, we will explain a use case in which a data input screen is automatically generated from a dataset 400 related to the calculation of an index, items whose status has been changed from "default value" to "entered" are detected, and an evaluation is returned to the user.

[0044] FIG. 10 is a specific example of a data input screen. The user instruction input function 610 of the user terminal 600 reads the dataset 400 related to the calculation of the index and generates a data input screen from the dataset 400. For example, an input field is generated for the input value included in the dataset 400. This input field may be capable of accepting text input or a pull-down menu. Similarly, the user instruction input function 610 can display expressions and outputs and accept changes, etc. A default value is displayed in each input field, which can be changed by the user.

[0045] The input values ​​for calculating indicators are not necessarily only the information that is available. In such cases, if a field is left blank or filled with zeros, an error may occur in the indicator calculation. Therefore, this system generates an input screen that reflects default values ​​so that you can increase the information that you need to enter while checking which items will change the indicators if you improve them.

[0046] 11 is a flowchart of input control. The user terminal 600 sequentially executes the following steps S401 to S404. Step S401: The user instruction input function 610 obtains identification information for the desired output. Then, the process proceeds to step S402. Step S402: The user instruction input function 610 receives a default value from the information processing system 500. Then, the process proceeds to step S403. Step S403: The user instruction input function 610 accepts input from the user and changes the default value to the input value. Then, the process proceeds to step S404. Step S404: The user terminal 600 sends back to the information processing system 500 the values ​​of the items that have been changed to the extent that the user knows, and data that changes the status of the items from the default value to "entered," and ends the process.

[0047] FIG. 12 shows a specific example of input value display. The information processing system 500 sets stages for different calculation methods for calculating the same index according to the number of required input values, and can calculate the index using a calculation method that satisfies the currently required input values ​​while providing information on the input values ​​required for the calculation method of the next stage. FIG. 12 shows an example of calculating a GX (green transformation) index. Maturity level 1 corresponds to a method that calculates the GX index with relatively few inputs. Maturity level 2 corresponds to a method that calculates the GX index using more inputs than maturity level 1. The higher the maturity level, the more inputs are required and the higher the accuracy of the resulting index, and it is therefore desirable to increase the maturity level appropriately.

[0048] In Figure 12, all inputs required for calculating the GX index at maturity level 1 have been obtained, and the maturity level 1 GX index achievement rate is 100%. For the next stage, maturity level 2, inputs are insufficient, and the maturity level 2 GX index achievement rate is 62%. As shown in the processing in Figure 11, the status of the items for which input has been made changes from "default value" to "entered", so the percentage of inputs achieved can be calculated by taking the total number of inputs for index calculation as the denominator and the number of items whose status has changed to "entered" as the numerator.

[0049] Below, we will explain the process of selecting multiple calculations for the same indicator and displaying the differences between them. In particular, we will explain elements that can be displayed in chronological order. Figure 13 is an explanatory diagram of comparison of the same indicator. For the same output information, different values ​​can be obtained by calculating using, for example, different time periods, different inputs, and different formula information. Figure 13 shows an example of a screen that displays and compares these multiple values ​​in chronological order. It is possible to obtain different values ​​for each of multiple indicators, depending on the time period, input, formula information, etc.

[0050] Due to changes in regulations and the policies of each organization, the formula and its input for the same output information of the GX indicator may differ. Therefore, it is necessary to search for past evidence information from the output information 430 and plot and display the differences in order to compare multiple data. In addition, by selecting output information, it is possible to provide a function to display a snapshot showing the breakdown of the output, and by selecting the output to be compared, it is possible to provide a function to extract and display the differences in the inputs and formulas between the selected outputs.

[0051] FIG. 14 is a flowchart showing the process of comparing identical indicators. The process of comparing identical indicators includes the following steps S501 to S504. Step S501: The user instruction input function 610 of the user terminal 600 accepts input of identification information for the outputs to be compared. Then, the process proceeds to step S502. Step S502: The user instruction input function 610 sends the identification information for the outputs to be compared to the information processing system 500. Then, the process proceeds to step S503. Step S503: The user terminal 600 selects data to be compared in chronological order from the information in the dataset related to the calculation of the indicator. Then, the process proceeds to step S504. Step S504: If the user terminal 600 can display the data in chronological order, it individually identifies and displays the different inputs to be compared and the information calculated by the formula on the screen, and ends the process.

[0052] The following describes a process for selecting multiple indicators and displaying them in a series. Figure 15 shows a specific example of displaying multiple indicators. Because GX indicators are evaluated using indicators from multiple perspectives, it is necessary to obtain an overview of the overall results of various indicators. In Figure 15, various indicators are plotted on a radar chart, making it possible to check multiple indicators. In Figure 15, inputs 1 to 4 and outputs 1 to 3 are shown as the axes of the radar chart. In addition, two patterns of input, output, etc. are displayed using solid and dashed lines for comparison. By comparing the pattern shown by the solid line with the pattern shown by the dashed line, it can be seen that input 4 is different and that the difference in input 4 affected outputs 1 and 3.

[0053] FIG. 16 is a flowchart showing the processing steps for displaying multiple indicators. The displaying multiple indicators includes the following steps S601 to S603. Step S601: The user instruction input function 610 of the user terminal 600 accepts input of identification information for multiple outputs to be compared. Then, the process proceeds to step S602. Step S602: The user instruction input function 610 sends the identification information for the outputs to be compared to the information processing system 500. Then, the process proceeds to step S603. Step S603: The user terminal 600 displays the data to be compared in a radar chart from the information in the dataset related to the calculation of the indicators, and ends the process. While a radar chart is shown as an example in FIGS. 15 and 16, various indicators can be displayed for comparison in any format, such as a pie chart.

[0054] The display of structured information will be explained below. Figure 17 is an explanatory diagram of the display of company information. Because companies undergo repeated mergers, name changes, and divisions, it is necessary to display and confirm company information as data with From-To relationships. The display example in Figure 17 shows that initially there were companies A, B, and C, and that company B was merged into company A, company C changed its name to company D, company A changed its name to company E, and company E was merged into company D.

[0055] 18 is a flowchart showing the steps of the structure display process. The structure display process includes the following steps S701 to S703. Step S701: The user instruction input function 610 of the user terminal 600 accepts the selection of the structure and its data to be displayed. Then, the process proceeds to step S702. Step S702: The user instruction input function 610 sends the target structure and its data identifier information to the information processing system 500. Then, the process proceeds to step S703. Step S703: The user terminal 600 displays the information structure based on the information received from the information processing system 500, and ends the process.

[0056] FIG. 19 is an explanatory diagram of data tracing. The information processing system 500 can recognize and identify output information and input information by their identification names. This makes it possible to specify one data set and display the data processing before and after it. For example, if the identification names of the output information and input information are hierarchically structured, tracing is possible by following the hierarchical structure. FIG. 19 shows that it is possible to trace the data source side (upstream side) and the impact destination side (downstream side) using the selected data set as the reference.

[0057] 20 is a flowchart showing the steps of the data trace display process. The data trace display process includes the following steps S801 to S803. Step S801: The user instruction input function 610 of the user terminal 600 accepts the designation of the data set to be displayed and an instruction to display the traceability structure. Then, the process proceeds to step S802. Step S802: The user instruction input function 610 sends the data set identifier and instruction information for displaying the traceability structure to the information processing system 500. Then, the process proceeds to step S803. Step S803: The user terminal 600 receives the traceability results from the information processing system 500, displays the structure, and ends the process.

[0058] 21 is an explanatory diagram for tracing the flow of energy. In this case, the user terminal 600 refers to the energy performance and the From-To relationship of the energy flow, and displays the structure of how energy is supplied from the energy source to the energy consumer while being coupled and distributed.

[0059] FIG. 22 is an explanatory diagram of the display of usage statistics for datasets. In FIG. 22, the usage statistics and monetization information calculation function 320 displays a graph showing how often each dataset is referenced for the CO2 aggregate value. Specifically, the CO2 aggregate value for 2023 for Plant A is referenced the most, followed by the CO2 aggregate value for 2022 for Plant A, and then the CO2 aggregate value for 2022 for Plant B. In this way, by collecting reference frequency statistics for the same indicator in different years or locations, the value of each dataset can be evaluated.

[0060] FIG. 23 is an explanatory diagram of an example of calculating and displaying monetization usage information from the usage amount of a data set. In FIG. 23, the usage statistics / monetization information calculation function 320 collects statistics on the amount of references to each type of data in terms of data volume. By collecting statistics on the amount of references to each data in this way, the importance of each data type can be evaluated. Note that while usage volume is used as an example here, the importance of each data type can also be evaluated using any value as an indicator, such as the amount of data accumulated.

[0061] Next, I will explain the GX index. In recent years, promoting energy conservation has become an important issue. In order to promote energy conservation, there are cases where companies are required to report, for example, if they have not been able to improve their energy consumption rate by an average of 1% or more per year over the past five years, or if their energy consumption rate has not improved compared to the previous year, they must report the reasons for this.

[0062] Energy consumption intensity is used as an indicator of the rationalization of energy use. A factory's energy consumption intensity (hereafter abbreviated as "factory energy intensity") represents the amount of energy (factory input) used to produce a unit amount of product (factory output). It is also believed that production volume is proportional to the amount of energy effectively used to produce products in the production process. Energy intensity can also be interpreted as a quantity proportional to the inverse of the "factory energy efficiency." Therefore, if a factory's energy intensity decreases, it means that the factory's energy efficiency has increased.

[0063] The energy consumption unit used as an indicator for the "Energy Rationalization Criteria" can be calculated using the following formula.

[0064] The "production volume, etc." in the denominator of the formula is defined as "a value closely related to production volume, total building floor area, or other energy consumption." In other words, there is room for discretion in how the denominator is calculated. Companies that do not want their production volume to be leaked to the public could consider calculating it using other methods, such as total floor area. Furthermore, total floor area is also information used as collateral when providing equipment financing, so even a banker could potentially calculate it. In other words, a banker might calculate it using total floor area, while a corporate power division might use actual production volume. Thus, even the same indicator may be calculated based on different input values. The disclosed system manages data traceability and definitions, enabling accurate comparison of indicators.

[0065] The numerator in the formula, "energy consumption," is the amount of energy used by the factory. If multiple types of energy, such as electricity and fuel, are used, the units must be consistent when adding them up. One approach is to use the value obtained by converting the amount of energy consumption into the amount of primary energy (heat value and crude oil equivalent).

[0066] Primary energy refers to resources that produce energy (crude oil, coal, natural gas, etc.). Secondary energy refers to energy in the form of petroleum products (gasoline, kerosene, heavy oil, etc.), city gas, electricity, and heat used by energy consumers such as factories and homes. Secondary energy is also called final energy. Secondary energy is primary energy that is transformed in the power generation and conversion sectors (power plants, oil refineries, etc.) to make it more convenient for consumers to use. In the energy conversion process, power generation and transmission losses occur in the power system, and refining losses occur in the fuel system. As such, various conversion values ​​are used in the process of calculating indicators, making the calculations complicated.

[0067] The calculation of the basic unit is also multi-level and complex. When comparing and evaluating each output value or considering improvement measures, it is desirable to be able to determine what formula and input each output was based on. The disclosed system can evaluate each value as a set, based on what values ​​were used to calculate it.

[0068] Here we will explain how to calculate the energy intensity, taking into consideration the inclusive structure of a factory. Energy usage can be managed not only for the factory as a whole, but also by monthly aggregation of intensity by product type, department, process, equipment, and lot. Improvements to intensity should be managed by breaking down the data into departments, processes, and ultimately by major equipment. The factory intensity, department intensity, process intensity, and equipment intensity can be calculated as follows:

[0069] As a concrete example, we will explain the calculation of pump equipment energy consumption rate and boiler. The consumption rate of a cooling water pump attached to production equipment is as follows. The numerator is the amount of power used by the pump, and the denominator is the production volume of the production equipment to which the pump sends cooling water (= related production volume). In this case, a flow meter is installed at the pump outlet, and cooling water thermometers are installed before and after the production equipment to measure the "total cooling water flow rate" and "cooling heat amount of the production equipment," and the energy consumption rate can be calculated using the following formula. In this way, even when calculating the same basic unit, several different calculation methods can be obtained by expanding the formula. The disclosed system makes these methods comparable.

[0070] The basic unit focusing on fuel for boiler equipment is as follows. The denominator is the production volume (= related production volume) of the production equipment to which the boiler sends steam. The numerator is the amount of boiler fuel used. (Since we are only focusing on fuel as an energy source, the amount used does not need to be converted into crude oil.) If we break down the basic unit into two indicators using the boiler output, "steam volume," as an intermediary variable, we can express it in the following formula. The first term can be calculated by determining the boiler steam generation rate using figures from the boiler's monthly operation report, etc., to obtain the steam volume equivalent to the "production department's steam intensity." Dividing the steam volume by the production volume related to boiler maintenance represents the amount of steam used to produce a unit amount of product. This is an indicator that should be managed by the production department. The second term, known as the "boiler fuel intensity," represents the amount of fuel used to generate a unit amount of steam. This is an indicator proportional to the inverse of boiler efficiency and should be managed by the power department. By breaking down the "boiler equipment intensity" into these two indicators, if the intensity increases, it is possible to determine which indicator has increased and determine the direction of specific improvement measures. Note that the above formula corresponds to formula information 420 in dataset 400. Furthermore, the production volume, boiler fuel consumption, and steam volume related to the boiler equipment in the above formula correspond to input information 410 in dataset 400. Furthermore, the boiler equipment intensity in the above formula corresponds to output information 430 in dataset 400. This formula is an example of a calculation method that complies with predetermined regulations, and the calculation method for the values ​​of each item and the formula itself on the left can be changed.

[0071] Figure 24 is a specific example of a dataset for calculating boiler equipment intensity. Figure 24 corresponds to the above formula and shows two patterns of dataset for calculating boiler equipment intensity. One dataset does not use steam volume, but assigns floor area to production volume, and calculates boiler equipment intensity by 'boiler fuel consumption' / 'production volume related to boiler equipment'. The other dataset has a higher maturity level, and uses steam volume, and calculates boiler equipment intensity by ('steam volume' / 'production volume related to boiler equipment') * ('boiler fuel consumption' / 'steam volume').

[0072] Next, we will explain management indicators and environmental indicators. The management indicators net profit and ROE (Return on Equity: capital adequacy ratio) can be calculated as follows: Net profit = Sales - Manufacturing costs - Selling and general administrative expenses + Non-operating income and expenditure + Extraordinary income and expenditure - Corporate taxes, etc. ROE = Net profit / Shareholders' equity Net profit is used to calculate ROE. In this way, the indicators are multi-staged, and net profit can be interpreted as the intermediate output.

[0073] Let us take GHG emissions as an example of an environmental indicator. Here, we consider a manufacturing company that produces the same type of product throughout the year, for example, duralumin, which is made from aluminum, copper, and magnesium. Production volume can be calculated as follows: Production volume = Ending inventory volume - Beginning inventory volume + Sales volume = Ending inventory volume - Beginning inventory volume + Sales / Average product price If the product's components are (Al:Cu:Mg) = (a:b:c), then GHG emissions (Scope 1), which are the greenhouse gas emissions emitted directly by the company through fuel use and industrial processes, can be calculated as follows: (Amount of Al used * Emissions intensity + Amount of Cu used * Emissions intensity) x Production volume = (Amount of Al used * 1.49 + Amount of Cu used * 4.49) x Production volume

[0074] Here, the production volume can be roughly estimated from sales and the average unit price of the product, as described above. Therefore, if the material composition and parts composition of the product are known, it is possible to calculate the GHG emissions (Scope 1) from information disclosed to investors, etc., even if the business operator does not directly disclose the production volume.

[0075] The material composition and parts composition correspond to the product structure shown in Figure 4. In the example of duralumin, a parent-child relationship is registered in the product structure, with duralumin as the parent and aluminum, copper, and magnesium as the children. Furthermore, the relationship between the product name and product identification information and the general name and chemical formula is managed in the product name master data in Figure 4. The output status management function 220 has the functions of "importing product name master data and product structure information," "expressing parent-child relationships as mathematical expressions," and "inserting GX parameters," and calculates the GX index using these functions.

[0076] FIG. 25 is a flowchart of the GX index calculation process. The GX index calculation process includes the following steps S901 to S903. Step S901: The output status management function 220 of the information processing system 500 acquires the product name and product structure using the "function for importing product name master data and product structure information" and separates the hierarchies corresponding to input, formula, and output. Then, the process proceeds to step S902. Step S902: The output status management function 220 generates a formula by associating the separated hierarchies with the right-hand side (output) and each term on the left-hand side of the formula using the "function for formulating parent-child relationships." Then, the process proceeds to step S903. Step S903: The output status management function 220 acquires information that can be used as input values ​​using the "function for inserting GX parameters" and executes formula processing. Then, the process ends. Information that can be used as input values ​​is not limited to information managed by the business operator, but also includes substance names and their multipliers specified in regulations.

[0077] In this way, the information processing system 500 can acquire information by linking with information from specific departments, such as information on financial statements for investors, product structures, etc. This not only makes it possible to automatically create data for the necessary items and formulas from the product structure, but also makes it possible to trace the formulas and items created there, making it easier to understand the basis for the values ​​of indicators later.

[0078] Furthermore, each term in the formula expansion can be expanded to various levels, such as by department, process, or equipment. This allows for management of input achievement levels at each level, and allows for appropriate display output. Even if the names of output indicators are the same, differences in the formulas used for calculation and the calculation of the values ​​of each item in those formulas can be identified and visualized. For example, it is possible to display whether a certain value is a standard value or is being quoted from actual department data.

[0079] As described above, the disclosed information processing system includes: an auxiliary storage device 1300 as a storage unit that stores a dataset 400 related to the calculation of a predetermined index, the dataset storing input value data necessary for calculating the predetermined index, at least one or more formula structures for calculating the predetermined index, and output value data that is the calculation result of the predetermined index, all of which are associated with each other; and a CPU 1100 as a processing unit that can output information related to the input values, the formula, or the output values ​​related to the predetermined index based on the dataset. This configuration and operation makes it possible to trace back the calculation process of the index, i.e., to achieve traceability for the calculation process of the index, thereby managing the reliability of the index.

[0080] Furthermore, the data set indicates the type of data of the input value, the content of the processing to be performed using the input value, and the type of data of the output value, and when data of the type specified as the input value is obtained, the processing unit executes the processing using the data to obtain the output value, and the processing unit manages the value of the data used as the input value, the content of the processing that was executed, and the value of the output value obtained as a result of executing the processing in association with each other. Therefore, the input value and the content of the processing used to calculate the output value can be verified later.

[0081] The processing unit obtains multiple calculation results for the same index by performing calculations in which at least one of the input data value and the processing content is different and the output data type is the same. The processing unit uses a first calculation result and a second calculation result for the same index, and displays and outputs a difference between the first calculation result and the second calculation result so that they can be compared, as well as displaying and outputting the input values ​​and / or processing content related to the first calculation result and the second calculation result. This makes it possible to compare output values ​​of the same type obtained through different processes.

[0082] The processing unit also generates a digital signature from a combination of the value of the data used as the input value, the content of the executed process, and the value of the output value obtained as a result of the execution of the process, and assigns the digital signature to the combination, thereby preventing tampering with the calculation process of the output value.

[0083] Furthermore, the data set distinguishes between primary data, which are input values ​​acquired from an external source, and secondary data, which are input values ​​calculated from the primary data, and the processing unit outputs the ratio of the primary data to the input values ​​together with the output value. Therefore, the ratio of the primary data can be used to evaluate the index.

[0084] The processing unit also sets stages for different calculation methods for calculating the same index according to the number of required input values, calculates the index using a calculation method that satisfies the currently required input values, and provides information on the input values ​​required for the calculation method of the next stage, thereby helping to improve the maturity level.

[0085] The processing unit can start the processing when some of the input values ​​are obtained, manage progress information of the processing, and output intermediate results of the processing, so that the progress of the index can be checked as needed.

[0086] The processing unit also refers to the correspondence between identification information of data obtainable from outside and identification information that uniquely identifies data within the dataset, and converts the data obtained from outside into data that serves as an input value for the dataset. The processing unit also refers to the correspondence between identification information that uniquely identifies data within the dataset and a data format used by an output destination of the index, and converts the calculation result of the index into the data format of the output destination, and outputs it. Therefore, by managing reserved words that can uniquely identify the type of data managed in the database, and combining them, it is possible to ensure the uniqueness of the meaning and data source for the data in the entire dataset.

[0087] The processing unit also manages the usage history of the calculation results of the index and evaluates the dataset used in the calculation of the index based on the usage history of the index, so that the amount of reference and use of the dataset can be used as an evaluation index.

[0088] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, not only can the configurations be deleted, but also replacements and additions of configurations are possible.

[0089] 100: Function for converting into calculation processing based on mathematical formula, 200: Input value state management function, 210: Formula executable state management function, 220: Output state management function, 230: DBMS, 300: Usage management function, 400: Data set, 500: Information processing system, 600: User terminal, 800: Database, 1000: Computer, 1100: CPU, 1200: Memory, 1300: Auxiliary storage device, 1400: Communication device, 1500: Input device, 1600: Output device

Claims

1. An information processing system comprising: a memory unit that stores a dataset relating to the calculation of a specified index, in which input value data required to calculate the specified index, at least one or more formula structures for calculating the specified index, and output value data that is the calculation result of the specified index are associated and stored; and a processing unit that is capable of outputting information relating to the input value, the formula, or the output value related to the specified index based on the dataset.

2. An information processing system as described in claim 1, wherein the data set indicates the type of data of the input value, the content of the processing to be performed using the input value, and the type of data of the output value; and when data of the type specified as the input value is obtained, the processing unit executes the processing using the data to obtain the output value; and the processing unit manages, in correspondence with each other, the value of the data used as the input value, the content of the processing executed, and the value of the output value obtained as a result of executing the processing.

3. An information processing system as described in claim 2, characterized in that the processing unit obtains multiple calculation results for the same index by performing calculations in which at least one of the input value data value and the processing content is different and the output value data type is the same.

4. An information processing system as described in claim 3, wherein the processing unit uses a first calculation result and a second calculation result for the same indicator, displays and outputs a difference between the first calculation result and the second calculation result in a comparable manner, and displays and outputs input values ​​and / or processing contents related to the first calculation result and the second calculation result.

5. An information processing system as described in claim 2, characterized in that the processing unit generates an electronic signature from a combination of the value of the data used as the input value, the content of the processing executed, and the value of the output value obtained as a result of executing the processing, and assigns the electronic signature to the combination.

6. An information processing system as described in claim 1, wherein the data set distinguishes between primary data, which are input values ​​obtained from outside, and secondary data, which are input values ​​calculated from the primary data, for a plurality of input values, and the processing unit outputs, together with the output value, the ratio of the primary data among the plurality of input values.

7. An information processing system as described in claim 1, wherein the processing unit sets stages for different calculation methods for deriving the same index according to the number of required input values, calculates the index using a calculation method that satisfies the currently required input values, and provides information on the input values ​​required for the calculation method of the next stage.

8. An information processing system according to claim 2, characterized in that the processing unit is capable of starting the processing when a portion of the input value is obtained, managing progress information of the processing, and outputting intermediate results of the processing.

9. An information processing system as described in claim 1, characterized in that the processing unit refers to the correspondence between identification information of data that can be obtained from outside and identification information that uniquely identifies data within the dataset, and converts the data obtained from outside into data as an input value of the dataset.

10. An information processing system as described in claim 1, characterized in that the processing unit refers to the correspondence between identification information that uniquely identifies data within the dataset and the data format used by the output destination of the index, and converts the calculation result of the index into the data format of the output destination and outputs it.

11. An information processing system as described in claim 1, wherein the processing unit manages the usage history of the calculation results of the index, and evaluates the data set used to calculate the index based on the usage history of the index.

12. A method for calculating an index, characterized in that an information processing system refers to a dataset related to the calculation of a specified index, in which data on input values ​​required to calculate the specified index, the structure of at least one or more equations for calculating the specified index, and data on output values ​​which are the calculation results of the specified index are associated with each other, and includes the steps of acquiring the input values, executing a process indicated in the equation, setting intermediate and / or final results of the execution of the process as output values, and associating and storing the results of acquiring the input values, the results of executing the process, and the output values ​​as the intermediate and / or final results.

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