Simulation device and simulation method

Abstract

This simulation device comprises: a financial information processing unit 10 that calculates direct revenue and expenditures when decarbonization measures are implemented under introduction conditions, and also estimates indirect revenue resulting from non-financial information; a determination support unit 7 that, when the decarbonization measures are implemented under the introduction conditions, performs a simulation as to whether or not a financial balance target and a decarbonization target are satisfied taking the indirect revenue into account; and a dashboard 100 that outputs a screen regarding the simulation by the determination support unit 7.

Description

Simulation device and simulation method

[0001] The present invention relates to a simulation device and a simulation method, and is suitable for application to a simulation device relating to technology for presenting decarbonization measures according to decarbonization targets, for example.

[0002] In recent years, there has been growing interest in environmental considerations in the production of products. Patent Document 1 discloses a technology for effectively supporting the selection of measures to reduce the burden on the environment, in which measures acquired from a measure information table are sorted based on values ​​corresponding to priorities for selecting measures to be implemented, a cumulative value of the environmental conservation effect value for each measure is calculated, and the measure and the cumulative value are output.

[0003] JP 2010-134688 A

[0004] However, although there are other possible indirect incomes that can be derived from environmental considerations, the technology disclosed in Patent Document 1 does not take into consideration quantitatively indicating such indirect incomes, making it difficult to determine whether the proposed measures are appropriate.

[0005] The present invention has been made in consideration of the above points, and aims to propose a simulation device and a simulation method that can quantitatively present indirect income when formulating decarbonization measures.

[0006] In order to solve such problems, the present invention comprises a target input unit that inputs a decarbonization target related to decarbonization and a financial balance target related to financial balance; a condition setting unit that sets the conditions for introducing decarbonization measures that correspond to the decarbonization target; a financial information processing unit that calculates direct income and expenditure when the decarbonization measures are implemented under the introduction conditions and estimates indirect income obtained as a result of non-financial information; a judgment support unit that performs a simulation regarding whether the financial balance target and the decarbonization target will be met, taking into account the indirect income, when the decarbonization measures are implemented under the introduction conditions; and an interface that outputs a screen related to the simulation by the judgment support unit.

[0007] In addition, in the present invention, the system includes a target input step in which the target input unit accepts input of a decarbonization target related to decarbonization and a financial balance target related to financial balance; a condition setting step in which the condition setting unit sets conditions for introducing decarbonization measures corresponding to the decarbonization target; a financial information processing step in which the financial information processing unit calculates direct income and expenditure when the decarbonization measures are implemented under the introduction conditions and estimates indirect income obtained as a result of non-financial information; a judgment support step in which the judgment support unit executes a simulation regarding whether the financial balance target and the decarbonization target will be met, taking into account the indirect income, when the decarbonization measures are implemented under the introduction conditions; and an output step in which a screen related to the simulation by the judgment support step is output to an interface.

[0008] According to the present invention, indirect income can be quantitatively presented when formulating decarbonization measures.

[0009] 1 is a system configuration diagram showing an example of the configuration of a simulation device according to this embodiment. FIG. 2 is a diagram showing an example of a KPI tree. FIG. 3 is a diagram showing an example of the causal relationship that ESG activities have on management. FIG. 4 is a diagram showing an example of an income prediction algorithm. FIG. 5 is a diagram showing an example of an estimate of the increase in the amount of ESG non-investment. FIG. 6 is a diagram showing an example of a prediction of the unit cost of ESG (Environment, Social, Governance) investment income using a deductive method. FIG. 7 is a diagram showing an example of a predicted value of access funds (ESG). FIG. 8 is a diagram showing an example of a simulation screen. FIG. 9 is a diagram showing an example of a simulation screen.

[0010] An embodiment of the present invention will be described in detail below with reference to the drawings. Fig. 1 is a system configuration diagram showing an example of the configuration of a simulation device 300 according to this embodiment. The simulation device 300 includes a KPI (Key Performance Indicators) tree 200, a dashboard 100, a goal input unit 1, a policy proposal selection unit 2, a financial information processing unit 10, a judgment support unit 7, and a database 400.

[0011] The database 400 has various tables as described below and can store various data. The database 400 can store, for example, a decarbonization measure proposal list 21 (described below) that includes at least one decarbonization measure proposal for achieving a decarbonization target (hereinafter referred to as a "decarbonization measure proposal"), as well as decarbonization measures and their implementation conditions.

[0012] The dashboard 100 is an example of an interface, and displays a simulation screen relating to a simulation performed by the judgment support unit 7 and forms such as a condition input form for the simulation. Furthermore, under the control of the judgment support unit 7, the dashboard 100 outputs a simulation result screen as the result of the simulation performed by the judgment support unit 7.

[0013] In the dashboard 100, for example, a target related to decarbonization (hereinafter referred to as a "decarbonization target") and a target related to financial balance (hereinafter referred to as a "financial balance target") are input by an operator (hereinafter simply referred to as an "operator"), such as a manager involved in planning decarbonization. The dashboard 100 displays the results of a determination made by the determination support unit 7, which will be described later. Details of the dashboard 100 will be described later.

[0014] The KPI tree 200 represents a KPI tree that can be defined from a management perspective, for example. The KPI tree 200 is displayed on the dashboard 100. The KPI tree 200 will be described in detail later.

[0015] The goal input unit 1 receives input of a decarbonization target related to decarbonization and a financial balance target related to financial balance via the dashboard 100 (goal input step), and registers information about the decarbonization target and information about the financial balance target in the database 400. Specifically, the goal input unit 1 displays, for example, a predetermined form (described below) on the dashboard 100, and registers, in the database 400, information about the decarbonization target and the financial balance target input into the form by the operator.

[0016] The policy proposal selection unit 2 is an example of a condition setting unit, and sets the introduction conditions for decarbonization measures corresponding to decarbonization measure proposals for achieving the decarbonization target (condition setting step). The policy proposal selection unit 2 selects decarbonization measure proposals for achieving the decarbonization target from the database 400 based on the introduction conditions for the decarbonization measures input by the operator in the above-mentioned form. Note that the policy proposal selection unit 2 can also newly create at least one of a decarbonization measure proposal and its introduction conditions and register it in the database 400.

[0017] The policy proposal selection unit 2 reads the decarbonization policy proposal list 21 from the database 400 and selects one of the multiple decarbonization policy proposals included in the decarbonization policy proposal list 21. The decarbonization policy proposal list 21 is a list containing multiple decarbonization policy proposals for achieving the decarbonization goal. When a new decarbonization policy proposal is added to the decarbonization policy proposal list 21 as described above, the new decarbonization policy is added to the list accordingly. In this embodiment, for example, a CO2 emission reduction target of reducing CO2 by XX (XX: numerical value) tons (corresponding to "XXtCO2" in the figure) is used as an example of a decarbonization policy proposal. Note that when considering all the effects of greenhouse gases (GHGs) other than CO2 (carbon dioxide), such as methane and nitric oxide, XXtCO2-e is used, which means emissions equivalent to CO2 emissions.

[0018] The financial information processing unit 10 calculates direct income and expenditures when decarbonization measures are implemented under the above-mentioned implementation conditions, and estimates indirect income obtained as a result of non-financial information (financial information processing step). Here, "indirect income obtained as a result of non-financial information" refers to other income not included in the direct income and expenditures when decarbonization measures are implemented under the above-mentioned implementation conditions. Details of the financial information processing unit 10 will be described later.

[0019] The judgment support unit 7 performs a simulation to determine whether the above-described financial balance target and decarbonization target will be met, taking into account indirect income, when the decarbonization measures are implemented under the above-described implementation conditions (judgment support step). The judgment support unit 7 performs display control to display a simulation screen (described later), forms such as a condition input form for inputting conditions for executing this simulation (effect simulation conditions (described later)), and a simulation result screen regarding the results of this simulation. In this embodiment, these screens are also collectively referred to as "simulation-related screens." The dashboard 100 outputs a screen regarding the simulation performed in the above-described judgment support step (output step).

[0020] Details of the above-mentioned financial information processing unit 10 will be described. The financial information processing unit 10 includes a specification calculation unit 3, a rough cost calculation unit 4, a rough income calculation unit 5, a product sales target calculation unit 51, an ESG investment capital increase impact calculation unit 52 (indirect income estimating unit), a carbon credit calculation unit 54 (indirect income estimating unit), a profit calculation unit 6, and a risk management unit 90 (indirect income estimating unit). In this embodiment, of these, the ESG investment capital increase impact calculation unit 52, the carbon credit calculation unit 54, and the risk management unit 90 are examples of indirect income estimating units that estimate indirect income obtained as a result of non-financial information.

[0021] The specification calculation unit 3 outputs detailed specifications of the decarbonization measure proposal selected by the measure proposal selection unit 2. Here, an example of the detailed specifications of the decarbonization measure proposal is to set the power consumption to XX (XX: numerical value) kilowatts ("XX KW (kilowatts)"). The specification calculation unit 3 reads a specification calculation basic unit 31 based on the CO2 emission reduction target. Here, in this embodiment, the "basic unit" indicates, for example, the converted amount of CO2 emitted in accordance with corporate activities.

[0022] The rough cost calculation unit 4 reads a cost unit table 41 based on a carbon tax market situation and unit 42 indicating the market situation and unit 42 of the carbon tax, and calculates the rough cost. The cost unit table 41 includes information on, for example, installation costs, operating costs, and the carbon tax reduction degree indicating the degree of carbon tax reduction.

[0023] The risk management unit 90 is an example of an indirect income estimation unit, and executes control to estimate indirect income obtained as a result of the non-financial information described above. The non-financial information may include, for example, risks obtained by machine learning, which will be described later.

[0024] The risk management unit 90 manages at least one of pessimistic risk and optimistic risk that may affect the estimation of indirect income (hereinafter sometimes abbreviated as "indirect income").

[0025] The risk management unit 90 may predict pessimistic and optimistic risks by machine learning using, for example, generative AI (Artificial Intelligence).

[0026] The risk management unit 90 may, for example, learn a risk prediction model using the production volume of a product of another company that competes with the company's own product and the size of the market for that product as explanatory functions, and whether the risk is likely to be a pessimistic risk or an optimistic risk as an objective function, and use the learned risk prediction model to predict whether a future risk is likely to be a pessimistic risk or an optimistic risk (or how serious the risk is).

[0027] Alternatively, the risk management unit 90 may perform risk management using other methods without using the generation system AI.

[0028] As part of its risk management for pessimistic risks, the risk management department 90 first manages the risk that it will be difficult to achieve decarbonization targets and financial balance targets due to the situation of other companies, for example, if a competitor releases a similar product.

[0029] Secondly, as a risk management measure for pessimistic risks, the risk management department 90 manages the risk that, for example, the amount of electricity generated by wind power generation installed in the company is lower than initially predicted, the effects of decarbonization are less than expected, and it becomes difficult to achieve the decarbonization target and financial balance target.

[0030] Thirdly, as a risk management measure for pessimistic risks, the risk management department 90 manages the risk that, for example, investment in the company will not grow as much as initially predicted due to geographical factors, making it difficult to achieve decarbonization targets and financial balance targets.

[0031] In this way, when the risk management unit 90 manages pessimistic risks, the approximate income calculation unit 5 calculates income in a direction that decreases the income. In addition, it is also possible to handle cases where the examples given here occur in combination.

[0032] On the other hand, the risk management unit 90 manages optimistic risks, for example, the risk that there will be more hours of sunshine than usual and the amount of electricity generated by the solar power generation system installed in the company will be higher than usual.

[0033] In this way, when optimistic risks are managed by the risk management unit 90, the approximate income calculation unit 5 calculates income in a direction that increases income. In addition, it can also handle cases where multiple optimistic risks occur in combination.

[0034] The risk management unit 90 provides the ESG investment capital increase impact calculation unit 52 with, for example, an ESG investment capital increase impact logic / unit 55 that indicates the logic and unit that may affect the ESG investment capital increase based on at least one of the optimistic risk and pessimistic risk that it manages.

[0035] The ESG investment capital increase impact calculation unit 52 is an example of an indirect income estimation unit, and estimates indirect income obtained as a result of the non-financial information described above. The ESG investment capital increase impact calculation unit 52 calculates investment impact information regarding the impact of ESG investment on capital increases based on the ESG investment capital increase impact logic / basic unit 55, and estimates indirect income based on this investment impact information.

[0036] Furthermore, the risk management unit 90 provides, for example, the carbon credit market conditions and transitional intensity 57 to the carbon credit calculation unit 54 based on at least one of the optimistic risk and the pessimistic risk that it manages.

[0037] The carbon credit calculation unit 54 is an example of an indirect income estimation unit, and estimates indirect income obtained as a result of the non-financial information described above. The carbon credit calculation unit 54 calculates carbon credits based on the carbon credit market conditions and transitional intensity 57.

[0038] The product sales target calculation unit 51 calculates, for example, a target operating profit as a product sales target.

[0039] The approximate income calculation unit 5 receives product sales targets from the product sales target calculation unit 51, receives investment impact information regarding the impact of ESG investment on capital increases from the ESG investment capital increase impact calculation unit 52, and receives carbon credits from the carbon credit calculation unit 54 to calculate approximate income, and outputs the approximate income to the profit calculation unit 6.

[0040] The profit calculation unit 6 calculates the approximate profit by subtracting the approximate cost calculated by the approximate cost calculation unit 4 from the approximate income calculated by the profit calculation unit 6 .

[0041] The judgment support unit 7 creates judgment support information for supporting judgment from the approximate profit calculated by the profit calculation unit 6 based on the judgment logic judgment criteria 71, and outputs the information to the dashboard 100. The dashboard 100 displays the above-mentioned KPI tree 200 and a simulation screen, which will be described later, as an example of the judgment support information.

[0042] The operator refers to the KPI tree 200 and judgment support information on the simulation screen displayed on the dashboard 100 to set decarbonization targets and develop decarbonization plans.

[0043] FIG. 2 is a diagram showing an example of a KPI tree 200. The KPI tree 200 has a management KPI tree 601, decarbonization measures 602, and decarbonization and reduction targets 603. The KPI tree 200 has the following connection relationships. Note that, in the following, "connection" indicates that, when considering KPIs, the tip of the connecting arrow may affect the rear end. First, profit (profit and loss) is connected to income and expenditure (cost).

[0044] Revenue is connected to operating revenue and non-operating revenue. Operating revenue is connected to sales. Sales are connected to product A as an example of a product, service B as an example of a service, etc. On the other hand, non-operating revenue is connected to investments and loans (ESG), stock income, carbon credits, subsidies, etc.

[0045] The management KPI tree 601 has direct effects such as ESG disclosure, CFP (Carbon Foot Print) disclosure, and CO2 emission reduction.

[0046] On the other hand, expenditures (costs) are connected to capital investment, operating costs, maintenance costs, raw fuel costs, labor costs and carbon taxes.

[0047] The decarbonization measures 602 include visualization by organization, visualization by product, purchasing renewable energy (energy) power sources, process electrification, introduction of renewable energy (energy), change of production base, change of production plan, change of process, change of raw materials / parts, change of procurement source, change of transportation method, energy saving (energy) of in-house products, introduction of hydrogen / ammonia, introduction of bio-humus, introduction of CCUS (Carbon Capture Usage and Storage), hydrogen steelmaking and product charging.

[0048] The decarbonization / reduction target 603 includes categories 1 to 15 (corresponding to "Cat 1 to Cat 15" shown in the figure), including overall, Scope 1 (direct emissions), Scope 2 (indirect emissions), and Scope 3 (others). Scopes 1 to 3 indicate, for example, indicators of greenhouse gas emissions in a supply chain related to a product. Scope 1 indicates direct greenhouse gas emissions associated with business activities. Scope 2 indicates indirect greenhouse gas emissions in the production stage of heat and energy used in business activities. Scope 3 indicates indirect greenhouse gas emissions other than those in Scopes 1 and 2.

[0049] An arrow extending from a decarbonization / reduction target 603 to a decarbonization measure 602 indicates that the decarbonization / reduction target 603 at the end of the arrow affects the decarbonization measure 602 at the tip of the arrow. An arrow extending from a decarbonization measure 602 to a management KPI tree 601 indicates that the decarbonization measure at the tip of the arrow affects the item at the tip of the arrow.

[0050] In the illustrated example, for example, the "Scope 1 direct emissions" of the decarbonization / reduction target 603 affects, for example, the "Introduction of renewable energy (renewable energy)" of the decarbonization measures 602, and this "Introduction of renewable energy (renewable energy)" affects, for example, the "Capital investment" and "Operating volume" of the "Cost" of "Profit" in the management KPI tree 601.

[0051] Figure 3 is a diagram showing an example of the causal relationship that ESG activities have on management. In the illustrated example, ESG activities are divided into "strategy" and "execution." "Strategy" leads to an increase in corporate brand value and access funds by disclosing medium- to long-term activity plans and implementation details. On the other hand, "execution" is "execution" based on a plan, and can reduce specific costs and GHG (Greenhouse Gas) emissions. This can also lead to CC income from reduced GHG emissions. Note that in the following explanation, "planning" is linked to promoting corporate value in the medium to long term, leading to increased product sales and increased access funds (investment) due to improved brand value.

[0052] The ESG strategy action plan is related to the implementation of ESG activities (steady implementation based on the action strategy) as a short-term effect, and to the disclosure of ESG activity strategies, plans, and implementation details as a medium- to long-term effect.

[0053] The implementation of ESG activities is related to ESG activity costs (corresponding to management KPIs), ESG activity revenue (corresponding to management KPIs), and ESG activity effects (corresponding to decarbonization KPIs). ESG activity costs (corresponding to management KPIs) are related to, for example, the installation / operation of equipment, which is a type of operating revenue. ESG activity revenue is related to, for example, carbon tax reduction / carbon credit revenue, which is a type of non-operating revenue. ESG activity effects are related to energy consumption / GHG emission reductions, and do not fall under operating revenue or non-operating revenue.

[0054] On the other hand, ESG activity strategies, plans, and implementation details are related to the improvement of corporate brand value / risk reduction and the increase in access funds. The improvement of corporate brand value / risk reduction is related to the increase in sales of the company's products, which is a type of operating income. The increase in access funds is related to the increase in sales of the company's products, which is a type of non-operating income.

[0055] Figure 4 shows an example of a revenue forecasting algorithm. The illustrated example overcomes the difficulty of estimating revenue, presents a rough estimate that allows for strategic planning, and forecasts at a granularity of approximately one year. In addition, the illustrated example calculates the effects of ESG activities by dividing revenue into operating revenue and non-operating revenue.

[0056] "Operating income" leads to increased market share and preventing companies from leaving the company. Here, the amount of the increase in the base line is recorded as an annual rate. "Non-operating income" is directly related to ESG activities, as it includes access funds, carbon credits, and subsidy acquisition. "Access funds" will be discussed later.

[0057] First, revenue includes operating revenue and non-operating revenue. Operating revenue includes sales. Sales are related to product A as an example of a product, service B as an example of a service, etc.

[0058] Product A and service B, etc., are related to an increase in the company's brand value (for example, an increase in switching to the company), which has the effect of the company's ESG activities being recognized and the market share of the company's products increasing, and this is expressed as an annual rate, etc.

[0059] Furthermore, the increase in the corporate brand value leads to a reduction in risk (for example, a reduction in switching to other companies), which has the effect of recognizing ESG activities and reducing the number of business partners that leave the company, and this can be expressed as an annual rate, etc.

[0060] On the other hand, non-operating income includes access fund investments (ESG), carbon credits, subsidies, etc., and other income (interest, dividends, real estate, sales, license fees, litigation settlements, foreign exchange gains, etc.).

[0061] Access Fund investments are related to the company's average ESG score, index, environmental score, maturity score, carbon credits, subsidies, etc. Here, the company's average ESG score, etc. can affect the above-mentioned corporate brand value improvement and risk reduction. The company's average ESG score, etc. corresponds to an ESG resource unit.

[0062] Carbon credits are related to the achievement of target emissions (for example, a company's own emission target based on the NDC (Nationally Determined Contribution)), which may affect the above-mentioned carbon credit market conditions and trend intensity 57. Subsidies and the like are related to participation plans in internal and external projects.

[0063] 5 is a diagram showing an example of an estimate of the increase in the amount of non-ESG investment. In the example shown, access fund investment is linked to the company's "ESG score," and the investment amount is calculated by multiplying it by a basic unit. In the following explanation, the "ESG investment basic unit" is defined as follows, for example: In this embodiment, an inductive method based on past performance and a deductive method useful for future predictions are used. The choice of which to use is up to the company. In the case of the deductive method, the change in ESG investment amount is multiplied by the company's industry (for example, reflecting the level of interest in ESG) and the regional investment ratio (for example, reflecting the level of interest in each region), and the investment basic unit is calculated proportionally based on the company's business scale.

[0064] First, access fund investment (ESG) is related to the company's average ESG score, index, environmental score, and maturity score. These company's average ESG score and other factors correspond to the ESG investment unit mentioned above.

[0065] A company's average ESG score is related to the ESG score specifications (e.g., average value, specified period, etc.) based on each evaluation feedback, the company's environmental activity evaluation based on a questionnaire, and its maturity score. Here, the ESG score has a function to calculate the results of ESG activities based on an "ESG score" by a third-party organization. It is also possible to use an environmental maturity score based on an environmental activity evaluation using a questionnaire method, etc.

[0066] On the other hand, the ESG investment intensity is related to the functional and deductive approaches. The functional approach uses a historical performance table, which includes, for example, the company's own ESG scores and those of its peers versus investment amounts.

[0067] On the other hand, the deductive method uses the company's business scale. This company's business scale includes its share in the industry. The company's market size is affected by the trend in investors' ESG investment amounts (e.g., trends and forecasts of global ESG investment amounts), the ESG investment ratio in the company's industry (e.g., the business owner's investment ratio to total investments), and the ESG investment ratio in the business target area (e.g., the regional ratio of business target areas to total ESG investments).

[0068] 6 is a diagram showing an example of a forecast of ESG investment income per unit cost using a deductive method. First, in this embodiment, the "ESG investment per unit cost" is calculated by multiplying the growth in interest in ESG investment (ESG investment amount) based on the base year (year 0), and then multiplying that by the proportion of the company's own industry and the proportion of the region to calculate the (projected) income from ESG investment for the company. Therefore, the "ESG investment per unit cost" indicates the normal ESG income that can be expected if ESG activities are carried out at the same level as other companies.

[0069] In the example of a deductive methodology for forecasting ESG investment income per unit, as shown in the lower graph, the estimated ESG investment amount per unit increases each year (0-5).

[0070] FIG. 7 is a diagram showing an example of a predicted value of access funds (ESG). The access funds (ESG) prediction is calculated by multiplying the ESG investment amount basic unit shown in FIG. 6 above by a representative value (index) of ESG points issued by a third-party institution. A simulation is performed assuming that the ESG point index fluctuates from year to year. In the example shown, the actual ESG investment amount fluctuates relative to the estimate depending on the company's ESG points.

[0071] Here, an example of quantitative determination logic for income in this embodiment will be described. In this embodiment, the effects of introducing renewable energy (renewable energy) on decarbonization KPIs and management KPIs will be examined.

[0072] In this embodiment, for (1) the decarbonization KPI, the necessary amount of measures to be introduced is calculated from the decarbonization target. In this embodiment, if the solar cell installation is XXX (XXX: numerical value) kilowatts ("XXX_KW"), for example, the decarbonization reduction amount AA [tons] can be calculated as follows: XX (XX: numerical value) kWh × YY (YY: year) × ZZ (ZZ: numerical value) [tons] / kW.

[0073] Furthermore, in this embodiment, for (2) management KPI, "profit and loss" = "income" - "expenses", that is, (increase (maintenance) amount of orders for product A + contribution to investment capital increase + contribution to stock income + CC + subsidy) - (capital investment + operating costs + maintenance costs - carbon tax) = BB (BB: amount) ¥ (Japanese yen).

[0074] In this embodiment, there are two final decision logics for determining whether to implement a measure. In the first decision logic, the decision is made based on the profitability of the business. In the first decision logic, the payback plan is used instead of a single year. If BB > 0 yen, the measure is implemented, while if BB < 0 yen, the measure is not implemented or a management decision is made. A management decision can be to implement the measure if, for example, even if it results in a loss, it is very small compared to the size of the company (or within a range that is considered to be an acceptable investment), or if it is judged that the measure should be implemented even if it results in a loss in anticipation of future potential.

[0075] The second decision logic is based on the effect of the investment on decarbonization. In the second decision logic, the investment amount per unit of CO2 reduction is evaluated, and if it is higher than the carbon tax rate, it is not implemented (or implemented in some cases), and if it is lower, it is implemented. BB (BB: amount) ¥ (Japanese yen) / AA (AA: numerical value) CO2 [tons]) > Carbon tax rate

[0076] The simulation device 300 has the above-described configuration. Next, an example of the simulation screen 500 displayed on the dashboard 100 of the simulation device 300 will be described.

[0077] 8 to 10 are diagrams showing an example of a simulation screen 500. This simulation screen 500 is an example of a screen related to a simulation, and is displayed on the dashboard 100 shown in FIG. 1. In this embodiment, this simulation screen 500 is used to perform a simulation of the effects of measures ("decarbonization measures") that should be taken in consideration of the decarbonization target and the financial balance target.

[0078] In the simulation screen 500 shown in Figure 8, a list of proposed decarbonization measures 510 is located in the lower right, an emission reduction details field 520 is located in the upper right, an emission reduction target scope target input field 530 is located in the lower left, and a GHG emission breakdown field 540 is located in the upper left.

[0079] In the decarbonization measure proposal list 510, cursors 501 corresponding to multiple decarbonization measures are arranged vertically, and any of the cursors can be selected. In the example shown, "Consider changing procurement sources" is selected.

[0080] The simulation screen 500 presents multiple introduction conditions and displays the results of a simulation performed when decarbonization measures are implemented based on specific introduction conditions selected from the multiple introduction conditions (display step).

[0081] Specifically, when the operator clicks on one of the decarbonization measure cursors 501 (for example, "Consider changing procurement sources"), a condition input form 550 (corresponding to the decarbonization measure details input screen described later) is displayed for inputting effect simulation conditions as an example of conditions for introducing decarbonization measures, as shown in Figure 9.

[0082] In this condition input form 550, for example, the selected "Consideration of change of procurement source" is displayed as an effect simulation condition in the upper left corner 554, a current procurement status column 555 is displayed in the center of the horizontal direction, and a procurement source change scenario input column 556 is displayed on the right side.

[0083] The current procurement status column 555 displays the target product, target parts, and total GHG emissions at the top, and at least one supplier manufacturer (corresponding to the "supplier manufacturer" shown in the figure) at the bottom. In this example, supplier manufacturers include, for example, Company A, Company B, and Company C.

[0084] On the other hand, above the supplier change scenario input field 556, a display field 553 is displayed in which the scenario name, GHG emission reduction target, and GHG emission amount can be input, and at the bottom right of this, an add button 552 is displayed for adding a supplier and performing a simulation, and at the top right of this, a calculation execution button 551 is displayed for executing the simulation.

[0085] Here, as the scenario name indicates, the simulation results for a scenario in which procurement from Company B is reduced and parts from Company D are procured instead of parts from Company C, displaying a GHG emission reduction target of "12 tCO2e" and a GHG emission amount of "41 tCO2e." In this embodiment, "t" indicates "tons" of weight. In this embodiment, since the results of this simulation are determined to meet, for example, the decarbonization target, a display 556A indicating this, for example, "Emission target met," is displayed.

[0086] Furthermore, a Register New Reduction Method button 502 is displayed at the bottom of the decarbonization measure proposal list 510. This Register New Reduction Method button 502 is pressed when registering a new reduction method as the cursor described above. When the Register New Reduction Method button 592 is pressed, a form for inputting a new reduction method is displayed, allowing the new reduction method to be registered. The registered new reduction method is added to and displayed as a cursor in the decarbonization measure proposal list 21.

[0087] On the other hand, the emission reduction details field 520 shown in FIG. 8 is a display area in which the emission source can be identified, and Tier 0 to Tier 2 are displayed according to the shipping destination, such as Europe, Asia, or North America. Tier 0 indicates the target product. Here, the product PSCN is shown as an example. Tier 1 indicates the part name and quantity (weight) [g] for each part ID (identifier) ​​of the parts that make up the target product. Here, the target part name, "XXX unit," is displayed, for example, in a highlighted manner as a part that poses a problem in achieving the decarbonization target. Tier 2 indicates the part name and quantity (weight) [g] for each part ID of each part. Here, the target part name, "YYY panel," is displayed, for example, in a highlighted manner as a part that poses a problem in achieving the decarbonization target.

[0088] The emission reduction target scope target input field 530 has a target scope selection field 531A, a target category selection field 531B, and a target value field 532. When the target scope selection field 531 is clicked, multiple target scopes are displayed in the form of a pull-down menu, and one of the scopes can be selected (in the illustrated example, "Scope 3" is selected).

[0089] When the target category selection field 531B is clicked, a plurality of target categories are displayed in the form of a pull-down menu, and one of the categories can be selected (in the illustrated example, "Cat1 (Category 1)").

[0090] The target value field 532 is an input field for inputting a target value corresponding to the scope selected in the target scope selection field 531 and the category selected in the target category selection field 531B. A simulation is performed according to these input contents.

[0091] The GHG emissions breakdown column 540 displays the breakdown of GHG emissions for, for example, Company X, for the decarbonization measure corresponding to the cursor selected in the decarbonization measure proposal list 510, as a result of running a simulation in accordance with the input content in the emissions reduction target scope target input column 530.

[0092] In the illustrated example, for example, the emission rates for Category 1 of Scope 1, Scope 2, and Scope 3 (corresponding to "Cat 1" in the figure), and Category 11 of Scope 3 (corresponding to "Cat 11" in the figure) are displayed.

[0093] When the simulation results are displayed in display field 553 in condition input form 550 shown in FIG. 9, pressing display field 553 displays simulation result screen 560 showing detailed contents of the effect simulation results shown in FIG. 10.

[0094] The simulation result screen 560 displays the above-mentioned scenario, the solution to be introduced, cost forecast, and revenue forecast in a display field 561 on the left side. The revenue forecast includes indirect revenue.

[0095] The simulation result screen 560 displays, in a display field 562 in the horizontal center, the simulation results of carbon dioxide emissions by year, for the case where no measures are taken and for the case where the simulation is run under at least one scenario (in the illustrated example, scenarios (1) and (2)). These scenarios (1) and (2) represent scenarios in which decarbonization measures are adopted under the respective selected implementation conditions.

[0096] In the illustrated example, it is visually clear that adopting scenario (2) is more effective in reducing carbon dioxide emissions than adopting scenario (1), which is more effective in reducing carbon dioxide emissions than no measures.

[0097] The simulation result screen 560 shows, for example, a financial balance target, and in a display field 563 to the right of it, the results of simulating revenue for each year are displayed, showing the results when no measures are taken and when a simulation is run using at least one scenario (in the illustrated example, scenarios (1) and (2)). In the illustrated example, the higher the figure, the higher the revenue, and the lower the figure, the higher the costs.

[0098] In the illustrated example, it is visually clear that adopting scenario (2) is more effective in increasing revenue than adopting scenario (1), which is more effective in reducing carbon dioxide emissions than no measures. At the same time, although costs are higher in scenarios (1) and (2) than when no measures are taken, the revenues exceed the increased costs, so it can be seen that these are the scenarios that should be implemented.

[0099] As described above, the simulation device 300 according to this embodiment comprises a target input unit 1 that inputs a decarbonization target related to decarbonization and a financial target related to financial balance; a policy proposal selection unit 2 that sets the conditions for introducing decarbonization measures that correspond to the decarbonization target; a financial information processing unit 10 that calculates direct income and expenditure when decarbonization measures are implemented under the introduction conditions and estimates indirect income obtained as a result of non-financial information; a judgment support unit 7 that executes a simulation regarding whether the financial target and decarbonization target will be met, taking into account indirect income, when decarbonization measures are implemented under the introduction conditions; and a dashboard 100 that outputs a screen related to the simulation by the judgment support unit 7.

[0100] The simulation method according to this embodiment includes a target input step in which the target input unit 1 accepts input of a decarbonization target related to decarbonization and a financial balance target related to financial balance; a condition setting step in which the policy proposal selection unit 2 sets conditions for introducing decarbonization measures corresponding to the decarbonization target; a financial information processing step in which the financial information processing unit 10 calculates direct income and expenditure when decarbonization measures are implemented under the introduction conditions and estimates indirect income obtained as a result of non-financial information; a judgment support step in which the judgment support unit 7 performs a simulation regarding whether the financial balance target and decarbonization target will be met, taking into account indirect income, when decarbonization measures are implemented under the above-mentioned introduction conditions; and an output step in which a screen related to the simulation performed by the judgment support step is output to the dashboard 100.

[0101] In this way, indirect income can be quantitatively presented when formulating decarbonization measures, which can contribute to consensus among operators such as managers.

[0102] In this embodiment, the financial information processing unit 10 has a risk management unit 90 (mainly exemplified by the ESG investment capital increase impact calculation unit 52 and the carbon credit calculation unit 54) that estimates indirect income obtained as a result of non-financial information in the financial information processing step. In this way, decarbonization measures can be formulated based not only on direct income but also on quantitative indirect income.

[0103] In this embodiment, the risk management unit 90 manages at least one of pessimistic and optimistic risks that may affect the estimation of the indirect income described above. In this way, it is possible to formulate decarbonization measures taking such risks into consideration.

[0104] In this embodiment, the risk management unit 90 predicts pessimistic risks and optimistic risks through machine learning in the financial information processing step. In this way, it is possible to formulate decarbonization measures based on the risks according to the results of machine learning.

[0105] In this embodiment, in the financial information processing step, the approximate income calculation unit 5 calculates income in a direction that decreases income when pessimistic risks are managed by the risk management unit 90, and calculates income in a direction that increases income when optimistic risks are managed by the risk management unit 90. In this way, decarbonization measures can be formulated according to the risks managed by the risk management unit 90.

[0106] In this embodiment, in the display step, the screen related to the simulation presents multiple introduction conditions and is displayed in a manner that includes the results of the simulation when decarbonization measures are implemented based on specified introduction conditions selected from the multiple introduction conditions.

[0107] The present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the spirit and scope of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, the elements described in parallel in the present embodiment may be configured such that at least one of the elements is connected in series to the other elements.

[0108] The present invention can be applied to a simulation device relating to a technology for presenting decarbonization measures according to a decarbonization target.

[0109] 1....Goal input section, 2...Measure proposal selection section, 3...Specification calculation section, 4...Rough cost calculation section, 5...Rough income calculation section, 6...Profit calculation section, 7...Decision support section, 51...Product sales target calculation section, 52...ESG investment capital increase impact calculation section, 90...Risk management section, 100...Dashboard, 200...KPI tree, 300...Simulation device

Claims

1. A simulation device comprising: a goal input unit for inputting a decarbonization target regarding decarbonization and a financial target regarding a financial balance; a condition setting unit for setting conditions for introducing decarbonization measures corresponding to the decarbonization target; a financial information processing unit for calculating direct income and expenditures when the decarbonization measures are implemented under the introduction conditions and estimating indirect income obtained as a result of non-financial information; a judgment support unit for executing a simulation regarding whether or not the financial target and the decarbonization target will be met, taking into account the indirect income, when the decarbonization measures are implemented under the introduction conditions; and an interface for outputting a screen related to the simulation by the judgment support unit.

2. The simulation device according to claim 1, characterized in that the financial information processing unit has an indirect income estimation unit that estimates indirect income obtained as a result of the non-financial information.

3. The simulation device according to claim 2, characterized in that the indirect income estimation unit manages at least one of pessimistic risk and optimistic risk that may affect the estimation of the indirect income.

4. The simulation device according to claim 3, characterized in that the indirect income estimation unit predicts the pessimistic risk and the optimistic risk through machine learning.

5. The simulation device described in claim 3, characterized in that the financial information processing unit calculates income in a direction that reduces income when the indirect income estimation unit manages the pessimistic risk, and calculates income in a direction that increases income when the indirect income estimation unit manages the optimistic risk.

6. The simulation device described in claim 1, characterized in that the screen related to the simulation by the judgment support unit presents a plurality of the introduction conditions and includes the results of the simulation performed when the decarbonization measures are implemented based on a predetermined introduction condition selected from the plurality of introduction conditions.

7. A simulation method comprising: a goal input step in which a goal input unit accepts input of a decarbonization target regarding decarbonization and a financial balance target regarding a financial balance; a condition setting step in which a condition setting unit sets conditions for introducing decarbonization measures corresponding to the decarbonization target; a financial information processing step in which a financial information processing unit calculates direct income and expenditure when the decarbonization measures are implemented under the introduction conditions and estimates indirect income obtained as a result of non-financial information; a judgment support step in which a judgment support unit executes a simulation regarding whether or not the financial balance target and the decarbonization target will be met, taking into account the indirect income, when the decarbonization measures are implemented under the introduction conditions; and an output step in which a screen related to the simulation performed by the judgment support step is output to an interface.

8. The simulation method according to claim 7, characterized in that in the financial information processing step, an indirect income estimation unit estimates indirect income obtained as a result of the non-financial information.

9. The simulation method according to claim 8, characterized in that the indirect income estimation unit manages at least one of pessimistic risk and optimistic risk that may affect the estimation of the indirect income.

10. The simulation method according to claim 9, characterized in that the indirect income estimation unit predicts the pessimistic risk and the optimistic risk through machine learning.

11. The simulation method described in claim 9, characterized in that the financial information processing unit calculates income in a direction that reduces income when the indirect income estimation unit manages the pessimistic risk, and calculates income in a direction that increases income when the indirect income estimation unit manages the optimistic risk.

12. The simulation method described in claim 7, further comprising a display step of presenting a plurality of the introduction conditions on a screen relating to the simulation by the judgment support unit, and displaying the results of the simulation when the decarbonization measures are implemented based on a predetermined introduction condition selected from the plurality of the introduction conditions.

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