JP2024024905A - Business improvement supporting system and business improvement supporting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a business improvement supporting system and so on which predicts and presents tasks of potential future problems or of the factors of potential future occurring problems just by entering a business flowchart of a survey target.

SOLUTION: A business improvement supporting system has means for acquiring each piece of task position information for multiple tasks consisting of a business flow chart of survey objects, and shape pattern classification discrimination means for discriminating a shape pattern classification for classifying the business flowchart shapes into multiple types of shape patterns, for the business flow of the survey objects based on the acquired each piece of task position information. The business improvement supporting system extracts task information corresponding to the shape pattern classification discriminated by the shape pattern classification discrimination means and presents it with reference to the database storing the task information indicating the occurred task and each discriminated shape pattern classification in association with each other for each of multiple business flow charts that have been analyzed in the past to determine shape pattern classification.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to technology for supporting business improvement, and in particular to a business improvement support system and method that predicts and presents problems that may occur in the future based on the shape pattern of a business flowchart, and the shape of a business flowchart. The present invention relates to a business improvement support system and a business improvement support method that present tasks that are likely to cause problem factors based on patterns.

Conventionally, in order to extract issues related to business and improve business, there has been a method of improving and analyzing business processes using business flowcharts that represent the flow of business consisting of multiple tasks (tasks) in chronological order. be. A work flowchart represents the work contents, work stages, workers, etc. of each task in chronological order, and can visualize the overall picture of the work, which is very useful for such analysis. For example, in Patent Document 1, a work flowchart and work problems are selected based on interview items for checking work-related problems and questionnaire sheet information that is the answer. Disclosed are inventions relating to a business flowchart creation method and creation system for creating a business flowchart in which the following are combined.

JP 2019-185272 Publication

Proposals for improvement measures based on the business flowchart must be made after comprehensively considering the work content, work stages, workers, etc. of each task in the business flowchart, and there is a part that relies on the experience and skills of experts such as consultants. is large. For example, an expert such as a consultant looks at a client company's business flowchart, discusses and analyzes the current issues facing the client company, and then develops improvement measures to improve the client company's business operations. Make suggestions. Specifically, experts such as consultants conduct a questionnaire survey of the workers or persons in charge of each task, compare the details of the task (work), the work stages, the previous and subsequent tasks, the workers, etc. Through trial and error, we identify issues and formulate reform and improvement plans to resolve them. In some cases, client companies may not be able to grasp the issues that are currently occurring.

Furthermore, among the proposed reforms and improvement plans, we consult with the client company and decide which ones are possible and how to respond, taking into account the client company's circumstances, such as the cost that can be spent on improvements and the time period that can be spent on improvements. The process involves defining what cannot be done and deciding on the final reform and improvement measures, which is extremely time-consuming and labor-intensive.
The method disclosed in the above-mentioned Patent Document 1 merely involves manually extracting problems as a questionnaire and presenting the extracted problems in association with a business flowchart. Furthermore, when modifying a work flowchart, the administrator has no choice but to proceed with the modification while consulting with employees, managers, etc. involved in the work.

The present invention has been made in view of this situation, and provides a business improvement support system and a business improvement support method that present problems that are predicted to occur based on the shape pattern of a business flowchart, and It is an object of the present invention to provide a business improvement support system and a business improvement support method that present tasks that are likely to cause problem factors as estimated cause tasks based on the shape pattern of a business flowchart.

The business improvement support system of the present invention is a business improvement support system that supports business improvement by analyzing a business flowchart representing the flow of business consisting of a plurality of tasks. Regarding tasks, a task position information acquisition means for acquiring position information of each task in the business flowchart, and a shape pattern classification for classifying the shape of the business flowchart into a plurality of types of shape patterns, the task position information acquisition means a shape pattern classification determination means for determining the shape pattern classification of the business flowchart to be investigated based on the location information of each task acquired by the processor; For each, by referring to a task information database that stores task information indicating the problem that has occurred in association with each determined shape pattern classification, the problem corresponding to the shape pattern classification determined by the shape pattern classification discriminating means is determined. It is characterized by having a task information extraction means for extracting information, and a predicted task information presentation means for presenting the task information extracted by the task information extraction means as predicted task information, which is a task that is predicted to occur. shall be.

The business improvement support system of the present invention is a business improvement support system that supports business improvement by analyzing a business flowchart representing the flow of business consisting of a plurality of tasks. Regarding tasks, a task position information acquisition means for acquiring position information of each task in the business flowchart, and a shape pattern classification for classifying the shape of the business flowchart into a plurality of types of shape patterns, the task position information acquisition means a shape pattern classification determination means for determining the shape pattern classification of the business flowchart to be investigated based on the location information of each task acquired by the processor; For each, a shape pattern classification database is created that stores problem occurrence factor information, which includes location information in the business flowchart of the task that was the cause of the problem, as factor location information, in association with each determined shape pattern classification. problem occurrence factor information extracting means for referencing and extracting the problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification discriminating means; , a task in which the task corresponding to the factor location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means is presented as a presumed factor task that may be a factor in the occurrence of the problem. The invention is characterized by having a generation factor estimation means.

The database includes a condition information acquisition means for acquiring condition information indicating conditions related to business improvement, and the shape pattern classification database is configured to detect the occurrence of the problem for each of the plurality of business flowcharts that have been analyzed in the past and whose shape pattern classifications have been determined. In association with the cause information, the countermeasures implemented for the cause of the issue in order to solve the issue and the conditions necessary to implement the countermeasure are further stored as countermeasure history information. The factor information extraction means refers to the shape pattern classification database and extracts condition information acquired by the condition information acquisition means from among the problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determination means. The problem occurrence factor estimating means extracts the problem occurrence factor information associated with the countermeasure history information including the conditions that match the problem, and extracts the problem occurrence factor information that is associated with the countermeasure history information including the conditions that match the problem occurrence factor. The task is configured to present the task corresponding to the cause location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means as a presumed cause task that may be a cause of the problem occurrence. Good too.

The problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determining means with reference to the shape pattern classification database includes conditions that match the condition information acquired by the condition information acquisition means. The problem occurrence factor estimation means includes a countermeasure history information extraction means for extracting countermeasure history information, and the problem occurrence factor estimation means extracts the problem occurrence factor information extraction means from among the plurality of tasks constituting the business flowchart that is the subject of the investigation. The task corresponding to the factor location information included in the problem occurrence factor information that has been extracted is presented as an estimated factor task that may be a factor in the problem occurrence, and further, the countermeasure history information extraction means extracts the task. The configuration may be such that countermeasures are presented based on countermeasure history information.

The problem occurrence factor estimation means calculates the cause location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means among the plurality of tasks constituting the business flowchart that is the investigation target. The task corresponding to the task may be presented as the estimated factor task on the business flowchart to be investigated.

The business improvement support method of the present invention is a business improvement support method that supports business improvement by analyzing a business flowchart representing the flow of business consisting of a plurality of tasks. Regarding tasks, a task position information acquisition step of acquiring position information of each task in the business flowchart, and a shape pattern classification that classifies the shape of the business flowchart into a plurality of types of shape patterns, the task position information acquisition step a shape pattern classification determination step of determining the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired in the step; For each, by referring to a task information database that stores task information indicating the problem that has occurred in association with each determined shape pattern classification, the problem corresponding to the shape pattern classification determined in the shape pattern classification determination step is determined. The present invention is characterized by comprising a task information extraction step of extracting information, and a predicted task information presentation step of presenting the task information extracted in the task information extraction step as predicted task information, which is a task that is predicted to occur. do.

The business improvement support method of the present invention is a business improvement support method that supports business improvement by analyzing a business flowchart representing the flow of business consisting of a plurality of tasks. Regarding tasks, a task position information acquisition step of acquiring position information of each task in the business flowchart, and a shape pattern classification that classifies the shape of the business flowchart into a plurality of types of shape patterns, the task position information acquisition step a shape pattern classification determination step of determining the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired in the step; For each, a shape pattern classification database is created that stores problem occurrence factor information, which includes location information in the business flowchart of the task that was the cause of the problem, as factor location information, in association with each determined shape pattern classification. a problem occurrence factor information extraction step of referencing and extracting the problem occurrence factor information corresponding to the shape pattern classification determined in the shape pattern classification determination step; , problem occurrence in which the task corresponding to the factor location information included in the problem occurrence factor information extracted in the problem occurrence factor information extraction step is presented as a presumed factor task that may be a factor in the issue occurrence; The method is characterized by comprising a factor estimation step.

According to the business improvement support system or business improvement support method of the present invention that presents predicted problem information that is a problem that is predicted to occur based on the shape pattern classification of the business flowchart, it is possible to predict problems from the business flowchart. , it can significantly reduce the analysis work by experts such as consultants, and contribute to increasing profits, increasing efficiency, and reducing management risks based on business improvements for client companies, including those that are unaware of issues.
According to the business improvement support system or business improvement support method of the present invention, which presents estimated factor tasks that are tasks that are likely to cause problem factors based on the shape pattern classification of the business flowchart, a plurality of tasks constituting the business flowchart are presented. It is possible to present the estimated factor task from among the tasks, which can significantly reduce the analysis work by experts such as consultants, and contribute to increasing profits, increasing efficiency, reducing management risk, etc. based on business improvement of client companies. can.

1 is a schematic diagram showing a configuration example of a business improvement support system S in this embodiment. This is an example of a business flowchart. It is a schematic diagram in which each task of a business flowchart is defined on an xy plane. FIG. 3 is a diagram showing an approximately linearized business flowchart. This is an example of approximate linearization of each of the business flowcharts 101 to 106. 7 is a diagram illustrating an example in which each of the business flowcharts 101 to 120 is approximated linearly to obtain a slope at an arbitrary location. FIG. This is an example of a dendrogram. This is an example of an assignment information database (DB). This is an example of an assignment information database (DB). This is an example of a business flowchart analyzed in the past. This is an example of information registered in the first type DB of the shape pattern classification database (DB). This is an example of a business flowchart analyzed in the past. This is an example of information registered in the first type DB of the shape pattern classification database (DB). This is an example of a business flowchart analyzed in the past. This is an example of information registered in the first type DB of the shape pattern classification database (DB). 2 is a flowchart for explaining business improvement support processing by the control unit 11 of the business improvement support server 1. FIG. This is an example of an input screen for inputting a business flowchart to be investigated and extraction conditions. This is an example of a business flowchart and condition information to be investigated acquired in step S1. This is an example in which the factor location information included in the problem occurrence factor information extracted in step S4 is plotted on the xy plane. This is an example in which the business flowchart shown in FIG. 14 and the schematic diagram plotted in FIG. 15 are superimposed on the xy plane. This is an example in which estimated factor tasks are presented on a business flowchart. This is an example of a display screen of the display unit 13.

Embodiments of the present invention will be described with reference to the drawings. However, the embodiments described below are merely examples, and there is no intention to exclude the application of various modifications and techniques not specified below. That is, the present invention can be implemented with various modifications (such as combining the embodiments) as long as the effects are achieved. In addition, in the description of the drawings below, the same or similar parts are denoted by the same or similar symbols. The drawings are schematic and do not necessarily correspond to actual dimensions or proportions. The drawings may also include portions that differ in dimensional relationships and ratios. In addition, in order to avoid unnecessary redundancy in the following explanation and to facilitate understanding for those skilled in the art, detailed explanations of already well-known matters and duplicate explanations of substantially the same configurations are omitted. There is.

Embodiments of the present invention will be described.
The inventors have previously used business flowcharts, which represent the flow of business operations consisting of multiple tasks (work) in chronological order, to visualize the overall picture of business processes and improve business operations when supporting business improvement of customer companies. We have been formulating proposals for improvement. A work flowchart represents the work content, work stages, workers, etc. of each task in chronological order, and can visualize the overall picture of the work.
Based on the inventors' empirical rules, it has been found that there is a correlation between the shape of the business flowchart, the problem that actually occurred, and the position of the task that caused the problem to occur in the business flowchart. In other words, according to the inventors' empirical rules, the shape of the business flowchart is considered to be an important factor in determining the task and the task that causes the issue to occur.

Here, information related to previously analyzed business flowcharts (issue information, issue occurrence factor information, countermeasure history information, etc.) is accumulated and managed in the issue information database and shape pattern classification database for each shape pattern classification of the business flowchart. A business improvement support system S that can provide business improvement support by presenting problems that are predicted to occur with respect to a business flowchart to be investigated and estimated factor tasks that are estimated as factors for the occurrence of the problem will be described.

The business improvement support system S according to the present embodiment is a business improvement support system that supports business improvement by analyzing a business flowchart representing the flow of business consisting of a plurality of tasks. Regarding the task, a task position information acquisition means acquires position information of each task in the work flowchart, and a shape pattern classification classifies the shape of the work flowchart into a plurality of types of shape patterns, the task position information acquisition means comprises: A shape pattern classification determination means that determines the shape pattern classification of the business flowchart to be investigated based on the acquired position information of each task, and Task information extraction that extracts task information corresponding to the shape pattern classification determined by the shape pattern classification discriminator by referring to a task information database that stores task information indicating a task in association with each determined shape pattern classification. and predicted task information presentation means for presenting the task information extracted by the task information extraction means as predicted task information that is a task predicted to occur.

FIG. 1 is a schematic diagram showing a configuration example of a business improvement support system S in this embodiment. The business improvement support system S includes a business improvement support server 1 and terminal devices 2A to 2D connected to the business improvement support server 1 via a network 100 so as to be able to exchange information.
A plurality of terminal devices 2A to 2D exist in the business improvement support system S and are configured of, for example, a personal computer, a smartphone, or a tablet computer that can access the business improvement support server 1 through the network 100. The users who operate the terminal devices 2A to 2D are, for example, experts such as consultants who have obtained permission from the business providing the business improvement support system S, and they operate the business through the web browser etc. on the terminal devices 2A to 2D. By accessing the improvement support server 1, the control unit 11 of the business improvement support server 1 receives execution instructions for each step through workflow control, and executes the process. Note that the business improvement support system S may be configured such that a customer company or the like that has obtained permission from the system provider who is setting up the business improvement support system S operates the terminal devices 2A to 2D to utilize the business improvement support system S.

Next, the business flowchart will be explained. There are multiple notations for business flowcharts, one of which is BPMN (Business Process Model and Notation) developed by the international standards organization OMG. BPMN is a flowchart method that models the steps of a business process from beginning to end, and this embodiment will be described based on an example in which BPMN is adopted as the notation for business flowcharts.
However, the present invention can be applied to various notation methods for business flowcharts as long as information such as multiple tasks, branches, connections, etc. that are generally required to describe a business flowchart can be expressed, and the shape of the business flowchart can be analyzed. It is possible.

FIG. 2 shows an example of a business flowchart. In the example shown in the figure, the horizontal axis represents the passage of time, and the vertical axis represents workers and departments. The business flowchart 101 is composed of a plurality of tasks (works). The business flowchart 101 shown in the figure is composed of ten tasks (SEQ1 to SEQ10). Note that the shapes and meanings of objects such as tasks, branches, and connections in the business flowchart 101 are based on BPMN, so their explanations will be omitted.

The business improvement support server 1 is a device provided by a system provider who sets up the business improvement support system S. The business improvement support server 1 is a computer consisting of a CPU (Central Processing Unit) with arithmetic functions, a working RAM (Random Access Memory), a ROM (Read Only Memory) for storing various data and programs, a hard disk drive, etc. a control unit 11, a storage unit 12 equipped with a hard disk drive, etc., a display unit 13 equipped with a display screen such as a monitor, a control unit that receives instructions from a business operator that operates the business improvement support system S and sends instruction signals in accordance with the instructions. 11 (e.g., keyboard, mouse, operation panel (including touch panel), etc.) 14, communicates with terminal devices 2A to 2D, etc. via various networks (including LAN (Local Area Network)) The communication section 15 is configured to include a communication section 15 for communication. Each component is interconnected via a bus.
The control unit 11 realizes various functions by, for example, having a processor execute a program held in a memory. The processor may include an MPU (Micro Processing Unit), a CPU, a DSP (Digital Signal Processor), a GPU (Graphical Processing Unit), and the like.

The storage unit 12 stores a task information database (DB), a shape pattern classification database (DB), etc., and each database stores various information described later.
Although each means and each function of the control unit 11 is executed according to a program stored in a ROM or the like, they may be configured by independent devices, or may be configured by cloud computing. Furthermore, the storage unit 12 may be configured by a cloud service. Further, the functions of the business improvement support server 1 may be provided to the terminal devices 2A to 2D in a SaaS (Software as a Service) format.

The control unit 11 cooperates with other members to perform task position information acquisition means, shape pattern classification determination means, task information extraction means, predicted task information presentation means, task occurrence factor information extraction means, and task occurrence factor estimation according to the present invention. It functions as a means for acquiring conditions, a means for extracting countermeasure history information.

In the task information database (DB) of the storage unit 12, task information indicating issues that actually occurred when performing tasks according to the previously analyzed task flowcharts is stored in association with each shape pattern classification of the task flowcharts. has been done.

The shape pattern classification database (DB) in the storage unit 12 registers each piece of information in association with each shape pattern classification of the business flowcharts for previously analyzed business flowcharts. In this embodiment, the shape patterns of business flowcharts are classified into five types, ie, the first to fifth classes, and a database is provided for each classification of the shape patterns of business flowcharts. In this embodiment, a separate database is provided for each shape pattern classification of the business flowchart, but it is sufficient that each piece of information can be stored in association with the shape pattern classification of the business flowchart, for example, a single database may be used.

<Shape pattern classification>
Next, an example of a classification method for classifying business flowcharts into any number of shape patterns will be described.
<1> First, a business flowchart 101 in which the horizontal axis represents the passage of time and the vertical axis represents workers and departments can be defined on an xy plane with the horizontal axis as the x axis and the vertical axis as the y axis. The positional information (x, y) of the tasks on the xy plane is acquired for a plurality of tasks (works) constituting the business flowchart.

<2> FIG. 3 is a schematic diagram in which each task of the business flowchart 101 is defined on the xy plane. As shown in the figure, the position information (x, y) of each task in the business flowchart 101 shown in FIG. 2 is acquired as position information on the xy plane. In the example shown in the figure, illustrations other than tasks (SEQ1 to SEQ10), connection lines, and branches are omitted.

<3> Next, based on the position information (x, y) of each task on the xy plane of the workflow chart 101, the workflow chart 101 is defined as a scatter diagram on the xy plane, and this is approximately linearized. Then, the slope a (a at y=ax+b) at an arbitrary location is obtained. FIG. 4 is an example in which the business flowchart 101 shown in FIG. 2 is defined as a scatter diagram and approximated linearly.

The operations <1> to <3> described above are performed for a plurality of business flowcharts. FIG. 5 is a diagram showing an example in which operations <1> to <3> are performed on each of a plurality of business flowcharts 101 to 106 to approximate linearization, and FIG. FIG. 12 is a diagram showing an example of performing the operations <1> to <3> and performing approximate linearization to obtain a slope at an arbitrary location.

Next, the business flowcharts are classified (clustered).
FIG. 7 is a diagram showing an example of a dendrogram representing the hierarchical structure of the set of slopes shown in FIG. 6. By using a dendrogram, it is possible to visually recognize the hierarchical structure of a set and adjust the dissimilarity threshold for determining similarity.

The vertical axis in FIG. 7 represents the degree of difference, and the horizontal axis represents numbers representing the codes of the business flowcharts 101 to 120. By adjusting the threshold of the degree of difference on the vertical axis, the number of classifications (clustering) of the shape patterns of the business flowchart can be adjusted. FIG. 7 is an example in which the dissimilarity threshold is set between 15 and 20 (indicated by dotted lines) and the shapes of business flowcharts are classified (clustered) into five types.

Using the above method, the shapes in the xy plane are analyzed for a plurality of business flowcharts, and arbitrary several types of shape pattern classifications are determined.
In addition, in the <Business improvement support process> executed by the control unit 11, which will be described later, when determining the shape pattern classification of the business flowchart to be investigated, the processes in <1> to <3> and then classification (clustering) are used. , determine the shape pattern classification of the business flowchart to be investigated. Both processes are performed under the control of the control unit 11.

Note that since the shape of the business flowchart is analyzed based on the position information of the task, the multiple locations (for example, x value) where the slope a (a in y = ax + b) is obtained are the same in all business flowcharts to be analyzed. Preferably, it is a location.

In this embodiment, the shape of the business flowchart is analyzed using the method described above, but the method of analyzing the shape of the business flowchart is not limited to the above-mentioned method, as long as the shape pattern classification can be determined by analyzing the shape of the business flowchart. , other shape analysis methods may also be used.

<Registration to database>
<Assignment information database (DB)>
In the task information database (DB) of the storage unit 12, task information that actually occurred when performing work according to the work flowchart analyzed in the past is registered.
FIGS. 8A and 8B are examples of an assignment information database (DB). In the assignment information database (DB), assignment content "assignment content" and "assignment identification information" for uniquely identifying the assignment content are registered in association (Figure 8A). For each shape pattern classification of the business flowchart analyzed in , "task identification information" that identifies the "task content" that actually occurred when the business was executed according to the business flowchart is registered as task information (FIG. 8B).

In this embodiment, among the tasks that actually occurred, tasks whose occurrence probability is higher than a predetermined threshold value (for example, 50% or more) in each shape pattern classification are registered as task information. In the example of FIG. 8B, the tasks whose occurrence probability is equal to or higher than a predetermined threshold in a business flowchart whose shape pattern classification is type 1 are those whose "issue identification information" is Issue ID 1 and Issue ID 2, and whose "issue content" is quality and cost (Figure 8A). In this way, in association with the shape pattern classification, problems whose occurrence probability is equal to or greater than the predetermined threshold in the shape pattern classification are registered in association with each other.
Note that the predetermined threshold value can be changed as appropriate. For example, it is configured to be updated or changed to an appropriate value as the years pass.

<Shape pattern classification database (DB)>
The shape pattern classification database (DB) includes a database for each shape pattern classification of business flowcharts for business flowcharts analyzed in the past. As an example of the issue occurrence factor information, the cause of the issue that actually occurred, the task that caused the issue, and the location information of the task that caused the issue are registered, and countermeasure history information is also registered.

This will be explained using an example of a previously analyzed business flowchart shown in FIG. 9A. The business flowchart in Figure 9A is classified into the shape pattern classification "Type 1", the issue that actually occurred is "quality", and the tasks that caused the issue are "SEQ3" and "SEQ5". .

FIG. 9B is an example of information registered in the first type DB of the shape pattern classification database (DB) for the business flowchart of FIG. 9A.
In the example shown in the figure, as an example of issue occurrence factor information, the issue occurrence factor (base factor), the task that caused the cause, and the location information of the task that caused the cause as an example of the location information of the cause are registered in association with each other. . The base factors are, for example, the causes (factors) of the problem, such as difficulty in using tools, duplicate processes, lack of manuals, paper work, individualization, transcription work, etc.

Furthermore, in this embodiment, the deep factors that caused the base factors are analyzed, and the deep factors obtained as a result of the analysis are also registered in association with each base factor. Deep factors are the results of deeper analysis of basic factors, such as the number of people in the department who performed the task, average age, age deviation, presence or absence of a manual, results of comprehension training and tests, number of work branches, etc. This is a factor in

In the example of FIG. 9B, deep factor 1 and deep factor 2 obtained as a result of analysis are registered for base factor 1 that occurred in factor occurrence task "SEQ3" factor location information (x3, y3). Deep factor 3 and deep factor 4 obtained as a result of analysis are registered for base factor 2 that occurred in factor occurrence task "SEQ5" factor location information (x5, y5).

A deep factor that has a high causal relationship with the base factor may be selected and registered from a plurality of deep factors obtained as a result of the analysis. As a selection method, for example, a correlation coefficient indicating a correlation with a base factor is calculated, and a deep factor whose correlation coefficient is greater than or equal to a predetermined threshold is selected. Alternatively, the effects (effectiveness) of the measures actually taken may be analyzed, and deep factors for which the effectiveness is equal to or higher than a predetermined threshold may be selected. Any method may be used to calculate and analyze the correlation coefficient and effect (effectiveness) and is not particularly limited.

Furthermore, countermeasures actually implemented and conditions necessary for implementing the countermeasures are registered as countermeasure history information in association with problem occurrence factor information. The conditions necessary for implementing the countermeasure include, for example, the cost required for implementing the countermeasure, the period required for implementing the countermeasure, and the like.

In the example of FIG. 9B, countermeasure 1 and its condition 1, countermeasure 2 and its condition 2, countermeasure 3 and its condition 3 are registered as countermeasure history information in association with the issue occurrence factor information of base factor 1, and the countermeasure 1 and its condition 1 are registered as countermeasure history information. In association with the problem occurrence factor information of factor 2, countermeasure 4 and its conditions 4, countermeasures 5 and its conditions 5, countermeasures 6 and its conditions 6, countermeasures 7 and its conditions 7 are registered as countermeasure history information. Note that, as shown in the figure, when deep factors are registered, countermeasures and their conditions may be registered in association with each other for each deep factor.

Moreover, in the example of FIG. 9B, the effect (effectiveness) after implementing the countermeasure is further registered as countermeasure history information. For example, the effectiveness of each countermeasure against the actual cause of the problem is calculated and analyzed, and registered as an effect. For example, consultants work with client companies to confirm the progress of improvements and calculate and analyze their effectiveness. FIG. 9B is an example in which effectiveness is calculated on a scale of 100 points and registered as countermeasure history information. Although it is preferable to calculate and analyze the effectiveness for base factors, the effectiveness for base factors and the effectiveness for deep factors may be analyzed in detail, or either one of them may be used.

As explained above, a plurality of business flowcharts are analyzed and information is accumulated in the task information database (DB) and the shape pattern classification database (DB) for each shape pattern classification. Examples of other business flowcharts analyzed are shown in FIGS. 10A and 11A. FIG. 10B shows the information registered in the shape pattern classification database (DB) regarding the work flowchart of FIG. 10A, and FIG. 11B shows the information registered in the shape pattern classification database (DB) regarding the work flowchart of FIG. 11A.

The business flowchart in Figure 10A is classified into the shape pattern classification "Type 1", the issue that actually occurred is "quality", and the tasks that caused the issue are "SEQ4", "SEQ6", and " SEQ8”. The business flowchart in Figure 11A is classified into the shape pattern classification "Type 1", the issue that actually occurred is "cost", and the tasks that caused the issue are "SEQ5" and "SEQ7". .

In this embodiment, among the tasks that actually occur, tasks whose probability of occurrence is higher than a predetermined threshold in the shape pattern classification of the business flowchart are registered as task information in the task information database (DB) (FIG. 8B). Therefore, the contents of the tasks that actually occurred in the business flowcharts shown in FIGS. 9A, 10A, and 11A are used to calculate the probability of occurrence of the tasks registered in the task information database (DB). In this way, each time a business flowchart is analyzed, the probability of occurrence of a task is calculated, and the task information database (DB) is updated.

In the business flowcharts shown in FIGS. 9A, 10A, and 11A, the shape pattern classification is type 1, so the information (FIGS. 9B, 10B, and 11B) is all stored in the shape pattern classification database (DB). Registered in the Category 1 DB. The information registered in the first type DB of the shape pattern classification database (DB) is the same as the content detailed in FIG. 9B, so a detailed explanation will be omitted.
In this way, information is accumulated in all DBs (first class DB to fifth class DB) of the shape pattern classification database (DB) based on a plurality of business flowcharts.

<Business improvement support processing>
Next, occurrences are predicted for the business flowchart to be investigated, which is the target of business improvement support, based on information about previously analyzed business flowcharts accumulated in the issue information database (DB) and the shape/turn classification database (DB). A business improvement support procedure that presents issues and estimated factor tasks that are estimated to be the cause of the issue will be explained. FIG. 12 is a flowchart for explaining business improvement support processing by the control unit 11 of the business improvement support server 1. When execution of the processing program is instructed by a user's operation, a screen shown in FIG. 13 is displayed on the display screen of the display unit 13.

For example, when a user clicks (selects) the input selection button 30 on the display screen, a screen (not shown) for importing the business flowchart to be investigated as data opens, and the system is configured so that the business flowchart data can be input. Ru. Furthermore, extraction conditions for business improvement are input into the input frame 31 on the display screen by a user's operation. The extraction conditions are, for example, information such as the cost that can be spent on business improvement (budget condition) and the period that can be spent (period condition).

Then, when the input completion button 32 is clicked (selected), the control unit 11 acquires the input business flowchart, and further functions as a condition information acquisition means, and uses the input extraction conditions to improve the business process. is acquired as condition information indicating conditions related to (step S1). Note that when the close button 33 is clicked (selected), the input business flowchart and the extraction conditions input in the input frame 31 are deleted, and the state returns to the state before input.
FIG. 14 is an example of a business flowchart and condition information to be investigated, which the control unit 11 acquired in step S1.

Next, the business flowchart obtained in step S1 is analyzed to determine the shape pattern classification (step S2). First, the control unit 11 functions as a task position information acquisition means, and acquires position information of each task in the business flowchart acquired in step S1 for a plurality of tasks forming the business flowchart. Next, the control unit 11 functions as a shape pattern classification determination means, and determines the shape pattern classification of the business flowchart acquired in step S1 based on the position information of each task acquired by the task position information acquisition means.

According to the example shown in FIG. 14, position information is acquired for each of the plurality of tasks SEQ1 to SEQ8 forming the business flowchart to be investigated, and the shape pattern classification of the business flowchart is determined based on the position information. In the following description, a case where the shape pattern classification of the business flowchart shown in FIG. 14 is determined to be type 1 will be explained using FIGS. 8A to 11B as an example.

Next, the control unit 11 functions as a task information extraction means, refers to the task information database (DB) in the storage unit 12, and extracts task information corresponding to the shape pattern classification determined in step S2 (step S3). . For example, in the case of the work flowchart shown in FIG. 14, the task contents "quality" and "cost" are extracted in the example of the task information database (DB) shown in FIGS. 8A and 8B.

Next, the control unit 11 functions as a problem occurrence factor information extraction means, and extracts problem occurrence factor information based on the shape pattern classification determined in step S2 and the condition information acquired in step S1 (step S4). . Specifically, with reference to the shape pattern classification database (DB), countermeasures that include conditions that match the condition information acquired in step S1 among the problem occurrence factor information corresponding to the shape pattern classification determined in step S2 are determined. Extract issue cause information associated with history information.

For example, among the information registered in the first type DB of the shape pattern classification database (DB) shown in FIGS. 9B, 10B, and 11B, the condition information (budget condition, period condition) obtained in step S1 is matched. When an example of conditions is Condition 1, Condition 2, Condition 8, Condition 14, Condition 21, and Condition 26, problem occurrence factor information associated with countermeasure history information including these conditions is extracted. In FIGS. 9B, 10B, and 11B, examples of compatible conditions are clearly underlined.

Then, the control unit 11 functions as a predicted task information presenting means, and presents the task information extracted in step S3 as predicted task information (step S5). In addition, the control unit 11 functions as a problem occurrence factor estimation means, and based on the cause location information included in the problem occurrence factor information extracted in the problem occurrence factor information step S4, the control unit 11 determines the location of the corresponding work flowchart acquired in step S1. The task is presented as an estimated factor task that may be a factor in the occurrence of the issue (step S6).

FIG. 15 is an example in which the factor location information included in the task occurrence factor information extracted in step S4 is plotted on the xy plane. Specifically, the factor location information (x3, y3), (x5, y5) included in the issue occurrence factor information extracted from the information in FIG. 9B, and the factors included in the issue occurrence factor information extracted from the information in FIG. 10B. The location location information (x6, y6) and the factor location information (x5, y5) and (x7, y7) included in the task occurrence factor information extracted from the information in FIG. 11B were plotted on the xy plane.

FIG. 16 is an example in which the business flowchart to be investigated shown in FIG. 14 and the schematic diagram plotted in FIG. 15 are superimposed on the xy plane. Among the tasks constituting the business flowchart to be investigated, the task located at the position corresponding to the factor location information included in the issue occurrence factor information extracted in step S4 is presented as the estimated factor task (FIG. 17). FIG. 17 is an example in which estimated factor tasks are presented on a business flowchart to be investigated. In the example shown in the figure, "SEQ3", "SEQ4", and "SEQ5" are presented as estimated factor tasks.

Next, the control unit 11 functions as a countermeasure history information extracting means, and extracts countermeasure history information based on the problem occurrence factor information extracted in step S4 and the condition information acquired in step S1 (step S7). Specifically, with reference to the shape pattern classification database (DB), countermeasures that include conditions that match the condition information acquired in step S1 among the problem occurrence factor information corresponding to the shape pattern classification determined in step S2 are determined. Extract historical information. Then, based on the extracted countermeasure history information, a countermeasure is presented (step S8), and the process ends.

For example, among the information registered in the first type DB of the shape pattern classification database (DB) shown in FIGS. 9B, 10B, and 11B, an example of a condition that matches the condition information acquired in step S1 is condition 1. , condition 2, condition 8, condition 14, condition 21, and condition 26, countermeasure history information including these conditions is extracted in step S7, and countermeasure 1, countermeasure 2, countermeasure 8, and countermeasure included in this are extracted in step S8. 14, measures 21 and 26 are presented.

FIG. 18 is an example of the display screen of the display unit 13, and the figure shows an example in which predicted task information (step S5), estimated factor task (step S6), and countermeasures (step S8) are presented on the display screen. be. By displaying on one screen, you can understand at a glance predicted issues (quality, cost), estimated factor tasks (SEQ3, SEQ4, SEQ5) that may be the cause of the issue, and countermeasures. Can be done. Note that, as shown in the figure, the estimated factor tasks (SEQ3, SEQ4, SEQ5) may be associated with their factors (deep factors or base factors) and presented.

Furthermore, the Tobe model may be presented in step S8. The Tobe model analyzes the gap between the current situation and the Tobe (ideal) state, and indicates the issues to be addressed and an ideal model. For example, a newly created business flowchart may be presented taking into account the details of the countermeasures.

In the business improvement support system S according to the present embodiment, by simply inputting a business flowchart to be investigated, problems that may occur in the future (predicted problem information) are predicted and presented in the business to be executed according to the business flowchart, and further, We have described a configuration that presents tasks (estimated cause tasks) that may be a factor in the occurrence of a problem, and also presents countermeasures. The present invention is not limited to this configuration; for example, the present invention may not include any other configuration other than the configuration that presents predicted task information, and may not include any other configuration other than the configuration that presents the estimated factor task, for example. You can.

Alternatively, for example, predicted task information and/or estimated factor tasks may be presented based on a work flowchart, and an expert such as a consultant confirms the presented predicted task information and/or estimated factor tasks and uses the method described above. It may be used as material when considering countermeasures using other methods not available in the above.

Furthermore, it is not necessary to use the condition information acquired in step S1. For example, in step S4, task occurrence factor information is extracted based on the shape pattern classification determined in step S2, and in step S6, an estimated factor task is presented based on the factor location information included in the task occurrence factor information. may be configured. In this case, a larger number of estimated factor tasks will be presented than when narrowing down based on condition information, but experts such as consultants should check the presented estimated factor tasks and, for example, discuss them with the client company. It can also be used as analysis material for business improvement while taking into account the circumstances of the client company.

When constructing the business improvement support system S with a configuration that presents predicted task information, the task position information acquisition means, shape pattern classification determination means, task information extraction means, and predicted task information presentation means are essential components. In addition, when constructing the business improvement support system S in a configuration that presents estimated factor tasks, task position information acquisition means, shape pattern classification discrimination means, problem occurrence factor information extraction means, and problem occurrence factor estimation means are essential. It becomes the composition.

According to the business improvement support system S according to the present embodiment described above, by simply inputting a business flowchart to be investigated, problems that may occur in the future and causes of problems that may occur in the future can be identified in the business that will be executed based on the business flowchart. It is possible to predict and present tasks.

In this embodiment, in step S4, a shape pattern classification database (DB) is referred to, and among the problem occurrence factor information corresponding to the shape pattern classification determined in step S2, the condition information acquired in step S1 is used. Since issue occurrence factor information associated with countermeasure history information including matching conditions has been extracted, issues etc. can be presented in consideration of the customer company's circumstances.

Further, in this embodiment, in step S8, countermeasure history information including conditions that match the condition information acquired in step S1 is extracted, and countermeasures are presented based on the extracted countermeasure history information, so that the customer company's circumstances It is possible to present countermeasures that take into account.

The scope of application of the present invention is not limited to the embodiments described above. Although the business improvement support server 1 is configured to include each means included in the business improvement support system S of the present invention, it may be realized by a system in which a plurality of devices are configured to be mutually accessible.

1 Business improvement support server 11 Control unit 12 Storage unit 13 Display unit 14 Input unit 15 Communication unit 2A to 2D Terminal device

Claims (8)

In a business improvement support system that supports business improvement by analyzing business flowcharts that represent the flow of business consisting of multiple tasks,
task position information acquisition means for acquiring position information of each of the tasks in the business flowchart for a plurality of tasks constituting the business flowchart to be investigated;
Shape pattern classification for classifying the shape of a business flowchart into a plurality of types of shape patterns, the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired by the task position information acquisition means. a shape pattern classification determination means for determining the
For each of the plurality of business flowcharts that have been analyzed in the past and the shape pattern classifications have been determined, issue information indicating the issues that have occurred is stored in association with each determined shape pattern classification. task information extraction means for extracting the task information corresponding to the shape pattern classification determined by the shape pattern classification determination means;
Predicted task information presentation means for presenting the task information extracted by the task information extraction means as predicted task information that is a task that is predicted to occur;
A business improvement support system characterized by having the following. In a business improvement support system that supports business improvement by analyzing business flowcharts that represent the flow of business consisting of multiple tasks,
task position information acquisition means for acquiring position information of each of the tasks in the business flowchart for a plurality of tasks forming the business flowchart to be investigated;
Shape pattern classification for classifying the shape of a business flowchart into a plurality of types of shape patterns, the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired by the task position information acquisition means. a shape pattern classification determination means for determining the
For each of the multiple business flowcharts that have been analyzed in the past and the shape pattern classification determined, the issue occurrence factor information, which includes the location information in the business flowchart of the task that was the cause of the issue as the cause location information, was determined. problem occurrence factor information extraction means for extracting the problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determination means with reference to a shape pattern classification database stored in association with each shape pattern classification; ,
Among the plurality of tasks constituting the business flowchart to be investigated, the task corresponding to the cause location information included in the issue occurrence factor information extracted by the issue occurrence factor information extraction means is A means for estimating a task occurrence factor, which is presented as an estimated factor task that may be a factor;
A business improvement support system characterized by having. For each of the plurality of business flowcharts that have been analyzed in the past and the shape pattern classifications have been determined, issue cause information that includes the position information in the business flowchart of the task that was the cause of the problem that occurred as the cause location information is determined. problem occurrence factor information extraction means for extracting the problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determination means by referring to a shape pattern classification database stored in association with each shape pattern classification; and,
Among the plurality of tasks constituting the business flowchart to be investigated, the task corresponding to the cause location information included in the issue occurrence factor information extracted by the issue occurrence factor information extraction means is designated as an issue. A means for estimating a task occurrence factor, which is presented as an estimation factor task that may be a cause of the occurrence;
The business improvement support system according to claim 1, characterized by comprising: It has a condition information acquisition means for acquiring condition information indicating conditions related to business improvement,
The shape pattern classification database associates each of the plurality of business flowcharts whose shape pattern classifications have been analyzed in the past with the issue cause information, and identifies the cause of the issue in order to solve the issue. further memorize the countermeasures implemented and the conditions necessary to implement the countermeasures as countermeasure history information;
The problem occurrence factor information extraction means refers to the shape pattern classification database, and the condition information acquisition means acquires the problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determination means. Extracting the problem occurrence factor information associated with countermeasure history information including conditions that match the condition information,
The problem occurrence factor estimation means calculates the cause location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means among the plurality of tasks constituting the business flowchart that is the investigation target. 4. The business improvement support system according to claim 2 or 3, wherein the task corresponding to the problem is presented as an estimated factor task that may be a factor in the occurrence of the problem. The problem occurrence factor information corresponding to the shape pattern classification determined by the shape pattern classification determining means with reference to the shape pattern classification database includes conditions that match the condition information acquired by the condition information acquisition means. It has a countermeasure history information extraction means for extracting countermeasure history information,
The problem occurrence factor estimation means calculates the cause location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means among the plurality of tasks constituting the business flowchart that is the investigation target. The present invention is characterized by presenting the task corresponding to the issue as an estimated factor task that may be a factor in the occurrence of the problem, and further presenting a countermeasure based on the countermeasure history information extracted by the countermeasure history information extraction means. The business improvement support system according to claim 4. The problem occurrence factor estimation means calculates the cause location information included in the problem occurrence factor information extracted by the problem occurrence factor information extraction means among the plurality of tasks constituting the business flowchart that is the investigation target. 4. The business improvement support system according to claim 2, wherein the task corresponding to the task is presented as the estimated factor task on the business flowchart to be investigated. In a business improvement support method that supports business improvement by analyzing a business flowchart representing the flow of business consisting of multiple tasks,
a task position information acquisition step of acquiring position information of each of the tasks in the business flowchart for the plurality of tasks forming the business flowchart to be investigated;
Shape pattern classification for classifying the shape of a business flowchart into multiple types of shape patterns, the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired in the task position information acquisition step. a shape pattern classification discrimination step for determining the
For each of the plurality of business flowcharts that have been analyzed in the past and the shape pattern classifications have been determined, issue information indicating the issues that have occurred is stored in association with each determined shape pattern classification. a task information extraction step of extracting the task information corresponding to the shape pattern classification determined in the shape pattern classification determination step;
a predicted task information presentation step of presenting the task information extracted in the task information extraction step as predicted task information that is a task that is predicted to occur;
A business improvement support method characterized by having the following. In a business improvement support method that supports business improvement by analyzing a business flowchart representing the flow of business consisting of multiple tasks,
a task position information acquisition step of acquiring position information of each of the tasks in the business flowchart for the plurality of tasks forming the business flowchart to be investigated;
Shape pattern classification for classifying the shape of a business flowchart into multiple types of shape patterns, the shape pattern classification for the business flowchart to be investigated based on the position information of each task acquired in the task position information acquisition step. a shape pattern classification discrimination step for determining the
For each of the multiple business flowcharts that have been analyzed in the past and the shape pattern classification determined, the issue occurrence factor information, which includes the location information in the business flowchart of the task that was the cause of the issue as the cause location information, was determined. With reference to the shape pattern classification database (FIGS. 9B, 10B, and 11B) stored in association with each shape pattern classification, the problem occurrence factor information corresponding to the shape pattern classification determined in the shape pattern classification determination step is obtained. an issue occurrence factor information extraction step that extracts
Among the plurality of tasks constituting the business flowchart to be investigated, the task corresponding to the cause location information included in the issue occurrence factor information extracted in the issue occurrence factor information extraction step is A process of estimating the cause of the problem, presenting it as a task of estimating factors that may be the cause;
A business improvement support method characterized by having the following.

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