Information processing system, information processing method and program

Abstract

To enable supporting greenhouse gas reduction.SOLUTION: An information processing system includes: an acquisition part for acquiring environmental information including emission amount information relating to greenhouse gas emission amounts, social information, and governance information; a solution storage part for storing at least solution information relating to greenhouse gas reduction means; an extraction part for extracting solution information matching the emission information; and a provision part for providing the extracted solution information to users.SELECTED DRAWING: Figure 3

Description

[Technical field]

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

[0002] Solutions to reduce carbon dioxide emissions are being introduced (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2015-219542 A Summary of the Invention [Problem to be solved by the invention]

[0004] It's hard to know what solutions are available.

[0005] The present invention has been made in view of the above background, and has an object to provide a technique that can assist in reducing greenhouse gas emissions. [Means for solving the problem]

[0006] The main invention of the present invention for solving the above problem is an information processing system comprising an acquisition unit that acquires environmental information including emission information on greenhouse gas emissions, social information, and governance information, a solution storage unit that stores at least solution information related to means of reducing the greenhouse gases, an extraction unit that extracts the solution information that matches the emission information, and a provision unit that provides the extracted solution information to a user.

[0007] Other problems and solutions disclosed in this application will be made clear in the description of the preferred embodiments of the invention and the drawings. Effect of the Invention

[0008] The present invention can assist in reducing greenhouse gas emissions. [Brief description of the drawings]

[0009] [Figure 1] 1 is a diagram illustrating an example of the overall configuration of an information processing system according to an embodiment of the present invention. [Diagram 2] FIG. 2 illustrates an example of a hardware configuration of a management server 200. [Diagram 3] FIG. 2 illustrates an example of the software configuration of a management server 200. [Figure 4] FIG. 13 illustrates a first modified example of the software configuration of the management server 200. [Diagram 5] FIG. 13 illustrates a second modified example of the software configuration of the management server 200. [Figure 6] FIG. 13 is a conceptual diagram showing data acquisition and data linkage in the analysis layer 270. [Figure 7] This is an image diagram showing the construction of operational DX and ESG data pipelines in the analysis layer 270. [Figure 8] FIG. 2 is a diagram illustrating the operation of the management server 200. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Fig. 1 is a diagram showing an example of the overall configuration of an information processing system according to this embodiment. The information processing system according to this embodiment is configured to include a management server 200. The management server 200 is communicatively connected to a user terminal 100 via a communication network 300. The communication network is, for example, the Internet, which is constructed using a public telephone line network, a mobile phone line network, wireless communication paths, Ethernet (registered trademark), and the like. When this information processing system is used by users, a buyer and a supplier, the user terminal 100 is the terminal used by the buyer, and the user terminal 101 is the terminal used by the supplier.

[0011] The user terminal 100 is a computer operated by a user. The user terminal 100 may be, for example, a smartphone, a tablet computer, or a personal computer.

[0012] The management server 200 may be a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing.

[0013] <Management Server> FIG. 2 is a diagram showing an example of the hardware configuration of the management server 200. Note that the illustrated configuration is an example, and other configurations may be used. The management server 200 includes a CPU 201, a memory 202, a storage device 203, a communication interface 204, an input device 205, and an output device 206. The storage device 203 is, for example, a hard disk drive, a solid state drive, or a flash memory that stores various data and programs. The communication interface 204 is an interface for connecting to the communication network 3, and is, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line network, a wireless communication device for wireless communication, a USB (Universal Serial Bus) connector or an RS232C connector for serial communication, etc. The input device 205 is, for example, a keyboard, a mouse, a touch panel, a button, a microphone, etc. that input data. The output device 206 is, for example, a display, a printer, a speaker, etc. that output data. Each functional unit of the management server device 2 described later is realized by the CPU 201 reading a program stored in the storage device 203 into the memory 202 and executing it, and each storage unit of the management server 200 is realized as part of the storage area provided by the memory 202 and the storage device 203.

[0014] FIG. 3 is a diagram showing an example of the software configuration of the management server 200. The management server 200 includes a data collection layer 250, an analysis layer 270, a data management and dashboard layer 240, and a solution layer 260. The analysis layer 270 is an example of one analysis unit, but may be composed of multiple analysis units as shown in Modification 1 of FIG. 4. For example, the analysis layer 270 may be composed of an analysis unit 270E1 for E1, an analysis unit 270E2 for E2, an analysis unit 270E3 for E3, an analysis unit 270E4 for E4, an analysis unit 270E5 for E5, an analysis unit 270S1 for S1, an analysis unit 270S2 for S2, an analysis unit 270S3 for S3, an analysis unit 270S4 for S4, and an analysis unit 270G for G. Note that the management server 200 may be used instead of one analysis unit, for example, the analysis unit 270E1. In this case, the management server 200 includes a data collection layer 250, an analysis layer 270, a data management and dashboard layer 240, and a solution layer 260 outside the management server 200. The analysis layer 270 may be configured by an analysis unit for environmental information (analysis unit 270E for E1 to E5), an analysis unit for social information (analysis unit 270S for S1 to S4), and an analysis unit 270G for governance information. The data collection layer 250 is also called an acquisition unit 250. The analysis layer 270 is also called an analysis unit 270. The data management and dashboard layer 240 is also called an output unit 240 or a provision unit 240. The solution layer 260 is also called a solution unit 260.

[0015] 5, a management server 201 may be provided, and information may be transmitted and received between the management server 201 and the analysis layer 270, and between the management server 201 and the data management / dashboard layer 240. In this case, the management server 201 may be the management server 200 of the second embodiment.

[0016] The data collection layer 250 performs real-time or periodic data collection. The collected data are ten items: E1, E2, E3, E4, E5, S1, S2, S3, S4, and G. The collected data are not limited to these ten items. E1, E2, E3, E4, and E5 are information related to the environment. S1, S2, S3, and S4 are information related to society. G is information related to governance.

[0017] E1 is climate change data. There are two types of climate change data: transition risk type and physical risk type. Examples of climate change data of the physical risk type include location information of the target base, base attribute information (building information, etc.), financial information (asset value, etc.), greenhouse gas emissions, etc.

[0018] E2 is pollution data. Examples of pollution data are: emissions, transfers, consumption, waste records of hazardous substances, establishments and conditions of known pollution, emissions of air pollutants, emissions to water, emissions of inorganic pollutants, emissions of ozone depleting substances, microplastics, total amount of substances of concern generated or used during production, total amount of substances of concern procured, total amount of substances of concern shipped, significant risks, opportunities and financial impacts arising from pollution-related impacts, operational and capital expenditures related to accidents and deposits, incidents (e.g. interruption of production resulting in pollution), targets for determining regional ecological thresholds (TNFD / SBTN based), site location information of adopted policies, contextual information of targets and response to shortcomings in DNSH criteria, etc.

[0019] E3 is data on water and marine resources. Examples of data on water and marine resources are water withdrawals, water discharges, information on bases in water-stressed areas, water recycling rate, COD (biochemical oxygen demand), BOD (chemical oxygen demand), targets for water and marine resources (TNFD / SBTN based), reduction targets for water withdrawals, reduction targets for water discharges, total water use in areas with significant water risks, information on water quality and quantity in the watershed, total amount of water recycled and reused, total amount of water storage and changes in storage, potential financial impacts of significant risks / opportunities, and exposure to related products and services.

[0020] E4 is biodiversity data. Examples of biodiversity data are: location of business activities, business sector information, financial information (e.g. asset values), TNFD / SDPI based targets, avoidance / minimization / restoration / offset targets, area of ​​land permanently protected, area of ​​land restored, number of sites with improved ecosystem integrity, number and area of ​​material sites, land use based on LCA, change in land cover over time (e.g. deforestation), changes in ecosystem management over time, changes in spatial configuration of landscapes, changes in structural connectivity of ecosystems, financial impact of risks / opportunities, products / services exposed, etc.

[0021] E5 is circular economy data. Examples of circular economy data are: amount and percentage of recycled materials in procurement, total amount and percentage of waste, repairability, degradability, SBTN-based target setting, resource use and circular economy related targets (e.g. increasing circular design, increasing circular material usage), ecological thresholds and quotas, sustainable procurement related targets, targets for the value chain, absolute and percentage weight of renewable input materials, weight of products and materials (non-virgin) that are reused or recycled in both absolute and percentage values, information on materials discharged from production process (e.g. durability, reusability, repairability, degradability, remanufacturability / refurbishability), total amount and percentage of waste (hazardous / non-hazardous), financial impact of significant risks / opportunities, related products / services at risk, etc.

[0022] S1 is the data of your company's employees. Examples of your company's employee data include data in your company's HR system, history of interactions with labor unions, employee incidents, etc.

[0023] S2 is data on employees in the value chain. An example of data on employees in the value chain is data collected in the form of a questionnaire based on the SAQ established by the United Nations (customized for each industry and company). In the following explanation, the value chain will be referred to as "VC."

[0024] S3 is data on affected communities. S4 is data on consumers and end customers. G is data on business activities. The priority of data to be collected is as follows: E1 for transition risks is the top priority, followed by E1 for physical risks, E3, E4, S2, S3, S4, E5, E2, S1, and G.

[0025] The collected data may also include business partner data, such as company name and financial data, personnel data, recycling data, human rights data, financial data, and design data.

[0026] The data collection layer 250 can be connected to ERP (Enterprise Resource Planning) and can easily collect internal data. The data collection layer 250 can also collect external data. The data collection layer 250 can color-code collected data. Examples of color-coding include standardizing data definitions, recognizing data with high materiality, unifying awareness, understanding double counting, and erasing. The data collection layer 250 can link data. Examples of data linking include collaborative editing within a team or with an external consultant, output to an external analysis partner via API, and connection to a financial accounting system, etc. The data collection layer 250 can manage stakeholders. Examples of stakeholder management include restricting access to highly important information and schedule management for creating disclosure documents, etc.

[0027] Such a data collection layer 250 makes it possible to synchronize data in real time between workers (including external consultants). Other benefits include: Contact history and the like can be tracked by theme. Scheduling can be easily done between the parties involved. Stakeholder information can be listed. The definition of collected data is standardized between the parties involved, and there is no return. The preparation of work manuals and other things are somewhat standardized. It becomes possible to reduce the effort required for collecting information from a wide range of stakeholders. It becomes possible to manage stakeholder lists. It becomes possible to conduct surveys, tally up data, and consolidate data. It becomes possible to carry out fixed-point observation. It becomes possible to standardize data definitions between groups. It becomes possible to eliminate double counting.

[0028] The data collection layer 250 also has functions that can be executed in the following order: (1) Register and organize suppliers from which ESG information is collected. This is done for each material business and product. This is called the supplier registration / structuring function. (2) You can select which data you want to collect for disclosure and enter company / business information. This is called the premise / purpose input function. (3) For each ESG area, a list of data sets that need to be collected is displayed and a person in charge is assigned. This is called the list of collected data items and person in charge assignment function. (4) The SAQ template is displayed and automatically distributed when a supplier is selected. This is called the hearing form template display / supplier selection function. (5) Promote data entry with an actionable UX. This is called the supplier input function. (6) Progress can be tracked for each data item and each supplier. This is called the progress tracking function. (7) The results of the calculation can be displayed and output. This is called the data calculation / output function. (8) It is possible to link to the analysis layer 270 and the data management and dashboard layer 240. This is called the linking function to the analysis / dashboard.

[0029] The analysis layer 270 performs analysis of the collected data. (E1) If the collected data is E1 and the type is physical risk, analyze chronic and acute risks based on climate change scenarios. Note that if the collected data is E1 and the type is transition risk, no analysis is performed. (E2) If the data to be collected is E2, perform regular observation and evaluate the visualization of the improvement status. (E3) If the data to be collected is E3, a water stress analysis will be conducted and interviews will be conducted with subsidiaries to see how they are responding. (E4) If the data to be collected is E4, perform a LEAP analysis (TNFD framework). (E5) If the data to be collected is E5, perform a circular economy assessment of the InFlow and OutFlow. (S1) If the data to be collected is S1, a benchmark comparison analysis is performed. (S2) If the data to be collected is S2, a conformity assessment with the UN guidelines will be performed. (S3) If the data to be collected is S3, obtain certification from a third party, etc. (S4) If the data to be collected is S4, perform a due diligence analysis based on the OECD Guidelines. (G) If the data to be collected is G, an evaluation such as an internal audit is performed.

[0030] Furthermore, the analysis layer 270 identifies data to be prioritized from among the collected data. The analysis layer 270 prioritizes the data using the following three viewpoints (1) to (3). Note that the viewpoints are not limited to three. (1) The data involves a high workload. This is a perspective that indicates that the data is subject to disclosure requirements regardless of materiality, that it is data related to requirements in a new field (being undertaken for the first time), or that it is data that involves frequent issues or tasks. (2) The data is of urgency This is a perspective that indicates that the data is already subject to disclosure pressure under other frameworks (other EU laws / ISSB / TNFD / human rights due diligence, etc.) or that the data is a high priority in terms of management issues. (3) The data must be compatible with information processing systems. This is a perspective that indicates that the data can be collected from information in the value chain and that it is possible to conduct data-driven analysis.

[0031] The resulting priority order is as follows: Result 1: The data related between viewpoint (1) and viewpoint (2) is data of S1, which has a priority of medium. Result 2: The data related between viewpoint (1) and viewpoint (3) is data E5, which has a priority of medium. Result 3: The data related between viewpoint (2) and viewpoint (3) is the data of E2, which has a priority of medium. Result 4: The relevant data among all viewpoints are E1, E3, E4, S2, S3, and S4, and are priority=high data.

[0032] The data E1, E3, and E4 are natural capital data, and the data S2, S3, and S4 are human capital data. The number of types of natural capital data and human capital data is the same, but when comparing the number of more detailed types, the number of types of natural capital data is greater than the number of types of human capital data, since the E1 data is classified into two types: E1 data for transition risks and E1 data for physical risks. In this way, the analysis layer 270 can identify prioritized data (areas).

[0033] There are two types of data on human capital: the type of company and the type of data obtained in VC. The type of company includes: breakdown of employees by country, number of employees by gender, number of employees in countries with 50+ employees, employee information by contract type by region, employee definition and category, employee turnover, total number of unemployed workers, percentage of workers covered by collective bargaining agreements, definition of company workers covered by collective bargaining agreements, link with works councils and trade unions, information on social dialogue, definition of top management, gender of top management, paying workers a fair wage, identifying workers who are not receiving a fair wage, percentage of workers below a fair wage, calculation of minimum wage, fair wage benchmark, indicative reference value for minimum wage, social protection of life events, countries and types of employees with and without social protection, employees with and without social protection. number of non-employed workers, percentage of disabled workers, gender breakdown, percentage of performance reviews, percentage of reviews agreed by management, average total training hours, average training hours by gender, employee categories, number of work-related injuries and fatalities due to work-related diseases, number and percentage of recordable work-related accidents, number of recordable cases of work-related diseases, number of days lost due to work-related injuries, work-related diseases and deaths due to disease, information on internal audits or external certifications, maternity / paternity / parental / carer's leave, pay gap, ratio of highest paid employee to median paid employee, gender pay gap, information on work-related grievances, incidents and claims, information on serious human rights impacts and incidents, incidents and / or grievances and actions taken, discrimination cases, serious cases regarding human rights issues and incidents.

[0034] Types of data captured in VC include: significant impacts on value chain workers and policies, scope and form of policy, alignment with UN Guiding Principles, alignment with relevant policies, engagement with value chain workers, disclosure of the company's process, reflecting the perspective of value chain workers, capturing the perspective of specific worker groups, remediation process for value chain workers, description of channels to value chain workers, tracking / monitoring issues and effectiveness of channels, approach and process for redress for value chain workers, existence of third-party mechanisms, protection against retaliation, addressing specific adverse impacts on value chain workers, provision of redress and ensuring effectiveness, prevention of significant adverse impacts and relationship to other business pressures, reporting of human rights issues and incidents, summary of action plans and resources, effective management / tracking / evaluation of significant impacts, etc.

[0035] Next, an example of analysis using E4 data will be shown. The analysis layer 270 inputs the data points necessary for analysis, such as location information of business activities, business sector information, and business financial information collected in the data collection layer 250, and performs the analysis. The analysis will be shown as an example of LEAP analysis. This analysis is an analytical approach recommended by the TNFD and the ESRS, which references it, for verifying biodiversity risks. This analysis is conducted in four phases: (1) the business's contact with nature, (2) the impact and dependency on nature, (3) evaluation of risks and opportunities, and (4) goal setting and response.

[0036] The results of the analysis are output separately for quantitative and qualitative requirements. The output is output by the data management and dashboard layer 240.

[0037] Quantitative requirements include, for example, number and area of ​​material sites, TNFD / SDPI-based target setting, area of ​​land permanently protected, area of ​​land restored, number of sites with improved ecosystem integrity, land use based on LCA, changes in land cover over time (e.g. deforestation), changes in ecosystem management over time, changes in the spatial configuration of the landscape, changes in the structural connectivity of ecosystems, financial impacts of risks / opportunities, and products and services exposed to risk.

[0038] Examples of qualitative requirements include: alignment of strategy and business model, impact drivers and mitigation actions, explanation of biodiversity offsets, assessment of the resilience of business model related to biodiversity and ecosystems, process for identifying significant impacts, risks and opportunities, disclosure of verified biodiversity and ecosystem scenarios, policy on restricting sourcing of raw materials, information on products derived from ecosystems, disclosure of biodiversity offsets, and policy on raw material sourcing.

[0039] Although an example of analysis in four phases has been shown, the four phases may be set as follows. (Phase 1) Discover points of contact with nature throughout the supply chain and identify priority areas. (1-1) Business footprint (1-2) Contact with nature (1-3) Analysis of priority areas (1-4) Analysis of impacts (Phase 2) Diagnose the dependencies and impacts of your company's business activities on nature. (2-1) Identifying relevant environmental assets and ecosystem services (2-2) Identifying dependencies and impacts (2-3) Dependency Analysis (2-4) Analysis of impacts (Phase 3) Based on the results of the diagnosis, evaluate significant risks and opportunities. (3-1) Risk Identification and Evaluation (3-2) Mitigating and managing existing risks (3-3) Mitigating and managing additional risks (3-4) Evaluation of importance (3-5) Opportunity Identification and Evaluation (Phase 4) Prepare to address nature-related risks and opportunities and report to investors. (4-1) Strategy and resource allocation (4-2) Performance measurement (4-3) Report (4-4) Announcement

[0040] Next, data acquisition and data linkage in the analysis layer 270 will be described with reference to FIG. 6. First, the analysis layer 270 acquires and analyzes data linked with the company and group companies. The analysis layer 270 acquires and analyzes pollution-related data, such as hazardous substance data for PRTR regulations, from the environmental database. The analysis layer 270 also acquires and analyzes data related to water and marine resources / biodiversity, such as equipment information, location information, and financial data, from the asset management system and ERP. The analysis layer 270 also acquires and analyzes data related to the circular economy, such as regenerated materials and recycled materials, from the procurement system and BOM / PLM. The analysis layer 270 also acquires and analyzes data related to human capital, such as wage data / executive data / human rights data, from the personnel system and human rights database. Furthermore, the analysis layer 270 acquires and analyzes third-party data. The analysis layer 270 acquires and analyzes data related to human capital, such as wage data / executive data / human rights data, from the personnel system and human rights database. The analysis layer 270 also acquires and analyzes data from the circular PF. The analysis layer 270 also acquires and analyzes data from supplier sustainability reports, CDPs, and ESG rating databases. The analysis layer 270 also acquires and analyzes data from subsidiaries, group companies, and suppliers. The subsidiaries and group companies include, for example, Subsidiary AA, which is a subsidiary of Subsidiary A. The suppliers include, for example, Supplier AA, which is a lower hierarchical level of Supplier A. The subsidiaries and group companies acquire data from the analysis layer 270 through the UX / UI. The subsidiaries and group companies also add or overwrite data to be output to the analysis layer 270.

[0041] Next, the operation DX and ESG data pipeline construction in the analysis layer 270 will be explained using FIG. 7. The analysis layer 270 receives disclosure request information from investors, rating agencies, business partners, national regulations, etc. In the front end, the analysis layer 270 reads disclosure items / requirements, sets workflows for each disclosure destination / purpose, and manages and creates a tree of suppliers. Next, the flow is from the front end to the back end, where the analysis layer 270 stores and links ESG data. In the back end, the analysis layer 270 generates an ESG data table. The ESG data table is a data table in which data such as E1, E3, E4, E5, and S1 is stored. In the back end, the analysis layer 270 stores the data collected in the front end in these tables, tags them with the disclosure destination / purpose, and enables the extraction of related data using these as keys. In other words, it performs mapping with the disclosure destination / purpose. In this way, the requirements for each disclosure destination / purpose are broken down into data items, making it possible to design tables in each ESG area. Next, the flow goes from the backend to the frontend, where the extracted data is output to the frontend. In the frontend, the analysis layer 270 creates questionnaires and supports responses (referencing past responses / industry practices) based on the extracted data, links collected data with disclosure destinations / purposes, extracts data for each disclosure destination / purpose, and outputs this data to be responded to and disclosed to investors, rating agencies, business partners, and national regulations. Examples of data sources collected by the analysis layer 270 include suppliers, subsidiaries / business companies, in-house systems, and 3rd party data.

[0042] The process for digitalizing ESG data collection and disclosure operations is as follows: (1) Workflow by disclosure recipient / purpose Workflows can be set up for each investor and disclosure regulation, and progress can be managed by assigning in-house staff to each task. (2) Questionnaire creation and response support You can create questionnaires based on templates for each disclosure destination / purpose. You can refer to past responses and industry practices, which can reduce the work of responding. (3) Linking collected data with recipients / purposes of disclosure It is possible to link data items collected not only from suppliers / subsidiaries but also from internal systems with disclosure destinations / purposes. (4) Extraction of data by disclosure destination / purpose It is possible to extract data by disclosure destination / purpose.

[0043] The ESG data pipeline will be constructed as follows: (1) Breaking down requirements for each disclosure recipient / purpose into data items The requirements for each disclosure destination / purpose have been broken down into data items, and tables have been designed for each ESG area. (2) Mapping with disclosure recipients / purposes The data collected on the front end is stored in these tables and tagged with the recipient / purpose of disclosure, making it possible to extract related data using these keys.

[0044] The data management / dashboard layer 240 extracts data to be used for disclosure. It also decides which collected and analyzed data to use for which disclosure. It also saves data used for past disclosures and the calculation process. The data management / dashboard layer 240 outputs to documents. In this way, the person in charge can easily edit and output data. The data management / dashboard layer 240 is a dashboard for management. This dashboard allows you to grasp KPIs. It also allows for a common understanding among stakeholders. The data management / dashboard layer 240 performs business management. Examples of business management include alerts for material events and grasping differences through fixed-point observation. The data management / dashboard layer 240 discloses various reports. The types of reports are CDP, ISSB, GRI, RE100, the Global Warming Act, CSRD, CSDD, etc. In this way, the data management / dashboard layer 240 has a consulting function by disclosing various reports.

[0045] Before the introduction of Data Management & Dashboard Layer 240, it was a hassle to integrate scattered ESG data, and even after integration, it was difficult to identify important items, KPIs important to the company could not be shared or tracked with relevant parties, and VC information was not even understood (even if the data was available, it was not compiled). With the introduction of Data Management & Dashboard Layer 240, it is now possible to share important items with relevant parties in an easy-to-understand manner. In addition, real-time synchronization can be used to output alerts for differences. Furthermore, the way data is displayed can be easily customized by the person in charge. VC information can be automatically collected from Data Management & Dashboard Layer 240.

[0046] The solution layer 260 provides solutions to buyers. The solution layer 260 can also provide solutions to third parties other than buyers. The third parties are, for example, suppliers.

[0047] The Data Management & Dashboard Layer 240 can solve the following: (1) Strengthening ESG management: Strengthening ESG management from a medium- to long-term perspective will make it possible to achieve sustainable management. (2) Strengthening ESG ratings: By strengthening ratings set by the EU (SFDR Article 9 labeling) and rating agencies (MSCI / Ecovalis / Moody's), it will be possible to acquire more competitive funds. (3) Business risk management: (Apart from regulatory compliance) it is possible to accurately grasp the ESG risks of the business. In addition to transition risks, it is possible to understand the business impact of biodiversity, physical risks, and human capital risks. (4) Compliance with various regulations: Efficiently comply with regulations such as CSRD / CBAM / CS3D / TNFD / ISSB / CDP / Battery regulations. (5) Providing information to business partners and investors: It is possible to efficiently respond to requests for ESG-related data from ad-hoc investors and major business partners.

[0048] In the analysis layer 270, the following can be solved: (1) Diverse ESG analysis: This solves the problem of the need to conduct highly specialized analysis in a variety of areas, which would be costly if done through consulting.

[0049] The data collection layer 250 can resolve: (1) Data collection costs at VCs: It will be possible to increase the efficiency of ESG data collection at VCs, which is labor-intensive and difficult to guarantee quality, while also promoting supplier engagement.

[0050] The data management and dashboard layer 240 can be used in cases such as strengthening ESG management, strengthening ESG ratings, business risk management, compliance with various compliance standards, and providing information to business partners / investors. In addition, the data management and dashboard layer 240 has functions such as dashboarding of ESG material matters, rating simulation (e.g. SFDR, MSCI), monitoring of ESG risks by business unit, ESG scoring for each supplier, data extraction and output according to business partner / investor / disclosure requirements, data feed to external systems (e.g. Catena-X), automatic linkage and difference detection with the data collection layer 250 and analysis layer 270. The analysis layer 270 has functions such as partner linkage (API linkage between each analysis PF and the data collection layer 250 and data management and dashboard layer 240). Each analysis PF can also be built by oneself. The data collection layer 250 has functions such as questionnaires, setting of data items (preparing templates for each purpose / disclosure), data input assistance, validation, tracking, scheduling, and management of supplier information and aggregation results.

[0051] <System Overview> An example of an information processing system that provides solutions will be described below using greenhouse gas emissions, which are data on E1, as an example. The information processing system of this example provides information (hereinafter referred to as solution information) on emission reduction means (also called solutions) to users who are emitters of greenhouse gases (carbon dioxide, methane, nitrous oxide, fluorocarbons, etc.). Solution providers register the solution information, and users can view the solution information. Users can also contact the provider regarding the solution.

[0052] 3 is a diagram showing an example of the software configuration of the management server 200 in this example. The management server 200 includes a storage unit 230 (solution storage unit, user information storage unit, emission amount information storage unit), a data collection layer 250 (emission amount information acquisition unit, performance acquisition unit), an analysis layer 270 (extraction unit), a data management / dashboard layer 240 (provision unit), and a solution layer 260 (billing processing unit). The data collection layer 250 is also referred to as the acquisition unit 250. The analysis layer 270 is also referred to as the analysis unit 270. The data management / dashboard layer 240 is also referred to as the output unit 240 or the provision unit 240. The solution layer 260 is also referred to as the solution unit 260.

[0053] <Storage section> The solution storage unit constituting the storage unit 230 stores solution information. The solution storage unit can store the solution information in association with provider identification information (provider ID) that identifies a provider that provides a reduction means. The solution information can include cost information for determining the cost of the reduction means and reduction information for determining the expected reduction amount of greenhouse gases when the reduction means is adopted. In this example, the solution information can include information for identifying the solution (solution ID), provider ID, solution name, solution description, price, reduction amount, and introduction conditions. The solution name is the name of the reduction means (solution). The solution description is a description of the solution, and can include, for example, text data, image data, and voice data. The price may be information for determining the amount of money involved when a user adopts the solution. As the price, a unit price related to the provision unit of the solution may be set, or an estimated value of a standard introduction cost may be set. The price may be specified by a range such as a price range. The reduction amount may be information indicating the expected reduction amount of greenhouse gases by introducing the solution. The reduction amount may be set as a standard amount of greenhouse gases per company that is reduced when the solution is introduced, or may be a standard value of the reduction amount per unit when the device is introduced, or may be a function that calculates the reduction amount according to various activity amounts. The introduction conditions may be set as conditions for the emitter that introduces the solution. The introduction conditions may specify, for example, the business or activity content or activity amount that is the target of the solution. The introduction conditions may also specify the scope and / or category to be reduced. The solution storage unit stores not only solution information for environmental information, but also solution information for social information and solution information for governance information.

[0054] The user information storage unit constituting the storage unit 230 stores information (hereinafter referred to as user information) relating to users (discharge entities). The user information may include information (user ID) identifying the user (or discharge entity), the name of the user (or discharge entity) (user name), information relating to the business conducted by the discharge entity (business information), information relating to the facilities used in the business (facilities information), and the like. The user information storage unit stores not only user information relating to environmental information, but also user information relating to social information and user information relating to governance information.

[0055] The emission information storage unit constituting the storage unit 230 stores information on the amount of greenhouse gas emissions by the emission entity (hereinafter referred to as emission information). The emission information may include an aggregated value of the amount of emissions by the emission entity. The emission information may include attributes of the emission entity. The attributes of the emission entity may include the emission entity's business, number of employees, region, etc. The attributes of the emission entity may also include accounting information such as sales, purchases, and labor costs. The emission information may include additional information related to the activity related to the emission. The additional information may include, for example, activity amount (actual value, aggregated value of actual value, predicted value, etc.). The additional information may include information for estimating the activity amount. The information for estimating the activity amount may include, for example, floor area, roof area, number of products that can be produced, etc. In this embodiment, the emission information includes information identifying the emission entity (for example, company ID), activity amount, additional information, and emission amount. The emission amount and activity amount may be an aggregated value of the emission amount and activity amount for each scope and category related to the GHG Protocol for a predetermined aggregation period (for example, year and month). The additional information may have different setting items depending on the discharge entity.

[0056] <Functional section> The emission information acquisition unit constituting the data collection layer 250 acquires emission information. The emission information acquisition unit can receive emission information from the user terminal 100. The emission information acquisition unit may access another system to acquire emission information. The management server 200 may include an emission calculation unit that acquires, for example, an activity amount and an emission coefficient related to the emission entity, and calculates an emission amount by multiplying the acquired activity amount and emission coefficient, and can acquire various information used in calculating the emission amount, such as the emission amount and activity amount calculated by the emission calculation unit, as emission information. The data collection layer 250 acquires not only emission information, but also information related to society and information related to governance.

[0057] The extraction unit constituting the analysis layer 270 acquires solution information that matches the emission amount information. The extraction unit can match the emission amount and additional information with the solution information. The extraction unit can extract the user information of the emission entity and / or the emission amount information that satisfies the introduction condition included in the solution information. The extraction unit can preferentially extract a predetermined number of scopes and categories in descending order of emission amount among the emission amounts by scope and category included in the emission amount information, and can search for solution information in which the emission amount and / or the corresponding additional information related to the scope and category satisfies the introduction condition, for example. The extraction unit can calculate the unit cost per unit reduction amount determined based on the reduction amount determined based on the reduction information and the cost determined by the cost information, and can extract a predetermined number of solution information in descending order of unit cost from the solution information that matches the emission amount information. The extraction unit also extracts solution information that matches the information on society and solution information that matches the information on governance.

[0058] The providing unit constituting the data management and dashboard layer 240 can provide the extracted solution information to the user.

[0059] The performance acquisition unit constituting the data collection layer 250 acquires information indicating a solution adopted by the waste generator and information including the amount of reduction achieved by the solution (hereinafter referred to as performance information). The management server 200 may include a performance information storage unit that stores the performance information.

[0060] The billing processing unit constituting the solution layer 260 performs processing (billing) to charge the provider for using the system. The billing processing unit can bill the provider who provided the solution according to the amount of reduction included in the performance information. The billing processing unit may also bill the emission entity that adopted the solution according to the amount of reduction included in the performance information. The billing processing unit may, for example, determine the billing amount so that the billing amount is higher when the amount of reduction is large. The billing processing unit may, for example, determine the billing amount so that the billing amount is lower when the amount of reduction is large. The solution layer 260 also processes solution information of information related to society and information related to governance. In the case of the second modified example of FIG. 5, it is preferable to provide the solution layer 260 outside the management server 200.

[0061] <Operation> 8 is a diagram for explaining the operation of the management server 200. The management server 200 acquires solution information from the provider and registers it in the solution storage unit (S801), and acquires emission amount information from the emission subject and registers it in the emission amount storage unit (S802). The management server 200 extracts solution information that matches the emission amount for each piece of emission information (S803), and provides the extracted solution information to the emission subject that is the provider of the emission information (S804). The management server 200 acquires performance information (S805), and can perform charging according to the reduction amount included in the performance information (S806).

[0062] As described above, the information processing system of this embodiment can match solution information with the emitter (emission amount information).

[0063] Although the present embodiment has been described above, the above embodiment is intended to facilitate understanding of the present invention, and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit of the present invention, and equivalents thereof are also included in the present invention.

[0064] For example, conditions for solution information can be set in the emission amount information, and the management server 200 can narrow down solution information that matches the emission amount information to only those that satisfy the emission amount information conditions.

[0065] The management server 200 can display a list of solution information on the user terminal 100. The management server 200 can display the list of solution information in the order in which the solution information was registered.

[0066] The management server 200 can manage the solution information viewed by the user terminal 100, and can provide the solution information with a priority according to the number of views. For example, the management server 200 can display the solution information sorted in order of the number of views. Furthermore, the management server 200 can transmit only a predetermined number of solution information to the user terminal 100 in order of the number of views.

[0067] The management server 200 can display a list of only a portion of the solution information on the user terminal 100, accept selection (tap or click) of solution information from the user terminal 100, and manage the selection of solution information. The management server 200 can provide solution information with a priority according to the number of selections. For example, the management server 200 can display the solution information sorted in order of the number of selections. Furthermore, the management server 200 can transmit only a predetermined number of solution information to the user terminal 100 in order of the number of selections.

[0068] The management server 200 can acquire and manage evaluations of solutions from users. For example, a list of evaluation values ​​acquired from users and / or an aggregated value (e.g., an average value or a total value) can be set in the solution information. The management server 200 can provide the solution information with a priority according to the aggregated evaluation value. For example, the management server 200 can display the solution information sorted in order of evaluation value. Furthermore, the management server 200 can transmit only a predetermined number of solution information to the user terminal 100 in order of evaluation value.

[0069] Furthermore, the management server 200 can provide solution information preferentially when an additional fee has been paid by a provider.

[0070] The management server 200 may also include an application processing unit that accepts an application for a solution. The management server 200 may provide a reward to a user for the application for a solution.

[0071] Furthermore, when a contract for a solution is concluded, the management server 200 can charge the provider a predetermined percentage of the contract fee. Furthermore, the management server 200 can include a notification unit that notifies the user and / or the provider of the conclusion of a contract.

[0072] <Summary of the Invention> The present invention will be described below with reference to the preferred embodiments thereof. [Item 1] An information processing system comprising: an acquisition unit that acquires environmental information including emission information regarding the amount of greenhouse gas emissions by an emission entity that emits greenhouse gases, social information, and governance information from a user who is an emission entity that emits greenhouse gases; a solution storage unit that stores at least solution information regarding means of reducing the greenhouse gases; an extraction unit that extracts the solution information that matches the emission information; and a provision unit that provides the extracted solution information to the user. [Item 2] An information processing system according to item 1, characterized in that conditions for the releasing entity are set in the solution information, and the extraction unit extracts the releasing entity that satisfies the conditions included in the solution information. [Item 3] 3. An information processing system according to claim 2, characterized in that the emission information is accompanied by additional information relating to activities related to the emission amount, and the extraction unit matches the emission amount and the additional information with the solution information. [Item 4] Item 1 is an information processing system, wherein the emission information includes greenhouse gas emissions aggregated for each scope and category related to the GHG Protocol, and the extraction unit preferentially extracts the solution information corresponding to the scope and category with the highest emission amount. [Item 5] 2. An information processing system according to claim 1, wherein the solution information includes cost information for determining the cost of the reduction means and reduction information for determining an expected amount of reduction of the greenhouse gas when the reduction means is adopted, and the extraction unit calculates a unit cost per unit reduction amount determined based on the reduction amount determined based on the reduction information and the cost determined by the cost information, and extracts a predetermined number of the solution information that matches the emission information in order of the unit cost. [Item 6] 2. An information processing system according to claim 1, wherein the solution information includes an expected reduction amount, and a predetermined number of the solution information is extracted according to the reduction amount. [Item 7] Item 1 is an information processing system according to the present invention, characterized in that it comprises: a performance acquisition unit that acquires information indicating the solution adopted by the emission entity and the amount of reduction achieved by the solution; and a billing processing unit that charges the provider according to the amount of reduction.

[0073] Although an example of an information processing system is shown in the disclosure, each process (step) of the information processing system can also be an information processing method executed by a computer and a program for causing a computer to execute the method. [Explanation of symbols]

[0074] 100 user terminals 200 Management Server

Claims

1. An acquisition unit that acquires emission information regarding greenhouse gas emissions, A solution storage unit that stores at least solution information relating to greenhouse gas reduction means, which includes cost information for determining the cost of the reduction means, reduction information for determining the expected amount of greenhouse gas reduction when the reduction means is adopted, and implementation conditions which are conditions for the emitter that introduces the solution. An extraction unit that extracts solution information that matches the emission information and for which the emission entity satisfies the introduction conditions, A provisioning unit that provides the extracted solution information to the user, An information processing system characterized by comprising the following features.

2. The information processing system according to claim 1, The emissions information includes greenhouse gas emissions aggregated by scope and category related to the GHG protocol. The extraction unit prioritizes extracting solution information corresponding to the scope and category with the highest discharge volume. An information processing system characterized by the following.

3. The information processing system according to claim 1, A performance acquisition unit that acquires information indicating the solution adopted by the aforementioned emitter and performance information including the amount of reduction achieved by said solution, A billing processing unit that charges the provider that provided the solution information in accordance with the amount of reduction included in the performance information, An information processing system characterized by comprising the following features.

4. The information processing system according to claim 1, An analysis unit identifies priority information from the information acquired by the acquisition unit, An information processing system characterized by comprising the following features.

5. Steps to obtain emission information regarding greenhouse gas emissions, A step of storing solution information relating to greenhouse gas reduction means, which includes cost information for determining the cost of the reduction means, reduction information for determining the amount of greenhouse gas reduction expected when the reduction means is adopted, and implementation conditions which are conditions for the emitter that introduces the solution. A step of extracting solution information that matches the emission information and for which the emission entity satisfies the introduction conditions, The steps include providing the extracted solution information to the user, An information processing method characterized by a computer executing the following.

6. Steps to obtain emission information regarding greenhouse gas emissions, A step of storing solution information relating to greenhouse gas reduction means, which includes cost information for determining the cost of the reduction means, reduction information for determining the amount of greenhouse gas reduction expected when the reduction means is adopted, and implementation conditions which are conditions for the emitter that introduces the solution. A step of extracting solution information that matches the emission information and for which the emission entity satisfies the introduction conditions, The steps include providing the extracted solution information to the user, A program that causes a computer to execute something.

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