Information processing device, information processing method, and program

Abstract

An information processing device is provided that can generate an effective action plan for solving organizational problems by improving the accuracy of evaluating the state of an organization. [Solution] The information processing device includes at least an analysis unit that evaluates the state of an organization by analyzing biometric data of multiple members belonging to the organization, and a generation unit that generates a first action plan to solve the organization's problems based on the evaluation results of the state of the organization. The biometric data includes biological data indicating biometric information extracted from biological samples of the members.

Description

[Technical Field]

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

[0002] The information processing device described in Patent Document 1 includes a first acquisition unit that acquires information indicating a user's motivation from responses to a survey for the user inputted into a terminal device, a second acquisition unit that acquires information indicating the user's health condition acquired by the terminal device in the survey, a calculation unit that calculates an index associated with an organization based on the information indicating the user's motivation and the information indicating the user's health condition, and an output unit that outputs the index. As a result, it is possible to visualize an index that takes user motivation into consideration.

[0003] The information indicating the condition includes vital data such as an autonomic nervous index calculated by pulse wave variability analysis or heart rate variability analysis, respiratory rate, oxygen saturation, blood pressure, weight, and body composition. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2024-135377 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the information processing device described in Patent Document 1, information such as vital data may have low resolution as an index for evaluating an individual's condition, which may result in a decrease in the accuracy of the evaluation of the individual's condition.

[0006] For example, vital signs data has limitations in identifying the root causes of problems an individual is experiencing. In other words, vital signs data cannot identify detailed biochemical factors such as nutritional deficiencies or the accumulation of toxins in the body. These biochemical factors can be the root causes of various ailments such as a lack of concentration or energy.

[0007] Because an organization is a collection of individuals, low resolution indicators for assessing the status of an individual will reduce the accuracy of the assessment of the status of the organization to which the individual belongs. For example, if the detailed biochemical factors described above cannot be identified, it will be impossible to identify the root cause of an individual's problem, which may cause organizational problems, and ultimately the root cause of organizational problems. This can make it difficult to generate an effective action plan to resolve organizational problems.

[0008] Therefore, the present disclosure has been made in consideration of the above-mentioned problems, and its purpose is to provide an information processing device, an information processing method, and a program that can generate an effective action plan for solving organizational issues by improving the accuracy in evaluating the state of an organization. [Means for solving the problem]

[0009] According to the present disclosure, an information processing device can be provided that includes at least an analysis unit that evaluates the state of an organization by analyzing biometric data of multiple members belonging to the organization, and a generation unit that generates a first action plan to solve the organization's problems based on the evaluation results of the organization's state, wherein the biometric data includes biological data indicating biometric information extracted from biological samples of the members.

[0010] According to the present disclosure, an information processing method can be provided, which includes a step in which a computer evaluates the state of an organization by analyzing at least biometric data of multiple members belonging to the organization, and a step in which the computer generates a first action plan for solving the organization's problems based on the evaluation results of the organization's state, wherein the biometric data includes biological data indicating biometric information extracted from biological samples of the members.

[0011] According to the present disclosure, a program can be provided that causes a computer to perform at least the steps of evaluating the state of an organization by analyzing biometric data of multiple members belonging to the organization, and generating a first action plan for solving the organization's problems based on the results of the evaluation of the organization's state, wherein the biometric data includes biological data indicating biometric information extracted from biological samples of the members. [Effects of the Invention]

[0012] The present disclosure provides improved accuracy in assessing the state of an organization, thereby enabling the generation of effective action plans to resolve organizational challenges. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a diagram illustrating an example of the configuration of a support system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of an information processing device according to the embodiment. [Figure 3] 1A is a schematic diagram showing biological-related data according to the embodiment, and FIG. 1B is a schematic diagram showing mind-related data according to the embodiment. [Figure 4] FIG. 10 is a diagram illustrating an example of an operation of the information processing device according to the embodiment. [Figure 5] FIG. 10 is a diagram showing an example of an organizational action plan according to the embodiment. [Figure 6] FIG. 10 is a diagram illustrating an example of an organizational root cause map according to the embodiment. [Figure 7] FIG. 10 is a diagram showing an example of an organization evaluation report according to the embodiment. [Figure 8] FIG. 10 is a diagram showing an example of a group of action plan candidates for generating an organizational action plan according to the embodiment. [Figure 9] FIG. 10 is a diagram showing an example of an individual action plan according to the embodiment. [Figure 10] FIG. 10 is a diagram showing an example of an individual root cause map according to the embodiment. [Figure 11] FIG. 10 is a diagram showing an example of a personal evaluation report according to the embodiment. [Figure 12] FIG. 10 is a diagram showing an example of a group of action plan candidates for generating an individual action plan according to the embodiment. [Figure 13] 10 is a schematic diagram showing an example of self-evaluation data of bio-related data according to the embodiment; FIG. [Figure 14] FIG. 2 is a schematic diagram showing an example of biological data of living body-related data according to the embodiment. [Figure 15] FIG. 10 is a schematic diagram showing an example of analysis logic information for biological data according to the embodiment. [Figure 16] 10 is a schematic diagram showing an example of analysis logic information for self-assessment data and biological data according to the embodiment. FIG. [Figure 17] FIG. 10 is a schematic diagram showing an example of thinking tendency data of mind-related data according to the embodiment. [Figure 18] FIG. 10 is a diagram showing an example of an analysis logic table for thinking tendency data according to the embodiment. [Figure 19] FIG. 10 is a schematic diagram showing an example of behavioral tendency data of mind data according to the embodiment. [Figure 20] 1A is a schematic diagram showing an example of analysis logic information according to the embodiment, and FIG. 1B is a schematic diagram showing an example of an analysis logic table according to the embodiment. [Figure 21] FIG. 10 is a schematic diagram showing an example of interview data according to the embodiment. [Figure 22]10 is a flowchart illustrating an example of an information processing method for an organization according to the embodiment. [Figure 23] 10 is a flowchart illustrating an example of an information processing method for members according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0015] 1 is a diagram showing an example of the configuration of a support system SYS according to an embodiment of the present invention. The support system SYS (information processing system 1) evaluates the members and state of an organization, and generates an action plan for solving the problems of the members and the organization.

[0016] An organization is not particularly limited, but may be, for example, a company, an organization, an institution (e.g., a medical institution, a research institute), or a business entity. An organization may be, for example, a for-profit organization or a non-profit organization. An organization may also be a group, as long as it has multiple members. A group may be, for example, a department formed within a company, or a team such as a sports team. An organization's challenges may be, for example, one or more of the following: a worsening turnover rate, an increase in employees on leave, a shortage of leadership talent, a passive organizational culture, and sluggish sales (Figure 6).

[0017] As shown in FIG. 1, the support system SYS includes an information processing system 1, one or more organization terminals T1, one or more member terminals T2, a doctor terminal T3, a health coach terminal T4, and a mind coach terminal T5. The information processing system 1 includes an information processing device 100, a biological-related database device 200, and a mind-related database device 300. The organization terminal T1, the member terminal T2, the doctor terminal T3, the health coach terminal T4, the mind coach terminal T5, the information processing device 100, the biological-related database device 200, and the mind-related database device 300 are connected to a network NW. The network NW includes, for example, one or more of the Internet, a LAN (Local Area Network), a public telephone network, a closed network, and a short-range wireless network.

[0018] The organization terminal T1 is a terminal assigned to a member in charge of running or managing the organization. The member in charge of running or managing the organization is, for example, a member of the management, upper management, or human resources department of the organization. The member terminal T2 is a terminal assigned individually to a member of the organization and used by the member.

[0019] The doctor terminal T3 is a terminal used by a doctor. The doctor terminal T3 is installed in, for example, a medical institution such as a hospital or a clinic. The health coach terminal T4 is a terminal used by a health coach. The health coach supports the physical health of the member via the health coach terminal T4 in accordance with the personal action plan generated by the information processing device 100. The health coach is, for example, an expert in nutrition and exercise instruction. The health coach supports, for example, the improvement of dietary and lifestyle habits. The mind coach terminal T5 is a terminal used by a mind coach. The mind coach supports the member responsible for operating or managing the organization from a psychological perspective in accordance with, for example, the organizational action plan generated by the information processing device 100. The mind coach is, for example, an expert in cognitive psychology and / or behavioral psychology. Note that the mind coach may support each individual member in accordance with the personal action plan.

[0020] Cognitive psychology is a science that scientifically elucidates mental processes (e.g., thought patterns) such as perception, memory, judgment, and decision-making based on human cognitive functions.

[0021] Behavioral psychology is a science that analyzes observable behavior based on human psychological or mental factors, and scientifically elucidates the mechanisms by which behavior occurs and the mechanisms by which behavior can be changed (e.g., behavioral tendencies).

[0022] The organization terminal T1, member terminal T2, doctor terminal T3, health coach terminal T4, and mind coach terminal T5 are personal computers such as desktop computers and laptop computers, or mobile terminals such as tablets and smartphones.

[0023] Hereinafter, transmitting information or data to the organization terminal T1, member terminal T2, doctor terminal T3, health coach terminal T4, or mind coach terminal T5 includes, for example, placing the information or data on the cloud (on a server) so that it can be accessed by the organization terminal T1, member terminal T2, doctor terminal T3, health coach terminal T4, or mind coach terminal T5. Also, transmitting information or data to the information processing device 100 includes, for example, placing the information or data on the cloud (on a server) so that it can be accessed by the information processing device 100.

[0024] The biological-related database device 200 stores biological-related data. The biological-related data includes biological data of each member. The mind-related database device 300 stores mind-related data. The mind-related data includes mind data of each member. The biological-related database device 200 and the mind-related database device 300 are, for example, database servers.

[0025] The information processing device 100 analyzes at least the biological data of multiple members belonging to an organization, and generates an action plan (hereinafter, "organizational action plan") to solve organizational problems based on the analysis results. In this way, the accuracy of evaluating the status of members is improved using the biological data. As a result, the accuracy of evaluating the status of an organization, which is a collection of multiple members, is also improved. Therefore, an effective organizational action plan can be generated. The information processing device 100 is, for example, a server. The organizational action plan corresponds to an example of a "first action plan" in the present disclosure.

[0026] Preferably, the information processing device 100 performs an integrated analysis of the biological data and mind data of multiple members belonging to an organization and generates an organizational action plan based on the analysis results. Therefore, the integrated analysis from both biochemical and psychological / mental perspectives improves the accuracy of the status assessment of each member, and ultimately improves the accuracy of the status assessment of the organization to which each member belongs. Therefore, a more effective organizational action plan can be generated.

[0027] Next, the information processing device 100 will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example configuration of the information processing device 100. As shown in Fig. 2, the information processing device 100 includes a processing unit 110, a communication unit 150, and a storage unit 160. The information processing device 100 may also include an input unit 130 and an output unit 140.

[0028] The processing unit 110 executes various processes (various calculations). The processing unit 110 controls the input unit 130, the output unit 140, the communication unit 150, and the storage unit 160. The processing unit 110 includes one or more processors. The processor is a central processing unit (CPU), a graphics processing unit (GPU), a field programmable gate array (FPGA), a digital signal processor (DSP), or an application specific integrated circuit (ASIC). The processor may operate by a program or by hardwired logic.

[0029] The input unit 130 is an input device for inputting various pieces of information to the processing unit 110. For example, the input unit 130 is a keyboard and pointing device, or a touch panel.

[0030] The output unit 140 outputs various types of information. The output unit 140 includes, for example, a display unit that displays various types of information and an audio output unit that outputs audio. The display unit is, for example, a liquid crystal display, an organic electroluminescence display, or a head-mounted display. The audio output unit is, for example, a speaker.

[0031] The communication unit 150 is connected to the network NW. The communication unit 150 communicates with the organization terminal T1, the member terminal T2, the doctor terminal T3, the health coach terminal T4, the mind coach terminal T5, the biological-related database device 200, and the mind-related database device 300 via the network NW. The communication unit 150 is a communication device that communicates according to a predetermined communication protocol, and includes, for example, a network interface controller. The predetermined communication protocol is, for example, a protocol compliant with Ethernet (registered trademark), the Internet Protocol Suite, or a protocol compliant with a short-range wireless communication standard.

[0032] The storage unit 160 includes one or more storage devices and stores data and programs. The storage unit 160 includes a main storage device such as a semiconductor memory, and an auxiliary storage device such as a semiconductor memory and a storage drive. The storage drive is, for example, a hard disk drive or a solid-state drive. The storage unit 160 is, for example, a non-transitory computer-readable storage medium.

[0033] The processing unit 110 includes an acquisition unit 111, an analysis unit 112, a generation unit 113, and an output control unit 114. Specifically, the processor of the processing unit 110 executes a program stored in the storage device of the storage unit 160, thereby functioning as the acquisition unit 111, the analysis unit 112, the generation unit 113, and the output control unit 114.

[0034] The organization terminal T1, member terminal T2, doctor terminal T3, health coach terminal T4, and mind coach terminal T5 each include a processing unit, a communication unit, a memory unit, an input unit, and an output unit. The hardware configurations of the processing unit, communication unit, memory unit, input unit, and output unit of the organization terminal T1, member terminal T2, doctor terminal T3, health coach terminal T4, and mind coach terminal T5 are similar to the hardware configurations of the processing unit 110, communication unit 150, memory unit 160, input unit 130, and output unit 140, respectively.

[0035] Next, the bio-related data D1 and the mind-related data D2 will be described with reference to Fig. 3. Fig. 3(a) is a schematic diagram showing the bio-related data D1. Fig. 3(b) is a schematic diagram showing the mind-related data D2.

[0036] 3(a), the living body-related database device 200 stores living body-related data D1 for each member. The living body-related data D1 includes biological function data D12 of the member.

[0037] The biological function data D12 includes biological data D121. The biological data D121 includes biological information extracted from a biological sample of the member. The biological sample is, for example, one or more of a body fluid, a microbiome, DNA, and hair. The body fluid is, for example, one or more of blood, interstitial fluid, saliva, and urine.

[0038] The biological data D121 includes, for example, one or more of blood test information related to nutrients, blood glucose levels, salivary cortisol test information, microbiome test information, urinary organic acid test information, DNA test information, hair test information, and blood test information related to physiological functions. Preferably, the biological data D121 includes blood test information related to nutrients, blood glucose levels, and salivary cortisol test information. This is because these three pieces of information particularly represent a biological state for identifying the root cause of a disorder symptom of a living organism.

[0039] Blood test information related to nutrients is, for example, information on blood components that directly or indirectly indicate nutrients such as magnesium, zinc, and iron. The blood glucose level may be the blood glucose level itself or may be indicated by a glucose value. Information such as blood glucose spikes and hypoglycemia can be obtained from the blood glucose level. The blood glucose level may be measured, for example, by a sensing device and transmitted to the biological-related database apparatus 200, or may be transmitted to the biological-related database apparatus 200 via a member's mobile terminal or the like. The sensing device is, for example, a CGM (Continuous Glucose Monitoring) sensor worn on the human body.

[0040] Salivary cortisol test information can be used to estimate, for example, the presence or absence and degree of functional dysfunction of the HPA axis (hypothalamus-pituitary-adrenal axis). This can in turn be used to estimate, for example, the degree of adrenal fatigue. Microbiome test information can be used to estimate, for example, the state of the intestinal environment. Examples of the state of the intestinal environment include a decrease in benign bacteria, indigestion, intestinal inflammation, overgrowth of malignant bacteria, and overgrowth of Candida. An example of a microbiome test is a GI-MAP test. Urinary organic acid test information can be used to estimate, for example, damage to the body, the state of neurotransmitters, and the TCA cycle. Damage to the body can be, for example, inflammation, oxidative stress, insulin resistance, hypoglycemia, and increased protein catabolism. Neurotransmitters include, for example, serotonin and dopamine. The TCA cycle can be used to evaluate, for example, mitochondrial function. DNA test information can be used to estimate, for example, the state of brain function. Hair test information can be used to detect, for example, the state of toxin accumulation. Examples of blood test information related to physiological functions include, but are not limited to, CRP, ferritin, and neutral fat.

[0041] The biological data D121 includes a score indicating a primary evaluation of each of the multiple pieces of biological information. The primary evaluation indicates that the biological information alone is evaluated according to a predetermined standard (threshold or range). In this case, the biological information can be considered as an evaluation item.

[0042] The biological function data preferably includes vital data D122. The vital data D122 is information indicating the vital signs of the member (vital sign information). The vital data D122 includes, for example, sleep information of the member. The sleep information indicates information related to the member's sleep. The sleep information is, for example, information indicating a sleep score obtained by a sensing device, a melatonin cycle, or a caffeine level. Note that the vital data D122 is not limited to sleep information and may include, for example, blood pressure and heart rate information (e.g., heart rate and heart rate variability index).

[0043] The vital data D122 may be measured by a sensing device such as a wearable device and transmitted to the biological-related database device 200, or may be transmitted to the biological-related database device 200 via a member's mobile terminal or the like.

[0044] The vital sign data D122 includes a score indicating a primary evaluation of each of the multiple vital sign information. The primary evaluation indicates that the vital sign information is evaluated individually according to a predetermined standard (threshold or range). In this case, the vital sign information can be considered as an evaluation item.

[0045] The biological data D121 and the vital data D122 may be transmitted to the living body-related database device 200 directly or via the information processing device 100 from the doctor terminal T3 or the member terminal T2, for example.

[0046] The biological-related data D1 preferably includes self-assessment data D11 of the member. The self-assessment data D11 includes scores for each of a plurality of evaluation items for identifying the biochemical causes of symptoms that appear in humans. The scores are based on input from the member. Biochemistry is the science that elucidates life and physiological phenomena from a chemical perspective.

[0047] The biological function data D12 may include information on the number of steps and / or the amount of physical activity (for example, METs). The information on the number of steps and the amount of physical activity is measured by a sensing device such as a wearable device.

[0048] 3(b), the mind-related database device 300 stores mind-related data D2 for each member. The mind-related data D2 includes mind data D21.

[0049] The mind data D21 is information based on the members' responses to the questionnaire. In other words, the mind data is data based on the members' self-evaluations. Specifically, the mind data D21 includes at least one of the members' thinking tendency data D211 and the members' behavioral tendency data D212. Preferably, the mind data D21 includes the members' thinking tendency data D211. More preferably, the mind data D21 includes both the members' thinking tendency data D211 and the members' behavioral tendency data D212. The thinking tendency data D211 includes information indicating the members' thinking tendency based on their cognitive functions. The thinking tendency may also be called a thinking characteristic. The behavioral tendency data D212 includes information indicating the members' behavioral tendency based on their psychological or mental factors. The behavioral tendency may also be called a behavioral characteristic. The mind data D21 preferably includes the thinking tendency data D211, and more preferably includes the thinking tendency data D211 and the behavioral tendency data D212.

[0050] The mind-related data D2 preferably includes interview data D22. The interview data D22 includes information indicating the results of an interview between the member and a mind coach. For example, the interview data D22 is dialogue log data or interpersonal observation data from the interview. The interview data D22 includes scores for each of a plurality of evaluation items for evaluating the member's thinking tendencies and / or behavioral tendencies. The scores are based on input from the mind coach. The mind coach is an expert in evaluating human thinking tendencies and / or behavioral tendencies.

[0051] Next, the operation of the information processing device 100 will be described with reference to Fig. 4. Fig. 4 is a diagram for explaining an example of the operation of the information processing device 100. As shown in Fig. 4, the acquisition unit 111 acquires at least biologically related data D1 from the biologically related database device 200 (Fig. 1). The storage unit 160 (Fig. 2) stores the biologically related data D1. The biologically related data D1 includes at least biological function data D12. The biological function data D12 includes at least biological data D121.

[0052] The analysis unit 112 evaluates the state of the organization by analyzing at least the biological data D121 of multiple members belonging to the organization. Specifically, the analysis unit 112 evaluates the state of each member by analyzing at least the biological data D121 of the members. Then, the analysis unit 112 evaluates the state of the organization based on the evaluation results of the states of the multiple members. For example, the analysis unit 112 evaluates the state of the organization by aggregating and analyzing the evaluation results of the states of the multiple members. The aggregating and analyzing may include, for example, statistical processing.

[0053] The generation unit 113 generates an organizational action plan for solving the organizational issues based on the evaluation result of the organizational state. The output control unit 114 generates image information representing the organizational action plan and displays it on the organization terminal T1 (FIG. 1).

[0054] As described above, in this embodiment, high-resolution biological data D121 is used as an index for evaluating the status of members. This allows for improved accuracy in evaluating the status of members. Furthermore, since an organization is a collection of members, a high accuracy in evaluating the status of a member improves the accuracy in evaluating the status of the organization to which the member belongs. As a result, by using the highly accurate evaluation results, an effective organizational action plan can be generated to solve organizational issues.

[0055] Specifically, an organization is a social and physiological system composed of multiple members who interact with one another under a common purpose or goal. The function of an organization fluctuates depending on the status and interrelationships of each member. Therefore, to accurately evaluate the status of an organization, it is desirable to grasp the physiological status of each member. However, conventional indicators for evaluating an individual's status, such as those described in Patent Document 1, have low information resolution. Low information resolution indicators for evaluating an individual's status also reduce the accuracy of estimating the status of the organization to which the individual belongs. For example, if biochemical factors (nutritional deficiency, oxidative stress, hormonal imbalance, etc.) cannot be identified, the individual-level root causes of poor performance and inefficient decision-making in the organization cannot be identified. As a result, the root causes of organizational issues cannot be accurately identified, making it difficult to generate effective organizational action plans and intervention strategies. In contrast, this embodiment uses high-resolution biological data D121 as an indicator for evaluating the status of members, thereby improving the accuracy of evaluation of the status of members and, ultimately, the status of the organization. As a result, it becomes possible to generate effective organizational action plans and intervention strategies.

[0056] For example, by using the biological data D121, it is possible to identify the root causes of problems experienced by members. In other words, the biological data D121 can identify detailed biochemical factors, such as nutrient deficiencies and the accumulation of harmful metabolic products and toxic substances in the body. These biochemical factors affect members' neuroendocrine and energy metabolic systems, and can be the underlying factors that induce functional disorders such as poor concentration and lack of energy. Furthermore, by identifying the biochemical factors that cause members' symptoms of illness (e.g., functional disorders) that may cause problems in the organization, the root causes of the organizational problems can also be identified. As a result, an effective organizational action plan can be generated that includes solutions that address the root causes of the organizational problems.

[0057] In particular, the data includes one or more of biological data D121, blood test information related to nutrients, blood glucose levels, salivary cortisol test information, microbiome test information, urinary organic acid test information, DNA test information, hair test information, and blood test information related to physiological functions. These factors affect members' neuroendocrine systems, metabolic systems, and cognitive functions, and can be fundamental factors that cause breakdowns in energy homeostasis and attention control. Therefore, by including and analyzing this information in the vital data D122, it is possible to generate effective organizational action plans that include solutions that address the root causes of members' symptoms (e.g., breakdowns in energy homeostasis and attention control), and ultimately, the root causes of organizational challenges.

[0058] Furthermore, the biochemical state of the member can be evaluated from multiple angles using biological data D121 acquired from different types of bodily fluids (blood, interstitial fluid, saliva, and urine). Furthermore, the biochemical state of the member can be evaluated from even more multiple angles using biological data D121 acquired not only from bodily fluids but also from other biological samples (microbiome, DNA, and hair). In this way, the biochemical state of the member can be analyzed and evaluated in detail. Therefore, the root cause of the member's ill symptoms can be accurately identified, and ultimately, the root cause of organizational issues can be accurately identified. Therefore, more effective organizational action plans including solutions to organizational issues can be generated.

[0059] In the above, the analysis unit 112 may evaluate the state of the organization by analyzing the vital data D122 and / or the self-assessment data D11 in addition to the biological data D121 of the multiple members.

[0060] Preferably, in this embodiment, the acquisition unit 111 acquires the mind-related data D2 from the mind-related database device 300 (FIG. 1). The storage unit 160 (FIG. 2) stores the mind-related data D2. The mind-related data D2 includes at least mind data D21.

[0061] The analysis unit 112 evaluates the state of the organization by analyzing the biological data D121 and mind data D21 of multiple members. Specifically, the analysis unit 112 evaluates the state of each member by analyzing the biological data D121 and mind data D21 of the members. Then, the analysis unit 112 evaluates the state of the organization based on the evaluation results of the states of the multiple members. For example, the analysis unit 112 evaluates the state of the organization by aggregating and analyzing the evaluation results of the states of the multiple members. The aggregating and analysis may include, for example, statistical processing.

[0062] As described above, this embodiment analyzes both the biological data D121, which is biochemical data, and the mind data D21, which is based on psychological factors. Therefore, the mind data D21 complements psychological factors that cannot be fully captured by the biological data D121 alone, while the biological data D121 complements medical validity that cannot be obtained by the mind data D21 alone. This synergistic effect further improves the accuracy of the assessment of the organizational state, ultimately enabling the generation of a more effective organizational action plan.

[0063] For example, as described above, the function of an organization fluctuates depending on the state and interrelationships of individual members. Therefore, in order to evaluate the state of an organization with higher accuracy, it is more preferable to understand the physiological, psychological, and cognitive states of members from multiple perspectives. However, conventional indices for evaluating an individual's state, such as those described in Patent Document 1, are unable to reflect cognitive and psychological aspects and have limited information resolution for grasping the overall picture of an individual's state. In contrast, in this embodiment, by analyzing not only the biological data D121 but also the mind data D21, the accuracy of the member state evaluation can be further improved with higher information resolution. As a result, the accuracy of the evaluation of the organizational state is further improved, enabling the generation of more effective organizational action plans and intervention strategies.

[0064] Specifically, in this embodiment, the analysis unit 112 evaluates the state of the organization by comprehensively analyzing the biological data D121 and the mind data D21 for a plurality of members.

[0065] As a first example, the analysis unit 112 evaluates the condition of each member by comprehensively analyzing the biological data D121 and mind data D21 of the member. Then, the analysis unit 112 evaluates the condition of the organization based on the evaluation results of the conditions of the multiple members. Or, as a second example, the analysis unit 112 evaluates the condition of each member by analyzing the biological data D121 of the member, and evaluates the condition of each member by analyzing the mind data D21. Then, the analysis unit 112 evaluates the condition of the organization by comprehensively analyzing the overall evaluation results of the multiple members based on the biological data D121 and the overall evaluation results of the multiple members based on the mind data D21. In the second example as well, the biological data D121 and the mind data D21 are comprehensively analyzed indirectly.

[0066] In this way, in this embodiment, by performing an integrated analysis, it is possible to perform a high-level evaluation of the state of the organization, including the interaction and causal relationship between the biological data D121 and the mind data D21, and therefore it is possible to generate a more effective organizational action plan.

[0067] Preferably, the mind data D21 includes scores for each of a plurality of evaluation items for identifying the thinking tendency based on the cognitive function of the member. In this case, the scores are based on the input of the member. The scores enable the member's thinking tendency to be quantitatively grasped, and more objective and systematic analysis and evaluation of the thinking tendency can be performed.

[0068] Preferably, the mind data D21 includes scores for each of a plurality of evaluation items for identifying behavioral tendencies based on psychological or mental factors of the member. In this case, the scores are based on input by the member. The scores enable a quantitative understanding of the member's behavioral tendencies, enabling more objective and systematic analysis and evaluation of the behavioral tendencies.

[0069] Preferably, in this embodiment, the biological data D1 includes vital data D122 in addition to biological data D121. The analysis unit 112 evaluates the state of the organization by comprehensively analyzing the biological data D1 and mind data D21 for multiple members. In this case, the biological data D121 can identify detailed biochemical factors, while the vital data D122 can capture daily fluctuations and rhythms of biological functions and instantaneous physical reactions. This improves the accuracy of the evaluation of the state of the organization, and ultimately enables the generation of a more effective organizational action plan.

[0070] In particular, it is preferable that the vital data D122 include sleep information. Sleep abnormalities, such as lack of sleep, poor sleep quality, and short sleep duration, can be the root causes of employee ill-health. Therefore, by including sleep information in the vital data D122 and analyzing it, it is possible to generate an effective organizational action plan that includes solutions that address the root causes of employee ill-health, and ultimately the root causes of organizational issues.

[0071] Preferably, in this embodiment, the bio-related data D1 includes self-assessment data D11 in addition to the biological data D121, or includes self-assessment data D11 in addition to the biological data D121 and vital data D122. The analysis unit 112 then evaluates the state of the organization by comprehensively analyzing the bio-related data D1 and the mind data D21 for multiple members.

[0072] The self-assessment data D11 includes scores for each of a plurality of assessment items for identifying the biochemical causes of symptoms observed in humans. The biological data D121 includes biological information related to the assessment items in the self-assessment data D11. This enables comparative analysis of the self-assessment data D11, which is subjective data, and the biological data D121, which is objective data. As a result, the accuracy of the assessment of each member's condition is further improved, and ultimately the accuracy of the assessment of the organization's condition is further improved.

[0073] Preferably, in this embodiment, the mind-related data D2 includes interview data D22 in addition to mind data D21. The analysis unit 112 evaluates the state of the organization by comprehensively analyzing the biometric data D1 and the mind-related data D2 for multiple members. In this case, the biometric data D1 includes biological data, or includes self-assessment data D11 in addition to biological data D121, or includes vital data D122 and self-assessment data D11 in addition to biological data D121.

[0074] The interview data D22 indicates the results of an interview between a mind coach and a member. A mind coach is an expert in evaluating human thinking and / or behavioral tendencies. Specifically, the interview data D22 is information regarding the member's thinking and / or behavioral tendencies obtained during an interview between the mind coach and the member. More specifically, the interview data D22 includes scores for each of a plurality of evaluation items for evaluating the member's thinking and / or behavioral tendencies. In this way, by including the interview data D22 in the analysis in addition to the mind data D21 based on the member's self-evaluation, a more accurate and in-depth identification of the member's thinking and / or behavioral tendencies is possible.

[0075] For example, a mind coach can extract a member's true feelings and thought processes elicited in face-to-face dialogue, thereby identifying the member's thinking tendencies and / or behavioral tendencies that cannot be captured by analyzing mind data D21 based on self-evaluation alone, and record the identified tendencies as interview data D22. Also, for example, a mind coach can ask the member questions in an interview based on the contents of a pre-questionnaire for the member regarding their thinking tendencies and / or behavioral tendencies, score the responses, and record the results as interview data D22. Therefore, based on the score of the pre-questionnaire and the interview data D22, for example, the "difference between the pre-questionnaire and the interview content" can be grasped, and "bias to look good" can be extracted.

[0076] As described above with reference to FIG. 4, the analysis unit 112 evaluates the state of an organization by comprehensively analyzing the biometric data D1 and mind-related data D2 of multiple members. Then, the generation unit 113 generates an organizational action plan for solving organizational issues based on the evaluation results of the state of the organization. The output control unit 114 generates image information representing the organizational action plan and displays it on the organization terminal T1 (FIG. 1). The organizational action plan may be provided as, for example, a roadmap.

[0077] FIG. 5 is a diagram showing an example of the organizational action plan PL1. In the diagram, "Q" represents an integer equal to or greater than 2. As shown in FIG. 5, the organizational action plan PL1 includes action plan information 700 for each implementation date. The action plan information 700 includes organizational challenges and content. The content represents coaching content (coaching information) for resolving the challenges. The coaching content is determined, for example, from the perspective of cognitive psychology and / or behavioral psychology. As an example, a mind coach provides coaching to members responsible for managing or operating the organization in accordance with each piece of action plan information 700 in the organizational action plan PL1. Note that, in the example of FIG. 5, the action plan information 700 represents content to be implemented in one day, but it may also represent content to be implemented over two or more days.

[0078] For example, the organizational action plan PL1 may include, depending on the results of the assessment of the organizational state, one or more of the following: coaching information (content) for resolving issues related to turnover, coaching information (content) for resolving issues related to employees on leave, coaching information (content) for resolving issues related to human resources, coaching information (content) for resolving issues related to organizational culture, and coaching information (content) for resolving issues related to sales. Therefore, the organization can be provided with action plans for addressing typical and important issues faced by companies, such as a worsening turnover rate, an increase in employees on leave, a shortage of leadership talent, a passive organizational culture, and / or sluggish sales. In particular, the coaching information for resolving issues related to turnover, employees on leave, human resources, organizational culture, and sales preferably includes coaching information for resolving the root causes of the worsening turnover rate, the increase in employees on leave, a shortage of leadership talent, a passive organizational culture, and sluggish sales, respectively.

[0079] Preferably, the generation unit 113 generates information indicating the basis for the organizational action plan PL1 based on the integrated analysis results of the biological-related data D1 and the mind-related data D2. The basis for the organizational action plan PL1 includes, for example, the reason for implementing the organizational action plan PL1 and / or the state of change in the organization after implementation. The output control unit 114 then displays information indicating the basis for the organizational action plan PL1 on the organization terminal T1. In this way, an explainable approach can improve the persuasiveness and effectiveness of the organizational action plan PL1. By clearly explaining the reasons why the organizational action plan PL1 is effective, it is possible to increase the sense of acceptance among the organization and its members and promote motivation for behavioral change.

[0080] For example, the content of the action plan information 700 may include the basis for the coaching indicated by the action plan information 700 as the basis for the organizational action plan PL1.

[0081] Specifically, as an example, the storage unit 160 stores basis generation information (e.g., a basis generation table) for generating information indicating the basis for an organizational action plan. The basis generation information is information in which multiple pieces of organizational state information are associated with multiple pieces of basis candidate information. For example, one piece of organizational state information is associated with one piece of basis candidate information. The organizational state information indicates evaluation information of the state of the organization. The basis candidate information indicates candidate basis for the organizational action plan. The generation unit 113 acquires, from the basis generation information, basis candidate information associated with the organizational state information corresponding to the evaluation of the state of the organization based on the integrated analysis results of the biological-related data D1 and the mind-related data D2. Then, the generation unit 113 adopts the acquired basis candidate information as the basis for the organizational action plan. In this way, the generation unit 113 generates information indicating the basis for the organizational action plan.

[0082] Preferably, in this embodiment, the analysis unit 112 identifies (estimates) the cause of the organizational issue by analyzing at least the mind-related data D2. The mind-related data D2 includes mind data D21, or includes mind data D21 and interview data D22. The analysis unit 112 then estimates an error event that may occur in the organization based on the identification (estimation) of the cause (e.g., root cause) of the organizational issue. It can be directly estimated that the organizational issue is caused by the error event. The error event indicates a specific problematic behavior or phenomenon that derives from the cause of the organizational issue. The output control unit 114 then generates image information (hereinafter referred to as an "organizational root cause map MP1") that shows the identification result of the cause and the estimation result of the error event, as well as the organizational issue, and displays the image information on the organizational terminal T1.

[0083] Fig. 6 is a diagram showing an example of the organizational root cause map MP1. As shown in Fig. 6, the organizational root cause map MP1 is information that visualizes a structured chain of events from the root cause 401 of an organizational issue 403 to the occurrence of the issue 403. Specifically, the organizational root cause map MP1 includes information on the root cause 401, the error event 402, and the organizational issue 403. In Fig. 6, black rectangles indicate items that apply to the organization being evaluated.

[0084] In this way, by visualizing the causes (e.g., root causes) of organizational issues and the estimated results of error events and providing them to the organization, the administrator or manager of the organization can clearly understand the structured chain leading from the root causes to the occurrence of the issues. More preferably, the analysis unit 112 estimates the causes (e.g., root causes) of organizational issues by comprehensively analyzing the mind-related data D2 and the biological-related data D1. In this case, the causes of organizational issues can be estimated more accurately.

[0085] Specifically, as an example, the storage unit 160 stores cause-error correspondence information (e.g., a cause-error correspondence table) that indicates the correspondence between causes of organizational issues and error events. The cause-error correspondence information is information in which multiple error event candidates are associated with multiple pieces of cause information. For example, one or more error event candidates are associated with one piece of cause information. The cause information indicates the fundamental cause of an organizational issue. The error event candidates are candidates for error events that can be derived from the cause information. The generation unit 113 refers to the cause-error correspondence information and acquires, from the cause-error correspondence information, error event candidates associated with cause information corresponding to the identified cause (estimated cause). Then, the generation unit 113 adopts the acquired error event candidates as the error event. In this way, the generation unit 113 infers the error event. Note that an example of identifying (estimating) the cause (root cause) of an organizational issue will be described later.

[0086] Preferably, the generation unit 113 generates an organization evaluation report based on the integrated analysis results of the bio-related data D1 and mind-related data D2 of multiple members. The organization evaluation report is a report that shows the evaluation results of the state of the organization. Note that the organization evaluation report may include the evaluation results of the state of the organization based on the analysis results of the bio-related data D1 and / or the evaluation results of the state of the organization based on the analysis results of the mind-related data D2.

[0087] 7 is a diagram showing an example of an organization evaluation report 500. As shown in Fig. 7, the organization evaluation report 500 includes, for example, an organization health score 501, number of employees information 502, improvement rate information 503, and investment effect information 504.

[0088] The organizational health score 501 is a composite score obtained by aggregating the scores of the biological-related data D1 and the mind-related data D2 for each member and then aggregating the aggregation results for multiple members of the organization. Therefore, the organizational health score 501 is an index that represents the state of the organization, reflecting the physical health conditions and psychological performance of multiple members. Psychological performance indicates the degree of the member's condition from a psychological or mental perspective.

[0089] The number of employees information 502 indicates the number of employees participating in the support for the organization provided by the information processing device 100 (hereinafter, "the support"). The improvement rate information 503 is a value expressed as a percentage of the increase in the organizational health score at the time of evaluation relative to the organizational health score at the start of the support. The investment effect information 504 includes a value indicating the economic return on the investment amount for the support in monetary terms and a return on investment (ROI) indicating the economic return on the investment amount for the support. For example, if the support reduces employee turnover, the economic return is the amount equivalent to the expenditure of recruitment costs, since the expenditure of recruitment costs that would have been incurred due to employee turnover is eliminated. Furthermore, if the support improves productivity, the economic return is the increase in sales due to the productivity improvement.

[0090] For example, the organizational assessment report 500 also includes a health distribution chart 505 and departmental health scores 506 .

[0091] Health distribution chart 505 shows the distribution of individual health scores of members of an organization. The individual health score is a composite score obtained by aggregating the scores of the member's biological-related data D1 and mind-related data D2. Therefore, the individual health score is an index that represents the individual member's condition, reflecting their physical health and psychological performance.

[0092] The departmental health score 506 is a score obtained by aggregating the individual health scores for each department. Therefore, the departmental health score 506 is an index that represents the state of the department, reflecting the physical health conditions and psychological performance of the members belonging to the department.

[0093] Note that the above is an example, and the contents of the organization evaluation report 500 are not particularly limited.

[0094] Returning to FIG. 4, a detailed example of the integrated analysis and generation of an organizational action plan will be described. The analysis unit 112 calculates an integrated score for each member based on the scores of the evaluation items in the biometric-related data D1 and the scores of the evaluation items in the mind-related data D2 for each member. The analysis unit 112 then aggregates the integrated scores for multiple members and evaluates the state of the organization based on the aggregation result. In this case, the analysis unit 112 may output the aggregation result of the integrated scores for multiple members as the evaluation result of the state of the organization.

[0095] In this way, by calculating and aggregating the integrated scores of multiple members, it is possible to perform an objective and highly reproducible "assessment of the state of the organization" based on quantitative analysis.

[0096] Specifically, the analysis unit 112 calculates an integrated score by integrating the scores of the evaluation items of the biological-related data D1 and the scores of the evaluation items of the mind-related data D2 using a predetermined function (hereinafter referred to as the "predetermined function PF"). The predetermined function PF is configured, for example, by addition, multiplication, subtraction, or division, or a combination of two or more of these. For example, the predetermined function PF may be a statistical model (mathematical model) or a learning model. Furthermore, when integrating, weighting may be applied to the scores between the evaluation items of the biological-related data D1 and the evaluation items of the mind-related data D2.

[0097] In this case, the combination of evaluation items to be integrated from among the multiple evaluation items of the biological-related data D1 and the multiple evaluation items of the mind-related data D2 (hereinafter, this may be referred to as a "heterogeneous item combination") is determined in advance by, for example, one or more of a doctor, a mind coach, and a health coach depending on the purpose of the evaluation by integration, and is stored in the storage unit 160. The heterogeneous item combination is, for example, a combination of evaluation items such as "nutrient deficiency" and "magnesium" of the biological-related data D1 (biological data D121) with evaluation items such as "thought pattern" of the mind-related data D2 (mind data D21).

[0098] A heterogeneous item combination is a combination of one or more evaluation items in the biometric-related data D1 and one or more evaluation items in the mind-related data D2. A heterogeneous item combination is not limited to a combination of one evaluation item in the biometric-related data D1 and one evaluation item in the mind-related data D2. Furthermore, the purpose of the integrated evaluation is to identify (estimate) various root causes of organizational issues, such as a worsening turnover rate or an increase in employees on leave, and there are multiple root causes. Therefore, a heterogeneous item combination is predefined for each purpose of the integrated evaluation. Furthermore, for example, even the same issue may have different root causes depending on the characteristics and circumstances of the organization. Therefore, multiple heterogeneous item combinations are defined for the same issue (e.g., a worsening turnover rate). In other words, because a single organizational issue may have multiple different root causes, multiple heterogeneous item combinations are defined to correspond to each of the multiple root causes.

[0099] For example, if the aggregated result (aggregated score) of the integrated scores for a certain combination of heterogeneous items for multiple members is above a certain value, the root cause corresponding to that combination of heterogeneous items is identified (estimated) as the root cause of the issues in the organization being evaluated.

[0100] Specifically, the analysis unit 112 aggregates the integrated scores of multiple members for each objective of the integrated evaluation (for each combination of heterogeneous items). For example, if an organizational issue is a worsening turnover rate, the analysis unit 112 aggregates the integrated scores of multiple members for each combination of heterogeneous items corresponding to each of the multiple root causes of the issue. Then, the analysis unit 112 identifies (estimates) one or more root causes that are causing the issue in the organization being evaluated, among the multiple root causes, based on the aggregation result of each of the multiple combinations of heterogeneous items corresponding to each of the multiple root causes. For example, if there are multiple possible root causes for a certain issue, the analysis unit 112 identifies the root cause corresponding to the combination of heterogeneous items whose aggregation result of the integrated score (aggregate score) is equal to or greater than a certain value as the root cause of the issue in the organization being evaluated.

[0101] The aggregated result of the integrated score (aggregate score) and the identified root causes are an example of an assessment result of the state of the organization.

[0102] The storage unit 160 stores multiple candidate action plans for each of multiple issues that may occur in the organization. In this case, a candidate action plan is prepared for each root cause. Therefore, the generation unit 113, for example, acquires a candidate action plan corresponding to the issue and root cause of the organization from among the multiple candidate action plans. Also, for example, the generation unit 113 acquires a candidate action plan corresponding to the aggregation result of the integrated score (aggregate score) from among the multiple candidate action plans. In this way, the generation unit 113 acquires a candidate action plan corresponding to the evaluation result of the state of the organization. Then, the generation unit 113 sets the acquired candidate action plan as the organizational action plan.

[0103] FIG. 8 is a diagram showing an example of an action plan candidate group PL10 for generating an organizational action plan. In the figure, "Q" represents an integer equal to or greater than 2. The action plan candidate group PL10 is stored in the storage unit 160. As shown in FIG. 8, the action plan candidate group PL10 includes action plan candidate information 700a for each implementation date. The action plan candidate information 700a includes organizational issues and content. The content indicates coaching details (coaching information) for solving the issues. The coaching details are determined, for example, from the perspective of cognitive psychology and / or behavioral psychology.

[0104] For example, the generating unit 113 acquires a plurality of pieces of action plan candidate information 700a according to the evaluation results of the state of the organization from the group of action plan candidates PL10. Then, the generating unit 113 sets the acquired plurality of pieces of action plan candidate information 700a in a plurality of pieces of action plan information 700 (FIG. 5), respectively, to generate an organization action plan PL1 (FIG. 5) including a plurality of pieces of action plan information 700.

[0105] Another example of the process for generating an organizational action plan will be described with continued reference to Fig. 4. The analysis unit 112 evaluates the state of the organization by comprehensively analyzing the biological-related data D1 and the mind-related data D2 for multiple members.

[0106] In this case, for example, a plurality of tissue evaluation candidates are stored in advance in the storage unit 160 as candidates for evaluating the state of the tissue. Therefore, the analysis unit 112 selects a tissue evaluation candidate from the plurality of tissue evaluation candidates according to the results of the integrated analysis and sets the selected tissue evaluation candidate as the evaluation result of the state of the tissue. In this case, the "result of the integrated analysis" is, for example, the "aggregated result of the integrated score (aggregated score)" described above. Note that the analysis unit 112 may select two or more tissue evaluation candidates by assigning priorities (recommended orders), for example. In this case, the analysis unit 112 transmits the integrated analysis result and information on the two or more tissue evaluation candidates assigned priorities (recommended orders) to one or more of the mind coach terminal T5, the doctor terminal T3, and the health coach terminal T4 via the communication unit 150. Then, via one or more of the mind coach terminal T5, the doctor terminal T3, and the health coach terminal T4, an organizational evaluation candidate selected from the plurality of organizational evaluation candidates according to the judgment results of one or more of the mind coach, the doctor, and the health coach is set as an evaluation result of the state of the organization and transmitted to the analysis unit 112 of the information processing device 100. In this case, the fact that the analysis unit 112 has acquired information on the evaluation result of the state of the organization corresponds to the analysis unit 112 evaluating the state of the organization.

[0107] One or more of the mind coach, doctor, and health coach may modify the tissue evaluation candidate selected by the analysis unit 112 or the mind coach, etc. via the mind coach terminal T5, etc. In this case, the modified tissue evaluation candidate is set as the evaluation result of the tissue state.

[0108] Furthermore, the generation unit 113 generates an organizational action plan in accordance with first action plan selection information (e.g., a first action plan selection table) based on the evaluation result of the organizational state. The first action plan selection information is information for selecting an organizational action plan according to the evaluation result of the organizational state. The first action plan selection information is stored in the storage unit 160. Specifically, the first action plan selection information includes information in which multiple organizational state information are associated with multiple action plan candidates. The organizational state information is information that can be adopted as the evaluation content of the organizational state. The generation unit 113 refers to the first action plan selection information to obtain the action plan candidate associated with the organizational state information corresponding to the evaluation result of the organizational state, and adopts the obtained action plan candidate as the organizational action plan. Note that the above-mentioned "aggregated result of the integrated score (aggregated score)" may be used as the "evaluation result of the organizational state."

[0109] In this way, by using the first action plan selection information that systematically associates organizational state information with action plan candidates, it becomes possible to generate an objective and consistent organizational action plan through simple processing.

[0110] The generating unit 113 may select two or more candidate action plans by prioritizing them (recommended order). In this case, the generating unit 113 may transmit information about the two or more candidate action plans with the priorities (recommended order) to the organization terminal T1 via the communication unit 150. Then, a member who operates or manages the organization may select an action plan candidate appropriate for the organization from the two or more candidate action plans via the organization terminal T1 and set the selected candidate action plan as the organization action plan. Information about the organization action plan is transmitted from the organization terminal T1 to the generating unit 113 of the information processing device 100. In this case, the generating unit 113 acquiring the organization action plan from the organization terminal T1 corresponds to the generating unit 113 generating the organization action plan.

[0111] As another example, an organizational action plan may be generated as follows. That is, the generation unit 113 may transmit the evaluation results of the organizational state and information on multiple candidate action plans to the mind coach terminal T5 via the communication unit 150. Then, the mind coach selects an effective candidate action plan for solving the organizational issues from among the multiple candidate action plans based on the evaluation results of the organizational state via the mind coach terminal T5, and sets the selected candidate action plan as the organizational action plan. The mind coach terminal T5 then transmits information on the organizational action plan to the generation unit 113 of the information processing device 100. In this case, the generation unit 113's acquisition of the organizational action plan from the mind coach terminal T5 corresponds to the generation of the organizational action plan by the generation unit 113. Note that the generation unit 113 may transmit the evaluation results of the organizational state and information on multiple candidate action plans to one or more of the mind coach terminal T5, the doctor terminal T3, and the health coach terminal T4 via the communication unit 150. In this case, an action plan candidate selected from among multiple action plan candidates based on the judgment results of one or more of the mind coach, doctor, and health coach is set as an organizational action plan via one or more of the mind coach terminal T5, doctor terminal T3, and health coach terminal T4, and is transmitted to the generation unit 113 of the information processing device 100.

[0112] In these examples, the above-described "aggregated result of integrated scores (aggregated score)" may be used as the "evaluation result of the organization's state." Furthermore, two or more candidate action plans may be selected from among a plurality of candidate action plans by prioritizing (recommended order) them based on the judgment results of one or more of the mind coach, doctor, and health coach via one or more of the mind coach terminal T5, doctor terminal T3, and health coach terminal T4. In this case, information about the two or more candidate action plans with the priorities (recommended order) assigned may be transmitted to the generating unit 113 of the information processing device 100. The generating unit 113 then transmits the information about the two or more candidate action plans with the priorities (recommended order) assigned to the organization terminal T1 via the communication unit 150. A member responsible for operating or managing the organization may then select an action plan candidate appropriate for the organization from among the two or more candidate action plans via the organization terminal T1 and set the selected candidate action plan as the organization action plan. Information about the organization action plan is transmitted from the organization terminal T1 to the generating unit 113 of the information processing device 100. In this case, the generation unit 113 acquiring the organizational action plan from the organization terminal T1 corresponds to the generation of the organizational action plan by the generation unit 113.

[0113] Continuing to refer to FIG. 4, preferably, in this embodiment, the analysis unit 112 evaluates the condition of each member by comprehensively analyzing the bio-related data D1 and mind-related data D2. Then, the generation unit 113 generates an action plan (hereinafter, "individual action plan") for each member based on the evaluation results of the member's condition to solve the member's problems. The individual action plan may be provided as, for example, a roadmap. The contents of the bio-related data D1 and mind-related data D2 are as described with reference to FIG. 3. The individual action plan corresponds to an example of a "second action plan" in the present disclosure.

[0114] In this way, both the biological-related data D1, including the biological data D121, which is biochemical data, and the mind-related data D2, including the mind data D21, based on psychological factors, are analyzed. Therefore, the mind data D21 complements psychological factors that cannot be captured by the biological data D121 alone, while the biological data D121 complements medical validity that cannot be obtained by the mind data D21 alone. This synergistic effect further improves the accuracy of the assessment of the member's condition, making it possible to generate an effective individual action plan personalized for each member.

[0115] In particular, by providing not only organizational action plans at the organizational level but also individual action plans at the individual level for each member, it is possible to provide support to both the organization and its members, thereby contributing to the resolution of organizational issues through the improvement of the health and performance of each member.

[0116] FIG. 9 is a diagram showing an example of an individual action plan PL2. In the figure, "q" represents an integer equal to or greater than 2. As shown in FIG. 9, the individual action plan PL2 includes action plan information 710 for each implementation date. The action plan information 710 includes the member's assignment and content. The content 712 indicates coaching content (coaching information) for solving the assignment 711. The coaching content is, for example, health-related content determined from a biochemical perspective. As an example, a doctor and / or a health coach provides coaching to the member in accordance with each piece of action plan information 710 in the individual action plan PL2. Note that in the example of FIG. 9, the action plan information 710 represents content to be implemented in one day, but it may also represent content to be implemented over two or more days.

[0117] For example, the individual action plan PL2 may include one or more of the following information: coaching information (content) for resolving nutritional issues and coaching information (content) for resolving lifestyle issues, depending on the evaluation results of the individual's condition. In this way, by providing optimal coaching information from the perspectives of nutrition and lifestyle based on the individual's evaluation results, effective intervention can be provided that addresses the unique challenges of each individual member.

[0118] Preferably, in this embodiment, the analysis unit 112 identifies (estimates) the cause (root cause) of the member's problem (illness) by analyzing at least the biological data D1. The contents of the biological data D1 are as shown in FIG. 3. Then, the analysis unit 112 estimates the physiological damage that may occur to the member based on the identification result (estimation result) of the cause (root cause) of the member's problem. Furthermore, the analysis unit 112 estimates the bodily system related to the physiological damage based on the estimation result of the physiological damage. It can be directly estimated that the bodily system related to the physiological damage is causing the member's problem (illness). The bodily system refers to the biological element that is the basis for maintaining biological functions. Then, the output control unit 114 generates image information (hereinafter referred to as the "personal root cause map MP2") showing the identification result of the cause (root cause), the estimation result of the physiological damage, the estimation result of the bodily system, and the member's problem (illness), and displays the image information on the member terminal T2.

[0119] FIG. 10 is a diagram showing an example of an individual root cause map MP2. As shown in FIG. 10, the individual root cause map MP2 is information that visualizes a structured chain from the root cause 411 of a member's problem 414 (illness symptom) to the member's problem 414 (illness symptom). Specifically, the individual root cause map MP2 includes information on the root cause 411, physiological damage 412, internal system 413, and problem 414 (illness symptom). In FIG. 10, black rectangles indicate items that apply to the member being evaluated.

[0120] In this way, by visualizing and providing the member with the estimated results of the cause (root cause) of the member's problem (illness), physiological damage, and internal system, the member can clearly understand the structured chain leading from the root cause to the member's problem (illness). More preferably, the analysis unit 112 estimates the cause (root cause) of the member's problem by comprehensively analyzing the mind-related data D2 and the biological-related data D1. In this case, the cause of the member's problem can be estimated more accurately.

[0121] Specifically, as an example, the storage unit 160 stores cause / damage correspondence information (e.g., a cause / damage correspondence table) that indicates the correspondence between the causes of member issues and physiological injuries. The cause / damage correspondence information is information in which multiple cause information items are associated with multiple physiological injury candidates. For example, one or more physiological injury candidates are associated with one cause information item. The cause information indicates the root cause of the member's issue. The physiological injury candidates are candidates for physiological injuries that can be derived from the cause information. The generation unit 113 refers to the cause / damage correspondence information and acquires, from the cause / damage correspondence information, physiological injury candidates associated with the cause information corresponding to the identified cause (estimated cause). Then, the generation unit 113 adopts the acquired physiological injury candidate as the physiological injury. In this way, the generation unit 113 estimates the physiological injury. Note that an example of identifying (estimating) the cause (root cause) of a member's issue will be described later.

[0122] As an example, the memory unit 160 stores injury-internal system correspondence information (e.g., an injury-internal system correspondence table) that indicates the correspondence between physiological injury and the internal body system of the member. The injury-internal system correspondence information is information in which multiple pieces of physiological injury information are associated with multiple internal body system candidates. The generation unit 113 then refers to the injury-internal system correspondence information, obtains from the injury-internal system correspondence information the internal body system candidate associated with the physiological injury information corresponding to the estimated physiological injury, and adopts it as the internal body system. In this way, the generation unit 113 estimates the internal body system.

[0123] Preferably, the generation unit 113 generates an individual evaluation report based on the integrated analysis results of the member's biological-related data D1 and mind-related data D2. The individual evaluation report is a report that shows the evaluation results of the member's condition. Note that the individual evaluation report may include the evaluation results of the individual's condition based on the analysis results of the biological-related data D1 and / or the evaluation results of the individual's condition based on the analysis results of the mind-related data D2.

[0124] Fig. 11 is a diagram showing an example of an individual evaluation report 800. As shown in Fig. 11, the individual evaluation report 800 includes, for example, blood test information 801, biological function analysis information 802, mind analysis information 803, wellness analysis information 804, and performance analysis information 805.

[0125] Blood test information 801 is information indicating the results of a member's blood test. Biofunction analysis information 802 is information indicating biofunctions such as nutritional status and intestinal inflammation. Biofunction analysis information 802 is information obtained by aggregating scores of biological data D121 and based on the aggregation results. Mind analysis information 803 is information indicating a member's thinking tendencies, such as thought patterns and the balance between the right and left brain. Mind analysis information 803 may also include information indicating a member's behavioral tendencies, such as the type of behavioral tendency. Mind analysis information 803 is information obtained by aggregating scores of mind data D21 and based on the aggregation results.

[0126] The wellness analysis information 804 includes an index indicating the physical health state of the member and an index indicating the psychological health state of the member. The index indicating the physical health state is an index based on the aggregated score of the member's biological data D121. The index indicating the psychological health state is an index based on the aggregated score of the member's mind data D21.

[0127] The performance analysis information 805 includes a productivity index that indicates the productivity of the member and a creativity index that indicates the creativity of the member. Each of the productivity index and the creativity index is a composite score obtained based on the aggregation result of the scores of the member's biological data D121 and the scores of the member's mind data D21.

[0128] Note that the above is an example, and the contents of the individual evaluation report 800 are not particularly limited.

[0129] Returning to FIG. 4, a detailed example of the integrated analysis and generation of an individual action plan will be described. The analysis unit 112 calculates an integrated score based on the scores of the evaluation items in the member's biological-related data D1 and the scores of the evaluation items in the mind-related data D2. The analysis unit 112 then evaluates the member's condition based on the integrated score. In this case, the analysis unit 112 may output the member's integrated score as an evaluation result of the member's condition.

[0130] In this way, by calculating the integrated score of each member, it is possible to perform an objective and highly reproducible "assessment of the member's status" based on quantitative analysis.

[0131] Specifically, the analysis unit 112 calculates an integrated score by integrating the scores of the evaluation items of the biological-related data D1 and the scores of the evaluation items of the mind-related data D2 using a predetermined function PF. The predetermined function PF is configured, for example, by any one of addition, multiplication, subtraction, and division, or a combination of two or more of these. For example, the predetermined function PF may be a statistical model (mathematical model) or a learning model. Furthermore, when integrating, weighting may be applied to the scores between the evaluation items of the biological-related data D1 and the evaluation items of the mind-related data D2.

[0132] In this case, the combination of evaluation items to be integrated from among the multiple evaluation items of the biological-related data D1 and the multiple evaluation items of the mind-related data D2 (hereinafter, sometimes referred to as a "heterogeneous item combination") is predetermined, for example, by at least a doctor, depending on the purpose of the evaluation by integration, and is stored in the storage unit 160. Note that a mind coach and / or a health coach may also be involved in determining the heterogeneous item combination. A heterogeneous item combination is, for example, a combination of evaluation items such as "nutrient deficiency" and "magnesium" in the biological-related data D1 (biological data D121) with evaluation items such as "thought pattern" in the mind-related data D2 (mind data D21).

[0133] A heterogeneous item combination is a combination of one or more evaluation items in the biometric data D1 and one or more evaluation items in the mind-related data D2. A heterogeneous item combination is not limited to a combination of one evaluation item in the biometric data D1 and one evaluation item in the mind-related data D2. Furthermore, the purpose of the integrated evaluation is to identify (estimate) various root causes of issues that cause members' problems, such as decreased concentration or chronic fatigue, and there may be multiple root causes. Therefore, a heterogeneous item combination is predefined for each purpose of the integrated evaluation. Furthermore, even for the same issue, for example, the root causes may differ depending on the characteristics and circumstances of the member. Therefore, multiple heterogeneous item combinations are defined for the same issue (e.g., decreased concentration). In other words, because there may be multiple different root causes for a single issue of a member, multiple heterogeneous item combinations are defined corresponding to each of the multiple root causes.

[0134] For example, if the integrated score of a certain combination of heterogeneous items for a member is equal to or greater than a certain value, the root cause corresponding to the combination of heterogeneous items is identified (estimated) as the root cause of the issue of the member being evaluated.

[0135] Specifically, the analysis unit 112 calculates the member's integrated score for each objective of the integrated evaluation (for each combination of heterogeneous items). For example, if the member's problem is a decline in concentration, the analysis unit 112 calculates the member's integrated score for each of multiple combinations of heterogeneous items corresponding to multiple root causes of the problem. Then, the analysis unit 112 identifies (estimates) one or more root causes that are causing the problem of the member to be evaluated, from among the multiple root causes, based on the integrated scores of each of the multiple combinations of heterogeneous items corresponding to the multiple root causes. For example, if there are multiple possible root causes for a certain problem, the analysis unit 112 identifies the root cause corresponding to the combination of heterogeneous items with an integrated score equal to or greater than a certain value as the root cause of the problem of the member to be evaluated.

[0136] The combined score and identified root causes are an example of an assessment result of a member's condition.

[0137] The storage unit 160 stores multiple candidate action plans for each issue that may arise for a member. In this case, a candidate action plan is prepared for each root cause. Therefore, the generation unit 113, for example, acquires a candidate action plan from the multiple candidate action plans that corresponds to the member's issue and root cause. Also, for example, the generation unit 113 acquires a candidate action plan from the multiple candidate action plans that corresponds to the integrated score. In this way, the generation unit 113 acquires a candidate action plan that corresponds to the evaluation result of the member's state. Then, the generation unit 113 sets the acquired candidate action plan as an individual action plan.

[0138] FIG. 12 is a diagram showing an example of a group of action plan candidates PL20 for generating an individual action plan. In the figure, "q" represents an integer equal to or greater than 2. The group of action plan candidates PL20 is stored in the storage unit 160. As shown in FIG. 12, the group of action plan candidates PL20 includes action plan candidate information 710a for each implementation date. The action plan candidate information 710a includes tasks and content for the members. The content indicates coaching details (coaching information) for solving the tasks. The coaching details are, for example, determined from a biochemical perspective.

[0139] For example, the generation unit 113 acquires multiple pieces of behavior plan candidate information 710a according to the evaluation results of the member's state from the behavior plan candidate group PL20. Then, the generation unit 113 sets the acquired multiple pieces of behavior plan candidate information 710a in multiple pieces of behavior plan information 710 (FIG. 9), respectively, to generate an individual behavior plan PL2 (FIG. 9) including the multiple pieces of behavior plan information 710.

[0140] Another example of the process of generating an individual action plan will be described with continued reference to Fig. 4. The analysis unit 112 evaluates the individual's condition by comprehensively analyzing the member's biological-related data D1 and mind-related data D2.

[0141] In this case, for example, a plurality of individual evaluation candidates are stored in advance in the storage unit 160 as candidates for evaluating the member's condition. Accordingly, the analysis unit 112 selects an individual evaluation candidate from the plurality of individual evaluation candidates according to the result of the integrated analysis and sets the selected individual evaluation candidate as an evaluation result of the individual's condition. The "result of the integrated analysis" in this case is, for example, the "integrated score" described above. The analysis unit 112 may select two or more individual evaluation candidates by prioritizing them (recommended rankings), for example. In this case, the analysis unit 112 transmits the integrated analysis result and information on the two or more individual evaluation candidates with the priorities (recommended rankings) to at least the doctor terminal T3 via the communication unit 150. Then, the individual evaluation candidate selected by the doctor from the plurality of individual evaluation candidates according to the doctor's diagnosis results is set as an evaluation result of the individual's condition and transmitted to the analysis unit 112 of the information processing device 100 via the doctor terminal T3. In this case, the analysis unit 112's acquisition of information on the evaluation result of the individual's condition corresponds to the analysis unit 112's evaluation of the individual's condition.

[0142] The doctor may correct the individual evaluation candidate selected by the analysis unit 112 or the doctor via the doctor terminal T3. In this case, the corrected individual evaluation candidate is set as the evaluation result of the individual's condition.

[0143] As described above, the analysis unit 112 may evaluate the condition of an individual based on the results of the integrated analysis and the input information input via the doctor terminal T3. By using the input information from the doctor, it is possible to obtain highly reliable evaluation results while ensuring legal and medical legitimacy.

[0144] It should be noted that a health coach may be involved in the assessment of the individual's condition via the health coach terminal T4.

[0145] Furthermore, the generation unit 113 generates an individual action plan according to second action plan selection information (e.g., a second action plan selection table) based on the evaluation results of the member's condition. The second action plan selection information is information for selecting an individual action plan according to the evaluation results of the individual's condition. The second action plan selection information is stored in the memory unit 160. Specifically, the second action plan selection information includes information in which multiple pieces of individual condition information are associated with multiple action plan candidates. The individual condition information is information that can be adopted as the evaluation content of the individual's condition. The generation unit 113 refers to the second action plan selection information to obtain action plan candidates associated with the individual condition information corresponding to the evaluation results of the individual's condition, and adopts the obtained action plan candidates as the individual action plan. Note that the above-mentioned "integrated score" may be used as the "evaluation result of the individual's condition."

[0146] In this way, by using the second action plan selection information that systematically associates the personal condition information with the action plan candidates, it is possible to generate an objective and consistent personal action plan through simple processing. Note that the doctor may modify the personal action plan generated by the analysis unit 112 via the doctor terminal T3. In this case, the modified personal action plan is set as the final personal action plan.

[0147] The generation unit 113 may select two or more candidate action plans by prioritizing them (recommended order). In this case, the generation unit 113 may transmit information about the two or more candidate action plans with the priorities (recommended order) to the member terminal T2 via the communication unit 150. The member may then select an action plan candidate that suits him or her from the two or more candidate action plans via the member terminal T2 and set the selected candidate action plan as an individual action plan. Information about the individual action plan is transmitted from the member terminal T2 to the generation unit 113 of the information processing device 100. In this case, the generation unit 113 acquiring the individual action plan from the member terminal T2 corresponds to the generation of the individual action plan by the generation unit 113.

[0148] As another example, an individual action plan may be generated as follows. That is, the generation unit 113 may transmit the evaluation result of the individual's condition and information on multiple action plan candidates to at least the doctor terminal T3 via the communication unit 150. Then, the doctor selects an action plan candidate that is effective for solving the individual's problem from among the multiple action plan candidates based on the evaluation result of the individual's condition via the doctor terminal T3, and sets the selected action plan candidate as the individual action plan. Then, the doctor terminal T3 transmits information on the individual action plan to the generation unit 113 of the information processing device 100. In this case, the generation unit 113's acquisition of the individual action plan from the doctor terminal T3 corresponds to the generation of the individual action plan by the generation unit 113. Note that the doctor may also modify the selected action plan candidate via the doctor terminal T3 and set the modified action plan candidate as the individual action plan.

[0149] In these examples, the above-described "integrated score" may be used as the "evaluation result of the individual's condition." Furthermore, two or more candidate action plans may be selected from among a plurality of candidate action plans, with priorities (recommended ranks) assigned according to the doctor's judgment, at least via the doctor terminal T3. In this case, information about the two or more candidate action plans with priorities (recommended ranks) assigned is transmitted to the generation unit 113 of the information processing device 100. The generation unit 113 then transmits the information about the two or more candidate action plans with priorities (recommended ranks) assigned to the member terminal T2 via the communication unit 150. The member may then select a candidate action plan appropriate for themselves from among the two or more candidate action plans via the member terminal T2 and set the selected candidate action plan as an individual action plan. Information about the individual action plan is transmitted from the member terminal T2 to the generation unit 113 of the information processing device 100. In this case, the generation unit 113's acquisition of the individual action plan from the member terminal T2 corresponds to the generation of the individual action plan by the generation unit 113.

[0150] It should be noted that a health coach may be involved in generating the personal action plan via the health coach terminal T4.

[0151] As described above, the generation unit 113 may generate an individual action plan based on the evaluation result of the member's condition and the input information input via the doctor terminal T3. In this case, the input information includes information related to the individual action plan (doctor input information).

[0152] By using information input by a doctor, it becomes possible to provide a more reliable and safer personal action plan that combines the analysis results of the vital function data D12 with the doctor's clinical knowledge and diagnosis, thereby achieving effective support while ensuring legal and medical legitimacy.

[0153] Next, a detailed example of the biometric data D1 will be described with reference to FIGS.

[0154] FIG. 13 is a schematic diagram showing self-assessment data D11 of the biological-related data D1. As shown in FIG. 13, the self-assessment data D11 includes biochemical categories 71, evaluation items 72, question items 73, answer information 74, and an evaluation score 75. The biochemical categories 71 include, for example, nutrient deficiencies, damage to the living body, adrenal glands, thyroid gland, mitochondrial function, neurotransmitters, improvement of the intestinal environment, toxins, and brain function. The biochemical categories 71 can also be considered as "evaluation items." The evaluation score 75 is also an example of a "score."

[0155] The evaluation items 72 indicate evaluation targets included in the biochemical category 71. For example, if the biochemical category 71 is "nutrient deficiency," the evaluation items 72 are magnesium, zinc, and iron.

[0156] A plurality of question items 73 for members are assigned to one evaluation item 72. The question item 73 includes a question for evaluating the evaluation target indicated by the evaluation item 72. The answer information 74 includes an answer to the question in the question item 73. The answer information 74 is information indicating "yes" or "no" to the question in the question item 73. The evaluation score 75 indicates a score according to the answer information 74 of the member to the question in the question item 73. For example, if the answer information 74 is "yes", the evaluation score 75 is set to "1", and if the answer information 74 is "no", the evaluation score 75 is set to "0". The evaluation score 75 is, for example, binary information.

[0157] The information processing device 100 transmits the self-assessment data D11, in which the answer information 74 and the evaluation score 75 have not yet been set, as a questionnaire to the member terminal T2. The member then sets the answer information 74 in the questionnaire via the member terminal T2. The information processing device 100 (analysis unit 112) then sets a score corresponding to the answer information 74 as the evaluation score 75. The information processing device 100 stores the self-assessment data D11 in the biometric-related database device 200 in association with the member's identification information.

[0158] FIG. 14 is a schematic diagram showing biological data D121 of the living body-related data D1. As shown in FIG. 14, the biological data D121 includes a biochemical category 91, an evaluation item 92, and a plurality of pieces of test information 93. The biochemical category 91 corresponds to the biochemical category 71 (FIG. 13) of the self-assessment data D11. The evaluation item 92 corresponds to the evaluation item 72 (FIG. 13) of the self-assessment data D11 and indicates an evaluation target included in the biochemical category 91. The biochemical category 91 can also be considered as an "evaluation item."

[0159] The plurality of test information 93 includes, for example, two or more pieces of information related to a blood test (nutrients), a hair test, a blood glucose test, a saliva cortisol test, a microbiome test, a urine organic acid test, and a DNA test (methylation). The plurality of test information 93 may include, for example, information related to a sleep test. Furthermore, one piece of test information 93 may be assigned to one evaluation item 92, or two or more pieces of test information 93 may be assigned to one evaluation item 92.

[0160] Each piece of test information 93 includes biometric test information 931 extracted from a biological sample of the member and an evaluation score 932. The evaluation score 932 is an example of a "score." The biometric test information 931 is, for example, blood test information related to nutrients, hair test information, blood glucose test information, saliva cortisol test information, microbiome test information, urinary organic acid test information, or DNA test information. Furthermore, one piece of test information 93 may be assigned to one evaluation item 92, or two or more pieces of test information 93 may be assigned to one evaluation item 92. The evaluation score 932 indicates a score corresponding to the biometric test information 931.

[0161] The vital data D122 has a similar structure to the biological data D121.

[0162] FIG. 15 is a schematic diagram showing analysis logic information LG1 for biological data D121. As shown in FIG. 15, the analysis logic information LG1 includes a biochemical category 201, evaluation items 202, and multiple pieces of determination criterion information 203. The biochemical category 201 corresponds to the biochemical category 91 (FIG. 14) of the biological data D121. The evaluation items 202 correspond to the evaluation items 92 of the biological data D121 and indicate evaluation targets included in the biochemical category 201. The determination criterion information 203 indicates the determination criteria used to determine the evaluation score 932 (FIG. 14) for the biopsy information 931 (FIG. 14). For example, the determination criterion information 203 defines determination conditions for the test values ​​indicated by the biopsy information 931, and assigns points depending on whether the determination conditions are met. For example, the criteria information 203 specifies that if the test value is equal to or greater than the threshold, the evaluation score 932 is set to "1," and if the test value is less than the threshold, the evaluation score 932 is set to "0." The evaluation score 932 is, for example, binary information.

[0163] The analysis unit 112 refers to the criteria information 203 and sets an evaluation score 932 (FIG. 14) for the biopsy information 931 (FIG. 14).

[0164] 13 to 15, the analysis unit 112 calculates a total score (hereinafter referred to as "total score TS") as the result of addition by adding the sum of the evaluation scores 75 for the evaluation item 72 in the self-assessment data D11 (FIG. 13) and the sum of the evaluation scores 932 for the evaluation item 92 in the biological data D121 (FIG. 14). As a result, the total score TS is calculated for each evaluation item 72 (evaluation item 92) from the self-assessment data D11 to the biological data D121. For example, the total score TS for the evaluation item 72 (evaluation item 92) "magnesium" is calculated by adding the sum of the evaluation scores 75 for the evaluation item 72 "magnesium" and the sum of the evaluation scores 932 for the evaluation item 92 "magnesium" that has the same content as the evaluation item 72.

[0165] Then, based on the analysis logic information LG2, the analysis unit 112 sets evaluation information corresponding to the total score TS for the evaluation item 72 (evaluation item 92). The total score TS is an example of a "score."

[0166] FIG. 16 is a schematic diagram showing analysis logic information LG2 for the self-assessment data D11 and the biological data D121. As shown in FIG. 16, the analysis logic information LG2 includes a biochemical category 211, evaluation items 212, criterion information 213, and evaluation information 214. The biochemical category 211 corresponds to the biochemical categories 71 and 91 (FIGS. 13 and 14). The evaluation items 212 correspond to the evaluation items 72 and 92 and indicate the evaluation targets included in the biochemical category 211. The criterion information 213 indicates the criterion used to determine the evaluation information for the total score TS. In the example of FIG. 16, the criterion information 213 includes a range of points for the total score TS. In the analysis logic information LG2, evaluation information 214 for the total score TS is associated with each range in a stepwise manner.

[0167] Based on the analysis logic information LG2, the analysis unit 112 sets evaluation information 214 corresponding to the total score TS for the evaluation item 72 (evaluation item 92). Note that the total score TS and the evaluation information 214 are an example of an evaluation result of the individual's condition.

[0168] The analysis unit 112 can evaluate the condition of the member from a biochemical perspective by analyzing the member's biological data D121 and self-assessment data D11. Therefore, the validity of the self-assessment data D11, which is subjective data, can be verified by the biological data D121, which is objective data.

[0169] Next, a detailed example of the mind-related data D2 will be described with reference to FIGS.

[0170] Fig. 17 is a schematic diagram showing an example of thinking tendency data D211 of the mind-related data D2. As shown in Fig. 17, the thinking tendency data D211 includes a plurality of section data A1 to AN. N is an integer of 2 or more. The section data A1 to AN may be collectively referred to as section data An. n is an integer of 1 or more.

[0171] Section data An includes multiple segment data 10. The segment data 10 includes question items 11, answer information 12, and an evaluation score 13. The evaluation score 13 is an example of a "score." The question items 11 include questions for identifying a thinking tendency based on the cognitive function of the member. In other words, the question items 11 are evaluation items for identifying a thinking tendency based on the cognitive function of the member. The answer information 12 includes multiple answer candidates for the question in question item 11. An answer candidate selected by the member from the multiple answer candidates is set as the answer information 12. In the example of Figure 17, black rectangles indicate answer candidates selected by the member. The answer information 12 indicates the member's answer to the question in question item 11. The evaluation score 13 indicates the score set for the evaluation item (question item) according to the answer information 12.

[0172] For example, sections A1 through A7 each contain 11 questions about thinking patterns (how you perceive and think about things), right-brain / left-brain balance (is your information processing style logical or intuitive?), risk and reward (in what situations do you tend to take action?), future / present / past (where is the timeline for decision-making?), reward system (what motivates you), modal channel (which sense is your best at receiving information—auditory, visual, emotional, or physical senses?), and prefrontal cortex activity (levels of planning, self-control, and creativity). The titles of these sections A1 through A7 can also be considered "assessment items." Motivation, for example, refers to the motivation that drives action.

[0173] The information processing device 100 transmits the thinking tendency data D211, in which the answer information 12 and the evaluation score 13 have not yet been set, to the member terminal T2 as a questionnaire. Then, the member sets the answer information 12 in the questionnaire via the member terminal T2. Then, the information processing device 100 (analysis unit 112) sets a score corresponding to the answer information 12 as the evaluation score 13. The information processing device 100 associates the thinking tendency data D211 with the member's identification information and stores it in the mind-related database device 300.

[0174] Fig. 18 is a diagram showing an analysis logic table TB1 for thinking tendency data D211. As shown in Fig. 18, the analysis logic table TB1 is stored in the storage unit 160. The analysis logic table TB1 includes analysis logic information B1 to BN assigned to each of the section data A1 to AN. N is an integer of 2 or more. The analysis logic information B1 to BN may be collectively referred to as analysis logic information Bn. n is an integer of 1 or more.

[0175] The analysis logic information Bn includes cognitive psychology indexes 21, section information 22, criterion information 23, and type information 24.

[0176] The cognitive psychology index 21 indicates a category of thinking tendency identified by the section data An corresponding to the analytical logic information Bn. For example, the cognitive psychology index 21 corresponds to each of the section data A1 to AN and includes a thinking pattern, an information processing style, a behavioral type, a time axis of thinking, a source of motivation, a dominant sensory channel, and a self-growth potential.

[0177] The section information 22 is information for identifying the section data An corresponding to the analysis logic information Bn. The judgment criteria information 23 includes range information defined for the total score 14 (FIG. 17), which is the sum of the evaluation scores 13 for each section data An. The type information 24 includes information on the type of thinking tendency corresponding to each range defined in the judgment criteria information 23. The type information 24 is, for example, analytical / risk management type, balanced type, or creative / goal-oriented type.

[0178] The analysis unit 112 calculates the total score 14 of the evaluation scores 13 for each piece of section data An. Then, the analysis unit 112 refers to the judgment criteria information 23 of the analysis logic information Bn corresponding to the section data An to identify the range to which the total score 14 belongs. Furthermore, the analysis unit 112 refers to the type information 24 to identify the type (the type of thinking tendency of the member) corresponding to the range to which the total score 14 belongs. Note that the total score 14 and the type information 24 are an example of the evaluation result of an individual's condition.

[0179] Fig. 19 is a schematic diagram showing an example of behavioral tendency data D212 of mind data D21. As shown in Fig. 19, behavioral tendency data D212 includes a plurality of section data C1 to CK. K is an integer of 2 or more. The section data C1 to CK may be collectively referred to as section data Ck. k is an integer of 1 or more.

[0180] The section data Ck includes multiple segment data 30. The segment data 30 includes question items 31, answer information 32, and an evaluation score 33. The question items 31 include questions for identifying behavioral tendencies based on the member's psychological or mental factors. In other words, the question items 31 are evaluation items for identifying behavioral tendencies based on the member's psychological or mental factors. The answer information 32 includes multiple answer candidates for the question in the question item 31. An answer candidate selected by the member from the multiple answer candidates is set as the answer information 32. The answer information 32 indicates the member's answer to the question in the question item 31. The evaluation score 33 indicates a score set for the evaluation item (question item) according to the answer information 32. The evaluation score 33 is an example of a "score."

[0181] Here is an example where K = 6. For example, section data C1 to C6 each contain 31 questions related to "Analyzer" (analysis, organization, planning), "Believer" (trust, mission, ethics), "Empathizer" (warmth, relationships, security), "Innovator" (creativity, play, freedom), "Driver" (challenge, action, results), and "Reflector" (insight, serenity, conception) in the CRM (Cognitive Response Model) model.

[0182] The CRM model is a diagnostic model that focuses on "which cognitive pathways people prioritize when under stress or making decisions." In the CRM model, "Analyzer," "Believer," "Empathizer," "Innovator," "Driver," and "Reflector" represent personality types. Each type is distinguished by its information processing style, motivation, interpersonal tendencies, and stress response.

[0183] The information processing device 100 has previously transmitted the behavioral tendency data D212, in which the answer information 32 and the evaluation score 33 have not yet been set, to the member terminal T2 as a questionnaire. The member then sets the answer information 32 in the questionnaire via the member terminal T2. The information processing device 100 (analysis unit 112) then sets a score corresponding to the answer information 32 as the evaluation score 33. In the example of FIG. 19, black rectangles indicate answers by the members. The information processing device 100 associates the behavioral tendency data D212 with the identification information of the members and stores the same in the mind-related database device 300.

[0184] Next, the analysis logic information EX and the analysis logic table TB2 for the behavioral tendency data D212 will be described with reference to Fig. 20. The analysis logic information EX and the analysis logic table TB2 are stored in the storage unit 160.

[0185] FIG. 20(a) is a schematic diagram showing analysis logic information EX. As shown in FIG. 20(a), the analysis logic information EX includes rule information for determining the type of behavioral tendency of a member. The rule information is information indicating that the total score 34 (FIG. 19), which is the sum of the evaluation scores 33 for each section data Ck, is ranked and the type of behavioral tendency is identified according to the ranking. For example, the personality type (e.g., "Analyzer") corresponding to the section data Ck having the highest total score 34 may be identified as the basic type (e.g., Base) of the member's behavioral tendency. Furthermore, for example, the personality type (e.g., "Driver") corresponding to the section data Ck having the second highest total score 34 may be identified as a secondary type (e.g., Phase) of the member's behavioral tendency.

[0186] The analysis unit 112 calculates and ranks the total score 34 of the evaluation scores 33 for each section data Ck. Then, the analysis unit 112 refers to the analysis logic information EX and identifies the type of behavioral tendency of the member according to the ranking of the total score 34. The total score 34 and the type of behavioral tendency are examples of the evaluation results of the individual's state.

[0187] Fig. 20(b) is a schematic diagram showing the analysis logic table TB2. As shown in Fig. 20(b), the analysis logic table TB2 includes a plurality of pieces of analysis logic information F1 to FK, where K is an integer of 2 or greater. The analysis logic information F1 to FK may be collectively referred to as analysis logic information Fk, where k is an integer of 1 or greater.

[0188] The analysis logic information Fk associates type information 41 indicating the personality type corresponding to the section data Ck with attribute information 42 of the personality type indicated by the type information 41. The attribute information includes, for example, the characteristics of the personality type (e.g., psychological needs), recommended responses (e.g., communication tips), etc.

[0189] The analysis unit 112 refers to the analysis logic information Fk, among the analysis logic information F1 to FK, that corresponds to the type of behavioral tendency (personality type) of the member identified based on the analysis logic information EX, to identify and acquire attribute information 42 associated with the type of behavioral tendency of the member. Note that the attribute information 42 is an example of the evaluation result of the individual's condition.

[0190] Fig. 21 is a schematic diagram showing an example of the interview data D22. As shown in Fig. 21, the interview data D22 includes first interview information D221 and second interview information D222.

[0191] The first interview information D221 includes question items 51, record information 52, standard scores 53, evaluation standard information 54, and evaluation scores 55. The evaluation scores 55 are an example of a "score."

[0192] The question items 51 include questions for identifying the thinking tendencies and / or behavioral tendencies of the members. In other words, the question items 51 are evaluation items for identifying the thinking tendencies and / or behavioral tendencies of the members. The question items 51 are, for example, questions about "experiences of challenging high goals."

[0193] The recorded information 52 includes a record of the member's answers to the questions 51 during the interview by the mind coach and the results of the observations. The standard score 53 indicates the number of points to be awarded when the member's answers correspond to the criteria indicated by the evaluation criteria information 54. The evaluation criteria information 54 indicates the criteria for evaluating the member's thinking tendency and / or behavioral tendency based on the recorded information 52 for the questions 51. The standard score 53 and the evaluation criteria information 54 are options. The evaluation score 55 indicates the number of points actually awarded for the evaluation items in accordance with the member's answer results, with reference to the standard score 53 and the evaluation criteria information 54.

[0194] During an interview via the mind coach terminal T5 and the member terminal T2, the mind coach asks the member questions 51 and records recorded information 52. The mind coach then refers to the standard score 53 and evaluation standard information 54 and sets an evaluation score 55 based on the member's answers and the results of observation.

[0195] The information processing device 100 may transmit the first interview information D221 as a questionnaire to the member terminal T2 in advance. Then, the member sets an evaluation score 55 as an answer result to the question item 51 in the questionnaire via the member terminal T2. In this case, the mind coach can grasp the difference between the member's evaluation score 55 (answer result) in advance and the evaluation score 55 by the mind coach for the same question item 51 at the time of the interview.

[0196] The second interview information D222 includes observation items 56, record information 57, standard scores 58, evaluation standard information 59, and an evaluation score 60. The evaluation score 60 is an example of a "score."

[0197] The observation items 56 indicate matters to be observed in an interview to identify the member's thinking tendencies and / or behavioral tendencies. In other words, the observation items 56 are evaluation items for identifying the member's thinking tendencies and / or behavioral tendencies. The observation items 56 are, for example, observations of "goal setting and motivation to achieve." The record information 57 includes a record of the member's observation results for the observation items 56 during the interview by the mind coach.

[0198] The standard score 58 indicates the number of points to be awarded when the member's observation results correspond to the criteria indicated by the evaluation criteria information 59. The evaluation criteria information 59 indicates the criteria for evaluating the member's thinking tendency and / or behavioral tendency based on the observation items 56. The standard score 58 and the evaluation criteria information 59 are options. The evaluation score 60 indicates the number of points actually awarded for the evaluation items based on the member's observation results, with reference to the standard score 58 and the evaluation criteria information 59.

[0199] During an interview via the mind coach terminal T5 and the member terminal T2, the mind coach observes the member based on the observation items 56. The mind coach then refers to the standard score 58 and the evaluation standard information 59 and sets an evaluation score 60 based on the observation results of the member.

[0200] The interview data D22 is transmitted from the mind coach terminal T5 to the mind-related database device 300.

[0201] The analysis unit 112 can evaluate the member's state from a psychological or mental perspective by analyzing the member's mind data D21 and interview data D22. Specifically, the analysis unit 112 identifies at least one of the member's thinking tendency and behavioral tendency by analyzing the member's mind data D21 and interview data D22. The interview data D22 is information regarding at least one of the member's thinking tendency and behavioral tendency obtained through an interview between the mind coach and the member. Therefore, by including the interview data D22 in the analysis in addition to the mind data D21 based on the member's self-evaluation, it is possible to more accurately and deeply identify the member's thinking tendency and / or behavioral tendency.

[0202] Next, the flow of processing by the information processing device 100 will be described with reference to FIGS.

[0203] 22 is a flowchart showing an example of an information processing method relating to an organization according to this embodiment. The information processing method is executed by the information processing device 100 shown in FIG.

[0204] 22, the information processing method includes steps S1 to S13. A program stored in the storage unit 160 of the information processing device 100 causes the processing unit 110 to execute steps S1 to S13. In other words, the program product realizes steps S1 to S13 when the program is executed by the processing unit 110. The processing unit 110 corresponds to an example of the "computer" in the present disclosure.

[0205] First, in step S1, the acquiring unit 111 acquires the biometric data D1 of the members from the biometric database device 200.

[0206] Next, in step S2, the analysis unit 112 analyzes the living body-related data D1 and evaluates the condition of the member from a biochemical point of view based on the analysis results.

[0207] Next, in step S3, the acquisition unit 111 acquires the mind-related data D2 of the members from the mind-related database device 300.

[0208] Next, in step S4, the analysis unit 112 analyzes the mind-related data D2 and evaluates the state of the member from a psychological perspective based on the analysis results.

[0209] Next, in step S5, the analysis unit 112 comprehensively analyzes the evaluation results of the member's condition based on the analysis results of the bio-related data D1 and the evaluation results of the member's condition based on the analysis results of the mind-related data D2 to obtain an integrated analysis result.

[0210] Next, in step S6, the analysis unit 112 determines whether or not the processing of steps S1 to S5 has been completed for all members to be supported.

[0211] If a negative determination is made in step S6 (NO), the process proceeds to step S1, where processing for another member is executed.

[0212] On the other hand, if the determination in step S6 is affirmative (YES), the process proceeds to step S7.

[0213] Next, in step S7, the analysis unit 112 tally and analyzes the integrated analysis results (step S5) for all members, and evaluates the state of the organization based on the tallying and analysis results.

[0214] Next, in step S8, the generation unit 113 acquires a candidate action plan associated with the evaluation result of the state of the organization from the candidate action plan group for the organization, and sets the candidate action plan as the organization action plan. The storage unit 160 stores the organization action plan.

[0215] Next, in step S9, the output control unit 114 causes the organization terminal T1 to display the organization action plan.

[0216] Next, in step S10, the generation unit 113 generates an organizational root cause map based on the results of the aggregation and analysis of the integrated analysis results for all members (step S7). Note that the generation unit 113 may also generate the organizational root cause map based on the analysis results of the mind-related data D2 for all members. The storage unit 160 stores the organizational root cause map.

[0217] Next, in step S11, the output control unit 114 causes the organization root cause map to be displayed on the organization terminal T1.

[0218] Next, in step S12, the generation unit 113 generates an organization evaluation report based on the analysis results of step S2 for all members, the analysis results of step S4 for all members, and the results of aggregating and analyzing the integrated analysis results in step S7. The storage unit 160 stores the organization evaluation report.

[0219] Next, in step S13, the output control unit 114 causes the organization evaluation report to be displayed on the organization terminal T1, and the information processing method then ends.

[0220] The order of steps S1 and S2 and steps S3 and S4 may be reversed. Steps S10 and S11 and steps S12 and S13 can be executed at any timing after step S7.

[0221] Furthermore, steps S3 to S5 are omitted when generating an organizational action plan based on the biological-related data D1 including at least the biological data D121. Then, in step S7, the analysis unit 112 compiles the analysis results of the biological-related data D1 for all members and evaluates the state of the organization based on the analysis results.

[0222] 23 is a flowchart showing an example of an information processing method relating to members according to this embodiment. The information processing method is executed by the information processing device 100 shown in FIG.

[0223] 23, the information processing method includes steps S21 to S31. A program stored in the storage unit 160 of the information processing device 100 causes the processing unit 110 to execute steps S21 to S31. That is, the program product realizes steps S21 to S31 when the program is executed by the processing unit 110. The processing unit 110 corresponds to an example of the "computer" in the present disclosure.

[0224] First, steps S21 to S24 are executed. The processes in steps S21 to S24 are the same as the processes in steps S1 to S4 in FIG.

[0225] Next, in step S25, the analysis unit 112 comprehensively analyzes the evaluation results of the member's condition based on the analysis results of the bio-related data D1 and the evaluation results of the member's condition based on the analysis results of the mind-related data D2, and evaluates the member's condition based on the analysis results.

[0226] Next, in step S26, the generation unit 113 acquires a candidate action plan associated with the member's status evaluation result (step S25) from the candidate action plan group for the member, and sets the candidate action plan as the individual action plan. The storage unit 160 stores the individual action plan.

[0227] Next, in step S27, the output control unit 114 causes the individual action plan to be displayed on the member terminal T2.

[0228] Next, in step S28, the generation unit 113 generates an individual root cause map based on the integrated analysis result (step S25). Note that the generation unit 113 may generate the individual root cause map based on the analysis result of step S22. The storage unit 160 stores the individual root cause map.

[0229] Next, in step S29, the output control unit 114 causes the individual root cause map to be displayed on the member terminal T2.

[0230] Next, in step S30, the generation unit 113 generates an individual evaluation report based on the analysis result of step S22, the analysis result of step S24, and the integrated analysis result of step S25. The storage unit 160 stores the individual evaluation report.

[0231] Next, in step S31, the output control unit 114 causes the personal evaluation report to be displayed on the member terminal T2, and the information processing method then ends.

[0232] The order of steps S21 and S22 and steps S23 and S24 may be reversed. Steps S28 and S29 and steps S30 and S31 can be executed at any timing after step S25.

[0233] (Example of the use of generative AI (artificial intelligence)) The generation unit 113 may generate the organizational action plan by using a generation AI such as a large language model (LLM). The following description will be given taking the LLM as an example.

[0234] For example, the information processing device 100 inputs a prompt and reference data (context data) to the LLM to generate an organizational action plan.

[0235] In this case, as a first example, the reference data includes biometric data D1 for each member, analysis logic information for analyzing the biometric data D1 (e.g., analysis logic information LG1, LG2), aggregation analysis rules for the analysis results of the biometric data D1 of multiple members, a group of action plan candidates (e.g., a group of action plan candidates PL10) including candidates for organizational action plans, and an action plan selection rule (e.g., first action plan selection information). The action plan selection rule is information that associates the analysis results of the biometric data D1 based on the aggregation analysis rules with the optimal action plan candidates when the analysis results are obtained. The analysis results include, for example, an evaluation result of the state of the organization based on the scoring results (including the aggregation results) of the biometric data D1 and / or the scoring results (including the aggregation results) of the biometric data D1. Furthermore, the biometric data D1 includes at least biological data D121. Furthermore, the prompt includes (1) analyzing the biometric data D1 for each member according to the analysis logic information, (2) aggregating and analyzing the analysis results of all members according to the aggregation and analysis rules, (3) referring to the action plan selection rules, selecting an action plan candidate associated with the analysis results obtained according to the aggregation and analysis rules as the organizational action plan, (4) obtaining the specific content of the selected organizational action plan from the group of action plan candidates, and (5) generating image information of the organizational action plan according to a predetermined format.

[0236] For example, the analysis unit 112 may execute processing corresponding to prompts (1) to (3), and the generation unit 113 may input the execution results (analysis results) to the LLM, so that the LLM executes the processing of prompts (4) and (5).

[0237] As a second example, the reference data includes biometric data D1 for each member, analysis logic information for analyzing the biometric data D1, mind-related data D2 for each member, analysis logic information for analyzing the mind-related data D2 (e.g., analysis logic information Bn, EX, Fk), integration rules for the analysis results (scoring results) of the biometric data D1 and the analysis results (scoring results) of the mind-related data D2 (e.g., a predetermined function PF that specifies the integration), aggregation analysis rules, a group of candidate action plans including candidates for organizational action plans, and action plan selection rules.

[0238] In this case, the aggregation and analysis rules are rules for aggregating and analyzing the integrated analysis results (e.g., integrated scores) of the analysis results (scoring results) of the biological-related data D1 and the mind-related data D2 obtained for each member according to the integration rules. The action plan selection rules are information that associates the analysis results based on the aggregation and analysis rules with the optimal action plan candidates when the analysis results are obtained. The analysis results based on the aggregation and analysis rules include, for example, the evaluation results of the organization's state and / or the aggregation results of the integrated scores. Furthermore, the biological-related data D1 includes at least biological data D121. The mind-related data D2 includes at least mind data D21.

[0239] Furthermore, the prompt includes (1) analyzing the biometric-related data D1 for each member according to the analysis logic information, (2) analyzing the mind-related data D2 for each member according to the analysis logic information, (3) integrating the analysis results of the biometric-related data D1 and the analysis results of the mind-related data D2 according to the integration rules, (4) aggregating and analyzing the integrated analysis results for all members according to the aggregation analysis rules, (5) referring to the action plan selection rules, selecting as the organizational action plan a candidate action plan associated with the analysis results obtained according to the aggregation analysis rules, (6) obtaining the specific contents of the selected organizational action plan from the group of action plan candidates, and (7) generating image information of the organizational action plan according to a predetermined format.

[0240] For example, the information processing device 100 inputs a prompt and reference data (context data) to the LLM to generate an individual action plan.

[0241] In this case, as a third example, the reference data includes the member's biometric-related data D1, analysis logic information for analyzing the biometric-related data D1, the member's mind-related data D2, analysis logic information for analyzing the mind-related data D2, integration rules for the analysis results (scoring results) of the biometric-related data D1 and the analysis results (scoring results) of the mind-related data D2, aggregation analysis rules, a group of personal plan candidates including candidates for personal action plans, and action plan selection rules.

[0242] Furthermore, the aggregation and analysis rules are rules for aggregating and analyzing the integrated analysis results (e.g., integrated scores) of the analysis results (scoring results) of the member's biological-related data D1 and the analysis results (scoring results) of the mind-related data D2 obtained according to the integration rules. The action plan selection rules are information that associates the analysis results based on the aggregation and analysis rules with the optimal action plan candidates when the analysis results are obtained. The analysis results based on the aggregation and analysis rules include, for example, the evaluation results of the member's condition and / or the aggregation results of the integrated scores. Furthermore, the biological-related data D1 includes at least biological data D121. The mind-related data D2 includes at least mind data D21.

[0243] Furthermore, the prompt includes (1) analyzing the member's biometric-related data D1 in accordance with the analysis logic information, (2) analyzing the member's mind-related data D2 in accordance with the analysis logic information, (3) integrating the analysis results of the biometric-related data D1 and the analysis results of the mind-related data D2 in accordance with the integration rules, (4) aggregating and analyzing the integrated analysis results in accordance with the aggregation analysis rules, (5) referring to the action plan selection rules, selecting as a personal action plan a candidate action plan associated with the analysis results obtained in accordance with the aggregation analysis rules, (6) obtaining the specific contents of the selected personal action plan from the group of personal plan candidates, and (7) generating image information of the personal action plan in accordance with a predetermined format.

[0244] In the second and third examples, for example, the analysis unit 112 may execute processing corresponding to prompts (1) to (4), and the generation unit 113 may input the execution results (analysis results) to the LLM, causing the LLM to execute processing of prompts (5) to (7).

[0245] For example, the information processing device 100 (generation unit 113) inputs a prompt and reference data (context data) to the LLM to generate the organization assessment report 500 or the organization root cause map MP1.

[0246] In this case, as a fourth example, the reference data includes the analysis results of the biometric data D1 of multiple members (scoring results, organizational state evaluation results), the analysis results of the mind-related data D2 of multiple members (scoring results, organizational state evaluation results), the results of an integrated analysis of the biometric data D1 and mind-related data for multiple members (integrated score, organizational state evaluation results), and information on the visualization format (display format) of the analysis results. The visualization format information is information that defines the configuration of the organization assessment report 500 or the organizational root cause map MP1, such as the type of graph and configuration format. The prompt indicates that the analysis results of the biometric data D1 and mind-related data D2 of multiple members are visualized in accordance with the visualization format information to generate image information representing the organization assessment report 500 or the organizational root cause map MP1.

[0247] In the fourth example, similarly to the first to third examples, the LLM may be made to execute the processes from analysis to generation of the tissue evaluation report 500 and the like.

[0248] Furthermore, for example, the information processing device 100 (generation unit 113) may input a prompt and reference data (context data) to the LLM to generate the personal assessment report 800 or the personal root cause map MP2. In this case, as a fifth example, the reference data includes the analysis results of the member's biometric-related data D1, the analysis results of the member's mind-related data D2, the results of an integrated analysis of the member's biometric-related data D1 and mind-related data, and information on the visualization format (display format) of the analysis results. The prompt indicates that the analysis results of the member's biometric-related data D1 and mind-related data D2 are visualized in accordance with the visualization format information to generate image information representing the personal assessment report 800 or the personal root cause map MP2. Note that in the fifth example as well, as in the first to third examples, the LLM may be caused to perform processes from analysis to generation of the personal assessment report 800, etc.

[0249] (Summary of biological data D1 and mind-related data D2) The biological-related data D1 to be analyzed by the analysis unit 112 includes biological data D121. Preferably, the biological-related data D1 includes biological data D121 and vital data D122. More preferably, the biological-related data D1 includes self-assessment data D11 and / or vital data D122 in addition to the biological data D121. Furthermore, the mind-related data D2 to be analyzed by the analysis unit 112 includes mind data D21. The mind data D21 includes thinking tendency data D211. Preferably, the mind data D21 includes thinking tendency data D211 and behavior tendency data D212. Furthermore, preferably, the mind-related data D2 includes mind data D21 and interview data D22.

[0250] (Variation) A modified example of this embodiment will be described with reference to FIG. 4. In the above embodiment, the focus is on the organization, and an organizational action plan PL1 and the like are generated. However, in a modified example, the focus is on the individual, and an individual action plan PL2 is generated. In the modified example, an individual assessment report 800 and / or an individual root cause map MP2 may be generated. In the modified example, the organizational action plan PL1, the organizational assessment report 500, and the organizational root cause map MP1 are not generated.

[0251] In a modified example, the analysis unit 112 evaluates the subject's condition by analyzing at least the bio-related data D1. Preferably, the analysis unit 112 evaluates the subject's condition by analyzing the bio-related data D1 and the mind-related data D2. More preferably, the analysis unit 112 evaluates the subject's condition by comprehensively analyzing the bio-related data D1 and the mind-related data D2. The subject is an example of an "individual."

[0252] The generation unit 113 generates an individual action plan PL2 for solving the subject's problems based on the evaluation results of the subject's condition. The generation unit 113 may also generate an individual assessment report 800 and / or an individual root cause map MP2 based on the analysis results of the biological-related data D1, the analysis results of the mind-related data D2, the integrated analysis results of the biological-related data D1 and the mind-related data D2, and / or the evaluation results of the subject's condition.

[0253] The contents of the biological-related data D1 and mind-related data D2 analyzed by the analysis unit 112 are as described with reference to Fig. 3. In addition, in the description of the above embodiment, by replacing "member" with "subject (individual)", the description can be changed to that of the modified example, except for the part related to the organization. For example, the processing according to the flowchart in Fig. 23 can be similarly implemented in the modified example.

[0254] In the modified example, as in the above embodiment, both biological-related data D1, including biological data D121, which is biochemical data, and mind-related data D2, including mind data D21 based on psychological factors, are analyzed. Therefore, the mind data D21 complements psychological factors that cannot be fully captured by the biological data D121 alone, while the biological data D121 complements medical validity that cannot be obtained by the mind data D21 alone. This synergistic effect further improves the accuracy of the subject's condition assessment, allowing for the generation of an effective individual action plan PL2 personalized for the subject. In other words, the modified example improves the accuracy of the individual condition assessment, allowing for the generation of an effective individual action plan PL2 for resolving the individual's issues. Additionally, the modified example has the same effects as those related to members in the above embodiment.

[0255] Although the preferred embodiments and modifications of the present disclosure have been described in detail above with reference to the accompanying drawings, the technical scope of the present disclosure is not limited to such examples. It is clear that a person skilled in the art of the present disclosure can conceive of various modified or altered examples within the scope of the technical idea described in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0256] Furthermore, the devices or systems described in this specification may be realized as a single device, or may be realized by multiple devices (e.g., cloud servers) some or all of which are connected via a network.

[0257] Furthermore, the series of processes performed by the devices described in this specification may be realized using any of software, hardware, and a combination of software and hardware.

[0258] Furthermore, the processes described herein using flowchart diagrams need not necessarily be performed in the order shown, some process steps may be performed in parallel, additional process steps may be employed, and some process steps may be omitted.

[0259] Furthermore, the effects described herein are merely descriptive or exemplary and are not limiting. That is, the technology according to the present disclosure may achieve other effects in addition to or in place of the above-described effects that would be apparent to a person skilled in the art from the description of this specification.

[0260] The following configurations also fall within the technical scope of the present disclosure.

[0261] (Item 1) an analysis unit that evaluates the state of an organization by analyzing biometric data of at least a plurality of members belonging to the organization; a generation unit that generates a first action plan for solving the problem of the organization based on the evaluation result of the state of the organization, An information processing device, wherein the biological-related data includes biological data indicating biological information extracted from a biological sample of the member.

[0262] (Item 2) the analysis unit evaluates the state of the organization by analyzing the biological-related data and mind-related data of the plurality of members; the mind-related data includes mind data; The information processing device described in Item 1, wherein the mind data includes at least one of thinking tendency data indicating thinking tendencies based on the cognitive functions of the member, and behavioral tendency data indicating behavioral tendencies based on psychological or mental factors of the member.

[0263] (Item 3) Item 3. The information processing device according to item 2, wherein the analysis unit evaluates the state of the organization by comprehensively analyzing the biological-related data and the mind-related data for the plurality of members.

[0264] (Item 4) The analysis unit calculating an integrated score for each member based on the scores of the evaluation items of the biological-related data and the scores of the evaluation items of the mind-related data; 4. The information processing device according to item 3, wherein the integrated scores for the plurality of members are tallied and the state of the organization is evaluated based on the tallied results.

[0265] (Item 5) the generation unit generates the first action plan in accordance with first action plan selection information; the first action plan selection information includes information associating a plurality of pieces of organizational state information with a plurality of action plan candidates, 3. The information processing device according to claim 1, wherein the generation unit refers to the first action plan selection information, acquires the candidate action plan associated with the organizational state information corresponding to the evaluation result of the state of the organization, and adopts the acquired candidate action plan as the first action plan.

[0266] (Item 6) the biometric data includes self-assessment data based on input from the member; The self-assessment data includes scores for each of a plurality of assessment items for identifying the cause of symptoms appearing in a human from a biochemical perspective, 3. The information processing device according to item 1 or 2, wherein the biological data includes the biological information related to the evaluation item.

[0267] (Item 7) 3. The information processing device according to item 1 or 2, wherein the biological-related data includes vital data indicating a vital sign of the member.

[0268] (Item 8) The thought tendency data includes scores for each of a plurality of evaluation items for identifying the thought tendency based on the cognitive function of the member, 4. The information processing device according to item 2 or 3, wherein the score is based on an input from the member.

[0269] (Item 9) The behavioral tendency data includes scores for each of a plurality of evaluation items for identifying a behavioral tendency based on psychological factors or mental factors of the member, 4. The information processing device according to item 2 or 3, wherein the score is based on an input from the member.

[0270] (Item 10) The mind-related data includes interview data; The information processing device described in item 2 or item 3, wherein the interview data indicates the results of an interview between an expert regarding the evaluation of human thinking tendencies and / or behavioral tendencies and the member, and includes scores for each of a plurality of evaluation items for evaluating the thinking tendencies and / or behavioral tendencies of the member.

[0271] (Item 11) The analysis unit identifies the cause of the organizational problem by analyzing at least the mind-related data, and estimates an error event that may occur in the organization based on the result of identifying the cause; Item 2 or Item 3. The information processing device according to item 2 or 3, further comprising an output control unit that generates image information showing the identification result of the cause, the estimation result of the error event, and issues of the organization, and displays the image information on a terminal of the organization.

[0272] (Item 12) Item 4. The information processing device according to item 2 or 3, wherein the generation unit generates a basis for the first action plan based on an analysis result of the biological-related data and the mind-related data.

[0273] (Item 13) The information processing device described in item 1 or 2, wherein the first action plan includes, depending on the evaluation results of the state of the organization, one or more of coaching information for resolving issues related to turnover rate, coaching information for resolving issues related to employees on leave, coaching information for resolving issues related to human resources, coaching information for resolving issues related to organizational culture, and coaching information for resolving issues related to sales.

[0274] (Item 14) the analysis unit analyzes the biological-related data and the mind-related data for each of the members to evaluate the state of the members; Item 4. The information processing device according to item 2 or 3, wherein the generation unit generates, for each of the members, a second action plan for solving the problem of the members based on the evaluation result of the status of the members.

[0275] (Item 15) Item 15. The information processing device according to item 14, wherein the generation unit generates the second action plan based on the evaluation result of the member's condition and input information input via a doctor's terminal.

[0276] (Item 16) the generation unit generates the second action plan in accordance with second action plan selection information; the second action plan selection information includes information associating a plurality of pieces of personal condition information with a plurality of action plan candidates, The information processing device described in item 14, wherein the generation unit refers to the second action plan selection information to obtain the candidate action plan associated with the personal status information corresponding to the evaluation result of the member's status, and adopts the obtained candidate action plan as the second action plan.

[0277] (Item 17) A step in which a computer evaluates the state of an organization by analyzing at least biological-related data of a plurality of members belonging to the organization; generating, by the computer, a first action plan for solving the organizational problem based on the assessment result of the organizational state; An information processing method, wherein the biological-related data includes biological data indicating biological information extracted from a biological sample of the member.

[0278] (Item 18) On the computer, Evaluating the state of an organization by analyzing at least biometric data of a plurality of members belonging to the organization; generating a first action plan for solving the organizational problem based on the assessment result of the organizational state; The program, wherein the biological-related data includes biological data indicating biological information extracted from a biological sample of the member. [Explanation of symbols]

[0279] 100 information processing device, 111 acquisition unit, 112 analysis unit, 113 generation unit, 114 output control unit, T1 organization terminal, T2 member terminal, T3 doctor terminal, T4 health coach terminal, T5 mind coach terminal

Claims

1. an analysis unit that evaluates the state of an organization by analyzing bio-related data and mind-related data of a plurality of members belonging to the organization; a generation unit that generates a first action plan for solving the problem of the organization based on the evaluation result of the state of the organization, the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, the generation unit generates the first action plan in accordance with first action plan selection information; the first action plan selection information includes information associating a plurality of pieces of organizational state information with a plurality of action plan candidates, The generation unit refers to the first action plan selection information to obtain the candidate action plan associated with the organizational state information corresponding to the evaluation result of the state of the organization, and adopts the obtained candidate action plan as the first action plan.

2. The information processing device according to claim 1 , wherein the analysis unit evaluates the state of the organization by comprehensively analyzing the biological-related data and the mind-related data for the plurality of members.

3. The analysis unit calculating an integrated score for each member based on the scores of the evaluation items of the biological-related data and the scores of the evaluation items of the mind-related data; The information processing device according to claim 2 , wherein the integrated scores for the plurality of members are tallied, and the state of the organization is evaluated based on the tallied results.

4. the biometric data includes self-assessment data based on input from the member; The self-assessment data includes scores for each of a plurality of assessment items for identifying the cause of symptoms appearing in a human from a biochemical perspective, The information processing device according to claim 1 , wherein the biological data includes the biological information related to the evaluation item.

5. The information processing device according to claim 1 , wherein the biological data includes vital data indicating a vital sign of the member.

6. The thought tendency data includes scores for each of a plurality of evaluation items for identifying the thought tendency based on the cognitive function of the member, The information processing device according to claim 1 or 2, wherein the score is based on an input from the member.

7. The behavioral tendency data includes scores for each of a plurality of evaluation items for identifying a behavioral tendency based on psychological factors or mental factors of the member, The information processing device according to claim 1 or 2, wherein the score is based on an input from the member.

8. The information processing device according to claim 1 , wherein the generating unit generates the basis for the first action plan based on an analysis result of the biological-related data and the mind-related data.

9. 3. The information processing device according to claim 1, wherein the first action plan includes, depending on the evaluation results of the state of the organization, one or more of the following information: coaching information for resolving issues related to turnover rate, coaching information for resolving issues related to employees on leave, coaching information for resolving issues related to human resources, coaching information for resolving issues related to organizational culture, and coaching information for resolving issues related to sales.

10. the analysis unit analyzes the biological-related data and the mind-related data for each of the members to evaluate the state of the members; The information processing device according to claim 1 , wherein the generation unit generates, for each of the members, a second action plan for solving the problem of the member based on the evaluation result of the state of the member.

11. The information processing device according to claim 10 , wherein the generation unit generates the second action plan based on the evaluation result of the member's condition and input information input via a doctor's terminal.

12. An analysis unit that evaluates the state of an organization by analyzing bio-related data and mind-related data of multiple members belonging to the organization; a generation unit that generates a first action plan for solving the problem of the organization based on the evaluation result of the state of the organization, the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; The mind-related data includes mind data and interview data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, The interview data indicates the results of an interview between an expert and the member regarding the evaluation of human thinking tendencies and / or behavioral tendencies, and includes scores for each of a plurality of evaluation items for evaluating the member's thinking tendencies and / or behavioral tendencies.

13. An analysis unit that evaluates the state of an organization by analyzing bio-related data and mind-related data of multiple members belonging to the organization; a generation unit that generates a first action plan for solving the problem of the organization based on the evaluation result of the state of the organization, the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, the analysis unit identifies a cause of the organizational problem by analyzing the mind-related data and the biological-related data, and estimates an error event that may occur in the organization based on the result of the cause identification; The information processing device further comprises an output control unit that generates image information showing the cause identification result, the error event estimation result, and issues of the organization, and displays the image information on a terminal of the organization.

14. An analysis unit that evaluates the state of an organization by analyzing bio-related data and mind-related data of multiple members belonging to the organization; a generation unit that generates a first action plan for solving the problem of the organization based on the evaluation result of the state of the organization, the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, the analysis unit analyzes the biological-related data and the mind-related data for each of the members to evaluate the state of the members; the generation unit generates, for each of the members, a second action plan for solving the problem of the member based on the evaluation result of the state of the member; When generating the second action plan, the generation unit generates the second action plan in accordance with second action plan selection information; the second action plan selection information includes information associating a plurality of pieces of personal condition information with a plurality of action plan candidates, The generation unit refers to the second action plan selection information to obtain the candidate action plan associated with the personal status information corresponding to the evaluation result of the member's status, and adopts the obtained candidate action plan as the second action plan.

15. A step in which a computer evaluates the state of an organization by analyzing biometric data and mind-related data of multiple members belonging to the organization; generating, by the computer, a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, In the step of generating the first action plan, the first action plan is generated according to first action plan selection information; the first action plan selection information includes information associating a plurality of pieces of organizational state information with a plurality of action plan candidates, In the step of generating the first action plan, the first action plan selection information is referenced to obtain the candidate action plan associated with the organizational state information corresponding to the evaluation result of the state of the organization, and the obtained candidate action plan is adopted as the first action plan.

16. A method of evaluating the state of an organization by a computer analyzing bio-related data and mind-related data of multiple members belonging to the organization; generating, by the computer, a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; The mind-related data includes mind data and interview data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, An information processing method in which the interview data indicates the results of an interview between an expert and the member regarding the evaluation of human thinking tendencies and / or behavioral tendencies, and includes scores for each of a plurality of evaluation items for evaluating the member's thinking tendencies and / or behavioral tendencies.

17. A method of evaluating the state of an organization by analyzing bio-related data and mind-related data of multiple members of the organization by a computer; generating, by the computer, a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, The computer Identifying the cause of the organizational issue by analyzing the mind-related data and the biological-related data, and estimating an error event that may occur in the organization based on the result of identifying the cause; An information processing method that generates image information showing the results of identifying the cause and the results of estimating the error event, as well as issues of the organization, and displays the image information on a terminal of the organization.

18. A method of evaluating the state of an organization by analyzing bio-related data and mind-related data of multiple members of the organization by a computer; generating, by the computer, a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, a step in which the computer analyzes the biological-related data and the mind-related data for each of the members to evaluate the state of the members; The method further includes a step in which the computer generates, for each of the members, a second action plan for solving the problem of the members based on the evaluation result of the status of the members, In the step of generating the second action plan, the second action plan is generated in accordance with second action plan selection information; the second action plan selection information includes information associating a plurality of pieces of personal condition information with a plurality of action plan candidates, In the step of generating the second action plan, the second action plan selection information is referenced to obtain the candidate action plan associated with the personal status information corresponding to the evaluation result of the member's status, and the obtained candidate action plan is adopted as the second action plan.

19. On the computer, assessing the state of an organization by analyzing biometric and mind-related data of a plurality of members belonging to the organization; generating a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, In the step of generating the first action plan, the first action plan is generated according to first action plan selection information; the first action plan selection information includes information associating a plurality of pieces of organizational state information with a plurality of action plan candidates, In the step of generating the first action plan, the program refers to the first action plan selection information to obtain the candidate action plan associated with the organizational state information corresponding to the evaluation result of the state of the organization, and adopts the obtained candidate action plan as the first action plan.

20. A computer comprising: assessing the state of an organization by analyzing biometric and mind-related data of a plurality of members belonging to the organization; generating a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; The mind-related data includes mind data and interview data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, A program in which the interview data indicates the results of an interview between an expert and the member regarding the evaluation of human thinking tendencies and / or behavioral tendencies, and includes scores for each of a plurality of evaluation items for evaluating the member's thinking tendencies and / or behavioral tendencies.

21. A computer comprising: assessing the state of an organization by analyzing biometric and mind-related data of a plurality of members belonging to the organization; generating a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, The computer, Identifying the cause of the organizational problem by analyzing the mind-related data and the biological-related data, and estimating an error event that may occur in the organization based on the result of the cause identification; a program that generates image information showing the results of identifying the cause and the results of estimating the error event, as well as issues of the organization, and displays the image information on a terminal of the organization.

22. A computer comprising: assessing the state of an organization by analyzing biometric and mind-related data of a plurality of members belonging to the organization; generating a first action plan for solving the organizational problem based on the assessment result of the organizational state; the biological-related data includes biological data indicating biological information extracted from a biological sample of the member; the mind-related data includes mind data; The mind data includes at least one of thought tendency data indicating a thought tendency based on the cognitive function of the member and behavior tendency data indicating a behavior tendency based on psychological or mental factors of the member, The computer, evaluating the condition of each of the members by analyzing the biological-related data and the mind-related data; and generating, for each of the members, a second action plan for solving the problem of the member based on the evaluation result of the member's state; In the step of generating the second action plan, the second action plan is generated in accordance with second action plan selection information; the second action plan selection information includes information associating a plurality of pieces of personal condition information with a plurality of action plan candidates, In the step of generating the second action plan, the program refers to the second action plan selection information to obtain the candidate action plan associated with the personal status information corresponding to the evaluation result of the member's status, and adopts the obtained candidate action plan as the second action plan.

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