JP2008225635A - Estimated value integration support device, estimated value integration support method, and its program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an estimated value integration support device for supporting an integrator of estimated values to highly precisely integrate estimated values. <P>SOLUTION: In the estimated value integration support device, estimated values collected from a plurality of estimators are statistical analized, and each of the collected estimated values, statistical analytic result, the number of the past estimation experience of each estimator and the past estimating precision of each estimator are displayed. An estimated value integrator sets a parameter for correction for each of the estimated values by referring to display. The estimated value of each estimator is corrected by using the parameter for correction set by the estimated value integrator. Analysis is operated by a statistical analytic method to a corrected estimated value as an estimated value after correction. Each of the corrected estimated values and the analytic result of the corrected estimated value analytic method are displayed. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an estimated value aggregation support apparatus, an estimated value aggregation support method, a program thereof, and a storage medium.

  It is important to improve the accuracy of estimation of the scale and man-hours.

  The estimate is usually made while checking the specifications.

  Up to now, as a method for improving the accuracy of estimation, a method for counting the number of screens, the number of forms, the number of functions, etc. J. et al. Various estimation methods such as Albrecht's function point method (Non-Patent Document 1) or Boehm's COCOMO (Non-Patent Document 2) have been proposed and implemented.

  However, if the specifications themselves are ambiguous at the time of the estimation, the specifications can be interpreted in multiple ways, and even if the same estimation method is used, the interpretation of the estimation rules differs depending on the estimater, so the estimate value differs for each estimater. Is normal.

  In this case, in order to improve estimation accuracy, a plurality of estimation methods or a plurality of estimaters are used for estimation, and a method of aggregating the estimated results based on the plurality of results is used.

  The Delphi method is known as a method for aggregating a plurality of results.

  The Delphi method is a method developed by a research institution in the United States, Land Corporation, and gathers opinions by repeatedly carrying out the work of multiple experts each giving their own opinions, referring to each other, and giving opinions again. Is the method.

  The problem with this Delphi method is that the gathering of opinions depends on the subjective judgment of the estimator.

  Aggregation of opinions is realized by reviewing estimates based on the estimate values of other estimaters received by the estimater as feedback, and adjusting the estimate values to be aggregated.

  Therefore, subjective adjustment may be included, and it may not be an objective aggregation.

  Furthermore, in order to collect opinions, it is very time-consuming because it is necessary to repeat the work of estimating all of the experts, feeding back the estimation results of all of them to the estimater, and performing the estimation again and again.

  Therefore, in the present day when short delivery is required, the Delphi method is rarely implemented in practice, and when only one estimate is obtained by multiple quoters or when the estimate is not fully aggregated. In many cases, the person in charge of the project (for example, a project manager) has to determine a reasonable estimate, and in that case, there was no means to aggregate the estimate objectively.

  As a prior art made in view of such circumstances, for example, there is a technique of Patent Document 1. That is, in Patent Document 1, an estimater is made to estimate an applicable project based on estimation base information necessary for estimation, a plurality of estimated values are stored and held, and a plurality of estimated values are calculated using a statistical analysis technique. A technique for determining a final estimated value from the above is disclosed.

Further, Patent Document 2 calculates an absolute estimated value by performing statistical analysis on estimated values obtained from a plurality of estimators, and calculates the difference between the absolute estimated value and the estimated value by each estimator. There is disclosed a technique for detecting each “blur value” for each and notifying the quoter of this blur value, thereby prompting the quoter to improve the estimation method.
JP-A-11-203351 JP 2005-128703 A Albrecht, A.M. J. et al. & Gaffney, "Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Evidence Validation." SE-9, No6, Nov. 1983, 639-648 Toshiki Mano et al., “Estimation Methods-Practical Estimation Techniques in Software Development”, Nikka Giren, 1990, p. 63-87

  By the way, although the tendency of an estimated value changes for every estimater, the technique of patent document 1 cannot determine the final estimated value in consideration of such a tendency of the estimated value for each estimater.

  Further, since the technique of Patent Document 2 uses the “blur value” described above, an optimal final estimated value can be expected by considering the tendency of the estimated value for each estimator as compared with the technique of Patent Document 1. May. However, in the technique of Patent Document 2, since the estimation trend of the estimater can be obtained only by comparing the difference with the estimate value by another estimater at that time for each estimate, the estimate trend for each estimater can be grasped with high accuracy. As a result, the correction cannot be performed correctly, and as a result, a highly accurate estimated value cannot be obtained.

  The present invention has been made to solve the above-described problems, and an estimated value aggregation support apparatus and an estimated value aggregation support method for assisting an aggregator of estimated values so as to aggregate estimated values with higher accuracy than before. And to provide a program.

  In order to solve the above-described problem, the estimated value aggregation support apparatus of the present invention is input by a plurality of estimaters in the estimate value aggregation support apparatus that supports the aggregation work of estimated values estimated by a plurality of estimaters. A collecting means for collecting estimated values; an estimated value analyzing means for analyzing the estimated values collected by the collecting means by a statistical analysis technique; each of the estimated values collected by the collecting means; 1st display control which performs control which displays the analysis result by a value analysis means, the estimated experience number information which shows the past estimated experience number for every estimater, and the estimation accuracy information regarding the accuracy of the past estimate for every estimater And a correction parameter setting method that enables correction values for each of the estimated values collected by the collecting means to be set by an estimated value aggregator who performs an aggregation operation of these estimated values. And a correction unit that corrects the estimated value for each estimater using the correction parameter set by the estimated value aggregator, and a statistic for the corrected estimated value that is an estimated value corrected by the correcting unit. A corrected estimated value analyzing means for performing an analysis by a dynamic analysis method, a second display control means for performing control for displaying each of the corrected estimated values and an analysis result by the corrected estimated value analyzing means, It is characterized by providing.

  The estimated value aggregation support apparatus of the present invention collects estimated values respectively input by a plurality of estimaters in an estimated value aggregation support apparatus that supports the aggregation work of estimated values estimated by a plurality of estimaters. A first display control means for performing control to display each of the estimated values collected by the collecting means, and estimated experience number information indicating a past estimated experience number for each estimate person; and the collecting means Correction parameter setting means for enabling correction values for each of the estimated values collected by the estimate value aggregator to perform an aggregation operation of the estimated values, and a correction parameter set by the estimated value aggregator And a correction means for correcting the estimated value for each estimator, and a correction for performing an analysis by a statistical analysis method on the corrected estimated value which is an estimated value corrected by the correcting means And estimated value analysis means, and with each of the corrected estimated value, analysis results and by the corrected estimated value analysis means, and second display control means for performing control to display a, comprising: a.

  The estimated value aggregation support apparatus of the present invention collects estimated values respectively input by a plurality of estimaters in an estimated value aggregation support apparatus that supports the aggregation work of estimated values estimated by a plurality of estimaters. Collecting means, first display control means for performing control to display each estimated value collected by the collecting means, and estimation accuracy information regarding the accuracy of past estimates for each estimater, and collecting by the collecting means Correction parameter setting means for enabling correction parameters for each estimated value to be set by an estimate value aggregator who performs aggregation of these estimated values, and a correction parameter set by the estimate value aggregator Correction means for correcting the estimated value for each estimate person, and correction for performing an analysis by a statistical analysis method on the corrected estimated value which is an estimated value corrected by the correcting means And estimated value analysis means, and with each of the corrected estimated value, analysis results and by the corrected estimated value analysis means, and second display control means for performing control to display a, comprising: a.

  In the estimated value aggregation support apparatus of the present invention, the estimated value collecting support device further includes estimated value analyzing means for analyzing the estimated value collected by the collecting means by a statistical analysis method, and the first display control means includes the estimated value It is also preferable to perform control to display the analysis result by the analysis means.

  In the estimated value aggregation support apparatus of the present invention, an exclusion operation for excluding any of the estimated values collected by the collecting means from the object of correction by the correcting means and the analysis by the corrected estimated value analyzing means. It is preferable that the configuration is possible.

  In the estimated value aggregation support apparatus of the present invention, specification storage means for storing specification information related to the specification to be estimated, input means for receiving input of estimated values by each estimator, estimated values of estimates made in the past, An estimate / actual result database that stores and holds the actual value in the project subject to the estimate, and a similar search and extract from the estimate / actual database for past estimate values and actual values that are similar to the specification to be estimated Control is performed to display an estimate search / extraction means, a specification acquired from the specification storage means, and past estimate values and actual values extracted by the similar estimate search / extraction means at the time of estimation by each estimater. It is preferable that an estimate value display control unit is provided, and the estimated value input to the input unit is collected by the collection unit.

  In the estimated value aggregation support device of the present invention, the specification storage means for storing the specification information related to the specification to be estimated, the input means for receiving the input of the estimated value by each estimator, and the specification acquired from the specification storage means An estimater display control means for performing control to be displayed when an estimate is made by the estimater, and the estimater display control means further displays an input form corresponding to an estimate rule corresponding to each estimate object. Thus, it is preferable that the input from the input unit is supported, and the estimated value input to the input unit is collected by the collection unit.

  In the estimated value aggregation support device of the present invention, the specification storage means for storing the specification information related to the specification to be estimated, the input means for receiving the input of the estimated value by each estimator, and the specification acquired from the specification storage means Whether or not to finalize the estimated value of the analysis result obtained as a result of the analysis by the estimated value analysis means after the estimation and the display control means for the estimater that performs control to be displayed when the estimate is made by the estimater Final estimate value selection control means for controlling the estimate value aggregator to select the estimate value input to the input means is collected by the collection means, and the analysis result estimate value is obtained. When selection is made not to make the final estimated value, the display control means for the estimater controls to display the estimated value of the analysis result, and causes each estimater to make an estimate again. Door is preferable.

  The estimate value aggregation support method of the present invention collects estimate values respectively input by a plurality of estimaters in the estimate value aggregation support method for supporting the aggregation work of estimate values estimated by a plurality of estimaters. A first step, a second step of analyzing the estimated values collected in the first step by a statistical analysis technique, each of the estimated values collected in the first step, Control for displaying the analysis result in the process of 2, the estimated experience number information indicating the past estimated experience number for each estimater, and the estimated accuracy information regarding the accuracy of the past estimate for each estimater. A third process performed after the process, and a control for setting a correction parameter for each of the estimated values collected in the first process by an estimated value aggregator who performs an aggregation operation of these estimated values. And the estimate The fifth process of correcting the estimated value for each estimator using the correction parameter set by the aggregator, and the corrected estimated value that is the estimated value corrected by the fifth process are statistical A computer performs a sixth step of performing analysis by an analysis method, a seventh step of performing control for displaying each of the estimated values after correction, and an analysis result of the sixth step. It is said.

  The estimate value aggregation support method of the present invention collects estimate values respectively input by a plurality of estimaters in the estimate value aggregation support method for supporting the aggregation work of estimate values estimated by a plurality of estimaters. A second step of performing control to display a first step, each of the estimated values collected in the first step, and estimated number-of-experience information indicating a past estimated number of experience for each estimator; A third step in which control for setting correction parameters for each of the estimated values collected in the first step is performed by the estimated value aggregator who performs the aggregation operation of these estimated values after the second step. And a fourth process of correcting the estimated value for each estimator using the correction parameter set by the estimated value aggregator, and an estimated value after correction that is an estimated value corrected by the fourth process For statistical analysis The computer performs a fifth step of performing analysis, a sixth step of performing control to display each of the estimated values after correction, and the analysis result of the fifth step. .

  The estimate value aggregation support method of the present invention collects estimate values respectively input by a plurality of estimaters in the estimate value aggregation support method for supporting the aggregation work of estimate values estimated by a plurality of estimaters. A control for displaying a first process, and a control for displaying each of the estimated values collected in the first process and the estimation accuracy information regarding the accuracy of the past estimation for each estimater. And the control for setting the correction parameters for each of the estimated values collected in the first process by the estimated value aggregator who performs the aggregation work of these estimated values is performed after the second process. The third process, the fourth process for correcting the estimated value for each estimator using the correction parameter set by the estimated value aggregator, and the estimated value after the correction in the fourth process For the estimated value after correction The computer performs a fifth step of performing analysis by a statistical analysis method, and a sixth step of performing control to display each of the corrected estimated values and the analysis result of the fifth step. It is characterized by that.

  Further, the program of the present invention is characterized in that, in a computer-executable program, the computer executes the estimated value aggregation support method of the present invention.

  The storage medium of the present invention stores the program of the present invention.

  According to the present invention, the estimated experience number information indicating the estimated experience number such as the estimated number of projects estimated by the estimator in the past and the number of estimated functions (estimated function number), and the estimated accuracy regarding the accuracy of the estimation performed in the past Since the information is displayed, the estimate value aggregator can accurately recognize the past estimation tendency (for example, the accuracy is high, the estimation is larger or smaller than the actual value) for each estimater. Then, referring to such information, the estimate value aggregator can set the correction parameter, so that a plurality of estimate values can be aggregated into objectively valid values.

  Embodiments according to the present invention will be described below with reference to the drawings.

[First Embodiment]
FIG. 1 is a block diagram showing a configuration of an estimated value aggregation support apparatus 100 according to the first embodiment.

  As shown in FIG. 1, an estimated value aggregation support apparatus 100 according to the present embodiment is for supporting an aggregation operation of estimated values such as scale and man-hour, for example. A data processing device 2, a storage device 3 for storing information, and an output device (display device) 4 for performing display output.

  The data processing device 2 includes, for example, a CPU (computer), a ROM (storage medium) that stores an operation program (program) for the CPU, and a RAM that functions as a work area of the CPU. 1 functions as the specification registration means 21, the specification display means 22, the estimated / actual data search display means 23, the estimated value registration means 24, the analysis means 25, and the like shown in FIG. .

  The storage device 3 includes a specification storage unit 31, an estimate / result data storage unit 32, an estimated value storage unit 33, and an analysis unit storage unit 34.

  The specification registering unit 21 receives specifications necessary for estimation input from the input device 1 as data and stores them in the specification storage unit 31.

  The specification display unit 22 performs control to read data of specifications necessary for estimation from the specification storage unit 31 and display the data on the output device 4. By this control, it is possible for the estimater to view the data of the specification necessary for the estimate.

  The estimate / actual data search and display means 23 searches the estimate / actual data storage unit 32 for past estimate / actual data (described later) similar to the specification to be estimated based on the search condition input from the input device 1. Then, the search result and the corresponding estimate / actual data are displayed to the estimater.

  The estimated value registration unit 24 stores the estimated information (estimated value, estimated name, preconditions, restrictions, etc.) from the estimated person input from the input device 1 in the estimated value storage unit 33. That is, a plurality of estimated values are collected.

  The analysis unit 25 analyzes a plurality of estimated values obtained from the estimated value storage unit 33. At this time, the analysis method selected via the input device 1 from the analysis methods stored in the analysis method storage unit 34, or the past estimate / result for each estimate person read from the estimate / result data storage unit 32 Analyze estimated values and adjust estimated values based on data to determine final estimated values.

  The analysis result by the analyzing means 25 and the final estimated value are output from the output device 4. Further, these values can be stored in the estimate / result data storage unit 32.

  The specification storage unit 31 can store information regarding the specification to be estimated.

  The estimated / actual data storage unit 32 can store estimated values and actual data regarding past projects.

  The estimated value storage unit 33 can store estimated information (estimated value, estimater name, preconditions, restrictions, etc.) performed on the specification to be estimated.

  The analysis technique storage unit 34 can store analysis rules using statistical analysis techniques such as arithmetic mean, median, variance, and standard deviation.

  Next, the operation will be described.

  FIG. 2 is a flowchart showing the flow of operation of the first embodiment.

  First, data related to the specification to be estimated, which is input to the estimated value aggregation support device 100 by an input operation on the input device 1, is supplied to the specification registration unit 21. The specification registration unit 21 stores the data in the specification storage unit 31 (step A1 in FIG. 2).

  Next, the estimater performs an operation of causing the output device 4 to output the data related to the specification registered in the specification storage unit 31 in the previous step A1 under the control of the specification display means 22, and browses the data ( Step A2) in FIG.

  Next, the estimater searches the estimate / actual data search / display means 23 from the estimate / actual data storage unit 32 for past estimate / actual data similar to the specification to be estimated, for reference. The display operation is performed and the data is browsed (step A3 in FIG. 2).

  Next, the estimater inputs (registers) estimate information from the input device 1. The input estimate information is stored in the estimate value storage unit 33 by the estimate value registration means 24 (step A4 in FIG. 2).

  Next, it is confirmed whether all the estimate persons have registered the estimate information (step A5 in FIG. 2). If the registration has not been completed (No in step A5), the process returns to step A4 to complete the registration. The estimate person who has not done so registers the estimate information. When the registration of all the members is completed (Yes in step A5), the process proceeds to step A6.

  In step A6, the final decision maker (estimated value aggregator) of the estimated value analyzes a plurality of estimated results read from the estimated value storage unit 33 in the analyzing means 25.

  FIG. 3 is a diagram showing an image of a screen displayed on the output device 4 at the time of analysis (step A6).

  FIG. 3 shows an example in which there are five estimaters (estimator 1, estimater 2,... Estimater 5), for example.

  As shown in FIG. 3, the output device 4 includes a column for an estimater input value, a column for a final determiner reference value, a column for a final determiner adjustment value, a column for statistical data before adjustment, a column for adjusted statistical data, And the column of the final estimated value is displayed.

  Among them, the estimate information input by each estimater is displayed in the column of the estimater input value. The estimate information has, for example, an estimater name, affiliation, estimate target number, preconditions, and restrictions as attributes.

  Further, in the column of the final decision person reference value, the estimated experience number (estimated experience number information) and risk (estimated accuracy information) for each estimater are displayed.

  The “arithmetic mean value”, “median value”, “mode value”, “standard deviation”, etc. displayed as items in the pre-adjustment statistical data column are statistical analyzes read from the analysis means storage unit 34. This method is selected from the input device 1 by the final decision maker. In addition, the result of analysis by the selected analysis method (numerical data displayed in the column below each item) is also displayed in the pre-adjustment statistical data column. Note that the pre-adjustment statistical data is a result of performing an analysis by a selected analysis method on an estimated value before adjustment (correction) described later.

  At this stage, the final determiner adjustment value column, the adjusted statistical data column, and the final estimated value column are left blank as shown in FIG. 3, for example.

  Here, for example, when the screen is realized by a Web browser, when each underlined display value is clicked, the detailed information is retrieved from the specification storage unit 31, the estimated / actual data storage unit 32, and the estimated value storage unit 33. And it may be extracted and displayed.

  At the time when the screen of FIG. 3 is displayed, the final determinant confirms the value of the standard deviation of the statistical data before adjustment, for example, and if the value is larger than a certain reference value, the variation in the estimated value is too large. It can be objectively determined that there is a problem with the specification itself (the specification may be too vague).

  In addition, the “estimated experience number” of the item in the final decision person reference value column is the estimated project number or estimate function estimated in the past from the estimate / actual data storage unit 32 based on the estimater information. The number (number of estimated functions) is extracted and used by the final decision maker to confirm the experience of each estimator.

  In addition, for the item “risk” in the final decision reference field, the estimate information in the estimate project estimated by the estimater in the past is extracted from the estimate / result data storage unit 32 based on the estimater information. The accuracy of the estimate (difference between the estimated value and the actual value) is automatically calculated from the extracted estimated information and displayed. Therefore, the “risk” is used by the final decision maker to confirm the accuracy of estimation or the tendency of the estimation (for example, the accuracy is high, the estimation is larger or smaller than the actual value).

  For example, in the case of the estimate person 1, the “risk” column is “−30% to + 200%”. This indicates that, in the past estimation by the estimater 1, for example, when the estimated value is “100”, the actual value that is known as a result of the project being in the range of “70 to 200”. Therefore, it can be said that the estimater 1 has a tendency to estimate the estimated value slightly in the past.

  The final decision maker performs analysis with reference to the columns of “estimator input value”, “final decision maker reference value”, and “statistical data before adjustment”. That is, for example, by adjusting the estimated value weighting value (correction parameter) for each estimator, adjusting the estimated value, or excluding an estimated value that is significantly different from others as an abnormal value from the comparison target Can do.

  FIG. 4 is a diagram illustrating an example of a screen after the final determiner sets a weight value of the estimated value for each estimater.

  As shown in FIG. 4, after the final decision maker sets the weight value of the estimated value for each estimator, numerical data is displayed in the final decision maker adjustment value column, and also in the adjusted statistical data column. Numerical data is displayed, and the value displayed in the column of the selected analysis method (for example, arithmetic mean value) in the adjusted statistical data is also displayed in the column of the final estimated value.

  Here, the adjusted statistical data is a result of performing an analysis by the selected analysis method on the estimated value after the adjustment (correction).

  As shown in FIG. 4, for example, in the case of the estimator 1, 3 is given as the weight because the estimated number of experiences is small and there is a tendency to estimate slightly with reference to past estimation results. The corrected estimated value is given as “weighting” × “estimated value” = “corrected estimated value”.

  If there is an estimated value that is too far from other estimaters, the effective flag (see FIG. 4) corresponding to the estimated value can be set to 0 to be excluded from the analysis target. In the example of FIG. 4, the estimated values of all the estimators 1 to 5 are valid (valid flag is 1).

  4. After the display of FIG. 4 is made, the final decision maker further includes “estimator input value”, “final decision maker reference value”, “final decision maker adjustment value”, “statistic data before adjustment”, “after adjustment”. The final statistical value is determined by confirming the columns of “statistical data” and “final estimated value” respectively, and appropriately modifying and changing the weighting value and the valid flag. The estimation result including the final estimated value (final value of each item as displayed in FIG. 4) can be stored in the estimated / actual data storage unit 32 (step A7 in FIG. 2).

  According to the first embodiment as described above, the following effects can be obtained.

  The first effect is that the estimation results can be aggregated objectively.

  The reason is that data of a plurality of estimators can be aggregated and statistical analysis can be performed.

  The second effect is that the accuracy of estimation can be increased.

  The reason is that the accuracy can be improved by using the estimation experience of the estimater in the past and performing an appropriate correction on the estimated value.

[Second Embodiment]
Next, a second embodiment will be described.

  FIG. 5 is a block diagram showing a configuration of an estimated value aggregation support apparatus 200 according to the second embodiment.

  As shown in FIG. 5, the estimated value aggregation support apparatus 200 according to the present embodiment is the estimated value aggregation support apparatus according to the first embodiment described above in that the storage device 3 includes an estimated rule storage unit 35. 100 (FIG. 1). Other components are the same as those of the estimated value aggregation support apparatus 100, and are denoted by the same reference numerals.

  In the present embodiment, since the storage device 3 includes the estimation rule storage unit 35, when the estimater makes an estimate, an input form according to the estimation rules such as the function point method, the number of screens, the number of forms, and the number of functions is displayed. The estimated value can be calculated according to the estimation rule by using the value provided from the input form on the estimated value registration means 24 by presenting to the estimate person from the output device 4.

  As described above, the estimate value aggregation support apparatus 200 provides and supports the estimate environment, so that each estimate person not only inputs the estimate result to the estimate value aggregation support apparatus 200 but also the estimate work itself. 200 can be performed.

  FIG. 6 is a flowchart showing an operation flow of the second embodiment.

  The operation shown in FIG. 6 differs from FIG. 2 (first embodiment) in that steps A8 and A9 are added, and is otherwise the same as FIG.

  That is, in step A8, the data processing device 2 determines whether or not an operation for determining the estimated value displayed in the final estimated value column as the final estimated value has been performed by the final decision maker. If it is determined (if determined) (Yes in step A8), the estimated value is determined (step A9).

  On the other hand, when it is determined that the final decision value is not determined by the final decision maker to determine the estimated value displayed in the final estimated value column (No in step A8), the process returns to step A3 again. Return and ask each quoter to make another quote.

  Through these steps A8 and A9, the estimated values determined by analyzing the collected estimated values can be fed back to the respective estimators and re-estimated. By performing the re-estimation in this way, it is possible to further improve the estimation accuracy.

  According to the second embodiment as described above, each estimator can not only input the estimated result to the estimated value aggregation support apparatus 200 but also perform the estimation work itself on the estimated value aggregation support apparatus 200. .

  Further, the estimated value determined by analyzing the collected estimated value can be fed back to each estimator again and re-estimated, so that the estimation accuracy can be further improved.

  In each of the above embodiments, an example in which there is one input device 1 and one output device 4 has been described. However, the input device 1 and the output device 4 are prepared for each estimater, and the input of each estimater. The device 1 and the output device 4 may be connected to the data processing device 2 via a network.

  In the above, at the start of analysis, as shown in FIG. 3, the final decision-maker adjustment value column, the adjusted statistical data column, and the final estimated value column are left blank. As described above, at the start of the analysis, for example, in the final decision-maker adjustment value column, the weight for each estimater's estimate is “1” and the valid flag is “1”, respectively. The value column is the same value as the estimated value column in the quoter input value column, the adjusted statistical data column is the same value as the pre-adjusted statistical data column, and the adjusted statistical data The value displayed in the column of the selected analysis method may be displayed in the column of the final estimated value.

  In each of the above embodiments, an example has been described in which both the “estimated experience number (estimated experience number information)” and “risk (estimated accuracy information)” are displayed on the screen during analysis by the final decision maker. However, only one of “estimated number of experiences” and “risk” may be displayed on the screen.

It is a block diagram which shows the structure of the estimated value aggregation assistance apparatus which concerns on 1st Embodiment. It is a flowchart which shows the flow of operation | movement of 1st Embodiment. It is a figure which shows the screen image at the time of analysis implementation (before correction | amendment). It is a figure which shows the screen image at the time of analysis implementation (after correction | amendment). It is a block diagram which shows the structure of the estimated value aggregation assistance apparatus which concerns on 2nd Embodiment. It is a flowchart which shows the flow of operation | movement of 2nd Embodiment.

Explanation of symbols

1 Input device (input means)
2 Data processing device (functions as first display control means, correction parameter setting means, second display control means, estimate display control means, final estimated value selection control means)
23 Estimate / actual data search and display means (functions as similar estimate search / extraction means)
24 Estimated value registration means (functions as collection means)
25 Analysis means (functions as estimated value analysis means, correction means, and corrected estimated value analysis means)
31 Specification storage unit (specification storage means)
32 Estimated / actual data storage (estimated / actual database)
33 Estimated value storage unit (functions as collection means)
100 Estimated Value Aggregation Support Device 200 Estimated Value Aggregation Support Device

Claims (13)

In the estimate value aggregation support device that supports the aggregation work of estimate values estimated by multiple estimaters,
A collection means for collecting estimated values respectively input by a plurality of estimaters;
An estimated value analyzing means for performing an analysis by a statistical analysis method on the estimated value collected by the collecting means;
Each of the estimated values collected by the collecting means, the analysis result by the estimated value analyzing means, estimated experience number information indicating the past estimated experience number for each estimater, and the accuracy of the past estimate for each estimater First display control means for performing control to display estimated accuracy information;
Correction parameter setting means for enabling correction parameters for each of the estimated values collected by the collecting means to be set by an estimate value aggregator who performs an aggregation operation of these estimated values;
Correction means for correcting the estimated value for each estimater using the correction parameter set by the estimate value aggregator,
A corrected estimated value analyzing means for performing an analysis by a statistical analysis method on the corrected estimated value which is an estimated value corrected by the correcting means;
Second display control means for performing control to display each of the corrected estimated values and the analysis result by the corrected estimated value analyzing means;
An estimated value aggregation support apparatus comprising: In the estimate value aggregation support device that supports the aggregation work of estimate values estimated by multiple estimaters,
A collection means for collecting estimated values respectively input by a plurality of estimaters;
First display control means for performing control to display each estimated value collected by the collecting means and estimated experience number information indicating a past estimated experience number for each estimate person;
Correction parameter setting means for enabling correction parameters for each of the estimated values collected by the collecting means to be set by an estimate value aggregator who performs an aggregation operation of these estimated values;
Correction means for correcting the estimated value for each estimater using the correction parameter set by the estimate value aggregator,
A corrected estimated value analyzing means for performing an analysis by a statistical analysis method on the corrected estimated value which is an estimated value corrected by the correcting means;
Second display control means for performing control to display each of the corrected estimated values and the analysis result by the corrected estimated value analyzing means;
An estimated value aggregation support apparatus comprising: In the estimate value aggregation support device that supports the aggregation work of estimate values estimated by multiple estimaters,
A collection means for collecting estimated values respectively input by a plurality of estimaters;
First display control means for performing control to display each of the estimated values collected by the collecting means and estimated accuracy information relating to the accuracy of past estimates for each estimater;
Correction parameter setting means for enabling correction parameters for each of the estimated values collected by the collecting means to be set by an estimate value aggregator who performs an aggregation operation of these estimated values;
Correction means for correcting the estimated value for each estimater using the correction parameter set by the estimate value aggregator,
A corrected estimated value analyzing means for performing an analysis by a statistical analysis method on the corrected estimated value which is an estimated value corrected by the correcting means;
Second display control means for performing control to display each of the corrected estimated values and the analysis result by the corrected estimated value analyzing means;
An estimated value aggregation support apparatus comprising: Estimate value analysis means for performing analysis by a statistical analysis method on the estimate value collected by the collection means,
The estimated value aggregation support apparatus according to claim 2, wherein the first display control unit also performs control to display an analysis result by the estimated value analysis unit.   The present invention is characterized in that an excluding operation for excluding any of the estimated values collected by the collecting means from being corrected by the correcting means and being analyzed by the corrected estimated value analyzing means is configured. The estimated value aggregation support apparatus according to any one of claims 1 to 4. Specification storage means for storing specification information related to the specification to be estimated;
An input means for accepting an input of an estimated value by each estimator;
An estimate / actual database that stores the estimated value of the estimate made in the past and the actual value of the project subject to the estimate;
Similar estimate search / extraction means for searching and extracting past estimate values and actual values similar to the specification to be estimated from the estimate / result database;
Estimator display control means for performing control to display the specifications acquired from the specification storage means, the past estimated value and the actual value extracted by the similar estimate search / extracting means at the time of estimation by each estimater; ,
With
6. The estimated value aggregation support apparatus according to claim 1, wherein the estimated value input to the input unit is collected by the collecting unit. Specification storage means for storing specification information related to the specification to be estimated;
An input means for accepting an input of an estimated value by each estimator;
Display control means for an estimater that performs control to display the specifications acquired from the specification storage means when estimating by each estimater;
With
The estimater display control means further supports input from the input means by displaying an input form corresponding to an estimate rule corresponding to each estimate object,
7. The estimated value aggregation support apparatus according to claim 1, wherein the estimated value input to the input unit is collected by the collecting unit. Specification storage means for storing specification information related to the specification to be estimated;
An input means for accepting an input of an estimated value by each estimator;
Display control means for an estimater that performs control to display the specifications acquired from the specification storage means when estimating by each estimater;
Final estimated value selection control means for performing control to allow the estimated value aggregator to select whether or not the analysis result estimated value obtained as a result of analysis by the corrected estimated value analyzing means is to be determined as a final estimated value. When,
With
The estimated value input to the input means is collected by the collecting means,
When it is selected that the analysis result estimated value is not the final estimated value, the display control means for the estimater performs control to display the analysis result estimated value, The estimate value aggregation support apparatus according to claim 1, wherein an estimate is performed. In the estimate value aggregation support method that supports the aggregation work of estimate values estimated by multiple estimaters,
A first process of collecting estimate values respectively input by a plurality of estimaters;
A second step of analyzing the estimated values collected in the first step by a statistical analysis method;
Each of the estimated values collected in the first process, the analysis result in the second process, estimated experience number information indicating the estimated number of past experiences for each estimater, and past estimates for each estimater A third step of performing control for displaying estimated accuracy information on accuracy after the second step;
A fourth step of performing control to set a correction parameter for each of the estimated values collected in the first step by an estimated value aggregator who performs an aggregation operation of these estimated values;
A fifth step of correcting the estimated value for each estimator using the correction parameter set by the estimated value aggregator;
A sixth step of performing an analysis by a statistical analysis method on the corrected estimated value which is the estimated value after the correction in the fifth step;
A seventh step of performing control to display each of the estimated values after correction and the analysis result of the sixth step;
Estimated value aggregation support method, characterized in that computer performs. In the estimate value aggregation support method that supports the aggregation work of estimate values estimated by multiple estimaters,
A first process of collecting estimate values respectively input by a plurality of estimaters;
A second step of performing control to display each of the estimated values collected in the first step and estimated number-of-experience information indicating a past estimated number of experience for each estimator;
A third step in which control for setting correction parameters for each of the estimated values collected in the first step is performed by the estimated value aggregator who performs the aggregation operation of these estimated values after the second step. When,
A fourth step of correcting the estimated value for each estimator using the correction parameter set by the estimated value aggregator;
A fifth step of analyzing the corrected estimated value, which is an estimated value after the correction in the fourth step, by a statistical analysis method;
A sixth step of performing control to display each of the corrected estimated values and the analysis result of the fifth step;
Estimated value aggregation support method, characterized in that computer performs. In the estimate value aggregation support method that supports the aggregation work of estimate values estimated by multiple estimaters,
A first process of collecting estimate values respectively input by a plurality of estimaters;
A second step of performing a control to display each of the estimated values collected in the first step and a control to display the estimation accuracy information regarding the accuracy of the past estimation for each estimator;
A third step in which control for setting correction parameters for each of the estimated values collected in the first step is performed by the estimated value aggregator who performs the aggregation operation of these estimated values after the second step. When,
A fourth step of correcting the estimated value for each estimator using the correction parameter set by the estimated value aggregator;
A fifth step of analyzing the corrected estimated value, which is an estimated value after the correction in the fourth step, by a statistical analysis method;
A sixth step of performing control to display each of the corrected estimated values and the analysis result of the fifth step;
Estimated value aggregation support method, characterized in that computer performs.   A computer-executable program for causing a computer to execute the estimated value aggregation support method according to any one of claims 9 to 11.   A storage medium storing the program according to claim 12.

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