JP2006048577A - Achievement target processing system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system which performs the processing of a plurality of achievement targets. <P>SOLUTION: The achievement target processing system has an operation unit which calculates the actual result information and the plan information of achievement targets, a display unit which displays processing results of the operation unit, and achievement target database which stores the actual result information and the plan information of a terminal component index which are variables constituting the actual results information and the plan information of the achievement targets. The display unit displays an achievement target adjustment screen including a graph of the actual result information of the achievement targets and an adjustment lever to adjust the value of the terminal component index. The operation unit calculates the plan information of the achievement targets based on the change of a value of the terminal component index by the adjustment lever and displays the plan information together with the actual result information to the graph on the achievement target adjustment screen. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a performance target processing system for processing a plurality of performance targets, and more particularly to a performance target processing system suitable for use in a corporate management strategy.

  Business executives pursue multiple performance objectives when formulating a business plan. However, there are cases where there are correlations among performance targets, and in particular, there may be a trade-off relationship. Therefore, multiple performance objectives cannot be achieved simultaneously or independently. Business managers need to weight multiple performance objectives according to their importance while considering such correlations. Traditionally, such cases have relied on managers' experience and intuition.

  Japanese Patent Application Laid-Open No. 6-290163 describes a method of operating a meter or the like from an input device to determine a target value and realizing optimization by simulation.

JP-A-6-290163

  An object of the present invention is to be able to display a plurality of performance objectives so as to be easily understood visually.

  According to the present invention, the display device displays a performance target adjustment screen including a graph of performance information of the performance target and an adjustment lever for adjusting the value of the terminal component index. When the value of the terminal component index is changed by the adjustment lever, the plan information of the performance target is calculated, and the plan information is displayed on the graph on the performance target adjustment screen together with the result information.

  According to the present invention, a plurality of performance objectives can be displayed so as to be easily understood visually.

  FIG. 1 shows a configuration example of the entire system including a performance target processing system according to the present invention. The performance target processing system of this example includes a server device 101, a performance target database 108, and a correlation database 109. The server apparatus 101 is connected to a plurality of terminal apparatuses 105 via a communication network 104.

  The server device 101 has a performance target processing program 102 and a Web server program 103. The performance target processing program 102 performs performance target processing and display processing. The Web server program 103 receives user input data from the terminal device 105, executes input processing and display processing, and transmits the result to the terminal device 105.

  The terminal device 105 includes a browser 106, and the browser 106 displays a result processed by the server device 101.

  Here, the terminal device 105 and the server device 101 are configured separately, but may be configured as the same.

  The performance target database 108 includes performance information 1801 and plan information 1802 as shown in FIG. The performance information is a past performance value, and is obtained from financial information, sales, and purchase information collected from the core system, sales, and purchase system. The plan information is a predicted value calculated by the user using the performance target processing system of this example. The performance target database 108 can be used for analysis for predictive management and business management.

  The performance information 1801 and the plan information 1802 include data on performance targets, component element indices, and terminal component element indices. The performance target, component element index, and terminal component element index will be described. A performance target is an index that is necessary for a company's managers to judge their management status. Generally, the return on equity (ROE), free cash flow (FCF), days of inventory (DOH), return on assets (ROA), etc. are used as performance indicators in the manufacturing industry.

  A component index refers to an index or a variable that constitutes a performance target. For example, return on equity (ROE) can be calculated by the following formula.

Return on equity (ROE) = Profit ÷ Shareholders' equity (Formula 1)
Profit = Sales-Cost (Formula 2)
Sales = Price x Quantity (Formula 3)

  As is clear from these equations, the return on equity (ROE) is a function that takes profit, shareholder capital, sales, cost, price, and quantity as variables. Profit, sales, shareholder capital, cost, price, and quantity are called component indicators of return on equity. Of these component indicators, shareholders' equity, price, quantity and cost are independent variables. Shareholder capital, cost, price, and quantity are called terminal component indicators of return on equity. The terminal component index includes an index that cannot be arbitrarily changed by the user, such as shareholder capital, and an index that can be arbitrarily changed by the user, such as a price. Hereinafter, unless otherwise specified, the terminal component index refers to a terminal component index that can be arbitrarily changed by the user.

  The correlation database 109 has correlation information between terminal component indices as shown in FIG. The correlation between terminal component indices refers to a causal relationship that affects each other. For example, when the price is lowered, the sales quantity increases, and when the price is raised, the sales quantity decreases. Therefore, there is a correlation between price and sales volume. In the example of FIG. 19, correlation information 1901 between price and sales quantity, correlation information 1902 between price and cost, and correlation information 1903 between sales quantity and stock are stored. Such correlation information is often obtained by empirical rules, and is stored in the correlation database 109 as a trade secret. Correlation may be calculated and registered systematically from the performance target database 108.

  The overall flow of this system will be described with reference to FIGS. Figure 2 shows the overall flow of the system. FIG. 11 is a transition diagram of screens displayed on the browser 106 of the user terminal device 105. The user's browser 106 displays a performance target configuration setting screen 181, a performance information display screen 182, a performance target adjustment screen 183, and each performance target adjustment result screen 184. These screens are transmitted from the server apparatus 101 to the terminal apparatus 105. Details will be described with reference to FIGS. 12, 13, 14, and 15. FIG. In the following description, the processing executed by the server apparatus 101 is actually executed by the performance target processing program 102.

  In step S1, basic information setting is performed. First, the user displays the performance target configuration setting screen 181 on the browser 106 of the terminal device 105, and sets the relationship between the performance target and the component index. For example, when the return on equity is selected as the performance target, the relationship of (Formula 1) to (Formula 3) is set. Next, a constraint condition for the terminal component index is set. When the user clicks the performance target calculation button 162 on the performance target configuration setting screen 181, the server apparatus 101 acquires the performance information of the terminal component index from the performance target database 108 and converts it into the relational expression set by the user. Substitute and calculate performance targets. Further, when the user clicks the influence degree calculation button 163 on the achievement target configuration setting screen 181, the server apparatus 101 calculates the influence degree of the terminal component index on the achievement target. The server apparatus 101 stores the data thus obtained in the performance target database 108 as performance information. Details of the basic information setting in step S1 will be described with reference to FIGS.

  In step S2, performance information is displayed. The user displays the achievement information display screen 182 on the browser 106 of the terminal device 105. The achievement information display screen 182 displays the achievement information of each achievement target and the top five influence levels (%).

  In step S3, the performance target adjustment screen is displayed. When the user clicks the performance target adjustment screen display button 1303 on the performance information display screen 182, the browser 106 of the terminal device 105 displays the performance target adjustment screen 183. On the performance target adjustment screen 183, the initial value of the performance target, that is, performance information is displayed in a radar chart. On the performance target adjustment screen 183, the adjustment levers of the terminal component index are displayed as a group. Details of the display of the performance target adjustment screen in step S3 will be described with reference to FIG.

  In step S4, performance target optimization adjustment is performed. The user generates a planned value by changing the actual value of the performance target. That is, in this example, the user creates a planned value (predicted value) using the actual value (past value) of the performance target. The user changes the value of the terminal component index by operating the adjustment lever displayed on the performance target adjustment screen 183. When the server apparatus 101 receives the change value of the terminal component index transmitted from the terminal apparatus 105, the server apparatus 101 calculates the planned value of the performance target in consideration of the correlation. The server device 101 transmits the planned value of the performance target to the terminal device 105. On the performance target adjustment screen 183, the planned value is displayed together with the actual value of the performance target. Details of the performance target optimization adjustment in step S4 will be described with reference to FIG.

  In step S5, the adjustment result is displayed for each performance target. When the user clicks an expand button 1407 to each performance target on the performance target adjustment screen 183, the browser 106 of the terminal device 105 displays each performance target adjustment result screen 184. Each performance target adjustment result screen 184 displays the plan value of each performance target, together with the performance information and the influence degree of each performance target. The user can visually compare the actual value and the planned value.

  In step S6, the server apparatus 101 determines whether or not there is a rechange in the value of the terminal component index from the user. If there is a re-change, the processing from step S3 to step S6 is executed again. If there is no re-change, the process proceeds to step S7.

  In step S7, the component index of the performance target is registered in the performance target database 108. When the user clicks the DB registration button 1503 on each performance target adjustment result screen 184, the server apparatus 101 registers the performance target and the planned value of the terminal component index in the performance target database 108.

  FIG. 3 shows a flow of basic information setting in step S1 of FIG. In step S11, index setting is performed. The index setting in step S11 will be described with reference to FIG. In step S111, the user selects a performance target and sets it on the performance target configuration setting screen 181 of FIG. 12 displayed on the browser 106 of the terminal device 105. In step S112, the user uses the configuration setting toolbar 150 on the performance target configuration setting screen 181 in FIG. In step S113, the user sets the constraint condition of the terminal component index using the constraint condition toolbar 158 of the performance goal configuration setting screen 181 of FIG. In step S114, the server apparatus 101 stores the component element index and the constraint condition of the terminal component element index in the performance target database 108. When all the settings are completed, the process proceeds to step S12.

  Returning again to FIG. In step S12, the server apparatus 101 acquires the performance information of the terminal component index from the performance target database 108. In step S13, the user clicks a performance target calculation button 162 on the performance target configuration setting screen 181 of FIG. The server device 101 calculates the performance value of the performance target based on the performance information of the terminal component index. The server device 101 transmits the performance value of the performance target to the terminal device 105, and enables the use of the influence calculation button 163 on the performance target configuration setting screen 181 of FIG.

  In step S14, the user clicks the influence calculation button 163. The server apparatus 101 calculates the degree of influence of the terminal component index on the performance target. Details of the calculation of the influence degree in step S14 will be described with reference to FIG. When step S14 is completed, the process proceeds to displaying the result information in step S2 of FIG.

  FIG. 5 shows calculation of the influence of the terminal component index on the performance target in step S14 of FIG. The calculation of the influence level is executed by the performance target processing program 102 of the server apparatus 101. In step S141, time series values X1 to Xn of terminal component indices are acquired from the performance target database 108. In step S142, the performance target time series values Y1 to Yn for the terminal component index are acquired from the performance target database 108.

  In step S143, the cumulative total of time series values of performance targets is calculated. In step S144, the time series values X1 to Xn of the terminal component indices are each changed by 1%. In step S145, the time series values Y1 to Yn of the changed performance target index are calculated. In step S146, the cumulative value of the performance target after the change is calculated. In step S147, the change rate of the performance target value before and after changing the time series value of the terminal component index by 1% is calculated, and the value is set as the degree of influence of the terminal component index on the performance target.

  FIG. 6 shows the display flow of the performance target adjustment screen 183 in step S3 of FIG. When the user clicks the performance target adjustment screen display button 1303 on the performance information display screen 182 in FIG. 13, the performance target adjustment screen 183 in FIG. 14 is displayed.

  In step S31, the level of the radar chart is set. Details of step S31 will be described with reference to FIG. In step S32, the level of the adjustment lever is set. Details of step S32 will be described with reference to FIG. In step S33, the adjustment levers are grouped. Details of step S33 will be described with reference to FIG. In step S34, the performance information of each index is read from the performance target database 108. In step S35, the performance target adjustment screen 183 is displayed.

  FIG. 7 shows the flow of level setting of the radar chart in step S31. Here, the level of the radar chart is a scale on the three axes of the radar chart displayed on the performance target adjustment screen 183 of FIG. For example, when the whole scale is 0 to 100, the upper limit level is 100 and the lower limit level is 0. The level range refers to the distance between two points on the axis, and the range between the upper limit level and the lower limit level is 100. Further, when the whole scale is divided into 10 equal parts, one scale becomes 10. The level setting of the radar chart is performed using the level setting toolbar 1401.

  In step S <b> 311, the server apparatus 101 acquires performance information for each performance target from the performance target database 108. In step S312, the performance information of the performance target is set to be the midpoint of the radar chart axis of the performance target. In step S313, an upper limit level and a lower limit level from the midpoint are set. The server apparatus 101 obtains the level range specification 1403 information and level setting information 1404 and 1405 information set by the user on the performance target adjustment screen 183 in FIG. 14, and based on this information, sets the upper limit level and the lower limit level. Set. In step S314, the range from the upper limit to the lower limit is equally divided. For example, when the upper limit level is 100 and the lower limit level is 0, 0-100 are divided into 10 equal parts. Thereby, one scale of all scales 1402 becomes 10. Adjustment of these level values can be performed by an increase / decrease button 1406.

  FIG. 8 shows the flow of the adjustment lever level setting process in step S32. The level of the adjustment lever refers to the scale 1409 in the adjustment lever box 1408 displayed on the performance target adjustment screen 183 in FIG. The level setting of the adjustment lever is performed using the level setting toolbar 1401.

  In step S321, the server apparatus 101 refers to the restriction condition of the terminal component index from the performance target database 108, and extracts the terminal component index for which the variable range is set. In step S322, the upper limit of the constraint condition is set to the upper limit level of the adjustment lever of the index, and the lower limit of the constraint condition is set to the lower limit level of the adjustment lever of the index. In step S323, the range between the upper limit level and the lower limit level is divided by level range designation information. For example, the level range is divided into 10 equal parts.

  FIG. 9 shows the flow of the adjusting lever grouping process in step S33. In step S331, first, a terminal component index common to each performance target is extracted. Next, one adjustment lever is assigned to the extracted common terminal component index. In step S332, the correlation database 109 is accessed to search for common terminal component indices for which correlations are registered, and display those adjustment levers in the same adjustment lever box.

  The performance target optimization adjustment in step S4 of FIG. 2 will be described with reference to FIG. A specific example of this step will be described later with reference to FIG. As described above, the performance target adjustment screen 183 in FIG. 14 is displayed on the browser 106 of the terminal device 105 in the display of the performance target adjustment screen in step S3 in FIG. In FIG. 14, not only the performance value of the performance target shown by the broken line graph but also the plan value of the performance target shown by the solid line is displayed together, but the performance target optimization adjustment in step S4 is executed. Before being performed, only the performance value of the performance target indicated by the broken line graph is displayed.

  In step S41, the server apparatus 101 receives from the terminal apparatus 105 a change in the value of the terminal component index, that is, a change from the actual value to the planned value. In step S42, the server apparatus 101 accesses the correlation database 109 to search whether or not a terminal component index having a correlation with the changed terminal component index is registered. If it is determined in step S43 that no correlated terminal component index is registered, the process proceeds to step S45.

  If it is determined that a correlated terminal component index is registered, the process proceeds to step S44. In step S44, server apparatus 101 acquires correlation information from correlation database 109, and changes the value of the terminal component index. For example, assume that the user increases the price, which is a terminal component index, by 1%. Correlation information that the sales volume is reduced by 2% in such a case is obtained from the correlation database 109.

  In step S45, the value of the performance target is calculated again using the value of the terminal component index changed by the user. If there is a terminal component index having a correlation, the performance target is calculated again using the value and the value of the terminal component index changed by the user. For example, if the price is increased by 1%, the performance target is calculated on the assumption that the sales volume has decreased by 2%.

  In step S 46, the recalculation result of the performance target is transmitted to the terminal device 105, and the terminal device 105 displays the adjustment result information on the browser 106.

  The performance target composition setting screen 181 in FIG. 12 will be described. Only the configuration setting toolbar 150, the constraint condition toolbar 158, the performance target calculation button 162, and the impact calculation button 163 are initially displayed on the performance target configuration setting screen 181. The configuration setting toolbar 150 includes a brother node definition button 151, a parent node definition button 152, an addition definition button 153, a multiplication definition button 154, a child node definition button 155, a subtraction definition button 156, and a division definition button 157. The constraint condition toolbar 158 includes a fixed button 159, a variable range designation bar 160, and a variable range designation button 161.

  The user sets the performance target 164 and the component element indexes 165 to 170 using the configuration setting toolbar 150 of the performance target configuration setting screen 181 and sets the constraint condition of the terminal component index using the constraint condition toolbar 158. To do.

  First, the setting of the performance target 164 and the component index 165 to 170 will be described. In the example of FIG. 12, the user sets a return on equity (ROE) 164 as a performance target. Next, the user sets a constituent element index for return on equity. The component indicators of return on equity are profit, sales, equity, cost, price and quantity. A return on equity (ROE) 164 is defined as a parent node using a parent node definition button 152. Define profit 165 as a child node of return on equity (ROE) 164 using child node definition button 155. Use the brother node definition button 151 to define shareholder capital 166 as a brother node of profit 165. Thus, the return on equity (ROE) 164, profit 165, and shareholder capital 166 are defined as a parent node, a child node, and a younger brother node via the multiplication definition 171 and the division definition 172.

  Similarly, the parent node definition button 152 is used to define profit 165 as a parent node, and the child node definition button 155 is used to define sales 167 as a child node of profit 165. Using the brother node definition button 151, the cost 168 is defined as the brother node of the sales 167. The profit 165, the sales 167, and the cost 168 are defined as a parent node, a child node, and a younger brother node via the addition definition 173 and the subtraction definition 174.

  The parent node definition button 152 is used to define the sales 167 as a parent node, and the child node definition button 155 is used to define the price 169 as a child node of the sales 167. Using the brother node definition button 151, the quantity 170 is defined as the brother node of the price 169. Sales 167, price 169, and quantity 170 are defined as a parent node, a child node, and a younger brother node via a multiplication definition 175.

  Next, setting of constraint conditions for terminal component indices will be described. The terminal component indicators of return on equity (ROE) 164 are shareholders' equity 166, cost 168, price 169, and quantity 170. First, one of the terminal component indices is selected. When the value of the selected component index cannot be changed arbitrarily, the check mark of the fixed button 159 is displayed, and when the value can be changed, the check mark of the fixed button 159 is deleted and variable in the variable range designation bar 160 Specify a range. For example, shareholders' equity cannot be changed and prices can be changed. This process has been described with reference to FIG.

  When the setting of the constraint conditions for all the terminal component indices is completed, the setting result on the performance target configuration setting screen 181 is stored in the performance target database 108. Next, the user clicks the performance target calculation button 162. The server apparatus 101 collects the performance information of the terminal component index from the performance target database 108 and calculates the performance value of the performance target. Next, the user clicks the influence degree calculation button 163. The server device 101 calculates the influence degree.

  FIG. 13 shows an example of the record information display screen 182. The performance information display screen 182 displays performance information 1300 for each performance target set by the user. Here, the performance information of the return on equity (ROE), free cash flow (FCF), and inventory days (DOH) set by the user as performance targets is displayed.

  In the performance information 1300, a graph 1302 of performance information of performance targets for each fixed period (monthly, quarterly, half-year, fiscal year) is displayed, and the terminal component index list 1301 has a high influence on the performance targets. They are displayed in order. In addition, the value (%) of the degree of influence of the terminal component index on the performance target is also displayed. When the past performance information is confirmed and the user presses the performance target adjustment screen display button 1303, the performance target adjustment screen 183 is displayed.

  FIG. 14 shows an example of the performance target adjustment screen 183. On the performance target adjustment screen 183, first, a level setting toolbar 1401, three axes of the radar chart 1412 of the performance target, and an adjustment lever box 1408 of a terminal component index are displayed. In the adjustment lever box 1408, a scale 1409, an adjustment lever 1410 and an initial value bar 1411 are displayed. The adjustment lever 1410 indicates the planned value of the terminal component index, and the initial value bar 1411 indicates the initial value of the terminal component index, that is, the actual value. There are terminal component indicators that cannot be changed, such as shareholders' equity, and those that cannot be changed, such as price and quantity. Provide an adjustment lever box.

  In this example, the return on equity (ROE), free cash flow (FCF), and inventory days (DOH) are set on the three axes of the radar chart 1412. First, the performance target performance information is set at the midpoint of the radar chart axis. This is because we prepared for both an increase and a decrease in performance targets. If the performance target increases but does not decrease, the performance target performance information may be set at the lower limit of the three-axis level. Next, the user sets a fluctuation range of the performance target, that is, an upper limit value and a lower limit value. Set the upper limit of the performance target to the upper limit of the scale of the radar chart axis, set the lower limit of the performance target to the lower limit of the scale of the radar chart axis, and divide the interval equally to set one scale.

  Next, the user determines an upper limit value and a lower limit value of the terminal component index. The upper limit value of the terminal component index is set to the upper limit of the scale 1409 in the adjustment lever box 1408, and the lower limit value of the terminal component index is set to the lower limit of the scale 1409. The scale 1409 in the adjustment lever box 1408 is equally divided to set one scale.

  In addition, when the upper limit value and the lower limit value of the terminal component index are given, approximate values of the upper limit value and the lower limit value of the performance target can be obtained based on the upper limit value and the lower limit value. Based on this approximate value, the upper and lower limits of the scale of the radar chart axis may be set.

  As shown in the figure, when two adjustment lever boxes 1408a and 1408b are connected, terminal component indices corresponding to these adjustment lever boxes indicate that they are correlated with each other. For example, price and sales volume are correlated with each other. The price adjustment lever box 1408a and the sales quantity adjustment lever box 1408b are connected.

  The user can adjust the value of the terminal component index by moving the adjustment lever 1410. When one of the adjustment levers of the terminal component indicators that are correlated with each other is moved, the other adjustment lever is automatically moved accordingly. For example, when the price adjustment lever is increased, the sales volume adjustment lever is automatically decreased.

  In this way, by changing the value of the terminal component index by moving the adjustment lever, the change value of the performance target, that is, the planned value is obtained. The solid line graph on the radar chart indicates the planned value of the performance target. Compared with the actual value, which is a broken line graph, in this example, the return on equity was adjusted from 10% of the actual value to 11% of the planned value. The number of days of inventory (DOH) was adjusted from the actual value of 8 days to the planned value of 9 days. Free cash flow (FCF) has been adjusted from the actual value of ¥ 100 million to the planned value of ¥ 100.8 billion.

  The user only has to move the adjustment lever so that the performance target displayed on the radar chart becomes an optimum value. When the optimum value of the performance target is obtained, the user clicks a deployment button 1407 for each performance target. Thereby, each performance target adjustment result screen 184 of FIG. 15 is displayed.

  FIG. 15 shows an example of each performance target adjustment result screen 184. Each performance target adjustment result screen 184 displays an adjustment result screen 1500 for each performance target set by the user. The adjustment result screen 1500 displays a graph 1502 of performance information of performance targets and a graph 1503 of plan information for each fixed period (monthly, quarterly, semi-annual, fiscal year), and the planned value of the terminal component index List 1501 is displayed in descending order of influence on the performance target.

  Since each performance target adjustment result screen 184 displays both the performance target performance information and the plan information, it is possible to analyze the difference between the performance information and the plan information. Here, if the user thinks that it is necessary to adjust the planned value of the performance target again, the user may return to the performance target adjustment screen 183 of FIG. When the user thinks that it is not necessary to readjust the planned value of the performance target, the user may click the database registration button 1503. Thereby, the performance target and the planned value of the terminal component index are registered in the performance target database 108 and can be reused as plan information.

  The concept of grouping of adjustment levers on the performance target adjustment screen 183 will be described with reference to FIG. FIG. 16A shows a terminal component index that is highly influential and adjustable for each performance target and an adjustment lever for it. For example, in the case of return on equity (ROE), price, quantity, and cost are high-impact and adjustable terminal component indicators, and in the case of inventory retention (DOH), quantity, price, and The amount of input is a highly adjustable and adjustable terminal component index, and in the case of free cash flow (FCF), the price and shelf are highly adjustable and adjustable terminal component indices. is there.

  As shown in FIG. 16B, common terminal component indices included in each performance target are extracted, and the adjustment lever boxes are grouped. In this example, common terminal components include price and quantity. Therefore, the price adjustment lever box and the quantity adjustment lever box are grouped. As shown in FIG. 16C, when there is a correlation among the terminal component indices, the adjustment lever is displayed in the same adjustment lever box. In the correlation database 109, correlations between terminal component indices are registered. When one value of a plurality of terminal component indexes that are correlated with each other is changed, the values of the other terminal component indexes are automatically changed. Therefore, if a plurality of adjustment levers are displayed in the adjustment lever box, one of them may be adjusted.

  Here, grouping is performed based on the correlation of terminal component indices, but grouping may be performed based on other conditions.

  With reference to FIG. 17, a specific example of the performance target optimization adjustment process in step S4 of FIG. 2 will be described. FIG. 17 shows an enlarged view of a part of the performance target adjustment screen 183. The performance target processing program 102 is based on the performance target database 108, the actual return on equity (ROE) is 10%, the free cash flow (FCF) is 100 million yen, and the inventory retention days (DOH) is 8 days. The actual price value of 150,000 yen and the actual quantity value of 100,000 are obtained, thereby displaying the radar chart and adjustment lever box of FIG.

  A broken line graph 1701 in the radar chart of FIG. 17 represents the actual value of the performance target. Initially, only a graph of performance values of this performance target is displayed. In the adjustment lever box 1703 of FIG. 17, a price initial value bar 1704, a price adjustment lever 1705, a quantity initial value bar 1706, and a quantity adjustment lever 1707 are displayed. As described above, the price and the quantity are displayed in one adjustment lever box 1703 because they are terminal component indices common to the three performance targets and are correlated with each other. The price initial value bar 1704 indicates a price actual value of 150,000 yen, and the quantity initial value bar 1706 indicates a quantity actual value of 100,000 pieces. Initially, the price adjustment lever 1705 is placed over the initial price bar 1704, and the quantity adjustment lever 1707 is placed over the quantity initial value bar 1706.

  The user moves the price adjustment lever 1705 to lower the price by 1%. That is, the actual price of 150,000 yen is reduced to the planned value of 150,000 yen. The performance target processing program 102 acquires from the correlation database 109 correlation information that the price increases by 2% when the price decreases by 1%. Accordingly, the quantity adjusting lever 1707 automatically rises by 2%. That is, the actual value of 100,000 pieces changes to the planned value of 108,000 pieces. A solid line graph 1702 of the radar chart in FIG. 17 represents the planned value of the performance target. That is, when the user moves the price adjustment lever 1705, a graph 1702 of the planned value of the performance target is displayed.

  In the following, as an example, a sales plan based on the return on equity (ROE), free cash flow (FCF) and days of inventory (DOH) is made as a performance target, and a price reduction as an action plan for realizing the plan. Take up the case where This will be described in the order of the processing in FIG. First, basic information setting in step S1 will be described. On the performance target composition setting screen 181 in Fig. 12, select return on equity (ROE), free cash flow (FCF) and days of inventory (DOH) as performance targets, and define the component indicators for each performance target I do. For example, the component index of return on equity (ROE) is profit, sales, shareholder capital, cost, price, and quantity. Next, a restriction condition is set for a changeable terminal component index. For example, terminal component indicators of return on equity (ROE) are shareholder capital, cost, price, and quantity. Here, since the price can be changed, a price range is set. For example, the current price is set to 150,000 yen, and the variable range of the price is set from 10% to 50%. The price range is 165000-75000 yen.

  Next, using these data, the performance target performance is calculated, and the influence of the terminal component index on the performance target is calculated. Here, an example of calculating the influence of the terminal component index “price” on the free cash flow that is the performance target will be described with reference to FIG. It is assumed that 150,000 yen, 160,000 yen, and 170000 yen are acquired in the time series value acquisition process of the terminal component index in step S141. Assume that 1000 M yen, 2000 M yen, and 3000 M yen have been acquired in the time series value acquisition process of the performance target in step S142. In the calculation of the cumulative value of the time series value of the performance target in step S143, 1000M yen + 2000M yen + 3000M yen = 6000M yen is obtained. Here, it is assumed that the free cash flow is a cumulative value.

  Next, in the terminal component index change process in step S144, the price value is changed by 1%. Thereby, 151500 yen, 161600 yen, and 171700 yen are obtained as time series values of the terminal component index. In the process of acquiring the time series value of the performance target after the change in step S145, 1100 M yen, 2200 M yen, and 3300 M yen are obtained. In the calculation of the cumulative value of the time series value of the performance target after the change in step S146, 1100 M yen + 2200 M yen + 3300 M yen = 6600 M yen is obtained. Therefore, in the influence degree calculation process in step S147, (6600 yen-6000 yen) / 6000 yen = about 10% is obtained as the influence degree.

  In the result information display of step S2, the result information display screen 182 of FIG. 13 is displayed. The display of the performance target adjustment screen in step S3 will be described. An example of displaying a return on equity (ROE) on a radar chart will be described. Assume that the actual return on equity (ROE) was 10%. Set the midpoint of the axis of the radar chart displaying the return on equity (ROE) to 10%. Next, a value input by the user is set as the range of the upper and lower limits of the axis and the level of the axis. For example, the upper and lower limit range of the axis is 10%. Since the midpoint is 10%, an axis of 0% to 20% is created. Next, if the axis is divided into 10 equal parts, one scale is 2%, and the level is set every 2%.

  Next, set the adjustment lever. Since the price range is 165000-75000 yen, the upper limit of price 165000 is set as the upper limit level of the price adjustment lever, and the lower limit of price 75000 is set as the lower limit level of the adjustment lever. Subsequently, the lower limit 75000 is subtracted from the upper limit price 165000 to obtain the price range 90000. Divide this into 10 equal parts to get 9000, which is one scale of price. Similarly, the adjustment lever of the component index of other performance targets is set.

  Next, the adjustment levers are grouped. Price and quantity are terminal component indices common to all performance targets and are correlated with each other. Therefore, put the adjustment lever of price and quantity into one adjustment lever box. In this way, the performance target adjustment screen 183 of FIG. 14 is obtained.

  The performance target optimization adjustment in step S4 will be described. In the example of Fig. 17, the actual value of return on equity (ROE) is 10%, the actual value of free cash flow (FCF) is 100 million yen, the actual value of days of inventory (DOH) is 8 days, and the actual price The value is 150,000 yen, and the actual quantity is 100,000 pieces.

  For example, the user decreases the adjustment of the “price” of the terminal component index by 1%. As a result, the price drops from 150,000 yen to 14.850,000 yen. By referring to the correlation database 109, a correlation is obtained that the quantity increases by 2% when the price decreases by 1%. Therefore, the quantity increases by 2%, from 100,000 to 102,000. Recalculate performance targets based on changed prices and quantities.

  The user can adjust the terminal component index again on the performance-purpose adjustment screen 183. When there is no additional adjustment, the result set on the performance purpose adjustment screen 183 is registered in the performance target database. Users get information that they can achieve their performance goals by reducing prices by 1% and increasing sales volume by 2%. Therefore, it is possible to examine and implement a scenario in which a sales campaign is performed, the price is reduced, and the sales volume is increased.

It is a figure which shows the example of whole structure containing the performance target processing system by this invention. It is a figure which shows operation | movement of the performance target processing system by this invention. It is a figure which shows a basic information setting process. It is a figure which shows an index setting process. It is a figure which shows the calculation process of the influence degree with respect to a performance target. It is a figure which shows the display process of a performance target adjustment screen. It is a figure which shows the setting process of the level of a radar chart. It is a figure which shows the setting process of the level of an adjustment lever. It is a figure which shows the grouping process of an adjustment lever. It is a figure which shows a performance target optimization adjustment process. It is a figure which shows the screen transition by this invention. It is a figure which shows a performance target structure setting screen. It is a figure which shows a performance information display screen. It is a figure which shows a performance target adjustment screen. It is a figure which shows each performance target adjustment result screen. It is a figure which shows grouping of an adjustment lever. It is a figure which shows the detail of a performance target optimization adjustment process. It is a figure which shows a performance target database. It is a figure which shows a correlation database.

Explanation of symbols

101 ... Server device, 102 ... Program, 104 ... Network, 105 ... Terminal device, 106 ... Browser, 108, 109 ... Database

Claims (7)

  Past performance values and future performance target values that are used to judge business conditions, past performance values and plan information that are forecast values, and past component values that are variables that constitute the performance goals. A performance target database that stores the predicted value of the performance target, a calculation device that calculates the performance information and plan information of the performance target, and a display device that displays a processing result of the calculation device. A performance target adjustment screen including a graph of performance information of performance targets and an adjustment lever for adjusting the value of the terminal component index is displayed, and the arithmetic unit displays the value of the terminal component index by the adjustment lever. Based on the change, the plan information of the performance target is calculated, and the plan information is displayed together with the result information on a graph on the performance target adjustment screen. .   2. The performance target processing system according to claim 1, further comprising a correlation database for storing correlation information between the terminal component indices, wherein the arithmetic unit configures the performance target from the correlation database. A performance target processing system characterized by detecting a correlation between a plurality of terminal component indexes and calculating plan information of the performance target based on the detected correlation.   2. The performance target processing system according to claim 1, wherein the display device includes an adjustment lever for a terminal component index having a correlation among a plurality of terminal component indexes constituting the performance target on the performance target adjustment screen. Performance target processing system characterized by displaying as one group.   2. The performance target processing system according to claim 1, wherein the computing device calculates the degree of influence of the terminal component index on the performance target, and the display device corresponds to the terminal component index and the terminal component index. A performance target processing system that displays the value of the degree of influence in descending order of the degree of influence.   2. The performance target processing system according to claim 1, wherein the display device includes a component setting button for setting the performance target and a component index constituting the performance target on the performance target adjustment screen, the performance target, and the performance target. A configuration tool bar including a calculation definition button for defining a calculation between component element indexes, and configuring the performance target and the performance target based on the setting by the component setting button and the definition by the calculation definition button The relationship between the element indexes is displayed, and the arithmetic unit calculates the value of the performance target based on the relationship between the performance target set by the setting toolbar and the component index constituting the performance target. A performance target processing system for calculating an influence degree of the constituent element index on the performance target.   A step of displaying a performance target adjustment screen including a graph of performance information of the performance target and an adjustment lever for adjusting a value of a terminal component index constituting the performance target; and the terminal component index of the terminal component index by the adjustment lever A performance target processing method comprising: calculating the plan information of the performance target based on a change in value; and displaying the plan information together with the result information on a graph on the performance target adjustment screen.   A computer-readable program for causing a computer to execute the performance target processing method according to claim 6.

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