JP2009276982A - Project management device, project management method for project management device, and project management program for project management device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a project management device capable of using a probability distribution model corresponding to the level of the risk of an operation in the progress prediction of an operation. <P>SOLUTION: In a project management device 100 which manages operating situations, a plan management part 100a associates the types of risks for each operation and stores them as a project information part 30, and a risk management part 100c associates the type of risk with risk evaluation information for calculating the level of the risk and stores it as a risk information part 31, and a probability distribution database part 100d stores a plurality of probability distribution models preliminarily defined according to the level of the risk, and a plan prediction part 100b acquires the risk evaluation information corresponding to the type of the risk corresponding to an operation acquired from the project information part 30, and calculates the level of the risk on the basis of the risk evaluation information, and creates the probability distribution of the operating situations by using the probability distribution model corresponding to the level of the risk selected from the probability distribution database part 100d. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a project management apparatus that manages a project, and more particularly to a project management apparatus that can use a probability distribution that differs for each operation when project prediction is performed.

In a conventional project management apparatus, when a project is predicted, one probability distribution (statistical probability distribution of the organization) statistically calculated as an organization is defined as a probability distribution used for progress prediction. (See Patent Document 1). However, the statistical probability distribution of an organization may vary from project to project.
JP 2003-345958 A

  In conventional project management devices, when a project is predicted using a statistical probability distribution model of an organization, risks different from the same work of other projects in software development and hardware development are not considered in the probability distribution model. For this reason, it is difficult to make predictions according to the actual situation. When multiple projects are operating in an organization, there can be the same work for different projects (for example, there are A project and B project, both of which are related to system development, the same work (system design , Program development, etc.)). In this case, even if the work is the same, the risk may differ depending on the project, so that the same probability distribution model is used for prediction even if the work is the same as in the conventional project management device. If it does, it will be difficult to make predictions that match the actual situation.

  The present invention was made to solve the above-mentioned problems, and it is intended to define a relationship between different risks in the same work and a statistical probability distribution of the organization and to make a prediction according to the actual situation. To do.

The project management apparatus according to the present invention is:
In a project management apparatus that manages a work situation for each of the plurality of works for a project composed of a plurality of works,
A plan management unit that stores in a storage device as project information in association with a type of risk that is predicted to occur for each of the plurality of operations;
A risk management unit that stores risk information in a storage device in association with risk evaluation information for calculating a risk type and a risk magnitude;
A probability distribution database unit for storing a plurality of pre-defined probability distribution models according to the size of the risk;
For each of the plurality of operations, the risk type corresponding to the operation is acquired from the project information stored by the plan management unit, and the risk type is acquired from the risk information stored by the risk management unit. Obtain risk assessment information, calculate a risk magnitude by the processing device based on the obtained risk assessment information, and select a probability distribution model corresponding to the computed risk magnitude from the probability distribution database unit And a plan predicting unit that generates a probability distribution of the work status of the work by the processing device using the selected probability distribution model.

  According to the present invention, in a project management apparatus that manages a work situation for each of a plurality of works for a project composed of a plurality of works, the plan management unit determines the type of risk that is predicted to occur for each of the plurality of works. Correspondingly stored in the storage device as project information, the risk management unit stores the risk type information and risk evaluation information for calculating the risk magnitude in association with each other and stored in the storage device as a probability distribution database unit Stores a plurality of pre-defined probability distribution models according to the size of the risk, and the plan prediction unit obtains the type of risk corresponding to the work from the project information for each of the plurality of work, and the risk information from the risk information. Obtain risk assessment information corresponding to the type, and calculate the risk size based on the obtained risk assessment information The probability distribution model corresponding to the calculated risk size is selected from the probability distribution database unit, and the probability distribution of the work status of the work is generated using the selected probability distribution model. It is possible to select a statistical probability distribution of the organization that is linked to the depth, and it is possible to perform highly accurate prediction that matches the actual situation.

  FIG. 1 is a diagram illustrating an example of an appearance of a project management apparatus 100 according to the first embodiment. In FIG. 1, a project management apparatus 100 includes a system unit 910, a display device 901 having a CRT (Cathode / Ray / Tube) or LCD (liquid crystal) display screen, a keyboard 902 (Key / Board: K / B), and a mouse 903. , FDD904 (Flexible Disk Drive), compact disk device 905 (CDD), printer device 906, scanner device 907, and the like, and these are connected by cables and signal lines.

  The system unit 910 is a computer, and is connected to the facsimile machine 932 and the telephone 931 via a cable, and is connected to the Internet 940 via a local area network 942 (LAN) and a gateway 941.

  FIG. 2 is a diagram illustrating an example of hardware resources of the project management apparatus 100 according to the embodiment described below.

  In FIG. 2, the project management apparatus 100 includes a CPU 911 (also referred to as a central processing unit, a central processing unit, a processing unit, a processing unit, a microprocessor, a microcomputer, and a processor) that executes a program. The CPU 911 includes a ROM 913, a RAM 914, a communication board 915 (an example of a communication device, a transmission device, and a reception device), a display device 901, a keyboard 902, a mouse 903, an FDD904, a CDD905, a printer device 906, a scanner device 907, via a bus 912. It is connected to a magnetic disk device 920 and controls these hardware devices. Instead of the magnetic disk device 920, a storage device such as an optical disk device or a memory card read / write device may be used.

  The RAM 914 is an example of a volatile memory. The storage media of the ROM 913, the FDD 904, the CDD 905, and the magnetic disk device 920 are an example of a nonvolatile memory. These are examples of a storage device or a storage unit.

  The communication board 915, the keyboard 902, the scanner device 907, the FDD 904, and the like are examples of an input unit and an input device.

  Further, the communication board 915, the display device 901, the printer device 906, and the like are examples of an output unit and an output device.

  Although not shown, the communication board 915 is connected to a facsimile machine, a telephone set, a LAN, and the like. The communication board 915 may be connected not only to the LAN but also to a WAN (wide area network) such as the Internet or ISDN.

  The magnetic disk device 920 stores an operating system 921 (OS), a window system 922, a program group 923, and a file group 924. The programs in the program group 923 are executed by the CPU 911, the operating system 921, and the window system 922.

  The program group 923 stores programs for executing functions described as “˜unit” and “˜means” in the description of the embodiments described below. The program is read and executed by the CPU 911.

  The file group 924 includes “risk information section (risk information)”, “project information section (project information)”, “probability distribution database section”, “project prediction result section”, etc. Information, data, signal values, variable values, and parameters described as “determination results”, “calculation results”, and “processing results of” are “˜file”, “˜database”, It is stored as each item of “˜data”. “˜file”, “˜database”, and “˜data” are stored in a recording medium such as a disk or a memory. Information, data, signal values, variable values, and parameters stored in a storage medium such as a disk or memory are read out to the main memory or cache memory by the CPU 911 via a read / write circuit, and extracted, searched, referenced, compared, Used for CPU operations such as calculation, calculation, processing, output, printing, and display. Information, data, signal values, variable values, and parameters are temporarily stored in the main memory, cache memory, and buffer memory during the CPU operations of extraction, search, reference, comparison, operation, calculation, processing, output, printing, and display. Is remembered.

  In addition, the arrows in the flowcharts described in the following description of the embodiments mainly indicate input / output of data and signals. The data and signal values are the RAM 914 memory, the FDD 904 flexible disk, the CDD 905 compact disk, and the magnetic field. The data is recorded on a recording medium such as a magnetic disk of the disk device 920, another optical disk, a mini disk, or a DVD (Digital Versatile Disk). Data and signals are transmitted online via a bus 912, signal lines, cables, or other transmission media.

  Further, in the description of the embodiment described below, what is described as “˜unit” such as “plan management unit”, “plan prediction unit”, “risk management unit”, etc. is “˜circuit”, “˜device”, It may be “˜apparatus” and “means”, and may be “˜step”, “˜procedure”, and “˜processing”. That is, what is described as “˜unit” may be realized by firmware stored in the ROM 913. Alternatively, it may be implemented only by software, only hardware such as elements, devices, substrates, wirings, etc., or a combination of software and hardware, and further a combination of firmware. Firmware and software are stored as programs in a recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, and a DVD. The program is read by the CPU 911 and executed by the CPU 911. That is, the program causes the computer to function as “to part” described below. Alternatively, the procedure or method of “to part” described below is executed by a computer.

Embodiment 1 FIG.
In the present embodiment, a project management apparatus 100 that manages the work status of a work that is a project in an organization and that is a project composed of a plurality of work will be described. In particular, the project management apparatus 100 that can predict a project using a probability distribution that differs for each work when the project management apparatus 100 predicts a project for each of a plurality of works will be described.

  Project management (project management) refers to a method of managing the overall progress by adjusting human resources, funds, equipment, supplies, and schedules in a balanced manner to achieve the goals given to the team. In project management, as one method for making a plan, a configuration diagram called WBS (Work, Breakdown, Structure), which is an entire project divided into detailed operations, is used. Here, each of the plurality of operations in the project indicates, for example, each operation when a project defined in the WBS is broken down into detailed operations.

  Project management refers to, for example, predicting the work status of a work and proceeding the project in a better direction while modifying the work plan based on the prediction result. The project management apparatus 100 according to the present embodiment, for example, regarding the work status of the work to be predicted, for example, work quality (Q: Quality), cost (C: Cost), process (delivery date (D: Date)), etc. Make a prediction.

  In project management, when the work situation is predicted, the work situation is predicted based on the probability distribution model. For example, the prediction of the date when the A work ends in the project is to apply the plan value of the day when the A work ends to the probability distribution model to generate a probability distribution on the day when the A work ends. The probability distribution model may use a statistically calculated one based on the past data of the organization in which the project is conducted, or a statistically defined probability distribution (eg, normal distribution). May be used.

  FIG. 3 is a block configuration diagram showing functional blocks of the project management apparatus 100 according to the first embodiment. The block configuration in FIG. 3 indicates the minimum unit block configuration in the project management apparatus 100. Each functional block of the project management apparatus 100 according to the first embodiment will be described with reference to FIG.

  In FIG. 3, the project management apparatus 100 includes a plan management unit 100a, a plan prediction unit 100b, and a risk management unit 100c. In addition, the project management apparatus 100 stores the project information unit 30, the risk information unit 31, the probability distribution database unit 100d, and the project prediction result unit 40 in a storage device.

  Here, the plan management unit 100a, the plan prediction unit 100b, and the risk management unit 100c are implemented only by hardware such as elements, devices, substrates, and wiring. Alternatively, it may be realized by firmware stored in the ROM 913. Alternatively, a combination of software and hardware, or a combination of firmware may be used. In the case of firmware or software, the program is stored in a recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, and a DVD. The program is read by the CPU 911 and executed by the CPU 911.

  The probability distribution database unit 100d stores a plurality of probability distribution models defined in advance according to the magnitude of risk. The probability distribution database unit 100d is a storage unit stored in a storage device included in the project management apparatus 100. Although FIG. 3 shows a storage device different from the storage device in which the project information unit 30 and the risk information unit 31 are stored, they may be stored in the same storage device. Also, different storage devices may be used. The probability distribution model defined in advance according to the magnitude of the risk is a statistical probability distribution model of the organization defined in conjunction with the magnitude of the risk. A risk is a danger that is considered to occur. For example, with respect to the work “design”, there is considered a risk of occurrence of “insufficient personnel”, “insufficient skills”, etc., that is, risks.

  FIG. 4 is a diagram showing an image 201 of a statistical probability distribution model of an organization defined in conjunction with the risk magnitude according to the first embodiment. The organization statistical probability distribution model used by the project management apparatus 100 according to the present embodiment will be described with reference to FIG. The statistical probability distribution model of an organization is a probability distribution model used for project prediction by an organization that manages the project (to which the project belongs). As described above, the statistical probability distribution model of the organization may be a probability distribution model calculated from the past data of the organization to which the project belongs, or may be statistically defined as a normal distribution, for example. It may be a probability distribution model.

  In the image 201 of the statistical probability distribution model of the organization linked to the risk magnitude in the present embodiment, as shown in FIG. 4, the risk magnitude is classified into a plurality of categories (high risk, medium risk, and low risk). (3 levels). Here, the risk magnitude classification is made into three stages, but the risk magnitude classification is not limited to three stages. For example, it is considered that the accuracy of prediction is further improved by dividing the risk category into three or more levels (for example, five levels). However, if the risk level is set too high, the original data for statistical processing for generating the probability distribution model also becomes enormous. Therefore, ideally, it is preferable to divide into stages where the original data can be processed as linear values.

  In the image 201 of the statistical probability distribution model of the organization linked to the magnitude of the risk, the probability distribution model 20a corresponds to the large risk, the probability distribution model 20b corresponds to the medium risk, and the small risk Corresponds to the probability distribution model 20c. In this way, in the image 201 of the statistical probability distribution model of the organization linked to the magnitude of the risk shown in FIG. 4, when the risk is small, the deviation from the general case to the best or worst becomes small and the risk is large. Sometimes it shows a large deviation from the general case to the best or worst.

  Moreover, in each probability distribution model 20a, 20b, 20c, the vertical lines on both sides indicate the maximum value and the minimum value in the magnitude of the corresponding risk. Further, in each probability distribution model 20a, 20b, 20c, black thick line portions (black belt portions) 20d, 20e, 20f cover, for example, 99.73% of the entire probability distribution models 20a, 20b, 20c. The range of 6σ in the normal distribution is shown. Here, the overall coverage shown by the black belt portions 20d, 20e, and 20f is 99.73%, which is 6σ of the normal distribution, but this value is arbitrary depending on the actual state of the organization or the statistical data of the past of the organization. It does not indicate that it is always 99.73% of 6σ. In addition, in the image 201 of the statistical probability distribution model of the organization linked to the risk size shown in FIG. 4, it is shown that the value of the general case is always the same regardless of the risk size. It is not a thing.

  The image 201 of the statistical probability distribution model of the organization linked to the magnitude of the risk has a small deviation from the general case to the best or worst when the risk is small, and the best from the general case when the risk is large. It is a conceptual diagram showing that it is easier to manage by dividing the magnitude of the risk step by step because the deviation to the worst is large. In addition, by managing the risk size in stages, the project management apparatus 100 can select a probability distribution model corresponding to the risk, and perform prediction using the probability distribution model corresponding to the risk. By performing, it is possible to perform prediction with higher accuracy.

  FIG. 5 is a diagram illustrating an example of the configuration of the probability distribution database unit 100d according to the first embodiment. The probability distribution database unit 100d has a configuration shown in the image 201 of the statistical probability distribution model of the organization linked to the risk size in FIG. 4 according to the risk size (large risk, medium risk, small risk). The probability distribution models 20a, 20b, and 20c are defined and stored in advance. The probability distribution database unit 100d may store a probability distribution model 20 corresponding to the magnitude of risk for each work (for example, for each “design”, “development”, and “test”). Alternatively, the probability distribution database unit 100d may store a probability distribution model 20 corresponding to the magnitude of risk for each work evaluation information (quality, cost, process) for evaluating the work situation. Alternatively, the probability distribution database unit 100d may store one probability distribution model 20 for the project.

  Next, returning to FIG. 3, the functional blocks of the project management apparatus 100 will be described.

  The plan management unit 100a associates each type of work of a project with a risk type predicted to occur for the work and stores it in the storage device as a project information part 30 (project information) for management. The plan management unit 100a explicitly associates each work of the WBS, which is a configuration diagram obtained by disassembling the entire project into detailed work, quality (Q), cost (C), process (delivery date (D)), and risk (R). The project information unit 30 is managed.

  The risk management unit 100c stores the risk type and the risk evaluation information for calculating the magnitude of the risk in association in the storage device as the risk information unit 31. The risk management unit 100c manages a risk information unit 31 that manages risks (risk types) that are explicitly associated with each work of the WBS that has broken down the entire project into detailed work.

  Here, the project information unit 30 and the risk information unit 31 managed by the plan management unit 100a will be described. FIG. 6 is a diagram illustrating a configuration of the project information unit 30 managed by the plan management unit 100a and the risk information unit 31 managed by the risk management unit 100c according to the first embodiment. The project information unit 30 and the risk information unit 31 are stored in a storage device included in the project management device 100.

  In FIG. 6, the project information unit 30 stores a work item 301 for setting the work content of a project, a start date 302, and an end date 303. The work content unit 30a stores the work content unit 30a. , As the result 304, the work content of the work item 301 shown in the work content part 30a (the work content set in the work item 301, hereinafter also referred to simply as work), the quality 305 (Q), The related information unit 30c stores (defines) the relationship between the cost 306 (C), the step 307 (D), and the risk 308 (R) (risk type).

  Here, quality items 305 (Q), cost 306 (C), and step 307 (D), which are vertical items of the related information section 30 c, are work evaluation information for evaluating the work content of the work item 301. The project management apparatus 100 predicts the quality 305 (Q), the cost 306 (C), and the process 307 (D), which are work evaluation information, for each work content of the work item 301 and manages each work content.

  For example, the work content “AAAA (program development)” of the work item 301 is the program development work. In the program development work, since the quality of the program (for example, the number of occurrences of bugs) is an object of work evaluation and is related to the quality, the quality 305 of the related information unit 30c is set to “(relevant)”. Also, a planned quality value (for example, “number of defects 10”) in the work content “AAAA (program development)” may be set.

  In the program development work, since the cost of the program is a target of the work evaluation and is related to the cost, the cost 306 of the related information unit 30c is also set to “(relevant)”. Further, a planned cost value (for example, “aaa circle per piece”) in the work content “AAAA (program development)” may be set.

  In the program development work, since the process of the program (for example, the completion date delay) is an object of work evaluation and related to the process, “(related)” is set in the process 307 of the related information section 30c. Further, a planned value of the process in the work content “AAAA (program development)” (for example, “work end date m month n day”) may be set.

  In addition to these plan values (quality, cost, process), when setting other plan values, other items may be created as the plan values and set.

  In FIG. 6, the risk information part 31 includes a risk item part 31a composed of a risk item 311 for recording the risk contents (risk type) detected as a risk, and the risk contents (in the risk item 311) set in the risk item part 31a. A risk evaluation result section 31b for filling in the result 312 of the effect 312 on the content of the risk to be set (hereinafter also simply referred to as risk) and the actualization rate 313 that the risk will actually be realized; Based on the result of the result section 31b, the risk countermeasure definition section 31c is composed of countermeasures 314 that define the presence / absence and implementation of countermeasures against risks.

  By associating the risk content (risk type) set in the risk 308 of the project information unit 30 with the risk content (risk type) set in the risk item unit 31a of the risk information unit 31, the project information unit 30 And the risk information part 31 are associated with each other. In addition, the work item 301 of the project information unit 30 assumes the above-described WBS WP (Work Package) or the like. WP means the minimum unit work in WBS.

Here, a specific example of the risk content set in the risk 308 corresponding to the work content set in the work item 301 of the project information unit 30 is shown below.
・ For work content “Creating xx chapter of requirement definition document”, risk content “May not be able to agree with customer by xx of requirement definition period”, risk content “implicit knowledge of customer because of new field” May not be documented. "
・ In contrast to the work content “Creation of xx chapters of the system design document”, the risk content “Design may not be completed in the planning period due to lack of developer skills”.
・ In contrast to the work content “Review of the xx chapter of the method design document”, the risk content “Because of the new design method, there is a possibility that it cannot be handled by the conventional quality control”.
・ In contrast to the work content “xx test of combination test”, the risk content “the arrangement of test equipment may not be in time for the test”.
・ In contrast to the work content “From detailed development design to integration test”, the risk content is “There is a large number of projects, so there is a possibility that detailed grasp of the detailed process may not be possible in real time”.

  Further, the risk information unit 31 associates a risk evaluation result unit 31b (an example of risk evaluation information) for calculating the magnitude of the risk with respect to the risk content of the risk item 311. In the risk evaluation result part 31b, an impact 312 (amount, for example, abc yen) and an actualization rate 313 (occurrence rate, for example, mm%) indicating the impact when a risk occurs are defined and recorded in advance. Is done.

  In the project management apparatus 100 according to the present embodiment, as a method for calculating the magnitude of risk, for example, the plan prediction unit 100b calculates the influence 312 × the actualization rate 313 based on the information of the risk evaluation result unit 31b, The amount of risk is taken as the risk countermeasure cost of the measure 314, and the magnitude of the risk can be determined based on the amount of the risk measure cost. However, the magnitude of the risk is not limited to the risk countermeasure cost. For example, the ratio of the request amount of the project and the risk countermeasure cost can be considered.

  The plan prediction unit 100b, for each of a plurality of work contents set in the work item 301, the risk content (risk type) of the risk 308 corresponding to the work content from the project information unit 30 stored by the plan management unit 100a. To get. The plan prediction unit 100b acquires a risk evaluation result unit 31b (risk evaluation information) corresponding to the risk content (risk type) from the risk information unit 31 stored by the risk management unit 100c, and acquires the acquired risk evaluation result unit Based on 31b (risk evaluation information), the magnitude of the risk corresponding to the work content is calculated by the processing device. The plan prediction unit 100b selects a probability distribution model corresponding to the calculated magnitude of the risk from the probability distribution database unit 100d, and uses the selected probability distribution model to determine the work status (quality (Q), The work status of the project is predicted by generating a probability distribution of cost (C) and process (D) by the processing device.

  FIG. 7 is a diagram illustrating an output image of a result predicted by the plan prediction unit 100b in the project management apparatus 100 according to the first embodiment. The plan prediction unit 100b performs a plan prediction process, generates a project prediction result unit 40 as a predicted result, and stores it in the storage device.

  As illustrated in FIG. 7, one project prediction result unit 40 is generated for the work content “AAAA” set in the work item 301. The plan prediction unit 100b calculates the magnitude of the risk based on the risks “xxxx” and “zzz” defined in the project information unit 30 corresponding to the work content “AAAA”. As described above, the risk size corresponding to the work content “AAAA” is calculated from the risk evaluation result unit 31b in which the result of estimating the actualization rate 313 that the risk information unit 31 will actually embody is entered. To do.

  The plan predicting unit 100b selects a reference probability distribution model from the probability distribution database unit 100d based on the calculated risk size, and sets it as the reference probability distribution unit 40a of the project prediction result unit 40.

  The plan prediction unit 100b applies the quality distribution calculated based on the distribution information of the reference probability distribution unit 40a and the quality (Q) of the work content unit 30a and the related information unit 30c to the quality distribution unit 40b of the project prediction result unit 40. Set. The plan prediction unit 100b adds the cost distribution calculated based on the distribution information of the reference probability distribution unit 40a and the cost (C) of the work content unit 30a and the related information unit 30c to the cost distribution unit 40c of the project prediction result unit 40. Set. The plan prediction unit 100b adds the process distribution calculated based on the distribution information of the standard probability distribution unit 40a and the process (D) of the work content unit 30a and the related information unit 30c to the process distribution unit 40d of the project prediction result unit 40. Set.

  Here, the result shown in the project prediction result section 40 is shown for each work content of the work item 301 in the work content section 30a. However, even if a plurality of work contents are collected and the project prediction result section 40 is output. I do not care.

  FIG. 9 is a flowchart showing processing of the project management method of the project management apparatus 100 according to the first embodiment. The project management method of the project management apparatus 100 according to the first embodiment will be described with reference to FIG.

<Plan management step: S101>
First, the plan management unit 100a inputs information on the work content unit 30a including the work item 301 and the start date 302 and the end date 303 as information to be defined in advance in the project information unit 30, and stores it as the project information unit 30. Store in the device. The information defined in advance in the project information unit 30 is, for example, input to the project management apparatus 100 by an administrator using an input device. A work item 301 in the project information part 30 and a work content part 30a composed of a start date 302 and an end date 303 are defined as WBS for performing a project.

  Next, the plan management unit 100a, as information defined in advance in the project information unit 30, is information regarding the presence or absence of an influence on the quality (Q), cost (C), and process (D) of the work content set in the work item 301. To store (define) information related to the presence / absence of the influence on the quality (Q), cost (C), and process (D) items of the related information section 30c. In addition, the plan management unit 100a inputs a risk that affects the work content set in the work item 301 as information to be defined in advance in the project information unit 30, and the risk content in the risk (R) item of the related information unit 30c. (Risk type) is stored (defined).

  The plan management unit 100a may input a project information file defined and created in advance by a project manager or the like and store the file as the project information unit 30 in a storage device.

<Risk management step: S102>
Next, the risk management unit 100c includes, as information predefined in the risk information unit 31, a risk item unit 31a including a risk item 311, a risk effect 213, and a risk evaluation result unit 31b including a risk manifestation rate 313, a risk The information of the risk countermeasure definition unit 31c including the countermeasures 314 is input and stored in the storage device as the risk information unit 31. The risk management unit 100c inputs the risk content input from the administrator or the like through the input device as information to be set in the risk item 311 of the risk information unit 31, and the input risk content (risk type) is input to the risk information unit 31. The risk item 311 is set. The risk content input from the administrator or the like through the input device is, for example, input as a result of examination by the administrator or the like as a risk that may occur for each work content when the project is executed.

  The risk management unit 100c includes, as information to be set in the risk evaluation result unit 31b including the risk impact 312 and the risk manifestation rate 313, the impact (amount) corresponding to the risk content input from the administrator or the like through the input device. The actualization rate (%) is input, and the input influence (amount) and the actualization rate (%) are set in the influence 312 and the actualization rate 313 of the risk evaluation result unit 31b of the risk information unit 31.

  Next, the risk management unit 100c, as information to be defined in the risk countermeasure definition unit 31c of the risk information unit 31, measures that include the presence / absence of countermeasures and the implementation contents when a risk is embodied through an input device from an administrator or the like. The information of 314 is input, and the input information of the countermeasure 314 is set (defined) in the risk countermeasure definition unit 31c.

  The risk management unit 100c may input a risk information file defined and created in advance by a project manager or the like and store the file as the risk information unit 31 in the storage device.

<Risk association step: S103>
In S101, the plan management unit 100a stores (defines) the risk content (risk type) in the risk (R) item of the related information unit 30c of the project information unit 30, and the risk management unit 100c in S102. By defining the risk content (risk type) in the risk item 311 of the risk information part 31, which work of the work content part 30a of the project information part 30 in which the risk of the risk item 311 of the risk information part 30 is registered It is possible to define the relationship between contents and their influence.

<Planned prediction step: S104>
<Probability distribution model selection step: S1041 to S1044)>
The plan predicting unit 100b determines whether the processing is completed for all the work contents of the work item 301 by the processing device (S1042). When the process is completed for all the work contents of the work item 301 (Yes in S1042), the plan predicting unit 100b ends the process. If the processing has not been completed for all the work contents of the work item 301 (No in S1042), the plan predicting unit 100b moves the process to S1043.

<Risk size calculation step: S1043>
The plan prediction unit 100b acquires the risk content corresponding to the work content of the work item 301 to be processed from the project information unit 30 by the processing device. For example, the plan prediction unit 100b acquires risk contents “xxxx” and “zzz” corresponding to the work contents “AAAA”. The plan prediction unit 100b acquires from the risk information unit 31 a risk evaluation result unit 31b corresponding to the acquired risk contents (“xxxx” and “zzz”). The plan predicting unit 100b calculates the size of the risk corresponding to the work content of the work item 301 to be processed based on the acquired risk evaluation result unit 31b. The plan predicting unit 100b calculates abc circle × mm% (see FIG. 6) as the risk size of the risk content “xxxx”. In addition, the plan prediction unit 100b calculates ghi circle × pp% (see FIG. 6) as the risk magnitude of the risk content “zzz”.

  Here, an example will be described in which the plan prediction unit 100b calculates the magnitude of risk when there are a plurality of risks assigned to one work content. For example, when there are a plurality of risks assigned to one work content (when “xxxx” and “zzz” are set in the risk 308 in FIG. 6), the plan predicting unit 100 b Is calculated by the processing device. The plan prediction unit 100b may simply add the magnitudes of the respective risks, and use the addition result as the risk magnitude when selecting the “probability distribution database”. In this case, the magnitude of the risk of the work content “AAAA” is (abc circle × mm%) + (ghi circle × pp%). That is, when one work is related to a plurality of risks, the risk of the work itself increases, and therefore a probability distribution model (distribution value) having a large deviation is selected from the probability distribution database unit 100d. .

  Alternatively, when there are multiple risks assigned to one work content, the specific gravity of the risk magnitude is defined for each work content, and the risk magnitude assigned to each work is represented by the ratio of specific gravity. May be added, and the result of the addition may be used as the risk magnitude when selecting the “probability distribution database”. In this case, unlike the case of simple addition, even if the risk is large, an operation with a small specific gravity selects a distribution value with a small deviation from the probability distribution database unit 100d.

<Probability distribution model selection step: S1044>
Based on the risk magnitude calculated as described above, the plan prediction unit 100b selects a probability distribution model serving as a reference from the probability distribution database unit 100d by the processing device. For example, when the risk size corresponding to the work content “AAAA” in FIG. 6 is 70 (high risk), the plan predicting unit 100b uses the probability distribution model stored in the probability distribution database unit 100d shown in FIG. A probability distribution model 20a corresponding to a risk value of 70 (large risk) is selected by the processing device. The plan prediction unit 100b sets the selected probability distribution model 20a as the reference probability distribution unit 40a of the project prediction result unit 40.

<Quality prediction step: S1045>
The plan predicting unit 100b applies the plan value of the quality of the work content to be processed to the selected standard probability distribution model by the processing device, and generates a quality probability distribution. The plan prediction unit 100 b sets the generated probability distribution of quality in the quality distribution unit 40 b of the project prediction result unit 40. In the quality distribution unit 40b of the project prediction result unit 40, the distribution state of the quality when the cost and the process are fixed in the state of risk of the work content to be processed is set.

<Cost prediction step: S1046>
The plan predicting unit 100b applies a plan value of the cost of the work content to be processed to the selected standard probability distribution model by the processing device, and generates a cost probability distribution. The plan prediction unit 100 b sets the generated probability distribution of costs in the cost distribution unit 40 c of the project prediction result unit 40. In the cost distribution unit 40c of the project prediction result unit 40, the distribution state of costs when the quality and the process are fixed in the state of the risk of the work content to be processed is set.

<Cost prediction step: S1047>
The plan predicting unit 100b applies a plan value of the process of the work content to be processed to the selected standard probability distribution model by the processing device, and generates a probability distribution of the process. The plan prediction unit 100 b sets the generated probability distribution of the process in the process distribution unit 40 d of the project prediction result unit 40. In the process distribution unit 40d of the project prediction result unit 40, the process distribution state when quality and cost are fixed in the state of risk of the work content to be processed is set.

<Display processing of project prediction result unit 40: S1048>
The display part (refer FIG. 2) with which the project management apparatus 100 is provided outputs the probability distribution of the work condition which the plan prediction part 100b produced | generated to a display apparatus. Or the output part (refer FIG. 2) with which the project management apparatus 100 is provided outputs the probability distribution of the work condition which the plan prediction part 100b produced | generated to the output apparatus.

  FIG. 8 is a diagram showing the distribution value of the probability distribution selected by the plan predicting unit 100b. FIG. 8A is a probability distribution in which the distribution range is calculated by multiplying the planned value of the project by a percentage. b) shows a probability distribution for calculating the distribution range by adding the number of days to the planned value of the project. A process of generating a probability distribution of the work status (quality, cost, process) of the work content to be processed will be described with reference to FIG.

  For example, in the case of generating a probability distribution of quality, when the planned quality value of the work content “AAAA” is “number of defects 10”, the plan predicting unit 100b uses the processing device, and FIG. The project plan value “number of defects 10” is applied to the probability distribution model 20a shown in FIG. The plan prediction unit 100b multiplies the project plan value “number of defects 10” by the percentage indicated in the probability distribution model 20a, thereby obtaining the maximum value, the minimum value, the maximum value of the normal distribution 6σ, and the minimum value of the normal distribution 6σ. Is calculated by the processing device to generate a probability distribution of quality.

  For example, in the case of generating a probability distribution of costs, when the planned value of the cost of the work content “AAAA” is “aaa circle per piece”, the plan predicting unit 100b uses FIG. The project planned value “aaa circle per piece” is assigned to the probability distribution model 20a shown in FIG. The plan prediction unit 100b multiplies the project plan value “aaa circle per piece” by the percentage shown in the probability distribution model 20a, thereby obtaining the maximum value, the minimum value, the maximum value of the normal distribution 6σ, and the minimum value of the normal distribution 6σ. The value is calculated by the processing device to generate a probability distribution of costs.

  For example, in the case of generating a probability distribution of a process, when the planned value of the process of the work content “AAAA” is “work end date m / month / day”, the plan prediction unit 100b uses a processing device to The project plan value “work end date m month n day” is applied to the probability distribution model 20a shown in FIG. The plan predicting unit 100b adds the number of days obtained by the probability distribution model 20a to the project plan value “work end date m / month / day” to obtain a maximum value (delayed 10 days from m / month n) and a minimum value (m 2 days before the month n), the maximum value of the normal distribution 6σ (5 days after m month n day) and the minimum value of the normal distribution 6σ (m month n day) are calculated by the processing device, and the probability distribution of the process is calculated. Generate.

  As described above, the plan predicting unit 100b calculates the risk magnitude for all work contents set in the work item 301, and uses the probability distribution model used for predicting the work situation based on the risk magnitude. Since the probability distribution model of the work situation can be generated by the probability distribution model selected and matched to the magnitude of the risk, the probability distribution of the work situation with higher accuracy can be generated.

  As described above, since the distribution status of quality (Q), cost (C), and process (D) is calculated with respect to the work content, the entire project is viewed and the efficiency that best suits the purpose of the project is high. It is possible to judge quantitatively to take risk countermeasures.

Embodiment 2. FIG.
In the first embodiment, the minimum configuration of the functional block configuration of the project management apparatus 100 has been described. In project management, for example, a project plan may be changed based on a prediction result of a project management apparatus or due to a change in the environment surrounding the project. In such a case, it is necessary to change the contents of the project information section (WBS) of the project management apparatus, but in this embodiment, a constraint condition or a change condition regarding the change of the contents of the project information section is added. A project management apparatus 200 having a function capable of performing the above will be described.

  FIG. 10 is a functional block configuration diagram of the project management apparatus 200 according to the second embodiment. In FIG. 10, the same functional blocks as the functional blocks of the project management apparatus 100 described in the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The project management apparatus 200 shown in FIG. 10 includes a change condition definition unit 200b that defines a change condition database unit 200i (change condition database) in addition to the functional blocks of the project management apparatus 100 of FIG. 3 described in the first embodiment. A plan storage unit 200g for storing the project information unit 50 and the risk information unit 31 in a storage device, a risk-plan association unit 200d for associating a risk with a plan, and a constraint database unit 200j (a constraint database) The block configuration includes a constraint condition data generation unit 200f to be generated.

  Here, the plan management unit 100a, the plan prediction unit 100b, the risk management unit 100c, the change condition definition unit 200b, the risk-plan association unit 200d, and the constraint condition data generation unit 200f include elements, devices, It is implemented only with hardware such as boards and wiring. Alternatively, it may be realized by firmware stored in the ROM 913. Alternatively, a combination of software and hardware, or a combination of firmware may be used. In the case of firmware or software, the program is stored in a recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, and a DVD. The program is read by the CPU 911 and executed by the CPU 911.

  The plan management unit 100a manages the project information unit 50 that explicitly associates WBS with quality (Q), cost (C), process (D), and risk (R).

  The change condition definition unit 200b defines a change condition when changing the work of the project information unit 50, and stores it in the storage device as the change condition database unit 200i. The change condition definition unit 200b defines constraints due to dependency of work or the like for changes to the project information unit 50 managed by the plan management unit 100a, and stores them in the storage device as the change condition database unit 200i.

  The risk management unit 100c manages the risk (R) explicitly associated with the project information unit 50 managed by the plan management unit 100a.

  The risk-plan association unit 200d explicitly defines the risk (R) relationship with the project information unit 50 managed by the plan management unit 100a.

  The plan prediction unit 100b uses the project information unit 50 managed by the plan management unit 100a and the statistical probability distribution of the organization linked to the risk size stored in the probability distribution database unit 100d to work the project. Make predictions.

  The constraint condition data generation unit 200f defines a constraint condition for work-related information, which is information such as resources of the project information unit 50, and stores it in the storage device as a constraint condition database unit 200j. The constraint condition data generation unit 200f defines a constraint condition based on exclusive information such as resources (work-related information necessary for performing the work contents) in response to a change to the project information unit 50 managed by the plan management unit 100a. And stored in the storage device as the constraint condition database unit 200j.

  The plan storage unit 200g manages the update history of the project information unit 50 that has been associated with the risk / plan association unit 200d with respect to the project information unit 50 managed by the plan management unit 100a.

  The probability distribution database unit 100d stores a statistical probability distribution of an organization linked to the magnitude of risk.

  FIG. 11 is a diagram illustrating a configuration of the project information unit 50 of the project management apparatus 200 according to the second embodiment. FIG. 12 is a diagram illustrating a configuration of the project information unit (after change) 60 after the information in the project information unit 50 is changed in the project management apparatus 200 according to the second embodiment.

  As shown in FIG. 11, the project information unit 50 according to the second embodiment has a configuration in which a resource 50d and a period 50e are added to the project information unit 30 of FIG. 6 described in the first embodiment. In other words, the project information part 50 and the project information part (after change) 60 show the project information part before and after the change of work in the project.

  In FIG. 11, the project information unit 50 includes a work content unit 50a that defines the work content, start date, and end date of the project, a performance unit 50b that records the implementation status of the work content unit 50a, and the work shown in the work content unit 50a. And information (quality) (Q), cost (C), process (D), related information part 50c that defines the relationship of risk (R), resource 50d that shows the relationship between the work shown in the work content part 50a and the resource used, work content part The period 50e shows the relationship between the work shown in 50a and the schedule. Here, the resource 50d indicating the relationship between the work and the resource used in the work content part 50a and the period 50e indicating the relationship between the work and the schedule shown in the work content part 50a are necessary for performing the corresponding work content. It is an example of work related information.

  In FIG. 12, the project information section 60 includes a work content section 60a that defines the work contents, start date, and end date of the project, a performance section 60b that records the implementation status of the work content section 60a, and the work shown in the work content section 60a. And the relation information part 60c that defines the relationship between the quality (Q), cost (C), process (D), and risk (R), the resource 60d that shows the relation between the work and the resource used in the work content part 60a, and the work content part It is comprised from the period 60e which showed the relationship between the operation | work shown to 60a, and a schedule.

  Next, the registration method of the change condition database unit 200i, the registration method of the constraint database unit 200j, the registration method of the project information unit 50 to the plan storage unit 200g, and the risk information unit 31 for the project management apparatus 200 in the present embodiment. The registration method to the plan storage unit 200g will be described.

FIG. 13 is a diagram illustrating an example of the change condition database unit 200i. The change condition database unit 200i in FIG. 13 is an example of a change condition when changing the work B to the work E in the work B and the work E that are registered in the project information unit 50 and related in software development. Is shown as follows.
(A) Work B involves work C, but work F is not performed.
(B) Work E is accompanied by work F, but work C is not performed.
(C) Work F is not performed in the same project as work D.

FIG. 14 is a diagram illustrating an example of the constraint condition database unit 200j. Similarly, the constraint condition database unit 200j of FIG. 14 similarly, for example, is a constraint condition of resources or the like when the work B is changed to the work E in the related work B and work E registered in the project information unit 50. An example is shown as follows.
(D) Work B uses resource X.
(E) The work F uses the resource X.
(F) The resource X is used in the period of R to S in another project W.

  A registration method of the change condition database unit 200i in the project management apparatus 200 according to Embodiment 2 will be described. First, in the project management apparatus 200, the change condition definition unit 200b inputs information (including change conditions (a), (b), and (c)) defined as the change condition from the input device, and the change condition The data is stored in the storage device as the database unit 200i. That is, in the project management apparatus 200, the change condition (a) is defined by the administrator using the change condition definition unit 200b, and the defined information (change condition) is stored in the change condition database unit 200i by the change condition definition unit 200b. Is done. Similarly, the change conditions (b) and (c) are defined by the administrator using the change condition definition unit 200b, and the defined change conditions (information) are stored in the change condition database unit 200i by the change condition definition unit 200b. .

  Next, a registration method of the constraint condition database unit 200j in the project management apparatus 200 according to Embodiment 2 will be described. In the project management apparatus 200, the constraint data generation unit 200f inputs information defined as constraint conditions (including constraint conditions (d) and (e)) from the input device, and stores it as a constraint database unit 200j. Store in the device. Next, the constraint condition data generation unit 200f uses the contents of the project information unit 50 registered in advance in the plan storage unit 200g, and information on limitations on resources and the like related to the stored constraint conditions (b) and (e). Are automatically retrieved by the processing device. The constraint condition data generation unit 200f automatically generates a constraint condition (f) by the processing device based on the searched result and registers it in the constraint condition database unit 200j. The constraint data generation unit 200f also stores the result of automatic search using the processing device by the constraint data generation unit 200f.

  That is, the constraint condition (d) “work B uses resource X” is defined by the administrator or the like using the constraint condition data generation unit 200f, and the defined constraint condition (d) (information) is the constraint condition data. It is stored in the constraint database unit 200j by the generation unit 200f. Similarly, the constraint condition (d) “work F uses resource X” is defined by the administrator using the constraint condition data generation unit 200f, and the defined constraint condition (e) (information) is the constraint. It is stored in the constraint data base 200j by the condition data generator 200f.

  Next, the constraint data generation unit 200f has already sent information related to the restrictions on the resources (resource X, resource Y) related to the constraints (d) and (e) to the plan storage unit 200g using the processing device. Search from the contents of the registered project information section 50. Based on the result of the search, the constraint data generation unit 200f automatically generates a constraint (f) “resource X is being used for another project W during the period R to S” by the processing device. To do. The restriction condition data generation unit 200f stores the restriction condition (f) (information related to resource restrictions) automatically generated by the processing device in the restriction condition database part 200j.

  Next, a registration method of the project information unit 50 in the project management apparatus 200 according to the second embodiment will be described. FIG. 11 is a diagram showing a configuration of the project information unit 50 according to the second embodiment. As described in the first embodiment, the plan management unit 100a inputs the work item, the start date, and the end date of the work content unit 50a as information defined in the project information unit 50 (WBS for performing a project). And stored in the project information section 50. In addition, the plan management unit 100a defines the presence / absence of the influence on the quality (Q), cost (C), and process (D) with respect to the related information unit 50c after completing the input of the work item in the work content unit 50a. Is stored in the project information unit 50.

  In the second embodiment, the plan management unit 100a inputs resource information necessary for the work item of the set work content unit 50a as information to be defined in the resource 50d of the project information unit 50, and the plan storage unit 200g It is stored (defined) in the resource 50d of the project information unit 50. Further, the plan management unit 100a, as information defined in the period 50e of the project information unit 50, is information indicating the relationship between the set work content unit 50a and the schedule (for example, “work A is performed during the period P to Q”). Is stored in the period 50e of the project information unit 50 of the plan storage unit 200g (defined).

  As in the first embodiment, the plan management unit 100a inputs a file of project information content defined and generated in advance by an administrator or the like, and the project information unit 50 is stored in the plan storage unit 200g of the project management apparatus 200. You may register.

  Next, a method for registering the risk information unit 31 in the planned storage unit 200g will be described. The process in which the risk management unit 100c registers the risk information unit 31 in the storage device (plan storage unit 200g) is the same as that described in the first embodiment. The risk management unit 100 c registers the risk information unit 31 in the plan storage unit 200 g of the project management device 200.

  The risk and plan associating unit 200d associates the risk and the plan between the registered risk information unit 31 and the registered project information unit 50 by the processing device. The risk and plan associating unit 200d inputs information about which content of the work content unit 50a of the project information unit 50 the risk content of the risk item 311 of the risk information unit 31 relates to, and based on the input information A relationship is defined for the risk (R) of the related information part 50c. That is, the risk and plan associating unit 200d stores the risk content corresponding to the work item in the risk (R) column of the related information unit 50c of the project information unit 50.

  Next, based on the change condition database part 200i shown in FIG. 13 and the constraint condition database part 200j shown in FIG. 14, the work B is registered in the project information part 50 and related work B and work E. A method for changing the project information section when changing to work E will be described. Hereinafter, in the project management apparatus 200 according to the present embodiment, an operation of the project management apparatus 200 when the project information unit 50 stored in the plan storage unit 200g is changed will be described.

  Here, the administrator or the like performs a process of changing the work B of the project information unit 50 stored in the plan storage unit 200g to the work E by an input device (for example, a keyboard) of the project management apparatus 200. In this case, the plan management unit 100a that manages the project information unit 50 inputs change information for changing the work B input from the administrator or the like by the input device to the work E, and based on the input change information. The change condition database unit 200i and the constraint condition database unit 200j are referred to by the processing device, and the change processing of the project information unit 50 is executed by the processing device.

  When the plan management unit 100a inputs change information for changing the work B of the project information unit 50 to the work E, the plan management unit 100a retrieves the contents of the project information unit 50 stored in the plan storage unit 200g from the storage device. When changing the content of the work B of the extracted project information unit 50 to the work E, the plan management unit 100a first processes the change condition related to the work B among the change conditions registered in the change condition database unit 200i. Search (reference) by device. As a result of the search, the plan management unit 100a obtains the related change condition (1 (a) in FIG. 13) related to the work B from the information registered in the change condition database unit 200i by using the processing device. The operation B acquires the related change condition that “the operation B is accompanied by the operation C but the operation F is not performed”. Moreover, the plan management unit 100a acquires the condition (1 (b) in FIG. 13) related to the work E from the information registered in the change condition database unit 200i by the processing device, and “(b) the work E is The related change condition “Accomplishing operation F but not executing operation C” is acquired.

  The plan management unit 200a uses the processing device to change “work B and work C” to “work E and work F” based on the related change conditions (a) and (b) registered in the change condition database unit 200i. Replace with Furthermore, the plan management unit 100a obtains the change condition related to the work F that is newly related from the information registered in the change condition database unit 200i by the processing device. That is, the plan management unit 100a acquires the condition related to the work F (1 (c) in FIG. 13) by the processing device, and “(c) the work F is not performed in the same project as the work D”. Get the related change condition with. The plan management unit 100a deletes the work D from the project information unit 50 by the processing device based on the related change condition (c) registered in the change condition database unit 200i.

  Next, a process in which the plan management unit 100a updates the content of the project information unit 50 based on the content of the constraint condition database unit 200j will be described.

  As described above, the plan management unit 100a replaces “work B and work C” with “work E and work F” based on the contents of the change condition database unit 200i. That is, the plan management unit 100a inputs change information for changing the work B to the work E, and the contents of the work B (the work content part 50a and the related information part) of the project information part 50 stored in the plan storage part 200g. 50c, resource 50d, period 50e) are changed to the contents of work E (work contents part 50a, related information part 50c, resource 50d, period 50e), and the contents of work C are changed to the contents of work F. Furthermore, the plan management unit 100a deletes the contents of the work D.

  Here, for the newly added work E, the plan management unit 100a searches the processing device for constraint conditions (information) related to the work E from information registered in the constraint condition database unit 200j. Similarly, for the operation F, the related constraint condition (information) is searched by the processing device.

  For the work F, the resource 60d of the project information unit 60 is automatically updated to use the resource X with the information defined in the relation (e). And also regarding the start date and end date of the work content part 60a of the project information part 60, information related to the work E is searched from the information registered in the constraint database part 200j. Similarly, for work F, related information is searched. For the work F, the information defined in the relation (f) defines that the resource X is used in the period R and S in another project W. The start date and the end date of the work content part 60a are automatically updated in a vacant period.

  FIG. 12 is a diagram showing the contents of the project information part (after change) 60 after the project information part 50 is changed in the project management apparatus 200 according to the second embodiment.

  As described above, the plan management unit 100a inputs the change information for changing the work B to the work E, the work content part 50a of the work B of the project information part 50 stored in the plan storage part 200g, and related information. The contents of the part 50c and the resource 50d are changed to the contents of the work E. As a result, the project information part 50 is updated to the contents of the work content part 60a, the related information part 60c, and the resource 60d of the project information part (after change) 60.

  As described above, according to the project management apparatus 200 according to the second embodiment, it is possible to register change conditions and constraint conditions related to a project in the change condition database unit 200i and the constraint condition database unit 200j. In addition, the project management apparatus 200 according to the second embodiment is based on the change conditions and the constraint conditions registered in the change condition database unit 200i and the constraint condition database unit 200j when a project change by an administrator or the like occurs. Since the project information unit 50 is changed, it is possible to prevent adjustment of resources and other work with other projects and necessary work omission.

Embodiment 3 FIG.
In the present embodiment, a description will be given of a project management apparatus 300 having a configuration to which a function for updating the statistical probability distribution model information of an organization linked to the magnitude of risk stored in the probability distribution database unit 100d is added.

  FIG. 15 is a functional block configuration diagram showing a functional block configuration of the project management apparatus 300 according to the third embodiment. FIG. 15 shows the statistical probability distribution of the organization linked to the magnitude of the risk based on the collected project information (project information section 50) in the minimum unit block configuration of the project management apparatus 100 shown in the first embodiment. It is a system block diagram (functional block block diagram) to which a function for updating model information is added.

  In the description of the present embodiment, in FIG. 15, functional blocks having the same functions as the functional blocks described in the first or second embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  As described in the first or second embodiment, the project management apparatus 300 explicitly projects the WBS and the quality (Q), the cost (C), the process (D), and the risk (R). The plan management unit 100a that manages the unit 50, the plan prediction unit 100b that performs prediction using the statistical probability distribution model 20 stored in the project information unit 50 and the probability distribution database unit 100d, and explicitly associated with the WBS The risk management unit 100c that manages the risk (R) as the risk information unit 31 and the plan storage that manages the update history of the project information that has been associated with the risk for the project information unit 50 that is managed by the plan management unit 100a 200g and probability distribution data storing the statistical probability distribution model 20 of the organization linked to the magnitude of the risk And an over scan portion 100d.

  Here, the plan management unit 100a, the plan prediction unit 100b, the risk management unit 100c, and the probability distribution database update unit 300f are implemented only by hardware such as elements, devices, substrates, and wirings. Alternatively, it may be realized by firmware stored in the ROM 913. Alternatively, a combination of software and hardware, or a combination of firmware may be used.

  In the present embodiment, further, based on the data of the project information unit 50 (that is, the project information unit 50 that collects information on completion of the work) in which the actual value indicating the actual result of the work when the work is completed is recorded. In addition, a probability distribution database update unit 300f that updates information on the statistical probability distribution model 20 of the organization linked to the magnitude of the risk stored in the probability distribution database unit 100d is provided.

  The plan management unit 100a stores, for each work item, a result value indicating a result of the work when the work is completed as a part of the project information unit 50.

  The probability distribution database update unit 300f updates the probability distribution model of the probability distribution database unit 100d based on the actual value of the project information unit 50 stored by the plan management unit 100a.

  For example, the probability distribution database update unit 300f obtains necessary data from the end date (an example of the actual value) set in the work content unit 50a of the project information unit 50 or the recorded content (an example of the actual value) of the actual unit 50b. The collected statistical processing is performed, and the probability distribution database unit 100d is updated. That is, the probability distribution database update unit 300f sets, for each work content set in the work item 301, the end date (an example of the actual value) set in the work content unit 50a or the performance unit 50b based on the related information unit 50c. From the recorded contents (an example of the actual value), "Risk size at the end of work plan and whether it was finished" or "Difference between risk magnitude and plan at the actual end of work", etc. Collect data (cost, process, quality) from the viewpoint, and perform statistical processing to update the probability distribution database.

  The project management apparatus 300 according to the third embodiment, for example, at the update time of the probability distribution database unit 100d determined by the organization, the value of the project information of each project accumulated (that is, the actual value of each project obtained from the above viewpoint). ) Is statistically processed to update the probability distribution database unit 100d. However, for example, the probability distribution database unit 100d may be updated at the end of each project operation.

  Next, the operation of the probability distribution database update process of the probability distribution database update unit 300f of the project management apparatus 300 will be described.

  First, as a premise, a large flow from the registration process of the project information unit 50 to the project plan prediction process in the project management apparatus 300 is shown below. Since the registration process of the project information unit 50 and the project plan prediction process are the same as those described in the first embodiment and the second embodiment, they will be briefly described. In the project management apparatus 300, the defined project information is registered as the project information unit 50 from the plan management unit 100a to the plan storage unit 200g. Then, risk information (risk information unit 31) defined separately is registered as the risk information unit 31 from the risk management unit 100c to the plan storage unit 200g. The registered risk information (risk information 31) defines, for example, the relationship between the work content of the work item of the project information unit 50 registered by the risk and plan association unit 200d and the risk (R), and the project information The unit 50 is updated and stored in the plan storage unit 300d. Then, the plan prediction unit 100b uses the probability distribution model stored in the probability distribution database unit 100d at the time when the association between the project information unit 50 and the risk information unit 31 is completed. Generate (calculate) a predicted distribution for the item.

  FIG. 16 is a flowchart showing the flow of the probability distribution database update process of the project management apparatus 300 according to the third embodiment. The probability distribution database update process of the project management apparatus 300 according to the third embodiment will be described with reference to FIG.

First, here, the probability distribution database update processing by the probability distribution database update unit 300f is premised on updating the probability distribution database unit 100d by performing the following processing.
(A) The risk magnitude is classified into three categories.
(B) The maximum value is obtained for each classified risk category.
(C) Find the minimum value for each classified risk category.
(D) For each classified risk category, a range within 6σ covering 99.73% is obtained.
(E) An average value is obtained for each classified risk category.
(F) For each classified risk category, obtain a probability that can be realized with an average value.

  The probability distribution database update unit 300f analyzes the information of the project information unit 50 registered in the plan storage unit 300d by the processing device, and calculates the information of the processing (f) from the processing (a). The probability distribution database update unit 300f updates the contents of the probability distribution database unit 100d by storing the calculated process (a) to process (f) information in the probability distribution database unit 100d.

<Risk category setting process: S1001>
First, the probability distribution database update unit 300f sets the risk category of the first hierarchy as the risk category to be processed. Here, the risk classification means a range of risk magnitudes when the risk magnitude (height direction) of the probability distribution database unit 100d is divided into three as shown in FIG. As an example of risk classification, for example, as shown in FIG. 5, “Risk classification in the first hierarchy ⇒ Risk magnitude small / eg, risk magnitude 0 or more and less than 30”, “Risk risk classification in the second hierarchy Category⇒Risk size medium / for example, risk size 30 to less than 60 ”,“ Level 3 risk category⇒Risk size / for example, risk size 60 or more ” Can do.

  Returning to FIG. 16, the description of the probability distribution database update processing by the probability distribution database update unit 300f is continued.

<Update data storage processing: S1004 to S1009>
The probability distribution database update unit 300f performs risk assessment on the work content data that has already been completed among a plurality of work content set in the work item 301 of the project information unit 50 registered in the plan storage unit 200g. The size is calculated by the processing device. The method for calculating the magnitude of risk is as described in the first embodiment. The probability distribution database update unit 300f aggregates data of work contents whose risk magnitude corresponds to the risk category to be processed by the processing device, and calculates the maximum value for each development phase and work item by the processing device. And stored in the probability distribution database unit 100d (maximum value storage processing: S1004). Similarly, the probability distribution database update unit 300f calculates the minimum value for each development phase and work item by the processing device and stores it in the probability distribution database unit 100d (minimum value storage processing: S1005).

  The probability distribution database update unit 300f aggregates work content data whose magnitude of risk corresponds to the risk category to be processed by the processing device, and calculates a standard deviation for each development phase and work item by the processing device. (Standard deviation calculation processing: S1006). Based on the calculated standard deviation, the probability distribution database update unit 300f calculates the 6σ range of the normal distribution for each development phase and work item by the processing device and stores it in the probability distribution database unit 100d (6σ value storage) Processing: S1007).

  The probability distribution database update unit 300f aggregates data of work contents whose magnitude of risk corresponds to the risk category to be processed by the processing device, and calculates an average value for each development phase and work item by the processing device. And stored in the probability distribution database unit 100d (average value storage processing: S1008).

  The probability distribution database update unit 300f calculates the corresponding development phase based on the data of the work content corresponding to the risk category to be processed whose risk magnitude is aggregated when calculating the average value and the calculated average value. For each work item, the probability that can be realized by the average value is calculated by the processing device and stored in the probability distribution database unit 100d (the probability that can be realized by the average value is stored: S1009).

  The probability distribution database update unit 300f performs the processing from S1004 to S1009 for all risk categories.

<Storage Value Confirmation Process (S1010)>
In the stored value confirmation processing (S1010), the probability distribution database update unit 300f performs the processing from S1004 to S1009 for all risk categories, confirms the values stored in the probability distribution database unit 100d, and uses them as an organization. Make adjustments as possible values. For example, the project management apparatus 300 stores conditions for determining whether or not the probability distribution model of the probability distribution database unit 100d can be used as an organization as confirmation condition information in a storage device. Based on the confirmation condition information stored in the storage device, the probability distribution database update unit 300f determines whether or not the value is usable as an organization, and adjusts the stored value (that is, the probability distribution) Model adjustment).

  As described above, the probability distribution database update unit 300f generates the statistical probability distribution model 201 of the organization linked to the magnitude of the risk based on the data of the project information unit 50 registered in the plan storage unit 300d. By calculating and storing the necessary data, it is possible to update the probability distribution database unit 100d, so that a probability distribution model more suitable for the actual situation of the project can be used, and the accuracy of prediction is improved. Can be made.

  In the first to third embodiments, the project management apparatus having the following features has been described.

  The project management apparatus according to the first embodiment uses a statistical probability distribution model of an organization used for estimation of progress of estimation and plan in project management of software development and hardware development. It is characterized by using a statistical probability distribution model.

  The project management apparatus according to Embodiment 1 explicitly associates WBS with quality (Q), cost (C), process (D), and risk (R) in software development and hardware development project management. Is managed as integrated project information.

  The project management apparatus according to the second embodiment includes a list of constraints and dependency information and the conditions when changing the project information of the plan management unit and when changing the plan inside and outside the project in software development and hardware development project management. It has a change condition definition section for defining the contents.

  The project management apparatus according to the first embodiment, in software development and hardware development project management, based on the project information of the plan management unit, the overall probability distribution, cost (C) and process (D) that can be achieved. Probability distribution of quality (Q) when quality is fixed, probability distribution of cost (C) when quality (Q) and process (D) are fixed, quality (Q) and cost (C) A plan predicting section characterized by calculating a probability distribution that can be achieved in the step (D) in the case of fixing.

  The project management apparatus according to the first embodiment is a probability distribution database that can be associated with project information of the plan management unit as probability distribution data used in calculation of the plan prediction unit in project management of software development and hardware development. Part.

  The project management apparatus according to the second embodiment uses the statistical probability distribution data of the organization linked to the magnitude of risk in the project management of software development and hardware development, and uses WBS, quality (Q), cost (C ), A plan storage unit that can store and retrieve project information data that explicitly associates the process (D) and the risk (R) as necessary.

  The project management apparatus according to the first embodiment manages risk (R) as information associated with the plan management unit for risk (R) explicitly associated with WBS in software development and hardware development project management. Has a risk management department.

  The project management apparatus according to the second embodiment includes risk information of a risk management unit that manages a risk (R) that is explicitly associated with a WBS in project management of software development and hardware development, and a project of the plan management unit It has a risk and plan associating unit capable of setting association with information.

  In the project management apparatus according to the second embodiment, in the project management of software development and hardware development, when the project information of the plan management unit is changed, the information that becomes a constraint on the work of the project when the plan is changed inside or outside the project The definition contents of the list and its conditions are stored, and a change condition database part that can be used at the time of calculation is provided.

  The project management apparatus according to the second embodiment is a list of information that must be handled exclusively inside and outside the project when calculating the project information of the plan management unit in the project prediction unit in the project management of software development or hardware development. And a constraint condition database section in which the constraints are defined.

  The project management apparatus according to the second embodiment uses a plan in order to create or update a constraint database used when calculating project information in the plan management unit in the project management of software development or hardware development. Based on the project information accumulated in the storage unit, there is a constraint data generation unit capable of generating data of a constraint database unit that can be used by the plan management unit.

  The project management apparatus according to the third embodiment includes a plan storage unit for creating or updating a statistical probability distribution of an organization used for estimation and progress prediction of a plan in project management of software development and hardware development. A probability distribution database updating unit that can be associated with the plan management unit based on the accumulated project information and can generate data of the probability distribution database unit that can be used by the plan prediction unit.

  Although the first to third embodiments have been described above, two or more of these embodiments may be combined. Alternatively, one of these embodiments may be partially implemented. Or you may implement combining two or more embodiment among these partially.

  In the description of the first to third embodiments, the plan management unit 100a, the plan prediction unit 100b, the risk management unit 100c, the change condition definition unit 200b, the constraint condition data generation unit 200f, and the association between the risk and the plan. The unit 200d and the probability distribution database update unit 300f are configured as independent functional blocks, but may be a single functional block. Further, these functional blocks may be configured in any other combination.

  The project management device and the project management method of the project management device according to the first embodiment use hardware such as a CPU (processing device) and a storage device, and information processing by software is specifically performed using hardware. It has been realized. That is, the project management apparatus and the project management method of the project management apparatus according to the first to third embodiments described above aim to realize the project management apparatus and the project management method of the project management apparatus by the operation of the hardware using the natural law. It corresponds to technical creation using the laws of nature.

The figure which shows an example of the external appearance of the project management apparatus 100 which concerns on embodiment. The figure which shows an example of the hardware resource of the project management apparatus 100 which concerns on embodiment. FIG. 3 is a block configuration diagram showing functional blocks of the project management apparatus 100 according to the first embodiment. The figure which shows the image 201 of the statistical probability distribution model of the structure | tissue defined according to the magnitude | size of the risk which concerns on Embodiment 1. FIG. FIG. 3 is a diagram illustrating an example of a configuration of a probability distribution database unit 100d according to the first embodiment. The figure which shows the structure of the project information part 50 and the risk information part 31 in the project management apparatus 100 which concerns on Embodiment 1. FIG. The figure which showed the output image of the result which the plan prediction part 100b in the project management apparatus 100 which concerns on Embodiment 1 estimated. It is a figure which shows the example of the distribution value of the probability distribution model which the plan prediction part 100b selected, (a) is a probability distribution model which calculates a distribution range by multiplying the plan value of a project with a percentage, (b ) Is a diagram showing a probability distribution model for calculating the distribution range by adding days to the planned value of the project. FIG. 3 is a flowchart showing a process of a project management method of the project management apparatus 100 according to the first embodiment. The block block diagram which shows the functional block of the project management apparatus 200 which concerns on Embodiment 2. FIG. The figure which shows the structure of the project information part 50 of the project management apparatus 200 which concerns on Embodiment 2. FIG. The figure which shows the content of the project information part (after change) 60 after changing the project information part 50 in the project management apparatus 200 concerning Embodiment 2. FIG. The figure which shows an example of the change condition database part 200i of the project management apparatus 200 which concerns on Embodiment 2. FIG. The figure which shows an example of the constraint condition database part 200j of the project management apparatus 200 concerning Embodiment 2. FIG. FIG. 10 is a block configuration diagram showing a functional block configuration of a project management apparatus 300 according to a third embodiment. FIG. 10 is a flowchart showing a flow of probability distribution database update processing of the project management apparatus 300 according to the third embodiment.

Explanation of symbols

  20, 20a, 20b, 20c Probability distribution model, 30 Project information section, 30a Work content section, 30b Performance section, 30c Related information section, 31 Risk information section, 31a Risk item section, 31b Risk evaluation result section, 31c Risk countermeasure definition Part, 40 project prediction result part, 40a standard probability distribution part, 40b quality distribution part, 40c cost distribution part, 40d process distribution part, 50 project information part, 50a work content part, 50b performance part, 50c related information part, 50d Resource, 50e period, 60 Project information section (after change), 60a Work content section, 60b Performance section, 60c Related information section, 60d Resource, 60e period, 100 Project management device, 100a Plan management section, 100b Plan prediction section, 100c Risk management department, 100d Rate distribution database unit, 200 project management device, 200b change condition definition unit, 200d risk and plan association unit, 200f constraint condition data generation unit, 200g plan storage unit, 200i change condition database unit, 200j constraint condition database unit, 201 risk Statistical probability distribution model image of the organization linked to the size of, 300 project management device, 300f probability distribution database update unit, 301 work item, 302 start date, 303 end date, 304 results, 305 quality, 306 cost, 307 process, 308 risk, 311 risk item, 312 effect, 313 exposure rate, 314 countermeasure, 901 display device, 902 keyboard, 903 mouse, 904 FDD, 905 CDD, 906 printer device, 907 scan 920 system unit, 911 CPU, 912 bus, 913 ROM, 914 RAM, 915 communication board, 920 magnetic disk device, 921 OS, 922 window system, 923 program group, 924 file group, 931 telephone, 932 facsimile Machine, 942 LAN, 940 Internet, 941 gateway.

Claims (9)

In a project management apparatus that manages a work situation for each of the plurality of works for a project composed of a plurality of works,
A plan management unit that stores in a storage device as project information in association with a type of risk that is predicted to occur for each of the plurality of operations;
A risk management unit that stores risk information in a storage device in association with risk evaluation information for calculating a risk type and a risk magnitude;
A probability distribution database unit for storing a plurality of pre-defined probability distribution models according to the size of the risk;
For each of the plurality of operations, the risk type corresponding to the operation is acquired from the project information stored by the plan management unit, and the risk type is acquired from the risk information stored by the risk management unit. Obtain risk assessment information, calculate a risk magnitude by the processing device based on the obtained risk assessment information, and select a probability distribution model corresponding to the computed risk magnitude from the probability distribution database unit A project management apparatus comprising: a plan prediction unit that generates a probability distribution of a work situation of the work using the selected probability distribution model by a processing device. The plan management department
For each of the plurality of operations, a preset work situation plan value is stored as part of the project information,
The plan forecasting unit
The project management apparatus according to claim 1, wherein the work situation probability distribution is generated by applying the plan value of the work situation to the selected probability distribution model. The plan management department
For each of the plurality of work evaluation information for evaluating the work situation of the work, the plan value of the work situation is stored as part of the project information, and the work and the plurality of works Relevant information indicating the relationship with each evaluation information is stored as part of the project information,
The plan forecasting unit
Based on the related information of the project information stored in the plan management unit, the work evaluation information related to the work is acquired from the plurality of work evaluation information, and the plan value of the work status for the acquired work evaluation information The project management apparatus according to claim 2, wherein a probability distribution of the work situation for the acquired work evaluation information is generated by applying the selected probability distribution model. The plurality of work evaluation information is
The project management apparatus according to claim 3, comprising quality information indicating a quality of the deliverable in the work, cost information indicating the cost for the work, and process information indicating the progress of the work. The plan management department
For each of the plurality of operations, an actual value indicating the actual result of the operation when the operation is completed is stored as a part of the project information.
The project management device further includes:
The probability distribution database update part which updates the probability distribution model of the said probability distribution database part based on the actual value of the said project information which the said plan management part memorize | stored is provided. The project management device described. The plan management department
For each of the plurality of tasks, work-related information that is information necessary for performing the task is stored as part of the project information.
The project management device further includes:
A change condition definition unit that defines a change condition when changing the work of the project information and stores it in a storage device as a change condition database;
The project management apparatus according to claim 1, further comprising: a constraint condition data generation unit that defines a constraint condition for the work related information included in the project information and stores the constraint condition in a storage device as a constraint condition database. The plan management department
The work of the project information is changed based on the change condition database defined by the change condition definition unit and the constraint condition database defined by the constraint condition data generation unit. The project management device described. In the project management method of the project management apparatus for managing the work status for each of the plurality of works for a project comprising a plurality of works,
A plan management step in which the plan management unit associates a type of risk that is predicted to occur for each of the plurality of tasks and stores it in the storage device as project information;
A risk management unit that associates risk evaluation information for calculating a risk type and a risk magnitude and stores the risk information in a storage device as risk information;
A probability distribution database unit, a probability distribution database storage step for storing a plurality of predefined probability distribution models according to the magnitude of risk;
For each of the plurality of operations, the plan prediction unit obtains a risk type corresponding to the operation from the project information stored in the plan management step, and the risk information is stored in the risk information stored in the risk management step. The risk evaluation information corresponding to the type of the risk is acquired, the magnitude of the risk is calculated by the processing device based on the acquired risk evaluation information, and the probability distribution model corresponding to the calculated risk magnitude is the probability distribution database. A project management method for a project management apparatus, comprising: a plan prediction step selected from a section and generating a probability distribution of a work situation of the work by a processing device using the selected probability distribution model.   A project management program for causing a computer to execute the project management method of the project management apparatus according to claim 8.

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