JP6294180B2 - Improvement effect evaluation support apparatus and method - Google Patents

Description

  The present invention relates to a technology for supporting the provision of products and solutions suitable for solving business problems faced by customers, and in particular, based on the effects appearing to customers who have already introduced products and solutions. It relates to the technology to be evaluated.

  In order to grasp the problem of the current business of the customer and improve the business, the business is analyzed by calculating the feature amount such as the processing time for each user from the log of the business application. The key to business analysis is to find out the characteristics that indicate factors that hinder business and useful factors from various data, and it depends heavily on the experience and skills of the analyst. Even an experienced analyst requires a certain amount of man-hours for analysis.

  As a technique for solving this, in Patent Document 1, in a workflow management system, information on the analysis result of business features and a plurality of features defined for analyzing the business features of a plurality of business samples having different business features. Prepare a business pattern database in which values related to each vector component are registered, and retrieve business features related to the business to be analyzed by searching business samples with similar patterns of multiple feature vector component values from this business pattern database Provide technology. As a result, even an analyst with inexperienced analysis can analyze with reference to similar business samples.

JP 2002-279119 A

  The purpose of the business analysis is to grasp the current business of the customer, find out the factors that hinder or benefit the business, and improve the business. There are multiple factors that hinder operations and beneficial factors. Which barriers should be resolved as issues and which beneficial factors should be developed are determined by the customer's business domain, priority of problem resolution, and improvement. It depends on the customer's circumstances, such as the cost of spending. It is desirable for both the customer side and the solution presentation side to be able to take effective improvement measures without incurring costs.

  In the technology described in Patent Document 1, it is unclear how business sample improvement measures affect multiple factors indicated by feature vectors even if the business patterns are similar. The improvement measures of the business sample did not always solve the problem of the business to be analyzed.

  In addition, for the person who presents the solution, information on which customers should be engaged in sales activities of products and solutions is useful, but the compatibility of customer operations with the products and solutions can be improved. No quantitative evaluation has been done to make a judgment. Alternatively, even if quantitative evaluation is performed, it is a custom-made analysis / evaluation and cannot be applied to other customers in the same way.

  The present invention has been made to solve the above-mentioned problems, and the evaluator semi-automatically analyzes the suitability when introducing a solution measure that can be provided for a business problem held by a customer. The purpose is to provide technology to support the evaluation.

In order to achieve the above object, the present invention accumulates cases adapted to daily business changes, analyzes business problems, and presents solutions without preparing business patterns and feature vectors in advance. . For this purpose, we will formulate metrics that measure the customer's business issues and application effects that the solution has solved for the customer's business that introduced the solution. Use metrics to measure (periodically) post-implementation changes and record cases. Then, the customer business to be analyzed is measured using metrics, and a case having a large difference or ratio is extracted by comparison with the measured value after the case is applied. Assuming that problems similar to the problems that occurred in the case are also occurring in the business to be analyzed, a solution that solves the problems is presented. In addition, we analyze multiple business systems using analysis metrics of a solution, and extract business systems that showed highly effective measurement values. A customer who uses the extracted business system is a prospective customer of the solution. The present invention also includes the following aspects. This is to support the conformity assessment work of the customer's problem solving measures as follows. Basic business problem analysis that consists of business problems and solutions solved by cases, items to be extracted in order to measure the effects of introducing the solutions, and evaluation formulas calculated using the items to be extracted Prepare a metrics table. A plurality of basic business task analysis metrics tables are prepared for each business task. For example, if it is a task to improve efficiency, it may be possible to shorten the time or reduce the number of rework, but these measures quantify the improvement effect by measuring the time required for the work and the number of rework. It is possible. Here, a person who performs business analysis and evaluation is called an analyst. The analyst creates a business task analysis metrics table for the case based on the basic business task analysis metrics table. In addition, if there is no business problem analysis metrics table that matches the business problem solved by the case, you can create a new pattern of business problem analysis metrics table by customizing the basic business problem analysis metric table that is close to the case business problem. Like that.

Since log information is business-specific information, the analyst associates log information with items to be extracted. Even if a business log of another company is used, if the log is in the same format due to the use of the same business system, the linking operation may be performed once.
For any business task analysis metric, measurement data corresponding to items to be extracted from the business log is extracted, and the effect is estimated according to the evaluation formula. The business log is not limited to the log output by the application system, but may be data measured by the investigator using a stopwatch or questionnaire response data.

  In this way, by preparing a basic business problem analysis metric table, when a customer's problem is solved, the analyst can use the basic business problem analysis metric table based on the problem or the basic business problem analysis metric table. Business problem analysis metrics for evaluating the effectiveness of introducing solutions to customers who have not yet solved the problem by creating a business problem analysis metric table and linking the items to be extracted with the work log information A table can be created to evaluate the effectiveness of the solution.

The value calculated in this way is used as information for evaluating the compatibility with the solution measure. For example, out of a plurality of business task analysis metrics, there is a means to store the estimated effect value calculated using the same business task analysis metric and the customer identification information. It is possible to create a ranking of companies that are likely to be effective when applying a solution measure by outputting the estimated effect value measured by the problem analysis metrics and the customer identification information in the ranking from the higher value.
In addition, when you want to narrow down the functions that a company introduces, create business analysis metrics for each function, input customer identification information, output the estimated effect value that is stored together with the customer identification information, The use of increasing the priority of a function having a high estimated effect value with reference to the calculated estimated effect value is also conceivable.

  According to the present invention, it is possible to more easily perform suitability evaluation when an improvement measure is taken compared to the conventional case.

It is a system configuration figure of one embodiment of the present invention. It is a figure which shows an example of the basic composition of a business task analysis metrics table. It is a figure which shows the table of another pattern of the business task analysis metric shown in FIG. It is an example of the screen which defines a business analysis metric table. It is an example of the business task analysis metrics table created based on the business task analysis metrics table of FIG. It is a figure which shows matching with the extraction item and log data according to a system. It is an example of the business task analysis metrics table different from FIG. It is a figure which shows an example of the measurement data extracted by the measurement data extraction part. It is a figure which shows an example of the effect trial calculation score table obtained by applying this invention. It is a figure which shows an example of the flow of a process which supports the fitness evaluation work of the customer's problem-solving measure of one Example of this invention.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram showing a configuration of a conformity evaluation work support system for a customer problem solving measure according to the present embodiment. The analysis data 100 is a collection of customer business system logs, such as log data generated by a business application, log data obtained by an agent program, data measured by an investigator through on-site observation, and the like. It may include character information acquired from the business diary and sensor log data for measuring the movement of the worker. The business problem analysis metrics registration function 200 is a function that creates business problem metrics based on the case of a customer who has already introduced a product or solution, and registers the business problem analysis metrics in the business problem analysis metrics storage unit 400. The business task suitability search function 300 is a function for answering a result in response to a search request input from a person in charge of analysis. First, the measurement data extraction unit 310 reads data from the analysis data 100 and extracts measurement data based on the metrics defined in the business task analysis metrics storage unit 400.

  Next, the effect trial calculation unit 320 calculates the effect trial calculation value and records it in the effect trial calculation information storage unit 500, and the task suitability ranking creation unit 330 creates and answers the effect trial calculation value rank. The business problem analysis metrics storage unit 400 stores a metric definition for measuring the effect of introduction based on the case of a customer who has already introduced a product or solution. The estimated effect calculation information storage unit 500 stores the estimated effect calculation value. In the present embodiment, a database for recording measurement data, measurement data total values, and the like is not included in the configuration, but a configuration including these may be used.

  2 and 3 are diagrams showing a basic configuration example of the business task analysis metrics table. The business analysis metrics define metrics that measure the effectiveness of introduction based on the case of customers who have already introduced products and solutions and are showing results. In the business task analysis metrics registration function 200, the analyst edits the table configurations 410 and 420 to define business task analysis metrics 440 and 441 shown in FIG. Alternatively, 410 and 430 are edited to define business task analysis metrics 450 and 451 shown in FIG. The business task analysis metrics table includes basic data items 410 and metrics patterns. The basic data item is data for identifying a case when a certain measure is introduced, and includes a problem solution ID, a product name, a customer name, a solution measure, a proposal content, and a baseline. When a product is introduced and multiple problems can be solved, the analyst creates a business problem analysis metrics table for each problem that can be solved. When this table is created, the system assigns a task resolution ID to the business task analysis metrics table or enters a unique name that the analyst can identify. The product name is not an independent product, but may be anything that can be cut out and provided, such as the name of the device or solution that realized the solution, the solution menu, functions, and options. The baseline is a measured value that is measured by applying the metrics defined for the case after introduction, and is a value that serves as a basis for trial calculation. If time series changes in measured values are required, the baseline also has time series information.

  The metric pattern part prepares several patterns according to the type of business task, such as metric pattern_efficiency 420 and metric pattern_strict 430. The metric pattern is composed of a business task, a sub business task, metrics, an extraction item, necessary business information, a measurement value calculation formula, and an effect trial calculation formula. For example, the business task “efficiency” is classified into several sub business tasks such as time reduction and error reduction. As a metric for measuring “time reduction”, it is appropriate to measure the time required for the work of the analysis target, so the metric is “time required”. In any metric, basic data items to be extracted are defined as extraction items “work type”, “worker ID”, “matter ID”, “work amount”, “work group”, “start date / time”, and “end date / time”. These are the "start date" and "end date", who "work type" for a certain work "work type", how much "work amount" did what "work ID", and what work Is performed in the group “work group”.

If it is a log of the Web system, the "work amount" counts the number of times the screen is accessed, and it is necessary for the analyst to associate what is counted as the "work amount" according to the work. It becomes. The measurement value is a specific representation of the metric. In the case of the metric “required time”, the sum of (end date / time−start date / time) / sum of work amount is calculated as the time taken for the work unit. The value measured in the case is taken as the baseline, and the trial calculation formula is (measured value-baseline) x (assumed total work amount)
And The estimated value of the total amount of work is based on the amount of work when the measure is introduced, referring to the work before introduction.If the number of work does not change, the total amount of work before introduction is calculated. Use it, but if the number of tasks is halved, use 1/2 of the total amount of work before installation.

  Similarly, if the business problem is a reduction in mistakes, the reoccurrence rate of rebirth, if the risk opportunity is reduced, the number of opportunities that cause the risk, and if the compliance is strengthened, the case that was not carried out in a regular procedure The rate of occurrence is measured using extracted items.

  FIG. 4 is an example of a screen when the analyst edits the table structures 410 and 420 to define the business task analysis metrics 440 and 441 shown in FIG. Table configurations 410 to 440 are defined on the screen 600, and table configurations 420 to 441 are defined on the screen 610. On the screen 600, basic information of the case is input into the prepared items. When the creation button is pressed, the screen transitions to a screen 610, and when a business task and a sub business task are selected, a corresponding basic business analysis metric pattern is displayed. Here, the measurement value calculation formula, the effect calculation value, and the like are edited as necessary, and the system to be analyzed is registered.

  Figure 5 shows the efficiency of daily scrutiny work created by using the example of the case where company V introduces “cash cash machine + data batch management function ACT_Hx10” as a model of metric pattern_efficiency 420. 441. As the work is targeted for cash scrutiny work, information for identifying the work type of cash scrutiny work from the system log, information for identifying the work amount of cash scrutiny work for a certain period as a unit of work, This is added because the unit of the cash scrutiny work group is necessary for analysis.

  Here, the way of thinking when defining metrics will be described. Since there are many forms of products and solutions, the items to be measured differ depending on the business, but the basic idea is to measure the basic relationship between business issues and metrics, for example, the required time and the number of mistakes.

  The daily scrutiny that is shown as an example in FIG. 5 is one of the counters of the bank office. Many types of business are carried out at bank counters, and business systems support the business. Usually, a business system provides many functions, but since functions to be emphasized differ depending on financial institutions, there are functions that are incorporated in business systems and functions that are not. For example, the tightening operation is an operation for confirming that the slip and the cash in the sales office are totaled and matched. The cash machine has a function to identify cash, but after the store is closed, the cash is extracted from the cash machine, and the work of examining the extracted cash manually is carried out every day (daily review work). There is an overnight function as a function that simplifies the daily scrutiny. This is a function that allows you to continue working the next day without taking out the cash in the cash machine. By using this function, you can carry out several days of work that will be reviewed manually. Even if these functions are not introduced, business can be carried out, so it is difficult to determine whether to introduce them. Therefore, the effect of introducing the sales offices that have already been introduced is measured, and metrics are calculated to estimate how much the effect will be when introduced to sales offices that have not yet been introduced based on the actual measurement location.

The introduction of the overnight function can simplify the daily scrutiny that was performed manually, but from the perspective of efficiency by shortening the time, or from the perspective of stricter operations by reducing the opportunity to handle cash The calculation method of the effect changes depending on whether you want to see it. Considering the simplification of daily scrutiny by the overnight function from the viewpoint of improving work efficiency by shortening the time, the time required for cash scrutiny depends on the amount of cash and the number of employees performing the work. Assuming that the time taken for the scrutiny per banknote is the same, the time taken for the scrutiny per sheet is taken as a metric. In order to measure this, the amount of actual goods and the time required for work within a certain period are measured to calculate the time required for cash examination per piece. The estimated value of the effect differs when the daily scrutiny work is performed only with the overnight function and when it is performed manually, so a certain period is set in consideration of this execution cycle. The data items to be measured are the start time, the end time, the worker ID, and the measured number of cash for each type of cash. This is measured for each cash machine for automatic and manual inspections. Using the data measured for this measurement item, a measurement value is calculated. The amount of time it takes to examine the cash per sheet
Within a certain period of time (total time required for cash scrutiny) / (total number of cash)
Can be calculated. Here, the total time required for the cash scrutiny is the sum of the cash scrutiny by manual operation of each cash machine and the scrutiny by the automatic function of the cash machine. The total amount of time for manual cash scrutiny is the sum of the required time (end time-start time) x (number of workers) for cash machines, and the total scrutiny time by automatic function is (end time-start time) This is the sum of cash machines. The number of workers may be counted by duplicating the number of worker IDs in the work time zone. Although the concept of measurement items and measurement values may differ before and after installation, using the overnight function only reduces the number of manual operations, so measurement items and measurements before and after introduction The method for calculating the value is the same. The measured value after introduction calculated in this way is set as a baseline. The effect of shortening the time required for examining each cash can be calculated by (measured value before introduction of analysis target system-measured value of baseline). Actually, the effect appears differently depending on the amount of cash and the number of use of the overnight function, so (the effect of shortening the time required for cash per examination) × (the number of cash handled within a certain period) Use the trial calculation formula. Here, when “the number of cash” is considered as “the amount of work”, the effect calculation formula is (total of ((end date) −start date)) / (total amount of work) within a certain period of time.
It can be expressed as

  FIG. 6 is a diagram showing a system-specific data extraction definition table 442, in which information associated with a metric extraction item and a log corresponding to a problem solving ID is defined for each system. For example, SystemA Ver.2.0 system problem resolution ID: ACT_Hx10_n100 is intended for cash scrutiny, and system work and manual work are mixed in this work, so terminal logs and field survey data are used. The terminal log Act00x_count.csv is one of the log data and stores data associated with the extracted item. The data extraction program extraction_systemA is a program for extracting data corresponding to the extracted item from the terminal log Act00x_count.csv using information obtained by associating the extracted item of the metric with the log. Here, the association information only indicates the column number of the csv file, but there are rules such as extracting data between a specific character string and the character string, the number of digits to be extracted, etc. The data extraction program extracts data according to the rules.

  ACT_n100.xls is data created by manual measurement such as a stopwatch, and data is extracted from ACT_n100.xls with the data extraction program extraction_fieldData, as with the terminal log. Even if the terminal log is not available or the extraction rule is unknown, use the data measured by the investigator in the field survey. Moreover, when the analysis object is only system work and the work is recorded, the field survey data is not necessary. If the log corresponding to the extracted item is divided into a plurality of logs, the corresponding log is used. In this way, by defining the data extraction rules for each system, the analyst defines the data extraction rules once, thereby making a new definition for another company's system that uses the same system. It will be possible to analyze without.

Figure 7 shows the strict metrics for daily scrutiny, created by using the metric pattern_strictening 430 as a model, using the case where company V introduced “cash cash processor + data batch management function ACT_Hx10”. 451. As in FIG. 5, the simplification of the daily scrutiny by the overnight function is evaluated from the viewpoint of the business problem of stricter business by reducing the opportunity to handle cash. When defining metrics from this point of view, having fewer cash handling staff will reduce the chances of touching cash, but there is also the idea that handling by more than one person can reduce risk in terms of deterrence. Therefore, here, only the number of opportunities to touch cash is measured without considering the number of employees (of course, other data may be measured or the number of employees may be considered). The data items to be measured are the date and time of manual cash inspection for each cash machine and the worker ID. The worker ID is not always necessary to measure the number of times to touch the cash, but the metrics are whether the same person is always working or whether the worker pairing method is fixed. Since it may be incorporated, the worker ID is also a measurement item. Using the data measured for this measurement item, a measurement value is calculated. The number of manual cash reviews per cash machine is:
(Number of manual operations) / (Number of cash machines) within a certain period
It can be calculated by Here, when “the work type in which the risk occurs” is “cash check work”, the “number of manual work statements” can be expressed as “the total number of appearances of the work type in which the risk occurs”. If the “work group” is “cash machine ID”, the “number of cash machines” can be expressed as “number of work groups (counting without duplication)”.

  FIG. 8 is an example of measurement data extracted by the measurement data extraction unit 310 in accordance with the measurement data items of the business analysis metrics table 401. The measurement data items of the business analysis metrics tables 441 and 451 are managed in common, and information for identifying customer business and a function for storing the measurement data are provided. When measurement data has already been extracted, measurement data extraction is performed. It is also possible to omit the process 310. In addition, when it is necessary to measure time-series change information or when analysis is performed using a log of a fixed period, a function to periodically acquire and extract measurement data should be provided. The response time of the business task suitability search function 300 can be shortened.

FIG. 9 shows an example of the configuration of the effect trial calculation information table, which is a score table of the effect trial calculation values obtained by applying this embodiment. Problem solution ID = ACT_Hx10_n100 is the problem solution ID of the task analysis metrics table 441. The score table 501 is an estimated effect value calculated according to the measurement data of the business analysis metrics table 441 and the estimated effect equation. For example, when the fixed period is 1 week, the measured value of company Z is 68, and when processing 4550 sheets, the measured value of baseline is 27.
(68-27) × 4550 = 186550 seconds (fixed period: 1 week)
It becomes. This estimated effect value is a value for evaluating the suitability of the problem solution ID = ACT_Hx10_n100 for the company Z. In the score table 501, since the trial calculation value of the company Y is the largest, it can be evaluated that the measure of the problem solution ID = ACT_Hx10_n100 for the company Y is suitable among the calculated customers.

  In addition, if it is only necessary to evaluate whether or not the effect can be expected compared with the baseline that is the measurement value after introduction, as shown in the score table 502, the difference information between the measurement value and the baseline is used. If the difference information is positive, it may be evaluated that the effect can be expected.

  Fig. 10 shows that when an analyst inputs a business problem case solved by a certain product, a company ranking is created in descending order of the estimated effect when a product similar to the business problem case is introduced from log data of multiple companies. It is the figure which showed the flow of the process of the program output in this way. The program shown in FIG. 10 reads the problem solving ID input by the analyst as a search keyword and starts processing. In S1000, the business analysis metrics table of the problem solving ID is accessed, the measurement data items are referenced, and the business measurement data of the company to be analyzed is extracted. In the next step S1010, measurement data is put into a measurement value calculation formula to calculate a measurement value of a company to be analyzed. In the next step 1020, the baseline measurement value in the business analysis metric table is referred to, the trial calculation of the effect is calculated using the calculated measurement value and the baseline measurement value, the problem solution ID, the analysis target company and the effect are calculated. The estimated value is associated and stored. When the processes of S1000 to S1020 are performed for the business of the analysis target company, the process proceeds to S1030, rankings are created and output in descending order of the estimated trial value of the analysis target company, and the process ends.

  For example, if the salesperson in charge of a product is an analyst, enter the problem resolution ID of the product you are in charge of, and if the same problem solving measures as the problem resolution ID are introduced, it is estimated that it will be effective Since the output order is output, the use of introducing the product with reference to the output result can be considered.

  Further, the product names of the business analysis metrics tables 441 and 451 may be configured in a solution menu or a function unit of the product. For example, when considering business improvement of a company, the purpose is to calculate the estimated effect value for each function for multiple functions that the company is considering introducing, and to evaluate which function is preferentially introduced. It is also possible to use the estimated effect value.

  Furthermore, it is conceivable that log acquisition and analysis are automatically performed periodically in a cloud environment. For example, when a new function is released, it may be possible to estimate the effect of introducing the function and report it to the customer in a report format and use it as a material for studying the function introduction.

  As described above, according to the present embodiment, the analyst introduces improvement measures that can be provided to the business problem that the customer has by performing the work of associating the work log information with the items to be extracted prepared in advance. It is possible to obtain quantitative information for evaluating the suitability in the case of the above. By using this evaluation information, even if the analyst himself does not have the skill to calculate the effect, the improvement effect when the product or solution is introduced into the customer business can be calculated. In addition, when a plurality of functions are provided as a solution, the information can be used to determine which function should be introduced within a limited budget. Furthermore, in sales activities, it is possible to find a customer operation with a high improvement effect from a plurality of customer operations for a certain product or solution.

100 analysis data 200 business task analysis metrics registration function 300 business task suitability search function 400 business task analysis metrics storage unit 500 effect trial calculation information storage unit

Claims (10)

An improvement effect evaluation support device for supporting an improvement effect evaluation of work performed using work log data of a work system ,
Business analysis metrics indicating the correspondence between a problem solution identifier that identifies a solution to a business problem, an item to be extracted that is used for evaluation of improvement effects, and an evaluation formula that is estimated using the item to be extracted A storage unit for storing a plurality of tables;
Means for accepting correspondence with log data for the item to be extracted from an analyst, and defining the log data according to the accepted correspondence;
Based on the problem resolution identifier input from the analyst, a first business analysis metric table corresponding to the problem resolution identifier is identified from the plurality of business analysis metric tables, and is indicated in the first business analysis metric table. the first reference to the items to be and the first evaluation expression extraction, the effect estimated value using the first evaluation expression and the extracted data from the log data in response to the first item to be extracted for Means for calculating
An improvement effect evaluation support apparatus comprising: means for determining the estimated effect value as evaluation information. In the improvement effect evaluation support apparatus according to claim 1,
Means for storing a correspondence between items to be extracted and log data defined by the analyst for each business system;
Among the business systems, for the same business system, there is further provided means for using the above-mentioned definition, and the improvement effect evaluation support that makes it possible to omit the correspondence between items to be extracted and log data apparatus. In the improvement effect evaluation support apparatus according to claim 1,
For any business analysis metric, the value calculated using the data and evaluation formula extracted from the customer's business log before introduction, and the data and evaluation formula extracted from the business log of the customer who has already implemented the solution. An improvement effect evaluation support apparatus, further comprising means for calculating a difference from a value calculated by use as an estimated effect value. In the improvement effect evaluation support apparatus according to claim 1,
Means for accepting designation of business analysis metrics from the analyst;
An improvement effect evaluation support apparatus further comprising means for outputting evaluation information of a plurality of customers for the business analysis metrics that have received the designation. In the improvement effect evaluation support apparatus according to claim 1,
Means for accepting designation of the business system from the analyst ;
The improvement effect evaluation support apparatus further comprising means for outputting evaluation information obtained by applying a plurality of business analysis metrics to a business system of the same customer as the business system. An improvement effect evaluation support method for supporting an improvement effect evaluation of operations performed using operation log data of an operation system ,
Business analysis metrics indicating the correspondence between a problem solution identifier that identifies a solution to a business problem, an item to be extracted that is used for evaluation of improvement effects, and an evaluation formula that is estimated using the item to be extracted Store multiple tables,
For the item to be extracted, accept an association with log data from an analyst, define the log data according to the accepted association,
Based on the problem resolution identifier input from the analyst, a first business analysis metric table corresponding to the problem resolution identifier is identified from the plurality of business analysis metric tables, and is indicated in the first business analysis metric table. Referring to the first item and the first evaluation expression to be extracted, by using the evaluation formula and the extracted data from the log data to calculate the effect estimated value according to the first item to be extracted, the
An improvement effect evaluation support method, wherein the estimated effect value is determined as evaluation information. The improvement effect evaluation support method according to claim 6,
further,
For each business system, store the correspondence between items to be extracted and log data defined by the analyst,
For the same business system among the business systems, by using the above definition,
An improvement effect evaluation support method that makes it possible to omit the association between an item to be extracted and log data. The improvement effect evaluation support method according to claim 6,
further,
For any business analysis metric, the value calculated using the data and evaluation formula extracted from the customer's business log before introduction, and the data and evaluation formula extracted from the business log of the customer who has already implemented the solution. The improvement effect evaluation support method characterized by calculating the difference with the value calculated using it as an effect trial calculation value. The improvement effect evaluation support method according to claim 6,
further,
Accepting business analysis metrics from the analyst,
An improvement effect evaluation support method, comprising: outputting evaluation information of a plurality of customers for the business analysis metrics for which designation has been received. The improvement effect evaluation support method according to claim 6,
further,
Accepting designation of the business system from the analyst ,
An improvement effect evaluation support method comprising: outputting evaluation information obtained by applying a plurality of business analysis metrics to a business system of the same customer as the business system.

Images