Information processing device, information processing method, and program

Abstract

To enable efficient data entry using a familiar spreadsheet software interface, and to facilitate understanding of a company's emissions and consideration of reduction measures by visualizing greenhouse gas emissions. [Solution] Server 1 comprises an input template provision unit 51, a data acquisition unit 52, and a GHG emission calculation unit 53. The input template provision unit 51 provides the user terminal with an input template in spreadsheet software format for inputting energy consumption data. The data acquisition unit 52 acquires data, including energy consumption data, entered into the input template by the user. The GHG emission calculation unit 53 calculates greenhouse gas emissions based on the data, including energy consumption data. The visualization unit 54 visualizes the calculated greenhouse gas emissions.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] Conventionally, there has been a technology for a system that calculates a company's greenhouse gas (hereinafter referred to as "GHG") emissions (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in recent years, there has been a demand to eliminate the complexity of input work in web-based calculation systems and to improve data linkage between supply chains. However, conventional technologies, including the technology of Patent Document 1, cannot sufficiently meet such demands.

[0005] The present invention has been made in view of such a situation, and aims to enable efficient data input through a familiar interface of spreadsheet software and to facilitate the understanding of a company's emission status and the consideration of reduction measures by visualizing greenhouse gas emissions.

Means for Solving the Problems

[0006] To achieve the above object, an information processing apparatus according to one aspect of the present invention includes: input template providing means for providing an input template in the form of spreadsheet software for energy usage data input to a user terminal; A data acquisition means that acquires data including energy usage data entered by the user into the input template, A greenhouse gas emission calculation means that calculates greenhouse gas emissions based on data including the aforementioned energy consumption data, A visualization means for visualizing the calculated greenhouse gas emissions, It is equipped with.

[0007] Each of the information processing method and program according to one aspect of the present invention corresponds to each of the method and program corresponding to the information processing apparatus according to one aspect of the present invention. [Effects of the Invention]

[0008] According to the present invention, efficient data entry becomes possible through the familiar interface of spreadsheet software, and the visualization of greenhouse gas emissions makes it easier for companies to understand their emission status and consider reduction measures. [Brief explanation of the drawing]

[0009] [Figure 1] This is an overview diagram of the service that can be realized by an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 2] This is a configuration diagram of an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 3] Figure 2 shows the hardware configuration diagram of the server in the information processing system. [Figure 4] This is a functional block diagram showing the functional configuration of the server in Figure 3 that constitutes the information processing system in Figure 2. [Figure 5] Figures 1 to 4 show the input format screen of the server. [Figure 6] This diagram shows the product master for the servers shown in Figures 1 to 4. [Figure 7] Figures 1 through 4 show the server's component, raw material, logistics, and waste master data. [Figure 8]It is a diagram showing the equipment master of the server shown in FIGS. 1 to 4. [Figure 9] It is a diagram showing the connection master of the server shown in FIGS. 1 to 4. [Figure 10] It is a diagram showing the supply chain cooperation flow of the server shown in FIGS. 1 to 4. [Figure 11] It is a diagram showing the unit cost DB of the server shown in FIGS. 1 to 4. [Figure 12] It is a diagram showing the activity amount DB of the server shown in FIGS. 1 to 4. [Figure 13] It is a diagram showing the dashboard screen of the server shown in FIGS. 1 to 4.

Embodiments for Carrying Out the Invention

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a diagram showing an overview of this service that can be realized by an information processing system to which a server according to an embodiment of the information processing apparatus of the present invention is applied. As shown in FIG. 1, in this service of the present embodiment, the server 1 is connected to each user terminal 2 of a plurality of companies via a network, and provides a service for calculating and visualizing GHG emissions. An important feature of this service is the data linkage function corresponding to the Tier structure in the supply chain.

[0011] Specifically, the user terminal 2-1 of the Tier2 company (upstream company / supplier) uploads all energy consumption data related to the manufacture of parts such as PT substrates to the server 1. The server 1 automatically apportions and calculates the total GHG emissions generated during the manufacture of 100 PT substrates manufactured by the Tier2 company, and calculates the GHG emissions per unit. The calculated data is stored in the database as delivery data.

[0012] On the one hand, when manufacturing products such as main boards, the user terminal 2-2 of Tier 1 enterprises (downstream enterprises and manufacturers) inputs the code of Tier 2 enterprises (e.g., K02) and the product code of PT substrates (e.g., P01) into the connection master. By this input, the server 1 automatically acquires the corresponding GHG emission data from the delivery data of Tier 2 enterprises. When Tier 1 enterprises use 50 PT substrates, the GHG emissions for 50 pieces are automatically calculated and calculated as Tier 1 enterprises' SCOPE3.

[0013] Through such data linkage between enterprises, the grasp of the GHG emissions of the entire supply chain, which conventionally required manual questionnaire surveys and individual data input, is automated and made more efficient. Also, depending on the contract form (primary and secondary contracts), it is possible to control the scope of data disclosure between enterprises.

[0014] Figure 2 is a diagram showing the configuration of an information processing system to which a server according to an embodiment of the information processing apparatus of the present invention is applied.

[0015] As shown in Figure 2, the information processing system of this embodiment has a server 1 and a plurality of user terminals 2-1, 2-2, ··· 2-n connected via a network N. The user terminal 2 is a terminal used by the persons in charge of each enterprise (Tier 1 enterprises, Tier 2 enterprises, etc.).

[0016] Figure 3 is a diagram showing the hardware configuration of the server in the information processing system of Figure 2. As shown in Figure 3, the server 1 includes a CPU 11, a ROM 12, a RAM 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0017] The CPU 11 executes various processes according to the program recorded in the ROM 12 or the program loaded from the storage unit 18 into the RAM 13. Specifically, the CPU 11 performs various processes such as input template provisioning, data acquisition, GHG emission calculation, visualization, data provisioning, and data output. These processes enable automatic calculation of GHG emissions across the entire supply chain and inter-company collaboration.

[0018] RAM13 also stores data necessary for CPU11 to perform various processes. For example, RAM13 temporarily stores energy usage data, conversion factor data, calculated GHG emission data, customer information data, activity data, product master data, and consolidated master data. RAM13 also holds intermediate results of apportionment calculations and emission calculations performed by CPU11.

[0019] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. The bus 14 functions as a path for high-speed transmission of data and control signals between each component.

[0020] The input / output interface 15 is connected to an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20. The input unit 16 receives signals from input devices such as a keyboard or mouse. The output unit 17 sends signals to output devices such as a display or printer. The storage unit 18 consists of a large-capacity storage device such as a hard disk or SSD, and stores various databases and programs. The communication unit 19 sends and receives data to and from the user terminal 2 via the network N. The drive 20 has a slot and reads data from or writes data to the removable media 30 inserted (connected) into that slot. The removable media 30 consists of, for example, a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory. By using the removable media 30, it becomes possible to back up large amounts of master data and past emission data, and to exchange data with other systems.

[0021] Figure 4 is a functional block diagram showing the functional configuration of the server in Figure 3 that constitutes the information processing system in Figure 2. As shown in Figure 4, the CPU 11 of server 1 functions as follows: input template provision unit 51, data acquisition unit 52, GHG emission calculation unit 53, visualization unit 54, data provision unit 55, and data output unit 56.

[0022] Furthermore, one area of ​​the storage unit 18 of server 1 stores the following: energy consumption DB71, conversion factor DB72, GHG emissions DB73, customer information DB74, activity level DB75, template DB76, unit consumption DB77, emissions DB78, delivery data DB79, product master 81, parts / raw materials / logistics / waste master 82, equipment master 83, and linkage master 84. The product master 81, parts / raw materials / logistics / waste master 82, equipment master 83, and linkage master 84 are referred to as a master group.

[0023] The input template provider unit 51 provides the user terminal 2 with an input template in spreadsheet software format for inputting energy consumption data. Specifically, the input template provision unit 51 obtains Excel format input format templates (hereinafter referred to as "Excel files") from the template DB 76 and provides the obtained Excel files (for example, master input format, unit input format, activity level input format) to the user terminal 2. The Excel files provided to the user terminal 2 include multiple sheets such as a product master sheet, a parts / raw materials / logistics / waste master sheet, an equipment master sheet, and a linkage master sheet. Note that Excel is a registered trademark.

[0024] Regarding the method of providing the input template, an Excel file may be downloaded from server 1 to user terminal 2, or a platform (web page) provided by server 1 may be displayed on user terminal 2, and the input template screen (hereinafter referred to as the "Excel screen") (see Figure 5) may be displayed in response to user instructions on the web page, allowing the user to directly input data.

[0025] The data acquisition unit 52 acquires data, including energy usage data entered by the user into the input template. Specifically, the system receives an Excel file uploaded from user terminal 2, stores energy consumption data in energy consumption DB71, activity data in activity DB75, and unit energy data in unit energy DB77. Furthermore, the data acquisition unit 52 acquires data on the total energy consumption of the first company (for example, the Tier 2 company in Figure 1) and data on the activity volume of each trading partner, including the amount of products supplied (delivery quantity) from the first company to a specific trading partner company (for example, the Tier 1 company in Figure 1), and stores them in the trading partner information DB 74.

[0026] The GHG emissions calculation unit 53 calculates GHG emissions based on data including energy consumption data. Specifically, the GHG emission calculation unit 53 obtains energy consumption data from the energy consumption DB 71, obtains the corresponding conversion factor from the conversion factor DB 72, calculates the GHG emissions by multiplying the two, and stores it in the GHG emission DB 73. Furthermore, the GHG emission calculation unit 53 classifies the data, including energy consumption data, into one of three categories—SCOPE1, SCOPE2, or SCOPE3—according to the type of energy, and calculates the GHG emissions. Furthermore, the GHG emission calculation unit 53 calculates the total GHG emissions for the company from the company's total energy consumption data, and also calculates the company's allocated GHG emissions corresponding to a specific trading partner company by apportioning the total GHG emissions based on trading partner activity data. The calculation results of the allocated GHG emissions for each trading partner (allocated GHG emissions) are then stored in the emissions DB 78 and the delivery data DB 79. For example, if a Tier 2 company emits 1000 kg-CO2 of GHG per month and produces a total of 100 products, that amounts to 10 kg-CO2 per product, and this value is linked. If a Tier 1 company uses 50 products from the Tier 2 company, then 50 products × 10 kg-CO2 = 500 kg-CO2 is calculated as the GHG emissions for the Tier 1 company corresponding to the Tier 2 company's products.

[0027] The visualization unit 54 visualizes the calculated GHG emissions. Specifically, the visualization unit 54 acquires data from the GHG emission DB 73 and emission DB 78, generates a dashboard screen that displays at least one of the following: a total overview of calculated GHG emissions, a time-series trend analysis, and a trend analysis by energy type, and displays it on the user terminal 2.

[0028] The data provision unit 55 provides allocated GHG emissions to specific trading partners. It retrieves allocated data for trading partners from the delivery data DB 79 and provides it to the user terminal 2 of the trading partner company registered in the trading partner information DB 74.

[0029] The data output unit 56 outputs the calculated GHG emission data in at least one of several file formats, including at least Excel format, CSV format, and image format. It acquires data from GHG emission DB73 and emission DB78 and outputs it to files in various formats according to the user's request. Image format files include PDF files.

[0030] Figure 5 shows the input format screen of the server shown in Figures 1 to 4. As shown in Figure 5, the server 1 provides the user terminal 2 with an input format screen 101 having multiple tabs for each master input format. On the input format screen 101, users can input into each master input format by switching tabs. The master input format consists of master sheets for products, raw materials, equipment, connections, etc. In addition, there are sheets for unit consumption input, activity level input, etc. The master sheets are updated upon implementation and as needed, the unit consumption input sheets are updated annually to monthly, and the activity level input sheets are updated monthly. All of these input sheets are provided in Excel format, allowing users to edit them using their preferred spreadsheet software.

[0031] Figure 6 shows the product master of the servers shown in Figures 1 to 4. The data entered into the product master sheet among the master sheets is stored in the product master 81 shown in Figure 6. The product master 81 stores data related to the product. Specifically, the product master 81 includes fields such as production date, product name, product code, company manufacturing unit, unit conversion factor, and unit conversion (pieces), and data is stored in each field. For example, a Tier 2 company manages PT boards (product code: P01) on a piece-by-piece basis, and a Tier 1 company manages main boards (product code: P02) similarly on a piece-by-piece basis.

[0032] Figure 7 shows the component, raw material, logistics, and waste master data for the server shown in Figures 1 to 4. The data entered into the parts, raw materials, logistics, and waste master sheet among the master sheets is stored in the parts, raw materials, logistics, and waste master 82 shown in Figure 7. The parts, raw materials, logistics, and waste master 82 stores data related to parts, raw materials, logistics, and waste. Specifically, the parts, raw materials, logistics, and waste master 82 includes fields such as raw material / classification name, raw material / classification code, major classification code, major classification name, competitor name code, competitor name, competitor product code, competitor product name, and recycling flag, and data is stored in each of these fields. For example, when a Tier 1 company uses a PT substrate as a component, entering "K02" (the code for the Tier 2 company) in the "Other Company Name Code" field and "P01" (the product code for the PT substrate) in the "Other Company Product Code" field enables automatic coordination between supply chains.

[0033] Figure 8 shows the equipment master 83 of the server shown in Figures 1 to 4. The data entered into the equipment master sheet among the master sheets is stored in the equipment master 83 shown in Figure 8. The equipment master 83 stores data related to the equipment used to manufacture the product. Specifically, the equipment master 83 includes fields such as equipment name, equipment code, major equipment category code, major equipment category, equipment classification code, equipment classification, energy code, energy name, and energy unit, and data is stored in each field. For example, the molding machine (S02) is set to use heavy oil and electricity as energy sources.

[0034] Figure 9 shows the linked master of the servers shown in Figures 1 to 4. The data entered into the linked master sheet among the master sheets is stored in the linked master 84 shown in Figure 9. The linked master 84 stores data related to the allocation for each company by linking the data from each of the above masters. Specifically, the consolidated master 84 includes fields such as product code, product name, in-house manufactured / other code, in-house manufactured / other category, product / equipment / raw material / logistics / waste name code, product / equipment / raw material / logistics / waste name, energy code, energy name, allocation flag, unit, and product / equipment / raw material / logistics / waste category, and data is stored in each of these fields. For example, if you select "Black Circle" in the data field for the allocation flag, the energy will be calculated by allocating the values ​​entered for each company to the locations specified by the allocation flag based on the production volume. For instance, if a Tier 1 company uses 10,000 kW of electricity in total at one factory, and produces 100 mainboards (P02) and 100 other products, the energy will be allocated proportionally according to the activity level. In this case, 5,000 kW of electricity will be allocated to each product.

[0035] Figure 10 shows the supply chain collaboration flow of the servers shown in Figures 1 to 4. As shown in Figure 10, the supply chain collaboration flow consists of three steps, from STEP 1 to STEP 3.

[0036] In STEP 1, companies in the supply chain participate. Tier 2 companies (upstream suppliers) and Tier 1 companies (downstream manufacturers) each obtain company codes (K02, K01) and participate in this service.

[0037] In STEP 2, each company enters its own data. Tier 2 companies enter data such as PT substrate (P01) in the product master, ceramic (G01) in the raw materials, processing machine (S01) and molding machine (S02) in the equipment, and production volume of 100 units in the activity data. The system automatically calculates the CO2 emissions per PT board and stores it in the delivery data DB79. Tier 1 companies register the main board (P02) in the product master 81, specify K02 / P01 as the third-party collaboration, and input 100 PT boards for use. The system automatically obtains the emission factor from the Tier 2 company's delivery data and calculates the CO2 emissions for 100 boards.

[0038] In STEP 3, companies input their activity levels with their business partners. Each company inputs its activity levels with each business partner (e.g., quantity delivered), and then allocates its total CO2 emissions to each business partner. This allows each business partner to accurately understand the CO2 emissions attributable to them.

[0039] Here, after the input of Tier 2 companies is complete, we will explain the data input process for Tier 1 companies and the subsequent data generation process. First, Tier 1 companies download the master input format.xlsx from Server 1. Next, register the data in the master input format.xlsx file. In the product master sheet, enter the main board (product code: P02, unit: piece), which is the product to be manufactured. In the parts, raw materials, logistics, and waste master sheet, register that the Tier 1 company will use PT boards manufactured by the Tier 2 company as raw materials. At this time, by entering "K02" (the code of the Tier 2 company) in the other company name code field and "P01" (the product code of the PT board) in the other company product code field, the system will automatically retrieve the other company name, other company product name, and other company product production unit from the transfer data generated when the Tier 2 company was entered.

[0040] The contractual structure, which establishes a primary and secondary relationship between Tier 1 and Tier 2 companies, enables this automated linkage function within the supply chain. Furthermore, even if a contractual relationship exists, identifying a product requires a product code set by the Tier 2 company. Therefore, if a Tier 2 company does not want to disclose a product to a Tier 1 company, it can exclude that product from the collaboration by keeping the product code confidential. Furthermore, the necessary data is entered into the equipment master sheet and the linked master sheet. Next, when the master input format .xlsx file containing the entered data is uploaded to server 1, the system processes and stores the master data in the product master DB81, parts / raw materials / logistics / waste master DB82, equipment master DB83, and linked master DB84, respectively.

[0041] Next, download the Unit Cost Input Format.xlsx file from Server 1 and register the data in it. At this time, the emission coefficient (reference coefficient) for PT substrates linked from Tier 2 companies will be automatically displayed. Specifically, the average for the most recent 12 months, the average for the most recent period from April to March, and secondary designated values ​​(values ​​certified by the certification body) are displayed as reference values, allowing Tier 1 companies to set appropriate unit costs by referring to these values. When the unit cost input format is uploaded to Server 1, the system processes and stores the unit cost data in Unit Cost DB77.

[0042] Furthermore, when you download the Activity Input Format.xlsx from Server 1, the data linked from Tier 2 companies will already be reflected. You register actual data such as mainboard production volume, energy consumption of each piece of equipment, and PT board usage in the Activity Input Format.xlsx. For example, the user inputs data indicating that 100 main boards (P02) were produced, electricity was used in the processing machine (S01), city gas was used in the molding machine (S02), and 100 PT substrates (K02 / P01) were used.

[0043] When a user uploads an activity input format file (.xlsx) containing their activity data to Server 1, the activity data is stored in Activity DB75. Furthermore, the system calculates CO2 emissions from the activity data (such as product production quantities) read from Activity DB75 and the emission coefficients previously entered by the user, and stores this calculation in Emission DB78. In terms of specific processing on the server, the data acquisition unit 52 acquires the emission factor per product for each product manufactured by the company to which the user belongs (e.g., a Tier 1 company) and the production quantity (activity level) of the product at the time of production by that company. The GHG emission calculation unit 53 calculates the CO2 emissions emitted when producing the product based on the acquired emission factor and production quantity. The data provision unit 55 then provides the calculated CO2 emissions per production unit (calculated by dividing the CO2 emissions of the product by the production quantity) and the emission factor to a specific trading partner company (e.g., a company downstream of the Tier 1 company or other partner companies). For example, in the manufacturing of mainboards, CO2 emissions are calculated for each energy type in the categories of products, equipment, raw materials, logistics, and waste. For instance, in the equipment category, CO2 emissions from electricity use in processing machines and CO2 emissions from city gas use in molding machines are calculated, while in the raw materials category, the CO2 emissions from the amount used for 100 PT substrates are calculated based on the CO2 emission coefficients of PT substrates provided by Tier 2 companies.

[0044] Subsequently, the system processes the data for delivery to further downstream companies from the Tier 1 company and stores it in the delivery data DB79. At this time, the CO2 emissions per mainboard are calculated and the value obtained by dividing it by the number of units produced is stored. Finally, the generated data can be viewed using the dashboard function on Server 1. In this way, once Tier 2 companies have completed their input, Tier 1 companies can input the necessary data, and the CO2 emissions across the entire supply chain will be automatically linked and aggregated, allowing for an accurate understanding of each company's emissions.

[0045] Server 1 has five automation functions implemented, numbered 1 through 5. Specifically, these include: 1) automatic calculation of CO2 emissions (activity level × conversion factor), 2) automatic generation of transfer data (unit-based data allocated by production volume), 3) automatic linkage of upstream data (downstream companies do not need to manually input data), 4) automatic execution of allocation calculations (automatic allocation according to usage), and 5) automatic assurance of traceability (automatic tracking from Tier 2 to Tier 1).

[0046] Here, we will explain the database used to implement the above automation function. Figure 11 shows the unit cost database for the servers shown in Figures 1 to 4. The data entered on the unit cost input sheet screen of user terminal 2, or the data in the downloaded Excel file related to unit costs, is stored in the unit cost DB77 shown in Figure 11. Specifically, the Unit Intensity DB77 includes fields such as year and month, energy code, energy name, emission factor, unit intensity (for addition), emission intensity for CFP calculation, CO2 units, reference count (previous input: previous input value), reference factor (average of the most recent 12 months), reference factor (average of the most recent March-April months), reference factor (secondary designated value), secondary designated period (From), secondary designated period (To), standard value, CO2 data classification, and PDS standard value. Data is stored in the data field for each of these fields. Unit intensity is used when changing emission factors at the start of a new fiscal year or when changing contracts with power companies. Emission factors are entered by the user. For example, if the emission factor for heavy oil (E01) is 0.00249 and the emission factor for electricity (E02) is 0.00054, these newly entered unit data are registered in the Unit Factor DB77. Reference figures such as the previous input value, the average for the most recent 12 months, the average for the most recent March-April months, and secondary designated values ​​are displayed, which can assist the user in deciding which emission factors to enter. In addition, standard values ​​may also be displayed. Furthermore, when a Tier 1 company inputs unit consumption data, the emission coefficient for the PT substrate (P01) (0.06207 in this example) is automatically retrieved from the unit consumption DB77 based on data shared by a Tier 2 company and displayed on the unit consumption input sheet screen of user terminal 2. This allows for visual confirmation of data sharing across the supply chain.

[0047] Figure 12 shows the activity database of the servers shown in Figures 1 to 4. The data entered on the activity level input sheet screen of user terminal 2, or the data from the downloaded Excel file related to activity levels, is stored in the activity level DB75 shown in Figure 12. Specifically, the Activity Data DB75 includes fields for actual values ​​such as year and month, product code, product name, production volume, electricity consumption, and city gas consumption. The actual production volume, energy consumption, and other data entered into the data fields for each field are stored. For example, the main board (P02) of our company's product has a production volume of 100 units, the processing machine (S02) uses heavy oil as its energy source, and its activity level is stored as, for example, 2000L.

[0048] Figure 13 shows the dashboard screen of the server shown in Figures 1 to 4. As shown in Figure 13, the dashboard screen 102 displays data obtained from GHG emission DB73 and emission DB78, including total CO2 emissions (bar graph showing monthly trends), emissions by SCOPE (pie chart showing breakdown of SCOPE 1, 2, and 3), energy type breakdown (horizontal bar graph showing proportions of electricity, city gas, heavy oil, etc.), and time series trends (line graph showing year-on-year trends).

[0049] Additionally, the user terminal 2 displays the checkbox screen 103. The checkbox screen 103 has fields for items such as date, user, scope, and energy, and each field has a checkbox for that item. For example, the date field has input fields for the start date and end date, allowing you to set (restrict) a period for displaying data. The user's field includes checkboxes for individual companies such as "Company A," "Company B," "Company C," "Company D," and "Company E," as well as a checkbox for "All Companies." The scope section includes checkboxes for each scope classification, such as "SCOPE1," "SCOPE2," and "SCOPE3." The energy section includes checkboxes for each energy category, such as "gasoline," "gasoline (volatile oil)," "naphtha," "kerosene," "diesel fuel," "heavy oil A," "LPG," "liquefied petroleum gas (LPG)," and "petroleum hydrocarbon gas (butane)."

[0050] By checking the desired items in the desired item fields, the automated function extracts data for each desired item and generates graphs based on that data, allowing the user to view graphs categorized by their preferred items.

[0051] This server 1's dashboard function enables multifaceted analysis and review of emissions data generated from input data. It provides visualization tailored to user needs, from summary displays for management to detailed analyses for field personnel. Note that the display example shown in Dashboard Screen 102 above (pie chart, bar graph, line graph, etc.) is merely an example, and other display formats (such as displaying individual graphs separately) may also be used.

[0052] Although one embodiment of the present invention has been described above, the present invention is not limited to the embodiments described above, and any modifications, improvements, etc. that can achieve the objectives of the present invention are considered to be included in the present invention.

[0053] Furthermore, the system configuration shown in Figure 2 and the hardware configuration of Server 1 shown in Figure 3 are merely illustrative examples for achieving the objectives of the present invention and are not particularly limited. Furthermore, the functional block diagram shown in Figure 4 is merely illustrative and not particularly limiting. In other words, it is sufficient that the information processing system in Figure 2 has the functionality to execute the various processes described above as a whole, and the functional blocks and databases used to realize this functionality are not particularly limited to the example in Figure 4.

[0054] Furthermore, the location of the functional blocks and database is not limited to Figure 4 and can be arbitrary. For example, at least a portion of the functional blocks and database located on the server 1 side may be provided on the user terminal 2, or they may be provided on other information processing devices (not shown) connected to the network N.

[0055] Furthermore, the series of processes described above can be executed by hardware or by software. Furthermore, a single functional block may consist of hardware alone, software alone, or a combination of both.

[0056] When a series of processes are executed by software, the programs that make up that software are installed on a computer or other device from a network or storage medium. The computer may be a computer that is built into dedicated hardware. Furthermore, a computer can be any computer capable of performing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0057] Such recording media containing programs consist not only of removable media 30, as shown in Figure 3, which are distributed separately from the main unit of the device to provide the program to the user, but also of recording media that are pre-installed in the main unit of the device and provided to the user.

[0058] In this specification, the step of describing a program to be recorded on a recording medium includes not only processes that are performed chronologically in that order, but also processes that are not necessarily performed chronologically, but are executed in parallel or individually.

[0059] In summary, the information processing device to which the present invention applies only needs to have the following configuration, and can take various forms. (1) That is, the information processing device to which the present invention is applied (for example, Server 1 in Figures 2 to 4) is An input template providing means (for example, the input template providing unit 51 in Figure 4) provides an input template (for example, an Excel screen or Excel file) in a spreadsheet software format (for example, the Excel format in Figure 5) for inputting energy consumption data to a user terminal (for example, user terminal 2 in Figure 2), A data acquisition means (for example, the data acquisition unit 52 in Figure 4) that acquires data including energy usage data entered by the user into an input template, A greenhouse gas emission calculation means (for example, the GHG emission calculation unit 53 in Figure 4) that calculates greenhouse gas emissions based on data including energy consumption data, A visualization means for visualizing the calculated greenhouse gas emissions (for example, the visualization unit 54 in Figure 4), Having that will suffice.

[0060] In this way, the familiar interface of spreadsheet software avoids data loss and input control problems that occur with web forms due to screen refreshes, efficient data entry is possible through free movement between cells and copy-and-paste functions, and visualization of greenhouse gas emissions makes it easier for companies to understand their emission status and consider reduction measures.

[0061] (2) Furthermore, the input template providing means (for example, the input template providing unit 51 in Figure 4) provides an Excel format template (for example, the input format screen or Excel file in Figure 5) as an input template. It is possible.

[0062] This allows for immediate use in many companies without the need to install any special software, as it utilizes the Excel format, the most widely used spreadsheet software.

[0063] (3) Furthermore, the greenhouse gas emission calculation means (for example, the GHG emission calculation unit 53 in Figure 4) classifies the data, including energy consumption data, into one of the categories of SCOPE1, SCOPE2, and SCOPE3 (for example, the SCOPE classification in Figure 13) according to the type of energy, and calculates the greenhouse gas emissions. It is possible.

[0064] This enables emissions management in accordance with international standards that comply with the GHG protocol, and can be directly used for preparing corporate environmental reports and reporting to the CDP (Carbon Disclosure Project).

[0065] (4) Furthermore, the data acquisition means (for example, the data acquisition unit 52 in Figure 4) acquires the total energy consumption data of the first company (for example, the Tier 2 company in Figure 1) and the activity data by trading partner (for example, the data specified by the allocation flag in Figure 9), which includes the amount of products supplied (delivery quantity) from the first company to a specific trading partner company (for example, the Tier 1 company in Figure 1), The greenhouse gas emission calculation means (for example, the GHG emission calculation unit 53 in Figure 4) calculates the company's total greenhouse gas emissions from the company's total energy consumption data, and also calculates the company's allocated greenhouse gas emissions corresponding to a specific trading partner company by apportioning the company's total greenhouse gas emissions based on trading partner activity data. The system further includes a data provision means (for example, the data provision unit 55 in Figure 4) for providing proportional greenhouse gas emissions to specific trading partners. It is possible.

[0066] This enables efficient CO2 emission management across the entire supply chain, eliminating the need for individual companies to conduct surveys of upstream companies and allowing for the collection of accurate and timely SCOPE3 data.

[0067] (5) Furthermore, the system further includes a data output means (for example, a data output unit 56 in Figure 4) that outputs the calculated greenhouse gas emission data in at least one of several file formats, including at least Excel format, CSV format, and image format (for example, the various output formats in Figure 13), It is possible.

[0068] This allows data to be output in the most suitable format for each purpose, such as environmental reports, internal presentations, and reports to government agencies, reducing the effort required for secondary processing.

[0069] (6) Furthermore, the visualization means (for example, the visualization unit 54 in Figure 4) generates a dashboard screen that displays at least one of the following: a total understanding of the calculated greenhouse gas emissions, a time-series trend analysis, and a trend analysis for each energy type (for example, the dashboard screen in Figure 13). It is possible.

[0070] This enables multi-layered emissions management, from a comprehensive perspective for management to detailed analysis at the operational level, allowing for quantitative setting of reduction targets and evaluation of the effectiveness of measures. [Explanation of symbols]

[0071] 1...Server, 2...User terminal, 11...CPU, 12...ROM, 13...RAM, 14...Bus, 15...Input / Output interface, 16...Input unit, 17...Output unit, 18...Storage unit, 19...Communication unit, 20...Drive, 30...Removable media, 51...Input template provision unit, 52...Data acquisition unit, 53...GHG emission calculation unit, 54...Visualization unit, 55...Data 56...Data Output Section, 71...Energy Consumption DB, 72...Conversion Factor DB, 73...GHG Emissions DB, 74...Customer Information DB, 75...Activity Level DB, 76...Template DB, 77...Unit Cost DB, 78...Emissions DB, 79...Delivery Data DB, 81...Product Master, 82...Parts / Raw Materials / Logistics / Waste Master, 83...Equipment Master, 84...Linking Master, N...Network

Claims

1. An input template providing means that provides the user with an input template in spreadsheet software format for inputting energy consumption data, A data acquisition means that acquires data including company energy consumption data entered into the input template provided to the user terminal, A greenhouse gas emissions calculation means for calculating a company's greenhouse gas emissions based on data including the aforementioned energy consumption data, A visualization means for visualizing the calculated greenhouse gas emissions, An information processing device equipped with the following features.

2. The input template providing means provides an Excel format template as the input template. The information processing apparatus according to claim 1.

3. The greenhouse gas emission calculation means classifies the data, including the energy consumption data, into one of the following categories, SCOPE1, SCOPE2, or SCOPE3, according to the type of energy, and calculates the greenhouse gas emissions. The information processing apparatus according to claim 1.

4. The data acquisition means acquires data on the first company's total energy consumption and data on the activity volume of each trading partner, including the amount of products supplied from the first company to specific trading partners. The greenhouse gas emission calculation means calculates the total greenhouse gas emissions of the company from the total energy consumption data of the company, and calculates the allocated greenhouse gas emissions of the company corresponding to a specific trading partner company by apportioning the total greenhouse gas emissions of the company based on the activity data of each trading partner. The system further comprises a data provision means for providing the aforementioned apportioned greenhouse gas emissions to the aforementioned specific trading partner company. The information processing apparatus according to claim 1.

5. The system further includes a data output means for outputting the calculated greenhouse gas emission data in at least one file format from among multiple file formats, including at least Excel format, CSV format, and image format. The information processing apparatus according to claim 1.

6. The visualization means generates a dashboard screen that displays at least one of the following: a total overview of calculated greenhouse gas emissions, a time-series trend analysis, and a trend analysis for each energy type. The information processing apparatus according to claim 1.

7. In an information processing method executed by an information processing device, An input template provision step provides an input template in spreadsheet software format for inputting energy consumption data to a user terminal, A data acquisition step that acquires data including energy usage data entered by the user into the input template, A greenhouse gas emissions calculation step that calculates greenhouse gas emissions based on data including the aforementioned energy consumption data, A visualization step to visualize the calculated greenhouse gas emissions, Information processing methods including

8. On the computer, An input template provision step provides an input template in spreadsheet software format for inputting energy consumption data to a user terminal, A data acquisition step that acquires data including energy usage data entered by the user into the input template, A greenhouse gas emissions calculation step that calculates greenhouse gas emissions based on data including the aforementioned energy consumption data, A visualization step to visualize the calculated greenhouse gas emissions, A program that executes control processes, including those mentioned above.

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