Business design support system

Abstract

To provide a device for proposing appropriate business measures according to a situation by reflecting a business environment that changes daily to evaluate an effect and a risk of a business design.SOLUTION: A current business reproduction device 101 includes a data acquisition unit 103 for acquiring business log data, a simulation unit 105 for creating virtual log data from a simulation using a current business scenario generated by the business log data, and a log accumulation and comparison unit 106 for comparing an accumulation and statistic value of the business log data with an accumulation and statistic value of the virtual log data to calculate difference (confidence level). A future scenario evaluation device 102 includes a simulation unit 111 for generating and performing a simulation model by using a future scenario created by considering a disturbance pattern or a measure pattern and the current business scenario, and a scenario evaluation unit 113 for calculating KPI from the simulation model, and evaluation the future scenario.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] This invention supports the design and improvement of various operations such as maintenance operations. Work This paper deals with business design support systems. [Background technology]

[0002] In recent years, the business environment has been changing rapidly, and various industries are required to review and improve their business design in accordance with the business environment. For example, in maintenance work for infrastructure, railways, industrial equipment, medical equipment, etc., it is necessary to continuously carry out maintenance such as inspection and repair for safe and stable operation of assets (facilities). In such maintenance, organizational structures and work standards are designed taking into consideration the operating status and operational characteristics of assets, and the status of maintenance resources such as workers and tools. However, when the business environment changes, it is necessary to take some kind of business measures and review the maintenance business design to suit the environment. A method for supporting the construction of such business measures is described in Patent Document 1.

[0003] Patent document 1 discloses a business policy construction support system having a business simulator unit that generates a virtual business history by running a simulation of service work performed by a service provider under specified business policies, an acquisition unit that acquires virtual business history corresponding to each business policy by having the business simulator unit run simulations sequentially under different business policies, and an output unit that, when an evaluation value calculated based on the virtual business history acquired by the acquisition unit satisfies specified conditions, outputs the business policy corresponding to the virtual business history in association with the evaluation value. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2017-208035 A Summary of the Invention [Problem to be solved by the invention]

[0005] As the business environment, including society, the environment, customers, and technology, changes rapidly, the key to the sustainable development of a company is to accurately grasp the daily changes in the situation and continue to flexibly transform the business. The above-mentioned Patent Document 1 describes a method for presenting good business measures by calculating an evaluation value through a business simulation that generates a virtual business history, but the virtual business history generated by the business simulation is not compared to the business history in the real world to see if it correctly reflects it, and there is little certainty that the evaluation value of the simulation is reliable. For this reason, Patent Document 1 was unable to reflect the daily changing real-world business in real time and ensure the reliability of the prediction.

[0006] The purpose of this invention is to evaluate the effectiveness and risks of business design by reflecting the ever-changing business environment, and to propose appropriate business measures according to the situation. Business design support system The purpose of this invention is to provide [Means for solving the problem]

[0007] In order to achieve the above object, one representative task design support system of the present invention comprises a current task reproduction device which reproduces a current task, and a future scenario evaluation device which evaluates a future scenario, the current task reproduction device comprises a data acquisition unit which acquires task log data relating to an actual task from a task system, a first simulation unit which performs a task simulation using a current task scenario generated from the task log data acquired by the data acquisition unit to generate virtual log data, and a log aggregation and comparison unit which aggregates and statistically processes the task log data and the virtual log data, compares the aggregated and statistical values ​​of the task log data with the aggregated and statistical values ​​of the virtual log data, and calculates a reliability which is a difference, and the future scenario evaluation device comprises a second simulation unit which generates a simulation model using a future scenario and the current task scenario generated in consideration of a disturbance pattern or a measure pattern, and a scenario evaluation unit which calculates a KPI (Key Performance Indicator) from the simulation model generated by the second simulation unit to evaluate the future scenario. The business design support system displays on the display unit the past KPI actual value calculated from the business log data, the reliability calculated by the log aggregation and comparison unit, the fluctuation range of the KPI due to the disturbance pattern, and the KPI predicted value of a future scenario of the policy pattern. It is characterized by: Effect of the Invention

[0008] According to the present invention, the effects and risks of business design are evaluated by reflecting the ever-changing business environment, and appropriate business measures according to the situation are proposed. Business design support system can be provided. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a functional block diagram of a business process design support system 100 according to a first embodiment of the present invention. [Figure 2A] FIG. 13 illustrates an example of an asset operation log. [Figure 2B] FIG. 13 is a diagram illustrating an example of a worker action log. [Figure 3A] FIG. 13 is a diagram illustrating an example of log data aggregated on a monthly basis. [Figure 3B] FIG. 13 is a diagram illustrating an example of log data aggregated on a weekly basis. [Figure 4A] FIG. 13 is a diagram illustrating an example of a case where log data is aggregated for each base location. [Figure 4B] FIG. 13 is a diagram showing an example of aggregating data by skill unit. [Diagram 5] FIG. 13 is a diagram showing an example of a screen for setting a disturbance pattern. [Figure 6] FIG. 13 is a diagram showing an example of a setting screen for a policy pattern. [Figure 7] FIG. 13 is a diagram illustrating an example of a KPI setting screen. [Figure 8] FIG. 13 is a diagram showing an example of an output screen of an evaluation result. [Figure 9] 4 is a flowchart showing the process of the current task reproduction device 101 according to the first embodiment of the present invention. [Figure 10] 4 is a flowchart showing the processing of the future scenario evaluation device 102 according to the first embodiment of the present invention. [Figure 11] FIG. 11 is a functional block diagram of a business process design support system according to a second embodiment of the present invention. [Figure 12] 10 is a flowchart showing the process of a current task reproduction device 101 according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In each embodiment, maintenance work will be described as an example of a business, but the business is not limited to this. Each embodiment can also be applied to other industries, such as financial services and transportation, manufacturing industries such as chemicals and automobiles, and agriculture.

[0011] The maintenance work includes various tasks such as inspection, repair, maintenance, etc. The assets that are the subject of the maintenance work include various items such as facilities, equipment, machinery, and products. EXAMPLES

[0012] 1 is a functional block diagram of a business process design support system 100 according to a first embodiment of the present invention. The first embodiment includes a current business process reproduction device 101, a future scenario evaluation device 102, a current scenario storage unit 109, and a display unit 114.

[0013] The current task reproducing device 101 comprises a data acquiring unit 103, a current task scenario generating unit 104, a simulation unit 105, and a log tallying and comparing unit 106. The current task reproducing device 101 generates a scenario in accordance with information on the actual task system, and reproduces the current task on a computer by simulation.

[0014] The data acquisition unit 103 acquires information about business from a business system 1000 in the real world. Examples of the information about business include information such as the model, design information, location, age, and number of assets registered in an asset management system, information such as employee attendance information, affiliation, qualifications held, and work logs registered in a business management system, and information such as asset operation logs, failure logs, event logs, and sensor data stored in an asset performance management system or a status monitoring system. The data acquisition unit acquires business data for a specified period at a specified timing and periodically. Examples of business systems include EAM (Enterprise Asset Management), APM (Asset Performance Management), and FSM (Field Service Management).

[0015] The current scenario generation unit 104 generates a scenario that defines the current state and conditions of a business operation based on the business log data acquired by the data acquisition unit 103. A scenario is composed of a wide variety of information, such as information on the personnel and organization that executes the business operation, information on assets related to the business operation, information on the systems that configure the business operation, and information on business processes related to the execution rules of the business operation. For example, in the case of a maintenance operation, the information is as follows:

[0016] The information on personnel and organizations that perform the operations includes information such as the organizational structure of the maintenance business company, the number and locations of service bases that perform maintenance, the number and skills of maintenance workers, the operations and assets in charge, and working hours. The information on assets related to the operations includes information such as the type and model of assets, functions, components, causal relationships between elements, failure modes, failure occurrence rates for each failure mode, the number of units installed, installation locations, and operation times. In addition, information such as the type and model of components, inventory numbers, production frequency, and production times is also included in the asset information. The information on the systems that construct the operations includes asset management systems, operation management systems, operation log systems, sensors, status monitoring systems, and IoT technologies such as predictive diagnosis and remote diagnosis, and includes information such as performance, introduction costs, operation costs, and the scope of assets and organizations to which the operations are applied. The information on the business process related to the execution rules of the operations includes information such as business classifications such as inspection and repair, frequency of occurrence of work, work hours, skills required for work, tools required for work, costs required for work, and travel time.

[0017] In this embodiment, a current situation scenario is generated from business log data acquired by the data acquisition unit 103, and by periodically generating and updating the current situation scenario based on the latest information at the time of acquisition, a simulation can be performed to reproduce the current business operations reflecting the latest business status.

[0018] The simulation unit 105 (first simulation unit) receives the scenario generated by the current scenario generation unit 104, generates a simulation model, and performs a business simulation to reproduce the current business on a computer. The calculation method of the simulation unit 105 is premised on the ability to output a virtual business log corresponding to a real-world business log. This can be realized, for example, by agent simulation.

[0019] In agent simulation, each character in the real world is represented by a model called an agent. For example, in the case of an agent simulation of maintenance work, asset data that corresponds to each asset in the simulation world is generated for each management unit such as real-world assets or asset parts, and these assets operate and break down autonomously to reproduce the behavior of the real-world assets. The data generated at this time is called an agent, and in the case of assets, it is called an asset agent.

[0020] Similarly, agents are also generated in the simulation world for each maintenance worker, and are called maintenance worker agents. These perform actions such as waiting, moving, performing tasks, and resting in response to work instructions. In addition, agents are generated that correspond to the characters involved in maintenance work in the real world, such as an operation agent that operates assets and requests troubleshooting when problems occur, an allocation agent that assigns work to maintenance workers, and a scheduler agent that determines the schedule for carrying out work.

[0021] At the start of the simulation, each agent is generated according to the input scenario, and each agent operates autonomously as the simulation time progresses, and the behavior of each agent is recorded as simulation log data. For example, in the asset agent, the operation start time, operation end time, time of failure, time of repair and recovery, inspection time, etc. are recorded as an asset operation log for each individual asset. Also, in the maintenance worker agent, the work start time, work end time, work content, work time, etc. are recorded as a maintenance worker work log for each maintenance worker. These virtual log data are output as the results of the simulation unit.

[0022] The log tallying and comparing unit 106 receives business log data related to actual business operations from among the data of the business system acquired by the above-mentioned data acquiring unit 103. The log tallying and comparing unit 106 also receives the above-mentioned virtual log data output by the simulation unit 105. Examples of actual business log data include asset operation logs and worker action logs.

[0023] Fig. 2A is a diagram showing an example of an asset operation log. Fig. 2B is a diagram showing an example of a worker action log. As shown in Fig. 2A, the asset operation log records the time history of the asset status, and is composed of information such as start time, end time, asset ID, asset type, and status. As shown in Fig. 2B, the worker action log records the action history of the worker, and is composed of information such as start time, end time, worker ID, affiliation, skill, work target asset ID, and work type.

[0024] The log tallying and comparing unit 106 compares the actual log data acquired from the business system 1000 with the virtual log data output by the simulation unit 105. However, since the log data as described above is not continuous data in time, it is not possible to simply compare data values ​​at the same time. Therefore, some kind of tallying and statistical processing is necessary. For example, asset operation logs from the current time to the past year are tallied, and the total time during which the asset was in a normal operating state is calculated and compared. In addition, the total working hours of workers from the current time to the past month are calculated and compared. In this way, the data to be tallied and statistically processed is not limited to one type. In addition, the period for tallying is not limited to one type.

[0025] Fig. 3A is a diagram showing an example of log data collected on a monthly basis. Fig. 3B is a diagram showing an example of log data collected on a weekly basis. In Fig. 3A and Fig. 3B, the horizontal axis shows time, and the vertical axis shows average work time.

[0026] In Figure 3A, the annual average value is shown with a dashed line, and the monthly average value is shown with a solid line. Looking at the difference between the dashed and solid lines, it is possible to grasp business characteristics such as busy times at the end of the term and seasonal fluctuations. In addition, in Figure 3B, the monthly average value is shown with a dashed line, and the weekly average value is shown with a solid line. Looking at the difference between the dashed and solid lines, it is possible to grasp business characteristics such as busy times at the end of the month. In this way, by compiling while changing the aggregation period or time interval, it is possible to grasp the characteristics of changes in business status over time.

[0027] In addition, when tabulating data, the data may be grouped by area or by affiliated organization, and then tabulated and statistically processed.

[0028] Fig. 4A is a diagram showing an example of log data collected by base unit. Fig. 4B is a diagram showing an example of log data collected by skill unit. In Fig. 4A and Fig. 4B, the horizontal axis shows group name, and the vertical axis shows average work time.

[0029] In Figure 4A, the average work time is calculated for each location. The overall average for all locations is also shown with a dashed line. Looking at the difference between the overall average and the average value for each location, we can see that locations B and D have work times that are higher than the overall average, while locations A and C have work times that are lower than the overall average. In this way, Figure 4A makes it possible to grasp the work characteristics of each location or area.

[0030] In Figure 4B, the average task time is calculated for each skill. The overall average for all skills is also shown with a dashed line. Looking at the difference between the overall average and the average value for each skill, skills C and D have task times that are higher than the overall average, while skills A and B have task times that are lower than the overall average. In this way, Figure 4B makes it possible to grasp the work characteristics of each skill. In this way, by changing the group to be tabulated, it is possible to grasp the work characteristics of each group. Note that grouping is not limited to that specified in advance in the scenario, and grouping may also be performed using machine learning clustering, etc.

[0031] The log tallying and comparing unit 106 further calculates the difference between the tallying and statistical values ​​of the actual log data from the business system 1000 and the tallying and statistical values ​​of the virtual log data output by the simulation unit 105. This difference is called "reliability". The smaller the reliability, the smaller the difference between the actual log data and the virtual log data of the simulation, and the higher the reliability of the simulation. The calculated reliability data is passed to the display unit 114 and displayed on the screen of the display unit 114. This allows the user to quantitatively grasp the degree to which the current simulation result is consistent with the actual business. As described above, there may be multiple methods of log tallying and statistical processing, and therefore there may be multiple reliability values.

[0032] The current scenario used in the simulation by the current task reproduction device 101 is stored in the current scenario storage unit 109 .

[0033] Next, a configuration of the future scenario evaluation device 102 that evaluates the future scenario will be described.

[0034] 1, the future scenario evaluation device 102 has a future scenario generation unit 110, a simulation unit 111 (second simulation unit), a KPI calculation unit 112, and a scenario evaluation unit 113. The future scenario evaluation device simulates future business conditions taking into account possible future disturbances and measures, calculates key performance indicators (KPIs) for the business or operations, and compares the KPIs under various scenario conditions to evaluate the pros and cons of the scenarios and provide information to support decisions on business strategies and changes to operation design.

[0035] The future scenario generating unit 110 acquires the current situation scenario stored in the current situation scenario storage unit 109. Using the acquired current situation scenario as a reference condition, the unit changes the conditions taking into account disturbances and measures that may be expected in the future, and generates a future scenario.

[0036] In the first embodiment, possible disturbances and measures are patterned in advance. Examples of possible disturbance patterns include natural disasters, epidemics, and cyber attacks.

[0037] Fig. 5 is a diagram showing an example of a screen for setting a disturbance pattern. In Fig. 5, a set of condition parameters that change for each pattern is prepared, and the fluctuation range of each condition parameter is set. In this way, by preparing a set of scenario condition parameters for each disturbance pattern, the effort of setting the condition parameters can be reduced.

[0038] In FIG. 5, in the natural disaster pattern, the affected site is specified as site A, the affected base is specified as SC1, the fluctuation range of the number of maintenance personnel is specified as -5 to 0, the fluctuation range of the travel time between the base and the site is specified as 0 to +100%, and the status monitoring system is specified as the stopped system as the influencing condition parameters. This is a condition setting assuming a situation in which the assets of site A stop simultaneously due to a natural disaster such as a typhoon, up to five maintenance personnel are put into a state of incapacity to work at the service base of SC1, the travel time between the base and the site is doubled up to the maximum, and the status monitoring system stops. Note that these multiple condition parameters may be varied individually or simultaneously, and the variation patterns are diverse even for the natural disaster pattern alone.

[0039] In addition, in the epidemic pattern, SC1 and SC5 are specified as affected bases, and the fluctuation range of the number of maintenance personnel is specified as -20 to 0. This is a condition setting that assumes a situation in which a maximum of 20 people are unable to work at each of the service bases of SC1 and SC5 due to the epidemic.

[0040] In addition, in the cyber attack pattern, Site A and Site B are specified as affected sites, SC1 and SC5 are specified as affected bases, and the predictive diagnosis system is specified as the stopped system. This is a condition setting that assumes that a cyber attack causes the predictive diagnosis systems for assets at Site A and Site B to stop, making it impossible to access information at the service bases of SC1 and SC5.

[0041] By independently varying the condition parameters of the various disturbance patterns described above, a large number of variable conditions can be generated. By adding these variable conditions to the current situation scenario, multiple future scenarios that include variations due to various disturbances can be generated.

[0042] As with disturbance patterns, future scenarios that consider multiple future measures are generated by adding condition changes based on measures to the current scenario. Examples of measure patterns include IoT measures to introduce new IoT solutions such as predictive diagnosis, repair recommendations, and remote diagnosis, organizational change measures to change the number and locations of service bases and the number of workers at each service base, and maintenance policy change measures to change regular inspection periods and part replacement periods. In addition, composite measures that combine multiple business measure patterns can also be considered as one measure. Here, a measure means changing the parameters of information that can be intentionally changed among various information held by a scenario. For example, a measure to increase maintenance staff can be said to change the number of maintenance staff to an increased value, and an IoT introduction measure can be said to change the number of IoT technologies such as predictive diagnosis to an increased value. Note that a change includes changing to the same value, and can be said to be a status quo maintenance measure that continues the state of maintenance work at a certain point in time. In addition, the number of items to be changed is not limited to one, and multiple items can be changed at the same time.

[0043] FIG. 6 is a diagram showing an example of a setting screen for a policy pattern. In the example of FIG. 6, three different business policy scenario screens for policy scenarios A, B, and C are opened, and different policy settings are made for each. In the example of FIG. 6, predictive diagnosis is selected as the IoT policy pattern for setting policy scenario C, and a false alarm rate of 10% and a false alarm rate of 3% are input as performance values, which are condition parameters. In addition, as the scope of application of predictive diagnosis, specification by area is selected, and predictive diagnosis is specified to be applied to assets at site A. In addition, change in the number of maintenance personnel is selected as the organizational change policy pattern, and the number of people to be changed is input as +3 people as the condition parameter. In addition, specification by SC is selected as the scope of service bases to which the change is to be made, and SC1 and SC5 are specified. In addition, change in regular inspection cycle is selected as the maintenance policy change policy pattern, and the target is specified as the A component inspection as the condition parameter, and the cycle is input as 6 months. In other words, policy scenario C in FIG. 6 is an example of a business policy scenario that combines three policy patterns.

[0044] A large number of future scenarios that take into account disturbance patterns and policy patterns generated by the above-mentioned method are input to a simulation unit 111. The simulation unit 111 generates a simulation model for each of the received large number of future scenarios, and performs a business simulation that reproduces business operations for each future scenario on a computer.

[0045] The KPI calculation unit 112 receives the output data (simulation model) of the simulation unit 111, and calculates a preset KPI.

[0046] FIG. 7 is a diagram showing an example of a KPI setting screen. In the example of FIG. 7, the KPI items include asset utilization rate, CO2 emissions, response time, cost of measures, maintenance cost, labor cost, overtime hours, work efficiency, and total work man-hours. For example, asset utilization rate can be calculated by statistically analyzing asset operation logs, which are simulation results. Overtime hours can be calculated by statistically analyzing maintenance staff work logs, which are simulation results. If asset utilization rate is selected as the KPI, it is possible to consider a business design that satisfies the guaranteed utilization rate value in a maintenance contract that guarantees utilization rate. If CO2 emissions are selected as the KPI, it is possible to consider a business design that contributes to a decarbonized society. If overtime hours are selected as the KPI, it is possible to consider a business design that corresponds to work style reform that reduces overtime hours.

[0047] The scenario evaluation unit 113 compares and evaluates the KPIs for each future scenario calculated by the KPI calculation unit 112. The evaluation results are passed to the display unit 114 and displayed on the user's screen.

[0048] Fig. 8 is a diagram showing an example of an output screen of the evaluation result. In the example of Fig. 8, the asset utilization rate is displayed as the KPI. The evaluation result is shown in a graph with the horizontal axis being time and the vertical axis being KPI.

[0049] The center of the horizontal axis represents the present time, with the actual KPI values ​​calculated from past performance log data shown as solid lines to the left of the present time, and the predicted results from simulation shown as dashed lines to the right of the present time. By showing the history of past KPI performance at the same time, it is possible to grasp the fluctuation trends of the KPI. The predicted results from simulation show in grey the range of KPI fluctuations when simulating a future scenario that takes into account the disturbance patterns described above. In other words, it shows that the KPI may fluctuate within the grey range due to disturbances assumed in advance, such as natural disasters, epidemics, and cyber attacks, and from these results it is possible to perform a risk assessment of the extent to which the KPI is at risk of fluctuating.

[0050] In addition, in the example of Fig. 8, the reliability value calculated by the log aggregation and comparison unit 106 is displayed as an error bar. By displaying the reliability, it is possible to evaluate and judge the results while taking into account the error range of the simulation results. The example of Fig. 8 shows two simulation results: a current scenario in which the current business design remains the same, and an evaluation of measure pattern A. This makes it possible to quantitatively grasp that measure pattern A has improved the KPI and also reduced the range of fluctuation due to disturbances, providing a basis for judging that measure pattern A is a good measure.

[0051] Next, the processing of the current task reproduction device and the processing of the future scenario evaluation device will be described with reference to Fig. 9 and Fig. 10. Fig. 9 is a flowchart showing the processing of the current task reproduction device 101 according to the first embodiment of the present invention. Fig. 10 is a flowchart showing the processing of the future scenario evaluation device 102 according to the first embodiment of the present invention.

[0052] In FIG. 10, the user designates the timing of data acquisition from the business system 1000 to the data acquisition unit 103 (step S201).

[0053] The data acquisition unit 103 determines whether or not it is time to acquire data in accordance with an instruction from the user (step S202).

[0054] When the acquisition timing designated by the user has arrived (Yes in step S202), the data acquisition unit 103 acquires data from the business system 1000 and passes the data to the current scenario generation unit 104 (step S203). When the acquisition timing designated by the user has not arrived (No in step S202), the data acquisition unit 103 repeats the process of step S202.

[0055] The current situation scenario generating unit 104 generates a current situation scenario based on the data acquired by the data acquiring unit 103, and passes it to the simulation unit 105 (step S204).

[0056] The simulation unit 105 executes a simulation based on the current scenario generated by the current scenario generating unit 104, and passes a virtual log to the log tallying and comparing unit 106 (step S205).

[0057] The log tallying and comparing unit 106 compares the virtual log obtained by the simulation unit 105 with the actual log of the business system 1000 obtained by the data obtaining unit 103, and calculates the difference (reliability) (step S207). The log tallying and comparing unit 106 passes the calculated reliability to the display unit 114.

[0058] The current task reproduction device 101 stores the current scenario used in the simulation in the current scenario storage unit 109 (step S208).

[0059] The display unit 114 outputs the KPI of the current situation reproduction simulation calculated by the future scenario evaluation device 102 (described later) and the reliability calculated by the log tallying and comparing unit 106 to the display unit 114 (step S209).

[0060] As shown in FIGS. 3A to 4B, the log tallying and comparing unit 106 calculates a plurality of reliability degrees by changing the period or time interval for tallying the business log data and the virtual log data.

[0061] Next, the processing of the future scenario evaluation device will be described with reference to FIG.

[0062] In FIG. 10, the user sets a disturbance pattern and a measure pattern in the future scenario generating unit 110 (step S301).

[0063] The future scenario generator 110 acquires the current scenario from the current scenario storage unit 109 (step S302).

[0064] If the generation of future scenarios for all patterns has not been completed (No in step S303), the future scenario generator 110 selects one of the disturbance pattern and the measure pattern (step S304).

[0065] The future scenario generating unit 110 generates a future scenario based on the current scenario acquired from the current scenario storage unit 109, adds changes in the policy pattern or disturbance pattern, and passes the future scenario to the simulation unit 111 (step S305).

[0066] The simulation unit 111 executes a simulation based on the future scenario generated by the future scenario generation unit 110, and passes the result to the KPI calculation unit 112 (step S306).

[0067] The KPI calculation unit 112 calculates the KPI of the future scenario based on the result of the simulation executed by the simulation unit 111, and passes it to the scenario evaluation unit 113 (step S307).

[0068] The scenario evaluation unit 113 stores the calculated KPIs of the future scenario in the storage unit, and notifies the future scenario generation unit 110 that storage has been completed (step S308).

[0069] The future scenario generator 110 judges whether the current situation scenario has been updated (step S309), and if the current situation scenario has not been updated (No in step S309), executes the process from step S304. In step S304, it selects a policy pattern and a disturbance pattern that have not been selected.

[0070] If the current scenario has been updated (Yes in step S309), the future scenario generator 110 executes the process from step S302.

[0071] When the future scenario generation unit 110 completes generation of future scenarios for all patterns in step S303, it notifies the scenario evaluation unit 113 of the completion. The scenario evaluation unit 113 evaluates the future scenarios for all patterns and outputs them to the display unit 114 (step S310).

[0072] The display unit 114 displays the reliability from the current task reproduction device 101 and the evaluation result of the future scenario.

[0073] In the first embodiment, the current task reproduction device 101, future scenario evaluation device 102, current scenario storage unit 109, and display unit 114 are configured inside the same task design support system 100, but they may also be configured on separate systems. For example, the current task reproduction device 101 may be configured as a server at a client site where the task system is located, the current scenario storage unit and future scenario evaluation device may be configured in the cloud, and the display unit may be configured in a user's local PC, and these may be connected via a network.

[0074] 9 and 10, the processing flow may be executed by the future scenario evaluation device 102 after the processing by the current task reproduction device 101, or each may execute the processing in parallel at the same time. When the processing is executed independently, the current task reproduction device 101 can cooperate with the business system 1000 in real time, regardless of the processing by the future scenario evaluation device 102.

[0075] According to the first embodiment, scenario evaluation by simulation that reflects information of the business system in real time becomes possible, and good policy decisions that take into account real business characteristics in the real world can be supported.

[0076] Moreover, according to the first embodiment, risk assessment can be performed taking into account disturbances such as natural disasters.

[0077] Furthermore, according to the first embodiment, it is possible to evaluate a scenario based on the prediction reliability and validity of the simulation. EXAMPLES

[0078] Next, a second embodiment of the present invention will be described. Fig. 11 is a functional block diagram of a business process design support system according to the second embodiment of the present invention. In the second embodiment, the same components as those in the first embodiment are denoted by the same reference numerals, and detailed descriptions thereof will be omitted.

[0079] In the second embodiment, a judgment unit 107 and a parameter adjustment unit 108 are added as components of the current task reproduction device 101 to the first embodiment in FIG.

[0080] The determination unit 107 receives the reliability calculated by the log aggregation and comparison unit 106, and compares the reliability value with a preset threshold. If the reliability is smaller than the threshold, the current scenario is stored in the current scenario storage unit 109, and the reliability value is passed to the display unit 114. The operation in this case is the same as in the first embodiment. On the other hand, if the reliability is larger than the threshold, the reliability value is passed to the parameter adjustment unit 108, and the current scenario is not stored in the current scenario storage unit 109.

[0081] The parameter adjustment unit 108 adjusts the condition parameters of the current scenario in accordance with the received reliability value. The adjusted condition parameters are passed to the current scenario generation unit 104, which modifies the current scenario.

[0082] The condition parameters adjusted by the parameter adjustment unit 108 include, for example, parameters related to reliability such as the failure rate and deterioration level of an asset, the asset operation pattern, and the worker operation pattern. When, for example, the normal operation time of an asset is used as the reliability, the failure rate and deterioration level of the asset, or a parameter of the asset operation pattern is adjusted as a related parameter. When, for example, the working time of a worker is used as the reliability, a parameter of the worker operation pattern is adjusted. In this way, by defining the value calculated as the reliability and the parameter to be adjusted as a set, the parameters can be adjusted efficiently without changing the countless condition parameters indiscriminately.

[0083] 3A and 3B in the first embodiment, it is possible to capture business characteristics according to a calendar, such as seasonal fluctuations, busy periods at the end of a term, and busy periods at the end of a month, by changing the period or time interval of log collection. Therefore, by performing reliability judgment and parameter adjustment for multiple reliabilities in which the period or time interval of log collection is changed, it is possible to perform a simulation that reproduces business characteristics according to a calendar, such as seasonal fluctuations, busy periods at the end of a term, and busy periods at the end of a month.

[0084] 4A and 4B in the first embodiment, the group unit for log aggregation can be changed to capture the business characteristics of each group, such as base / area and skill. Therefore, by performing reliability judgment and parameter adjustment for multiple reliability levels in which the group for log aggregation is changed, a simulation can be performed that reproduces the business characteristics of each group, such as base / area and skill.

[0085] By adding the above-mentioned reliability judgment and parameter adjustment processes, only current scenarios that match the aggregated and statistical values ​​of actual log data within threshold ranges will be used in the future scenario evaluation device, ensuring the predictive reliability of scenario evaluation.

[0086] FIG. 12 is a flowchart showing the process of the current task reproduction device 101 according to the second embodiment of the present invention.

[0087] In FIG. 12, the user designates the timing of data acquisition from the business system 1000 to the data acquisition unit 103 (step S201).

[0088] The data acquisition unit 103 determines whether or not it is time to acquire data in accordance with an instruction from the user (step S202).

[0089] When the acquisition timing designated by the user has arrived (Yes in step S202), the data acquisition unit 103 acquires data from the business system 1000 and passes the data to the current scenario generation unit 104 (step S203). When the acquisition timing designated by the user has not arrived (No in step S202), the data acquisition unit 103 repeats the process of step S202.

[0090] The current situation scenario generating unit 104 generates a current situation scenario based on the data acquired by the data acquiring unit 103, and passes it to the simulation unit 105 (step S204).

[0091] The simulation unit 105 executes a simulation based on the current scenario generated by the current scenario generating unit 104, and passes a virtual log to the log tallying and comparing unit 106 (step S205).

[0092] The log tallying and comparing unit 106 compares the virtual log obtained by the simulation unit 105 with the actual log of the business system 1000 obtained by the data obtaining unit 103, and calculates a difference (reliability) (step S207). The log tallying and comparing unit 106 passes the calculated reliability to the determining unit 107.

[0093] The determination unit 107 compares a preset threshold with the reliability calculated by the log aggregation and comparison unit 106 (step S210). If the reliability is smaller than the threshold (Yes in step S210), the determination unit 107 (current task reproduction device 101) saves the current scenario used in the simulation in the current scenario storage unit 109, and passes the reliability value to the display unit 114 (step S211).

[0094] The display unit 114 outputs the KPI of the current situation reproduction simulation calculated by the future scenario evaluation device 102 and the reliability calculated by the log compilation and comparison unit 106 to the display unit 114 (step S212).

[0095] In step S210, if the reliability is greater than the threshold value (No in step S210), the judgment unit 107 (current task reproduction device 101) passes the reliability value to the parameter adjustment unit 108 and does not store the current scenario in the current scenario storage unit 109.

[0096] The parameter adjustment unit 108 adjusts the condition parameters of the current scenario in accordance with the received reliability value, and passes the adjusted condition parameters to the current scenario generation unit 104 (step S213).

[0097] The processing of the future scenario evaluation device 102 is similar to that in the first embodiment, and therefore a description thereof will be omitted.

[0098] In the second embodiment, similarly to the first embodiment, the processing flows shown in Fig. 12 and Fig. 10 may be executed by the current task reproduction device 101 followed by the future scenario evaluation device 102, or they may execute the processing in parallel at the same time. When the processing is executed independently, the current task reproduction device 101 can link with the business system 1000 in real time, regardless of the processing of the future scenario evaluation device 102. On the other hand, the future scenario evaluation device can constantly monitor risks by constantly evaluating future scenarios. Furthermore, by separating the processing, it becomes easy to configure the current task reproduction device and the future scenario evaluation device as separate systems.

[0099] According to the second embodiment, it becomes possible to evaluate measures and risks with a high prediction reliability.

[0100] The present invention is not limited to the above-described embodiments, and includes various modified examples. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the configurations described. It is also possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration. [Explanation of symbols]

[0101] 100...business design support system, 101...current business reproduction device, 102...future scenario evaluation device, 103...data acquisition unit, 104...current scenario generation unit, 105...simulation unit, 106...log aggregation and comparison unit, 107...judgment unit, 108...parameter adjustment unit, 109...current scenario storage unit, 110...future scenario generation unit, 111...simulation unit, 112...KPI calculation unit, 113...scenario evaluation unit, 114...display unit, 1000...business system

Claims

1. A business design support system that provides business support based on data from a business system, A current task reproducing device that reproduces a current task and a future scenario evaluating device that evaluates a future scenario are provided, The current task reproduction device comprises: a data acquisition unit that acquires business log data related to actual business from a business system; a first simulation unit that performs a business simulation using a current business scenario generated from the business log data acquired by the data acquisition unit to create virtual log data; and a log aggregation and comparison unit that aggregates and statistically processes the business log data and the virtual log data, compares the aggregated and statistical values ​​of the business log data and the aggregated and statistical values ​​of the virtual log data, and calculates a reliability that is a difference between the two. Equipped with The future scenario evaluation device includes: a second simulation unit that generates a simulation model using a future scenario generated in consideration of a disturbance pattern or a policy pattern and a scenario of the current business; and a scenario evaluation unit that calculates a KPI (Key Performance Indicator) from the simulation model generated by the second simulation unit and evaluates the future scenario; Equipped with The business design support system includes: A business design support system characterized by displaying on a display unit the past KPI actual values ​​calculated from the business log data, the reliability calculated by the log aggregation and comparison unit, the fluctuation range of the KPI due to the disturbance pattern, and the KPI predicted value of a future scenario of the policy pattern.

2. 2. The process design support system according to claim 1, a determination unit that compares the reliability with a preset threshold value, and a parameter adjustment unit that adjusts a parameter of the scenario of the current task when the reliability compared by the determination unit is greater than the threshold value; A business design support system comprising:

3. 3. The process design support system according to claim 1, The business process design support system is characterized in that the log aggregation / comparison unit calculates a plurality of reliability degrees by changing the period or time interval for aggregating the business log data and the virtual log data.

4. 3. The process design support system according to claim 2, A current situation scenario storage unit for storing a current situation scenario is provided, A task design support system comprising: a current scenario storage unit that stores a scenario of the current task when the reliability compared in the judgment unit is smaller than the threshold value.

5. 3. The process design support system according to claim 1, A business process design support system, wherein the future scenario evaluation device prepares a set of condition parameters to be changed in the future scenario for each disturbance pattern.

6. 3. The process design support system according to claim 1, A business process design support system, wherein the future scenario evaluation device prepares a set of condition parameters to be changed in the future scenario for each policy pattern.

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