Patent Application
20110301999
The present invention relates to a technique of supporting a project on the basis of estimates of earnings parameters such as costs of development and manufacturing, sales volume, profit and loss and the like concerning earnings from deliverables of the project.
At a starting-up or initial stage of a project that involves a sequence of development and selling of a product, a manufacturer usually estimates costs of development and manufacturing of the product, volume of sales of the product, and the like in order to decide the advisability of execution of the project or determine a budget for execution of the project. Thus, more accurate estimates of costs and the like are desirable when such estimates are required for making a decision to permit or reject execution of a project.
As an example of a conventional technique of estimating costs and the like concerning deliverables of a project, the following Patent Document 1 discloses a technique in which various kinds of productivity indexes are calculated on the basis of results data of past projects, and costs and the like are estimated accurately by using those various kinds of productivity indexes.
As described above, it is required to estimate costs and the like concerning earnings from deliverables of a project as accurately as possible in order to make a decision to permit or reject execution of the project or determine a budget for execution of the project, for example. However, it is usual that many estimation risk events such as unknown matters, indefinite matters and the like exist at an estimation stage. Thus, it is very difficult to estimate costs and the like accurately. And, estimates according to the technique described in Patent Document 1 are insufficient by themselves as data for deciding the advisability of a project or for determining a budget for a project.
Noticing these problems, an object of the present invention is to provide a technique of supporting a project by providing data that are effective for such purposes as deciding the advisability of a project and determining a budget for a project.
According to the present invention, a computer executes the following steps (1)-(6) to solve the above problems.
(1) A past data receiving step, in which an input means of the computer receives an estimate and an actual value of the earnings parameter concerning the earnings from the deliverables of each of a plurality of past project, and a risk event parameter group i.e. a set of risk event parameters indicating respectively degrees of estimation risks of a plurality of estimation risk events of the past project in question;
(2) A target data receiving step, in which the input means receives the estimate of the earnings parameter concerning the target project, and a risk event parameter group i.e. a set of risk event parameters indicating respectively degrees of estimation risks of the plurality of estimation risk events concerning the target project;
(3) A similarity calculation step, in which, for each of the plurality of past projects, a degree of similarity between the risk event parameter group of the past project in question and the risk object parameter group of the target project is obtained;
(4) An extraction step, in which top one or more past projects having highest degrees of similarities with the target project among the plurality of past projects are extracted according to previously-determined rule;
(5) A fluctuation information generation step, in which earnings fluctuation information concerning fluctuation of the earnings parameter with reference to the estimate of the target project is generated on a basis of the estimate and actual value of the earnings parameter of each of the one or more past projects extracted in the extraction step; and
(6) An information output step, in which an output means of the computer outputs the earnings fluctuation information.
Further, according to the present invention, it is favorable that the computer executes the following steps (7)-(13).
(7) A posterior-to-countermeasure parameter setting step, in which risk event parameters in the risk event parameter group of the target project are changed in such a direction that degrees of risks become smaller on the assumption of execution of risk countermeasures, to obtain a plurality of posterior-to-countermeasure risk event parameter groups;
(8) A posterior-to-countermeasure similarity calculation step, in which, for each of the plurality of past projects, a degree of similarity between a risk event parameter group of the past project in question and one of the posterior-to-countermeasure risk event parameter groups of the target project is obtained;
(9) A posterior-to-countermeasure extraction step, in which top one or more past projects having highest degrees of similarities with the one of the posterior-to-countermeasure risk parameter groups of the target project are extracted according to a previously-determined rule, among the plurality of past projects;
(10) A provisional fluctuation information generation step, in which provisional earnings fluctuation information concerning fluctuation of the earnings parameter with reference to the estimate of the target project is generated on a basis of the estimate and actual value of the earnings parameter of each of the one or more past projects extracted in the posterior-to-countermeasure extraction step;
(11) A processing control step, in which the posterior-to-countermeasure similarity calculation step, the posterior-to-countermeasure extraction step, and the provisional fluctuation information generation step are executed with respect to all the posterior-to-countermeasure risk event parameter groups obtained in the posterior-to-countermeasure parameter setting step;
(12) A posterior-to-countermeasure fluctuation information generation step, in which statistical processing of the provisional earnings fluctuation information is performed for each of all the posterior-to-countermeasure risk event parameter groups obtained in the posterior-to-countermeasure parameter setting step, to generate posterior-to-countermeasure earnings fluctuation information concerning fluctuation of the earnings parameter with reference to the estimate of the target project; and
(13) A posterior-to-countermeasure information output step, in which the output means is made to output the posterior-to-countermeasure earnings fluctuation information.
The present invention indicates earnings fluctuation information with reference to an estimate of an earnings parameter concerning a target project, and thus it is possible to support judgment on the advisability of execution of the target project, determination of a budget for the target project, or the like.
Now, an embodiment of a project support apparatus according to the present invention will be described referring to the drawings.
The project support apparatus of the present embodiment is an apparatus for outputting earnings fluctuation information that is a kind of earnings parameter and shows fluctuation of a development-manufacturing cost with reference to an estimate of the development-manufacturing cost. As shown in
The external storage 160 stores: a risk event content table 161 for storing contents and IDs of a plurality of estimation risk events such as matters that are unknown or indefinite at the estimation stage; an earnings data table 162 for storing various earnings data on a project as the target of support; a risk event parameter table 163 for storing risk event parameters that indicate degrees of risks of a plurality of estimation risk events respectively concerning the target project (hereinafter, a set of risk event parameters is referred to as a risk event parameter group); an earnings data table 164 for storing various earnings data on a plurality of past projects; a risk event parameter table 165 for storing risk event parameter groups for each of the plurality of past projects; and a countermeasure-requiring event table 165 for storing IDs and the like of risk event parameters that are different from the corresponding risk event parameters in a posterior-to-risk-countermeasure risk event parameter group used for generating the above-mentioned earnings fluctuation information, among the risk event parameters of the risk event parameter group before taking the countermeasures against the risks. Among these tables 161-166, the tables 162-166 except for the risk event content table 161 store data, in the course of processing that will be described referring to the flowcharts of
The external storage 160 further stores a project support program 169 to be executed by the CPU 110. The project support program 169 may be obtained by reproduction from a disk D storing the program 169 through the disk storage-reproduction unit 170, or may be obtained through the communication unit not shown in the figure.
Here, all the tables 161-166 are stored in the external storage 160. However, these tables may be stored in another storage unit. In particular, the earnings data table 162 on a target project, the risk event table 163 on the target project and the countermeasure-requiring risk event table 166 may be stored in the RAM 150.
In the RAM 150, there will be placed: a prior-to-countermeasure project similarity table 152 for storing the degrees of similarities between a risk event parameter group at a stage before taking countermeasures against the estimation risks of the target project and estimation risk event parameter groups of the plurality of past projects; and a posterior-to-countermeasure project similarity table 153 for storing the degrees of similarities between a risk event parameter group that is assumed taking countermeasures against the estimation risk events of the target project and the risk event parameter groups of the plurality of past projects. These tables 152 and 153 are prepared in the RAM 150 in the course of processing that will be described referring to the flowcharts of
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Description will be given referring to
The CPU 110 of the project support apparatus 100 functionally comprises: a receiving part 111 for receiving various data through the input unit 182 and the communication unit; an output part 112 for displaying various data on the display unit 181; a prior-to-countermeasure processing part 120 for generating the earnings fluctuation information prior to taking countermeasures against estimation risks; and a posterior-to-countermeasure processing part 130 for generating the earnings fluctuation information after taking countermeasures against estimation risks.
The prior-to-countermeasure processing part 120 comprises: a similarity calculation part 122 for obtaining the degrees of similarities between the prior-to-countermeasure risk event parameter group and the risk event parameter groups of the plurality of past projects; a project extraction part 123 for extracting IDs of the past projects of the top N highest degrees of similarity; a cost deviation calculation part 124 for obtaining cost deviations with reference to the estimate of the target project, based on the cost estimates and the actual costs of the N past projects; a prior-to-countermeasure fluctuation information generation part 127 for generating prior-to-countermeasure earnings fluctuation information by using these cost deviations; and a processing control part 126 for controlling these functional parts.
Further, the posterior-to-countermeasure processing part 130 comprises: a posterior-to-countermeasure parameter setting part 131 for setting a plurality of posterior-to-countermeasure risk event parameter groups by changing the parameters in the prior-to-countermeasure risk event parameter group; a similarity calculation part 132 for obtaining similarities between one posterior-to-countermeasure risk event parameter group out of the plurality of posterior-to-countermeasure risk event parameter groups and risk event parameter groups of the plurality of past projects; a project extraction part 133 for extracting IDs of the past projects of the top N highest degrees of similarity; a cost deviation calculation part 134 for obtaining cost deviations with reference to the estimate of the target project, based on the cost estimates and the actual costs of the N past projects; a provisional fluctuation information generation part 135 for generating provisional earnings fluctuation information by using the cost deviations; a processing control part 136 for controlling various functional parts, such as controlling the above-mentioned functional parts 132-135 so as to perform the processing on all the posterior-to-countermeasure risk event parameter groups; a posterior-to-countermeasure fluctuation information generation part 137 for generating posterior-to-countermeasure earnings fluctuation information by statistically processing the provisional earnings fluctuation information for each of all the posterior-to-countermeasure risk parameter groups; and a countermeasure-requiring event extraction part 138 for extracting risk event IDs of risk event parameters that are different from the corresponding risk event parameters in a posterior-to-countermeasure risk event parameter group used for generating the posterior-to-countermeasure earnings fluctuation information, among the risk event parameters in the prior-to-countermeasure risk event parameter group.
Here, all of the above-mentioned functional parts of the CPU 110 function when the CPU 110 executes the project support program 139 stored in the external storage 160.
Next, operation of the project support apparatus 100 will be described.
So as to make the project support apparatus 100 output earnings fluctuation information which indicates fluctuation of development-manufacturing cost with reference to an estimate of that cost, it is necessary to input earnings data and estimation risk event parameters of many past projects into the project support apparatus 100 in advance.
Thus, the receiving part 111 of the project support apparatus 100 receives IDs of a plurality of past projects, cost estimates and actual costs of those projects, and risk event parameter groups for each of those projects through the input unit 181, the communication unit or the like. Each of the received risk event parameter groups of the past projects is a set of risk event parameters corresponding respectively to the risk events stored in the risk event content table 161 (
Then, the receiving part 111 stores the IDs of the past projects in the project ID area 164a of the past project earnings data table 164 shown in
When the receiving of the past project earnings data and the estimation risk event parameters ends, it becomes possible for the project support apparatus 100 to receive earnings data or the like of the target project at any time, to generate earnings fluctuation information of the target project. That is to say, it becomes possible that the project support apparatus 100 executes the processing shown in the flowcharts of
Now, referring to the flowcharts shown in
First, as shown in the flowchart of
A user of the project support apparatus 100 sees the input screen 183 and operates the input unit 181 to input the project ID “PJ001001” of the target project in the project ID input field 183 and a cost estimate “75 (75 million)” of the target project in the cost estimate input field 183b. Further, the user refers to the risk event contents displayed in the risk event explanation field 183d, and checks the risk existence-nonexistence check field 183e if there is risk of the risk event concerned. Further, the user selects either “Minimum of cost fluctuation ranges” or “Minimum of average costs” displayed in the output type setting field 183f.
When the user finishes the input and the like of all the input fields 183a, 183b, 183f and the like, he pushes an execution button in the input screen 183. If the execution button should be pushed before the input and the like of all the input fields 183a, 183b, 183f and the like have been finished, the receiving part 111 judges that un-inputted data exists (S11) and prompts input or the like of the un-inputted data. On the other hand, if no un-inputted data exists, the receiving part 111 stores the received input data in the appropriate areas (S20).
In detail, the receiving part 111 stores the project ID “PJ00101” of the target project in the project ID area 162a of the target project earnings data table 162 shown in
Next, the processing control part 126 of the prior-to-countermeasure processing part 120 reads the target project earnings data table 162, the target project risk event parameter table 163, the past project earnings data table 164 and the past project risk event parameter table 165 from the external storage 60, and places these tables in the RAM 150 (S30) in order to make the prior-to-countermeasure processing part 120 execute a prior-to-risk-countermeasure earnings fluctuation information generation process (S40).
Now, the prior-to-risk-countermeasure earnings fluctuation information generation process (S40) by the prior-to-countermeasure processing part 120 will be described referring to the flowchart shown in
The similarity calculation part 122 of the prior-to-countermeasure processing part 120 extracts one of the risk event parameter groups at the time of estimation from the past project risk event parameter table 165 placed in the RAM 150 (S41), and calculates its degree of similarity to the risk event parameter group of “prior-to-countermeasure risk event parameter group 0” stored in the target project risk event parameter table 163 (
The degree of similarity S may be obtained by the following (Eq. 1) of the simplest collaborative filtering method or by another method such as another collaborative filtering method, a clustering method or the like.
Here,
The degree of similarity S obtained by (Eq. 1) is a value of not more than 1 and not less than 0. The value which is closer to 1 is recognized to indicate the higher degree of similarity.
Next, the similarity calculation part 122 judges whether there exists a past project risk event parameter group that has not been extracted (S43), and repeats the processing of the steps S41-S43 until there is no un-extracted risk event parameter group of a past project existed.
When it is found that there is no un-extracted risk event parameter group of a past project, the project extraction part 123 extracts the past project IDs of the top N (for example, four) of the highest degrees of similarity from the prior-to-countermeasure project similarity table 152 (
Next, the cost deviation calculation part 124 obtains a cost deviation ratio Dr of each of the past projects extracted in the step S44 according to the following (Eq. 2) by using the cost estimate E and the actual cost R corresponding to the ID of the past project concerned (S45).
Dr=(R−E)/E (Eq. 2)
For example, in the case of the past project ID “PJ000010”, the cost estimate E (=100.0) and the actual cost (=93.3) corresponding to that ID “PJ000010” are obtained by referring to the past project earnings data table 164 shown in
Successively, the cost deviation calculation part 124 obtains a cost deviation D of the target project for each of the cost deviation ratios Dr of the N past projects according to the following (Eq. 3) by using the cost deviation ratios Dr of the N past projects and the cost estimate of the target project (S46).
D=E·Dr (Eq. 3)
For example, in the case of the past project ID “PJ000010”, the cost estimate E (=75) of the target project is multiplied by the cost deviation ratio Dr (=−0.067) obtained in the step S45 with respect to the ID “PJ000010”, to obtain the cost deviation D (=−5.0) of the target project.
Next, the prior-to-countermeasure fluctuation information generation part 127 obtains the minimum deviation and the maximum deviation out of the N cost deviations D of the target project. That is to say, the N cost deviations D are statistically processed to obtain the minimum deviation and the maximum deviation. Then, the prior-to-countermeasure fluctuation information generation part 127 adds the minimum deviation to the cost estimate of the target project, and stores the result as the minimum cost in the prior-to-risk-countermeasure minimum cost area 162c of the target project earnings data table 162 (
For example, in the case where the target project's cost deviations D obtained in the step S46 are “35.0” for the cost deviation ratio Dr of “PJ000002”, “−5.0” for the cost deviation ratio Dr of “PJ000010”, “15.2” for the cost deviation ratio Dr of “PJ000037”, and “−3.7” for the cost deviation ratio Dr of “PJ000045”, the minimum deviation is “−5.0” and the maximum deviation is “35.0”. Thus, the minimum cost of the target project is “70.0 (=75.0−5.0)”, and the maximum cost of the target project is “110.0=750.0+35.0”. These values are stored in the prior-to-risk-countermeasure minimum cost area 162c and the prior-to-risk-countermeasure maximum cost area 162d of the earnings data table 162 (
In the present embodiment, the prior-to-risk-countermeasure earnings (cost) fluctuation information is information including the target project's minimum and maximum costs obtained in the step S47 and the cost fluctuation quantity i.e. a difference between the maximum cost and the minimum cost.
This is the end of the prior-to-risk-countermeasure earnings fluctuation information generation process (S40) by the prior-to-countermeasure processing part 120.
Now, description will be given referring to the flowchart shown in
When the prior-to-risk-countermeasure earnings fluctuation information generation process (S40) ends, then the posterior-to-countermeasure processing part 130 generates the posterior-to-risk-countermeasure earnings fluctuation information (S50).
Here, the posterior-to-risk-countermeasure earnings fluctuation information generation process (S50) by the posterior-to-countermeasure processing part 130 will be described referring to the flowchart shown in
The posterior-to-countermeasure parameter setting part 131 of the posterior-to-countermeasure processing part 130 changes a risk event parameter in the risk event parameter group of the target project in order to eliminate the risk in question. Such operation is performed until the risks of all the risk parameters do not exist, and all the posterior-to-counter measure risk event parameter groups obtained are stored in the target project risk event parameter table 163 (
In detail, the posterior-to-countermeasure parameter setting part 131 changes the first parameter “1” to “0” among the risk event parameters “0, 1, 0, . . . , 1, 1” of the risk event parameter group of the parameter group ID “Prior-to-countermeasure risk event parameter group 0” in the target project risk event parameter table 163 (
Next, the similarity calculation part 132 of the posterior-to-countermeasure processing part 130 extracts a pair of a parameter ID and a risk event parameter group from the target project risk event parameter table 163 (
Successively, the similarity calculation part 132 judges whether there is an un-extracted past project risk event parameter group (S55). If there is an un-extracted group, the processing returns to the step S53, and otherwise proceeds to the step S56.
Although the processing in the step S52 is performed repeatedly, the target project risk event parameter group extracted for the first time in the processing of the step S52 is the prior-to-countermeasure risk event parameter group. Further, although the processing in the steps S53-S55 is also performed repeatedly, the object of the processing in the steps 53-55 is a risk event parameter group at the time of estimation of a past project until a posterior-to-countermeasure risk event parameter group of the target project is extracted as a new parameter group in the step S52. That is to say, until a posterior-to-countermeasure risk event parameter group of the target project is extracted as a new parameter group in the step S52, the degree of similarity between each of the risk event parameter groups at the times of estimation of all the past projects and the prior-to-countermeasure risk event parameter of the target project is calculated in this repetitive processing of the steps S53-S55. And the calculated degrees of similarity are stored in the posterior-to-countermeasure project similarity table 153 shown in
When it is judged in the step S55 that there is no un-extracted risk event parameter group of a past project, then the project extraction part 133 extracts the past project IDs corresponding to the top N (for example, four) highest degrees of similarity from the posterior-to-countermeasure project similarity table 153 shown in
When the cost deviation D of the target project for each of the N cost deviation ratios Dr is obtained (S58), the processing control part 136 judges which of “Minimum of cost fluctuation ranges” and “Minimum of average costs” is stored as the output type 151 (
In the step S60, the provisional fluctuation information generation part 135 obtains the minimum cost deviation and the maximum cost deviation out of N cost deviations D obtained in the step S58, calculates a difference between the minimum and maximum cost deviations as a cost fluctuation range, and stores in the RAM 150 the obtained cost fluctuation range together with the minimum cost deviation, the maximum cost deviation, and the target project's risk event parameter group ID indicating the minimum cost deviation.
Next, the processing control part 136 judges whether there is an un-extracted risk event parameter group of the target project (S61). If there is an un-extracted risk event parameter, the processing returns to the step S52.
In the step 52, similarly to the above, the similarity calculation part 132 extracts a pair of a parameter ID and a risk event parameter group from the target project risk event parameter table 163 (
Here, a target project's risk event parameter group extracted in the second or later processing in the step S52 is a posterior-to-countermeasure risk event parameter group. Further, in that case, the object in the processing in the steps S53-S55 is a risk event parameter group at the time completion of a past project. That is to say, in this repetitive processing of the steps 53-55, the degree of similarities between each of the risk event parameter groups at the times of completion of all the past projects and the prior-to-countermeasure risk event parameter of the target project is calculated. And the calculated degrees of similarity are stored in the posterior-to-countermeasure project similarity table 153 shown in
After that, similarly to the above, the steps 56-61 are executed. Thus, until it is judged in the step S61 that there is no un-extracted risk event parameter group of the target project, the processing in the steps S52-S61 is repeated.
When it is judged in the step S61 that there is no un-extracted risk event parameter group of the target project, the posterior-to-countermeasure fluctuation information generation part 137 selects the minimum cost fluctuation range among a plurality of cost fluctuation ranges stored in the RAM 150, as a part of the posterior-to-countermeasure earnings fluctuation information. Successively, the posterior-to-countermeasure fluctuation information generation part 137 refers to the RAM 150 to obtain the minimum cost deviation and the maximum cost deviation corresponding to the minimum cost fluctuation range, these data being stored in the step S60, and adds the cost estimate to these deviations to obtain the posterior-to-countermeasure minimum cost and the posterior-to-countermeasure maximum cost. Then, the posterior-to-countermeasure fluctuation generation part 137 stores the posterior-to-countermeasure minimum cost in the posterior-to-risk-countermeasure minimum cost area 162e of the target project earnings data table 162 (
If it is judged in the step S59 that as the output type 151 (
Next, the processing control part 136 judges whether there exists an un-extracted risk event parameter group of the target project (S64). If there is an un-extracted risk event parameter of the target project, the processing returns to the step S52.
When the processing returns to the step S52, one of the posterior-to-countermeasure risk event parameter groups is extracted in this step S52 out of the risk event parameter groups of the target project, similarly to the case where the judgment in the step S61 causes returning to the step S52. And, in the repetitive processing of the steps S53-S55, the degree of similarity between each of the risk event parameter groups at the times of completion of all the past projects and the posterior-to-countermeasure risk event parameter of the target project is calculated. And after that, similarly to the above, the steps S56-S59, S63 and S64 are executed. And, until it is judged in the step S64 that there is no un-extracted risk event parameter group of the target project, the processing of the steps S52-S59, S63 and S64 is repeated.
When it is judged in the step S64 that there is no un-extracted risk event parameter group of the target project, then the posterior-to-countermeasure fluctuation information generation part 137 selects the minimum average cost among a plurality of average costs stored in the RAM 150, to take it as the posterior-to-countermeasure earnings fluctuation information. And, the minimum average cost is stored in the posterior-to-risk-countermeasure minimum average cost area 162g of the target project earnings data table 162 (
Returning again to the flowchart shown in
When the posterior-to-risk-countermeasure earnings fluctuation information generation process (S50) ends, the countermeasure-requiring event extraction part 138 extracts risk event IDs of risk event parameters that are, among the risk event parameters of the prior-to-countermeasure risk event parameter group, different from the corresponding risk event parameters of the posterior-to-countermeasure risk event parameter group used for generating the posterior-to-countermeasure earnings fluctuation information. The extracted risk event IDs are taken as countermeasure-requiring risk event IDs (S70).
Here, the countermeasure-requiring risk event extraction process (S70) performed by the countermeasure-requiring event extraction part 138 will be described referring to the flowchart shown in
First, the countermeasure-requiring event extraction part 138 extracts, out of all the risk event parameter groups of the target project, a risk event parameter group that is closest to the values indicated by the posterior-to-countermeasure fluctuation information (S71). Here, in the case where the posterior-to-countermeasure earnings fluctuation information includes the minimum cost fluctuation range after taking the countermeasure, the countermeasure-requiring event extraction part 138 refers to the RAM 150 in which the target project's risk event parameter group ID showing the minimum cost deviation is stored in the step S60 (
Among risk event parameters in the prior-to-countermeasure risk event parameter group, the countermeasure-requiring event extraction part 138 extracts risk event IDs whose parameters are different from the risk event parameters in the risk event parameter group extracted above (S72). Successively, from the risk event content table 161 (
Finally, the countermeasure-requiring event extraction part 138 stores the risk event IDs and their contents in the countermeasure-requiring risk event table 166 (
Referring to the flowchart shown in
When the countermeasure-requiring risk event extraction process (S70) ends, the output part 112 makes the display unit 182 display the output screen 184 shown in
This output screen 184 displays the target project ID 184a, the earnings fluctuation information 184b, and the risk-countermeasure-requiring events 184e.
The earnings fluctuation information 184b is shown by a bar graph whose vertical axis shows cost. This bar graph includes a bar graph 184c that indicates the prior-to-risk-countermeasure earnings fluctuation information and a bar graph 184d that indicates the posterior-to-countermeasure earnings fluctuation information. These bar graphs 184c and 184d each show the minimum and maximum costs concerned. And the color of the part between the minimum cost and the maximum cost is changed from the color of the other part, to indicate the cost fluctuation range also. Further, the cost estimate is shown in each of the bar graphs 184c and 184d.
The risk-countermeasure-requiring events 184e are a set of the risk event IDs and their contents stored in the countermeasure-requiring risk event table 166. As described above, the risk event IDs in the risk-countermeasure-requiring events 184e are the risk event IDs of the risk event parameters that are, among the risk event parameters in the prior-to-countermeasure risk event parameter group, different from the corresponding risk event parameters in the posterior-to-countermeasure risk event parameter group used for generating the posterior-to-countermeasure earnings fluctuation information. Thus, by taking countermeasures against the risk events in the risk-countermeasure-requiring events 184e, it is possible to change the prior-to-risk countermeasure cost into the posterior-to-countermeasure cost.
The present embodiment described hereinabove indicates cost (earning) fluctuation information with reference to a cost estimate regarding a target project, and thus it is possible to support judgment on the advisability of execution of the target project, determination of a budget for the target project, and the like. In addition, the present embodiment indicates not only the cost fluctuation information on the condition that countermeasures against a plurality of estimation risk events are taken, but also the risk events requiring the countermeasures in order to obtain the values indicated by the cost fluctuation information after taking the countermeasures. Thus, it is possible to promote countermeasures against risk events in advancing a project.
In the posterior-to-risk-countermeasure earnings fluctuation information generation process (S50) of the present embodiment, the posterior-to-countermeasure earnings fluctuation information is generated by using the prior-to-countermeasure risk event parameter group included in the risk event parameter groups of the target project. However, it is possible to arrange that posterior-to-countermeasure earnings fluctuation information is generated by using only the posterior-to-countermeasure risk event parameter groups without using the prior-to-countermeasure risk event parameter group.
Further, in the present embodiment, costs of development and manufacturing are employed as the earnings parameters. However the present invention is not limited to this, and sales volume, sales in units, profit and loss, and the like of deliverables of a project may be employed as earnings parameters. In that case, earnings fluctuation information is sales volume fluctuation information, unit sales fluctuation information, and profit-or-loss fluctuation information.
Further, in the present embodiment, the prior-to-risk-countermeasure earnings fluctuation information includes a fluctuation range of earnings (cost), and the minimum and maximum values as the values at both ends of the fluctuation range. And, the posterior-to-risk-countermeasure earnings fluctuation information includes the minimum fluctuation range of earnings, and the minimum and maximum values as the values at both ends of the fluctuation range, and the minimum average value. Needless to say, however, it is possible to support judgment on the advisability of execution of a target project, determination of budget for a target project, or the like only if the earnings fluctuation information includes any one of these values. However, the more types of data the earnings fluctuation information includes, the more useful the earnings fluctuation information is for judgment on the advisability of execution of a target project. Thus, it is favorable that the earnings fluctuation information includes more types of data as far as possible. Further, the prior-to-risk-countermeasure earnings fluctuation information may include, for example, the minimum and maximum deviations with reference to an estimate of earnings, and the posterior-to-risk-countermeasure earnings fluctuation information may include, for example, the maximum minimum deviation or the maximum minimum value, the minimum maximum deviation or the minimum maximum value, the maximum fluctuation range and the minimum and maximum values as values at both ends of the range, average minimum value, or the like concerning earnings.
Here, among the data types that may be included in the posterior-to-risk-countermeasure earnings fluctuation information, the maximum minimum deviation or the maximum minimum value of earnings is obtained as follows. First, the provisional fluctuation information generation part 135 obtains the minimum deviation among earnings parameter's deviations obtained from respective deviation ratios of a plurality of past projects, or obtains the earnings parameter's minimum value determined by that minimum deviation. Then, the posterior-to-countermeasure fluctuation information generation part 137 extracts the maximum value among the minimum deviations or minimum values obtained respectively from all the risk event parameter groups of the target project, and determines that maximum value as the maximum minimum deviation or maximum minimum value concerning the earnings. Further, the minimum maximum deviation or the minimum maximum value of earnings is obtained as follows. First, the provisional fluctuation information generation part 135 obtains the maximum deviation among earnings parameter's deviations obtained from respective deviation ratios of a plurality of past projects, or obtains the earnings parameter's maximum value determined by that maximum deviation. Then, the posterior-to-countermeasure fluctuation information generation part 137 extracts the minimum value among the maximum deviations or maximum values obtained respectively from all the risk event parameter groups of the target project, and determines that minimum value as the minimum maximum deviation or minimum maximum value concerning the earnings.
100: the project support apparatus, 110: the CPU, 111: the receiving part, 112: the output part, 120 the prior-to-countermeasure processing part, 122,132: the similarity calculation part, 123,133: the project extraction part, 124,134: the cost deviation calculation part, 126,136: the processing control part, 127: the prior-to-countermeasure fluctuation information generation part, 130: the posterior-to-countermeasure processing part, 131: the posterior-to-countermeasure parameter setting part, 135: the provisional fluctuation information generation part, 137: the posterior-to-countermeasure fluctuation information generation part, 138: the countermeasure-requiring event extraction part, 140: the ROM, 150: the RAM, 151: the output type, 152: the prior-to-countermeasure project similarity table, 153: the posterior-to-countermeasure project similarity table, 160: the external storage 161: the risk event table, 162: the target project earnings data table, 163: the target project risk event parameter table, 164: the past project earnings data table, 165: the past project risk event parameter table, 166: the countermeasure-requiring risk event table, 169: the project support program, 182: the display unit, 183: the input screen, 184: the output screen
| Number | Date | Country | Kind |
|---|---|---|---|
| 2009-033768 | Feb 2009 | JP | national |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/JP2009/069611 | 11/19/2009 | WO | 00 | 8/24/2011 |
