Patent Publication Number: US-2005125249-A1

Title: Method, program, and system of measuring the effect of investment in an IT system

Description:
CLAIM OF PRIORITY  
      The present application claims priority from Japanese application P2003-381622 filed on Nov. 11, 2003, the content of which is hereby incorporated by reference into this application.  
     BACKGROUND  
      This invention relates to a technique of measuring the effect of investment in an IT system built by a business organization or the like.  
      Lately, efficiency is pursued in investing in IT (information communication technology) systems as is elsewhere and people have come to pay closer attention than ever to ROI (Return On Investment) in IT systems. Now there is a need to estimate, before an IT system is introduced, how much benefit the system will bring and, after the system is installed, to monitor the operation status of the system constantly for evaluation of the system&#39;s contribution to increase in profit which is to be reflected in future IT investment strategies.  
      Against this background, methods and tools of evaluating the effect of investment in an IT system are being explored. An example of such tools is a system with which indicators such as receipts and payments for equipment, business cash flow, securities income and expense, and loan payable are calculated from financial statements inputted as data and, of the calculation results, ones that meet the purpose of analysis are displayed in the form of graph (JP 2001-188827 A).  
      The cited invention enables a user to visually grasp changes with time in amount of equipment investment such as IT investment and business cash flow and to judge the influence of the equipment investment over business cash flow, thus providing the user with decision-making materials to decide whether the equipment investment has been a success or not.  
      Another example is simple diagnosis software about computerization (JP 2002-352060 A). A company considering, or having troubles with, computerization consults a diagnostician (consultant) who conducts a preliminary survey and a face-to-face hearing on the company to grasp the outline and problems of the company&#39;s business process, and who uses this software to give diagnosis about the direction (category) of computerization, the business process efficiency, the current computerization condition, readiness to advance computerization, and business performance management fields as well as presenting solutions to the problems. This method provides a guideline on whether or not to invest in computerization, or what computerization investment is to be made, based on the present business process condition.  
     SUMMARY  
      Those conventional methods have problems given below.  
      The equipment investment management method of JP 2001-188827 A uses only the amount of money invested in comparison between equipment investment and business cash flow. The method therefore does not clarify how the equipment in which investment is made has been utilized and how much the equipment investment has contributed to business cash flow. In the first place, a simple comparison between the equipment investment amount and business cash flow does not yield a correct causal relation between the two since business cash flow does not depend solely on equipment investment but is influenced by other factors.  
      Furthermore, the method merely displays the equipment investment amount and business cash flow on the same graph in an overlapping manner, a qualitative presentation of a causal relation between the two. In order to obtain a quantitative understanding of an association between the two, an analyst has to take another measure for a separate analysis.  
      The simple diagnosis method about computerization which employs the simple computerization diagnosis software according to JP 2002-352060 A uses results of a face-to-face hearing conducted on proprietors and employees of a company to be diagnosed. The hearing results contain subjective views by the proprietors and employees interviewed, and therefore do not make an objective analysis.  
      In addition, the diagnostician chooses an answer to such a question item as “does the proprietor have a great interest in IT?” based on his/her evaluation of the hearing results which are constituted of top executives&#39;/department heads&#39; views on the corporate strategy, important business developments, and needs for computerization, current problems viewed by person in charge of the existing information system, and the like. Since a subjective evaluation of the hearing results by the diagnostician makes the basic data of analysis in this method, the diagnosis is subject to diagnostic skills and experience of the diagnostician.  
      It is therefore an object of this invention to provide system quantitatively estimating the effect of investment in an IT system on the basis of objective information on the IT system while screening out information that is based on subjective views by proprietors and employees of a company to be evaluated and eliminating information evaluation dependent on diagnostic skills and experience of diagnosticians.  
      In order to solve those problems and attain the above object, this invention uses data about profit obtained from a business system (revenue indicator), data indicative of the progress status of a business process (business process progress status indicator), and data indicative of the operation status of an IT system (system operation status indicator), and analyzes the correlation between the data. Thus system quantitatively evaluating influence of the operation status of the IT system over profit is provided.  
      This invention is comprised of, for the purpose of evaluating influence of the operation status of an IT system over profit, first unit analyzing the correlation between data classified as a system operation status indicator and data classified as a business process progress status indicator, second unit analyzing the correlation between data classified as a business process progress status indicator and data classified as a revenue indicator, and third unit analyzing the correlation between data classified as a system operation status indicator and data classified as a revenue indicator by integrating the first two correlations.  
      This invention is further comprised of fourth unit calculating, from the above-described correlation between data classified as a business process progress status indicator and data classified as a revenue indicator, the impact (contribution ratio) of data classified as a system operation status indicator on data classified as a revenue indicator and then calculating, from the contribution ratio as well as the revenue indicator data, a profit derived from the IT system, and fifth unit calculating the effect of investment in the IT system taking into account the calculated profit and the cost necessary to build and run the IT system.  
      This invention makes it possible to evaluate the correlation between company profit and an IT system quantitatively, so that the effect of investment can be measured with precision. This invention is also capable of providing a guideline on improvement of the IT system configuration to increase profit based on the correlation between an IT system operation status indicator, a business process progress status indicator, and a revenue indicator. In addition, the invention enables a user to detect a bottleneck in an IT system that adversely affects profit and to readjust the system configuration accordingly. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       FIG. 1  is a system configuration diagram showing an embodiment of this invention.  
       FIG. 2  is a function block diagram showing the configuration of an IT investment effect measuring system according to this invention.  
       FIG. 3  is a function block diagram of a data input unit according to this invention.  
       FIG. 4  is a function block diagram of a system-business correlation structure estimating unit according to this invention.  
       FIG. 5  is a function block diagram of a system-profit correlation structure estimating unit.  
       FIG. 6  is a function block diagram of an investment effect calculating unit.  
       FIG. 7  is an explanatory diagram showing an example of data outputted from a log output mechanism.  
       FIG. 8  is an explanatory diagram showing an example of items and values set to data attributes.  
       FIG. 9  is an explanatory diagram showing an example of system-profit correlation structure parameters displayed.  
       FIG. 10  is a system configuration diagram of a call center.  
       FIG. 11  is a business flow chart for the call center.  
       FIG. 12  is an explanatory diagram showing log data items collected at the call center.  
       FIG. 13  is an operation flow chart for an impact-on-profit evaluating unit.  
       FIG. 14  is an explanatory diagram showing an example of an impact-on-profit evaluation result displayed.  
       FIG. 15  is an operation flow chart for an improvement method analyzing unit.  
       FIG. 16  is an explanatory diagram showing an example of system configuration parameters.  
       FIG. 17  is an explanatory diagram showing an example of hardware component information. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
      An embodiment of this invention will be described below with reference to the accompanying drawings.  
       FIG. 1  is a system configuration diagram showing an embodiment of this invention.  
      In  FIG. 1 , a business system  4  (IT system) is in operation in a computer  220 , which is connected via a network  230  to a computer  210  where an IT investment effect measuring system  211  of this invention is run. Here, an example is shown in which the business system  4  is an IT system that is the subject of measurement by the IT investment measuring system  211 .  
      The term “IT system” refers to information communication system, for example, a system composed of hardware and software with which a business is carried out.  
      The business system  4  has a mechanism to send to the computer  210  log data which indicates the operation status of the system. The IT investment effect measuring system  211  run on the computer  210  receives the log data and analyzes the log data as will be described later to measure the effect of investment in the IT system.  
      Not-shown input devices such as a keyboard and a mouse are connected to the computer  210 , enabling an analyst to control processing. Also connected to the computer  210  are not-shown output devices such as a display and a printer, which are for displaying measurement results and analysis results. A storage system such as a hard disk connected to the computer  210  makes it possible to record data sent from the business system  4 , interim analysis data, and the like at any time.  
       FIG. 2  is a function block showing the configuration of the IT investment effect measuring system  211  according to this invention.  
      The IT investment effect measuring system  211  according to this invention is composed of a log output mechanism incorporated in the business system  4 ; a data input unit  1  which reads and sorts log data (time-series data) outputted; an investment effect measuring unit  2  which uses data sorted by the data input unit  1  to measure the effect of IT investment; and a system configuration improvement assisting unit  3  which monitors the operation status of the business system  4  through log data, detects a bottleneck that adversely affects profit, and optimizes the system configuration in a manner that maximizes the effect of investment.  
      The operation of the respective units will be described in detail below. In this embodiment, a call center is taken as an example of the business system  4 , which is the subject of investment effect measurement.  
      A system of a call center is shown in  FIG. 10 . At the call center, dedicated operators take calls from customers to answer customers&#39; questions about products and services, promote new products, and take orders. In some cases, the operators make calls to customers for sales and aftercare services. For quick and correct handling of such calls, the operators need to obtain, on site, customers&#39; history of purchases, past inquiries made to the call center, information on new products, and the like while talking with customers.  
      The call center system shown in  FIG. 10  attains these objects by integrating telephones and an information system in a manner that enables the operators to promptly obtain information necessary to deal with customers.  
      The information system is composed of a switchboard  901  which puts a call from a customer through an operator; a phone-system cooperation device  904  which controls cooperation between telephones and systems; a customer service system  905  which assists in retrieval and update of information necessary to deal with customers; a customer information database  906  which stores customers&#39; basic attributes such as age and sex and history of purchases; a product information database  907  which stores information on products in product lineup; a deal management database  908  for management of past deals; client PCs  909  through which operators in their cubicles manipulate the customer service system; and telephones  910  on which operators talk with customers. In this example, the switchboard  901 , the phone-system cooperation device  904 , the customer service system  905 , the databases  906 ,  907  and  908 , and a server where the above components operate correspond to the business system  4  shown in  FIGS. 1 and 2 .  
      The information system may further has an automatic answering machine  902  and an automatic dialer  903  for quicker answering to or contact to customers and resultant improvement in business efficiency.  
      How the call center business is carried out with the use of this system will be described referring to a business flow diagram of  FIG. 11 .  
      In  FIG. 11 , first, a call from a customer  1001  to the call center is received by the switchboard  901 . As the switchboard  901  receives the call, the phone-system cooperation device  904  connected to the switchboard notifies the customer service system  905  of reception of the call, along with an operator  1002  who is to take this call and the phone number of the caller which is notified by a caller identification service. The customer service system  905  accesses the customer information database  906  to retrieve customer information of the caller using the phone number of the caller, and displays the obtained information on one of the client PCs  909  that is used by the corresponding operator  1002 . Meanwhile, the switchboard  901  puts the call through the operator  1002 , who starts talking with the customer  1002  referring to the information displayed on his/her client PC.  
      During the discourse with the customer  1001 , the operator  1002  retrieves or updates information as the need arises on a screen of the customer service system  905  displayed on his/her client PC  909 . At the command from the operator, the customer service system  905  accesses the databases  906 ,  907  and  908  to retrieve or update information.  
      In the case where the customer  1001  asks technical questions that are beyond the knowledge of the operator  1002 , the operator  1002  forwards the call to a specialized department  1003  that can answer such questions. Notified by the switchboard  901  of the forward call, the phone-system cooperation device  904  instructs the customer service system  905  to provide necessary information to the specialized department to which the call is forwarded. The customer service system  905  follows the instruction and provides one of the client PCs  909  that is used by the specialized department  1003  with the information that is currently provided to the operator  1002 .  
      Receiving the forwarded call, the specialized department  1003  takes over dealing with the customer  1001  while retrieving or updating necessary information through the customer service system  905  as the operator  1002  did. When the customer  1001  is satisfied and ends the call, the contents of the call are recorded and arrangements necessitated by the call, whether it may be an order for a product or a request for repair, are made as post-processing.  
      In the call center business, the progress of the business is in this close conjunction with the call center system; the system operation status greatly influences the progress of the business and, resultantly, profit.  
      In practice, however, profit is not dependent solely on the system operation status and generally influence of the system over profit is merely one of factors that cause changes in profit. It is therefore necessary in evaluation of the effect of investment in the system to know to what extent the system operation status contributes to profit and to assess a profit that is derived from the system by checking the actual operation status.  
      This call center business is taken as an example to give a description on how a method and device of measuring the effect of investment in an IT system according to this invention evaluate profit brought by the system and measure the investment effect.  
      A log output mechanism  5  is incorporated in the business system  4  shown in  FIG. 2  to output necessary data at regular time intervals. Data items outputted by the log output mechanism  5  are as shown in  FIG. 7 , and include, at least, a data ID  601  indicating the type of data, a time stamp  602  indicating the time the data is obtained, and a data value  603 . The log output mechanism  5  therefore consults a data attribute  116  in order to sort output data by type and set data ID as shown in  FIG. 2 .  
      The data attribute  116  is, as shown in  FIG. 8 , a set of data constituted of a data ID  701 , a classification  702 , a data item name  703 , a profit calculation subject flag  704  indicating whether data is a subject of profit calculation or not, a monitor threshold  705  used in the system configuration improvement assisting unit  3 , which will be described later, and a section flag  706  indicating whether the threshold  705  is an upper limit value or a lower limit value. The attribute is set in advance for every type of data stored in the log data. The data ID  701  is consistent with the data ID  601  shown in  FIG. 7 , so data attributes (the classification  702 , the item  703 , the profit calculation subject flag  704 , and other attributes) are identified by referring to the data attribute  116  with the data ID  601  as a key. The data attribute  116  is also consulted by the data input unit  1  of  FIG. 2  and other components as will be described later. It is therefore necessary to make the data attribute  116  available for reference to the IT investment effect measuring system  211  in the case where the business system  4  holds the data attribute  116 . Alternatively, the data attribute  116  may be placed in another computer to be shared between the business system  4  and the IT investment effect measuring system  211 .  
       FIG. 12  shows an example of data items collected by the call center system shown in  FIG. 10 . The data is collected from the switchboard  901 , the phone-system cooperation device  904 , the customer service system  905 , the databases  906 ,  907  and  908 , the server on which these components operate, and others.  
      The data input unit  1  of  FIG. 2  sorts log data  101 , which is outputted from the log output mechanism  5 , to create data for analysis.  
      A function block diagram of the data input unit  1  is shown in  FIG. 3 . The data input unit  1  is composed of a data reading unit  201  and a data sorting unit  202  which are function components. As has been mentioned, the data input unit has an input device  6  (a display, a keyboard, a mouse, a network device, etc. which are not shown in the drawing) to allow separate input of data that is not contained in the log data  101 . The input device  6  also includes module collecting information from a network such as the Internet.  
      The data reading unit  201  reads data from the log data  101 . The read data is sent as it is to the data sorting unit  202 , where the data ID  601  in the read data is checked against the data ID  701  in the data attribute  116  and the data is sorted according to the classification  702  of the item that matches.  
      Every read data is classified as one of cost data  102  related to the cost to build and run the IT system, a revenue indicator  104  indicating profit of the company, a business process progress status indicator  105  indicating the progress status of the business process, a system operation status indicator  106  indicating the operation status of the IT system, an external factor  103  representing an external factor that could have influence over profit (weather conditions, economic trend, and the like), and a system configuration parameter  107  representing the current system configuration. Here, the cost data  102  and the revenue indicator  104  are outputted from the business system  4 . The term “business process” refers to the unit of activity or work in a company, for example, units constituting such elements as purchase, manufacture, sales, distribution, and customer support.  
       FIG. 12  shows an example of data classified as the revenue indicator  104 , the business process progress status indicator  105 , and the system operation status indicator  106  in the case of the call center system described above. It should be noted that the data shown in  FIG. 12  is merely an example and that other data may be used or some of the data in  FIG. 12  may not be used.  
      Data classified as the cost data  102 , data classified as the external factor  103 , and the system configuration parameter  107  are inputted separately from the log data through the input device  6 .  
      Data sorted in this manner is handed over to the investment effect measuring unit  2  and the system configuration improvement assisting unit  3  to be used for analysis.  
      The investment effect measuring unit  2  uses, of the data sorted by the data input unit  1 , the cost data  102 , the external factor  103 , the revenue indicator  104 , the business process progress status indicator  105 , and the system operation status indicator  106  to analyze.  
      The investment effect measuring unit  2  in  FIG. 2  is composed of function components including a system-business correlation structure estimating unit  110  which analyzes the correlation structure between data classified as the system operation status indicator  106  and data classified as the business process progress status indicator  105 ; a business-profit correlation structure estimating unit  108  which analyzes the correlation structure between data classified as the business process progress status indicator  105  and data classified as the revenue indicator  104 ; a system-profit correlation structure indicating unit  112  which analyzes the correlation structure between data classified as the system operation status indicator  106  and data classified as the revenue indicator  104 ; and an investment effect calculating unit  114  which calculates the final effect of investment in the system.  
      The operation of these function components will be described below.  
       FIG. 4  is a function block diagram of the system-business correlation structure estimating unit  110 . Data classified as the business process progress status indicator  105 , data classified as the system operation status indicator  106 , and data classified as the external factor  103  are chronologically arranged by pre-processing units  301 ,  302  and  303 , respectively, to supplement missing data and to perform pre-processing such as standardization that makes the average  0  and distribution  1 .  
      Then a correlation analysis processing unit  304  analyzes the correlation for each data that is classified as the business process progress status indicator  105  using, for explanatory variables, data that is classified as the system operation status indicator  106  and data that is classified as the external factor  103 .  
      The description here on the correlation analysis takes as an example a method that uses multiple linear regression analysis. When multiple linear regression analysis is employed, it is assumed that a data item of the business process progress status indicator  105 , that of the system operation status indicator  106 , and that of the external factor  103  have the following relation: 
 
 x   t,i =α i,1   f   t,2 α i,2   f   t,2 + . . . +α i,n   f   t,n +β i,1   g   t,1 , + . . . +β i,m   g   t,m +ε
          x t,i : an i-th data item classified as a business process progress status indicator     f t,i  an i-th data item classified as a system operation status indicator     g t,i : an i-th data item classified as an external factor     α i,n , β i,m : regression coefficient     ε t,i : residual term        

      Actually obtained data is used to calculate a regression coefficient by the following formula:  
         A   i     =         (       H   t     ⁢   H     )       -   1       ⁢     H   t     ⁢     X   i           
         A   i     =       (           α     i   ,   1             α     i   ,   2           ⋯         α     i   ,   n             β     i   ,   1             β     i   ,   2           ⋯         β     i   ,   m             )     t         
       H   =     (           f     1   ,   1             f     1   ,   2           ⋯         f     1   ,   n             g     1   ,   1             g     1   ,   2           ⋯         g     1   ,   m                 f     2   ,   1                                                                                                   ⋮                               ⋰                                           ⋮             f     t   ,   1                                   ⋯                                             g     t   ,   m             )         
         X   i     =       (           x     1   ,   i             x     2   ,   i           ⋯         x     t   ,   i             )     t         
 
      The calculated regression coefficient serves as a parameter that represents the correlation between an item included in the business process progress status indicator  105  and an item included in the system operation status indicator  106 .  
      This processing is performed on every data item that is included in the business process progress status indicator  105 , and the resultant group of regression coefficients is outputted as a system-business correlation structure parameter  111 .  
      The business-profit correlation structure estimating unit  108  performs the same processing as the system-business correlation structure estimating unit  110  shown in  FIG. 4 , except that the business process progress status indicator  105  which is input data in  FIG. 4  is replaced by the revenue indicator  104 , the system operation status indicator  106  which is input data in  FIG. 4  is replaced by the business process progress status indicator  105 , and the system-business correlation structure parameter  111  which is the output result in  FIG. 4  is replaced by a business-profit correlation structure parameter  109 .  
      As shown in  FIG. 5 , the system-profit correlation structure estimating unit  112  reads the system-business correlation structure parameter  111  outputted from the system-business correlation structure estimating unit  110  and the business-profit correlation structure parameter  109  outputted from the business-profit correlation structure estimating unit  108 . The parameters read are used by a structure parameter integrating unit  401  to calculate a coefficient of the correlation structure between a data item of the revenue indicator  104  and a data item of the system operation status indicator  106  through the following formula:  
         η     k   ,   i       =       ∑     j   =   1     n     ⁢       α   ji     ×     γ     k   ,   j               
          α j,i : the regression coefficient of a j-th data item of the system operation status indicator to the i-th data item of the business process progress status indicator     γk,j: the regression coefficient of a j-th data item of the business process progress status indicator to a k-th data item of the revenue indicator ‘ηk,j: the regression coefficient of the i-th data item of the system operation status indicator to the k-th data item of the revenue indicator        

      The calculation result is used by a contribution ratio calculating unit  402  to calculate the contribution ratio of a data item of the system operation status indicator  106  to a data item of the revenue indicator  104  through the following formula: 
 
r k,i =η k,i   2  
 
      The contribution ratio is outputted, along with the previously obtained system-business correlation structure parameter  111  and business-profit correlation structure parameter  109 , as a system-profit correlation structure parameter  113 .  
      The system-profit correlation structure parameter  113  is outputted to a display device or the like in a manner as the one shown in  FIG. 9 . This enables the analyst to visually grasp the correlation structure between data collected from the business system  4 , and helps the analyst to understand how the IT system contribute to profit.  
       FIG. 9  shows an example of displaying the sales amount, the number of new contracts, and the cost (cost data) in the upper area as elements of a revenue indicator  801 , the duration of dealing with customers, post-processing time, and on-hold time in the middle area as elements of a business process progress status indicator  802 , and the server operation ratio, the network load, and the outside line utilization ratio in the lower area as elements of a system operation status indicator  803 . The contribution ratio obtained by the above calculation is displayed between each two elements. For instance, according to  FIG. 9 , 0.3 of the server operation ratio contributes to the duration of dealing with customers and 0.3 of the duration of dealing with customers contributes to the sales amount. 0.5 of the network load contributes to the duration of dealing with customers, and 0.6 of the outside line utilization ratio contributes to the duration of dealing with customers. Thus the relation of the IT system operation status and business process progress status to the revenue indicator is made clear.  
      Although a method employing multiple linear regression analysis is shown here as the method of analyzing the correlation, similar correlation structure parameters can be calculated by other methods including one that uses factor analysis in combination with multiple linear regression analysis and one that uses covariance structure analysis.  
      The thus calculated system-profit correlation structure parameter  113  is sent to a system-derived profit calculating unit  501  of the investment effect calculating unit  114  shown in  FIG. 6 . The system-derived profit calculating unit  501  first reads the data attribute  116  and refers to the profit calculation subject flag  704  shown in  FIG. 8  to specify data items for use in calculation of profit. The system-derived profit calculating unit  501  then reads the revenue indicator data  104  and extracts, from the read data, data items that are subjects of profit calculation.  
      Thereafter, the system-derived profit calculating unit  501  reads the contribution ratio between the data items used for profit calculation and the data items of the system operation status indicator  106  from the system-profit correlation structure parameter  113 . The contribution ratio read is used together with data of profit calculation data items to calculate a system-derived profit  502  through the following formula:  
       Z   =       Y   k     ×       ∑     i   =   1     n     ⁢     r     k   ,   i               
          Z: system-derived profit     Y: profit calculation subject data        

      The thus obtained system-derived profit  502  is sent to an investment effect calculating unit  503 . The investment effect calculating unit  503  reads the cost data  102 , which is used along with the previously sent system-derived profit  502  to calculate an investment effect indicator  115 , the final output result of the investment effect measuring unit  2 , through the following formula:  
       ROI   =     Z   C         
          ROI: Return On Investment (investment effect indicator)     C: cost        

      The system configuration improvement assisting unit  3  is described next. After the investment effect measuring unit  2  estimates the system operation status indicator  106 , the business process progress status indicator  105 , and the revenue indicator  104 , the system configuration improvement assisting unit  3  monitors the system operation status and the business progress status by collecting real time the log data  101  of the business system  4 , in order to detect a bottleneck that adversely affects profit and analyzes an improvement guideline on a remedy for the bottleneck.  
      In  FIG. 2 , data inputted to the system configuration improvement assisting unit  3  includes the business process progress status indicator  105 , the system operation status indicator  106 , and the external factor  103  which are outputted from the business system  4 ; the system configuration parameter  107  which is configuration information of the business system  4 ; the data attribute  116  which shows attributes of the above data; and the correlation structure parameter  113  which is estimated by the investment effect measuring unit  2 . The system configuration improvement assisting unit  3  has an impact-on-profit evaluating unit  121  which monitors the system and the business progress state for evaluation of influence on profit and an improvement method analyzing unit  122  which, based on the evaluated impact, searches for a system configuration improvement idea that can increase profit. The units  121  and  122  provide information necessary to study system improvement measures (system configuration improvement assistance information  123 ). Given below are details of the operation of the system configuration improvement assisting unit  3 .  
      The operation flow of the impact-on-profit evaluating unit  121  is shown in  FIG. 13 . The impact-on-profit evaluating unit  121  first reads the business process progress status indicator  105  ( 1201 ) and refers to the threshold  705  and the section  706  which are recorded for each data item in the data attribute  116  shown in  FIG. 8  to judge whether a data item classified as the business process progress status indicator  105  meets an alarm-raising condition or not. This processing is performed on every data item classified as the business process progress status indicator  105  to extract alarm-raising data items which meet the alarm-raising condition ( 1202 ). Data is extracted as alarm-raising data when the business process progress status indicator  105  read is over, or under, the threshold  705  depending on the section  706 .  
      When extraction of alarm-raising data is finished, a coefficient of the correlation structure between data items of the business process progress status indicator that are extracted as alarm-raising data and profit calculation subject data is retrieved from the system-profit correlation structure parameter  113 . The product of the obtained correlation structure coefficient and the difference of an alarm-raising data value from the threshold is calculated. This processing is performed on every alarm-raising data, and the impact-on-profit amount is calculated as the sum of the obtained products ( 1203 ).  
      The thus obtained impact-on-profit amount is compared against the threshold  705  of the profit calculation subject data to judge whether there is more adverse affect on profit than acceptable or not ( 1204 ). When it is judged as a result that there is no adverse affect on profit that exceeds the acceptable level, the processing is ended at this point.  
      When it is judged as a result that there is more adverse affect on profit than acceptable, system operation status analysis processing  1205  is executed. In the system operation status analysis processing  1205 , the system-profit correlation structure parameter  113  is looked up for a coefficient of the correlation structure between the system operation status indicator  106  and the business process progress status indicator  105  to extract data items of the system operation status indicator  106  that are greatly correlated with alarm-raising data. Data values of the extracted data items are read out of the system operation status indicator data  106 , and the threshold  705  is read from the data attribute  116 .  
      The thus collected data is displayed as an impact-on-profit evaluation result  1206  on the display device. A display example of the evaluation result is shown in  FIG. 14 . In  FIG. 14 , items of the business process progress status indicator  105  that are extracted as alarm-raising data are listed under business process data  1301 . Also displayed are data values and thresholds  1302  of the items, and an impact-on-profit amount  1303  of the items. Data items  1304  of the system operation status indicator that are greatly correlated with the items, and data values and thresholds  1305  of the data items  1304  are also listed in the display. A data item of the system operation status indicator that exceeds the threshold is displayed in a manner that makes it easy to discriminate, for example, by coloring its display field. The thresholds  1302 , which are thresholds for the items of the business process data  1301 , and the thresholds  1305 , which are thresholds for the items of the corresponding system operation status data  1304 , are read from the data attribute  116 .  
      In this example, the response ratio of the business process data  1301  is lower than the section  706  (lower limit) of the threshold  705  set in the data attribute  116  of  FIG. 8 . The corresponding system operation status data  1304  that corresponds to the response ratio is the outside line utilization ratio, which exceeds (at 95%) the section  706  (upper limit) of the threshold  705  (70%) set in the data attribute  116 . The utilization ratio is therefore extracted as alarm-raising data, and the amount of resultant impact-on-profit is displayed (90 million yen). Similarly, the on-hold time of the business process data  1301  exceeds the section  706  (upper limit) of the threshold  705  set in the data attribute  116 , and the server operation ratio as the corresponding system operation status data  1304  that corresponds to the on-hold time exceeds (at 90%) the upper limit threshold 80% set in the data attribute  116 . The server utilization ratio is therefore extracted as alarm-raising data, and the amount of resultant impact-on-profit is displayed (15 million yen).  
      This enables the analyst to promptly detect which operation status (business process) of the information system is causing a problem.  
      When the impact-on-profit evaluating unit  121  in  FIG. 2  detects a bottleneck in operation process that adversely affects profit, the improvement method analyzing unit  122  assists the analyst in analyzing a method of improving the system configuration that eliminates the bottleneck.  
       FIG. 15  shows the operation flow of the improvement method analyzing unit  122 . Upon receiving the impact-on-profit evaluation result  1206  from the impact-on-profit evaluating unit  121 , the improvement method analyzing unit  122  reads the system configuration parameter  107  created by the data input unit  1 . The system configuration parameter  107  is outlined in  FIG. 16 . The system configuration parameter  107  contains: information  1501  on a server, a network device, and other components that constitute the system; information  1502  on the hardware configuration of the system such as the form of connection between components; information  1503  on software and process operating on a server; information  1504  on the work flow which shows the cooperation relation of the software and the process; and other information.  
      An example of the hardware component information  1501  is shown in  FIG. 17  as an example of the system configuration parameter  107 . The hardware component information  151  contains a set of a hardware component name  1601 , basic performance data  1602 , and a related system operation status indicator data item  1603 . The analyst can know a system component to be modified for improvement of a specific system operation status by consulting the hardware component information  1501 .  
      Once reading the data, the improvement method analyzing unit  122  moves on to processing of choosing a system configuration parameter that is to be modified in  FIG. 15  ( 1401 ). In this processing, as shown in  FIG. 14 , the analyst first looks over the impact-on-profit evaluation result  1206 , displayed on the display device and chooses, on the display screen, a data item of the system operation status indicator that the analyst desires to improve. The improvement method analyzing unit  122  consults the system configuration parameter  107  to extract a parameter related to the chosen data item.  
      The value of the extracted parameter is changed and the external factor data  103  is read before a system performance simulation is executed ( 1402 ). The system performance simulation provides a system operation status prediction result after the parameter change. Then data of the system-profit correlation structure parameter  113  is consulted to calculate influence on the business process and profit ( 1403 ).  
      When the calculation result is satisfactory (for instance, when the change of the system component improves the contribution ratio to profit or directly increases profit), the simulation result about the component is displayed and the processing is ended ( 1405 ). When the calculation result is not satisfactory, the parameter value is changed once more and simulation is executed with the new value ( 1404 ).  
      Whether the result is satisfactory or not may be judged by the analyst or by the improvement method analyzing unit  122 . In the latter case, a threshold is set in advance.  
      The final result obtained through this processing is a system improvement measure that can contribute to increase in profit as the analyst intends, and the analyst can form a plan of system configuration change based on this result.  
      The IT investment effect measuring system  211  can measure the effect of investment at any time. For instance, the investment effect measuring unit  2  and the system configuration improvement assisting unit  3  may execute their respective processing each time the revenue indicator  104  is established (e.g., quarterly settlement, monthly sales amount, or monthly profit) from the log data  101  which is outputted from the business system  4  and collected and accumulated by the data input unit  1 .  
      The log output mechanism  5  of the business system  4  may hold the log data  101  until the data input unit  1  requests the log output mechanism  5  to send the accumulated log data  101  at once. The log data  101  may be obtained from the data input unit  1  upon execution of investment effect measurement.  
      Alternatively, the log data  101  may be obtained on a steady basis, so the above evaluation of influence on profit and analysis for improvement of the IT system configuration are started when data of the business process progress state indicator  105  read and data of the revenue indicator  104  read meet, or do not meet, preset conditions. For instance, the analysis is started when there is a great change in revenue indicator  104  or when the contribution ratio is lower than a given value.  
      The revenue indicator  104  and the cost data  102 , which are obtained from the business system  4  in the above embodiment, may be inputted from the input device  6 .  
      The revenue indicator  104  is not limited to sales amount and other financial data such as profit or profit rate may be employed instead.  
      The IT investment effect measuring system  211  and the business system  4 , which are executed by the different computers  210  and  220  in the above embodiment, may be executed by the same computer.  
      The subject of measurement of the effect of IT investment is the business system  4  or a call center in the above embodiment. This is for exemplification only and any part or the entirety of hardware and software introduced by a company can be the measurement subject.  
      As has been described, this invention is applicable to an IT system consulting business which suggests the optimum IT system configuration in building an IT system. This invention is also applicable to an operation and management service business which constantly monitors the operation status of an existing IT system and analyzes the monitor results to improve the system configuration.  
      While the present invention has been described in detail and pictorially in the accompanying drawings, the present invention is not limited to such detail but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims.