Accounting management device, accounting management method, and accounting management program

Abstract

To provide an accounting management device that easily and quickly detects and displays an abnormal value in data related to contract work, for example, in a construction project.SOLUTION: An acquisition unit acquires a remaining order amount and a deemed cost when work for a predetermined contract is completed. A comparison unit compares the obtained ordering remainder amount with the deemed cost. Furthermore, a determination unit determines, when the deemed cost is greater than the ordering remainder amount, or when the deemed cost is less than the ordering remainder amount, an amount of the deemed cost to be abnormal. A display control unit then displays at least the ordering remainder amount and a deemed cost accounting status graph on a display unit, and displays the deemed cost accounting status graph determined to be an abnormal amount in a display format different from that of the ordering remainder amount.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an accounting management device, an accounting management method, and an accounting management program.

Background Art

[0002] Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2016-045819) discloses a performance management system capable of efficiently creating budget information. This performance management system includes a performance information DB that stores performance information on precedent cases, a budget information DB that stores budget information on cases to be created, a budget creation management unit budget system that creates budget information, and a budget input screen for exchanging information with a user.

[0003] Based on the identification information associated with the case to be created, the budget system extracts the performance information of related precedent cases related to the case to be created from the performance information of precedent cases stored in the performance information DB, and associates and outputs the extracted performance information of related precedent cases with the budget information of the case to be created. Thereby, budget information can be created efficiently.

[0004] In paragraph 0029 of such Patent Document 1, a technique is disclosed in which a prognostic diagnosis unit reads out the performance information of other precedent cases in which the case to be created and the implementation time (production period) are similar from the performance information DB, compares it with the cost items of the case to be created, diagnoses the possibility of an error occurring, and outputs a diagnosis result.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Here, for example, in the construction industry and the like, data related to the work of contracts such as construction may show abnormal values. Since the detection of abnormal values requires searching through a vast amount of data, manual detection is extremely difficult. Therefore, the development of a technology that can easily and quickly detect abnormal values is demanded.

[0007] The present invention has been made in view of the above-described problems, and an object thereof is to provide an accounting management apparatus, an accounting management method, and an accounting management program capable of easily and quickly detecting and displaying abnormal values of data related to contract work.

Means for Solving the Problems

[0008] In order to solve the above-described problems and achieve the object, an accounting management apparatus according to the present invention includes: an acquisition unit that acquires an outstanding order balance amount and an estimated cost when the work of a predetermined contract is completed; a comparison unit that compares the acquired outstanding order balance amount and the estimated cost; based on the comparison result of the comparison unit, determines whether the correlation between the outstanding order balance amount and the estimated cost is outside the allowable range of a predetermined trend or within the allowable range, and when the correlation between the outstanding order balance amount and the estimated cost is outside the allowable range of the predetermined trend, a determination unit that determines the amount of the estimated cost as an abnormal amount; and a display control unit that displays at least a graph of the accounting status of the outstanding order balance amount and the estimated cost on a display unit, and displays the graph of the accounting status of the estimated cost determined as an abnormal amount by the determination unit in a display form different from that of the outstanding order balance amount.

[0009] In addition, in order to solve the above-described problems and achieve the object, an accounting management method according to the present invention includes: an acquisition step in which an acquisition unit acquires an outstanding order balance and an estimated cost when work on a predetermined contract is completed; a comparison step in which a comparison unit compares the acquired outstanding order balance with the estimated cost; a determination step in which a determination unit determines, based on the comparison result of the comparison step, whether the correlation between the outstanding order balance and the estimated cost is outside the allowable range of a predetermined tendency or within the allowable range, and when the correlation between the outstanding order balance and the estimated cost is outside the allowable range of the predetermined tendency, determines the amount of the estimated cost as an abnormal amount; and a display control step in which a display control unit displays at least a graph of the accounting status of the outstanding order balance and the estimated cost on a display unit, and displays the graph of the accounting status of the estimated cost determined as an abnormal amount in the determination step in a display form different from that of the outstanding order balance.

[0010] In addition, in order to solve the above-described problems and achieve the object, an accounting management program according to the present invention causes a computer to function as an acquisition unit that acquires an outstanding order balance and an estimated cost when work on a predetermined contract is completed, a comparison unit that compares the acquired outstanding order balance with the estimated cost, a determination unit that determines, based on the comparison result of the comparison unit, whether the correlation between the outstanding order balance and the estimated cost is outside the allowable range of a predetermined tendency or within the allowable range, and when the correlation between the outstanding order balance and the estimated cost is outside the allowable range of the predetermined tendency, determines the amount of the estimated cost as an abnormal amount, and a display control unit that displays at least a graph of the accounting status of the outstanding order balance and the estimated cost on a display unit and displays the graph of the accounting status of the estimated cost determined as an abnormal amount by the determination unit in a display form different from that of the outstanding order balance.

Effects of the Invention

[0011] The present invention can easily and quickly detect and display abnormal values of data related to contract work.

Brief Description of the Drawings

[0012]

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Mode for Carrying Out the Invention

[0013] Hereinafter, an accounting management apparatus according to an embodiment to which the present invention is applied will be described in detail with reference to the drawings. As an example below, in a construction project of a predetermined project which is an example of contract work, an example of detecting an outlier value of the assumed cost recorded as an outlier value of data related to the contract work will be described. Further, as a detection method, the description will be made by using the "Hotelling method" or (and) the "rule-based method", but this is also an example, and other detection methods such as the "local outlier factor method" may be used. Thus, the present invention is not limited to the following embodiments.

[0014] (Hardware Configuration) As shown in FIG. 1, the accounting management apparatus 1 of the embodiment includes a storage unit 2, a control unit 3, a communication interface unit 4, and an input / output interface unit 5. An input device 6 and an output device 7 are connected to the input / output interface unit 5. As the output device 7, a display unit such as a monitor device (including a home TV), a printing device, or a speaker device corresponds. As the input device 6, in addition to a keyboard device, a mouse device, and a microphone device, a monitor device that realizes a pointing device function in cooperation with the mouse device can be used. The communication interface unit 4 is connected to a network such as a wide area network such as the Internet or a private network such as a LAN (Local Area Network).

[0015] As the storage unit 2, for example, a storage device such as a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an SSD (Solid State Drive) can be used. In the storage unit 2, an accounting management program that detects an abnormality in the estimated cost of each construction item accounted for in accounting and performs a predetermined alert display and various related data are stored.

[0016] (Functional Configuration of Accounting Management Apparatus) Next, the control unit 3 functions as a display control unit 21, an acquisition unit 22, a comparison unit 23, a determination unit 24, and a storage control unit 25 as shown in FIG. 1 by executing the accounting management program stored in the storage unit 2.

[0017] The acquisition unit 22 acquires the outstanding order amount and the estimated cost when the work (construction) of a predetermined contract is completed. The comparison unit 23 compares the acquired outstanding order amount with the estimated cost. The determination unit 24 determines whether the correlation between the outstanding order amount and the estimated cost is outside the allowable range of a predetermined trend or within the allowable range based on the comparison result of the comparison unit 23, and determines the amount of the estimated cost as an abnormal amount when the correlation between the outstanding order amount and the estimated cost is outside the allowable range of a predetermined trend.

[0018] As will be described in detail later, the determination of whether or not the correlation between the outstanding balance amount and the deemed cost is outside the allowable range of a predetermined trend can be made using, for example, the "rule-based method", the "Hotelling method", or the "local outlier factor method". When using the "rule-based method", the correlation between the outstanding balance amount and the deemed cost can be determined based on the direct magnitude relationship (not equal) between the outstanding balance amount and the deemed cost, and whether or not the difference between the outstanding balance amount and the deemed cost is outside a predetermined range. Also, when using the "Hotelling method", the correlation between the outstanding balance amount and the deemed cost can be determined based on whether or not it is outside the normal boundary line range of a predetermined significance level based on the normal distribution of the Mahalanobis distance. Further, when using the "local outlier factor method" or the like, the correlation between the outstanding balance amount and the deemed cost can be determined based on whether or not the LOF (Local Outlier Factor) index calculated from the local reachability density is equal to or greater than a predetermined threshold value.

[0019] The display control unit 21 displays at least the graphs of the accounting status of the outstanding balance amount and the deemed cost on the display unit (output device 7), and the display control unit 21 displays the graph of the accounting status of the deemed cost determined as an abnormal amount by the determination unit 24 in a display form different from that of the outstanding balance amount. As an example of the "different display form", there are, for example, a change in display color or a change in brightness.

[0020] Also, the acquisition unit 22 acquires the outstanding balance amount and the deemed cost for each predetermined item. The display control unit 21 displays the item-by-item status graph on the display unit, and the display control unit 21 displays the item-by-item status graph of the deemed cost of the construction determined as an abnormal amount by the determination unit 24 in a display form different from that of the item-by-item status graph of the outstanding balance amount. The predetermined items are, for example, material costs, outsourcing costs, labor costs, and expenses.

[0021] In addition, the acquisition unit 22 acquires the budget amount and the assumed cost for each type of contract work (by construction project). The display control unit 21 plots points corresponding to the acquired budget amount and assumed cost on a cost recording status graph for each type of work with one coordinate axis representing the budget amount and the other coordinate axis representing the assumed cost. The determination unit 24 determines, when points corresponding to the acquired budget amount and assumed cost are plotted on a cost recording status graph for each type of work (cost recording status graph by construction project) with one coordinate axis (for example, the X-axis) representing the budget amount and the other coordinate axis (for example, the Y-axis) representing the assumed cost, the amount of the assumed cost corresponding to points plotted at a distance greater than or equal to a predetermined distance from the center point of the population of each point as an abnormal amount.

[0022] The display control unit 21 plots and displays points corresponding to the acquired budget amount and assumed cost on a cost recording status graph for each type of work with one coordinate axis representing the budget amount and the other coordinate axis representing the assumed cost, and displays, in a display form different from other points, the points plotted at a distance greater than or equal to a predetermined distance from the center point of the population, which are determined as abnormal amounts, on the cost recording status graph for each type of work.

[0023] In addition, the display control unit 21 displays a normal range boundary line connecting the points plotted at positions corresponding to the outline of the population on the cost recording status graph by construction project.

[0024] In addition, the acquisition unit 22 acquires the amount for each predetermined cost item for each type of contract work (by construction project). The display control unit 21 displays, on the display unit, work-by-work cost-item-by-construction status data (construction-by-construction cost-item-by-construction status data) indicating the amount for each predetermined cost item for each type of contract work (by construction project).

[0025] In addition, the display control unit 21 displays, on the display unit, work detail data (construction detail data) including the business office and the person in charge who carried out the work (construction) of the contract for which the amount of the assumed cost is determined as an abnormal amount.

[0026] (Overview) For projects that have reached the completion stage, there are cases where the completed projects must be recorded as achievements before the invoices for the ordered work, which are the costs, are received from the order recipients. This includes cases where the invoices are received in the month following the month of project completion. In such cases, there is an operation of recording "estimated costs" as the amount that would originally occur as costs. Basically, as shown in Fig. 2(a), it is common to record the remaining order amount as it is as the "estimated cost".

[0027] However, in companies that have not automated this process or companies with a large number of unexpected purchases, operators manually record the "estimated costs", resulting in intentional cost increase or decrease operations and human registration errors. For example, in the case of group companies, since the estimated amounts are controlled by responsible persons such as the directors of each base, as shown in Fig. 2(b), cost inflation or post-recording of costs (recording after the reporting process), or as shown in Fig. 2(c), cost recording omissions may occur.

[0028] In the accounting management device 1 of the embodiment, as an example, as a method for detecting abnormal values of such estimated costs, the hoteling method shown in Fig. 3 that utilizes the occurrence tendency of estimated costs among projects of the same scale, or (and) the rule-based method shown in Fig. 4 that compares the remaining order amount with the estimated cost is used.

[0029] Projects of the same scale tend to have similar cost occurrence tendencies (time, material quantity, arranged number of personnel, etc.), and the amounts of the remaining orders at the completion time are also often similar. In the hoteling method shown in Fig. 3, such characteristics are utilized to detect abnormal values of estimated costs.

[0030] Also, depending on the company, there are also similar cases from perspectives such as work types, public or private, and organizations. Therefore, in the accounting management device 1 of the embodiment, comparison of estimated costs is performed in units of projects of the same scale using a common axis applicable to many companies to detect abnormal values. Perspectives such as work types, public or private, and organizations can be set as extraction items on the analysis screen side so that they can be utilized and analyzed according to the company.

[0031] On the other hand, in the case of industries such as the construction industry where there is an operation of treating the outstanding purchase orders as costs and recording them as such, the rule-based method shown in FIG. 4 utilizes this. In this rule-based method, "outstanding purchase orders > deemed cost" is detected as an omission in recording or an improper non-recording of costs (profit manipulation). Also, in the rule-based method, "outstanding purchase orders < deemed cost" is detected as an incorrect input or double recording.

[0032] When using the Hotelling method as an outlier detection method, the population that can be used in the Hotelling method needs to follow a normal distribution as shown in FIG. 5. In the Hotelling method, by utilizing the characteristics of data that follow a normal distribution, grouping such as clustering is performed as shown in FIG. 7, for example. Then, within this group, the Mahalanobis distance is calculated to determine the degree of abnormality.

[0033] Whether the correlation between the total cost budget and the deemed cost used for outlier detection in the accounting management device 1 of the embodiment follows the normal distribution illustrated in FIG. 5 depends on the transaction circumstances or rules of the using company. However, if it is known that it is reasonable to assume that it follows a normal distribution, by using the Hotelling method, the threshold for outlier determination can be automatically determined, enabling flexible and highly accurate outlier detection according to the characteristics of each company or project.

[0034] Also, as shown in FIG. 6, even in an example where it does not follow a normal distribution, if the population can be divided into units that follow a normal distribution by performing cluster analysis according to the types of construction work such as the type of work or public / private, the construction data can be labeled for each population of the divided clusters, and outlier detection can be performed by the Hotelling method using different thresholds for each.

[0035] Also, when it does not follow a normal distribution, it may be arbitrarily replaced with other known statistical methods that can be used and executed.

[0036] In any case, data above a specific threshold or below the threshold is detected as an outlier, and the results of this outlier detection can be uniformly processed.

[0037] In addition, when it can be confirmed that the total cost budget and the estimated cost tend to roughly follow a normal distribution, applying the Hotelling method can be expected to improve the accuracy of anomaly detection.

[0038] Next, in the accounting management device 1 of the embodiment, as an example, for completed construction projects, the detection and analysis of abnormal values of the estimated cost are performed. That is, for the remaining estimated cost at the completion time of the construction project, the presence or absence of anomalies is detected by comparing it with the planned cost or the outstanding order amount. It is difficult to consider cases where the cost fluctuates significantly at the completion time, and basically, there are many patterns where the outstanding order amount = the estimated cost.

[0039] On the other hand, construction projects for which no estimated cost is generated are excluded from the detection of abnormal values of the estimated cost. That is, in the accounting management device 1 of the embodiment, attention is paid to the estimated cost for each construction project at the completion time, and construction projects for which no estimated cost exists are treated as noise for the accounting management device 1 of the embodiment and are excluded from the confirmation target.

[0040] Next, for construction projects of the same scale, the types, qualities, and quantities of things (materials or personnel) required for the construction projects tend to be similar. Therefore, for construction projects of the same scale, the cost generation tendencies are also similar. The transportation costs to the construction site, arrangements with available subcontractors, and differences in material prices for each public and private construction project are cost elements whose amounts vary for each construction project. However, when compared with the total of major classifications such as material costs, subcontracting costs, labor costs, and expenses that make up the construction cost, the difference is within the error range. Therefore, since the bias of the population is absorbed to a certain extent, it is considered to roughly follow a certain normal distribution.

[0041] Next, since the accounting rules for estimated costs vary from company to company, it is difficult to uniformly determine the method for detecting abnormal values of estimated costs. Therefore, the accounting management device 1 of the embodiment enables the selection of an anomaly detection method, enabling flexible and general-purpose anomaly detection according to the operation mode, data trends, or characteristics of each company.

[0042] For example, when a simple accounting rule of treating the outstanding order balance as the estimated cost is applied as shown in Fig. 8(a), there are cases where automated accounting by the system is being carried out. In this case, there is a concern that checking oversights may occur, and there is a risk of fraudulent operations such as profit manipulation.

[0043] When automating the accounting rule of treating the outstanding order balance as the estimated cost, since it is a simple process, there is a perception that fraud is less likely to occur. Conversely, it often becomes a factor that induces fraud. Also, the accounting rule of treating the outstanding order balance as the estimated cost is often applied in companies with a large number of bases. However, since the checking is left to the bases, there is a risk that fraud at the base level may be concealed. Specifically, in the construction industry, the authority of the base manager is often strong, and in order to inflate the profit of the base, fraudulent operations may be carried out at the instruction of the base manager.

[0044] Therefore, the accounting management device 1 of the embodiment performs anomaly detection by the rule - based method, and visualizes not only the data volume and the number of bases but also the outstanding order balance and the estimated cost, making it easier for the operator to notice the occurring abnormal values. As a result, the content being operated and checked at the bases can also be confirmed at the head office, and it becomes easier to notice the abnormal values of the estimated cost. For this reason, as shown in Fig. 8(a), fraud due to the simple rule of treating the outstanding order balance as the estimated cost can be prevented.

[0045] Next, when confirming the anomaly of the estimated cost by comparing the estimated costs between projects of the same scale, it is difficult to make a comparison between projects of the same scale, and there is a risk of incurring a large amount of work costs. That is, when comparing between projects of the same scale, it is necessary to divide the total cost budget into several equal parts for classification, aggregate the actual results for each project by classification, and then make a comparison between projects of the same scale. For this reason, there is a risk of aggregation errors and huge costs. Also, it is difficult to define "projects of the same scale", and depending on the definition, it may be difficult to notice the anomaly of the estimated cost.

[0046] Therefore, in the accounting management device 1 of the embodiment, paying attention to the correlation between the total cost budget and the deemed cost, the system calculates the range that can be regarded as the same category (between similar construction projects), and detects the outside of this range that can be regarded as the same category (outsiders) as abnormal and notifies the operator (displays on the display unit). As a result, as shown in FIG. 8(b), the definition of the same category can be statistically determined on the system side (a definition with higher reliability than the method used in market analysis etc. can be used), and abnormal values of the deemed cost can be quickly detected.

[0047] Next, there is a case where the validity of the deemed cost is determined based on the recognition of the person in charge by base. When the awareness of the person in charge is low, it is strongly required that the management side confirm and correct it, which increases the burden on the management side.

[0048] That is, the confirmation of the validity of the deemed cost is carried out by confirming the purchases that may occur in the future based on the outstanding orders and past similar construction projects, or by comparing the deemed costs between similar construction projects. In either case, the confirmation range is wide, and in the case of group companies, it is often left to the persons in charge of each base for confirmation. Therefore, when the awareness of the person in charge side is low, it becomes difficult to notice the abnormality of the deemed cost, and there is a risk of having an adverse impact on the management state such as the growth of the company's profit being hampered.

[0049] Therefore, in the accounting management device 1 of the embodiment, the deemed costs are compared between similar construction projects as described above, and the outsiders are visualized as shown in FIG. 8(c). As a result, the validity of the general level of the deemed cost can be confirmed, and clearly abnormal values can be quickly detected.

[0050] In addition, even in other cases, the accounting management device 1 of the embodiment can switch between the rule-based method and the statistical method for statistically determining the definition of the same category on the system side, and can cope with various patterns.

[0051] Next, in the case of costs for which there is no order entry for labor costs and expenses etc., it may cause factors of abnormality in the construction cost such as omission or adjustment of the construction cost inclusion. Therefore, analysis by cost classification is necessary, but the work cost becomes enormous, and it is not realistic to check each time.

[0052] Also, the construction cost can be confirmed by analyzing it separately into material cost, outsourced cost, labor cost, and overhead as shown in Fig. 9. In this case, however, it is necessary to totalize for each construction project and cost classification, and there is a risk of occurrence of totalization omission and huge costs. Also, although it is possible to perform an abnormality analysis by comparing with the planned cost, if this is done for each construction project, there is a risk of further increase in the work cost.

[0053] Note that the material cost shown in the example of Fig. 9 is considered to be the same as the outstanding order balance and also consistent with the planned cost including the estimated portion, and there is no abnormality. The outsourced cost is less than the estimated cost compared to the outstanding order balance. For this reason, an omission in the recording of the estimated cost is considered. Conversely, when the estimated cost is more than the outstanding order balance, there is a possibility that unnecessary cost is recorded as the estimated cost. The labor cost is much more than the actual cost compared to the planned cost. For this reason, it is considered possible that wasteful labor costs and improper costs are occurring. The overhead is less than the actual cost compared to the planned cost. For this reason, although it is possible that the work of the construction project is being carried out with the overhead suppressed, there is also a possibility of omission in recording. For this reason, it is preferable to recognize it as an object to be confirmed.

[0054] The accounting management device 1 of the embodiment visualizes the planned amount to occur, outstanding order balance, order actual result, and estimated cost information for each construction project and cost classification. Thereby, it is possible to compare the planned and actual amounts of each cost and compare the outstanding order balance with the estimate on one display screen. For this reason, it is possible to quickly confirm the presence or absence of abnormality for each cost of each construction project and narrow down the range of costs that may be abnormal.

[0055] (Analysis screen) The display control unit 20 of the accounting management device 1 of the embodiment displays "the estimated cost amount with respect to the total cost budget for each construction project" and "the planned order, order actual result, outstanding order balance, and estimated cost for each cost classification within the construction project" on the analysis screen. Also, the display control unit 20 emphasizes and displays the detected abnormal information by changing the display form such as the display color or character size so that it can be visually recognized.

[0056] The confirmable anomaly detection data targets the estimated cost amount of completed construction work as described above, and the construction work determined to be abnormal varies depending on the anomaly detection method. For example, when using the hoteling method, construction work with a total cost budget that is not the same as the estimated cost within the same scale range is detected. Also, when using the rule-based method, construction work with an outstanding order estimated cost is detected.

[0057] (Screen Configuration) Figure 10 is a diagram showing an example of such an analysis screen. The display control unit 20 switches this analysis screen in the order of "display the result message indicating detected anomalies in a list" and "output the result message indicating detected anomalies at the summary level". As shown in this Figure 10, the display control unit 20 displays the timing of detection as an anomaly, the construction work, and the month in which the anomaly was detected, in the area R2 for displaying messages related to the anomaly detection process of the analysis screen. At this point, the display control unit 20 displays an overview of the anomaly detection. When a message is selected by the operator, it switches to the detailed analysis screen shown in Figure 11 and displays the detection information of the anomaly degree corresponding to the selected message. Also, when there are a large number of pieces of information detected as anomalies, the display control unit 20 displays each piece of information in a multiple vertical arrangement (for each column). Note that the area R1 shown in Figure 10 is the display area for the input field of the extraction conditions.

[0058] Figure 11 is a diagram showing an example of a detailed analysis screen. When a message is selected on the analysis screen shown in Figure 10, the display control unit 20 displays the detailed information corresponding to the selected message on the detailed analysis screen shown in Figure 11. This detailed analysis screen is provided with an area RS2 for displaying messages related to the anomaly detection process. The display control unit 20 displays the "detection method used when detecting the anomaly" and the "information that is the key to the data for which the anomaly was detected" in this area RS2. Also, when there are multiple pieces of information detected as anomalies, the display control unit 20 displays the messages corresponding to the number of them in the area RS2.

[0059] Also, when an operator selects a message displayed in this area RS2, the display control unit 20 highlights ( = changes in display form: thick line, high brightness display, display color change, etc.) the part related to the abnormality detection information of the selected message in each graph of areas RS3 to RS5 described below.

[0060] For area RS3, the display control unit 20 displays a graph of the "estimated cost amount regarded as the total budget cost of past construction works" and the "estimated cost amount regarded as the total budget cost of the construction works for which an abnormality has been detected". That is, the display control unit 20 displays a graph for this area RS3 that enables confirmation of the "correlation between the estimated total cost budget amount and the estimated cost amount for each construction work". The display is based on the premise that for construction works with similar total cost budgets, the actual results are output within a certain range of estimated cost amounts. It enables analysis of the degree of abnormality of the construction works for which an abnormality has been detected with respect to past construction works of the same scale.

[0061] The graph displayed in this area RS3 defines the range of similar total cost budgets as "construction works of the same scale" on the X-axis (since the definition of the range of the same scale varies from company to company, it is left to the analyst side to define the range).

[0062] In addition, the display control unit 20 displays this graph regardless of the abnormality detection method. When using the Hotelling method as the abnormality detection method, the display control unit 20 further adds and displays a boundary line that can be judged as the normal range to this graph. Also, even if the abnormality detection method is other than the Hotelling method, the tendency of the occurrence of construction works can be visualized from the tendency of the plots. For example, although abnormality detection is performed using the rule-based method, based on the plot situation, it is possible to judge the data tendency for which the Hotelling method can be used.

[0063] In addition, the display control unit 20 displays a graph of "estimated occurrence, remaining unrecorded, current actual performance, and assumed cost in the cost of the detected abnormal construction work" in area RS4. That is, the display control unit 20 displays in area RS4 the performance that was planned as the estimated occurrence for the current month at the end of the previous month (future estimated cost), the remaining unshipped and unordered items within the current month (remaining orders), the actual performance of orders and purchases made in the current month (actual performance), and the amount incorporated as the current month's cost performance based on the remaining orders (assumed cost).

[0064] Based on the graph in this area RS4, "remaining orders" and "assumed cost" are compared to confirm the "magnitude of the assumed cost". Also, "future estimated cost" and "actual performance + assumed cost" are compared to confirm the "magnitude of actual performance + assumed cost". If it is small, it can be judged as an omission in recording, and if it is large, it can be judged that there may be improper recording.

[0065] In addition, the display control unit 20 displays a graph of "estimated, actual performance, and remaining for the cost classification of the detected abnormal construction work" in area RS5. This enables the confirmation of abnormal values for each cost classification. Since labor costs and expenses are not included in the order, only the perspectives of future estimated cost and actual performance are confirmed. If the assumed amount is large for material costs, it can be analyzed whether there is an inclusion of items from other construction works. Also, if the assumed amount is large for subcontracting costs, it can be analyzed whether there are improper arrangements with subcontractors or whether there is a cash outflow to subcontractors, etc., to induce an analysis for investigating the basis of abnormalities.

[0066] In addition, the display control unit 20 numerically confirms the estimated, remaining, and actual performance for each construction work and cost classification in area RS6, and displays a table showing the ratio of the current cost to the planned cost landing for the construction work. That is, the display control unit 20 displays in area RS6 a table that enables the confirmation of the "status of cost accumulation at the completion of each construction work and cost classification". If the landing estimate exceeds 100%, it is detected as a construction work that may result in low profits or a deficit. By displaying this table, cost classifications leading to abnormalities can be analyzed, and related cost data can be investigated.

[0067] In addition, the display control unit 20 displays a table of "detailed information on the detected abnormal construction work" in the area RS7. That is, the display control unit 20 displays a table that enables confirmation of "detailed information on the detected abnormal construction work" in the area RS7. This table displays the organization, person in charge, supplier, and completion time for managing the construction work. Thereby, it is possible to provide notice of abnormalities and information on the destination for verifying the actual situation.

[0068] In addition, the area RS1 serves as an extraction condition area for data extraction, and the display control unit 20 displays the extraction conditions for the data displayed in the above-described graph or table. Specifically, when extracting and analyzing the settlement period to be confirmed, the display control unit 20 limits the construction work for which actual results have occurred within the accounting year range of the specified settlement period and displays it in the above-described graph or table. Also, when extracting and analyzing the output data at the organization level, the display control unit 20 designates a business office or department and displays the above-described graph or table.

[0069] (Processing flow) Next, the processing flow for displaying the above-described analysis screen and analysis details screen in the accounting management device 1 of the embodiment will be described. Although it is an example, as the abnormality detection method, the above-described hoteling method and rule-based method will be used. These abnormality detection methods can be changed according to the tendency of the data of the using company. Therefore, the following description should be understood as an example.

[0070] In the case of the accounting management device 1 of the embodiment, the following two processes can be performed.

[0071] 1. Check [construction work data], [construction cost data], and [construction order data] in the business data to detect abnormal construction work.

[0072] 2. Display the "abnormal data detected in 1" and the "data related to the abnormal data referred to for detection" on the analysis screen.

[0073] (Detection process for abnormal construction work) From the [construction data], [construction cost data], and [construction order data] within the business data of "1", the following data is used for the process of detecting construction projects with abnormal costs in accordance with the anomaly detection method.

[0074] <Business data>: Assumed data accumulated in the business · Construction data (see Figure 12(a)) · Construction cost data (see Figure 12(b)) · Construction order data (see Figure 12(c))

[0075] <Anomaly detection execution data>: Preset data · Automatic detection execution schedule data (see Figure 13(a)) · Automatic anomaly detection method data (see Figure 13(c)) · Anomaly judgment result registration target period data (see Figure 13(b)) · Acquisition range condition data of construction data

[0076] <Anomaly judgment result data>: Data storing the judgment result of anomaly detection execution · Anomaly judgment result data (see Figure 20(a)) · Anomaly judgment result message data (see Figure 20(b)) · Anomaly judgment result message detail data (see Figure 20(c)) · Anomaly judgment result attached information data (see Figure 20(d))

[0077] (Preset) First, the acquisition unit 22 acquires the automatic detection execution schedule data shown in Figure 13(a), the anomaly judgment result registration target period data shown in Figure 13(b), and the automatic anomaly detection method data shown in Figure 13(c), which are necessary for the anomaly detection of the assumed cost. The storage control unit 25 stores this information in the storage unit 2.

[0078] (Automatic execution) Next, the acquisition unit 22 refers to the automatic detection execution schedule data shown in FIG. 13(a) and the abnormal determination result registration target period data shown in FIG. 13(b) based on the detection identification information (detection ID) and the schedule ID shown in FIG. 13(d), and acquires timing information for detecting an abnormality.

[0079] Next, the determination unit 24 performs the automatic execution timing determination process shown in FIG. 14, which is a process of determining whether the timing of automatic execution is the timing for detecting an abnormality. When the determination result of "execute" is obtained by this automatic execution timing determination process, an abnormality detection process is performed based on the "hoteling method" or the "rule-based method" described below. On the other hand, when the determination result of "do not execute" is obtained by the automatic execution timing determination process, the subsequent process is not executed, and the accounting management device 1 waits until the next automatic execution timing determination process.

[0080] Note that the determination unit 24 refers to a calendar master (not shown) stored in the storage unit 2 to determine holidays and business days. This calendar master is based on the sales business calendar and is always updated to the latest.

[0081] Next, the acquisition unit 22 acquires necessary data based on the abnormality detection method (hoteling method or rule-based method) stored in the automatic abnormality detection data shown in FIG. 13(c). The comparison unit 23 and the determination unit 24 perform an abnormality detection process for the assumed cost based on the acquired data.

[0082] (When the hoteling method is set) When the "hoteling method" exemplified in FIGS. 16 and 17 is set as the abnormality detection method in the automatic abnormality detection data shown in FIG. 13(c), the acquisition unit 22 is based on the acquisition criteria (accounting year and month and construction progress status are "completed") set as parameters as shown in FIG. 15(a), and acquires the construction data shown in FIG. 15(b) and the construction cost data shown in FIG. 15(c).

[0083] That is, the construction data before the accounting year and month is the acquisition target. The target for anomaly detection is limited and anomaly determination is performed by referring to the "acquisition criteria" of the "data for the period of anomaly determination result registration target". In the case of this example, it is the month before the month to which the start date belongs, and the construction work completed before October 2022 is the target (only the completed construction work is the acquisition target).

[0084] In addition, the acquisition unit 22 acquires the budget amount for each construction work from the construction data shown in Fig. 15(b), and acquires the estimated cost amount for each construction work from the construction cost data shown in Fig. 15(c), and calculates the total amount of the estimated cost for each construction work. As shown in Fig. 15(d), the memory control unit 25 stores the budget amount for each construction work and the total amount of the estimated cost amount for each construction work in the storage unit 2.

[0085] Next, the determination unit 24 confirms the correlation between the estimated cost of all construction works and the total cost budget (budget amount) based on the budget amount for each construction work and the total amount of the estimated cost for each construction work shown in Fig. 15(d), and calculates the range considered normal.

[0086] Specifically, as shown in Fig. 19(a), the determination unit 24 calculates the distance (Mahalanobis distance) from the center point to each point in the above-mentioned population. Then, as shown in the formula of "a(x)=(x-μ) 2 ÷δ 2 =((x-μ)÷δ) 2 " in Fig. 19(b), the determination unit 24 fits the distance for each point to the normal distribution with the distance as an element, and determines the construction work that does not meet the range of "the significance level 0.05 of the anomaly determination method of the automatic anomaly detection method data" as the construction work with an abnormal estimated cost recorded.

[0087] The memory control unit 25 stores and holds the data of the plot information for the normal range boundary line shown in Fig. 18 in the storage unit 2 in order to output the normal range. Specifically, the determination unit 24 obtains the points for the normal range boundary line based on the condition of "the significance level 0.05 of the anomaly determination method of the automatic anomaly detection method data".

[0088] In other words, for "x" and "μ", they are applied to the Mahalanobis distance calculation as two variables of the assumed cost and the total cost budget. The calculated Mahalanobis distance is fitted to a normal distribution as shown in the formula of Fig. 19(b), and the construction work that does not meet the range of the significance level of 0.05 is determined as the construction work with an abnormal assumed cost recorded.

[0089] To explain in more detail, as shown in Fig. 62, the storage unit 2 stores automatic anomaly detection method data including the detection ID, method, usage example, reference value, comparison value, and anomaly determination method. In the case of this example, the determination unit 24 refers to the record of the "Hotelling method" of this automatic anomaly detection method data based on the detection ID, detects that the significance level is set to "0.05", and as described above, determines the construction work that does not meet the range of the significance level of 0.05 as the construction work with an abnormal assumed cost recorded.

[0090] Next, as shown in Fig. 20(a), the memory control unit 25 updates the anomaly determination result (whether it is an anomaly result) included in the anomaly determination result data of the construction work determined to be abnormal stored in the storage unit 2 to "True (anomaly exists)". Also, as shown in Fig. 20(b), the memory control unit 25 stores in the storage unit 2 the anomaly determination result message data including a message of an assumed cost alert such as "Construction work A has been detected". This message is displayed on the analysis screen described later.

[0091] In addition, the memory control unit 25 inputs the detection ID of the above-mentioned automatic detection execution schedule data (see Fig. 13(a)) to the anomaly determination result message detailed data shown in Fig. 20(c) and the anomaly determination result attached information data shown in Fig. 20(d), respectively.

[0092] (When the rule-based method is set) Next, when the "rule-based method" is set as the anomaly detection method using the automatic anomaly detection data shown in FIG. 13(c), the acquisition unit 22 acquires the construction data shown in FIG. 21(a), the construction cost data shown in FIG. 21(b), and the construction order data shown in FIG. 21(c) based on the acquisition criteria (accounting year and month and construction progress status are "completed") set as parameters as shown in FIG. 21(e).

[0093] Based on the construction cost data shown in FIG. 21(b), the memory control unit 25 inputs the estimated cost amount obtained by adding the estimated cost of materials and the estimated cost of outsourced work for Construction A in October 2022, which is the completion month of the construction, into the construction status data shown in FIG. 21(d).

[0094] Also, based on the construction order data shown in FIG. 21(c), the memory control unit 25 calculates the total amount of the order amounts for materials and outsourced work for Construction A in October 2022, which is the completion month of the construction, and calculates the total amount of the booked debt amounts for materials and outsourced work for Construction A in October 2022. Then, the memory control unit 25 calculates the outstanding order amount by subtracting the total amount of the booked debt amounts from the total amount of the order amounts (outstanding order amount = order amount - booked debt amount), and inputs it into the construction status data shown in FIG. 21(d).

[0095] Note that since labor costs and expenses are items related to salaries, no order amounts are incurred.

[0096] Next, the comparison unit 23 compares the two amounts as shown in FIGS. 22(a) and 22(b), with the outstanding order amount of Construction A in October 2022 input into the construction status data shown in FIG. 21(d) as the reference value and the estimated cost amount as the comparison target. FIG. 23 shows an example of this comparison result. The example in FIG. 23(a) is an example where the reference value, the outstanding order amount, and the comparison target, the estimated cost amount, are the same amount. The example in FIG. 23(b) is an example where the comparison target, the estimated cost amount, is larger than the reference value, the outstanding order amount. The example in FIG. 23(c) is an example where the comparison target, the estimated cost amount, is smaller than the reference value, the outstanding order amount.

[0097] Note that the example of FIG. 23 is an example of the condition "reference value > comparison target", but the comparison of the outstanding order amount and the assumed cost amount may be performed under the condition of "|reference value - comparison target| ≧ fixed value".

[0098] Next, in the case of the example shown in FIG. 22(b), the outstanding order amount (reference value) is 190,000 yen, the assumed cost amount (comparison target) is 170,000 yen, and the comparison target is smaller than the reference value. Since this indicates that the assumed cost is an abnormal value, the memory control unit 25 updates the abnormality determination result (whether it is an abnormal result) included in the abnormality determination result data of the construction work determined to be abnormal, which is stored in the memory unit 2, to "True (abnormality exists)" as shown in FIG. 24(a). In addition, the memory control unit 25 inputs the detection ID of the above-described automatic detection execution schedule data (see FIG. 13(a)) to the abnormality determination result message data shown in FIG. 24(b) and the abnormality determination result message detail data shown in FIG. 24(c), respectively.

[0099] (Display process of analysis screen) (When using the Hotelling method) Next, the process of displaying the detected abnormal data and the data related to the abnormal data on the analysis screen will be described. Note that the following example is an example of the display process of the analysis screen when abnormality detection is performed by the Hotelling method.

[0100] First, the acquisition unit 22 refers to the abnormality determination result data as shown in FIG. 25(b) to acquire the abnormality determination result of "True" and the JOBID (job ID) of "assumed cost alert". The memory control unit 25 sets the acquired abnormality determination result of "True" and the JOBID (job ID) of "assumed cost alert" to the parameters shown in FIG. 25(a). Note that in order to display a list of alerts for each construction work in which an abnormality in the assumed cost is detected, at this point, the detection ID is not acquired, and the setting of the detection ID for the parameters is not set.

[0101] Next, the acquisition unit 22 refers to the abnormality determination result message data shown in FIG. 25(c) and acquires the degree of abnormality, definition name, outline, and detection target. As shown in FIG. 25(e), the display control unit 21 generates message data for display on the analysis screen, including the acquired degree of abnormality, definition name, outline, and detection target. Then, the display control unit 21 displays a list of per-construction messages indicating that an abnormality has occurred, including the degree of abnormality, definition name, outline, and detection target, in area R2 of the analysis screen shown in FIG. 26. Note that the abnormality determination result message detail data shown in FIG. 25(d) is referred to when the analysis detail screen is displayed later.

[0102] Next, as shown in FIG. 27(a), the operator acquires the date when the analysis screen was activated as the "reference date" and sets it in the "reference date" of the extraction condition in area R1 of the analysis screen as shown in FIG. 27(b).

[0103] (Display process of the analysis detail screen) Next, among the messages of each construction listed on the analysis screen, the operator selects the message of the construction for which details are to be confirmed and operates the display button. When this display button is operated, the acquisition unit 22 acquires each data of the business office, department, person in charge, construction name, construction type, and completion time from the abnormality determination result data shown in FIG. 28(a). Also, the acquisition unit 22 acquires the detection method (in this case, the Hotelling method) from the abnormality determination result message detail data shown in FIG. 28(b).

[0104] The display control unit 21 generates a detailed message shown in FIG. 28(c), including the acquired business office, department, person in charge, construction name, construction type, completion time, and detection method, together with the listed message, and displays this in area RS2 of the analysis detail screen shown in FIG. 29. Thereby, the detailed message corresponding to the construction corresponding to the message selected from the list on the analysis screen can be provided to the operator via the analysis detail screen.

[0105] Next, the operator inputs the extraction conditions for the acquisition range for collecting analysis data into the input field for the extraction conditions in area RS1 of FIG. 29. For example, as shown in FIGS. 30(a) and 30(b), if there are completed construction works between November 2021 and October 2022, the operator sets "accounting year and month" in the extraction condition column, sets "November 2021" in the FROM condition, and sets "October 2022" in the TO condition as the analysis data acquisition range conditions, as shown in FIG. 30(c). Thereby, the memory control unit 25 stores in the storage unit 2 the initial values of the extraction conditions with the reference date shown in FIG. 31(a) being "November 8, 2022", the period start being "November 2021", the period end being "October 2022", and the target construction being "Construction A". The display control unit 21 displays the reference date, accounting year and month, etc. set by the operator in area RS1 of the analysis details screen shown in FIG. 31(c) as shown in FIG. 31(b).

[0106] Next, the acquisition unit 22 refers to the construction data shown in FIG. 32(b) based on the parameter of the period start and the parameter of the period end shown in FIG. 32(a) set by the operator, and acquires the budget amount for each construction. Also, the acquisition unit 22 refers to the construction cost data shown in FIG. 32(c) via the construction name and completion time of the construction data shown in FIG. 32(b), and acquires the estimated cost amount for each construction. The memory control unit 25 inputs the budget amount for each construction acquired and the total amount of the estimated cost for each construction (total amount for each construction) into the construction-by-construction cost accounting status data stored in the storage unit 2 as shown in FIG. 32(d).

[0107] Furthermore, the acquisition unit 22 also acquires the normal range boundary line information by referring to the abnormal determination result attached information data shown in FIG. 33(b) based on the abnormal determination result data shown in FIG. 33(a) in order to display the above-mentioned normal range boundary line.

[0108] Next, the acquisition unit 22 refers to the construction data shown in FIG. 34(b) based on the parameters shown in FIG. 34(a) and acquires the completion time of each construction. The memory control unit 25 inputs the completion time for each cost item of each construction into the construction-by-cost-item construction status data shown in FIG. 34(e) stored in the memory unit 2. Also, the acquisition unit 22 refers to the construction cost data shown in FIG. 34(c) and acquires the future planned cost for each cost item at the end of the previous month, for example, in September 2022 (in the case of construction A), and the future planned cost for each cost item in the completion month of each construction, for example, in October 2022 (in the case of construction A). The memory control unit 25 inputs the future planned cost for each cost item in September 2022 into the planned cost at the end of the previous month of the construction-by-cost-item construction status data, and inputs the future planned cost for each cost item in October 2022 into the future planned cost of the construction-by-cost-item construction status data.

[0109] Also, the acquisition unit 22 acquires the generated cost amount for each cost item shown in FIG. 34(c). The memory control unit 25 inputs the acquired generated cost amount as the generated cost amount for each cost item of the construction-by-cost-item construction status data shown in FIG. 34(e). Also, the acquisition unit 22 acquires the estimated cost amount for each cost item shown in FIG. 34(c). The memory control unit 25 inputs the acquired estimated cost amount for each cost item as the estimated cost amount for each cost item of the construction-by-cost-item construction status data shown in FIG. 34(e).

[0110] Also, the acquisition unit 22 acquires the order amount and the debt accounting amount for each cost item of the material cost and the outsourced cost in the month before the completion month of each construction from the construction order data shown in FIG. 34(d). The memory control unit 25 generates the outstanding order amount of the material cost and the outsourced cost by subtracting the debt accounting amount from the order amount of each cost item of the material cost and the outsourced cost, and inputs this as the outstanding order amount of the material cost and the outsourced cost in the previous month of the construction-by-cost-item construction status data shown in FIG. 34(e).

[0111] Further, the acquisition unit 22 acquires the ordered amount and the debt accounting amount of each item of material cost and outsourcing cost in the completion month of each construction project from the construction order data shown in FIG. 34(d). The memory control unit 25 generates the outstanding order amount of the material cost and the outsourcing cost by subtracting the debt accounting amount from the ordered amount of each item of the material cost and the outsourcing cost, and inputs this as the outstanding order amount of the current month of the material cost and the outsourcing cost in the construction project-by-item cost-by-item construction status data shown in FIG. 34(e).

[0112] Next, the acquisition unit 22 acquires the material cost and the outsourcing cost that are the outstanding orders of the current month for each construction project from the construction project-by-item cost-by-item construction status data shown in FIG. 35(a) formed in this way. The memory control unit 25 inputs the total amount of the acquired material cost and outsourcing cost as the outstanding order amount of the current month in the construction project-by-project construction status data shown in FIG. 35(b). Further, the acquisition unit 22 acquires the future planned cost of each item for each construction project from the construction project-by-item cost-by-item construction status data shown in FIG. 35(a). The memory control unit 25 inputs the total amount of the acquired future planned cost of each item as the future planned cost in the construction project-by-project construction status data shown in FIG. 35(b).

[0113] Also, the acquisition unit 22 acquires the generated cost amount of each item for each construction project from the construction project-by-item cost-by-item construction status data shown in FIG. 35(a). The memory control unit 25 inputs the total amount of the acquired generated cost amount of each item as the generated cost amount in the construction project-by-project construction status data shown in FIG. 35(b). Further, the acquisition unit 22 acquires the assumed cost amount of the material cost and the outsourcing cost from the construction project-by-item cost-by-item construction status data shown in FIG. 35(a). The memory control unit 25 inputs the total amount of the acquired assumed cost amount of the material cost and the outsourcing cost as the assumed cost amount in the construction project-by-project construction status data shown in FIG. 35(b).

[0114] Next, the acquisition unit 22 refers to the abnormal determination result data shown in FIG. 36(b) based on the parameters shown in FIG. 36(a), and acquires the construction name (Construction A) and completion date (October 2022) of the construction in which an abnormal value of the assumed cost was detected (the abnormal result is True). Further, the acquisition unit 22 refers to the construction data shown in FIG. 36(c) based on the construction name and completion date acquired from the abnormal determination result data, and acquires the business office name, department, person in charge, and construction type. Furthermore, the acquisition unit 22 refers to the construction order data shown in FIG. 36(d) based on the construction name and completion date acquired from the abnormal determination result data, and acquires the supplier.

[0115] The memory control unit 25 inputs the business office name, department, person in charge, construction name, construction type, completion date, and supplier acquired by the acquisition unit 22 into the construction detail data shown in FIG. 36(e) stored in the memory unit 2.

[0116] Next, based on the data binding information shown in FIG. 37(a) stored in the memory unit 2, the display control unit 21 generates drawing data for a construction-by-construction cost recording status graph with the total cost budget on the X-axis and the assumed cost amount on the Y-axis as shown in FIG. 38. Further, the display control unit 21 generates drawing data for plotting points corresponding to the total cost budget and the assumed cost amount of each construction shown in FIG. 37(b) on this construction-by-construction cost recording status graph. Furthermore, based on the abnormal determination result attachment information data shown in FIG. 37(c), the display control unit 21 generates drawing data for displaying a normal range boundary line connecting points corresponding to the outline of the population of the plotted points. Then, drawing data for the construction-by-construction cost recording status graph illustrated in FIG. 38 is generated.

[0117] In addition, the acquisition unit 22 refers to the construction status data for each construction project of, for example, Construction Project A shown by the parameters in FIG. 39(a) (FIG. 39(c)), and acquires the outstanding order amount for the current month, the planned cost in the future, the incurred cost amount, and the estimated cost amount indicated by the data binding information in FIG. 39(b). The display control unit 21 generates drawing data for drawing the accounting status graph of Construction Project A illustrated in FIG. 39(d). Further, the display control unit 21 generates a bar graph of the outstanding order amount for the current month to be displayed on this accounting status graph based on the acquired outstanding order amount for the current month.

[0118] In addition, the display control unit 21 generates a bar graph of the planned cost in the future to be displayed on the accounting status graph based on the acquired planned cost in the future. Further, the display control unit 21 sets the incurred cost amount as the actual amount, and generates drawing data for a bar graph in a state where the estimated cost amount is placed at the tip of this incurred cost amount based on the acquired incurred cost amount and estimated cost amount.

[0119] Next, the acquisition unit 22 refers to the construction status data for each construction project and each cost item shown in FIG. 40(c) based on the parameters shown in FIG. 40(a) stored in the storage unit 2, and acquires the outstanding order amount for the previous month, the outstanding order amount for the current month, and the estimated cost amount corresponding to the material cost and the outsourced cost of each construction project. In addition, by referring to the construction status data for each construction project and each cost item shown in FIG. 40(c), the acquisition unit 22 acquires the planned cost at the end of the previous month, the planned cost in the future, and the incurred cost amount for each cost item of material cost, outsourced cost, labor cost, and overhead cost.

[0120] The display control unit 21 generates data for drawing the accounting status graph by cost item illustrated in FIG. 40(d). Further, based on the outstanding order amount for the previous month, the outstanding order amount for the current month, and the estimated cost amount of the acquired material cost, the display control unit 21 generates data for drawing a bar graph of the outstanding order amount for the previous month of material cost and outsourced cost, a bar graph of the planned cost in the future, and a bar graph in a state where the estimated cost amount is placed at the tip of the incurred cost amount.

[0121] Further, the display control unit 21 generates data for drawing a bar graph of the incurred cost amounts of labor costs and expenses, and a bar graph of the assumed cost amount, based on the previous month's outstanding order balance, the current month's outstanding order balance, and the assumed cost amount of the obtained material costs.

[0122] Next, the acquisition unit 22 refers to the work item-by-item work status data shown in FIG. 41(c) based on the data binding information shown in FIG. 41(b), and obtains the previous month's outstanding order balance, the current month's outstanding order balance, the planned cost at the end of the previous month, the planned cost in the future, the incurred cost amount, and the assumed cost amount corresponding to each item of material costs, outsourced costs, labor costs, and expenses for each work.

[0123] The display control unit 21 generates drawing data for displaying the "table for confirming the cost accumulation status at the completion time by work and cost classification" shown in FIG. 41(d). Further, the display control unit 21 is based on the previous month's outstanding order balance, the current month's outstanding order balance, the planned cost at the end of the previous month, the planned cost in the future, the incurred cost amount, and the assumed cost amount of the obtained material costs, and calculates the outstanding order balance of material costs, the expected landing amount of material costs, the actual amount of material costs, the assumed cost amount of material costs, the expected landing amount obtained by adding the actual amount of material costs and the assumed cost, and the percentage (%) of the expected landing amount with respect to the amount obtained by adding the actual amount of material costs and the assumed cost. Note that the obtained planned cost in the future is used as the expected landing amount.

[0124] Further, the display control unit 21 is based on the previous month's outstanding order balance, the current month's outstanding order balance, the planned cost at the end of the previous month, the planned cost in the future, the incurred cost amount, and the assumed cost amount of the obtained outsourced costs, and calculates the outstanding order balance of outsourced costs, the expected landing amount of outsourced costs, the actual amount of outsourced costs, the assumed cost amount of outsourced costs, the expected landing amount obtained by adding the actual amount of outsourced costs and the assumed cost, and the percentage (%) of the expected landing amount with respect to the amount obtained by adding the actual amount of outsourced costs and the assumed cost. Note that the obtained planned cost in the future is used as the expected landing amount.

[0125] In addition, based on the planned cost at the end of the previous month, the planned cost in the future, and the incurred cost amount of the labor cost obtained, the display control unit 21 generates data for drawing the landing prediction amount, the actual amount, and the ratio (%) of the landing prediction amount to the actual amount of the labor cost.

[0126] In addition, based on the planned cost at the end of the previous month, the planned cost in the future, and the incurred cost amount of the expenses obtained, the display control unit 21 generates data for drawing the landing prediction amount, the actual amount, and the ratio (%) of the landing prediction amount to the actual amount of the expenses.

[0127] In addition, the acquisition unit 22 refers to the construction detail data shown in FIG. 42(c) based on the parameters shown in FIG. 42(a), and acquires the business place name, department, construction name, construction type, completion time, and supplier. The display control unit 21 refers to the data binding information shown in FIG. 42(d), and generates drawing data for displaying the "table for outputting detailed information of the detected abnormal construction" shown in FIG. 42(d). In addition, the display control unit 21 generates drawing data for displaying the acquired business place name, department, construction name, construction type, completion time, and supplier on the table for outputting detailed information of the detected abnormal construction.

[0128] Next, the display control unit 21 displays the construction cost accounting status graph illustrated in FIG. 38 in the area RS3 of the analysis detailed screen shown in FIG. 43. In addition, the display control unit 21 displays the accounting status graph shown in FIG. 39(d) in the area RS4 of the analysis detailed screen shown in FIG. 43. In addition, the display control unit 21 displays the subject-by-subject accounting status graph shown in FIG. 40(d) in the area RS5 of the analysis detailed screen shown in FIG. 43.

[0129] In addition, the display control unit 21 displays the "table for checking the cost accumulation status at the completion time by construction work and cost classification" shown in FIG. 41(d) in the area RS6 of the analysis details screen shown in FIG. 43. Further, the display control unit 21 displays the "table for outputting detailed information on the construction work with detected abnormalities" shown in FIG. 42(d) in the area RS7 of the analysis details screen shown in FIG. 43. Thereby, it becomes possible to immediately recognize the detailed information on the construction work in which an abnormal value of the assumed cost has occurred, and the degree of abnormality (such as the amount).

[0130] (Change display of display form) Furthermore, the display control unit 21 displays the display forms of the plot points, bar graphs, etc. corresponding to the construction work with the assumed cost being an abnormal value in a different display form from other plot points or bar graphs, etc.

[0131] Specifically, the acquisition unit 22 refers to the graph coloring parameters shown in FIG. 44(a) stored in the storage unit 2, and acquires the display colors of the abnormality flags, the display colors of the reference information flags, and the display colors of the plot points and broken lines when the abnormality result of the abnormality determination result data shown in FIG. 44(c) is "True" and "False". The display control unit 21 displays the plot points of the construction work (True) in which an abnormal value is detected, for example, as red points, as shown in the construction work-by-construction cost accounting status graph in the area RS3 of FIG. 44(d), based on the acquired display colors.

[0132] In addition, the acquisition unit 22 refers to the graph coloring parameters (for assumed cost) shown in FIG. 44(b), and acquires various information indicating the color schemes, shades, and brightness and darkness of each bar graph such as the remaining order amount for the current month, the planned cost amount in the future, the actual amount, and the assumed cost amount. The display control unit 21 displays each bar graph of the accounting status graph in the area R4 of FIG. 44(d) and each bar graph of the subject-by-accounting status graph in the area RS5 of FIG. 44(d) in a display form corresponding to the acquired various information indicating the color scheme, shade, and brightness and darkness.

[0133] On such an analysis details screen, detailed information including the object detected as abnormal (such as the construction name), the detection method, and the reference value determined as abnormal can be displayed based on the message displayed in area RS2. Therefore, analysis can be performed starting from a state where a construction with a potential abnormality is known.

[0134] Also, in the cost accounting status graph for each construction displayed in area RS3, the correlation between the total cost budget and the assumed cost can be confirmed from the information of past completed constructions. As a premise of the correlation relationship in the Hotelling method, an analysis is performed using the feature that "constructions of the same scale tend to have similar cost occurrence trends (time, material quantity, number of arranged personnel, etc.), and the occurrence amounts of outstanding orders at the completion time are also often similar". Then, constructions that are clearly different from past trends are identified.

[0135] In the example of Fig. 44, it can be seen that the construction with the plotted points displayed in red has clearly deviated performance compared to other constructions (the assumed cost shows an abnormal value).

[0136] Note that even for population data for which the Hotelling method cannot be used, there are cases where features appear from the plotting of the data. That is, if there is a correlation relationship, the features will appear.

[0137] As shown in Fig. 45, the accounting status graph displayed in area RS4 enables confirmation of the cost status of the construction detected as abnormal. This accounting status graph can visualize the following information.

[0138] 1. Status of outstanding orders and assumed cost for the current month: Basically, these two tend to match, but if there is a shortage, it is possible that there is an accounting omission from the outstanding orders to the assumed cost. 2. Status of planned cost in the future and actual + assumed cost: Whether it is a planned performance as planned, or if the actual performance is greater than planned, it is possible that the cost has been overaccumulated or the plan is too optimistic and adjustment is required.

[0139] As shown in FIG. 46, the itemized status graph displayed in area RS5 can confirm the planned and actual status in terms of the breakdown unit of cost. Specifically, for material costs, operations such as emergency procurement or cost reallocation to other projects can be considered. For outsourcing costs, operations such as capital outflows to outsourcing suppliers and cost reallocation to other projects can be considered.

[0140] The graph of labor costs is confirmed in parallel with the status graph shown in FIG. 45. It is information related to the actual part when comparing with the planned cost in the future. Also, when cost operations are carried out by excluding labor costs, characteristics will appear in this graph of labor costs.

[0141] The graph of expenses is confirmed in parallel with the status graph shown in FIG. 45. It is information related to the actual part when comparing with the planned cost in the future. When costs such as improper transportation expenses or entertainment expenses are accumulated, characteristics will appear in this graph of expenses.

[0142] (When using the rule-based method) Next, the display process of the analysis screen when anomaly detection is performed using the rule-based method will be described. Also in this case, first, the acquisition unit 22 refers to the anomaly determination result data as shown in FIG. 47(b) to acquire the anomaly determination result of "True" and the JOBID (job ID) of "estimated cost alert". The storage control unit 25 sets the acquired anomaly determination result of "True" and the JOBID (job ID) of "estimated cost alert" to the parameters shown in FIG. 47(a). Note that in order to display a list of alerts for each construction project where an anomaly in the estimated cost is detected, at this point, the detection ID is not acquired, and the setting of the detection ID for the parameters is not set.

[0143] Next, the acquisition unit 22 refers to the abnormality determination result message data shown in FIG. 47(c) and acquires the degree of abnormality, definition name, outline, and detection target. As shown in FIG. 47(e), the display control unit 21 generates message data for display on the analysis screen, including the acquired degree of abnormality, definition name, outline, and detection target. Then, the display control unit 21 displays a list of per-construction messages indicating that an abnormality has occurred, including the degree of abnormality, definition name, outline, and detection target, in area R2 of the analysis screen shown in FIG. 47(f). Note that the abnormality determination result message detail data shown in FIG. 47(d) is referred to when the analysis detail screen described later is displayed.

[0144] Next, the operator acquires the date when the analysis screen was activated as the "reference date" and sets it in the "reference date" of the extraction conditions in area R1 of the analysis screen.

[0145] (Display process of the analysis detail screen) Next, among the messages of each construction listed on the analysis screen, the operator selects the message of the construction for which details are to be confirmed and operates the display button. When this display button is operated, the acquisition unit 22 acquires each data of the business office, department, person in charge, construction name, construction type, and completion time from the abnormality determination result data shown in FIG. 48(a). In addition, the acquisition unit 22 acquires the detection method (in this case, the rule-based method) from the abnormality determination result message detail data shown in FIG. 48(b).

[0146] The display control unit 21 generates a detailed message shown in FIG. 48(c), including the acquired business office, department, person in charge, construction name, construction type, completion time, and detection method, together with the list-displayed message, and displays this in area RS2 of the analysis detail screen shown in FIG. 49. Thereby, the detailed message corresponding to the construction corresponding to the message selected from the list on the analysis screen can be provided to the operator via the analysis detail screen.

[0147] The display processing of graphs and tables to be displayed in areas RS4 to RS7 shown in Fig. 50, and the change processing of the display forms such as plotted points and bar graphs when displaying the graphs and tables are the same as when an abnormality is detected by the above-mentioned hotelling method. Regarding area RS3, the presence or absence of plotting of the normal range boundary line is different. For details, refer to the description of Fig. 44 etc.

[0148] In the construction cost accounting status graph displayed in area RS3 of the analysis details screen in Fig. 50(d), based on the rule-based method, a construction project where the outstanding order amount and the assumed cost do not match can be detected as an abnormal construction project.

[0149] Also, in the construction cost accounting status graph displayed in area RS3 of the analysis details screen in Fig. 50(d), the correlation between the total cost budget and the assumed cost can be confirmed from the information of past completed construction projects. If there is a correlation between the assumed cost and the total cost budget and the abnormal data is an outlier (when there is a point plotted at a position away from the population), a characteristic appears here. Therefore, when a plot is confirmed at a position away from the population from the construction cost accounting status graph, abnormal detection by the above-mentioned hotelling method may be performed.

[0150] The accounting status graph displayed in area RS4 of the analysis details screen in Fig. 50(d) can confirm the information of the key for abnormal detection. Check how the assumed cost has not been accumulated with respect to the outstanding order.

[0151] In area RS4, for example, as shown in Fig. 51(a), construction projects where the assumed cost amount added to the actual amount is significantly less than the outstanding order amount for the current month are graphed as bar graphs and displayed as the construction projects to be detected.

[0152] When there is an obvious difference between the amount of outstanding orders considered as such and the estimated cost, it is easy to confirm. However, as shown in Fig. 51(b), when the difference between the amount of outstanding orders considered as such for the current month and the estimated cost amount is small, it becomes difficult to confirm whether the estimated cost is an abnormal value. In such a case, the "table for confirming the cost accumulation status at the completion time by construction and cost classification" displayed in area RS6 of the analysis details screen in Fig. 50(d) is used.

[0153] Fig. 52 is a diagram showing an example of this "table for confirming the cost accumulation status at the completion time by construction and cost classification". In the accounting status graph, even when the difference between the amount of outstanding orders considered as such for the current month and the estimated cost amount is small, in the "table for confirming the cost accumulation status at the completion time by construction and cost classification", for example, when the amount of outstanding orders considered as such for the current month is "80" while the estimated cost amount is "70", the difference between the two can be clearly confirmed numerically. Therefore, even a small abnormal value of the estimated cost can be easily detected.

[0154] (Switching of the graph for analysis) Next, the accounting management device of the embodiment can perform analysis by switching the display of the graph for analysis. That is, the operator can extract data under desired extraction conditions and confirm abnormal values of the estimated cost with data that is easier to confirm.

[0155] As an example, to explain an example of specifying the type of construction work, the operator specifies and inputs "construction work" as the type of construction work as shown in Fig. 53 to the input field for extraction conditions displayed in area RS1 of the analysis details screen. The memory control unit 25 sets "construction work" as the type of construction work of the parameters stored in the memory unit 2 as shown in Fig. 54(a).

[0156] As a result, the acquisition unit 22 acquires the budget amount for each construction project corresponding to "construction work" from the construction data shown in Fig. 54(b), and also acquires the estimated cost amount for each construction project from the construction cost data shown in Fig. 54(c). As shown in Fig. 54(d), the memory control unit 25 inputs the acquired budget amount for each construction project (total cost budget) and the total amount of the estimated cost for each construction project into the construction cost accounting status data stored in the memory unit 2. The various data acquired from the construction data and the construction cost data, and the various data stored in the construction cost accounting status data are used for the display of the "table for confirming the cost accumulation status at the completion time by construction and cost classification" displayed in the area RS6 of the analysis details screen in Fig. 50(d).

[0157] Also, as shown in Fig. 55(a), the acquisition unit 22 refers to the construction data shown in Fig. 55(b) based on the parameter in which "building construction" is set as the construction type, and acquires the completion time of each construction project. The memory control unit 25 inputs the completion time for each cost item of each construction project into the construction project-by-cost-item construction status data shown in Fig. 55(e) stored in the memory unit 2. Also, the acquisition unit 22 refers to the construction cost data shown in Fig. 55(c), and acquires the future planned cost for each cost item at the end of the previous month, for example, in September 2022 (in the case of construction project A), and the future planned cost for each cost item in the completion month of each construction project, for example, in October 2022 (in the case of construction project A). The memory control unit 25 inputs the future planned cost for each cost item in September 2022 into the planned cost at the end of the previous month of the construction project-by-cost-item construction status data shown in Fig. 55(e), and inputs the future planned cost for each cost item in October 2022 into the future planned cost of the construction project-by-cost-item construction status data.

[0158] In addition, the acquisition unit 22 acquires the generated cost amount for each cost item from the construction cost data shown in FIG. 55(c). The memory control unit 25 inputs the acquired generated cost amount as the generated cost amount for each cost item in the construction item-by-cost item construction status data shown in FIG. 55(e). Further, the acquisition unit 22 acquires the estimated cost amount for each cost item from the construction cost data shown in FIG. 55(c). The memory control unit 25 inputs the acquired estimated cost amount for each cost item as the estimated cost amount for each cost item in the construction item-by-cost item construction status data shown in FIG. 55(e).

[0159] In addition, the acquisition unit 22 acquires the order amount and the debt accounting amount for each cost item of material cost and outsourced cost in the month before the completion month of each construction from the construction order data shown in FIG. 55(d). The memory control unit 25 generates the outstanding order amount of material cost and outsourced cost by subtracting the debt accounting amount from the order amount of each cost item of material cost and outsourced cost, and inputs this as the outstanding order amount of the previous month of material cost and outsourced cost in the construction item-by-cost item construction status data shown in FIG. 55(e).

[0160] In addition, the acquisition unit 22 acquires the order amount and the debt accounting amount for each cost item of material cost and outsourced cost in the completion month of each construction from the construction order data shown in FIG. 55(d). The memory control unit 25 generates the outstanding order amount of material cost and outsourced cost by subtracting the debt accounting amount from the order amount of each cost item of material cost and outsourced cost, and inputs this as the outstanding order amount of the current month of material cost and outsourced cost in the construction item-by-cost item construction status data shown in FIG. 55(e). The construction item-by-cost item construction status data shown in FIG. 55(e) and the like are used for the display of the "table for confirming the cost accumulation status at the completion time by construction and cost classification" displayed in the area RS6 of the analysis details screen, the "table for outputting detailed information of the construction where an abnormality is detected" displayed in the area RS7, and the display of the account-by-account accounting status graph displayed in the area RS5.

[0161] Even when the extraction conditions are changed, as shown in FIGS. 56(a) to 56(d), the display processing of the graphs and tables displayed in areas RS3 to RS7, and the change processing of the display forms such as the plotted points and bar graphs when displaying the graphs and tables are as described above. For details, refer to the description of FIG. 44 and the like.

[0162] As shown in Fig. 57(a), when there are a large number of points plotted on the cost recording status graph by construction type displayed in area RS3, it becomes difficult to detect construction works showing abnormal values of the assumed cost. In such a case, by specifying a construction type such as "building construction" as described above and extracting data, the number of points plotted on the cost recording status graph by construction type can be reduced as shown in Fig. 57(b), and it becomes possible to facilitate the detection of construction works showing abnormal values of the assumed cost.

[0163] Also, when there is information that can form clusters (groups) when classified by construction type, these can be visualized. The example in Fig. 57(b) is an example where two existing clusters (groups) are visualized. From this, it can be understood that the data used for the display of the cost recording status graph by construction type was not only one cluster (group) following a normal distribution. Also, it can be noticed that it cannot be detected by the Hotelling method. In this case, the anomaly detection method will be changed to a rule-based method to detect abnormal values of the assumed cost.

[0164] Note that cluster analysis may be performed in advance with parameters such as the construction type confirmed in this way, and analysis may be performed using the Hotelling method for each population of construction data.

[0165] (For cases where there is a high possibility that there is one or more (considering multiple) dense distributions of point groups whose condition for following a normal distribution or the condition serving as the key for cluster division is unknown) Next, if the key condition is known, the Hotelling method can be used for each cluster (group), but if the key condition is unknown, it becomes difficult to divide the cluster (group). In such a case, anomaly detection can be performed using the "local outlier factor method".

[0166] When using this "local outlier factor method", the operator sets the detection ID, method, columns to be used, reference value, comparison value, and anomaly determination method as automatic anomaly detection method data as shown in Fig. 58. As the "method", the "local outlier factor method" is set. As the "columns to be used", "estimated cost, budget amount" are set. As the "anomaly determination method", "number of neighbors = 2, threshold value = 1.5" is set. The memory control unit 25 stores this automatic anomaly detection method data in the storage unit 2.

[0167] The "number of neighbors" is a value that specifies how many points with close distances are to be referred to from each point. For example, when set as "number of neighbors = 2", in the example of Fig. 59, two points, point B and point C, are referred to as the neighboring points of point A.

[0168] Figs. 60(a) to 60(d) show the processing flow using the "local outlier factor method". First, the display control unit 21 calculates the local reachability density of each point. The "local reachability density" is the reciprocal of the average value of the reachability distances to each neighbor for a certain point, and the display control unit 21 calculates it based on the following formula.

[0169] lrd k (A)=1÷(((rd k (A,B))+(rd k (A,C))÷2)

[0170] "A" is the point itself, "B" is the first neighboring point (the point closest to A), and "C" is the second neighboring point (the second closest point to A). "rd" is the distance, and "rd(A,B)" is the distance from A to B. Also, the "distance" means the "reachability distance".

[0171] Next, the display control unit 21 calculates the LOF (Local Outlier Factor). The "LOF" is the average value of the values obtained by dividing the local reachability densities of two neighboring points by their own local reachability density respectively. The memory control unit 25 stores the calculated LOF of each point in the storage unit 2 as the score value of each point as shown in Fig. 60(b).

[0172] Next, as shown in FIG. 60(c), the determination unit 24 detects (determines) as an abnormality a point having a LOF larger than “threshold value = 1.5” set in the “abnormality determination method” of the automatic abnormality detection method data shown in FIG. 58.

[0173] Next, as shown in FIG. 60(d), the memory control unit 25 inputs and stores the total cost budget and the assumed cost amount of the point where LOF = 1.5 in the “abnormality determination result attached information data” stored in the memory unit 2.

[0174] FIG. 61 is a diagram showing an example of drawing each point and the point where LOF = 1.5. By drawing the points in the “abnormality determination result attached information data”, a threshold line (normal range boundary line) can be drawn as shown by the dotted line in FIG. 61. Thereby, even when there are a plurality of populations, it is possible to easily detect a construction work in which the assumed cost corresponding to a point away from each population shows an abnormal value.

[0175] (Effect of the Embodiment) As is clear from the above description, the accounting management device 1 of the embodiment displays, in a specific display form, the assumed cost indicating an abnormal value detected based on the rule-based method on the accounting status graph as an example, and also displays, in a specific display form, the assumed cost indicating an abnormal value detected based on the hotelling method on the cost accounting status graph for each construction work. Thereby, the abnormal value of the assumed cost of the recorded construction work can be detected and displayed flexibly and with high accuracy according to the characteristics of each enterprise or construction work, and the operator can easily and quickly recognize the construction work in which the abnormal value of the assumed cost has occurred.

[0176] In addition, the accounting management device 1 of the embodiment pays attention to the correlation between the total cost budget and the assumed cost, calculates on the system side the range that can be regarded as the same category (between similar construction works), and detects as an abnormality the range outside this range that can be regarded as the same category (being out of the group) and notifies the operator (displays on the display unit). Thereby, the definition of the same category can be statistically determined on the system side (a definition with higher reliability than the methods used in market analysis etc. can be used), and the abnormal value of the assumed cost can be quickly detected.

[0177] In addition, the accounting management device 1 according to the embodiment compares the estimated costs between similar construction works and visually displays outliers. As a result, the validity of the general level of the estimated costs can be confirmed, and clearly abnormal values can be quickly detected.

[0178] In addition, the accounting management device 1 according to the embodiment visually displays information on the planned amount, outstanding orders, actual orders, and estimated costs classified by construction work and cost category. As a result, it becomes possible to compare the planned and actual amounts of each cost and to compare the outstanding orders with the estimates on a single display screen. For this reason, it is possible to quickly confirm the presence or absence of abnormalities for each cost of each construction work and to narrow down the range of costs that may be abnormal.

[0179] [Contribution to the Sustainable Development Goals (SDGs) led by the United Nations] According to the present embodiment, it is possible to contribute to improving business efficiency and making appropriate management decisions for the company, and thus it is possible to contribute to Goals 8 and 9 of the SDGs.

[0180] In addition, according to the present embodiment, it is possible to contribute to reducing waste loss and promoting paperless digitization, and thus it is possible to contribute to Goals 12, 13, and 15 of the SDGs.

[0181] In addition, according to the present embodiment, it is possible to contribute to strengthening control and governance, and thus it is possible to contribute to Goal 16 of the SDGs.

[0182] [Other Embodiments] The present invention may be implemented in various different embodiments within the scope of the technical idea described in the claims, in addition to the embodiments described above.

[0183] For example, among the processes described in the embodiment, all or part of the processes described as being automatically performed may be manually performed, or all or part of the processes described as being manually performed may be automatically performed by a known method.

[0184] In addition, the processing procedures, control procedures, specific names, information including parameters such as registered data and search conditions for each process, screen examples, and database configurations shown in this specification and the drawings can be arbitrarily changed unless otherwise specified.

[0185] Regarding the accounting management device 1, each of the illustrated components is a functional concept and does not necessarily need to be physically configured as shown in the figure.

[0186] For example, with respect to the processing functions provided by the accounting management device 1, particularly each processing function performed by the control unit 3 and the control unit 3, all or any part of them may be realized by a CPU (Central Processing Unit) and a program interpreted and executed by the CPU, or may be realized as hardware by wired logic. The program is recorded on a non-transitory computer-readable recording medium including programmed instructions for causing an information processing device to execute the processing described in this embodiment, and is mechanically read by the accounting management device 1 as necessary. That is, in a storage unit such as a ROM or an HDD, a computer program for giving instructions to the CPU in cooperation with the OS to perform various processes is recorded. This computer program is executed by being loaded into the RAM and constitutes the control unit 3 in cooperation with the CPU.

[0187] In addition, the accounting management program of this accounting management device 1 may be stored in another server device connected to the accounting management device 1 via an arbitrary network, and all or part of it can be downloaded as necessary.

[0188] Further, an accounting management program for executing the processes described in this embodiment may be stored in a non-transitory computer-readable recording medium, or may be configured as a program product. Here, this "recording medium" includes any "portable physical medium" such as a memory card, a USB (Universal Serial Bus) memory, an SD (Secure Digital) card, a flexible disk, a magneto-optical disk, a ROM, an EPROM (Erasable Programmable Read Only Memory), an EEPROM (registered trademark) (Electrically Erasable and Programmable Read Only Memory), a CD-ROM (Compact Disk Read Only Memory), an MO (Magneto-Optical Disk), a DVD (Digital Versatile Disk), and a Blu-ray (registered trademark) Disc.

[0189] Also, the "program" is a data processing method described in any language or description method, and is not limited to a form such as source code or binary code. Note that the "program" is not necessarily limited to being configured singly, and also includes those that are distributedly configured as a plurality of modules or libraries, or those that achieve their functions in cooperation with another program represented by an OS. Regarding the specific configuration, reading procedure, and installation procedure after reading for reading the recording medium in the accounting management device 1 shown in the embodiment, well-known configurations and procedures can be used.

[0190] The storage unit 2 is a storage means such as a memory device such as a RAM or a ROM, a fixed disk device such as a hard disk, a flexible disk, and an optical disk, and stores various programs, tables, databases, and web page files used for various processes and website provision.

[0191] Further, the accounting management device 1 may be configured by an information processing device such as a known personal computer device or a workstation, or may be configured by an information processing device to which an arbitrary peripheral device is connected. Further, the information processing device may be realized by implementing software (including programs or data, etc.) for realizing the processing described in the present embodiment.

[0192] Furthermore, the specific forms of the distribution and integration of the devices are not limited to those illustrated, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various additions or according to the functional load. That is, the above-described embodiments may be arbitrarily combined and implemented, or the embodiments may be selectively implemented.

Industrial Applicability

[0193] The present invention is suitable for application to, for example, the accounting operations of the construction industry.

Explanation of Signs

[0194] 1 Accounting management device 2 Storage unit 3 Control unit 4 Communication interface unit 5 Input / output interface unit 6 Input device 7 Output device 21 Display control unit 22 Acquisition unit 23 Comparison unit 24 Determination unit 25 Storage control unit

Claims

1. An acquisition unit that acquires the outstanding order amount and the estimated cost when the work of a specified contract is completed; A comparison unit that compares the acquired outstanding order amount with the estimated cost; Based on the comparison result of the comparison unit, it is determined whether the correlation between the outstanding order amount and the estimated cost is outside the allowable range of a predetermined tendency or within the allowable range, and when the correlation between the outstanding order amount and the estimated cost is outside the allowable range of a predetermined tendency, a determination unit that determines the amount of the estimated cost as an abnormal amount; A display control unit that displays at least the accounting status graphs of the outstanding order amount and the estimated cost on a display unit, and displays the accounting status graph of the estimated cost determined as an abnormal amount by the determination unit in a display form different from that of the outstanding order amount; An accounting management device having the above.

2. The determination unit determines the amount of the estimated cost as an abnormal amount when the difference amount between the estimated cost and the outstanding order amount is more than a predetermined amount, or when the difference amount between the estimated cost and the outstanding order amount is less than a predetermined amount. The accounting management device according to claim 1, characterized by the above.

3. The acquisition unit acquires the outstanding order amount and the estimated cost by specified item; The display control unit displays an item-by-item status graph on the display unit, and displays the item-by-item status graph of the estimated cost of the item determined as an abnormal amount by the determination unit in a display form different from the item-by-item status graph of the outstanding order amount. The accounting management device according to claim 2, characterized by the above.

4. The acquisition unit acquires the budget amount and the estimated cost by work of the contract; When plotting points corresponding to the acquired budget amount and the estimated cost on a work-by-work cost accounting status graph with one coordinate axis as the budget amount and the other coordinate axis as the estimated cost, the determination unit determines the amount of the estimated cost corresponding to a point plotted more than a predetermined distance from the center point of the population of each point as an abnormal amount. The display control unit plots and displays points corresponding to the obtained budget amount and the assumed cost on a cost accounting status graph with one coordinate axis as the budget amount and the other coordinate axis as the assumed cost, and displays, in a display form different from other points, points plotted at a distance of a predetermined distance or more from the center point of the population, which are determined as abnormal amounts, on the cost accounting status graph by work. The accounting management device according to claim 3, characterized in that.

5. The display control unit displays, on the cost accounting status graph by work, a normal range boundary line connecting the points plotted at positions corresponding to the contour of the population. The accounting management device according to claim 4, characterized in that.

6. The acquisition unit acquires the amount for each predetermined cost item for each work of the contract. The display control unit displays, on the display unit, work-by-cost-item work status data indicating the amount for each predetermined cost item for each work of the contract. The accounting management device according to claim 5, characterized in that.

7. The display control unit displays, on the display unit, work detail data including the business office and the person in charge who performed the work of the contract for which the assumed cost amount was determined as an abnormal amount. The accounting management device according to claim 6, characterized in that.

8. An acquisition step in which an acquisition unit acquires an outstanding order balance and an assumed cost when the work of a predetermined contract is completed. A comparison step in which a comparison unit compares the acquired outstanding order balance with the assumed cost. A determination step in which a determination unit determines, based on the comparison result of the comparison step, whether the correlation between the outstanding order balance and the assumed cost is outside the allowable range of a predetermined trend or within the allowable range, and determines the amount of the assumed cost as an abnormal amount when the correlation between the outstanding order balance and the assumed cost is outside the allowable range of the predetermined trend. A display control step in which a display control unit displays, on the display unit, at least a graph of the accounting status of the outstanding order balance and the assumed cost, and displays, in a display form different from that of the outstanding order balance, the graph of the accounting status of the assumed cost determined as an abnormal amount in the determination step. An accounting management method having the above steps.

9. A computer is configured to include: An acquisition unit that acquires an outstanding order balance and an assumed cost when the work of a predetermined contract is completed. A comparison unit that compares the acquired outstanding order balance with the assumed cost. Based on the comparison result of the comparison unit, determine whether the correlation between the outstanding order amount and the assumed cost is outside the allowable range of a predetermined trend or within the allowable range. When the correlation between the outstanding order amount and the assumed cost is outside the allowable range of the predetermined trend, a determination unit that determines the amount of the assumed cost as an abnormal amount; A display control unit that causes at least the accounting status graphs of the outstanding order amount and the assumed cost to be displayed on a display unit, and causes the accounting status graph of the assumed cost determined as an abnormal amount by the determination unit to be displayed in a display form different from that of the outstanding order amount. Function as; An accounting management program characterized by the above.

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