JP4003499B2 - Estimate evaluation support program and estimate evaluation support system - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to evaluation support for estimation work in consideration of the number of files to be developed, the skill level of development personnel, and the like in the planning of a new project for software development and the like.
[0002]
[Prior art]
In project planning, the number of screens and forms to be newly created based on development requirements, the number of files, the degree of software asset diversion, the skill level of development personnel, etc. are considered, and the man-hours and development period considered necessary are determined. Make an estimate. If this estimate is wrong, it will cause a significant loss in profit and loss, and will cause a great deal of damage to the customer due to a shift in development time, so it is important to make an appropriate estimate.
[0003]
As such a project planning method, JP-A-62-152065 stores the work experience and productivity of development personnel, and the amount of work in the development process, and evaluates the plan while allocating each personnel and performing a simulation. Japanese Patent Laid-Open No. 2-68658 proposes a method for diagnosing a plan for each item by setting a plan value and an evaluation scale for some items for project management elements.
[0004]
In these proposals, since the project planner's subjectivity is included in the evaluation of the development personnel, or the work man-hours fluctuate depending on the contents of the project to be developed, the applicant has already been developed in Japanese Patent Laid-Open No. 2001-265917. An estimation evaluation support system for a new project was proposed based on the actual data of the project. As shown in FIG. 12, this system digitizes actual data for characteristic items such as the number of files and the presence / absence of a reuse program (actual data characteristic numerical means 101), groups similar data into groups, These characteristic items are digitized and used as evaluation reference data (evaluation reference setting means 102). Then, the evaluation target estimate data is digitized in the same way as the actual data (estimated data characteristic digitizing means 103), and compared with the evaluation reference data characteristic item, the estimate of the new project is reconsidered. Thus, an alarm is issued (estimated data evaluation means 104). This estimate evaluation support system has a feature that the project planner's subjectivity and evaluation scale do not change because it is based on the performance data.
[0005]
[Problems to be solved by the invention]
As described above, the estimate evaluation support system of Japanese Patent Laid-Open No. 2001-265917 groups performance data, creates an evaluation standard for the group, and compares the evaluation standard with the estimated data. In other words, the group is a group having a similar tendency, and the validity of the estimate is judged by looking at the estimate data to be evaluated and the group as a macro.
[0006]
In addition to the estimate evaluation support system previously proposed by the present applicant, the present invention regards factors that affect development productivity as productivity characteristic items, quantifies them, and sets the estimated data to be evaluated as equivalent. The purpose is to support estimation evaluation so that the accuracy of estimation can be further improved by pointing out items that are inferior to actual data having values of productivity characteristic items.
[0007]
[Means for Solving the Problems]
The principle of claim 1 of the present invention will be described with reference to FIG. The present invention comprises an actual data characteristic quantification procedure 1, a group evaluation value creation procedure 2, an estimated data characteristic quantification procedure 3, a group evaluation procedure 4, an actual data extraction procedure 5, and a productivity evaluation procedure 6. The data and display before and after each procedure in FIG. 1 represent inputs and outputs for the procedure.
[0008]
In the performance data characteristic quantification procedure 1, the accumulated performance data of the developed project is digitized by stage evaluation for predetermined project characteristic items and productivity characteristic items. The project characteristic item is an item related to the characteristic of the project, and includes a plurality of items such as a program language and the number of developed files. Digitization is performed so that 1 is used when the program language is 4GL, and 0 when the program language is 3GL. The productivity characteristic item is an item related to development productivity, and includes, for example, a plurality of items such as a customer participation rate in formulating development requirements and a component sharing rate for software sharing. Similar to the quantification of project characteristic items, this is quantified by a predetermined step evaluation.
[0009]
The group evaluation value creation procedure 2 classifies a plurality of actual data based on the quantified project characteristic items, groups similar projects, determines the numerical value of the project characteristic item for the group, and sets it as the group evaluation characteristic value. . That is, the group evaluation characteristic value is a value indicating the total value of the performance data.
In the estimated data characteristic quantification procedure 3, the estimated data to be evaluated is converted into numerical values for the project characteristic item and the productivity characteristic item in the same manner as the actual data.
[0010]
The group evaluation procedure 4 compares the value of the project characteristic item of the estimated data with the group evaluation characteristic value, and displays an alarm if it is different from this value. This alarm is used to warn that the estimated data is far from the actual data.
The actual data extraction procedure 5 calculates the sum of the actual data and the estimated data productivity characteristic item values in the actual data characteristic quantification procedure 1 and the estimated data characteristic quantification procedure 3 The actual data that is closest to the sum of the values of the productivity characteristic items is extracted.
[0011]
The productivity evaluation procedure 6 compares the value of the productivity characteristic item of the extracted actual data and the value of the productivity characteristic item of the estimated data for each item, and if there is a low numerical value item in the estimated data, Point out. From the viewpoint of productivity, this points out productivity characteristics items that are inferior in comparison with similar performance data in order to further increase the safety level of the estimate, and requires examination of the estimate.
[0012]
By configuring as described above, it is possible to evaluate whether the estimate at the time of planning a new project matches the trend of the actual data by group evaluation, and furthermore, from the viewpoint of productivity, it is possible to evaluate from the viewpoint of productivity. It can be performed.
The invention of claim 2 prescribes that the project characteristic items are the type of project, the number of development files, the development efficiency, the presence / absence of diversion of software assets, the type of program language, and the skill level of development personnel. For example, the project type is information system or core system, the number of development files is the number of files developed (or developed), the development efficiency is the number of screens and forms developed with respect to the total development man-hours. Productivity characteristics items are defined as customer participation level, technical difficulty level, software sharing level, skill level of development personnel, and presence / absence of organizational support. For example, the degree of customer participation is the degree to which a customer participates in developing development requirements and creating test data, and the technical difficulty level is whether it is a new technical field or the degree of complexity. Organizational support is the presence or absence of support outside the development department such as the quality control department. The skill level of the development personnel is listed as a characteristic item in both the project characteristic item and the productivity characteristic item.
[0013]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to FIGS.
FIG. 2 shows an example configuration of the present invention. The estimate evaluation support system 10 includes a data input unit 11, a characteristic item digitization unit 12, a group evaluation value creation unit 13, a group evaluation unit 14, and a productivity evaluation unit 15. It comprises a processing unit and a storage unit for a performance data table 16, a performance characteristic table 17, an estimated data table 18, an estimated characteristic table 19, a numerical value conversion table 20, and a group evaluation characteristic value table 21. Further, the estimate evaluation support system 10 is connected to an input device 30 for inputting estimate and performance data and a display device 40 for displaying the evaluation result.
[0014]
First, each processing unit will be described. First, the data input unit 11 reads the actual data and the estimated data from the input device 30 and stores them in the actual data table 16 and the estimated data table 18, respectively. The actual data is input at any time when the development of the project is completed and is accumulated in the actual data table 16. Estimated data is data to be evaluated that will be evaluated from now on.
[0015]
The characteristic item quantification unit 12 quantifies the project characteristic item and the productivity characteristic item with reference to the numerical value conversion table 20 with respect to the data of the actual data table 16 and the estimated data table 18, and the quantified data. Are stored in the performance characteristic table 17 and the estimated characteristic table 19. In the present embodiment, the project characteristic items include the project type, the number of files, the development efficiency, the presence / absence of asset diversion, the program language, and the development staff skill. Productivity characteristic items will be described later.
[0016]
The group evaluation value creation unit 13 sorts the data of the performance characteristic table 17 in the order of the project type, the number of files, and the development efficiency, and determines the values of the project characteristic items including whether the asset is diverted, the program language, and the development staff skill. Divide into groups based on similarity. Subsequently, the property items of asset diversion, program language, and personnel skill are digitized with reference to the numerical conversion table 20 and stored in the group evaluation characteristic value table 21. At this time, the project type, the number of files, and the development efficiency are stored as group discrimination criteria, and the presence / absence of asset diversion, the program language, and the staff skill are stored as intra-group evaluation criteria.
[0017]
The group evaluation unit 14 compares the project characteristic item value in the estimated characteristic table 19 with the group discrimination criterion in the group evaluation characteristic value table 21 to determine which of the groups the estimated data belongs to. It is determined whether the evaluation criteria are satisfied, and an alarm is displayed when the user is out of the group or out of the group evaluation criteria.
[0018]
The productivity evaluation unit 15 obtains the total for the productivity characteristic item values in the performance characteristic table 17 and the estimated characteristic table 19 and compares them to select and select the actual data closest to the total estimated data. When there is a low numerical value item in the estimated data by comparing the productivity characteristic item value of the actual data and the estimated data, the item is pointed out.
[0019]
Next, an example of the data structure of the storage unit will be described.
The performance data table 16 is a table for storing the performance data of projects that have been developed, and an example of the data structure is shown in FIG. The results data table 16 includes a PJ name (project name), a department in charge, a person in charge, a contact information, a PJ type (project type), a program language, a new development scale, an asset diversion scale, a man-hour by process, and an operating date. , Cost rate, productivity factor fields. Each field of new development scale and remodeling scale for asset diversion is composed of subfields of screen number, form number, file number, step number, and man-hours by process are SA (system design), UI (user interface) ), SS (detailed design), PS (program design), PG (programming), PT (program test), IT (interface test), ST (system test), OT (operation test), total (SA-OT man-hours) ), Working days and cost rates are planned and actual, productivity factors are customer participation rate, customer test data creation, new fields, complexity, software component rate, asset diversion rate, development personnel skills, organizational support Consists of subfields. Here, the productivity factor and its subfield will be described in more detail. The productivity factor is a factor that affects the productivity in the development of the system. In the embodiment of the present invention, eight factors in the subfield are taken up. First, the customer participation rate and the creation of customer test data are set as the customer participation rate. The customer participation rate is the degree of customer participation in the development requirements formulation, etc., and is expressed as a percentage (%) of the total. Customer test data creation indicates the degree provided by the customer in creating test data, and is a ratio to the total man-hour required for test data creation. Next, as the technical difficulty, the new field and complexity were raised. The new field is whether the project being developed was a technologically new field for the development department, the complexity is the degree of complexity of the system being developed. The software component ratio and asset diversion rate were used as the degree of software commonality. The software component ratio is the ratio of the number of software steps to the total number of development steps, and the asset diversion rate is the ratio of diverting software developed in other projects. The ratio of the number of steps of the diverted software to the total number of steps (the number of steps of the developed software + the number of diverted software steps). The development staff skill indicates the technical level of the member to be developed, and the organizational support indicates whether support is obtained from outside the development department.
[0020]
The performance characteristic table 17 is a table in which characteristic items are digitized using a numerical value conversion table 20 described later based on the performance data table 16. An example of this data structure is shown in FIG. The performance characteristic table 17 includes fields of a PJ name, a person in charge name, a cost rate, a project characteristic item, and a productivity characteristic item. Furthermore, the project characteristic item includes the sub-fields of the project characteristic described above. In addition, the productivity characteristic item is obtained by adding a total subfield to the subfield of the productivity factor of the actual data.
[0021]
The estimated data table 18 is a table that stores estimated data to be evaluated. An example of the data structure is shown in FIG. The estimated data table 18 has only the working date and cost rate fields of the above-described actual data table 16, and the remaining fields are the same.
The estimated characteristic table 19 is a table obtained by digitizing characteristic items using the numerical value conversion table 20 described below, and the data structure example is shown in FIG. The estimated characteristic table 19 has only the cost rate field of the actual characteristic table 17 described above, and the remaining fields are the same.
[0022]
The numerical value conversion table 20 is a numerical value conversion table used when creating the actual characteristic table 17 from the actual data table 16 and the estimated characteristic table 19 from the estimated data table 18. FIG. 7 shows an example of the data structure of the numerical value conversion table 20, and is composed of fields of project characteristic items and productivity characteristic items. The data in the actual data table 16 and the estimated data table 18 is digitized according to the definition indicated by the contents of this table. For example, in the case of PJ type, if the developed (or developed) project is a core system, 1 is set, and if it is an information system, it is set to 0, and the number of files is the number of newly developed files and the number of remodeled files diverted to assets. The total number of files. The productivity characteristic item is an item corresponding to the eight productivity characteristic factors described above, and is quantified with the contents shown in the items of this table.
[0023]
In the evaluation of estimated data, the group evaluation characteristic value table 21 indicates whether the estimated data belongs to a group created based on the actual data, or whether the estimated data matches the characteristics of the group even if it belongs to the group. It is a table which shows the criteria to evaluate. An example of the data structure of this table is shown in FIG. 8, and comprises a group name, a group discrimination criterion, an intra-group evaluation criterion, and an alarm message field. The group discrimination criterion is composed of subfields of PJ type, number of files, and development efficiency, and it is determined which group belongs by examining these three items of estimated data. The intra-group evaluation criteria is composed of three subfields of asset diversion presence / absence, program language, and development staff skill, and is set with contents corresponding to the same items in the numerical conversion table 20. When the estimated data belongs to a certain group, this group evaluation criterion is used to evaluate whether it matches the group characteristics. The alarm field is a warning text to be displayed when it differs from the in-group evaluation criteria.
[0024]
The components in FIG. 2 have been described above. Next, the flow of processing by these components will be described with reference to FIG. First, result data is input and stored in the result data table 16. The result data is sequentially input after completion of development, and the result data is stored in the result data table 16. Subsequently, the record data is fetched from the record data table 16. At this time, old data and special data are not taken in, because the evaluation accuracy is lowered. For example, it may be determined based on the date of the performance data operation date, and data from six months before the evaluation point may be taken in. With reference to the numerical value conversion table 20 for the captured actual data, the project characteristic item and the productivity characteristic item are digitized for each actual data. The digitized data is sorted in the order of PJ type, number of files, and productivity, and stored in the performance characteristic table 17 (S1 to S3).
[0025]
Based on the sorted numerical data, the similarity of each project characteristic item is examined and each project is grouped. For example, first categorize by PJ type, and then three patterns of the three items of whether asset diversion, programming language, and development staff skill in each numerical range that was initially specified for the number of files and development efficiency (eight from 000 to 111) Count the number of occurrences of The maximum value of the number of appearances (maximum number of appearances) and the ratio of the maximum value to the group (maximum number of appearances / number of actual data in the group) are temporarily stored for each group. Next, an appropriate value is selected as a group by looking at the value of temporary storage performed several times while changing the numerical range specified first. For each group, the values of three items of asset diversion presence / absence, programming language, and development staff skill are determined and stored in the group evaluation characteristic value table 21. In addition, an alarm message is set for each item of asset diversion, programming language, and development staff skill. Here, the PJ type, the number of files, and the development efficiency values set in the group evaluation characteristic value table 21 are referred to as group discriminating criteria for evaluation of estimated data, which will be described later, and the asset diversion, language, and skill flags are within the group. This is referred to as an evaluation standard. The actual result data of the actual result table 17 and the determined group range are displayed, and the necessity of changing the group is inquired (S4 to S6).
[0026]
Next, estimate data to be evaluated is input and stored in the estimate data table 18. Subsequently, the estimated data is digitized as if it were actual data, and stored in the estimated characteristic table 19 (S7, S8).
It is examined which group the estimated data belongs by referring to the numerically estimated data (that is, the data of the estimated characteristic table 19) and the group discrimination standard value of the group evaluation characteristic value table 21. If the group discrimination criteria do not match, the estimated data is out of the distribution of past performance data, indicating that the development efficiency is abnormally high. Conversely, this indicates that the man-hour estimate is too low. For example, an evaluation result as shown in FIG. 10 is output to prompt the estimate creator to review the estimate. FIG. 10 shows the range of evaluation groups, the distribution of actual data, and the position of estimated data using the actual characteristic table 17 and the group evaluation characteristic value table 21 (S9, S14).
[0027]
If there is a piece of estimated data that matches the group discrimination standard, it belongs to any group, and then the patterns of the intra-group evaluation standard are compared. If the pattern of the evaluation criteria within the group does not match, it indicates that there is a problem with any of the software asset diversion, program language, programming language, or skill level of the development personnel, and is set in the group evaluation characteristic value table 21. An alarm message is output to point out the points for reviewing the estimate creation (S10, S15).
[0028]
If the patterns of the evaluation criteria within the group match, next, the total value of the productivity characteristic item values in the performance characteristic table 17 and the estimated characteristic table 19 is obtained, and the actual data closest to the total value of the estimated data is extracted. The extraction process is assumed to have the smallest difference between the total value of the estimated data and the actual data. For example, the total value of the productivity characteristic items in the actual data in FIG. 4 is closest to the total value “21.5” of the productivity characteristic items in the estimated data (project name is “x-pj”) in FIG. It is assumed that “21” is “b-pj”. When the difference between the total values of the productivity characteristic items of the estimated data and the actual data is the same and there are a plurality of projects, a project with high development efficiency is selected by comparing the development efficiency of the actual data. This is to guide the direction of improving the development efficiency of estimated data (S11, S12).
[0029]
Next, compare each productivity characteristic item of the estimated data and the extracted actual data, and if there is a value of the estimated data lower than the actual data value, to increase the value of the corresponding item to the same as the actual data, Display the evaluation results. For example, when comparing the productivity characteristic items of the project name “x-pj” in FIG. 6 and the project name “b-pj” in FIG. 4, “x-pj” indicates the customer participation rate, customer test data creation, and asset diversion. Three items have low values, and an evaluation result as shown in FIG. 11 is displayed. This display recommends to project planners that a certain productivity characteristic item is lower than performance data with similar estimated data from the viewpoint of productivity, and that the difference to that item is considered ( S15).
[0030]
Each processing unit of the data input unit 11 to the productivity evaluation unit 15 shown in FIG. 2 is a program and is executed on the main memory of the computer.
(Supplementary note 1) An estimate evaluation support program that supports estimate evaluation when planning a new project.
Preliminarily quantified multiple project characteristic items that focus on project characteristics and multiple productivity characteristic items that focus on productivity based on predetermined stage evaluation for the accumulated performance data of developed projects The actual data characteristic quantification procedure,
Group evaluation value creation procedure for grouping actual data with similar values of project characteristic items, quantifying project characteristic items for groups, and creating group evaluation characteristic values as total values of actual data,
Estimated data characteristic quantification procedure for quantifying the project characteristic item and the productivity characteristic item for the estimated data to be evaluated;
A group evaluation procedure for displaying an alarm when the value of the project characteristic item of the estimate data is different from the group evaluation characteristic value;
The actual data extraction procedure for obtaining the total of the productivity characteristic item values of the estimated data and the actual data, and extracting the actual data closest to the total of the productivity characteristic item values of the estimated data,
Compare the value of each productivity characteristic item between the extracted actual data and estimated data, and if there is a low item in the estimated data, the productivity evaluation display procedure that points out the corresponding productivity characteristic item
An estimate evaluation support program characterized by causing a computer to execute.
[0031]
(Appendix 2) The project characteristic items are the project type, the number of development files, the development efficiency, the presence / absence of software asset diversion, the type of program language, and the skill level of the development personnel.
The productivity characteristic items include customer participation level, technical difficulty level, software sharing level, development staff skill level, and presence / absence of organizational support.
The estimate evaluation support program according to supplementary note 1, characterized in that:
[0032]
(Appendix 3) An estimate evaluation support system that supports estimate evaluation when planning a new project.
Preliminarily quantified multiple project characteristic items that focus on project characteristics and multiple productivity characteristic items that focus on productivity based on predetermined stage evaluation for the accumulated performance data of developed projects Performance data characteristics quantification means,
Group evaluation value creating means for grouping actual data with similar values of project characteristic items, quantifying project characteristic items for the group, and creating group evaluation characteristic values as total values of actual data,
Estimated data characteristic quantification means for quantifying the project characteristic item and the productivity characteristic item with respect to the estimated data to be evaluated;
A group evaluation means for displaying an alarm when the value of the project characteristic item of the estimate data is different from the group evaluation characteristic value;
An actual data extraction means for obtaining a sum of values of the productivity characteristic items of the estimated data and the actual data, and extracting actual data closest to the total of the productivity characteristic items of the estimated data;
Compare the value of each productivity characteristic item in the extracted actual data and the estimated data, and if there is a low item in the estimated data, the productivity evaluation display means that points out the corresponding productivity characteristic item
An estimate evaluation support system characterized by comprising:
[0033]
(Appendix 4) An estimate evaluation support method for supporting estimate evaluation when planning a new project.
Preliminarily quantified multiple project characteristic items that focus on project characteristics and multiple productivity characteristic items that focus on productivity based on predetermined stage evaluation for the accumulated performance data of developed projects The actual data characteristic quantification procedure,
Group evaluation value creation procedure for grouping actual data with similar values of project characteristic items, quantifying project characteristic items for groups, and creating group evaluation characteristic values as total values of actual data,
Estimated data characteristic quantification procedure for quantifying the project characteristic item and the productivity characteristic item for the estimated data to be evaluated;
A group evaluation procedure for displaying an alarm when the value of the project characteristic item of the estimate data is different from the group evaluation characteristic value;
The actual data extraction procedure for obtaining the total of the productivity characteristic item values of the estimated data and the actual data, and extracting the actual data closest to the total of the productivity characteristic item values of the estimated data,
Compare the value of each productivity characteristic item between the extracted actual data and estimated data, and if there is a low item in the estimated data, the productivity evaluation display procedure that points out the corresponding productivity characteristic item
An estimate evaluation support method characterized by comprising:
[0034]
(Appendix 5) A recording medium that records an estimate evaluation support program that supports estimate evaluation at the time of planning a new project.
Preliminarily quantified multiple project characteristic items that focus on project characteristics and multiple productivity characteristic items that focus on productivity based on predetermined stage evaluation for the accumulated performance data of developed projects The actual data characteristic quantification procedure,
Group evaluation value creation procedure for grouping actual data with similar values of project characteristic items, quantifying project characteristic items for groups, and creating group evaluation characteristic values as total values of actual data,
Estimated data characteristic quantification procedure for quantifying the project characteristic item and the productivity characteristic item for the estimated data to be evaluated;
A group evaluation procedure for displaying an alarm when the value of the project characteristic item of the estimate data is different from the group evaluation characteristic value;
The actual data extraction procedure for obtaining the total of the productivity characteristic item values of the estimated data and the actual data, and extracting the actual data closest to the total of the productivity characteristic item values of the estimated data,
Compare the value of each productivity characteristic item between the extracted actual data and estimated data, and if there is a low item in the estimated data, the productivity evaluation display procedure that points out the corresponding productivity characteristic item
A computer-readable estimate evaluation support recording medium in which a program for executing is recorded.
[0035]
【The invention's effect】
As described above, according to the present invention, by comparing the project characteristic item value of the estimated data to be evaluated with the evaluation characteristic value of the group created based on the actual data, the estimate created by the project planner is obtained. It can be evaluated macroscopically, and a predetermined productivity characteristic item can be evaluated from the viewpoint of productivity by comparing with performance data. As a result, it is possible to estimate with high accuracy.
[Brief description of the drawings]
FIG. 1 is a principle diagram of the present invention.
FIG. 2 is a configuration example of the present invention.
FIG. 3 is a structural example of a result data table.
FIG. 4 is a structural example of a performance characteristic table.
FIG. 5 is a structural example of an estimate data table.
FIG. 6 is a structural example of an estimated characteristic table.
FIG. 7 is a structural example of a numerical value conversion table.
FIG. 8 is a structural example of a group evaluation characteristic value table.
FIG. 9 is a processing flow example.
FIG. 10 is a screen example of a group evaluation result.
FIG. 11 is a screen example of a productivity evaluation result.
FIG. 12 shows a conventional estimate evaluation support system.
[Explanation of symbols]
1: Performance data characteristic quantification procedure
2: Group evaluation value creation procedure
3: Estimated data characteristic quantification procedure
4: Group evaluation procedure
5: Results data extraction procedure
6: Productivity evaluation procedure
10: Estimated evaluation support system
11: Data input part
12: Characteristic item digitizing section
13: Group evaluation value creation section
14: Group Evaluation Department
15: Productivity evaluation department
16: Results data table
17: Performance characteristics table
18: Estimated data table
19: Estimated characteristic table
20: Numerical value conversion table
21: Group evaluation characteristic value table
30: Input device
40: Display device
101: Performance data characteristic quantification means
102: Evaluation standard setting means
103: Estimated data characteristic quantification means
104: Estimated data evaluation means

Claims (2)

An estimate evaluation support program that supports estimate evaluation when planning a new project,
On the computer,
For project performance data accumulated in the storage unit of the computer , the predetermined project type indicating the characteristics of the project, the number of development files, development efficiency, presence / absence of software asset diversion, and program language type are included. Refer to the numerical conversion table that stores the stage evaluation of the computer for the project characteristic items and the productivity characteristic items including the degree of customer participation, technical difficulty, software sharing, and whether or not there is organizational support that affects productivity . The actual data characteristics quantification procedure
A group that groups actual data with similar values of project characteristic items, quantifies project characteristic items for the group, creates group evaluation characteristic values as total values of actual data, and stores them in the group evaluation value characteristic table Evaluation value creation procedure,
Estimated data characteristic quantification procedure for referring to the numerical value conversion table for the project characteristic item and the productivity characteristic item with respect to the estimated data to be evaluated;
A group evaluation procedure for displaying an alarm on the display unit when the value of the project characteristic item of the estimated data is different from the value of the group evaluation value table ;
And digitizing the said quotation data prompted the sum of respective values of productivity Characteristics Characteristics of the actual data, and actual data extraction procedure for extracting the nearest actual data to the sum of the value of productivity Characteristics Characteristics of quotation data,
By comparing the values of each production characteristic items which are extracted actual data and estimated data, if there is a low entry in quotation data, productivity evaluation performing display to point out productivity characteristic items corresponding to the display unit Display procedure and
Estimate evaluation support program to execute . An estimate evaluation support system that supports estimate evaluation at the time of planning a new project,
For project performance data accumulated in the storage unit of the computer, the predetermined project type indicating the characteristics of the project, the number of development files, development efficiency, presence / absence of software asset diversion, and program language type are included. Refer to the numerical conversion table that stores the stage evaluation of the computer for the project characteristic items and the productivity characteristic items including the degree of customer participation, technical difficulty, software sharing, and whether or not there is organizational support that affects productivity. Actual data characteristic quantification means for performing quantification,
A group that groups actual data with similar values of project characteristic items, quantifies project characteristic items for the group, creates group evaluation characteristic values as total values of actual data, and stores them in the group evaluation value characteristic table Evaluation value creation means;
Estimated data characteristic quantification means for quantifying the project characteristic item and the productivity characteristic item with reference to the numerical value conversion table for the evaluation target evaluation data;
A group evaluation means for displaying an alarm on a display unit when the value of the project characteristic item of the estimated data is different from the value of the group evaluation value table;
A performance data extraction means for obtaining a sum of values of the productivity characteristic items of the estimated data and the performance data that have been digitized, and extracting performance data closest to the sum of the values of the productivity characteristics items of the estimated data;
Productivity evaluation by comparing the values of each productivity characteristic item in the extracted actual data and the estimated data, and when the estimated data has a low item, the display section indicates the corresponding productivity characteristic item Display means and
Estimating evaluation support system characterized by comprising

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