Psychological safety estimation device

Abstract

In the present invention, a satisfaction level collection unit collects information about the satisfaction levels of members belonging to an organization using each method of a plurality of methods having different degrees of psychological safety impact. An information management unit manages organizational information about the organization and attribute data of the members thereof. A psychological safety estimation unit estimates information about psychological safety corresponding to the satisfaction levels for each attribute using information about a plurality of satisfaction levels collected by the satisfaction level collection unit and attribute data acquired from the information management unit.

Description

Psychological safety estimation device

[0001] The present invention relates to a psychological safety estimation device.

[0002] In recent years, there has been a demand for technological developments to measure the state of environments (places) such as the workplace, with the aim of improving the well-being of individuals and society (see, for example, Non-Patent Document 1). For example, technologies have been proposed for estimating psychological safety, which indicates a state in which people can safely express their opinions in an organizational environment. Such technologies for estimating psychological safety include those that use self-reported information (personal reports) and those that objectively estimate psychological safety based on detection by vital signs sensors or daily behavioral information.

[0003] Yukiko Uchida, "The state of the space that supports individual optimization: Toward co-creative well-being between individuals and spaces," FY2021 JST Future Society Creation Program "Realizing a society optimized for individuals" selected project [online], [Retrieved July 10, 2024], Internet <URL: https: / / www.jst.go.jp / mirai / jp / uploads / 004_event-221107.pdf>

[0004] However, there is room for improvement in the conventional technology. For example, with a method with low anonymity, such as self-reporting, detailed information can be collected on an individual or department basis, allowing for appropriate measures, but the content of the report may be highly dependent on the psychological safety of the organization. On the other hand, objective estimation methods using vital signs detection or daily behavioral information, etc., are thought to be less affected by psychological safety than self-reporting, but the information that can be obtained is more limited than self-reporting, making it difficult to improve accuracy. As such, both methods have issues, and there is room for improvement in the conventional technology, for example, in estimating information related to psychological safety. Therefore, there is a need for a method to appropriately estimate information related to psychological safety.

[0005] The present invention has been made in view of the above, and aims to appropriately estimate information regarding psychological safety.

[0006] In order to solve the above-mentioned problems and achieve the objectives, the psychological safety estimation device of the present invention is characterized by having a satisfaction collection unit that uses multiple methods each having a different degree of impact on psychological safety to collect information regarding the satisfaction of members belonging to an organization using each method, an information management unit that manages organizational information about the organization and attribute data of the members, and a psychological safety estimation unit that uses information regarding the multiple satisfaction levels collected by the satisfaction collection unit and the attribute data obtained from the information management unit to estimate information regarding psychological safety relative to satisfaction for each attribute.

[0007] According to the present invention, it is possible to appropriately estimate information regarding psychological safety.

[0008] FIG. 1 is a diagram showing an example of an outline of the processing of a psychological safety estimation system. FIG. 2 is a diagram showing an example of the configuration of a psychological safety estimation system according to an embodiment. FIG. 3 is a diagram showing an example of the configuration of a psychological safety estimation device according to an embodiment. FIG. 4 is a diagram showing an example of an analysis of influence attributes of psychological safety. FIG. 5 is a diagram showing an example of an analysis of influence factors. FIG. 6 is a diagram showing an example of a case where psychological safety is high. FIG. 7 is a diagram showing an example of questionnaire items. FIG. 8 is a flowchart showing an example of a processing procedure executed by a psychological safety estimation system. FIG. 9 is a diagram showing an example of a computer that executes an information processing program. FIG. 10 is a diagram showing an example of a problem in the prior art.

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. In addition, in the description of the drawings, the same parts are designated by the same reference numerals.

[0010] [Embodiment] [Overview] First, before describing the information processing executed by the psychological safety estimation system 1 (see FIG. 2 ) according to the embodiment, an overview and problems of existing technologies will be briefly described. Measurement results of employee satisfaction and well-being, etc., change depending on psychological safety.

[0011] For example, as shown in Fig. 10, information regarding employee satisfaction can be collected by various methods such as the following. Fig. 10 is a diagram showing an example of a problem in the prior art. Fig. 10 shows a case where information is collected using a terminal device DV and a sensor device SN for self-reporting about an employee EM, who is an example of a member whose employee satisfaction is to be estimated. Fig. 10 shows a case where the employee EM is an employee (staff member) of a company with low psychological safety, which is an example of an organization.

[0012] As shown in Figure 10, in self-reporting with low anonymity, such as in a questionnaire with low anonymity where the respondent can be identified, there is a possibility that the respondent will make a false report due to psychological safety. Therefore, in self-reporting with low anonymity, although the subjective data contains a large amount of information, psychological safety influences the results, and the degree of influence of psychological safety is large.

[0013] Furthermore, in the case of highly anonymous self-reports where individuals cannot be identified, psychological safety is relatively high, but it is difficult to detail attributes due to anonymity. Therefore, in highly anonymous self-reports, the impact of psychological safety is not large, and although the impact of psychological safety is moderate, the scope of its use is limited due to anonymity. On the other hand, there is a problem in that detailing attributes reduces anonymity, which reduces psychological safety.

[0014] Furthermore, methods using sensors, etc. (also known as "other-evaluation") are less affected by psychological safety, but their accuracy and amount of information are lower than subjective data. Therefore, evaluations by others using inferences using sensors or text mining are less affected by psychological safety, but are inferior to other methods in terms of accuracy and amount of information.

[0015] In organizations with low psychological safety, it is difficult to effectively utilize information at the individual or department level. Therefore, it is desirable to estimate information about psychological safety in an organization, and in this regard, existing technologies have room for improvement. Therefore, the psychological safety estimation system 1 performs the following process to appropriately estimate information about psychological safety.

[0016] The psychological safety estimation system 1 estimates information about psychological safety using information about the satisfaction of members belonging to an organization collected using multiple methods that have different degrees of impact on psychological safety. For example, the psychological safety estimation system 1 estimates information about psychological safety through the process shown in Fig. 1. Fig. 1 is a diagram showing an example of an outline of the process of the psychological safety estimation system.

[0017] In the following, an employee is used as an example of a member, and a company to which the employee belongs is used as an example of an organization. However, the organization is not limited to a company and may be any organization that includes multiple members, and the member is not limited to an employee but may be any person who belongs to an organization. In other words, a company may be read as an organization, and an employee may be read as a member. In the following, employee satisfaction is used as an example of satisfaction, but satisfaction may be any indicator related to members of an organization, such as various indicators of well-being.

[0018] 1, the psychological safety estimation system 1 collects information on employee satisfaction using a questionnaire with low anonymity, such as the self-reported data DT1. In this way, employee satisfaction can be acquired (measured) using a method that may be influenced by psychological safety, such as the self-reported data DT1.

[0019] 1, in the self-reported data DT1 with low anonymity, an employee (e.g., Employee D) who belongs to an organization with low psychological safety answers questions #1 and #2, which are questions that are highly influenced by psychological safety, with a maximum score of 5. However, if the answers were given under a highly anonymous environment, the employee (e.g., Employee D) might give question #1 a score of 2 and question #2 a score of 1. In this way, differences in the information obtained due to the influence of psychological safety can occur.

[0020] The psychological safety estimation system 1 estimates the employee satisfaction level of each employee using the survey results of each employee obtained from self-reported data DT1, etc. The psychological safety estimation system 1 estimates the employee satisfaction level of each employee using data that is influenced by psychological safety from the survey results of each employee. In FIG. 1 , the psychological safety estimation system 1 estimates the employee satisfaction level of each employee using each employee's answers (survey results) to questions #1 and #2, which are questions that are highly influenced by psychological safety, from the self-reported data DT1.

[0021] 1, the employee's responses to questions #1 and #2, which are questions that have a high degree of impact on psychological safety, are used in the estimation process. Note that the above is just one example, and the psychological safety estimation system 1 may also use the employee's responses to questions other than questions #1 and #2 in the estimation process.

[0022] The psychological safety estimation system 1 converts the survey results of each employee, obtained from the self-reported data DT1, etc., into an employee satisfaction level (numerical value) for each employee. In FIG. 1 , the psychological safety estimation system 1 converts each employee's responses to Questions #1 and #2, obtained from the self-reported data DT1, etc., into a scalar value indicating each employee's employee satisfaction level. For example, the psychological safety estimation system 1 may estimate (generate) each employee's employee satisfaction level using a function that calculates the employee satisfaction level for each employee, using the employee's self-reported data as a variable (input).

[0023] The above is merely an example, and the psychological safety estimation system 1 may estimate employee satisfaction using various information as long as it is possible to estimate employee satisfaction. For example, the psychological safety estimation system 1 may calculate the average score of each employee's answers to Questions #1 and #2 as the employee satisfaction level for each employee. Furthermore, the scalar value is merely an example, and employee satisfaction may be a multidimensional vector, etc.

[0024] In FIG. 1 , the psychological safety estimation system 1 estimates employee satisfaction for four employees belonging to Department #1 of Corporate CM: Director A, Section Manager B, Employee C, and Employee D, as indicated by the dots and dashed line in the satisfaction graph LS1. In this way, the psychological safety estimation system 1 estimates satisfaction information that is highly influenced by psychological safety using self-reported data with low anonymity. The satisfaction graph LS1 shows employee satisfaction estimated using a questionnaire with low anonymity. In this way, the satisfaction graph LS1 shows the results of a measurement method that is highly influenced by psychological safety. For example, since a method using a questionnaire with low anonymity is highly influenced by psychological safety, when belonging to an organization with low psychological safety, employees with attributes that are highly influenced by psychological safety (e.g., Employee C, Employee D, etc.) are likely to respond to the questionnaire with a higher evaluation than they actually are, out of concern for the eyes (monitoring) of others, such as their superiors.

[0025] 1, the psychological safety estimation system 1 collects information on employee satisfaction through estimation using sensors and text mining, as shown in the other-person evaluation data DT2. In this way, employee satisfaction is acquired (measured) using a method that is less affected by psychological safety, such as the other-person evaluation data DT2.

[0026] The psychological safety estimation system 1 estimates the employee satisfaction level of each employee using information about the employee's satisfaction level obtained from the other-evaluation data DT2, etc. For example, the psychological safety estimation system 1 estimates the employee satisfaction level of each employee using vital data obtained by a sensor for each employee. Note that the above is merely an example, and the psychological safety estimation system 1 may use various other-evaluation data in its estimation process, not limited to vital data; this point will be discussed later.

[0027] The psychological safety estimation system 1 converts vital data of each employee obtained from the other-evaluation data DT2, etc., into employee satisfaction (numerical values) for each employee. In FIG. 1 , the psychological safety estimation system 1 converts vital values ​​(e.g., heart rate, etc.) of each employee obtained from the other-evaluation data DT2, etc., into scalar values ​​indicating the employee satisfaction of each employee. For example, the psychological safety estimation system 1 may estimate (generate) the employee satisfaction of each employee using a function that calculates the employee satisfaction of the employee using the employee's vital values ​​as variables (inputs).

[0028] Note that the above is merely an example, and the psychological safety estimation system 1 may estimate employee satisfaction using various information as long as it is possible to estimate employee satisfaction. For example, measurement based on evaluations by others using such other-evaluation data DT2 mainly utilizes existing technology, and various techniques may be used, such as a method of estimating satisfaction (happiness) from heart rate data from a smartwatch or a method of estimating well-being from text data such as a daily report. Furthermore, the scalar value is merely an example, and employee satisfaction may be a multidimensional vector, etc.

[0029] In FIG. 1 , the psychological safety estimation system 1 estimates employee satisfaction for four employees belonging to Department #1 of Corporate Commercial Management: Director A, Section Manager B, Employee C, and Employee D, as indicated by the dots and two-dot chain line on the satisfaction graph LS2. In this way, the psychological safety estimation system 1 estimates satisfaction information with a low influence of psychological safety using highly anonymous third-party evaluation data. The satisfaction graph LS2 shows employee satisfaction estimated using highly anonymous third-party evaluation data. In this way, the satisfaction graph LS2 shows the results of a measurement method with a low influence of psychological safety. For example, because the method using third-party evaluation data is a method with a low influence of psychological safety, when employees belong to an organization with a low level of psychological safety, the results obtained for employees with attributes that are highly influenced by psychological safety (e.g., Employee C, Employee D, etc.) may differ significantly from the results obtained using a less anonymous method.

[0030] In FIG. 1 , the psychological safety estimation system 1 estimates information about psychological safety using information such as that shown in a satisfaction graph LS11, which includes information from both a satisfaction graph LS1 and a satisfaction graph LS2. The psychological safety estimation system 1 estimates information about psychological safety with respect to satisfaction for each attribute using attribute data for attributes in an organization. In FIG. 1 , the psychological safety estimation system 1 estimates information about psychological safety with respect to satisfaction for each of two attributes: a group of employees with managerial attributes and a group of employees with non-managerial attributes in a company. In FIG. 1 , the psychological safety estimation system 1 estimates information about psychological safety with respect to satisfaction for each of a managerial group AT11, which is a group of employees corresponding to managers A and section chief B, and a non-managerial group AT12, which is a group of employees corresponding to non-managerial employees C and D.

[0031] For example, the psychological safety estimation system 1 estimates information about psychological safety on satisfaction based on the difference for each attribute between satisfaction information with a low influence of psychological safety and satisfaction information with a high influence of psychological safety. In Figure 1, for the manager group AT11, the difference between satisfaction based on self-reported data (also referred to as "first satisfaction level") and satisfaction based on other-assessment data (also referred to as "second satisfaction level") is small, so the psychological safety estimation system 1 estimates that the degree of influence of psychological safety on satisfaction is small for the employee group with the manager attribute in the corporate CM (department #1).

[0032] In Figure 1, the psychological safety estimation system 1 estimates that for the non-manager group AT12, there is a large difference between the satisfaction level based on self-reported data (first satisfaction level) and the satisfaction level based on other-assessment data (second satisfaction level), and therefore estimates that the group of employees with non-managerial attributes in the corporate CM (department #1) are greatly influenced by psychological safety on their satisfaction level.

[0033] The above is merely an example, and the psychological safety estimation system 1 may use various information to estimate information related to psychological safety. For example, the psychological safety estimation system 1 may estimate attributes that influence psychological safety based on the relationships between attributes and changes in psychological safety; this will be discussed later.

[0034] As described above, for example, psychological safety estimation system 1 estimates information related to psychological safety using self-reported data that is influenced by psychological safety and other-assessment data that has a relatively low influence but contains little information. Note that the self-reported data and other-assessment data are not limited to those shown in FIG. 1 , and various information that can be used for processing may be used.

[0035] For example, self-reported data may be responses to a non-anonymous survey that can be viewed by the respondent's superior, text information from an internal collaboration tool, etc. Furthermore, other-evaluation data may be responses to an anonymous survey, sensor data obtained by sensors such as vital signs sensors and web cameras, etc. Furthermore, other-evaluation data may be information acquired by various sensors (sensing devices) such as wearable devices, cameras on personal computers (PCs), and office cameras, or may be text information (e.g., work reports) entered by employees on a daily basis. While such other-evaluation data is less affected by psychological safety, the types of information that can be estimated and the accuracy are limited compared to self-reported data, and the accuracy is often somewhat lower on an individual basis.

[0036] As described above, the psychological safety estimation system 1 converts self-reported data and other-assessment data into numerical values ​​on a uniform scale and statistically analyzes the differences on a group-by-group basis to analyze the degree of influence and factors of psychological safety. For example, if data acquired using multiple methods with different degrees of psychological safety influence are converted into numerical values ​​on a uniform scale, it is expected that the greater the influence of psychological safety, the greater the difference will be. In other words, psychological safety will produce differences in the results.

[0037] Therefore, the psychological safety estimation system 1 can estimate the impact of psychological safety by converting data acquired using multiple methods with different degrees of psychological safety into numerical values ​​on a uniform scale and using the converted numerical values. Note that because the acquired information may contain noise, clusters with statistical differences are extracted from the difference between self-reported employee satisfaction and employee satisfaction based on others' ratings in the group, and the main factors are analyzed.

[0038] In this way, the psychological safety estimation system 1 can eliminate noise due to individual differences by performing analysis on a group basis, such as by attribute. In the example of Figure 1, the psychological safety estimation system 1 can obtain, through analysis processing, an analysis result that indicates that non-managerial employees have low levels of satisfaction, but that psychological safety is low and employees are unable to speak their true feelings. Therefore, the psychological safety estimation system 1 can appropriately estimate information related to psychological safety.

[0039] [Configuration of the Psychological Safety Estimation System] An example of a psychological safety estimation system 1 that executes the above-described information processing will now be described with reference to Fig. 2. Fig. 2 is a diagram showing an example configuration of a psychological safety estimation system according to an embodiment. Note that the system configuration shown in Fig. 2 is merely an example, and the psychological safety estimation system 1 can adopt any device configuration as long as it is capable of executing the desired processing. Furthermore, processing described as being performed by the psychological safety estimation system 1 may be performed by any device capable of executing that processing, such as the psychological safety estimation device 100, depending on the device configuration of the psychological safety estimation system 1.

[0040] As shown in Fig. 2, the psychological safety estimation system 1 includes a terminal device 10 and a psychological safety estimation device 100. The psychological safety estimation device 100 is connected to the terminal device 10 via a predetermined network N so as to be able to communicate with the terminal device 10 via a wired or wireless connection. Fig. 2 is a diagram showing an example configuration of a psychological safety estimation system according to an embodiment. Note that the psychological safety estimation system 1 shown in Fig. 2 may include multiple terminal devices 10 and multiple psychological safety estimation devices 100.

[0041] The terminal device 10 is an information processing device (computer) used to collect information used for processing by the psychological safety estimation device 100. For example, the terminal device 10 may be a device used by employees to input self-reported data such as turnover in a questionnaire. For example, the terminal device 10 may be a smartphone, a tablet terminal, a laptop PC, or the like.

[0042] The terminal device 10 may also be a device having a sensor that detects vital data (biological information) such as the user's heart rate. For example, the terminal device 10 is not limited to the above, and may also be a wearable device such as a smart watch. Note that the vital data is not limited to the heart rate, and may be any vital data such as brain waves, pulse, odor, or sweat. The terminal device 10 may also have a sensor that detects any vital data used for processing by the psychological safety estimation device 100.

[0043] The terminal device 10 transmits information to the psychological safety estimation device 100. The terminal device 10 transmits collected information to the psychological safety estimation device 100. For example, the terminal device 10 transmits self-reported data entered by an employee to the psychological safety estimation device 100. For example, the terminal device 10 transmits vital data of an employee detected by a sensor to the psychological safety estimation device 100. Note that the terminal device 10 may collect various information, not limited to vital data of an employee.

[0044] For example, the terminal device 10 collects at least one of the employee's vital sign data, the employee's video data, the employee's input text, and the employee's speech information, and transmits the collected information to the psychological safety estimation device 100. For example, the terminal device 10 associates the collected information with information identifying the employee (such as an employee ID) and transmits it to the psychological safety estimation device 100.

[0045] Furthermore, the terminal device 10 may be an output device that outputs information provided by the psychological safety estimation device 100. For example, the terminal device 10 may have a display device (such as a display) that displays the information provided by the psychological safety estimation device 100, or may have an audio output device (such as a speaker) that outputs the information provided by the psychological safety estimation device 100 as audio. For example, the terminal device 10 outputs information notified by the psychological safety estimation device 100.

[0046] The psychological safety estimation device 100 is an information processing device (computer) that estimates the degree of impact of psychological safety on employee satisfaction for each attribute using information on multiple employee satisfaction levels collected using multiple methods that have different degrees of impact of psychological safety.

[0047] The psychological safety estimation device 100 receives at least one of employee vital data, employee video data, employee input text, and employee speech information as external information from a terminal device 10 used by the employee. The psychological safety estimation device 100 estimates employee satisfaction information that is less influenced by psychological safety using highly anonymous external information including at least one of employee vital data, employee video data, employee input text, and employee speech information.

[0048] The psychological safety estimation device 100 receives self-reported data, such as employee responses to employee questionnaires with low anonymity that enable at least the attributes of the respondent to be identified, from the terminal device 10 used by the employee. For example, the psychological safety estimation device 100 receives self-reported data, such as employee responses to questionnaires, along with the employee's name or information that identifies the employee (such as an employee ID), from the terminal device 10 used by the employee. The psychological safety estimation device 100 estimates employee satisfaction information that is highly influenced by psychological safety using self-reported data, such as questionnaires with low anonymity.

[0049] Note that the above is merely an example, and the psychological safety estimation system 1 may include a device (also referred to as an "administrator device") owned by a person other than an employee of an organization (such as a manager) when notifying the manager of information. In this case, the psychological safety estimation device 100 may notify the manager of information.

[0050] [Configuration of the Psychological Safety Estimation Device] Next, a description will be given of the configuration of the psychological safety estimation device 100, which is an example of a psychological safety estimation device that executes information processing according to the embodiment. Fig. 3 is a diagram illustrating an example of the configuration of the psychological safety estimation device 100 according to the embodiment.

[0051] 3, the psychological safety estimation device 100 of this embodiment is realized by a general-purpose computer such as a personal computer, and includes a communication unit 110, a storage unit 120, and a control unit 130. The psychological safety estimation device 100 may also include an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the psychological safety estimation device 100, a display unit (e.g., a liquid crystal display, etc.) that displays information, an audio output unit (e.g., a speaker, etc.) that outputs information aloud, etc.

[0052] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to a predetermined network such as the Internet via a wired or wireless connection, and transmits and receives information to and from other information processing devices such as the terminal device 10.

[0053] The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 3 , the storage unit 120 according to the embodiment includes an organization information storage unit 121, an attribute data storage unit 122, and a processing result information storage unit 123.

[0054] The storage unit 120 functions as an information management unit that manages organizational information about an organization and attribute data of its members. For example, the storage unit 120 manages organizational information including an organizational chart showing the hierarchical relationships of positions (job titles) in an organization such as a company. For example, the storage unit 120 manages employee attribute data including positions (job titles) based on the hierarchical relationships of employees in the organization such as a company.

[0055] The organizational information storage unit 121 according to the embodiment stores organizational information related to an organization. The organizational information storage unit 121 stores organizational information including an organizational chart of an organization such as a company to which multiple employees belong. For example, the organizational information storage unit 121 stores organizational information indicating the relationships between employees in an organization such as a company. For example, the organizational information storage unit 121 stores organizational information indicating the hierarchical relationships between employees in an organization such as a company. The organizational information storage unit 121 stores organizational information indicating the relationships between superiors and subordinates for each attribute in the company, etc.

[0056] The organization information storage unit 121 is not limited to the above, and may store various types of information depending on the purpose.

[0057] The attribute data storage unit 122 according to the embodiment stores information related to attributes. The attribute data storage unit 122 stores data related to each attribute in an organization. The attribute data storage unit 122 stores data related to the attributes of each employee in the organization. For example, the attribute data storage unit 122 stores information indicating the department, position, etc. to which each employee in the organization belongs as data related to attributes.

[0058] The attribute data storage unit 122 may store various types of information according to the purpose, not limited to the above. For example, the attribute data storage unit 122 may store an attribute table showing a list of employees in an organization that correspond to each attribute.

[0059] The processing result information storage unit 123 according to the embodiment stores the results of the processing. The processing result information storage unit 123 stores the results of the estimation process and the results of the analysis process. For example, the processing result information storage unit 123 stores information indicating the psychological safety of each estimated attribute. For example, the processing result information storage unit 123 stores information indicating the analysis result of the relationship between the attribute and the difference in psychological safety.

[0060] The processing result information storage unit 123 is not limited to the above, and may store various types of information depending on the purpose. For example, the processing result information storage unit 123 may store information to be notified.

[0061] Furthermore, the above is merely an example, and the storage unit 120 may store various types of information, not limited to the above. For example, the storage unit 120 may store collected information regarding employee satisfaction. The storage unit 120 stores at least one of employee vital sign data, employee video data, employee input text, and employee speech information as external information. For example, the storage unit 120 stores the external information related to an employee in association with information identifying the employee (such as an employee ID).

[0062] The storage unit 120 may store self-reported data such as employee questionnaire responses in association with information identifying the employee (such as an employee ID). For example, the storage unit 120 may store at least one of the employee's vital sign data, employee video data, employee input text, and employee speech information in association with information identifying the employee (such as an employee ID).

[0063] Returning to Figure 3 , the explanation will continue. The control unit 130 is realized, for example, by a processor such as a CPU (Central Processing Unit) executing a program (e.g., an information processing program) stored inside the psychological safety estimation device 100 using RAM or the like as a work area. The control unit 130 is also realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in Figure 3 , the control unit 130 includes an acquisition unit 131, an employee satisfaction level collection unit 132, a psychological safety estimation unit 133, and a notification unit 134.

[0064] The acquisition unit 131 executes an acquisition process to acquire information. For example, the acquisition unit 131 acquires various pieces of information from the storage unit 120. For example, the acquisition unit 131 acquires information from the organization information storage unit 121, the attribute data storage unit 122, or the processing result information storage unit 123. The acquisition unit 131 receives various pieces of information from an external information processing device such as the terminal device 10. For example, the acquisition unit 131 receives information collected by the terminal device 10 from the terminal device 10.

[0065] The employee satisfaction level collection unit 132 executes a collection process to collect information. The employee satisfaction level collection unit 132 collects information from other information processing devices such as the terminal device 10. For example, the employee satisfaction level collection unit 132 collects information by receiving information from other information processing devices such as the terminal device 10 via the communication unit 110.

[0066] The employee satisfaction level collection unit 132 functions as a satisfaction level collection unit that uses a plurality of methods each having a different degree of influence of psychological safety to collect information regarding the satisfaction of members belonging to the organization using each method. The employee satisfaction level collection unit 132 uses a plurality of methods each having a different degree of influence of psychological safety to collect information regarding the employee satisfaction of employees belonging to the organization using each method.

[0067] The employee satisfaction level collection unit 132 collects one or more of vital data, video data, input text, and speech information related to employees. The employee satisfaction level collection unit 132 collects one or more of vital data, video data, input text, and speech information related to employees. For example, the employee satisfaction level collection unit 132 collects vital data of employees.

[0068] The employee satisfaction level collection unit 132 collects self-reported data such as employee responses to questionnaires, etc. For example, the employee satisfaction level collection unit 132 collects self-reported data such as employee responses to questionnaires with low anonymity.

[0069] The psychological safety estimation unit 133 executes an estimation process to estimate information. The psychological safety estimation unit 133 functions as an estimation unit that estimates information. The psychological safety estimation unit 133 executes the estimation process based on various pieces of information stored in the storage unit 120. For example, the psychological safety estimation unit 133 executes the estimation process based on various pieces of information stored in the organization information storage unit 121, the attribute data storage unit 122, and the processing result information storage unit 123.

[0070] The psychological safety estimation unit 133 performs estimation processing based on various pieces of information acquired from an external information processing device such as the terminal device 10. The psychological safety estimation unit 133 estimates various pieces of information using the information acquired by the acquisition unit 131. The psychological safety estimation unit 133 estimates various pieces of information using the information collected by the employee satisfaction level collection unit 132.

[0071] The psychological safety estimation unit 133 generates various types of information using the estimated information. The psychological safety estimation unit 133 calculates various types of information using the estimated information. The employee satisfaction level collection unit 132 executes an analysis process using the various types of information acquired by the acquisition unit 131.

[0072] The psychological safety estimation unit 133 estimates information about psychological safety with respect to satisfaction for each attribute, using information about multiple satisfaction levels collected by the employee satisfaction level collection unit 132 and attribute data acquired from the storage unit 120. For example, the psychological safety estimation unit 133 estimates the degree of impact of psychological safety on employee satisfaction for each attribute, using information about multiple employee satisfaction levels and attribute data.

[0073] The psychological safety estimation unit 133 estimates employee satisfaction information that is less influenced by psychological safety using one or more of vital data, video data, input text, and speech information related to members. The psychological safety estimation unit 133 estimates employee satisfaction information that is more influenced by psychological safety using a questionnaire with low anonymity.

[0074] The psychological safety estimation unit 133 estimates attributes that influence psychological safety based on the relationships between each attribute indicated in the organizational information and changes in psychological safety. The psychological safety estimation unit 133 analyzes the relationship between attributes and differences in psychological safety based on the differences between each attribute between employee satisfaction information with a low influence of psychological safety and employee satisfaction information with a high influence of psychological safety.

[0075] 1 , the psychological safety estimation unit 133 compares the average value of the first satisfaction level of the manager group AT11 with the average value of the second satisfaction level of the manager group AT11, and estimates that the degree of influence of psychological safety on the satisfaction level of the attribute "manager" is small based on the comparison result. For example, the psychological safety estimation unit 133 estimates that the degree of influence of psychological safety on the satisfaction level of the attribute "manager" is small because the difference between the average value of the first satisfaction level of the manager group AT11 and the average value of the second satisfaction level of the manager group AT11 is less than a predetermined threshold.

[0076] 1 , the psychological safety estimation unit 133 compares the average value of the first satisfaction level of the non-manager group AT12 with the average value of the second satisfaction level of the non-manager group AT12, and estimates that the degree of influence of psychological safety on the satisfaction level of the attribute "non-manager" is large based on the comparison result. For example, the psychological safety estimation unit 133 estimates that the degree of influence of psychological safety on the satisfaction level of the attribute "non-manager" is large because the difference between the average value of the first satisfaction level of the non-manager group AT12 and the average value of the second satisfaction level of the non-manager group AT12 is equal to or greater than a predetermined threshold.

[0077] The notification unit 134 executes a notification process for notifying various types of information. The notification unit 134 notifies information by outputting the information to a notification destination device, which is a computer that is the notification destination. The notification unit 134 transmits the notification information to the notification destination device, such as the terminal device 10 or an administrator device.

[0078] The notification unit 134 transmits notification information including the result of the estimation process to the notification destination device via the communication unit 110. For example, the notification unit 134 controls the notification destination device to notify (output) the result of the estimation process by transmitting the notification information including the result of the estimation process to the notification destination device. For example, the notification unit 134 transmits the notification information including the result of the estimation process to the notification destination device, and causes the notification destination device to notify (output) the result of the estimation process.

[0079] [Processing Examples] Based on the above content, several processing examples will be described below. Note that the same points as those described above will not be described again.

[0080] For example, the psychological safety estimation system 1 may estimate attributes that are affected by psychological safety (also referred to as "influencing attributes"). This point will be explained using Fig. 4. Fig. 4 is a diagram showing an example of an analysis of the influencing attributes of psychological safety.

[0081] In Fig. 1, the psychological safety estimation system 1 estimates the influence attributes of psychological safety in a corporate CM using information such as that shown in satisfaction graphs LS11 and LS21. Similar to Fig. 1, satisfaction graph LS11 shows the satisfaction levels of Director A, Section Manager B, Employee C, and Employee D, who belong to Department #1 of the corporate CM. Furthermore, satisfaction graph LS21 shows the satisfaction levels of Director W, Section Manager X, Employee Y, and Employee Z, who belong to Department #2 of the corporate CM. For example, Director W and Section Manager X belong to a manager group AT21, which is a group of employees with manager attributes, and Employees Y and Z belong to a non-manager group AT22, which is a group of employees with non-manager attributes.

[0082] 4, the psychological safety estimation system 1 estimates the employee satisfaction levels of Director W, Section Manager X, Employee Y, and Employee Z in the same way as Director A, Section Manager B, Employee C, and Employee D. For example, as shown by the points and dashed-dotted line in satisfaction graph LS21, the psychological safety estimation system 1 estimates employee satisfaction levels that are highly influenced by psychological safety for four employees, Director W, Section Manager X, Employee Y, and Employee Z, who belong to Department #2 of Corporate CM, using self-reported data with low anonymity.

[0083] Furthermore, as shown by the points and two-dot chain line on satisfaction level graph LS2, psychological safety estimation system 1 estimates employee satisfaction levels with low psychological safety influence using highly anonymous evaluation data from others for four employees in Corporate CM's Department #2: Director W, Section Manager X, Employee Y, and Employee Z. Note that the information shown in satisfaction level graph LS21 is the same as the information shown in satisfaction level graph LS1, and therefore a detailed description will be omitted.

[0084] 4, the psychological safety estimation system 1 generates information such as that shown in the attribute table TB11 using information such as that shown in the satisfaction level graph LS11 and the satisfaction level graph LS21, organizational information about the corporate CM, and attribute data for each employee of the corporate CM. For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of Director A of Department #1 and the second satisfaction level of Director A of Department #1, thereby calculating the measurement result difference as "0.21" as shown in the attribute table TB11.

[0085] For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of Section Manager B of Department #1 and the second satisfaction level of Section Manager B of Department #1, thereby calculating the measurement result difference as "0.28" as shown in attribute table TB11. For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of Employee C of Department #1 and the second satisfaction level of Employee C of Department #1, thereby calculating the measurement result difference as "0.59" as shown in attribute table TB11. For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of Employee D of Department #1 and the second satisfaction level of Employee D of Department #1, thereby calculating the measurement result difference as "0.83" as shown in attribute table TB11.

[0086] For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of Department Manager W of Department #2 and the second satisfaction level of Department Manager W of Department #2, thereby calculating the measurement result difference as "0.17," as shown in attribute table TB11. For example, the psychological safety estimation system 1 calculates the difference between the first satisfaction level of each of Section Manager X, employee Y, and employee Z of Department #2 and the second satisfaction level of each of Section Manager X, employee Y, and employee Z of Department #2, thereby calculating the measurement result differences as "0.24," "0.02," and "0.30," as shown in attribute table TB11.

[0087] The psychological safety estimation system 1 estimates the influencing attributes of psychological safety using the measurement result difference and a predetermined threshold. For example, the psychological safety estimation system 1 estimates that the attributes of employees whose measurement result difference is equal to or greater than a predetermined threshold are the influencing attributes of psychological safety. In FIG. 4 , as shown by hatching in the attribute table TB11, the psychological safety estimation system 1 estimates that the influencing attributes are department #1 and non-manager, which are attributes of employees C and D whose measurement result difference is equal to or greater than the threshold "0.5." Note that 0.5 is merely an example, and the threshold is not limited to 0.5 and can be set to any value.

[0088] As shown in the analysis result RS11, the psychological safety estimation system 1 estimates the attribute "Department #1" and the attribute "Non-manager" as a combination of attributes that influence psychological safety. In this way, the psychological safety estimation system 1 creates a table of attributes and differences in employee satisfaction analyzed using multiple measurement methods, and analyzes the relationship between each attribute and the differences in employee satisfaction. For example, the psychological safety estimation system 1 may estimate an employee's psychological safety based on differences in the employee's measurement results. For example, the psychological safety estimation system 1 may estimate that the greater the difference in the employee's measurement results, the lower the employee's psychological safety. The psychological safety estimation system 1 may also perform attribute analysis using a decision tree or the like.

[0089] For example, the psychological safety estimation system 1 may estimate attributes that are influencing factors of psychological safety. This point will be explained using Fig. 5. Fig. 5 is a diagram showing an example of an analysis of influencing factors.

[0090] 5, the psychological safety estimation system 1 estimates attributes that influence psychological safety using information such as that shown in hierarchical graph GR11. In Fig. 5, the psychological safety estimation system 1 estimates that of the employees shown in hierarchical graph GR11, four employees, namely, Section Manager C, Section Manager D, Employee G, and Employee H, have attributes that influence psychological safety. For example, the psychological safety estimation system 1 estimates that Section Manager C, Section Manager D, Employee G, and Employee H are employees whose measurement result differences are equal to or greater than a predetermined threshold.

[0091] Based on the hierarchical relationships shown in hierarchical graph GR11, psychological safety estimation system 1 then estimates that department manager #2, who is the boss (immediately higher level) of section managers C and D, is an influential factor in psychological safety for the section managers. Based on the hierarchical relationships shown in hierarchical graph GR11, psychological safety estimation system 1 also estimates that section manager B, who is the boss (immediately higher level) of employees G and H, is an influential factor in psychological safety for the employees. In this way, psychological safety estimation system 1 can analyze the influential factors in reducing psychological safety by using information that graphs the relationships between attributes such as superiors and subordinates.

[0092] In the above example, we have described an organization with low psychological safety, but there are also cases where the psychological safety of an organization is high, and an example of satisfaction in this case is shown in Figure 6. Figure 6 is a diagram showing an example of a case where psychological safety is high. As shown by the satisfaction graph LS31 in Figure 6, in an organization with high psychological safety, the objective data (evaluation data by others) and the subjective data (self-reported data) match or the objective data exceeds the subjective data.

[0093] In Figure 6, for manager group AT31, which is an employee group including manager A and section chief B, the objective data (evaluation data from others) exceeds the subjective data (self-reported data). Furthermore, for non-manager group AT32, which is an employee group including non-manager employees C and D, the objective data (evaluation data from others) and the subjective data (self-reported data) are similar. Therefore, the psychological safety estimation system 1 estimates that young employees have a high level of psychological safety and are able to say what they want to say. The psychological safety estimation system 1 may also estimate that managers have a low level of psychological safety and may have poor relationships with their subordinates.

[0094] For example, the psychological safety estimation system 1 may generate reliable survey results by eliminating the influence of psychological safety. This point will be explained using FIG. 7. FIG. 7 is a diagram showing an example of survey items. FIG. 7 shows a case where questions #1 and #2 are heavily influenced by psychological safety, and questions #3 to #5 are less influenced by psychological safety. In this way, each of the self-reported survey items may have a high or low degree of influence of psychological safety.

[0095] Therefore, the psychological safety estimation system 1 sets the degree of influence of psychological safety for each item in advance, estimates psychological safety, and estimates the reliability of the response results for each item and attribute. By removing these from the statistical data, the reliability of the survey results can be increased even if the results are non-anonymous. Furthermore, the psychological safety estimation system 1 may use some of the items in the survey to calculate an index using the same scale as the estimation by others. For example, as shown in the usage question TG11, the psychological safety estimation system 1 may use questions #1 and #2 of questions #1 to #5 to calculate an index using the same scale as the estimation by others.

[0096] As described above, the psychological safety estimation system 1 may perform various processes. For example, the psychological safety estimation system 1 may acquire differences in satisfaction levels among multiple people and statistically extract attributes that influence psychological safety by clustering the amount of change for each attribute. This allows the psychological safety estimation system 1 to statistically use information from multiple people to improve accuracy, even if the results of surveys or sensing vary on an individual basis. Furthermore, the psychological safety estimation system 1 may estimate factors that influence psychological safety based on the relationships between attributes, such as between superiors and subordinates in the same organization or between different lines of responsibility in the same organization.

[0097] The psychological safety estimation system 1 performs clustering using respondent attribute information and changes in satisfaction for each measurement method. The psychological safety estimation system 1 estimates the following as the estimation results for department #1. For example, the psychological safety estimation system 1 estimates that psychological safety is high for managers and that the results of self-reported questionnaires are reliable. Furthermore, for example, the psychological safety estimation system 1 estimates that psychological safety is low for non-managers and that the results of self-reported questionnaires are unreliable. Furthermore, the psychological safety estimation system 1 estimates that, as an influencing factor of psychological safety, when comparing departments #1 and #2, the attribute "manager" of the attribute "department #1" influences subordinates.

[0098] [Flowchart] An example of the processing procedure executed by the psychological safety estimation system will now be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the processing procedure executed by the psychological safety estimation system. Note that the psychological safety estimation system 1 executes the processing shown in Fig. 8 at any timing, such as periodically or manually.

[0099] The psychological safety estimation system 1 acquires external information (step S101). For example, the psychological safety estimation device 100 receives at least one of the following external information from the terminal device 10 used by the employee: vital sign data of the employee, video data of the employee, text input by the employee, and speech information of the employee. The external information may be sensing data, text information, or the like, and is acquired continuously to improve accuracy.

[0100] The psychological safety estimation system 1 estimates psychological safety (high degree of anonymity) from external information (step S102). For example, the psychological safety estimation device 100 estimates highly anonymous psychological safety using highly anonymous external information including at least one of employee vital signs data, employee video data, employee input text, and employee speech information.

[0101] The psychological safety estimation system 1 branches the process depending on whether the survey has been updated (step S103). If the survey has not been updated (step S103: No), the psychological safety estimation system 1 branches the process depending on whether it is time to conduct a survey (step S104). Surveys are conducted at regular intervals. For example, if the survey is conducted at the end of each month, the psychological safety estimation device 100 determines that it is time to conduct a survey if the date and time of the processing is the end of the month.

[0102] If it is not time to conduct a survey (step S104: No), the psychological safety estimation system 1 returns to step S101 and performs processing. If it is time to conduct a survey (step S104: Yes), the psychological safety estimation system 1 estimates psychological safety (low anonymity) from the survey (step S105). For example, the psychological safety estimation device 100 estimates psychological safety with low anonymity using a survey with low anonymity. Then, the psychological safety estimation system 1 performs processing from step S106 onwards.

[0103] If there is an update to the questionnaire (step S103: Yes), the psychological safety estimation system 1 estimates psychological safety for each attribute (step S106). For example, if there is an update to the questionnaire and the date and time of processing is the end of the month, the psychological safety estimation device 100 estimates psychological safety for each attribute.

[0104] If there is an attribute with low psychological safety (step S107: Yes), the psychological safety estimation system 1 notifies the result (step S108) and terminates the process. For example, if there is an attribute with psychological safety below a predetermined threshold, the psychological safety estimation device 100 transmits notification information indicating the attribute to the notification destination device. On the other hand, if there is no attribute with low psychological safety (step S107: No), the psychological safety estimation system 1 terminates the process without issuing the notification in step S108.

[0105] [Effects] As described above, in the psychological safety estimation device 100 of this embodiment, the employee satisfaction collection unit 132, which is an example of a satisfaction level collection unit, uses multiple methods that differ in the degree of impact of psychological safety to collect information on the satisfaction of members belonging to the organization using each method. Furthermore, the storage unit 120, which is an example of an information management unit, manages organizational information about the organization and attribute data on the members. Furthermore, the psychological safety estimation unit 133 estimates information about psychological safety relative to satisfaction for each attribute using the multiple pieces of satisfaction level information collected by the satisfaction level collection unit and the attribute data acquired from the information management unit.

[0106] In this way, the psychological safety estimation device 100 can estimate the degree of influence of psychological safety for each attribute of an organization by using information on satisfaction levels collected using multiple methods that have different degrees of influence of psychological safety and attribute data to estimate the degree of influence of psychological safety on satisfaction levels for each attribute. Therefore, the psychological safety estimation device 100 can appropriately estimate information on psychological safety.

[0107] For example, engagement surveys and sensing technologies are being widely developed to measure and improve employee satisfaction (ES) and well-being in the workplace. Measurement methods can be broadly divided into self-reporting (personal reporting) and objective estimation by a third party (peer evaluation).

[0108] For example, self-reporting measurement methods include employee attitude surveys using self-reporting questionnaires such as regular "engagement surveys" and "pulse surveys," which are conducted by many companies. Self-reporting measurement methods can also be further categorized by the level of anonymity. For example, engagement surveys, which offer a high level of anonymity, can grasp general trends by collecting anonymous self-reported information across a wide range of company and organizational attributes. Methods with a low level of anonymity include pulse surveys and 360-degree evaluations, which are conducted under real names on a departmental basis, and which allow for more detailed responses on an individual basis depending on the content of the report.

[0109] Furthermore, for example, methods for measuring evaluations by others include technologies that estimate employee physical condition and consciousness from text such as daily reports, wearable devices, and sensing devices. These methods make it possible to estimate employee satisfaction and well-being without active behavior such as self-reporting.

[0110] Self-reporting and peer-assessment measurement methods each have their advantages and disadvantages. While self-reporting and less anonymity-based measurement methods allow for detailed information to be collected on an individual or departmental level, allowing for appropriate responses, the results may be heavily dependent on the psychological safety of the organization. For example, if an employee believes that entering negative information in a survey could result in reprimand from a superior, affect their performance evaluation, or require special measures such as a hearing, they may intentionally enter safe results. In other words, in organizations with low psychological safety, surveys with low anonymity are less reliable. This not only results in inaccurate results, but can also lead to incorrect responses.

[0111] Furthermore, while the impact of psychological safety can be reduced to some extent by increasing the anonymity of the reported content, the attribute information must be at a fairly large granularity in order to prevent individuals from being identified, so the scope of information utilization is limited compared to self-reporting with low anonymity. For example, objective measurement methods using vital sensors or daily behavioral information are thought to have less of an impact on psychological safety in measurement results compared to self-reporting. However, compared to self-reporting, there are issues such as a narrower range of information that can be obtained and lower accuracy.

[0112] Therefore, the psychological safety estimation device 100 enables measurement of psychological safety in an organization and estimation of the factors that cause it by combining multiple methods that have different degrees of influence of psychological safety. For example, the psychological safety estimation device 100 can estimate (measure) psychological safety for each organization and attribute by using the discrepancy between multiple measurement methods with different psychological safety. Furthermore, for example, the psychological safety estimation device 100 can enable identification of the factors that cause psychological safety by attribute clustering of psychological safety.

[0113] [Program] A program written in a computer-executable language may be created to execute the processes performed by the psychological safety estimation device 100 according to the above embodiment. In one embodiment, the psychological safety estimation device 100 can be implemented by installing an information processing program that executes the above information processing as package software or online software on a desired computer. For example, by executing the above information processing program on an information processing device, the information processing device can function as the psychological safety estimation device 100. Other examples of information processing devices include mobile communication terminals such as smartphones, mobile phones, and PHS (Personal Handyphone Systems), as well as slate terminals such as PDAs (Personal Digital Assistants). The functions of the psychological safety estimation device 100 may also be implemented on a cloud server.

[0114] 9 is a diagram showing an example of a computer that executes an information processing program. The computer 1000 includes, for example, a memory 1010, a CPU 1020, a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0115] The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1031. The disk drive interface 1040 is connected to a disk drive 1041. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to a mouse 1051 and a keyboard 1052, for example. The video adapter 1060 is connected to a display 1061, for example.

[0116] Here, the hard disk drive 1031 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. The various pieces of information described in the above embodiments are stored in the hard disk drive 1031 or memory 1010, for example.

[0117] Furthermore, the information processing program is stored in the hard disk drive 1031, for example, as a program module 1093 in which instructions to be executed by the computer 1000 are written. Specifically, the program module 1093 in which each process executed by the psychological safety estimation device 100 described in the above embodiment is written is stored in the hard disk drive 1031.

[0118] Furthermore, data used for information processing by the information processing program is stored as program data 1094, for example, in the hard disk drive 1031. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the hard disk drive 1031 into the RAM 1012 as necessary, and executes each of the above-described procedures.

[0119] The program module 1093 and program data 1094 related to the information processing program are not limited to being stored in the hard disk drive 1031, and may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1041. Alternatively, the program module 1093 and program data 1094 related to the information processing program may be stored in another computer connected via a network such as a LAN (Local Area Network) or a WAN (Wide Area Network), and read by the CPU 1020 via the network interface 1070.

[0120] Although the present invention has been described above as an embodiment, the present invention is not limited to the description and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention.

[0121] REFERENCE SIGNS LIST 1 Psychological safety estimation system 10 Terminal device 100 Psychological safety estimation device 110 Communication unit 120 Storage unit (information management unit) 121 Organization information storage unit 122 Attribute data storage unit 123 Processing result information storage unit 130 Control unit 131 Acquisition unit 132 Employee satisfaction level collection unit (satisfaction level collection unit) 133 Psychological safety estimation unit 134 Notification unit

Claims

1. A psychological safety estimation device comprising: a satisfaction level collection unit that uses a plurality of methods with different degrees of influence of psychological safety to collect information regarding the satisfaction of members belonging to an organization using each method; an information management unit that manages organizational information about the organization and attribute data of the members; and a psychological safety estimation unit that uses information regarding the plurality of satisfaction levels collected by the satisfaction level collection unit and the attribute data obtained from the information management unit to estimate information regarding psychological safety relative to satisfaction for each attribute.

2. The psychological safety estimation device described in claim 1, characterized in that the psychological safety estimation unit estimates satisfaction information with a low influence of psychological safety using one or more of vital data, video data, input text, and speech information related to the member, and estimates satisfaction information with a high influence of psychological safety using a questionnaire with a low degree of anonymity.

3. The psychological safety estimation device described in claim 1, characterized in that the psychological safety estimation unit estimates attributes that influence the psychological safety based on the relationship between each attribute indicated by the organizational information and changes in the psychological safety.

4. The psychological safety estimation device described in claim 1, characterized in that the psychological safety estimation unit analyzes the relationship between the attributes and the difference in psychological safety based on the difference for each attribute between satisfaction information with a low influence of psychological safety and satisfaction information with a high influence of psychological safety.

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