Supply chain risk evaluation device and method

Abstract

To make it possible to more appropriately evaluate an incident that may occur in a supply chain, with respect to a risk.SOLUTION: A supply chain risk evaluation device 1000 comprises: an information collection management unit 1100 for collecting restoration period information 2060 of an incident occurring in a supply chain, restoration pattern information 2120, and supply capability information of a product which is the object of the supply chain; an input / output interface unit 1600 for receiving a countermeasure plan for the incident; an incident influence scenario generation unit 1300 for generating an influence scenario indicating a degree of influence caused by the incident, from the occurrence to the restoration of the incident, on the capability of the supply chain by using the restoration period information, the restoration pattern information, and the supply capability information; and a supply chain supply-demand optimization calculation unit 1400 for identifying an evaluation value of the countermeasure plan that corresponds to a period for executing the countermeasure plan.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a technique for evaluating supply chain risks.

Background Art

[0002] As background art in this technical field, there is Patent Document 1. Patent Document 1 describes, "It has an item information acquisition means, a model setting means for setting a supply chain model corresponding individually to normal times and when a risk event occurs, an estimated data derivation means for deriving estimated data estimating the time-series situation in the supply chain, an actual result data acquisition means for acquiring actual result data from the supply chain in time series, a risk judgment means for judging the presence or absence of the occurrence of a risk event from the ratio of the estimated data and the actual result data, and when a risk event occurs, using a risk response supply chain model, performing a simulation, and a risk system derivation means for deriving a supply chain system and risk costs that minimize the risk loss occurring when a risk event occurs."

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Here, in order to improve the business continuity of the company itself, it is required to be prepared for disasters and geopolitical risks from normal times. Particularly from the perspective of supply chain risks, it is important to take countermeasures in consideration of the effects such as supply interruption from suppliers and an increase in transportation lead time, and the recovery period thereof. Also, since the period required until the execution of a countermeasure plan varies for each countermeasure plan, it is important to take a countermeasure plan in consideration of the period required for execution.

[0005] In contrast, Patent Document 1 describes a system that estimates the time-series state of a supply chain, determines the presence or absence of risk occurrence by comparing it with the actual data of the supply chain, and minimizes the loss caused by the risk and derives the risk cost when the risk occurs. However, in the description method of Patent Document 1, although a countermeasure plan can be formulated after the risk occurs, it is not possible to assume the risks that occur in the supply chain during normal times and take countermeasure plans in advance against those risks.

[0006] Therefore, an object of the present invention is to enable a more appropriate evaluation of risks for incidents that can occur in a supply chain, not limited to the presence or absence of risk occurrence. Note that an incident in the present application is an event that affects the supply chain and may require countermeasures, and includes accidents and events.

Means for Solving the Problems

[0007] To solve the above problems, in the present invention, an evaluation of an incident countermeasure plan is performed using supply chain recovery period information, recovery pattern information, and supply capacity information. Note that the evaluation of the present invention means specifying an evaluation value in the countermeasure plan, and although it is desirable to calculate the opportunity loss amount as the evaluation value, it also includes the calculation of the damage amount, the calculation of the delay period, and the like.

[0008] More specifically, in a supply chain risk assessment apparatus that assesses a supply chain in transactions between organizations, a recovery period information indicating a recovery period for an incident occurring in the supply chain, a recovery pattern information indicating a recovery pattern for the incident, and a supply capacity information indicating a supply capacity of a product targeted by the supply chain are collected by an information collection management unit, an input / output interface unit that receives a countermeasure plan for the incident, and an incident impact scenario generation unit that generates an impact scenario indicating a degree of impact from the occurrence to the recovery of the incident on the capacity of the supply chain caused by the incident, using the recovery period information, the recovery pattern information, and the supply capacity information. The supply chain risk assessment apparatus has an evaluation value specifying unit that specifies an evaluation value of the countermeasure plan according to a period for executing the countermeasure plan.

[0009] The present invention also includes a supply chain risk assessment method by a supply chain risk assessment apparatus, a supply chain risk assessment program that causes a supply chain risk assessment apparatus to function as a computer, and a storage medium storing the program. Further, a supply chain risk assessment system including the supply chain risk assessment apparatus and a method thereof are also an aspect of the present invention.

Effects of the Invention

[0010] According to the present invention, each incident assumed to occur in a supplier can be objectively evaluated. Further, even during normal times when an incident has not occurred, a more effective countermeasure plan can be formulated for the risk of the supplier. Problems, configurations, and effects other than those described above will be clarified by the following description of the embodiments.

Brief Description of the Drawings

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Mode for Carrying Out the Invention

[0012] Hereinafter, an embodiment of the present invention will be described. In this embodiment, an impact scenario due to an incident is generated for components of the supplier's supply capacity, such as the supplier's production capacity, transportation lead time, and inventory level, from public information such as the supplier's location information and hazard map information. Further, for each impact scenario due to an incident and for each countermeasure plan for the incident, a supply chain supply and demand optimization calculation is performed based on the disruption and recovery of supply and demand in the supply chain, and the assumed amount of opportunity loss of the company is calculated. Then, based on the expected value of the assumed amount of opportunity loss and the total amount of countermeasure costs for each risk scenario and countermeasure plan, it supports the selection of the countermeasure plan with the best cost-effectiveness for the risk.

[0013] More preferably, in a supply chain risk assessment device that assesses the supply chain in transactions between organizations, a recovery period information indicating the recovery period for an incident occurring in the supply chain, a recovery pattern information indicating the recovery pattern for the incident, and a supply capacity information indicating the supply capacity of the product targeted by the supply chain. An information collection management unit that collects the above, an input / output interface unit that receives a countermeasure plan for the incident, and an incident impact scenario generation unit that generates an impact scenario indicating the degree of impact from the occurrence to the recovery of the incident on the capacity of the supply chain caused by the incident, using the recovery period information, the recovery pattern information, and the supply capacity information. A supply chain risk assessment device having an evaluation value specifying unit that specifies an evaluation value of the countermeasure plan according to the period for executing the countermeasure plan. Furthermore, a supply chain risk assessment method using this, a supply chain risk assessment program that functions as a computer, and a storage medium storing this are also an aspect of this embodiment.

[0014] The impact scenario in this embodiment indicates the degree of impact on the supply chain's capabilities from the occurrence to the recovery of an incident. More preferably, it indicates the degree of impact on the business and utilization capabilities of the supply chain from the occurrence to the recovery of the incident. Also, the product (item) of this embodiment is an object handled in the supply chain, including raw materials, parts, assembled parts, modules, and units.

Example

[0015] In Example 1, the information collection and management unit 1100 also collects various information other than the recovery period information 2060, the recovery pattern information 2120, and the supply capacity information. Then, the incident impact scenario generation unit 1300 generates an impact scenario using these.

[0016] Also, in Example 1, an example of using the transportation lead time information 2070, the production capacity information 2100, and the inventory performance information 2190 as the supply capacity information will be described. However, for the transportation lead time information 2070, the production capacity information 2100, and the inventory performance information 2190, it is possible to generate incident impact scenario information using at least one of them. Furthermore, in Example 1, the transportation lead time impact scenario information 2130, the inventory impact scenario information 2140, and the production capacity impact scenario information 2150 are generated from the transportation lead time information 2070, the inventory performance information 2190, and the production capacity information 2100 respectively. However, as the impact scenario, it is possible to use at least one of the transportation lead time impact scenario information 2130, the inventory impact scenario information 2140, and the production capacity impact scenario information 2150. Hereinafter, the details of Example 1 will be described with reference to the drawings.

[0017] FIG. 1 is a diagram showing an example of the functional blocks of the supply chain risk assessment apparatus 1000 in the first embodiment. The supply chain risk assessment apparatus 1000 includes an information collection management unit 1100, a risk scenario generation unit 1200, an incident impact scenario generation unit 1300, a supply chain supply and demand optimization calculation unit 1400, a risk countermeasure plan evaluation result display unit 1500, an input / output interface unit 1600, and a data storage unit 2000.

[0018] First, the information collection management unit 1100 collects various information obtained from transaction data with suppliers and the like through the communication function and input function provided by the input / output interface unit 1600. That is, these information are collected from other devices and systems connected using the communication function, or input from users and the like using the input function. Then, the information collection management unit 1100 stores these in the data storage unit 2000.

[0019] The information to be collected is listed below. At this time, the information names stored in the data storage unit 2000 are also described in association. Handled item data: Handled item information 2010 Supplier location data obtained from map data and the like: Supplier location information 2020 Risk data obtained from a hazard map and the like: Incident occurrence risk information 2030 Incident occurrence probability data such as a hazard map: Risk occurrence probability information 2040 Recovery period required for disasters obtained from reports of governments, research institutions, etc.: Recovery period information 2060 Supplier's transport lead time data obtained from supplier transaction data and the like: Transport lead time information 2070 Transport lead time data at the time of incident occurrence obtained from reports of governments, research institutions, etc.: Additional transport lead time information 2080 Ratio data of available inventory at the time of incident occurrence obtained from reports of governments, research institutions, etc.: Available inventory information 2090 Production capacity data of each company obtained from supplier transaction data and the like: Production capacity information 2100 Data on the timing when an incident is assumed to occur: Incident occurrence assumed time point information 2110 Product price data obtained from transaction data with suppliers, etc.: Item price information 2160 BOM (Bill of Materials) data obtained from transaction data with suppliers and design data: BOM information 2170 Company's sales plan data: Demand information 2180 Actual inventory numbers of the company and its suppliers obtained from the company's database, EDI (Electronic Data Interchange) system, etc.: Actual inventory information 2190 Note that the "company" refers to the buyer who uses the supply chain risk assessment device 1000. However, when the supply chain risk assessment device 1000 is realized in a so-called cloud and shared by multiple companies, the information of each company is collected and stored separately. Also, a company is an example of an organization, and the object of this embodiment is not limited to companies, but also includes legal persons, public organizations, non-profit organizations, etc. Further, this example can be used not only by buyers but also by participants in the supply chain such as suppliers, carriers, and bases. Thus, the supply chain risk assessment system shown in FIG. 2 may be realized as an in-company system for a buyer or the like, or as a system that can be used by multiple companies (buyers and suppliers).

[0020] Also, the information collection management unit 1100 uses the input function provided by the input / output interface unit 1600 to accept the input of recovery patterns and countermeasure plans for incidents from the user. Then, the information collection management unit 1100 stores the recovery pattern as recovery pattern information 2120 in the data storage unit 2000. Further, the information collection management unit 1100 stores the countermeasure plan as countermeasure plan information 2200 in the data storage unit 2000.

[0021] In addition, the risk scenario generation unit 1200 generates risk scenario information 2050 including incidents that a supplier may experience and their probability data based on various information in the supply chain. Here, at least one of item handling information 2010, supplier location information 2020, incident occurrence risk information 2030, and risk occurrence probability information 2040 is used as the various information. For this generation, the risk scenario generation unit 1200 uses at least one of the item handling information 2010, supplier location information 2020, incident occurrence risk information 2030, and risk occurrence probability information 2040. However, it is more preferable to use all of this information. Here, it is desirable that these information are stored in the data storage unit 2000. Further, it is desirable that the risk scenario generation unit 1200 stores the generated risk scenario information 2050 in the data storage unit 2000.

[0022] In addition, the incident impact scenario generation unit 1300 generates an impact scenario for each countermeasure plan. Here, the impact scenario indicates the degree of impact from the occurrence to the recovery of the incident on the capabilities of the supply chain to respond to the incident. This capability includes transportation, inventory, and production capabilities. An example of the generation of this impact scenario is shown below. The incident impact scenario generation unit 1300 uses various information to generate transportation lead time impact scenario information 2130 indicating the impact scenario of the incident on the transportation lead time of the supplier. For this generation, at least one of the risk scenario information 2050, recovery period information 2060, transportation lead time information 2070, additional transportation lead time information 2080, and incident occurrence assumed time information 2110 is used. However, it is more preferable to use all of this information. Note that it is desirable that the incident impact scenario generation unit 1300 stores the generated transportation lead time impact scenario information 2130 in the data storage unit 2000.

[0023] In addition, the incident impact scenario generation unit 1300 generates inventory impact scenario information 2140 on the supplier's inventory due to an incident using various types of information. At least one of the risk scenario information 2050, available inventory information 2090, incident occurrence assumed time information 2110, and inventory performance information 2190 is used as the various types of information. However, it is more preferable to use all of this information. Note that it is desirable for the incident impact scenario generation unit 1300 to store the generated inventory impact scenario information 2140 in the data storage unit 2000.

[0024] In addition, the incident impact scenario generation unit 1300 generates production capacity impact scenario information 2150 on the supplier's production capacity due to an incident using various types of information. At least one of the risk scenario information 2050, recovery period information 2060, production capacity information 2100, incident occurrence assumed time information 2110, and recovery pattern information 2120 is used as the various types of information. However, it is more preferable to use all of this information. Note that the incident impact scenario generation unit 1300 stores the generated production capacity impact scenario information 2150 in the data storage unit 2000.

[0025] As a result of the above, the incident impact scenario generation unit 1300 will create an impact scenario including transport lead time impact scenario information 2130, inventory impact scenario information 2140, and production capacity impact scenario information 2150.

[0026] Note that the generation of the impact scenario in this embodiment can be executed as follows. The incident impact scenario generation unit 1300 creates an impact scenario using the recovery period information 2060, the recovery pattern information 2120, and the supply capacity information. The supply capacity information is information regarding the supply time in the supply chain and includes the transport lead time information 2070, the production capacity information 2100, and the inventory performance information 2190. In this case, the incident impact scenario generation unit 1300 generates the transport lead time impact scenario information 2130 from the recovery period information 2060 and the transport lead time information 2070. Also, the incident impact scenario generation unit 1300 generates the inventory impact scenario information 2140 from the inventory performance information 2190. Furthermore, the incident impact scenario generation unit 1300 generates the production capacity impact scenario information 2150 from the recovery pattern information 2120 and the production capacity information 2100.

[0027] Also, the supply chain supply-demand optimization calculation unit 1400 is an example of an evaluation value specifying unit that specifies the evaluation value of the countermeasure plan, and calculates the opportunity loss assumption amount information 2210 indicating the assumed amount of opportunity loss due to the incident as an example of the evaluation value. This opportunity loss amount includes the assumed opportunity loss amount of the corresponding company. Hereinafter, the supply chain supply-demand optimization calculation unit 1400 will be described using these as examples.

[0028] First, the supply chain supply-demand optimization calculation unit 1400 generates a supply chain model. For this purpose, the supply chain supply-demand optimization calculation unit 1400 uses at least one of the item information 2010, the transport lead time information 2070, the production capacity information 2100, the transport lead time impact scenario information 2130, the inventory impact scenario information 2140, the production capacity impact scenario information 2150, the item price information 2160, the BOM information 2170, the demand information 2180, the inventory performance information 2190, the countermeasure plan information 2200, and the countermeasure plan information 2200. However, it is more preferable to use all of this information. The details of generating the supply chain model will be described later.

[0029] Next, the supply chain demand and supply optimization calculation unit 1400 calculates opportunity loss assumption amount information 2210 indicating the assumed amount of opportunity loss of the company through supply chain demand and supply optimization calculation that calculates the PSI (Production, Sales, Inventory) of the company and its suppliers. Then, it is desirable for the supply chain demand and supply optimization calculation unit 1400 to store the calculated opportunity loss assumption amount information 2210 in the data storage unit 2000.

[0030] Also, the risk countermeasure plan evaluation result display unit 1500 is an example of an output unit that outputs various information. In this embodiment, the risk countermeasure plan evaluation result display unit 1500 displays risk scenario information 2050, countermeasure plan information 2200, countermeasure plan information 2200, and opportunity loss assumption amount information 2210. Furthermore, the risk countermeasure plan evaluation result display unit 1500 displays the countermeasure cost, the expected value of the opportunity loss assumption amount, and the total amount thereof for each risk scenario and countermeasure plan.

[0031] Next, FIG. 2 is a diagram showing a hardware configuration example of a supply chain risk evaluation system including the supply chain risk evaluation apparatus 1000 in this embodiment. In the supply chain risk evaluation system, the supply chain risk evaluation apparatus 1000 is connected to the terminal device 40 and the information providing device 50 via the network 30. First, the supply chain risk evaluation apparatus 1000 can be realized by a computer. For this reason, the supply chain risk evaluation apparatus 1000 includes a CPU 11, a RAM 12, a ROM 13, an auxiliary storage device 14, a display device 15, an input device 16, a media reading device 17, and an information transmission / reception device 18. Each of these configurations will be described below.

[0032] The CPU 11 is an example of a processor that executes various operations. In order to execute operations, the CPU 11 executes various processes by executing a predetermined supply chain risk evaluation program loaded from the auxiliary storage device 14 into the RAM 12.

[0033] Also, the supply chain risk assessment device 1000 is an application program that can be executed, for example, on an OS (Operating System) program. This supply chain risk assessment program may be installed in the auxiliary storage device 14 from a portable storage medium via the media reading device 17, for example. In this way, the supply chain risk assessment program is stored in a storage medium. Then, the CPU 11 executes the functions of the information collection management unit 1100, the risk scenario generation unit 1200, the incident impact scenario generation unit 1300, and the supply chain supply and demand optimization calculation unit 1400 according to the supply chain risk assessment program.

[0034] Also, the RAM 12 is a memory that stores the supply chain risk assessment program executed by the CPU 11 and data necessary for the execution of this supply chain risk assessment program. The ROM 13 is a memory that stores programs necessary for the startup of the supply chain risk assessment device 1000.

[0035] Also, the auxiliary storage device 14 is, for example, a device such as an HDD (Hard Disk Drive). It may be an SSD (Solid State Drive) using a flash memory or the like. Note that the auxiliary storage device 14 may be realized by a device separate from the supply chain risk assessment device 1000. In this case, the auxiliary storage device 14 may be realized by a file server connected to the network 30 or the like. Further, the auxiliary storage device 14 may be provided in both the supply chain risk assessment device 1000 and the outside, and may store information and the like in a shared manner.

[0036] Further, the display device 15 is, for example, a device such as a CRT display, an LCD (Liquid Crystal Display), or an organic EL (Electro-Luminescence) display. And the display device 15 executes the function of the risk countermeasure plan evaluation unit 1500 in FIG. 1. Also, the input device 16 is, for example, a device such as a keyboard, a mouse, or a microphone. And the input device 16 executes the function of the input / output interface unit 1600 in FIG. 1. Note that when the supply chain risk evaluation device 1000 is realized by a so-called server, the display device 15 and the input device 16 can be omitted. Further, in this case, the functions of the display device 15 and the input device 16 will be provided in the terminal device 40. Further, the display device 15 and the input device 16 may be integrally configured such as a touch panel.

[0037] Also, the media reading device 17 is a device that reads information from a portable storage medium having portability such as a CD-ROM. Also, the information transmitting / receiving device 18 is a device that transmits and receives data to and from external devices such as the terminal device 40 via the network 30. For example, it can be realized by a communication device that communicates with the network 30 such as a wired LAN or a wireless LAN, a dial-up router, an infrared communication device, or the like. Note that the information transmitting / receiving device 18 executes the function of the input / output interface unit 1600 in FIG. 1.

[0038] Also, in this embodiment, since the supply chain risk evaluation device 1000 is realized by a server, the network 30, the terminal device 40, and the information providing device 50 are used, and these will also be described. The network 30 only needs to be able to realize communication between devices, and its type such as a LAN or a WAN does not matter. Also, the terminal device 40 can be realized by a computer such as a PC or a tablet terminal, has the functions of the display device 15 and the input device 16, accepts operations from the user, and displays processing results in the supply chain risk evaluation device 1000 and the like. Note that in FIG. 2, only one terminal device 40 is shown, but the number may be plural.

[0039] In addition, the information providing device 50 includes an EDI system and a system for providing corporate information, and can be implemented by a computer such as a server that provides various types of information. And the supply chain risk assessment device 1000 will acquire various types of information from the information providing device 50 as described later. With the above, the description of the configuration of this embodiment is completed, and then the processing flow of this embodiment will be described.

[0040] FIG. 3 is a flowchart showing the overall processing flow of the supply chain risk assessment device 1000 in the first embodiment. First, the risk scenario generation unit 1200 of the supply chain risk assessment device 1000 generates risk scenario information 2050 indicating the risk scenario of the supplier (step S10). Also, the incident impact scenario generation unit 1300 generates an incident impact scenario based on the generated risk scenario information 2050, etc. (step S20).

[0041] In addition, the supply chain supply-demand optimization calculation unit 1400 executes supply chain supply-demand optimization calculation based on the generated incident impact scenario (step S30). And the risk countermeasure plan evaluation result display unit 1500 displays the expected value of the opportunity loss assumption amount and the countermeasure cost (step S40). Hereinafter, the details of the processing shown in this flowchart will be described. Specifically, the details of step S10 will be described with reference to FIGS. 4, 7 to 11.

[0042] Also, the details of step S20 will be described with reference to FIGS. 5, 12 to 21, and the details of the simulation in step S30 will be described with reference to FIGS. 6, 22 to 28 respectively. Furthermore, the detailed screen of the display in step S40 will be described later with reference to FIG. 28.

[0043] First, FIG. 4 is a flowchart showing the flow of the risk scenario generation process (step S10) in this embodiment. The details of the process in FIG. 4 will be described in detail below.

[0044] First, the risk scenario generation unit 1200 acquires various types of information via the input / output interface unit 1600 (step S110). The information to be acquired includes at least one of information on items handled by suppliers, location information of each supplier, incident occurrence risk information related to the location information of each supplier, and the occurrence probability of risks. However, more preferably, all of this information is acquired. The risk scenario generation unit 1200 stores the acquired data in the data storage unit 2000 as item handling information 2010, supplier location information 2020, incident occurrence risk information 2030, and risk occurrence probability information 2040. Here, the process of step S110 is repeatedly executed for each supplier. Here, the data acquired in the process of step S110 and the process will be described in detail.

[0045] First, FIG. 7 is a diagram showing an example of the item handling information 2010 used in the first embodiment. In FIG. 7, the item handling information 2010 has fields for company name (2011) and item (2012). In this way, the item handling information 2010 shows data on suppliers and the items handled by the suppliers. The item handling information 2010 is obtained, for example, by manual input / data upload via the input / output interface unit 1600 or by connecting to an EDI system or the like to acquire data.

[0046] Also, FIG. 8 is a diagram showing an example of the supplier location information 2020 used in the first embodiment. In FIG. 8, the supplier location information 2020 has fields for company name (2021) and location information (2022). The supplier location information 2020 shows the location information of the locations of each supplier stored in the item handling information 2010 in FIG. 7. For the location information (latitude / longitude) of the company, the supplier location information 2020 acquires the latitude / longitude information by comparing the address information existing in the EDI or public company information with the public map information from the EDI or public company information.

[0047] FIG. 9A and FIG. 9B are diagrams showing an example of incident occurrence risk information 2030 used in Example 1. In the present application, the incident occurrence risk information 2030 will be described separately in two parts, FIG. 9A and FIG. 9B, but it may also be configured integrally.

[0048] First, in FIG. 9A, it shows that the incident occurrence risk information 2030 has fields of risk (2031a), incident (2032a), and polygon ID (2033a). In this way, the incident occurrence risk information 2030 indicates data of risks that may occur in the supplier, incidents that occur in the supplier due to the risks, and polygon IDs regarding the damage range.

[0049] Also, in FIG. 9B, it shows that the incident occurrence risk information 2030 has fields of polygon ID (2031b) and damage range (2032b). Here, in FIG. 9B, position information for specifying the damage range is shown for the polygon ID in FIG. 9A. For example, the damage range of the polygon ID "1" for the risk "flood" and incident "0.0 - 0.5m inundation" in FIG. 9A is as follows. That is, it is the area within the polygon composed of polygon ID "1" and damage range "35.36469700,139.36724700, 35.35327094,139.36715574, 35.35034200,139.36867800" in FIG. 9B.

[0050] The incident occurrence risk information 2030 can be obtained, for example, from public information such as hazard maps provided by the Ministry of Land, Infrastructure, Transport and Tourism or the Geospatial Information Authority of Japan. Note that hazard map information provided by insurance companies, evaluation institutions, etc. may be purchased and registered as data via the input / output interface unit 1600. Therefore, the information providing apparatus 50 in FIG. 2 can provide a hazard map (information).

[0051] FIG. 10 is a diagram showing an example of risk occurrence probability information 2040. This risk occurrence probability information 2040 has fields of risk (2041) and occurrence probability (2042). And the risk occurrence probability information 2040 indicates the occurrence probability of the risk corresponding to the incident occurrence risk information 2030. Here, the occurrence probability of the risk is obtained from public information such as a hazard map provided by, for example, the Ministry of Land, Infrastructure, Transport and Tourism or the Geospatial Information Authority of Japan. Note that hazard map information provided by an insurance company, an evaluation institution, etc. may be purchased and registered as data via the input / output interface unit 1600.

[0052] Returning to the flowchart of FIG. 4, the risk scenario generation process will be described. Next, the risk scenario generation unit 1200 generates risk scenario information 2050 for each supplier and for each incident occurrence risk using various types of information (step S120). Here, at least one of the above-described supplier location information 2020, incident occurrence risk information 2030, and risk occurrence probability information 2040 is used as the various types of information. However, in a more preferred embodiment, all the information is used. Note that step S120 is repeatedly executed for each incident occurrence risk.

[0053] Hereinafter, the details of the information, data, and its processing generated in this step will be described. FIG. 11 is a diagram showing an example of risk scenario information 2050 used in the first embodiment. This risk scenario information 2050 has fields of company name (2051), incident (2052), and occurrence probability (2053). The risk scenario information 2050 indicates the assumed incident and its occurrence probability for each company. The method for generating the risk scenario information 2050 by the risk scenario generation unit 1200 will be described below.

[0054] For example, the supplier location information of the company name "Company A" in Figure 8 is "35.5510000, 139.6820000". For each polygon ID in Figure 9, for the polygon defined by the damage range, it is determined whether the supplier location information is inside or outside the polygon. In the examples of Figure 9A and Figure 9B, it is as follows. For the risk "flood", the incident "0.5 - 3.0m inundation", and the damage range of polygon ID "1000" "35.552857, 139.679958, 35.557557, 139.682905, 35.547137, 139.684566, 35.544282, 139.691100, 35.553149, 139.694955", the inside of the polygon is targeted. And within this polygon, the supplier location information "35.5510000, 139.6820000" of the company name "Company A" with supplier location information 2020 shown in Figure 8 exists. Furthermore, since the occurrence probability of the risk "flood" in the risk occurrence probability information 2040 shown in Figure 10 is "0.00001", the incident of the company name "Company A" in Figure 11 is "0.5 - 3.0m inundation", and the occurrence probability is "0.00001".

[0055] This concludes the description of step S120, that is, the process of step S10. Next, the details of the process of step S20 in Figure 3 will be described. Figure 5 is a flowchart showing the flow of the incident impact scenario generation process (step S20) in the first embodiment.

[0056] First, the incident impact scenario generation unit 1300 acquires various information via the input / output interface unit 1600 (step S210). The incident impact scenario generation unit 1300 stores the acquired information in the data storage unit 2000. Here, the various information acquired and stored is at least one of the following. Information regarding the recovery period of the incident: Recovery period information 2060 Information regarding the transport lead time: Transport lead time information 2070 Information regarding the additional lead time added due to the impact when the incident occurs: Additional transport lead time information 2080 Information on inventory losses at the time of incident: Available inventory information 2090 Information on production capacity: Production capacity information 2100 Information on the assumed time of incident occurrence: Incident occurrence assumed time information 2110 Information on the pattern during the recovery period from an incident: Recovery pattern information 2120 Hereinafter, details of these information and the processing after step S220 will be described. FIG. 12 is a diagram showing an example of the recovery period information 2060 used in the first embodiment. The recovery period information 2060 has fields of an incident (2061) and a recovery period (2062). Thus, the recovery period information 2060 indicates the recovery period, which is the period from the occurrence of the incident to the recovery to the normal state. The recovery period information 2060 is obtained, for example, by web crawling and scraping from public information such as disaster reports issued by the government or research institutions. Note that non-public information obtained individually may be registered by manual input or data upload via the input / output interface unit 1600.

[0057] Also, FIG. 13 is a diagram showing an example of the transport lead time information 2070 used in the first embodiment. The transport lead time information 2070 has fields of a transport origin (2071), a transport destination (2072), and a lead time (2073). Thus, the transport lead time information 2070 indicates the transport lead time from the transport origin company to the transport destination company. Also, the transport lead time information 2070 is obtained, for example, by manual input / data upload via the input / output interface unit 1600 or by connecting to an ERP system, an EDI system, etc.

[0058] Also, FIG. 14 is an example of the additional transportation lead time information 2080 used in Example 1. The additional transportation lead time information 2080 has fields for an incident (2081), an additional transportation lead time (2082), and an impact period (2083). Thus, the additional transportation lead time information 2080 indicates the additional transportation lead time for an incident and its impact period. For example, the additional transportation lead time information 2080 is associated with past supplier transaction data, the presence or absence of past incidents, and the content of the incidents from an EDI system or the like connected via the input / output interface unit 1600, and is calculated and obtained by a method such as machine learning. Note that the additional transportation lead time information 2080 may be obtained by manual input or data upload.

[0059] Also, FIG. 15 is a diagram showing an example of the available inventory information 2090 used in Example 1. The available inventory information 2090 has an incident (2091) and an available inventory coefficient (2092). Therefore, the available inventory information 2090 indicates the coefficient of the available number of inventories when an incident occurs. Here, a specific example of the available inventory information 2090 will be described with reference to FIG. 15. A certain company has 100 units of inventory before an incident occurs. When an incident of "0.0 to 0.5 m flooding" occurs, the available number of inventories is "100 × 1.0 = 100". Also, when an incident of "0.5 to 3.0 m flooding" occurs, the available number of inventories is "100 × 0.5 = 50".

[0060] Also, the available inventory information 2090 is obtained, for example, by manual input or data upload via the input / output interface unit 1600. For example, if the incident is flooding, the available inventory information 2090 is mechanically calculated based on the inventory management situation and building information to determine what percentage of the inventory is available according to the flood depth. Also, if the incident is an earthquake, the available inventory information 2090 can estimate the situation of the building at the time of the earthquake from the structural seismic resistance index.

[0061] Further, FIG. 16 is a diagram showing an example of production capacity information 2100 used in Example 1. The production capacity information 2100 has fields of company name (2101), time point (2102), and production capacity (2103). Therefore, the production capacity information 2100 indicates information regarding the production capacity of a company at a certain time point, for example, the number of units that can be produced. Here, a specific example of the production capacity information 2100 will be described with reference to FIG. 16. At the time point of "2023 / 6 / 23" for the company name "Company A", the production capacity is "140". For example, the production capacity information 2100 is obtained from the company's own ERP system or the production management system of a supplier via the input / output interface unit 1600. Note that the production capacity information 2100 may also be obtained by manual input or data upload.

[0062] Further, FIG. 17 is a diagram showing an example of incident occurrence assumed time point information 2110 used in Example 1. The incident occurrence assumed time point information 2110 has fields of company name (2111), incident (2112), and incident occurrence assumed time point (2113). Therefore, the incident occurrence assumed time point information 2110 indicates the assumed time point of occurrence of an incident occurring in a company. Here, a specific example of the incident occurrence assumed time point information 2110 will be described with reference to FIG. 17. For the company name "Company A" and the incident "0.5 to 3.0 m flooding", the assumed incident occurrence time point is "2023 / 6 / 26". For example, the incident occurrence assumed time point information 2110 is obtained by manual input or data upload via the input / output interface unit 1600. For example, for the incident occurrence assumed time point information 2110, the user can arbitrarily set the time point, or the time point is generated by a random number within a specific period.

[0063] Further, FIG. 18 is a diagram showing an example of an input screen of recovery pattern information 2120 in Example 1. In FIG. 18, the pattern input screen 181 and the pattern input screen 182 are example screens for inputting the recovery pattern of production capacity. Here, the unit time t is defined as "number of days elapsed since the incident occurred / recovery period". However, it is assumed that the number of days elapsed since the incident occurred does not exceed the recovery period, and the possible values of the unit time t are 0 ≦ t ≦ 1. Production capacity correction coefficient αt is defined as the degree of production capacity recovery from an incident at time t, and the production capacity at time t can be calculated by multiplying the production capacity 2103 of the production capacity information 2100 in FIG. 16 by α t By setting α at the time of recovery, that is, when t = 1, it represents that the production capacity returns to normal t

[0064] Next, the specific content of FIG. 18 will be described. The pattern input screen 181 in FIG. 18 shows an input example where the recovery pattern is a rectangular wave. This is an example simulating the case of recovering to normal as soon as possible. For example, to explain the data example on the pattern input screen 181, it shows that the production capacity does not return at all and remains zero from the time of the incident to the time of recovery, and the initial production capacity is restored all at once at the time of recovery. Assume that the production capacity of company "A" in the production capacity information 2100 shown in FIG. 16 is constant at "140", an incident occurs, and the recovery period is 4 days. In this case, "Day 1: t = (1 / 4), α 0.25 = 0.0, Day 2: t = (2 / 4), α 0.5 = 0.0, Day 3: t = (3 / 4), α 0.75 = 0.0, Day 4: t = (4 / 4), α 1.0 = 1.0". And the production capacity is "Day 1: 140 × α 0.25 = 0, Day 2: 140 × α 0.5 = 0, Day 3: 140 × α 0.75 = 0.0, Day 4: 140 × α 1.0 = 100".

[0065] Also, the pattern input screen 182 shows an input example where the recovery pattern is linear. This is an example simulating the case of gradually recovering to normal from the occurrence of an incident. To explain the data example on the pattern input screen 182, it shows that the production capacity is linearly restored from the time of the incident to the time of recovery. Assume that the production capacity of company "A" in the production capacity information 2100 shown in FIG. 16 is constant at "140", an incident occurs, and the recovery period is 4 days. In this case, "Day 1: t = (1 / 4), α 0.25 = 0.25, t = (2 / 4), α​0.5 = 0.05, Day 3: t = (3 / 4), α 0.75 = 0.75, Day 4: Day 4: t = (4 / 4), α 1.0 = 1.0. And the production capacity is, "Day 1: 140 × α 0.25 = 35, Day 2: 140 × α 0.5 = 70, Day 3: 140 × α 0.75 = 105, Day 4: 140 × α 1.0 = 140".

[0066] Also, the recovery pattern setting 183 shows an example of the setting screen for the recovery pattern for an incident. The recovery pattern setting 183 accepts the setting of what kind of recovery pattern to take for each incident.

[0067] Returning to the flowchart of FIG. 5, the processing after step S220 will be described. The incident impact scenario generation unit 1300 generates the transport lead time impact scenario information 2130 using various information (step S220). This various information includes at least one of the risk scenario information 2050, the transport lead time information 2070, the additional transport lead time information 2080, and the incident occurrence assumed time point information 2110. However, more preferably, all this information is used. Note that steps S220 to S240 are repeatedly executed for each risk scenario. Next, all the information used in step S220 and its processing will be described in detail.

[0068] First, FIG. 19 is a diagram showing an example of the transport lead time impact scenario information 2130 in Embodiment 1. The transport lead time impact scenario information 2130 has fields of the transport origin (2131), the transport destination (2132), the time point (2133), and the incident - considered lead time (2134). Thus, the transport lead time impact scenario information 2130 indicates the lead time from the transport origin to the transport destination at the time of the incident occurrence.

[0069] Next, a specific example of the method for generating the transportation lead time impact scenario information 2130 will be described. For example, in the case of the company name "Company A" in the risk scenario information 2050 shown in FIG. 11, it is as follows. First, when the incident "0.5 to 3.0 m flooding" occurs, the additional lead time is the lead time from the origin "Company A" to the destination "Company H" in the transportation lead time information 2070 shown in FIG. 13, which is "2 days". And for the incident "0.5 to 3.0 m flooding" in the additional transportation lead time information 2080 shown in FIG. 14, the additional transportation lead time is "5 days" and the impact period is "7 days". Furthermore, the incident occurrence time of the company name "Company A" in the incident occurrence assumption time information 2110 shown in FIG. 17 is "2023 / 6 / 26". From the above, the incident - considered transportation lead time from the origin "Company A" to the destination "Company H" from the time "2023 / 6 / 26" to "2023 / 7 / 3" in the transportation lead time impact scenario information 2130 shown in FIG. 19 is "2 days + 7 days = 9 days".

[0070] Returning to the flowchart of FIG. 5, step S230 will be described. The incident impact scenario generation unit 1300 generates inventory impact scenario information 2140 using various information (step S230). Here, the various information includes at least one of the risk scenario information 2050, available inventory information 2090, and incident occurrence assumption time information 2110. However, more preferably, it is desirable to use all of this information. Next, the information used in step S230 and its processing will be described in detail.

[0071] First, FIG. 20 is a diagram showing an example of the inventory impact scenario information 2140 in Example 1. The inventory impact scenario information 2140 has fields for company name (2141), time point (2142), and available inventory coefficient (2143). Therefore, the inventory impact scenario information 2140 indicates the available inventory coefficient of the company at the time of incident occurrence.

[0072] Next, a specific example of the method for generating the inventory impact scenario information 2140 by the incident impact scenario generation unit 1300 will be described below. For example, assume that an incident of "0.5 to 3.0 m inundation" occurs at Company "A" in FIG. 11. In this case, the available inventory coefficient for the incident of "0.5 to 3.0 m inundation" in FIG. 15 is "0.5". And the incident occurrence time of Company "A" in the incident occurrence assumption time point information 2110 shown in FIG. 17 is "2023 / 6 / 26". From these, the available inventory coefficient at the time point of "2023 / 6 / 26" for Company "A" in the inventory impact scenario information 2140 shown in FIG. 20 is "0.5".

[0073] Returning to the flowchart of FIG. 5, step S240 will be described. The incident impact scenario generation unit 1300 generates production capacity impact scenario information 2150 using various information (step S240). This various information includes at least one of risk scenario information 2050, recovery period information 2060, production capacity information 2100, incident occurrence assumption time point information 2110, and recovery pattern information 2120. However, more preferably, it is desirable to use all of this information. Next, the information used in step S240 and its processing will be described in detail.

[0074] FIG. 21 is a diagram showing an example of the production capacity impact scenario information 2150 in Example 1. The production capacity impact scenario information 2150 has fields of company name (2151), time point (2152), and incident - considered production capacity (2153). Therefore, the production capacity impact scenario information 2150 indicates the production capacity considering the recovery state of the company from the incident at the time of incident occurrence.

[0075] Next, a specific example of the method for generating the production capacity impact scenario information 2150 by the incident impact scenario generation unit 1300 will be described below with reference to FIGS. 11 to 21.

[0076] Based on the risk scenario information 2050 shown in Figure 11, assume that flooding of 0.5 to 3.0 m occurs at Company A on June 26, 2023. At this time, since the recovery period due to the flooding is 7 days from Figure 12, it can be seen that the production capacity of Company A will be affected from June 26, 2023 to July 3, 2023. Also, the recovery pattern in the production capacity (production capacity information 2100 in Figure 16) during this period is "linear with a correction coefficient of 0.0 at the time of incident and 1.0 at the time of recovery" from the pattern input screen 182 in Figure 18. From this, the daily production capacity of Company A from June 26, 2023 to July 3, 2023 will be 0, 20, 40, 60, 80, 100, 120, 140.

[0077] This concludes the explanation of step S240, that is, the process of step S20.

[0078] Next, the details of step S30 in Figure 3 will be explained. Figure 6 is a flowchart showing the flow of the supply chain demand and supply optimization calculation process (step S30) in the first embodiment.

[0079] First, the supply chain demand and supply optimization calculation unit 1400 acquires various information via the input / output interface unit 1600 (step S310). The supply chain demand and supply optimization calculation unit 1400 stores the acquired information in the data storage unit 2000. Here, the various information to be acquired and stored is at least one of the following. Information on the unit price of products handled by the supplier: Item price information 2160 BOM information of the products handled: BOM information 2170 Company's own demand information: Demand information 2180 Information on the initial inventory of supply chain constituent companies: Inventory performance information 2190 Countermeasure case information for incidents: Countermeasure case information 2200 Details of these information and the processes after step S320 will be described below. FIG. 22 is a diagram showing an example of item price information 2160 in Embodiment 1. The item price information 2160 has fields of company name (2161), item (2162), quantity (2163), and unit price (2164). Therefore, the item price information 2160 indicates the unit price for each product and quantity handled by the company. The item price information 2160 is obtained, for example, through manual input / data upload via the input / output interface unit 1600 or by collaborating with an EDI system or the like.

[0080] Also, FIG. 23 is a diagram showing an example of BOM information 2170 in Embodiment 1. The BOM information 2170 has fields of parent part (2171) and child part (2172). Therefore, the BOM information 2170 indicates the child parts necessary for manufacturing the parent part. The BOM information 2170 is obtained, for example, from trading companies such as an ERP system or a supplier via the input / output interface unit 1600.

[0081] Also, FIG. 24 is an example of demand information 2180 in Embodiment 1. This data table has fields of time point (2181), company name (2182), item (2183), and demand (2184). Therefore, the demand information 2180 is information regarding the demand for the products (items) handled by the company at each time point. The demand information 2180 is obtained, for example, through manual input / data upload of information generated from the company's sales plan, demand forecast, etc. via the input / output interface unit 1600 or by connecting to the company's database. Note that the company's database can be realized by the above-mentioned file server or information providing device 50.

[0082] Also, FIG. 25 is a diagram showing an example of inventory performance information 2190 in Example 1. The inventory performance information 2190 has fields of time point (2191), company name (2192), item (2193), and inventory quantity (2194). Therefore, the inventory performance information 2190 is information regarding the inventory quantity of products (items) handled by a company at the initial time point of the simulation. Also, the inventory performance information 2190 is obtained, for example, by manual input / data upload via the input / output interface unit 1600 or by connecting to an ERP system, an EDI system, etc.

[0083] Returning to the flowchart of FIG. 6, the description of the supply chain supply-demand optimization calculation process will be continued. The supply chain supply-demand optimization calculation unit 1400 sets the supply chain model (step S320). For this setting of the supply chain model, the supply chain supply-demand optimization calculation unit 1400 performs an MRP calculation based on its own demand information. As a result, the supply chain supply-demand optimization calculation unit 1400 will set its own demand data, BOM data, transportation lead time data, inventory data, and production capacity data necessary for calculating the PSI of itself and its suppliers. These pieces of information use, for example, the handled item information 2010, transportation lead time information 2070, production capacity information 2100, item price information 2160, BOM information 2170, demand information 2180, and inventory performance information 2190.

[0084] Also, the supply chain supply-demand optimization calculation unit 1400 acquires the countermeasure case information 2200 (step S330). Next, the information used in step S330 will be described in detail.

[0085] FIG. 26 is a diagram showing an example of a countermeasure case information input screen which is an input screen for the countermeasure case information 2200 in Example 1. In FIG. 26, three screens of countermeasure case information input screens 261 to 263 are shown. First, the countermeasure case information input screen 261 shows an example of an input screen when setting a countermeasure plan for inventory increase. And in the example of FIG. 26, the countermeasure case information input screen 261 shows an input example where the inventory addition amount of the item "ProdA" of the company name "Company H" is 500, the countermeasure execution period required to increase the inventory is 3 days, and the countermeasure cost at that time is 1 million yen. In this case, it means that "Company H" invests 1 million yen to implement a countermeasure to uniformly increase the inventory of "ProdA" by 500 units from the time point (2191) of the inventory performance information 2190 in FIG. 25 to the end point of the supply-demand optimization calculation.

[0086] Also, the countermeasure case information input screen 262 shows an example of an input screen when setting a countermeasure plan for multiple company purchases. And in the example of FIG. 26, the countermeasure case information input screen 262 shows that when "Company H" purchases the item "ItemA", the procurement source companies are "Company A, Company D", the purchase ratio is "0.7, 0.3", and the countermeasure cost at that time is 3 million yen. Also, the countermeasure execution period at the time of multiple company purchases means the period required to change the purchase ratio of the procurement source company when an incident occurs in either of the procurement source companies. And it shows that when an incident occurs in Company A, the execution period for changing the purchase ratio of Company D from 0.3 to 1.0 is 7 days.

[0087] Also, the countermeasure case information input screen 263 shows an example of an input screen when setting a countermeasure plan for supply chain switching. And in the example of FIG. 26, the countermeasure case information input screen 263 shows that when switching from the switching target "Company B" handling the item "PartsA" to the switching destination "Company E", the countermeasure execution period is "14 days" and the countermeasure cost is "0.5 million yen".

[0088] Return to the flowchart of FIG. 6 and continue the explanation of the supply chain supply-demand optimization calculation process. For each risk scenario and each countermeasure plan, the supply chain supply-demand optimization calculation unit 1400 sets an incident countermeasure supply chain model (step S340). For setting this incident countermeasure supply chain model, the supply chain supply-demand optimization calculation unit 1400 sets it using information, for example, with respect to the supply chain model set in step S320. Update the settings regarding the supply chain, transportation lead time, inventory, and production capacity. Here, the information used for this update is at least one of risk scenario information 2050, transportation lead time impact scenario information 2130, inventory impact scenario information 2140, production capacity impact scenario information 2150, and countermeasure plan information 2200.

[0089] As this update, for example, taking the case where flooding of 0.5 to 3.0 m occurs at Company A on June 26, 2023 from the risk scenario information 2050 in FIG. 11 as an example. The production capacity of Company A from June 26, 2023 to July 3, 2023 in the production capacity information 2100 in FIG. 16 is updated to 140. Also, from the production capacity impact scenario information 2150 in FIG. 21, the production capacity of Company A from June 26, 2023 to July 3, 2023 is updated to 0, 20, 40, 60, 80, 100, 120, 140.

[0090] Return to the flowchart of FIG. 6 and continue the explanation of the supply chain supply-demand optimization calculation process. The supply chain supply-demand optimization calculation unit 1400 performs supply chain supply-demand optimization calculation (step S350). As the supply chain supply-demand optimization calculation, the supply chain supply-demand optimization calculation unit 1400 performs supply-demand optimization calculation based on the payment and receipt calculation of PSI with the incident countermeasure supply chain model set in step S340 as the input. As a result, the supply chain supply-demand optimization calculation unit 1400 identifies the estimated amount of opportunity loss of the supply chain constituent enterprises and outputs this. The estimated amount of opportunity loss is defined, for example, as "(total delivery requirement - number of products that could be delivered on the delivery required date)". Here, the supply-demand optimization calculation is executed by a simulation method, a mathematical optimization method, or the like.

[0091] Also, the supply chain demand and supply optimization calculation unit 1400 calculates the assumed amount of opportunity loss (step S360). Next, the information used in step S360 and the details of the processing will be described.

[0092] First, FIG. 27 is a diagram showing an example of the assumed opportunity loss amount information 2210 in the first embodiment. The assumed opportunity loss amount information 2210 has fields of the target company (2211), occurrence probability (2212), incident (2213), countermeasure (2214), and assumed opportunity loss amount (2215). Therefore, the assumed opportunity loss amount information 2210 is information regarding the assumed opportunity loss amount of the company for each countermeasure when an incident occurs in the target company. Then, the supply chain demand and supply optimization calculation unit 1400 calculates the assumed opportunity loss amount information 2210 based on the calculated assumed opportunity loss amount in the demand and supply optimization calculation of step S350 and the unit price (2164) of the item price information 2160 in FIG. 22. This concludes the description of step S360, that is, the processing of step S30.

[0093] Next, an example of the output content of the processing result in the first embodiment will be described. FIG. 28 is a diagram showing an example of the output screen of the risk countermeasure plan evaluation result display unit 1500 in the first embodiment. FIG. 28 shows an example of a screen that outputs the expected value of the assumed opportunity loss amount and the countermeasure cost for each countermeasure plan for each risk scenario by the supply chain risk evaluation device 1000.

[0094] Here, the expected value of the assumed opportunity loss amount is calculated by the supply chain demand and supply optimization calculation unit 1400 according to "occurrence probability of the risk scenario × assumed opportunity loss amount". Here, from the assumed opportunity loss amount information 2210 in FIG. 27, when flooding of 0.5 to 3.0 m occurs in Company A, the assumed opportunity loss amount when taking a countermeasure of increasing inventory is 800,000 M￥, and its occurrence probability is 0.00001. Therefore, the expected value of the assumed opportunity loss amount of increasing inventory in FIG. 28 is "800,000 M × 0.00001 = 8 M￥".

[0095] According to the above Example 1, for each risk scenario, the countermeasure cost, the expected value of the assumed opportunity loss amount, and the total value of the expected value of the assumed opportunity loss amount and the countermeasure cost can be confirmed. Therefore, for each countermeasure plan, the average values of the total values of the expected value of the assumed opportunity loss amount and the countermeasure cost can be confirmed in ascending order. Thus, it becomes possible to easily select a countermeasure plan with higher profitability. Note that as a modification of Example 1, it is also possible to confirm the average values of the total values of the expected value of the assumed opportunity loss amount and the countermeasure cost in descending order. This concludes the description of Example 1.

[0096] Note that the present invention is not limited to the above-described embodiments and Example 1, and includes various modifications. For example, the above-described embodiments and Example 1 have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Also, a part of the configurations of these embodiments and Example 1 can be replaced with other configurations, and it is also possible to add other configurations to the configurations of the above-described embodiments and Example 1. Further, for a part of the configurations of the embodiments and Example 1, it is possible to add, delete, or replace with other configurations.

[0097] Also, each of the above configurations, functions, processing units, processing means, etc. may be realized in hardware by designing a part or all of them, for example, by an integrated circuit. Further, each of the above configurations, functions, etc. may be realized in software by a processor interpreting and executing a supply chain risk assessment program that realizes each function. Information such as a supply chain risk assessment program, table, file, etc. that realizes each function can be stored in a memory, a recording device such as a hard disk, SSD (Solid State Drive), or a recording medium such as an IC card, SD card, DVD.

Description of Reference Numerals

[0098] 1000 Supply Chain Risk Assessment Device 1100 Information Collection and Management Unit 1200 Risk Scenario Generation Unit 1300 Incident Impact Scenario Generation Unit 1400 Supply Chain Demand-Supply Optimization Calculation Unit 1500 Risk Mitigation Plan Evaluation Result Display Unit 1600 Input / Output Interface Unit 2000 Data Storage Unit

Claims

1. In a supply chain risk assessment device for assessing a supply chain in transactions between organizations, an information collection management unit that collects recovery period information indicating a recovery period for an incident occurring in the supply chain, recovery pattern information indicating a recovery pattern for the incident, and supply capacity information indicating a supply capacity of a product targeted by the supply chain; an input / output interface unit that receives a countermeasure plan for the incident; an incident impact scenario generation unit that generates an impact scenario indicating the degree of impact from the occurrence to the recovery of the incident on the capacity of the supply chain caused by the incident, using the recovery period information, the recovery pattern information, and the supply capacity information; A supply chain risk assessment device having an evaluation value specifying unit that specifies an evaluation value of the countermeasure plan according to the period for executing the countermeasure plan.

2. The supply chain risk assessment device according to claim 1, wherein the evaluation value specifying unit is a supply chain supply-demand optimization calculation unit that calculates an opportunity loss amount due to the incident.

3. The supply chain risk assessment device according to claim 2, wherein the supply chain supply-demand optimization calculation unit calculates an expected value of the opportunity loss amount and a total value of countermeasure costs.

4. The supply chain risk assessment device according to claim 1, wherein the supply capacity information includes transport lead time information, production capacity information, and inventory performance information.

5. The supply chain risk assessment device according to claim 4, The incident impact scenario generation unit is a supply chain risk assessment device that generates, as the impact scenario, transportation lead time impact scenario information, inventory impact scenario information, and production capacity impact scenario information from the transportation lead time information, the production capacity information, and the inventory performance information.

6. In a supply chain risk assessment method for assessing a supply chain in transactions between organizations by a supply chain risk assessment device, an information collection management unit collects recovery period information indicating a recovery period for an incident occurring in the supply chain, recovery pattern information indicating a recovery pattern for the incident, and supply capacity information indicating a supply capacity of a product targeted by the supply chain, an input / output interface unit receives a countermeasure plan for the incident, an incident impact scenario generation unit generates an impact scenario indicating the degree of impact from the occurrence to the recovery of the incident on the capacity of the supply chain caused by the incident, using the recovery period information, the recovery pattern information, and the supply capacity information, an evaluation value specifying unit specifies an evaluation value of the countermeasure plan according to a period for executing the countermeasure plan. A supply chain risk assessment method.

7. In the supply chain risk assessment method according to claim 6, the evaluation value specifying unit functions as a supply chain supply-demand optimization calculation unit that calculates an opportunity loss amount caused by the incident. A supply chain risk assessment method.

8. In the supply chain risk assessment method according to claim 7, the supply chain supply-demand optimization calculation unit calculates an expected value of the opportunity loss amount and a total value of countermeasure costs. A supply chain risk assessment method.

9. In the supply chain risk assessment method according to claim 6, The supply capacity information is a supply chain risk assessment method including transportation lead time information, production capacity information, and inventory performance information.

10. In the supply chain risk assessment method according to claim 9, The incident impact scenario generation unit generates, as the impact scenario, transportation lead time impact scenario information, inventory impact scenario information, and production capacity impact scenario information from the transportation lead time information, the production capacity information, and the inventory performance information, in the supply chain risk assessment method.

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