Attendance management device, attendance management method, and attendance management program

Abstract

It enables employees to increase their engagement with the organization based on their work situation. [Solution] An input unit 21 inputs attendance data 31 indicating the working status of a subject to a question generation model 41, which is a trained model. An output unit 22 outputs a model question, which is a question for confirming the subject's status, generated by the question generation model 41 in response to the attendance data 31 input by the input unit 21. An answer receiving unit 23 receives answers to the model questions.

Description

[Technical Field]

[0001] The present disclosure relates to techniques for increasing employee engagement with an organization. [Background technology]

[0002] Companies and other organizations are beginning to consider it important to increase employee engagement with their organizations. High employee engagement with an organization means that a relationship of trust has been built between the organization and the employee. In other words, high employee engagement with an organization means that the employee feels an attachment to or pride in the organization. In order to increase employee engagement with an organization, it is necessary to create a comfortable working environment. To create a comfortable working environment, it is important to reduce employee stress.

[0003] Patent Document 1 describes measuring the career development status of employees based on their responses to a questionnaire, and determining a career interview implementation policy according to the career development status. In this way, Patent Document 1 aims to promote employee career development and improve engagement. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-99907 Summary of the Invention [Problem to be solved by the invention]

[0005] The technology described in Patent Document 1 aims to improve engagement by conducting appropriate career interviews. Understanding workers' careers is also effective in improving engagement. In addition to careers, working conditions such as working hours are related to workers' stress, so managers' understanding of workers' working conditions and trying to make their working conditions closer to workers' wishes is effective in improving engagement. The present disclosure aims to increase workers' engagement with an organization based on their work status. [Means for solving the problem]

[0006] The attendance management device according to the present disclosure includes: an input unit that inputs attendance data indicating the working status of a subject into a question generation model that is a trained model; an output unit that outputs a model question, which is a question for confirming the state of the subject, generated by the question generation model in response to the attendance data input by the input unit; Equipped with. [Effects of the Invention]

[0007] In the present disclosure, model questions are output, which are questions to check the status of a subject in accordance with attendance data. By asking the subject the model questions, communication between the supervisor and the subject regarding the work situation may become smoother. As a result, the subject feels that the supervisor is trying to understand the work situation, which makes it easier for engagement to improve. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a configuration diagram of an attendance management device 10 according to a first embodiment. [Figure 2] 10 is a flowchart of a subject-side process according to the first embodiment. [Figure 3] FIG. 3 is an explanatory diagram of a specific example of an input to a question generation model 41 according to the first embodiment. [Figure 4]FIG. 3 is an explanatory diagram of a specific example of a model question according to the first embodiment. [Figure 5] FIG. 10 is a configuration diagram of an attendance management device 10 according to a second embodiment. [Figure 6] 10 is a flowchart of a template generation process according to the second embodiment. [Figure 7] FIG. 10 is an explanatory diagram of a specific example of an input to a template generation model 42 according to the second embodiment. [Figure 8] FIG. 10 is an explanatory diagram of a specific example of a template question 33 according to the second embodiment. [Figure 9] 10 is a flowchart of a process on the administrator side according to the second embodiment. [Figure 10] 10 is a flowchart of a subject-side process according to the second embodiment. [Figure 11] FIG. 10 is a configuration diagram of an attendance management device 10 according to a third embodiment. [Figure 12] 11 is a flowchart of a process on the administrator side according to the third embodiment. [Figure 13] FIG. 11 is an explanatory diagram of a specific example of input to the advice generation model 43 according to the third embodiment. [Figure 14] FIG. 11 is an explanatory diagram of advice according to the third embodiment. [Figure 15] FIG. 10 is a configuration diagram of an attendance management device 10 according to a fourth embodiment. [Figure 16] 10 is a flowchart of an evaluation process according to the fourth embodiment. [Figure 17] FIG. 11 is an explanatory diagram of a specific example of input to an evaluation model 44 according to the fourth embodiment. [Figure 18] FIG. 13 is a diagram showing an example of an output of an evaluation value according to the fourth embodiment. [Figure 19] FIG. 11 is a diagram showing an example of an evaluation value for each pair of an answer and a question according to Modification Example 3. [Figure 20] FIG. 10 is a configuration diagram of an attendance management device 10 according to a fifth embodiment. [Figure 21] 13 is a flowchart of an evaluation advice generation process according to the fifth embodiment. [Figure 22] FIG. 13 is an explanatory diagram of an adjustment process according to the fifth embodiment. [Figure 23] FIG. 13 is an explanatory diagram of a specific example of input to the advice generation model 43 according to the fifth embodiment. [Figure 24] FIG. 13 is an explanatory diagram of advice according to the fifth embodiment. [Figure 25] FIG. 20 is an explanatory diagram of a specific example of an input to a template generation model 42 according to the sixth embodiment. [Figure 26] FIG. 20 is an explanatory diagram of a specific example of a template question 33 according to the sixth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Embodiment 1 ***Configuration Description*** The configuration of an attendance management device 10 according to the first embodiment will be described with reference to FIG. The attendance management device 10 is a computer. The attendance management device 10 includes hardware such as a processor 11, a memory 12, a storage 13, and a communication interface 14. The processor 11 is connected to other hardware via signal lines and controls the other hardware.

[0010] The processor 11 is an IC that performs processing. IC stands for Integrated Circuit. Specific examples of the processor 11 include a CPU, a DSP, and a GPU. CPU stands for Central Processing Unit. DSP stands for Digital Signal Processor. GPU stands for Graphics Processing Unit.

[0011] The memory 12 is a storage device that temporarily stores data. Specific examples of the memory 12 include SRAM and DRAM. SRAM stands for Static Random Access Memory. DRAM stands for Dynamic Random Access Memory.

[0012] The storage 13 is a storage device that stores data. A specific example of the storage 13 is an SSD. SSD is an abbreviation for Solid State Drive. The storage 13 may also be a portable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. SD is an abbreviation for Secure Digital. DVD is an abbreviation for Digital Versatile Disk.

[0013] The communication interface 14 is an interface for communicating with external devices. Specific examples of the communication interface 14 include Ethernet (registered trademark), USB, and HDMI (registered trademark) ports. USB stands for Universal Serial Bus. HDMI stands for High-Definition Multimedia Interface.

[0014] The attendance management device 10 includes, as functional components, an input unit 21, an output unit 22, and a response receiving unit 23. The functions of the functional components of the attendance management device 10 are realized by software. The storage 13 stores a program that realizes the function of each functional component of the attendance management device 10. This program is read into the memory 12 by the processor 11 and executed by the processor 11. In this way, the function of each functional component of the attendance management device 10 is realized.

[0015] The storage 13 stores attendance data 31 and question and answer data 32.

[0016] The attendance management device 10 is connected to a question generation model 41, which is a trained model, via a communication interface 14. A trained model is what is known as generative AI. AI stands for artificial intelligence. A trained model may be constructed using algorithms such as BERT and GPT, for example. BERT stands for Bidirectional Encoder Representations from Transformers. GPT stands for Generative Pretrained Transformer. A trained model may be constructed by combining multiple algorithms, including these algorithms.

[0017] The attendance management device 10 is connected to a user terminal 51 and a manager terminal 52 via a communication interface 14. The user terminal 51 is a terminal such as a PC used by people working in an organization, such as employees. The manager terminal 52 is a terminal such as a PC used by a manager who manages workers. PC is an abbreviation for Personal Computer.

[0018] In FIG. 1, the question generation model 41 exists outside the attendance management device 10. However, the question generation model 41 may be provided as a functional component of the attendance management device 10. Hereinafter, not only the question generation model 41 but also the trained model may exist outside the attendance management device 10 or may be provided as a functional component of the attendance management device 10.

[0019] 1 shows only one processor 11. However, there may be a plurality of processors 11, and the plurality of processors 11 may cooperate to execute programs that realize the respective functions.

[0020] ***Explanation of Operation*** The operation of the attendance management device 10 according to the first embodiment will be described with reference to FIGS. The operation procedure of the attendance management device 10 according to the embodiment 1 corresponds to the attendance management method according to the embodiment 1. Moreover, the program that realizes the operation of the attendance management device 10 according to the embodiment 1 corresponds to the attendance management program according to the embodiment 1. The operation of the attendance management device 10 according to the first embodiment includes processing on the subject's side.

[0021] Referring to FIG. 2, the subject-side processing according to the first embodiment will be described. The subject-side process is executed after the subject, who is an employee of the organization, enters the previous day's attendance data. Here, it is assumed that the process in Figure 2 is executed when the subject enters the previous day's attendance data. Here, the previous day refers to the most recent working day for each subject.

[0022] (Step S11: Input processing) The input unit 21 inputs attendance data 31 indicating the working conditions of the subject person into a trained model, the question generation model 41. The attendance data 31 indicates, as working conditions, the arrival time, departure time, leave, absence, working hours, etc. for each day of a past reference period. At this time, the input unit 21 inputs to the question generation model 41 an instruction to generate a question to be asked to the subject in order to understand the subject's working status, taking into account the attendance data 31. The input unit 21 also inputs to the question generation model 41, as a constraint, the content of a question that must not be generated. Examples of questions that must not be generated include questions that lower the subject's motivation and questions that constitute harassment. The input unit 21 also inputs to the question generation model 41 the output format of the question.

[0023] A specific example of an input to the question generation model 41 according to the first embodiment will be described with reference to FIG. In Figure 3, the #instruction contains instructions to generate questions for the subject to understand the subject's status, taking into account the attendance data 31. The #constraints contain questions that should not be generated. The #attendance data contains the arrival and departure times, vacation / absences, and working hours for each day of the past reference period. In Figure 3, the #previous day's attendance input is set separately from the #attendance data, and the #previous day's attendance input contains the arrival and departure times, vacation / absences, and working hours for the previous day. Therefore, the #attendance data contains information for each day from the day before yesterday to the past reference period. The #output format describes the output format for the questions. In Figure 3, it is specified that there is one question, and that a total of five answer options should be prepared: four options and "other."

[0024] Here, the reason why #Previous day's attendance input is set separately from #Attendance data is to generate questions that emphasize the information from the previous day among the days in the past reference period. Instead of or in addition to setting the previous day's attendance input separately from the attendance data, the input unit 21 may instruct the system to generate a question that prioritizes the previous day's information. The input unit 21 may also instruct the system to generate a question that prioritizes the most recent information over older information.

[0025] When the attendance data 31 and the like are input in step S11, the question generation model 41 follows the instructions and generates a question as a model question to understand the subject's condition based on the attendance data 31. For example, if there is a lot of overtime work, a question to understand the subject's condition based on the attendance data 31 could be a question that shows concern for the amount of overtime work, such as "It seems like you're working a lot of overtime. Are you tired?". Also, if there is work on a holiday, a question that shows concern for the progress of work, such as "How is the progress of your work?"

[0026] (Step S12: Output processing) The output unit 22 acquires a model question, which is a question for confirming the subject's condition, generated by the question generation model 41 in response to the attendance data 31 input in step S11. The output unit 22 outputs the model question to a user terminal 51 used by the subject.

[0027] A specific example of a model question according to the first embodiment will be described with reference to FIG. Fig. 4 shows an example of a model question generated by the question generation model 41 when the information shown in Fig. 3 is input to the question generation model 41. In Fig. 3, it was specified that there was one question and that a total of five answers, including four options and others, were to be prepared, so in Fig. 4, one question with a total of five options is generated.

[0028] (Step S13: Response acceptance process) The answer receiving unit 23 receives input of an answer from the subject to the model question output in step S12. The answer receiving unit 23 writes the pair of the model question and the answer together with the subject's identification information and the date and time into the storage 13 as question and answer data 32. A manager who is the subject's superior or the like can understand the subject's condition by referring to the model question and answer pairs written in the question and answer data 32 from the manager terminal 52.

[0029] ***Effects of the First Embodiment*** As described above, the attendance management device 10 according to the first embodiment outputs model questions, which are questions for checking the status of a subject in accordance with attendance data. By having the manager refer to the set of model questions and answers for the subject, communication between the manager and the subject regarding the work situation may become smoother. As a result, the subject feels that the manager is trying to understand the work situation, which tends to improve engagement.

[0030] ***Other Configurations*** <Variation 1> If the process in Figure 2 is executed when the previous day's attendance data is entered, the process in Figure 2 will be executed every time the employee works. Therefore, model questions will be generated every time the employee works, and the employee will answer the model questions. If there is little change in the employee's attendance data 31, there is a possibility that similar model questions will be generated every day. Therefore, in step S11, the input unit 21 may input a past question and instruct the user to generate a different question, thereby preventing similar model questions from being generated every day.

[0031] Furthermore, in step S11, the input unit 21 may specify a plurality of question types and input past questions to instruct the system to generate different types of questions. This will result in different types of model questions being generated every day. Note that the input unit 21 may also instruct the system to generate randomly selected types of questions without inputting past questions. This will also result in different types of model questions being generated every day. As for the types of questions, it is conceivable to set multiple evaluation types related to engagement with the organization to which one belongs. These evaluation types include, for example, tolerance for overtime, willingness to take vacation, work-life balance, skill development, and positivity. Tolerance for overtime is an indicator of whether work can be done without overtime. Willingness to take vacation is an indicator of whether vacation is taken proactively. Work-life balance is an indicator of whether work and life are in harmony. Skill development is an indicator of whether one is working to improve one's skills or abilities. Positivity is an indicator of whether one has a positive attitude.

[0032] Embodiment 2 The second embodiment differs from the first embodiment in that it accepts input of a designated question 34, which is a question to confirm the status of the subject, from the subject's administrator. In the second embodiment, this difference will be explained, and explanation of the same points will be omitted.

[0033] ***Configuration Description*** The configuration of the attendance management device 10 according to the second embodiment will be described with reference to FIG. The attendance management device 10 differs from the attendance management device 10 shown in Fig. 1 in that it includes a question receiving unit 24 as a functional component. The attendance management device 10 also differs from the attendance management device 10 shown in Fig. 1 in that template questions 33 and specified questions 34 are stored in storage 13. The attendance management device 10 also differs from the attendance management device 10 shown in Fig. 1 in that it is connected to a template generation model 42, which is a trained model, via a communication interface 14.

[0034] ***Explanation of Operation*** The operation of the attendance management device 10 according to the second embodiment will be described with reference to FIGS. The operation of the attendance management device 10 according to the second embodiment includes a template generation process, a manager-side process, and a subject-side process.

[0035] The template generation process according to the second embodiment will be described with reference to FIG. The template generation process is executed during the initial setup of the attendance management device 10. The template generation process may also be executed when updating the template questions 33 set during the initial setup.

[0036] (Step S21: Input processing) The input unit 21 inputs a plurality of question types to the trained model, the template generation model 42. As described in the second modification, the question types may be a plurality of evaluation types related to engagement with the organization to which the user belongs. At this time, the input unit 21 inputs an instruction to generate a question for confirming the situation of the subject for each type to the template generation model 42. The input unit 21 also inputs an instruction to generate advice for the administrator based on the purpose of each question to the template generation model 42. The input unit 21 also inputs an output format of the question to the question generation model 41.

[0037] A specific example of an input to the template generation model 42 according to the second embodiment will be described with reference to FIG. In Figure 7, #Instructions contains instructions to generate questions to check the status of each target person by type, and instructions to generate advice for the manager. #Template contains the question types. In Figure 7, the question types are converted into the desired format and displayed. In Figure 7, the question types include items such as wanting to know the status of skill development, wanting to know if work-life balance is being achieved, and wanting to encourage vacation time. #Output format contains the output format for the questions.

[0038] When the question type and other information are input in step S21, the template generation model 42 generates questions for each type as template questions 33 in accordance with the instructions.

[0039] (Step S22: Output processing) The output unit 22 acquires template questions 33, which are questions for each of the multiple question types generated by the template generation model 42 in response to the multiple question types input in step S21. The output unit 22 outputs the template questions 33 for each type to the administrator terminal 52 used by the administrator. As a result, the template questions 33 are displayed on the display device of the administrator terminal 52, allowing the administrator to check the template questions 33.

[0040] A specific example of the template question 33 according to the second embodiment will be described with reference to FIG. FIG. 8 shows an example of a template question 33 generated by the template generation model 42 when the information shown in FIG. 7 is input to the template generation model 42. One or more template questions 33 are generated for each type of question. In Fig. 8, template questions 33 are generated for each category, such as to know the status of skill improvement, to know if work-life balance is being achieved, and to encourage vacation taking. In addition, advice to the manager is generated for each template question 33.

[0041] (Step S23: Storage processing) The output unit 22 writes the template questions 33 for each type acquired in step S22 into the storage 13.

[0042] When the template question 33 is output to the administrator terminal 52, the output unit 22 may accept a correction to the template question 33 from the administrator. Then, the output unit 22 may write the corrected template question 33 to the storage 13.

[0043] With reference to FIG. 9, the administrator-side process according to the second embodiment will be described. The administrator-side process is executed for each person under the administrator's control at a timing specified by the administrator. Here, it is assumed that the administrator-side process is executed when approving the attendance data for the previous day for each person.

[0044] (Step S31: Answer confirmation process) The answer receiving unit 23 acquires the question posed to the subject when he or she entered the previous day's attendance data and the answer to that question from the storage 13. Then, the answer receiving unit 23 outputs the question and the answer to the administrator terminal 52. This allows the administrator to confirm the question posed to the subject on the previous day and the answer to that question.

[0045] (Step S32: Question determination process) The question receiving unit 24 receives a selection from the administrator as to whether or not to input a specified question 34. The specified question 34 is a question entered by the administrator to confirm the status of the subject. For example, the specified question 34 is entered when there is something the administrator wants to confirm with the subject based on the questions and answers from the previous day. If it is selected that the specified question 34 is to be input, the question receiving unit 24 proceeds to step S33. On the other hand, if it is selected that the specified question 34 is not to be input, the question receiving unit 24 ends the process.

[0046] (Step S33: Question acceptance process) The question receiving unit 24 outputs the template questions 33 for each type generated in the template generation process to the administrator terminal 52. At this time, the question receiving unit 24 may also output advice to the administrator to the administrator terminal 52. Then, the question receiving unit 24 receives a specified question 34 generated by the administrator by editing any of the template questions 33. Note that the question receiving unit 24 may also receive a specified question 34 created by the administrator, not based on a template question 33.

[0047] (Step S34: Question storage process) The question receiving unit 24 writes the specified question 34 received in step S33 to the storage 13 together with the identification information of the subject, the date and time, and a flag indicating that the question is unprocessed.

[0048] Referring to FIG. 10, the subject-side processing according to the second embodiment will be described. The subject-side process corresponds to the process shown in Figure 2. Similar to the process shown in Figure 2, the subject-side process is executed after the subject, who is a person working in an organization, enters the attendance data of the previous day. Here, it is assumed that the subject-side process is executed at the timing when the subject enters the attendance data of the previous day.

[0049] The processes in steps S42 and S43 are the same as the processes in steps S11 and S12 in FIG.

[0050] (Step S41: Designation determination process) The input unit 21 determines whether or not a specified question 34 for the subject, for which the flag is set to "unprocessed," is stored in the storage 13. If the specified question 34 is not stored, the input unit 21 advances the process to step S42. On the other hand, if the specified question 34 is stored, the input unit 21 advances the process to step S44.

[0051] (Step S44: Specified question output process) The output unit 22 reads out the specified question 34 for the subject, for which the flag is set to "unprocessed," from the storage 13. Then, the output unit 22 outputs the specified question 34 to the user terminal 51 used by the subject. At this time, the output unit 22 changes the flag for the read specified question 34 to "processed."

[0052] (Step S45: Response acceptance process) The answer receiving unit 23 receives input of an answer from the subject to the model question output in step S43 or the specified question 34 output in step S44. The answer receiving unit 23 writes a pair of the model question or the specified question 34 and the answer together with the subject's identification information and the date and time into the storage 13 as question and answer data 32.

[0053] Through the above process, the question and answer are output to the administrator terminal 52 on the business day following the day the subject enters attendance data and answers the question, and the administrator determines whether or not it is necessary to enter the designated question 34. If the designated question 34 is entered, the designated question 34 is output to the user terminal 51 the next time the subject enters attendance data.

[0054] ***Effects of the Second Embodiment*** As described above, the attendance management device 10 according to the second embodiment accepts the specified question 34 from the manager and outputs it to the user terminal 51. This allows the manager to ask any question when there is something he or she wants to confirm with the subject.

[0055] ***Other Configurations*** <Variation 2> In the second embodiment, it is assumed that only one question is output per day. Therefore, only one of the model question and the specified question 34 is output. However, if it is acceptable to output multiple questions per day, when the specified question 34 is input, the specified question 34 may be output in addition to the model question.

[0056] Embodiment 3 The third embodiment differs from the first and second embodiments in that it generates advice to the administrator. In the third embodiment, this difference will be explained, and explanation of the same points will be omitted. In the third embodiment, a case where a modification is made to the second embodiment will be described. However, it is also possible to make modifications to the first embodiment.

[0057] ***Configuration Description*** The configuration of the attendance management device 10 according to the third embodiment will be described with reference to FIG. The attendance management device 10 differs from the attendance management device 10 shown in FIG. 5 in that it is connected to an advice generation model 43, which is a trained model, via a communication interface 14.

[0058] ***Explanation of Operation*** The operation of the attendance management device 10 according to the third embodiment will be described with reference to FIGS. The process on the administrator side differs from that in the second embodiment. The template generation process and the process on the subject side are the same as those in the second embodiment.

[0059] The administrator-side process according to the third embodiment will be described with reference to FIG. As in the second embodiment, it is assumed that the administrator-side process is executed at the timing when the attendance data of the subject person for the previous day is approved.

[0060] The process of step S51 is the same as the process of step S31 in Fig. 9. The processes of steps S54 to S56 are the same as the processes of steps S32 to S34 in Fig. 9.

[0061] (Step S52: Input processing) The input unit 21 inputs a pair of an answer and a question that is a model question or a specified question 34 to the advice generation model 43 that is a trained model. At this time, the input unit 21 inputs an instruction to generate advice for the manager to respond to the subject to the advice generation model 43. The input unit 21 also inputs an output format of the advice to the advice generation model 43. Here, the output format is, for example, a limit on the number of characters, etc.

[0062] A specific example of input to the advice generation model 43 according to the third embodiment will be described with reference to FIG. In Figure 13, the #instruction contains instructions for generating advice. The #question contains a model question or a specified question 34. The #answer contains the answer from the subject. The #output format contains the output format of the advice. It is also possible to input attendance data 31 of the subject for a past reference period including the previous day, and generate advice taking the attendance data 31 into consideration.

[0063] When a pair of an answer and a question is input in step S52, the advice generation model 43 generates advice in accordance with the instructions.

[0064] (Step S53: Output process) The output unit 22 acquires the advice generated by the advice generation model 43 in response to the pair of answer and question input in step S52. The output unit 22 outputs the advice to the administrator terminal 52 used by the administrator. For example, advice such as that shown in FIG. 14 is output. As a result, the advice is displayed on the display device of the administrator terminal 52, allowing the administrator to confirm the advice. Then, the administrator can refer to the advice and determine whether or not to input the specified question 34.

[0065] ***Effects of the Third Embodiment*** As described above, the attendance management device 10 according to the third embodiment outputs advice for the manager to use when dealing with the subject in response to a pair of an answer and a question. By referring to the advice, the manager can understand how to deal with the subject, facilitating smooth communication between the manager and the subject. As a result, the subject feels that the manager is trying to understand their work situation, which makes it easier for engagement to improve. Furthermore, it becomes possible to determine whether or not to enter a designated question 34 after referring to the advice, thereby enabling the appropriate designated question 34 to be entered.

[0066] Embodiment 4 The fourth embodiment differs from the first to third embodiments in that an engagement evaluation value for a target person is calculated from pairs of questions and answers. In the fourth embodiment, this difference will be explained, and explanation of the same points will be omitted.

[0067] ***Configuration Description*** The configuration of the attendance management device 10 according to the fourth embodiment will be described with reference to FIG. Fig. 15 shows an example in which a change has been made to the attendance management device 10 shown in Fig. 1. The attendance management device 10 differs from the attendance management device 10 shown in Fig. 1 etc. in that evaluation data 35 is stored in storage 13. The attendance management device 10 also differs from the attendance management device 10 shown in Fig. 1 etc. in that it is connected to an evaluation model 44, which is a trained model, via a communication interface 14.

[0068] ***Explanation of Operation*** The operation of the attendance management device 10 according to the fourth embodiment will be described with reference to FIGS. The operation of the attendance management device 10 according to the fourth embodiment includes evaluation processing.

[0069] The evaluation process according to the fourth embodiment will be described with reference to FIG. The evaluation process is executed at a timing designated by an administrator, etc. For example, the evaluation process is executed when the administrator wants to check the engagement of the target person.

[0070] (Step S61: Input processing) The input unit 21 inputs pairs of answers for each day of the evaluation period and questions that are model questions or specified questions 34 into the evaluation model 44, which is a trained model. The input unit 21 may also input attendance data for each day of the evaluation period into the evaluation model 44. The evaluation period may be, for example, a period of one month or one year, or may be the period during which a certain project was carried out. At this time, the input unit 21 inputs an instruction to calculate a numerical evaluation value of the subject's engagement with the organization to which the subject belongs to the evaluation model 44. The input unit 21 also inputs a target type, which is one or more evaluation types to be evaluated among a plurality of evaluation types related to engagement with the organization to which the subject belongs, to the evaluation model 44.

[0071] A specific example of input to the evaluation model 44 according to the fourth embodiment will be described with reference to FIG. In Figure 17, the #instruction contains instructions to calculate the evaluation value for the target type. The #attendance data contains attendance data for each day of the evaluation period. A pair of #question and #answer is set for each day of the evaluation period, with the #question being a model question or designated question 34 and the #answer being the answer from the target person. The #evaluation type contains the target type.

[0072] When a pair of an answer and a question is input in step S61, the evaluation model 44 calculates an evaluation value for each object type in accordance with the instructions.

[0073] (Step S62: Output process) The output unit 22 acquires the evaluation value for each object type calculated by the evaluation model 44 in response to the pair of answer and question input in step S61. The output unit 22 outputs the evaluation value to the administrator terminal 52 used by the administrator. As a result, the evaluation value is displayed on the display device of the administrator terminal 52, allowing the administrator to check the evaluation value. For example, the output unit 22 may display the evaluation value for each object type as a radar chart or the like, as shown in FIG.

[0074] (Step S63: Storage process) The output unit 22 writes the evaluation value for each object type acquired in step S62 into the storage 13 as evaluation data 35.

[0075] Here, the processes of steps S61 and S62 are executed in order for each object type. Then, when the processes for all object types have been completed, the evaluation values ​​for each object type are displayed as a radar chart or the like.

[0076] ***Effects of the Fourth Embodiment*** As described above, the attendance management device 10 according to the fourth embodiment calculates an engagement evaluation value for a subject from a pair of a question and an answer, thereby enabling a manager to easily check the engagement state of a subject.

[0077] ***Other Configurations*** <Variation 3> In the fourth embodiment, an evaluation value is calculated for each object type. Alternatively, an evaluation value may be calculated for each pair of an answer and a question, and an evaluation value for each object type may be calculated from the evaluation value for each pair. In this case, in step S61, the input unit 21 inputs to the evaluation model 44 an instruction to calculate an evaluation value for each pair of an answer and a question, and to calculate an evaluation value for each object type from the evaluation value for each pair. This allows for an evaluation value to be obtained for each answer-question pair, in addition to the evaluation value for each target type, as shown in Figure 19. By referring to the evaluation value for each answer-question pair, the administrator can check the engagement status in more detail. In this embodiment, what is referred to as the attendance management device may include other devices that use attendance management data and questions and answers posed to subjects. For example, it may be a data analysis device that receives attendance management data and questions and answers posed to subjects from the attendance management device and evaluates engagement.

[0078] Embodiment 5 The fifth embodiment differs from the fourth embodiment in that advice is generated based on an evaluation value. In the fifth embodiment, this difference will be explained, and explanation of the same points will be omitted.

[0079] ***Configuration Description*** The configuration of the attendance management device 10 according to the fifth embodiment will be described with reference to FIG. The attendance management device 10 differs from the attendance management device 10 shown in Fig. 15 in that it includes an adjustment receiving unit 25 as a functional component. The attendance management device 10 also differs from the attendance management device 10 shown in Fig. 15 in that it is connected to an advice generation model 43 via a communication interface 14.

[0080] ***Explanation of Operation*** The operation of the attendance management device 10 according to the fifth embodiment will be described with reference to FIGS. The operation of the attendance management device 10 according to the fifth embodiment includes an evaluation advice generation process.

[0081] The evaluation advice generation process according to the fifth embodiment will be described with reference to FIG. The evaluation advice generation process is executed after the execution of the evaluation process described in embodiment 4. For example, the evaluation advice generation process is executed at a timing designated by the subject after the execution of the evaluation process.

[0082] (Step S71: Adjustment process) The adjustment receiving unit 25 outputs the evaluation value for each object type for the subject obtained in the evaluation process to the user terminal 51 used by the subject. At this time, the adjustment receiving unit 25 outputs the average value of the evaluation value for each object type for the subject, along with the evaluation value for each object type for the subject, to the user terminal 51. As a result, as shown in FIG. 22, the evaluation value and the average value for each object type are displayed on the display device of the user terminal 51. The average value is the average value for people within a range compared with the subject. For example, the average value is the average value for the department to which the subject belongs. The adjustment receiving unit 25 receives input of an evaluation adjustment value, which is an adjusted evaluation value, from the subject for each subject type. If the evaluation value differs from the subject's self-evaluation, the subject adjusts the evaluation value by referring to the average value or the like.

[0083] (Step S72: Evaluation adjustment value storage process) The adjustment receiving unit 25 adds the evaluation adjustment value received in step S71 to the evaluation data 35 for the subject.

[0084] (Step S73: Input processing) The input unit 21 inputs the subject's evaluation adjustment value for the subject type into the advice generation model 43, which is a trained model. The input unit 21 also inputs the evaluation values ​​of others into the advice generation model 43. Here, the others are people whose evaluation values ​​were used when calculating the above-mentioned average value. Note that the others do not necessarily have to be all people whose evaluation values ​​were used when calculating the average value, but may be some people close to the subject. For example, if the average value is the average value in the subject's department, the others may be members of the project team to which the subject belongs in the subject's department. At this time, the input unit 21 inputs to the advice generation model 43 an instruction to generate advice for the subject that will increase the evaluation value of the subject's subject type.

[0085] A specific example of input to the advice generation model 43 according to the fifth embodiment will be described with reference to FIG. In Figure 23, the #instruction contains instructions to generate advice for a target person to increase their evaluation value. Note that Figure 23 shows target types as tolerance for overtime, willingness to take vacation, work-life balance, skill improvement, and positivity. #evaluation values ​​are set for the target person, Mr. A, and others, and evaluation values ​​for each target type are set in the #evaluation value. Note that an evaluation adjustment value is set as the evaluation value for the target person.

[0086] (Step S74: Output process) The output unit 22 acquires advice for the subject that increases the evaluation value for the subject's target type, which is generated by the advice generation model 43 in response to the evaluation value for the target type, etc., input in step S73. The output unit 22 outputs the advice to the user terminal 51 used by the subject. This allows the subject to refer to the advice. As shown in Fig. 24, advice is generated for each target type. The output unit 22 may also output the advice to the administrator terminal 52 used by the administrator.

[0087] ***Effects of the Fifth Embodiment*** The attendance management device 10 according to the fifth embodiment generates advice for increasing the evaluation value, thereby enabling the subject to understand what is necessary to improve his / her condition.

[0088] Embodiment 6 The sixth embodiment differs from the second embodiment in that current affairs information is input when generating a template. In the sixth embodiment, this difference will be explained, and explanation of the same points will be omitted.

[0089] ***Explanation of Operation*** The operation of the attendance management device 10 according to the sixth embodiment will be described with reference to FIGS. 6, 25, and 26. FIG. The template generation process differs from that of the second embodiment. The processes on the administrator side and the target user side are the same as those of the second embodiment.

[0090] The template generation process according to the sixth embodiment will be described with reference to FIG. The template generation process according to the sixth embodiment is executed when updating the template question 33 set at the time of initial setup. Usually, the template generation process according to the second embodiment may be executed first, and then the template generation process according to the sixth embodiment may be executed periodically. For example, the template generation process according to the sixth embodiment may be executed at the middle of the month or at the change of seasons.

[0091] The processes in steps S22 and S23 are the same as those in the second embodiment.

[0092] (Step S21: Input processing) The input unit 21 inputs current events information in addition to multiple question types, etc. The current events information is information about events occurring close to the time of execution of the template generation process, such as news articles and internal organizational events. The current events information may be set manually, such as news about internal organizational events, or may be set by the input unit 21 by acquiring news stored on an internal company network using web cloning or an API. API stands for Application Programming Interface.

[0093] A specific example of input to the template generation model 42 according to the sixth embodiment will be described with reference to FIG. FIG. 25 differs from the second embodiment in that current events information is listed under #CurrentAction. In FIG. 25, current events information 1 states, "Please ask a question in a positive manner about the possibility that the price of gasoline will rise to around 185 yen per liter in January of next year," and current events information 2 states, "A bowling tournament will be held as a company event on December 5th. Please ask about enthusiasm for the bowling tournament."

[0094] Then, the template generation model 42 generates template questions 33 that take into account the current affairs information. For example, as shown in Fig. 26, when the current affairs information shown in Fig. 25 is input, a question that takes into account current affairs information 1 and a question that takes into account current affairs information 2 are generated. At this time, the input unit 21 may instruct the template generation model 42 to generate questions and answers based on the current events information after acquiring the current events information.

[0095] ***Effects of the Sixth Embodiment*** As described above, the attendance management device 10 according to the sixth embodiment inputs current affairs information when generating a template. This prevents the template questions 33 from always being similar and becoming outdated.

[0096] <Variation 4> In the first embodiment, each functional component is realized by software. However, as a fourth modification, each functional component may be realized by hardware. The following describes the differences between the first embodiment and the fourth modification.

[0097] When each functional component is realized by hardware, the attendance management device 10 has an electronic circuit 15 instead of the processor 11, memory 12, and storage 13. The electronic circuit 15 is a dedicated circuit for realizing the functions of each functional component, the memory 12, and the storage 13.

[0098] The electronic circuit 15 may be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, or an FPGA. GA stands for Gate Array. ASIC stands for Application Specific Integrated Circuit. FPGA stands for Field-Programmable Gate Array. Each functional component may be realized by one electronic circuit 15, or each functional component may be realized by distributing it among a plurality of electronic circuits 15.

[0099] <Variation 5> As a fifth modification, some of the functional components may be realized by hardware, and other functional components may be realized by software.

[0100] The processor 11, memory 12, storage 13, and electronic circuit 15 are collectively referred to as a processing circuit. In other words, the functions of the respective functional components are realized by the processing circuit.

[0101] Furthermore, the term "unit" in the above description may be read as a "circuit," "step," "procedure," "process," or "processing circuit."

[0102] Various aspects of the present disclosure are summarized below as appendices. (Appendix 1) an input unit that inputs attendance data indicating the working status of a subject into a question generation model that is a trained model; an output unit that outputs a model question, which is a question for confirming the state of the subject, generated by the question generation model in response to the attendance data input by the input unit; An attendance management device comprising: (Appendix 2) The attendance management device further includes: a question receiving unit that receives input of a specified question from an administrator of the subject, the specified question being a question for confirming the subject's status; Equipped with The output unit outputs the specified question accepted by the question accepting unit. Attachment 1. The attendance management device according to claim 1. (Appendix 3) the input unit inputs a plurality of question types into a template generation model that is a trained model; the output unit outputs template questions which are questions for confirming a state of the subject for each of the plurality of question types generated by the template generation model in correspondence with the plurality of question types; The question receiving unit receives input of a specified question generated by the administrator based on the template question. Attachment 2. The attendance management device according to claim 2. (Appendix 4) The attendance management device further includes: an answer receiving unit that receives an input of an answer to the model question output by the output unit; Equipped with the input unit inputs a pair of the answer and the model question received by the answer receiving unit into an advice generation model that is a trained model; The output unit outputs advice to be given to the administrator when the administrator deals with the subject, which advice is generated by the advice generation model in correspondence with the pair of the answer and the model question. Attachment 1. The attendance management device according to claim 1. (Appendix 5) The attendance management device further includes: an answer receiving unit that receives an input of an answer to the model question output by the output unit; Equipped with the input unit inputs the answer and the model question received by the answer receiving unit into an evaluation model that is a trained model; The output unit outputs an evaluation value of the subject's engagement with the organization to which the subject belongs, calculated by the evaluation model, corresponding to the pair of the answer and the model question. Attachment 1. The attendance management device according to claim 1. (Appendix 6) The input unit inputs an instruction to the evaluation model to calculate an evaluation value for a target type, which is at least one of a plurality of evaluation types related to engagement with an organization; The output unit outputs the evaluation value for the target type calculated by the evaluation model. 6. The attendance management device according to claim 5. (Appendix 7) the input unit inputs the evaluation value for the target type into an advice generation model that is a trained model; The output unit outputs advice to the subject that increases an evaluation value for the subject's object type, the advice being generated by the advice generation model in response to the evaluation value for the object type. 7. The attendance management device according to claim 6. (Appendix 8) the input unit inputs information about current events in addition to the types of the plurality of questions to the template generation model; The output unit outputs template questions, which are questions for each of the plurality of question types generated by the template generation model in correspondence with the plurality of question types and the information on current events. 4. The attendance management device according to claim 3. (Appendix 9) The computer inputs attendance data showing the working status of the subject into a trained question generation model, An attendance management method in which a computer outputs model questions, which are questions for confirming the status of the subject, generated by the question generation model in response to the attendance data. (Appendix 10) An input process for inputting attendance data indicating the working status of the subject into a trained question generation model; an output process for outputting a model question, which is a question for confirming the status of the subject, generated by the question generation model in response to the attendance data input by the input process; An attendance management program that causes a computer to function as an attendance management device that performs the following.

[0103] The embodiments and modifications of the present disclosure have been described above. Some of these embodiments and modifications may be combined and implemented. Also, one or more of them may be implemented partially. Note that the present disclosure is not limited to the above embodiments and modifications, and various modifications are possible as needed. [Explanation of symbols]

[0104] 10 Attendance management device, 11 Processor, 12 Memory, 13 Storage, 14 Communication interface, 21 Input unit, 22 Output unit, 23 Answer reception unit, 24 Question reception unit, 25 Adjustment reception unit, 31 Attendance data, 32 Question answer data, 33 Template question, 34 Specified question, 35 Evaluation data, 41 Question generation model, 42 Template generation model, 43 Advice generation model, 44 Evaluation model, 51 User terminal, 52 Administrator terminal.

Claims

1. an input unit that generates instructions that include attendance data indicating the working status of a subject and generation instructions that instruct the subject to generate questions to ask the subject in order to understand the working status of the subject based on the attendance data, and inputs the instructions into a question generation model that is a trained model; a question receiving unit that receives an input of a designated question from a manager of the subject, the designated question being a question for confirming the status of the subject; an output unit that outputs at least one of the model question generated by the question generation model and the specified question accepted by the question accepting unit to a user terminal used by the subject; Equipped with the input unit generates an instruction including a plurality of question types and a generation instruction for instructing generation of template questions, the template questions being questions that confirm the state of the subject for each of the plurality of question types, corresponding to the plurality of question types; and inputs the instruction to a template generation model that is a trained model; The question receiving unit receives input of the specified question generated by the manager based on the template question generated by the template generation model.

2. The attendance management device further includes: an answer receiving unit that receives an input of an answer to the model question output by the output unit; Equipped with the input unit inputs a pair of the answer and the model question received by the answer receiving unit into an advice generation model that is a trained model; The output unit outputs advice to be given to the administrator when the administrator deals with the subject, which advice is generated by the advice generation model in correspondence with the pair of the answer and the model question. The attendance management device according to claim 1 .

3. The attendance management device further includes: an answer receiving unit that receives an input of an answer to the model question output by the output unit; Equipped with the input unit inputs the answer and the model question received by the answer receiving unit into an evaluation model that is a trained model; The output unit outputs an evaluation value of the subject's engagement with the organization to which the subject belongs, calculated by the evaluation model, corresponding to the pair of the answer and the model question. The attendance management device according to claim 1 .

4. The input unit inputs an instruction to the evaluation model to calculate an evaluation value for a target type, which is at least one of a plurality of evaluation types related to engagement with an organization; The output unit outputs the evaluation value for the target type calculated by the evaluation model. The attendance management device according to claim 3.

5. the input unit inputs the evaluation value for the target type into an advice generation model that is a trained model; The output unit outputs advice to the subject that increases an evaluation value for the subject's object type, the advice being generated by the advice generation model in response to the evaluation value for the object type. The attendance management device according to claim 4.

6. the input unit inputs information about current events in addition to the types of the plurality of questions to the template generation model; The output unit outputs template questions, which are questions for each of the plurality of question types generated by the template generation model in correspondence with the plurality of question types and the information on current events. The attendance management device according to claim 1 .

7. A computer generates instructions that include attendance data indicating the working status of a subject and generation instructions that instruct the computer to generate questions to be asked of the subject based on the attendance data in order to understand the working status of the subject, and inputs the instructions into a question generation model that is a trained model; a computer generates instructions that describe a plurality of question types and generation instructions that instruct the computer to generate template questions that correspond to the plurality of question types and that confirm the state of the subject for each of the plurality of question types; and inputs the instructions into a template generation model that is a trained model; a computer receives an input of a specified question, which is a question for confirming the status of the subject, generated by an administrator based on the template question generated by the template generation model; An attendance management method in which a computer outputs at least one of a model question generated by the question generation model and the specified question to a user terminal used by the subject.

8. an input process of generating instructions that include attendance data indicating the working status of the subject and generation instructions that instruct the subject to generate questions to ask the subject in order to understand the subject's working status based on the attendance data, and inputting the instructions into a question generation model that is a trained model; a question receiving process for receiving input of a designated question from an administrator of the subject, the designated question being a question for confirming the subject's status; an output process of outputting at least one of the model question generated by the question generation model and the specified question accepted by the question acceptance process to a user terminal used by the subject; and the input process generates an instruction that describes a plurality of question types and a generation instruction that instructs generation of template questions that correspond to the plurality of question types and that confirm the state of the subject for each of the plurality of question types, and inputs the instruction to a template generation model that is a trained model; The question reception process receives input of the specified question generated by the administrator based on the template question generated by the template generation model. An attendance management program that enables a computer to function as an attendance management device.

Images