JP6861176B2 - Project estimation support method and project estimation support device - Google Patents

Description

The present invention relates to a project estimation support method and a project estimation support device at the time of project startup.

As a background technology in this technical field, there is Patent No. 4086801 (Patent Document 1). In this gazette, "classification standard input means that accepts input of classification standard data, which is a standard for classifying the project into success and failure from project-specific data, and project characteristic weighting, which is a rate of increasing or decreasing project-specific data. Project characteristic weighted input means that accepts data input, main component score number input means that accepts input of the number of principal component scores, and data specific to the project specified by the project manager at the time of project planning for multiple past projects. The past project characteristic data including the above is classified into success and failure according to the classification standard data received by the classification standard input means and the data value peculiar to the project, and successful project characteristic data and failed project characteristic data are created. For the classification means and the project to be estimated, the estimation target project characteristic data including the data specific to the project specified by the project manager at the time of the project planning is increased or decreased by the project characteristic weighting data received by the project characteristic weighting input means. For each of the estimation target project characteristic data, the successful project characteristic data, and the unsuccessful project characteristic data that have been given and increased / decreased, the principal component scores of the number of principal component scores received by the principal component score input means are obtained. The total value calculated and added up is calculated, and the total value of the main component scores of each of the successful project characteristic data is compared with the total value of the main component scores of the project characteristic data to be estimated, and the difference is small. By extracting a predetermined number of characteristic data, similar projects of the estimation target project are estimated from the successful project characteristic data and used as similar successful project data. By comparing with the total value of the principal component scores of the project characteristic data to be estimated and extracting a predetermined number of the failed project characteristic data having a small difference, a similar project of the estimated project is estimated from the failed project characteristic data. A more significant success project by comparing the distribution of the actual data of the similar successful project data and the distribution of the actual data of the similar failure project data for each actual item with the similar project estimation means which is used as the similar failure project data. Narrow down, If the project manager receives a designation that the estimated data is not valid, it is provided with a significant estimation means that statistics the actual data of the narrowed down successful projects and creates the estimated data of the estimated target project. The classification standard input means accepts a change in the classification standard data, the project characteristic weighted input means accepts a change in the project characteristic weighted data, and the main component score number input means accepts a change in the number of main component scores, and the classification The means creates success project characteristic data and unsuccessful project characteristic data based on the changed classification criterion data, and the similar project estimation means is based on the changed project characteristic weighting data and the changed number of principal component scores. , Similar success project data and similar failure project data are extracted, and the significant estimation means is a project estimation support system characterized in that estimation data is created from the similar success project data and the similar failure project data. The method is described. That is, Patent Document 1 discloses a technique for calculating a project estimate using actual data of past successful projects.

There is also WO2010 / 095323 (Patent Document 2). This gazette provides "data that supports the execution feasibility judgment of a project based on the estimated cost value of the project deliverable. A collection of risk event parameters indicating the degree of estimated risk for each of a plurality of estimated risk events. With respect to the risk event parameter set, the similarity between the risk event parameter set of a plurality of past projects and the risk target parameter set of the target project is obtained (S41 to S43), and the target project is selected from the plurality of past projects. The N past projects with the highest degree of similarity are extracted (S43), and the cost deviation of the estimated cost value of the target project is obtained from the estimated cost value and the actual value of each of the N past projects (S45, 46). , Create cost fluctuation information based on the cost deviation of the target project (S47), and display this cost fluctuation information. ”(See abstract). That is, a technique for extracting a similar project group using the risk check items of the target project and the past project and predicting the cost deviation of the target project from the cost deviation information of the similar project group is disclosed.

Patent No. 4086801 WO2010 / 095323

When estimating a project, it is necessary to make an accurate estimate based on the work man-hours in consideration of the development scale and productivity of the project. On the other hand, there are always risks that affect the success of a project as it progresses. Therefore, it is difficult to make an accurate estimate.

In Patent Document 1, a project estimate is calculated using actual data of past successful projects. Thereby, the estimation accuracy can be improved. However, this technology does not fully consider the impact on cost due to the occurrence of risk, and it cannot be said that it is sufficient as data for estimation.
On the other hand, in Patent Document 2, cost fluctuations, that is, cost fluctuations, that is, past projects having a high degree of similarity to the target project are used by using a risk event parameter set which is a set of risk event parameters indicating the degree of estimated risk for each of a plurality of estimated risk events. , Calculates profit fluctuation information. However, to do so, it is necessary to list the major risk events that impede the success of the project in advance, and it is difficult to evaluate them at the time of estimation. In addition, when predicting cost deviation using check items that have little effect on loss, check items that should not be judged whether they are similar or not are also used, so cost deviation is used using past projects that are not similar to the target project. There was a problem that the prediction accuracy became low.
In order to solve this problem, it is necessary to predict cost fluctuations using project attribute information such as development form and development style that can be grasped at the time of project estimation, but since the project attribute itself is not a risk event, it is a target. There is no point in calculating the similarity between the project characteristics of the project and the past project. In particular, the combination of project characteristics of "quick delivery" and "new technology" can cause risk events such as "technology development is not in time", so recall the risk events from any project characteristics or combination of project characteristics. It is necessary to calculate the cost fluctuation. However, Patent Document 2 has a problem that the cost fluctuation cannot be calculated from such a viewpoint.

Therefore, an object of the present invention is to provide a technique capable of obtaining cost fluctuations (profit and loss fluctuations) in consideration of risk events and determining whether or not a project with high accuracy (category with high evaluation) can be executed.

In order to solve the above problems, in the present invention, data of past similar projects derived from the similarity of arbitrary project attribute items, for example, attribute items of attribute classification (business field, order form, development style, development scale, Attribute that has a factor that leads to failure in the combination of information of any attribute item when estimating the impact of risk of the target project using the information of the past project including the characteristics such as (project characteristics), planned value and actual value. Combination of item information, for example, extraction of categories that enable highly accurate prediction among the combination of project attributes, calculation of evaluation value for each category, and use of past project information that has the information of the attribute items Therefore, the forecast value of profit / loss fluctuation of the target project (for example, the estimated value of cost fluctuation) is calculated, and the influence of the risk of the target project, for example, the target sales (profit estimate) and the target profit / loss are estimated.

Specifically, it includes the following steps (1) to (5).
(1) Steps to accept project attributes (project name, attribute items, etc.) of the target project,
(2) A step of extracting a category for predicting cost fluctuations with high accuracy from a combination (category) of project attributes in the project attributes of the target project.
(3) Steps to extract past projects that belong to or are similar to the extracted category,
(4) Steps to calculate the cost fluctuation of the target project using the extracted cost fluctuation information (profit and loss deviation information) of the past project.
(5) A step of displaying the calculation result (profit and loss fluctuation forecast value) of the cost fluctuation of the target project.

When estimating the target project, by using a past project with a combination of attribute items (attribute values) that includes such risks, that is, that has factors that lead to failure, the predicted value of profit / loss fluctuation (cost fluctuation) It is possible to calculate a highly accurate estimate as an estimated predicted value).

For example, one of the representative project support devices and methods of the present invention is a project support method that supports the estimation of the target project based on the project attributes of the target project and the target information indicating the profit estimation of the target project.
The target project information reception step that executes the process of receiving the project attributes and target information of the target project and storing it in the target project information storage unit, and
For each project of the past project, a past project information storage step for executing a process of storing profit / loss deviation information indicating the profit of the past project and information of a project attribute group which is a collection of project attributes of the past project, and
From the profit / loss deviation information in the past project information storage unit, the evaluation value of the category composed of the combination of the project attribute groups is calculated, and the processing of storing the category evaluation information including the evaluation value in the category evaluation information storage unit is executed. Category evaluation calculation steps to be performed and
A similar project extraction step for executing a process of extracting a similar project having a high evaluation value from a plurality of past projects in the past project information storage unit using the evaluation value and the project attribute in the category evaluation information storage unit.
A forecast value calculation step for executing a process of calculating information including a profit / loss fluctuation predicted value related to a profit / loss fluctuation or a cost fluctuation with respect to the estimated value of the target project from the profit / loss deviation information of the similar project and the target information of the target project.
A forecast value display step for displaying the profit / loss fluctuation forecast value calculated by the forecast value calculation unit on the output device, and
It is characterized by having.

According to the present invention, it is possible to determine whether or not a project can be executed with high accuracy in consideration of risk. For example, when providing data that supports project estimation and execution feasibility judgment based on project characteristics, planned values (target information), and actual values of results for the plan, it is targeted as an estimated estimated value of cost fluctuations. It is possible to present a highly accurate forecast value of profit / loss fluctuation (forecast profit / loss fluctuation) of the project.

The block diagram which shows an example of the structure of the project estimation support apparatus of this invention. The figure which shows an example of the attribute information definition screen of this invention which inputs the definition of attribute item information. The figure which shows the item example of the attribute item definition information stored in the attribute item definition information DB. The figure which shows an example of the project information input screen of this invention which inputs the past project information. The figure which shows the item example of the past project information stored in the past project information DB of this invention. The flowchart which shows an example of the processing procedure of the estimation processing part of this invention. The flowchart which shows the other example of the processing procedure of the estimation processing part of this invention. The figure which shows an example of the project attribute input screen of this invention which inputs the target project information. The flowchart which shows an example of the processing procedure of the category evaluation processing part of this invention. The figure which shows the item example of the category evaluation value information stored in the category evaluation value information DB of this invention. The flowchart which shows an example of the processing procedure of the similar project extraction processing part of this invention. The figure which shows an example of the processing procedure of the predicted value calculation processing part of this invention. The figure which shows an example of the display screen which displays the estimation result displayed on the display part of an output device. The figure which shows the item example of the target project information stored in the target project information DB of this invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. For example, the project support device and method of the present invention are as follows. Calculate the predicted value of profit / loss fluctuation of the target project based on the project information (project attribute, target information / target sales, target profit / loss) of the target project and the project information (project attribute, actual information for the target information) of the past project. It is a project support device that outputs the predicted value as the estimation result of the target project.
It has a project information processing unit, a category evaluation processing unit, a similar project extraction processing unit, a predicted value calculation processing unit, and a predicted value display processing unit.
The project information processing department
Accepts the input of the project information of the target project, stores the received project attribute information in the target project information storage unit, and stores it.
The project information of the target project includes the project name, the attribute classification representing the characteristics of the project, the attribute items (business field, order form, development style, development scale, project characteristics) in the attribute classification, and the target information (target sales, target). It is the project attribute information including (profit and loss), and the past project information of the past project includes the project name, the attribute classification representing the characteristics of the project, and the attribute items (business field, order form, development style, development scale, development scale) in the attribute classification. Project attribute information including project characteristics) and profit / loss deviation information.
The category evaluation processing unit
A plurality of categories are created from a combination of attribute items of the target project information storage unit, the created plurality of categories are stored in the category evaluation information storage unit, and the categories are stored in the category evaluation information storage unit. On the other hand, the project group held by the category is extracted from the past project storage unit, and the evaluation value of the category is calculated using the profit / loss deviation information of the extracted project group.
Similar project extraction processing department
The project group used to calculate the predicted value based on the information in the category evaluation information storage unit is extracted as a similar project, and the project group is extracted.
The forecast value calculation processing unit calculates the profit / loss deviation information of the category and the forecast value (profit / loss fluctuation forecast value or cost fluctuation estimate forecast value) of the target project.
The predicted value display processing unit
A project support device characterized in that an estimation result including the predicted value is displayed on an output device.

In addition, the predicted value of profit / loss fluctuation of the target project is calculated based on the project information (project attribute, target information / target sales, target profit / loss) of the target project and the project information (project attribute, actual information for the target information) of the past project. However, it is a project support method in the project support device that outputs the predicted value as the estimation result of the target project.
The project support device consists of a computer, and the computer is
A project information processing step that accepts the input of the project information of the target project and stores the received project information in the target project information storage unit.
The project information of the target project is project attribute information including a project name, an attribute classification representing the characteristics of the project, an attribute item indicating an attribute in the attribute classification, and a target sales and a target profit / loss, and is a past project of the past project. The information is project attribute information including the project name, the attribute classification representing the characteristics of the project, the attribute item indicating the attribute in the attribute classification, and the profit / loss deviation information.
A plurality of categories are created from a combination of attribute items of the target project information storage unit, the created plurality of categories are stored in the category evaluation information storage unit, and the categories are stored in the category evaluation information storage unit. On the other hand, a category evaluation processing step of extracting a project group held by a category from the past project storage unit and calculating an evaluation value using the profit / loss deviation information of the extracted project group,
A similar project extraction processing step for extracting a project group used for calculating a predicted value based on the information in the category evaluation information storage unit as a similar project, and a similar project extraction processing step.
A forecast value calculation processing step for calculating profit / loss deviation information of the category and calculating a forecast value (profit / loss fluctuation forecast value) of the target project, and
A predicted value display processing step for displaying the estimated result including the predicted value on the output device, and
A project support method characterized by having.

Hereinafter, a project estimation support method and an embodiment of the apparatus according to the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing a configuration of a project estimation support device of the present invention.

The project estimation support device 113 is composed of, for example, a general computer, and has a central control device 103, an input device 104, an output device 105, a storage device 116, a processing device 117, and a communication interface 110. These are connected to each other by a bus.

Further, the project estimation support device 113 is a network 120 via the communication interface 110, and the attribute item definition terminal device 111 used when defining the attribute item of the project and the attribute item input used by the project manager or the like when estimating the target project. It is connected to the terminal device 112. The communication interface 110 constitutes a project definition receiving unit that receives a project definition.

The input device 104 includes an input unit such as a keyboard and a mouse for inputting and operating various information related to the project.

The output device 105 is a processing result processed by the processing device 117 based on the information input from the input device 104, the attribute item definition terminal device 111, the attribute item input terminal device 112, and the like, for example, the cost fluctuation. Includes a display such as a display that is displayed as a project estimation result that includes an estimated forecast value (profit and loss fluctuation forecast value).

The communication interface 110 includes a communication interface unit that transmits and receives various information to and from the attribute item definition terminal device 111, the attribute item input terminal device 112, and the like via the network 120.

The storage device 116 includes a storage unit including a database (hereinafter abbreviated as DB), for example, an attribute item definition information DB (definition information storage unit) 106, a target project information DB 107, a past project information DB 108, and a category evaluation information DB 109. And so on. The information items of each DB will be described later.

The processing device 117 includes an estimation processing unit (including target project information receiving unit) 102, a category evaluation processing unit (category evaluation calculation unit) 114, a similar project extraction processing unit 101, a predicted value calculation processing unit 115, and an item definition processing unit 118. Has.
The processing device 117 and the storage device 116 may be distributed on the network.

The central control device 103 controls the extraction and storage of information from each device, the operation control of each device, and controls the processing device 117 and the like according to the program stored inside.

The estimation processing unit 102 has, for example, a function of receiving the project information of the target project input from the attribute item input terminal device 112 and writing the project information into the target project information DB 107.

The category evaluation processing unit 114 extracts a category that predicts a highly accurate project estimate (profit / loss fluctuation / cost fluctuation) from a combination of project attributes (project name, attribute item) called a category in the project attribute of the target project. It has a function to perform the processing. The highly accurate project estimate forecast indicates an estimate forecast of a category in which cost fluctuations (profit and loss fluctuations) can be predicted with high accuracy, that is, a category with a high evaluation in FIG.
The attribute item represents the characteristics of the project such as "business field", "order form", "development style", "development scale", and "project characteristics", and the attribute item is an arbitrary attribute item. Including the specific attribute values in, for example, values (attribute values) such as "scratch", "package", and "current system diversion" are taken as attribute items of "development style". Details will be described later.

The similar project extraction processing unit 101 has a function of extracting a project group used for calculating a predicted value based on the information of the category evaluation information DB 109 as a similar project.

The predicted value calculation processing unit 115 has, for example, a function of calculating the profit / loss deviation information of the category and calculating the predicted value (profit / loss fluctuation predicted value) of the target project.

The item definition processing unit 118 reads the information (attribute classification, attribute item definition information including the attribute item) that defines the attribute item of the project input by the attribute item definition terminal device 111, and sets the read information as an attribute. It has a function of performing a process of writing to the item definition information DB 106.
The detailed operation of each processing unit will be described later with reference to FIGS. 9, 11, and 12.

FIG. 2 is a diagram showing an example of a definition screen of attribute item information in the attribute item definition terminal device 111.
In the figure, the attribute item information definition screen 20 defines the attribute classification 201 and the attribute item 202, and the locations 203 where the attribute classification 201 is input and the locations 204, 205, 206 where the attribute values of the attribute item 202 are input. , ・ ・ Has.

As described above, the attribute classification 201 is a classification showing the characteristics of the project such as the "business field", "order form", "development style", "development scale", and "project characteristics" of the attribute items (see FIG. 3). ..

The attribute item (202) refers to a specific attribute in any attribute classification as described above. For example, as a specific attribute item related to the attribute classification of "business field", "finance", "public", and "" Take values such as "manufacturing" and "distribution". In addition, as a specific attribute item related to the attribute classification called "order form", values such as "new development", "in-house replacement", and "replacement by another company" are taken, and a specific attribute classification related to "development style" is taken. As attribute items, values such as "scratch", "package", and "current system diversion" are taken.

The information (attribute values of the attribute classification 201 and the attribute item 202) input using the attribute item information definition screen 20 is written to the attribute item definition information DB 106 by clicking the registration button 207. The reset is performed by clicking the reset button 208.
FIG. 3 shows the state of registration of the result input using the attribute item information definition screen 20 in the attribute item definition information DB 106.

FIG. 3 is a diagram showing an example of information items in the attribute item definition information DB 106.
The attribute item definition information DB 106 has, for example, a table for storing the attribute item definition information, and has an area 301 for storing the attribute classification and an area 302 for storing the attribute items as shown in the figure.

That is, the value of the place 203 where the attribute classification 201 shown in FIG. 2 is input is in the area 301 of the attribute classification, and the values of the places 204 to 206 where the value of the attribute item 202 shown in FIG. 2 is input are the attribute items. It is stored in the area 302.
For example, "order form" is input in the place 203 where the attribute classification 201 shown in FIG. 2 is input, "new development" is input in the place 204 where the value of the attribute item 202 is input, and the place 205 where the value of the attribute item 202 is input. When "replacement by another company" is input in the place where the value of the attribute item 202 is input in "in-house replacement", the area 301 of the attribute classification and the area 302 of the attribute item in the attribute item definition information DB 106 shown in FIG. "Order form": "new development", "order form": "in-house replacement", "order form": "replacement of another company" are stored as records 303, 304, 305, respectively.

FIG. 5 is a diagram showing an example of information items of the past project information DB (past project information storage unit) 108.
The past project information DB 108 has, for example, a table in which information items of the past project are stored as features and actual values (data) of the past project, and the table has attributes together with an area 508 in which the project name is stored as shown in the figure. Areas 501 to 505 where business fields, order forms, development styles, development scales, project characteristics, etc. corresponding to the attribute classification area 301 stored in the item definition information DB 106 are stored, and areas where profit / loss deviation information is stored. 506). Further, although not shown, the table may have an area for storing the target value (estimated value) and the result (actual value) at the time of the project, which is the original data for calculating the profit deviation information of the past project. Good.

Then, information on one past project is stored for each record of each project (A to J projects). For example, "A project" in the area 508 of the project name includes "finance" in the area 501 of the business field, "new development" in the area 502 of the order form, "package" in the area 503 of the development style, and the area of development scale. "Small scale" is stored in 504, "quick delivery" is stored in the project characteristic area 505, and "-35%" is stored in the profit / loss deviation information area 506. Each information as shown in the figure is stored in the other B to J projects.

The profit / loss deviation information in the area 506) of FIG. 5 of the profit / loss deviation information is the sales target profit / loss deviation ratio obtained by dividing the profit / loss deviation (difference between the target profit / loss and the actual profit / loss) by the sales. It does not have to be a rate. For example, the rate of increase in cost or the deviation amount of profit or loss itself may be used. In other words, necessary past project information may be set according to the purpose of project estimation support. The target profit / loss information, which is the target project information, is input from the target project attribute input screen 80 for inputting the target project information items shown in FIG.
Further, the information stored in the past project information DB 108 may be directly written, but may be input using, for example, the past project information input screen 40 as shown in FIG.

FIG. 4 is a diagram showing an example of a project information input screen for inputting past project information in the input device 104 or the attribute item input terminal device 112.
In the figure, the past project information input screen 40 is a place 401 for inputting a project name as shown, a place 403 for inputting a business field, an order form, a development style, a development scale, a project characteristic, etc. as an attribute classification, and a project. It has a place 404, etc. for inputting profit / loss deviation information of. It also has a registration button 405 and a reset button 406.

The place to enter the business field includes, for example, a check box type attribute item for checking and selecting "finance", "public", "manufacturing", "distribution", etc., and the place for entering the order form is, for example. , "New development", "In-house replacement", "Replacement by other companies", etc. are checked and selected, including check box type attribute items, and the places to enter the development style are, for example, "Scratch", "Package", "Current". Check box to check and select "System diversion" etc. Check box to check and select "Large scale", "Medium scale", "Small scale", etc. The part including the type attribute item and inputting the project characteristics includes, for example, the part 403 of the check box type attribute item for checking and selecting "new customer", "quick delivery", "business reform" and the like.

The registration button 405 registers each information about the past project input in each attribute item in the past project information DB 108, and the reset button 406 resets the registered information.

The attribute classification part 402 and the attribute item part 403 of the business field, order form, development style, development scale, project characteristics, etc. are the values of the attribute classification area 301 and the attribute item area 302 of the attribute item definition information DB 106. Is displayed based on. The input contents of the past project information input screen 40 are stored in the past project information DB 108.

FIG. 6 is a flowchart showing an example of a processing procedure including the estimation processing unit 102, which is the core processing of the project estimation support method. The operation based on the flowchart of FIG. 6 is as follows.

First, in step 601 the estimation processing unit 102 includes the project information (project name, business field, order form, development style, development scale, project characteristics) of the target project input by the attribute item input terminal device 112. Estimated data / or estimated value (target sales, target profit / loss) is read, and the read target project information is written in the target project information DB 107 (see FIG. 14).

Here, the target project information is input using, for example, the target project attribute input screen 80 of the attribute item input terminal device 112 as shown in FIG.

The target project attribute input screen 80 is a place for inputting an attribute classification including a place for inputting a project name as shown in the figure 801 and a business field, an order form, a development style, a development scale, a project characteristic, etc. 803 (attribute items such as finance and public), 804 for inputting the target sales of the project, and 805 for inputting the target profit / loss. It also has a registration button 806 and a reset button 807 to reset.

The place to enter the business field includes the place to enter the check box type attribute item 801 to check and select "finance", "public", "manufacturing", "distribution", etc., and the place to enter the order form. Includes check box type attribute items to check and select "new development", "in-house replacement", "replacement by other companies", etc., and the places to enter the development style are "scratch", "package", "current system" Check and select check box type attributes such as "Divert", etc., and check and select "Large scale", "Medium scale", "Small scale", etc. in the place to enter the development scale. The place where the item is included and the project characteristics are input includes the check box type attribute item 803 for checking and selecting "new customer", "quick delivery", "business reform", and the like.

The registration button 806 registers each information about the target project input in each attribute item in the target project information DB 107, and the reset button 807 resets the registered information.

Attribute classification (business field, order form, development style, development scale, project characteristics) 802 and its attribute items (finance, public, manufacturing, new development, replacement of other companies, package, scratch, current system diversion, small scale, medium scale, Large-scale, quick delivery, new technology, new customer) 803 is displayed based on the attribute classification of the attribute item definition information DB 106 and the value of the attribute item (attribute classification of area 301 in FIG. 3, attribute item of area 302). To. The input contents of the target project attribute input screen 80 are stored in the target project information DB 107 (see FIG. 14).

FIG. 14 is a diagram showing an example of information items of the target project information DB 107.
The target project information DB 107 includes an area 1401 for storing the project name, an area 1408 for storing the target sales, and an area 1409 for storing the target profit / loss, and each attribute classification (area of FIG. 3) stored in the attribute item definition information DB 106. It has regions 1402-1406 of 301).
That is, in FIG. 14, there are a business field area 1402, an order form area 1403, a development style area 1404, a development scale area 1405, and a project characteristic area 1406 as attribute classification (attribute classification area 301 in FIG. 3). It is shown that.

For example, if the project name is "N project", the business field is "finance", the order form is "new development", the development style is "package", the development scale is "large scale", and the project characteristics are "new customer". It shows that it is stored as 1407.

Next, in step 602, the category evaluation processing unit 114 extracts a category for predicting a project estimate with high accuracy from a combination of project attributes called a category in the project attributes of the target project.

An example of extracting a category will be described. FIG. 9 is a flowchart showing a specific processing example of the category evaluation processing unit 114.

As shown in FIG. 9, the category evaluation processing unit 114 has a function of creating a category (step 901) and a function of calculating an evaluation value for each category (step 902).

The category creation (step 901) is created from the combination of the attribute items stored in the target project information DB 107.
The category is composed of a combination of "values of attribute items" or "all attribute items" stored for each attribute classification.

For example, as shown in record 1407 of FIG. 14, "finance" is in the area 1402 for storing the business field, "new development" is in the area 1403 for storing the order form, "package" is in the area 1404 for storing the development style, and the development scale. When "large scale" is stored in the area 1405 that stores the project and "new customer" is stored in the area 1406 that stores the project characteristics, the business field is "finance" or "all", and the order form is "new development" or "new development". Generate a combination of "all", development style "package" or "all", development scale "large scale" or "all", and project characteristics "new customer" or "all" as categories.
In this case, 32 categories, which are 2 to the 5th power, are created. The created category is stored in the category evaluation information DB 109 (see FIG. 10).

The created category is shown in FIG. The created category holds the attribute items held by each category (category 1 to 32) of the category evaluation information DB 109, and together with the area 1011 in which the category name is stored and the area 1006 in which the evaluation value is stored. For example, the attribute classification of the area 1001 in which the business field is stored, the area 1002 in which the order form is stored, the area 1003 in which the development style is stored, the area 1004 in which the development scale is stored, and the area 1005 in which the project characteristics are stored. Has a column of.

The attribute classification column has the value of the attribute item or the value of "all" held by the target project for each attribute classification.
Here, "all" means that the value of the attribute classification is not important in calculating the predicted value.

In the category evaluation information DB 109, "*" is used as the meaning of "all".
For example, in the record 1008 of FIG. 10, the business field is "all" (finance, public, manufacturing, distribution), the order form is "new development", the development style is "all" (scratch, package, current system diversion), and development. The scale is "all" (small, medium, large), and the project characteristics are "all" (quick delivery, new technology, new customers). Record 1010 has a business field of "finance" and an order form. Is the category of "new development", the development style is "package", the development scale is "large scale", and the project characteristics are "new customers".

Further, the record 1007 has a business field, an order form, a development style, a development scale, and a project characteristic of "all", and this is a category representing all the projects stored in the past project information DB 108. Further, since the category name area 1011 is a category identifier, an independent value is automatically assigned in the process of creating the category (step 901).

In the calculation of the evaluation value for each category (step 902), for each category stored in the category evaluation information DB 109, the project group holding the attribute items held by the category is extracted from the past project information DB 108. Then, the evaluation value in the evaluation value area 1006 is calculated using the profit / loss deviation information (see the area 506 in FIG. 5) of the extracted project group (projects A to J in FIG. 5).

The evaluation value (region 1006) is, for example, an evaluation value relating to the variation in the profit / loss deviation information (region 506 of FIG. 5) of the past project group belonging to the category.
Here, the fact that there is little variation means that a highly accurate predicted value can be calculated using the data of the past projects included in the category.

Next, in step 603, the similar project extraction processing unit (similar project extraction unit) 101 uses the similar project group from the past project information DB 108 to calculate the predicted value based on the information in the category evaluation information DB 109. Extract as (data of similar projects in the past).

The similar project extraction processing unit 101 is performed according to a predetermined rule. For example, according to the rule of ..., the extraction function (step 1101) for categorizing (category n) having a high evaluation value (see the evaluation value in FIG. 10) as shown in FIG. 11, and the attribute items held by the extracted category are selected. It is composed of a function to extract (step 1102) and a function to extract past projects (A, C, E, I projects) having attribute items (step 1103).

Extraction 1101 of a category having a high evaluation value is possible by searching for a category having a high evaluation value by the value of the evaluation value (area 1006 in FIG. 10) of the category evaluation information DB 109.

In the example shown in FIG. 10, the evaluation value "3.84" of the record 1009 is the most, assuming that the one with the smaller evaluation value has less variation in the profit / loss deviation information (area 506 of FIG. 5) of the past project group belonging to the category. It will be highly evaluated.

Extraction of the attribute items held by the category (step 1102) is to extract the attribute items of the highly evaluated category. For example, from record 1009, the business field is "all", the order form is "new development", and development. The style is "package", the development scale is "all", and the project characteristics are "all".

The extraction of the past project having the attribute item (step 1103) is to extract the project holding the attribute item extracted in the extraction of the attribute item held by the category (step 1102) from the past project DB (see FIG. 5) 108. is there.
For example, in the case of record 1009, records 507, 509, 510, and 511 of the A, C, E, and I projects in the example of FIG. 5 are extracted as projects whose order form is "new development" and development style is "package". To.

For a category consisting of a combination of attribute values of multiple attribute items, the risk of each combination is assumed.
For example, in the case of a combination (category) including business field: "public", order form: "replacement of other companies", and order style: "scratch", between "public" and "replacement of other companies", for example, the law Risks are expected due to the revision of.
In the case of a combination (category) that includes business field: "finance", order form: "new development", order style: "package", project characteristics: "quick delivery", "new development" and "package" In the meantime, for example, risks such as "technological development is not in time" are assumed.

Therefore, by estimating the target project using the past projects of the combination (category) of the attribute items (attribute values) that include such risks, that is, the factors that lead to failure, the predicted value of profit / loss fluctuation ( It is possible to calculate a highly accurate estimate as an estimated estimated value of cost fluctuations). As a result, it is possible to make an appropriate feasibility judgment by estimating the project including the impact of risk.

The predicted value calculation processing unit (predicted value calculation unit) 115 calculates the predicted value (predicted value of profit / loss fluctuation of the target project) in step 604. The predicted value calculation processing unit 115 includes, for example, a function of calculating profit / loss deviation information of the category as shown in FIG. 12 (step 1201) and a function of calculating the predicted value of the target project (step 1202).

The calculation of the profit / loss deviation information of the category (step 1201) uses the profit / loss deviation information of the project group (area 506 in FIG. 5) extracted by the extraction of the past project having the attribute item (step 1103), and the profit / loss of the target project. Calculate the fluctuation.

For example, projects (A, C, E, I) such as records 507, 509, 510, 511 (see FIG. 5) extracted as a project in which the order form of record 1009 is "new development" and the development style is "package". The average value of the profit / loss deviation information (“-35%”, “-20%”, “-25%”, “-20%” in the area 506 of FIG. 5) in the project) is calculated as the profit / loss deviation information.

In the calculation of the predicted value of the target project (step 1202), the value of the calculation of the profit / loss deviation information of the category (step 1201), the target sales of the target project information DB 107 (area 1408 in FIG. 14), and the target profit / loss (area 1409 in FIG. 14). From, the predicted value of the profit and loss fluctuation of the target project is calculated.

For example, if the calculated value (step 1201) of the profit / loss deviation information of the category is "-15%", the profit margin may fluctuate by -15% with respect to the target profit / loss (see 1409 in FIG. 14) in the target project. , Calculate the value when the profit margin of the target project fluctuates by -15% as the estimated estimated value of cost fluctuation.

In short, when estimating the risk impact of the target project based on the data of past similar projects derived from the similarity of arbitrary project attribute items, items that have factors that lead to failure in the combination of arbitrary item information. A combination of information (category) is extracted, and the risk impact of the target project is estimated using the past projects that have the item information of the extracted category.

In the display of the predicted value, the estimated predicted value of the cost fluctuation calculated by the predicted value calculation processing unit 115 is displayed on the predicted value display unit as the estimation result in step 605. FIG. 13 shows an example of a display screen of the estimation result.

That is, the information of the target project is shown in the frame 1301, and the estimated predicted value of the cost fluctuation calculated by the predicted value calculation processing unit 115 (step 604) is displayed in the frame 1302. In addition, the category on which the predicted value is calculated is also displayed in frame 1303.
More specifically, in the frame 1301, as the target project information, as shown in the figure, the project name: M project, the business field: finance, the order form: new development, the development style: package, the development scale: large scale, the project characteristics: new. Customers, target sales: XX yen, target profit / loss △△ yen, etc. are displayed, and in frame 1302, forecast profit / loss fluctuations: − □□ yen, etc. are displayed as profit / loss fluctuation forecast values, and in frame 1303, As the calculation basis category, business field: all, order form: new development, development style: package, development scale: all, project characteristics: all, etc. are displayed.

In this embodiment, an example of a derivative processing method of the processing (step 602) in the category evaluation processing unit 114 in the target project information input in the estimation processing unit 102 will be described.
Since the processes other than the category evaluation processing unit 114 (step 602) are the same as those in the first embodiment, the description thereof will be omitted.

FIG. 7 is a flowchart showing an example of a derivative processing procedure.
As the processing procedure of the estimation processing unit 102, the processing (step 702) in the category evaluation processing unit 114 is input of the project information of the target project (step 601), the processing in the similar project extraction processing unit 101 (step 603), and the predicted value calculation processing. It is processed separately from the part 115 (step 604) and the display of the predicted value (step 605). That is, the category evaluation process is performed separately from each process such as inputting the project information of the target project, extracting similar projects, calculating the predicted value, and displaying the predicted value.

In this case, the category of the category evaluation information DB 109 is composed of possible values of "values of attribute items" stored for each attribute classification or a combination of "all attribute items".
That is, the categories corresponding to the combination of the number of attribute items of each attribute classification + 1 multiplication are generated.
In this case, the similar project extraction processing unit 101 (step 603) does not search for a category with a high evaluation by the value of the evaluation value (area 1006 in FIG. 10) of the category evaluation information DB 109, but rather in the category evaluation information DB 109. It is necessary to perform a process of extracting a category having a high evaluation from the categories matching the combination of the attribute items stored in the target project information DB 107.

According to the above-described embodiment, when estimating the influence of the poetry risk of the target project, a combination of information of attribute items having a factor leading to failure is extracted from any combination of attribute items, and the extracted attribute By estimating the impact of the poetry of the target project using the past project with item information, it is not necessary to list the major risk events that hinder the success of the project, which is a problem of the prior art, and the risk is manifested. It can be expected to obtain a highly accurate project estimate that takes into account the cost impact of doing so.

The present invention is not limited to the above-described examples, and includes various modifications. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one including all the described configurations. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment in addition to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.
Further, each of the above configurations, functions, processing units, processing means and the like may be realized by hardware by designing a part or all of them by, for example, an integrated circuit. Further, each of the above configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be stored in a memory, a hard disk, a recording device such as an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

111 Attribute item definition terminal device 112 Attribute item input terminal device 113 Project estimation support device 117 Processing device 116 Storage device

Claims (6)

In the project estimation support device that supports the estimation of the target project based on the attributes of the target project and the target information indicating the profit estimation of the target project.
It has a target project information reception unit, a target project information storage unit, a past project information storage unit, a category evaluation information storage unit, a category evaluation calculation unit, a similar project extraction unit, a predicted value calculation unit, and a predicted value display unit.
The target project information reception department
Accepts the target project attribute of the target project and stores it in the target project information storage unit.
The past project information storage unit
For each project of the past project, profit / loss deviation information indicating the profit of the past project and information of the project attribute group which is a collection of project attributes of the past project are stored.
The category evaluation calculation unit
From the profit / loss deviation information in the past project information storage unit, the evaluation value of the category composed of the combination of the project attribute groups is calculated, and the category evaluation information including the evaluation value is stored in the category evaluation information storage unit.
The similar project extraction unit
Using the evaluation value and the project attribute in the category evaluation information storage unit, a similar project having a high evaluation value is extracted from a plurality of past projects in the past project information storage unit.
The predicted value calculation unit
From the profit / loss deviation information of the similar project and the target information of the target project, information including the profit / loss fluctuation predicted value regarding the profit / loss fluctuation or the cost fluctuation with respect to the estimated value of the target project is calculated.
The predicted value display unit displays the profit / loss fluctuation predicted value calculated by the predicted value calculation unit on the output device.
A project estimation support device characterized by this. In the project estimation support device according to claim 1,
The attribute items of the target project include a business field, an order form, a development style, a development scale, and a project characteristic, and the target information includes a target sales and a target profit / loss.
The order form includes new development, in-house replacement, replacement by another company, the development style includes package, scratch, current system diversion, and the project characteristics include short delivery time, new technology, new customer.
The category evaluation calculation unit is a project estimation support device, which calculates an evaluation value of the category from variations in profit / loss deviation information of the past project belonging to the category. In the project estimation support device according to claim 1,
In addition, it has a project definition reception unit and a definition information storage unit.
The project definition reception unit defines the attribute items of the target project, receives the project attributes including the attribute items, and stores them in the definition information storage unit.
A project estimation support device characterized in that the category evaluation calculation unit automatically generates the category using the information of the definition information storage unit. In the project estimation support method in the project estimation support device that supports the estimation of the target project based on the project attributes of the target project and the target information indicating the profit estimation of the target project.
The project estimation support device is
The target project information reception step that executes the process of receiving the project attributes and target information of the target project and storing it in the target project information storage unit, and
For each project of the past project, the past project information that executes the process of storing the profit / loss deviation information indicating the profit of the past project and the information of the project attribute group which is a collection of the project attributes of the past project in the past project information storage unit. Memory steps and
A process of calculating the evaluation value of the category composed of the combination of the project attribute groups from the profit / loss deviation information in the past project information storage unit and storing the category evaluation information including the evaluation value in the category evaluation information storage unit. Category evaluation calculation steps to be performed and
Similar project extraction step of executing a process of extracting a similar project having a high evaluation value from a plurality of past projects of the past project information storage unit using the evaluation value and the project attribute in the category evaluation information storage unit. When,
A forecast value calculation step for executing a process of calculating information including a profit / loss fluctuation predicted value related to a profit / loss fluctuation or a cost fluctuation with respect to an estimated value of the target project from the profit / loss deviation information of the similar project and the target information of the target project. ,
A forecast value display step for displaying the profit / loss fluctuation forecast value calculated by the forecast value calculation step on the output device, and a forecast value display step.
A project estimation support method characterized by having. In the project estimation support method described in claim 4,
The attribute items of the target project include a business field, an order form, a development style, a development scale, and a project characteristic, and the target information includes a target sales and a target profit / loss.
The order form includes new development, in-house replacement, replacement by another company, the development style includes package, scratch, current system diversion, and the project characteristics include short delivery time, new technology, new customer.
The category evaluation calculation step is a project estimation support method, characterized in that the evaluation value of the category is calculated from the variation of the profit / loss deviation information of the past project belonging to the category. In the project estimation support method according to claim 4 or 5,
The project estimation support device is
Further, it has a project definition reception step for defining the attribute items of the target project, accepting the project attributes, and executing the process of storing the project attributes in the definition information storage unit.
A project estimation support method, characterized in that the category is automatically generated using the information in the definition information storage unit in the category evaluation calculation step.

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