Schedule execution support device, method, and program

Abstract

In one aspect of this invention, a first evaluation value representing a degree of dispersion of required work time based on past work results of multiple personnel is calculated for each of the multiple tasks that make up a schedule, a second evaluation value representing a degree of dispersion of predicted values of required work time among the multiple personnel is calculated for each of the multiple tasks, and a degree of response to remuneration is estimated for each of the multiple tasks on the basis of the calculated first and second evaluation values. The result of estimating the degree of response is used to generate information indicating a priority level of remuneration for multiple target tasks constituting a critical path identified from the schedule, and output assistance information including information representing the generated priority level.

Description

[Technical Field]

[0001] One aspect of the present invention relates to a schedule execution support device, method, and program that support the execution of a schedule used in the development process of an object or system, for example. [Background technology]

[0002] In recent years, scheduling techniques used in the development of products and systems have been attracting attention. For example, Patent Document 1 describes a scheduling technique for assigning multiple personnel to multiple tasks with precedence constraints in the development process of a network management system or the like, taking into account the content of each task and the differences in the abilities of each personnel. Use of this technique is expected to minimize the overall development process period and the number of workers. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2017-211921 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the scheduling technology described in Patent Document 1 creates a fixed and deterministic schedule before development work begins, so if a delay occurs in one of the tasks while the schedule is being executed, it is not easy to absorb the impact of that delay in tasks on the critical path.

[0005] This invention has been made in light of the above circumstances, and aims to provide a technique that enables adaptive and effective shortening of a process period when it becomes necessary to shorten the process period during the execution of a schedule. [Means for solving the problem]

[0006] In order to solve the above problems, one aspect of a schedule execution support device or support method according to the present invention calculates, for each of a plurality of tasks constituting a schedule, a first evaluation value that represents the degree of dispersion of required task times based on past work performance of a plurality of personnel, and calculates, for each of the plurality of tasks, a second evaluation value that represents the degree of dispersion of predicted required task times among the plurality of personnel; For each of the plurality of tasks, the calculated the first evaluation value and The second evaluation value By calculating the average value of Then, based on the result of estimating the response level, information representing the priority of reward allocation for a plurality of target tasks that constitute the critical path identified from the schedule is generated, and support information including the generated information representing the priority is output.

[0007] According to one aspect of the present invention, when it becomes necessary to shorten the required time for a task on a critical path, it is possible to prioritize rewards for tasks on the critical path that have a high response rate to rewards. As a result, the required time for the task on the critical path can be effectively shortened, thereby enabling the required time for the entire schedule to be shortened without, for example, allocating additional personnel or by minimizing the allocation of additional personnel. Furthermore, the effect of reducing the required time relative to the amount of reward can be improved. [Effects of the Invention]

[0008] That is, according to one aspect of the present invention, it is possible to provide a technology that enables adaptive and effective shortening of a process period when it becomes necessary to shorten the process period during the execution of a schedule. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of the hardware configuration of a schedule execution support device according to an embodiment of the present invention. [Figure 2]FIG. 2 is a block diagram showing an example of the software configuration of the schedule execution support device according to an embodiment of the present invention. [Figure 3] FIG. 3 is a flowchart showing an example of the processing procedure and processing contents of the schedule execution support processing executed by the control unit of the schedule execution support device shown in FIG. [Figure 4] FIG. 4 is a diagram showing an example of the variance of the required time of a worker in a task with a small variance. [Figure 5] FIG. 5 is a diagram showing an example of the variance of the required time of a worker in a task with a large variance. [Figure 6] FIG. 6 is a diagram showing an example of a required time volatility coefficient that indicates how much the required time varies for each task (standard deviation of the rate of change). [Figure 7] FIG. 7 is a diagram illustrating an example of a critical path extracted from task allocation information. [Figure 8] FIG. 8 is a diagram showing an example of the required time volatility coefficient, task commodity coefficient, and reward reaction coefficient calculated for each task on the critical path shown in FIG. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] [One embodiment] (overview) In one embodiment of the present invention, when a delay occurs in any task during the execution of a schedule, and the impact of the delay needs to be absorbed by shortening the work time of a task on the critical path, a reward is given to the worker assigned to the task.

[0012] In this case, the system estimates the degree of responsiveness to rewards for each task, focusing on the fact that tasks with a higher proportion of human work are more sensitive to rewards, and that tasks with a higher proportion of human work have a larger variance in the estimated skill time required for each task and a larger discrepancy between the estimated required time and the actual required time. Specifically, for each task, an evaluation value of the degree of variance in the required time based on the worker's past work performance and an evaluation value of the degree of variance in the predicted required time between workers are calculated, and the degree of responsiveness to rewards for each task is calculated based on the obtained evaluation values. Then, based on the above calculation results, information indicating the priority of reward assignment for each task on the critical path is generated and output to, for example, a manager.

[0013] By doing this, for example, when it becomes necessary to shorten the work time of a task on the critical path, it becomes possible to give priority to the task on the critical path that has a high degree of response to the reward. As a result, the work time of the task on the critical path can be effectively shortened, which makes it possible to shorten the work time of the entire process without, for example, allocating additional personnel or by minimizing this. In addition, it is possible to increase the effect of shortening the work time relative to the amount of reward.

[0014] (Configuration example) 1 and 2 are block diagrams showing an example of the hardware configuration and software configuration, respectively, of a schedule execution support device according to an embodiment of the present invention.

[0015] The schedule execution support device SV is composed of a personal computer used by a manager who manages schedules related to system development or product development, for example. Note that the schedule execution support device SV is not limited to a personal computer, but may also be a server computer located on a local network such as a LAN (Local Area Network), or on the Web or cloud.

[0016] The schedule execution support device SV has a control unit 1 that uses a hardware processor such as a central processing unit (CPU), and this control unit 1 is connected to a memory unit having a program memory unit 2 and a data memory unit 3, and an input / output interface (hereinafter the interface will be referred to as I / F) unit 4 via a bus 5.

[0017] An input device 51 and an output device 52 are connected to the input / output I / F unit 4. The input device 51 includes, for example, a keyboard, a mouse, and operation buttons. The input device 51 is used by the administrator to input various information necessary for receiving support regarding the execution of the development schedule to be managed.

[0018] The output device 52 includes, for example, a display, and is used to display various information input by the administrator and support information generated by the control unit 1. The output device 52 may also include a printer, an external storage medium, etc.

[0019] The input / output I / F unit 4 may also have a communication interface function for transmitting and receiving information data to and from other information processing devices such as terminal devices and server devices via a network.

[0020] The program storage unit 2 is configured by combining, for example, a non-volatile memory such as a solid-state drive (SSD) as a storage medium that can be written to and read from at any time, and a non-volatile memory such as a read-only memory (ROM), and stores middleware such as an operating system (OS), as well as application programs required to execute various control processes according to one embodiment. Hereinafter, the OS and each application program will be collectively referred to as the program.

[0021] The data storage unit 3 is, for example, a combination of a non-volatile memory such as an SSD that can be written to and read from at any time as a storage medium, and a volatile memory such as a RAM (Random Access Memory), and is equipped with a forecast information storage unit 31, a performance information storage unit 32, a reward response coefficient storage unit 33, a job allocation information storage unit 34, and a critical path information storage unit 35 as the main storage units required to implement one embodiment of the present invention.

[0022] The prediction information storage unit 31 is used to store input prediction values ​​of the time required for each task for each worker. The actual performance information storage unit 32 is used to store input actual values ​​of the time required for each task for each worker. The reward response coefficient storage unit 33 is used to store reward response coefficients for each task calculated by the control unit 1. The task assignment information storage unit 34 is used to store input task assignment information in the development schedule. The critical path information storage unit 35 is used to store information generated by the control unit 1 that represents the critical path in the development schedule.

[0023] The control unit 1 includes, as processing functions used to implement one embodiment of the present invention, a forecast information acquisition processing unit 11, a business commodity coefficient calculation processing unit 12, a performance information acquisition processing unit 13, a required time volatility coefficient calculation processing unit 14, a reward reaction coefficient calculation processing unit 15, a business allocation information acquisition processing unit 16, a critical path information generation processing unit 17, an additional reward priority list generation processing unit 18, and a support information output processing unit 19.

[0024] These processing units 11 to 19 are all realized by causing the hardware processor of the control unit 1 to execute application programs stored in the program storage unit 2 .

[0025] Note that part or all of the processing units 11 to 19 may be realized using hardware such as an LSI (Large Scale Integration) or an ASIC (Application Specific Integrated Circuit).

[0026] The prediction information acquisition processing unit 11 acquires, via the input / output I / F unit 4, a task-specific required time prediction table for each worker input by the manager via the input device 6, and stores the acquired prediction table in the prediction information storage unit 31. The task-specific required time prediction table for each worker is a table showing predicted values ​​of required time for work set by the manager for each task based on the skills and past performance of each worker, etc.

[0027] The task commodity coefficient calculation processing unit 12 calculates a task commodity coefficient based on the task-specific required time prediction table for each worker stored in the prediction information storage unit 31. The task commodity coefficient is calculated by calculating the variance of the predicted values ​​of task-specific required time for each worker for all tasks, and then calculating a deviation value for each task based on the calculated variance.

[0028] The performance information acquisition processing unit 13 acquires, via the input / output I / F unit 4, a past performance table of the time required for each task for each worker, which is input by the manager via the input device 6, and stores the acquired performance table in the performance information storage unit 32. The performance table of the time required for each task for each worker is a table showing the performance values ​​of the work time for each task for each worker based on the execution results of past work schedules.

[0029] The required time volatility coefficient calculation processing unit 14 calculates the required time volatility coefficient for each task based on the task-specific required time actual result table for each worker stored in the performance information storage unit 32. The required time volatility coefficient is calculated by calculating the variance of the actual measured values ​​of the task-specific required time for each worker for all tasks, and then calculating the standard deviation for each task based on the calculated variance.

[0030] Reward reaction coefficient calculation unit 15 calculates the arithmetic mean of the business commodity coefficient calculated by business commodity coefficient calculation unit 12 and the required time volatility coefficient calculated by required time volatility coefficient calculation unit 14 for each business, and sets the arithmetic mean as the reward reaction coefficient for each business. This reward reaction coefficient is then stored in reward reaction coefficient storage unit 33 in association with the business identification information.

[0031] The task assignment information acquisition processing unit 16 acquires task assignment information input by the manager using the input device 6 via the input / output I / F unit 4, and stores the acquired task assignment information in the task assignment information storage unit 34. The task assignment information is information that indicates the results of worker assignment to each task when a management schedule is created.

[0032] The critical path information generation processing unit 17 identifies a critical path from the task allocation information stored in the task allocation information storage unit 34, and stores information representing the identified critical path in the critical path information storage unit 35.

[0033] The additional reward priority list generation processing unit 18 reads the reward response coefficient from the reward response coefficient storage unit 33 for each task that makes up the critical path stored in the critical path information storage unit 35, and generates an additional reward priority list by sorting the tasks that make up the critical path in descending order of the read reward response coefficient.

[0034] The support information output processing unit 19 generates support information including the additional reward priority list generated by the additional reward priority list generation processing unit 18, and outputs the generated support information from the input / output I / F unit 4 to the output device 7.

[0035] (Example of operation) Next, an example of the operation of the schedule execution support device SV configured as above will be explained. FIG. 3 is a flowchart showing an example of the processing procedure and processing contents of the support processing executed by the control unit 1 of the schedule execution support device SV.

[0036] (1) Obtaining forecast information For example, prior to executing a development schedule, the manager calculates a predicted value of the time required for each task that makes up the development schedule, referring to each worker's skills, past performance, etc. Then, following an input request, a worker task-specific time required prediction table showing the results is input from the input device 6.

[0037] In response to this, the control unit 1 of the schedule execution support device SV is in a standby state and monitors input requests for forecast information in step S10. When the input request is input from the input device 6 in this state, under the control of the forecast information acquisition processing unit 11, in step S11 the worker task required time prediction table is acquired via the input / output I / F unit 4 and the acquired worker task required time prediction table is stored in the forecast information storage unit 31.

[0038] The process of acquiring the worker task-specific required time prediction table may be performed by, for example, downloading the worker task-specific required time prediction table stored in advance in a schedule execution server (not shown) or the like via a network.

[0039] (2) Acquisition of performance information The manager collects the actual values ​​of the time required for each task by each worker for each task that makes up the development schedule based on the results of past task schedule execution, and inputs a table showing the collected actual values ​​of the time required for each task by the workers from the input device 6 following an input request.

[0040] In response to this, the control unit 1 of the schedule execution support device SV is in a standby state and monitors input requests for performance information in step S12. When the input request is input from the input device 6 in this state, under the control of the performance information acquisition processing unit 13, in step S14 the table of required time performance by worker task is acquired via the input / output I / F unit 4 and the acquired table of required time performance by worker task is stored in the performance information storage unit 32.

[0041] The process of acquiring the table of actual required time by worker task may also be performed by downloading it via a network such as a schedule execution server.

[0042] (3) Acquisition of task allocation information The manager also inputs information indicating the allocation of workers to each task set in the development schedule that is about to be executed, that is, task allocation information, from the input device 6 along with an input request.

[0043] In response to this, the control unit 1 of the schedule execution support device SV, in a standby state, monitors the input request for the above task assignment in step S15. When the input request is input from the input device 6 in this state, under the control of the task assignment information acquisition processing unit 16, in step S15 the above task assignment information is acquired via the input / output I / F unit 4 and the acquired task assignment information is stored in the task assignment information storage unit 34.

[0044] (4) Generate and output the additional reward priority list If a delay occurs in a certain task during the execution of the development schedule, and it becomes necessary to absorb this delay by shortening the work time of a task on the critical path, the manager will input a support request to the input device 6 to receive support for shortening the time of the process in the development schedule.

[0045] In response to this, the control unit 1 of the schedule execution support device SV monitors the input of the above support request in step S16 while in a standby state, and when the above support request is input in this state, it executes support processing to shorten the process time as follows.

[0046] (4-1) Calculation of business commodity coefficient The control unit 1 of the schedule execution support device SV first reads the task-specific required time prediction table for each worker from the prediction information storage unit 31 in the task commodity coefficient calculation processing unit 12. Then, based on the read task-specific required time prediction table for each worker, the control unit 1 calculates the task commodity coefficient for each task. This task commodity coefficient is calculated by calculating the variance of the predicted values ​​of the task-specific required time for each worker for all tasks, and then calculating the deviation value for each task based on the calculated variance.

[0047] (4-2) Calculation of the required time volatility coefficient The control unit 1 of the schedule execution support device SV then reads the task-specific required time actual result table of each worker from the actual result information storage unit 32 in the required time volatility coefficient calculation processing unit 14. Then, based on the read task-specific required time actual result table of each worker, the control unit 1 calculates the required time volatility coefficient for each task. This required time volatility coefficient is calculated by calculating the variance of the actual values ​​of the task-specific required time of each worker for all tasks, and then calculating the deviation value for each task based on the calculated variance.

[0048] The standard deviation of the task time required for each task can be calculated as the square root of the positive value obtained by adding up the squared value of the difference between the target data's required time value and its average, and then dividing the sum by the total number of target data.

[0049] For example, as shown in Figure 4, for task A, where the variance in the time required for each worker's task is small, the standard deviation (σ) is a small value of 7.5 minutes. On the other hand, as shown in Figure 5, for task A, where the variance in the time required for each worker's task is large, the standard deviation (σ) is a large value of 17.1 minutes. The relationship between the standard deviation calculated for each task and frequency can be shown, for example, in Figure 6, from which the deviation value for each of tasks A and B, that is, the time required volatility coefficient, can be calculated. In the example of Figure 6, the deviation value (time required volatility coefficient) for task A is "30," and the deviation value (time required volatility coefficient) for task B is "70."

[0050] (4-3) Calculation of reward response coefficient Next, in step S17, the control unit 1 of the schedule execution support device SV calculates, for each task, an arithmetic average value of the task commodity coefficient calculated by the task commodity coefficient calculation unit 12 and the required time volatility coefficient calculated by the required time volatility coefficient calculation unit 14 under the control of the reward reaction coefficient calculation unit 15. The reward reaction coefficient calculation unit 15 then stores the calculated arithmetic average value in the reward reaction coefficient storage unit 33 as the reward reaction coefficient for each task.

[0051] (4-4) Generating critical path information Next, in step S18, the control unit 1 of the schedule execution support device SV reads task assignment information from the task assignment information storage unit 34 under the control of the critical path information generation processing unit 17, and identifies a critical path based on this task assignment information. Then, the critical path information generation processing unit 17 stores information representing the identified critical path in the critical path information storage unit 35.

[0052] Fig. 7 shows an example of an identified critical path. In this example, the critical path CP is expressed as process route information indicating that the processes are executed in the order of Task A, Task B, Task D, and Task F. Meanwhile, Fig. 8 shows an example of the required time volatility coefficient, task commodity coefficient, and reward response coefficient calculated for each of the tasks A, B, D, and F on the critical path CP.

[0053] (4-5) Generate a priority list for additional rewards Next, in step S19, the control unit 1 of the schedule execution support device SV reads the critical path information from the critical path information storage unit 35 under the control of the additional reward priority list generation processing unit 18. Then, the additional reward priority list generation processing unit 18 reads the reward response coefficients for each of the tasks A, B, D, and F that make up the read critical path from the reward response coefficient storage unit 33. Then, the additional reward priority list is generated by sorting the tasks A, B, D, and F on the critical path CP in descending order of the reward response coefficients.

[0054] (4-6) Output of support information Finally, in step S20, the control unit 1 of the schedule execution support device SV generates support information including, for example, a corresponding message based on the additional remuneration priority list generated by the additional remuneration priority list generation processing unit 18 under the control of the support information output processing unit 19. Then, the generated support information is output from the input / output I / F unit 4 to the output device 7.

[0055] As a result, the support information is displayed on the output device 7. The support information may be printed out from the output device 7, or may be stored in a storage medium and then displayed or printed out on another terminal or the like.

[0056] Based on the support information provided, the manager identifies the task with the highest reward response coefficient among tasks A, B, D, and F on the critical path CP, and then provides additional reward to the worker in charge of this task.

[0057] The recipient of the additional reward is not limited to the worker in charge of the task with the highest reward response coefficient, but may be all workers in charge of tasks A, B, D, and F on the critical path CP, or multiple workers selected from among them. When additional rewards are awarded to multiple workers in this manner, the amount of reward may be differentiated, for example, according to an additional reward priority list, so that the higher the priority of the task, the higher the reward amount. This can significantly reduce time while keeping the total amount of additional rewards low. In addition, possible types of rewards include cash, virtual currency, points, merchandise, and personnel evaluation scores, and can be set arbitrarily depending on the type of task, the worker's employment status, and other factors.

[0058] (Actions and Effects) As described above, in one embodiment, the system acquires predicted values ​​of the required time for each task for each worker and actual values ​​of the required time for each task for each worker based on past schedule execution results, and also acquires task allocation information corresponding to the scheduled development schedule. In this state, if, for example, a task on the critical path needs to be shortened due to a delay in the task, the system calculates a task commodity coefficient and a required time volatility coefficient, which represent the degree of variability in the time required by each worker for each task, based on the predicted values ​​of the required time for each worker's task and the actual values ​​of the required time for each worker's task, and then calculates a reward response coefficient for each task based on the calculated coefficients. The system then generates an additional reward priority list in which the tasks on the critical path identified from the task allocation information are sorted in descending order of the reward response coefficient, and outputs support information including this list.

[0059] Therefore, among the tasks on the critical path, tasks that are sensitive to rewards are estimated, and an additional reward priority list is output, in which the estimated tasks are given a high reward priority. This allows the manager to determine which tasks on the critical path should be rewarded based on the list, and then award the rewards accordingly. This effectively reduces the work time for tasks on the critical path, thereby enabling the work time for the entire schedule to be reduced, for example, without or with a minimum of additional personnel assignments.

[0060] In one embodiment, when it becomes necessary to shorten the working time of a task, a series of processes are performed to calculate the required time volatility coefficient, task commodity coefficient, and reward response coefficient only for each task on the critical path identified from the task allocation information. This makes it possible to reduce the processing load on the control unit 1 compared to when the required time volatility coefficient, task commodity coefficient, and reward allocation coefficient are calculated for all tasks on the development schedule.

[0061] [Other embodiments] (1) In the embodiment, the processing by each of the processing units 11 to 19 included in the control unit 1 of the schedule execution support device SV is performed by a single personal computer. However, the processing by each of the processing units 11 to 19 may be distributed and performed by a plurality of information processing devices such as personal computers and servers.

[0062] (2) In one embodiment, forecast information, performance information, and task allocation information are acquired in advance and stored in the storage units 31, 32, and 34, respectively. However, when it becomes necessary to provide additional rewards, only the necessary information may be acquired from the schedule execution server, etc. This makes it possible to save the storage capacity of the storage unit 3 of the schedule execution support device SV.

[0063] (3) In addition, the configuration and processing functions of the schedule execution support device, the processing procedures and contents, the configuration of the support information, the types of remuneration, etc. can be modified and implemented in various ways without departing from the spirit of this invention.

[0064] Although the embodiments of the present invention have been described in detail above, the above description is merely an example of the present invention in every respect. It goes without saying that various improvements and modifications can be made without departing from the scope of the present invention. In other words, when implementing the present invention, specific configurations according to the embodiments may be appropriately adopted.

[0065] In short, this invention is not limited to the above-described embodiments, and in the implementation stage, the components can be modified and embodied without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining multiple components disclosed in the above-described embodiments. For example, some components may be omitted from all the components shown in the embodiments. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0066] SV: Schedule execution support device 1...Control unit 2...Program memory section 3...Data storage unit 4...Input / output interface 5...Bus 6. Input Device 7. Output device 11...Prediction information acquisition processing unit 12...Business commodity coefficient calculation processing unit 13...Actual performance information acquisition processing unit 14... Required time volatility coefficient calculation processing unit 15...Reward response coefficient calculation processing unit 16...Business assignment information acquisition processing unit 17...Critical path information generation processing unit 18...Additional reward priority list generation processing unit 19...Support information output processing unit 31...Prediction information storage unit 32...Actual performance information storage unit 33...Reward response coefficient memory unit 34...Work allocation information storage unit 35...Critical path information storage unit

Claims

1. A schedule execution support device that supports the execution of a schedule that allocates personnel to a plurality of tasks and executes predetermined processes, a first processing unit that calculates a first evaluation value representing a degree of variance in required work time for each of the plurality of tasks based on past work performance of a plurality of personnel; a second processing unit that calculates a second evaluation value representing a degree of dispersion of predicted values ​​of required work times among the plurality of personnel for each of the plurality of tasks; a third processing unit that calculates an arithmetic average of the first evaluation value and the second evaluation value for each of the plurality of tasks to estimate a degree of response to a reward for each of the tasks; a fourth processing unit that identifies a critical path that determines an overall required time for the work from the schedule; a fifth processing unit that generates information representing priorities of rewards for the plurality of target tasks constituting the critical path based on the estimation result of the degree of response, and outputs support information including the generated information representing the priorities; A schedule execution support device comprising:

2. 2. The schedule execution support device according to claim 1, wherein the first processing unit calculates, as the first evaluation value, a required time volatility coefficient representing a standard deviation of a rate of change in the required task time among the plurality of tasks, based on a degree of variance of the required task time based on past work performance of a plurality of personnel for each of the plurality of tasks.

3. 2. The schedule execution support device according to claim 1, wherein the second processing unit calculates, as the second evaluation value, a task commodity coefficient representing a deviation value of the predicted value of the required task time among the plurality of tasks, based on a degree of dispersion of the predicted values ​​of the required task time among the plurality of personnel for each of the plurality of tasks.

4. the first processing unit and the second processing unit calculate the first evaluation value and the second evaluation value for the plurality of target tasks that make up the critical path, respectively; The third processing unit calculates an arithmetic average of the first evaluation value and the second evaluation value to estimate the degree of response to a reward for each of the plurality of target tasks constituting the critical path.

2. The schedule execution support device according to claim 1.

5. A schedule execution support method executed by a device that supports execution of a schedule that allocates personnel to a plurality of tasks and executes predetermined processes, comprising: calculating a first evaluation value representing a degree of variance in required task times for each of the plurality of tasks based on past work performance of a plurality of personnel; calculating a second evaluation value representing a degree of dispersion of predicted values ​​of required task times among the plurality of personnel for each of the plurality of tasks; a step of estimating a degree of response to a reward for each of the plurality of tasks by calculating an arithmetic average of the first evaluation value and the second evaluation value for each of the plurality of tasks; A process of identifying a critical path that determines the overall work time from the schedule; generating information representing the priority of rewards for the plurality of target tasks constituting the critical path based on the estimation result of the degree of response, and outputting support information including the generated information representing the priority; A schedule execution support method comprising:

6. 5. A program for causing a processor included in the schedule execution support device to execute all of the processes of the first to fifth processing units included in the schedule execution support device according to claim 1.

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