JPWO2015193983A1 - Image display system and image display method - Google Patents

Abstract

Visualize how changes in specific KPIs in business data, such as execution of business improvement measures, have an effect on KPIs for business evaluation. Using a KPI causal model with a graph structure that shows the causal relationship between KPIs, KPIs that are on the path from the attention KPI to the evaluation KPI and KPIs that have no causal relationship with the attention KPI and have a causal relationship with the evaluation KPI are extracted. An image display system for plotting the actual values of these KPIs in a parallel coordinate system is provided.

Description

  The present invention relates to an image display system, and in particular, when drawing a chart for supporting business judgment using business data, business judgment is made based on the characteristics of business data and the causal relationship of KPI (Key Performance Indicator) related to the business. The present invention relates to an image display technique for drawing a chart that supports the above.

  In recent years, in order to acquire information useful for business execution from business data, many tools have been developed for analyzing business data through a screen-based visualization such as a graph.

  Regarding a method for visualizing the overall characteristics of data, Japanese Patent Application Laid-Open No. 2008-225940 (Patent Document 1) visualizes the degree of association between data and data using a group of arcs obtained by dividing a circular area and a curve connecting them. Proposes a bird's-eye view system.

  As a means of narrowing down the data to be analyzed, Special Table 2004-532489 (Patent Document 2) uses a plurality of plots to perform interactive filtering on a data set having a plurality of parameters. Proposes a narrowing system.

JP2008-225940 Special Table 2004-532489

  When making business decisions using business data, not only look at the behavior of business data itself, but also calculate the KPI value related to the business from business data and observe the KPI behavior to make the business situation more efficient. I can grasp it. Furthermore, based on the cause-and-effect relationship between KPIs, changes in specific KPIs (hereinafter referred to as “KPIs of interest”) due to implementation of business improvement measures, etc. If the causal relationship between all KPIs is not formulated and many causal relationships are involved, the fluctuation of the evaluation KPI due to the contribution of the attention KPI is grasped. It is difficult to do.

  In order to solve the above problems, the present invention uses a KPI causal model showing the causal relationship of KPIs, and evaluates KPIs on the causal path from the attention KPI to the evaluation KPI and no causal relationship with the attention KPI. KPIs that have a causal relationship with KPIs are distinguished and classified. Each KPI group and the value of the attention KPI and the evaluation KPI are calculated from the related business data and displayed on the parallel coordinate plot. For the KPI that has no causal relationship with the attention KPI and has the causal relationship with the evaluation KPI By narrowing down the data, a data set is generated in which the influence on the evaluation KPI due to the variation of the KPI having no causal relationship with the attention KPI that is the task determination target is created.

  Specifically, the image display system of the present invention is based on graph data composed of index value nodes related to business and edges indicating the relationship between the plurality of index values, and actual values of the plurality of index values. A storage unit that records actual value data, an input unit that receives input of information for selecting a first index value and a second index value among the plurality of index values, and the first index value A first group of one or more index values located on a path between the first index value and the second index value, and an index value not belonging to the first group, wherein the first index value is 1 A controller that determines the second group of one or more index values that are connected at the edges and that affect the determination of the first index value; and the coordinate axes of the first and second index values And part of the index values belonging to the first and second groups Or, in a coordinate system in which the coordinate axes of all index values are arranged in parallel, a display for displaying a parallel coordinate plot diagram in which the actual value data in which the second index value indicates the first value and the second value is plotted A part.

  In the image display method of the present invention, the graph data composed of the index value nodes related to the work and the edges indicating the relationship between the plurality of index values, and the actual value composed of the actual values of the plural index values Data, and an input unit that receives input of information for selecting a first index value and a second index value from among the plurality of index values; and the first index value and the second index A first group of one or more indices located in a path between values and an index value that does not belong to the first group, and is connected to the first index value by one or more edges, A second group of one or more index values that affect the determination of one index value, and the coordinate axes of the first and second index values, and the first and second groups Arrange the coordinate axes of some or all of the index values to which they belong in parallel In the coordinate system, and displays a parallel coordinate plot plotting the actual value data and the second index value indicating the first and second values.

  According to the present invention, using a plurality of data sets with different conditions, such as before and after the implementation of a business improvement measure, the user visually grasps the influence of the noticed KPI on the value of the evaluation KPI, and determines the effect of the measure Making it easier to make business decisions.

It is a block diagram which shows the outline of a structure of the image display apparatus which concerns on embodiment of this invention. It is a figure which shows the data structure of the KPI causal model information which concerns on embodiment of this invention. It is a figure which shows the example of the KPI causal model which the display part which concerns on embodiment of this invention displays. It is a figure which shows the example of the screen which the display part which concerns on embodiment of this invention displays. It is a flowchart which shows the business data analysis procedure using the image display apparatus which concerns on embodiment of this invention. It is a figure which shows the example which reflected the classification result of KPI in the KPI causal model which the display part which concerns on embodiment of this invention displays. It is a figure which shows the example of the parallel coordinate plot which the display part which concerns on embodiment of this invention displays. It is a figure which shows the example which narrowed down the data range of KPI which wants to suppress the influence on evaluation KPI with respect to the parallel coordinate plot which the display part which concerns on embodiment of this invention displays. It is a flowchart which shows the classification procedure of KPI which belongs to the KPI causal model which concerns on embodiment of this invention. It is a block diagram which shows the outline of a structure of the image display server which concerns on embodiment of this invention.

  Hereinafter, embodiments for implementing an image display apparatus according to the present embodiment will be described with reference to the accompanying drawings.

  First, the configuration of the image display apparatus according to the present embodiment will be described with reference to FIG.

  In various operations such as the manufacturing industry and the service industry, work instructions, work execution records, and the like are accumulated in a database in the business data server 10 or the corporate information system 11. The image display apparatus 1 collects information accumulated in the database in the business data server 10 or the enterprise information system 11 via the network 13, draws the results of the aggregation processing and analysis processing as characters and diagrams, and displays the screen 60. For example, a CPU (Central Processing Unit), memory, ROM (Read Only Memory), HDD (Hard Disk Drive), input / output interface, LCD (Liquid Crystal Display), keyboard and mouse.

  The network 13 may be a corporate intranet or the Internet.

  The image display device 1 is a communication unit that transmits and receives information to and from an input unit 2 that processes input from a user, a display unit 3 that has a screen that displays characters and charts of analysis results, a business data server 10, or an in-company information system 11. Unit 4, a storage unit 5 that stores KPI causal model information 20 representing the causal relationship between KPIs, a screen processing unit 21 that performs drawing of KPI causal models and parallel coordinate plots, management of a drawing target, control of a position, and the like, KPI A calculation processing unit 26 that performs classification, data selection, statistic calculation, and the like.

  In the example of FIG. 1, the screen processing unit 21 and the calculation processing unit 26 are part of the control unit 6. The control unit 6 is realized, for example, when the CPU executes a program stored in a memory. Therefore, in the following description, the processing executed by the control unit 6 (that is, the screen processing unit 21 and the calculation processing unit 26) is actually executed by the CPU according to the program stored in the memory.

  Further, as means for creating the KPI causal model information 20 held in the storage unit 5, the control unit 6 may include a KPI causal model editing processing unit 25 that generates a screen for performing editing processing of the KPI causal model, You may use the KPI causal model creation apparatus 12 connected with the network 13. FIG. Further, the communication unit 4 may acquire the KPI causal model information 20 stored in the business data server 10 or the database in the corporate information system 11 via the network 13.

  The KPI causal model creation device 12 is a computer device on which software for modeling a causal relationship of KPIs and creating a KPI causal model diagram using a GUI (Graphical User Interface) operates, and information on the created KPI causal model diagram is obtained. It is stored in the storage device in the apparatus as KPI causal model information.

  The business data server 10 is, for example, a so-called WMS (Warehouse Management System) server in the case of a distribution warehouse business, and manages information such as product information, shipping instructions, inventory, delivery destinations, delivery means, and work progress. . The business data server 10 having a database for all the information may be used, or a plurality of business data servers 10 having only a specific database may be used in cooperation, or an equivalent database may be used. You may use the in-company information system 11 which cooperates.

  Next, a configuration example of the KPI causal model information 20 held by the storage unit 5 will be described with reference to FIG. The KPI causal model information 20 shown in FIG. 2 represents the result of modeling the KPI causal relationship, and includes at least two or more KPI information 35 and at least one inter-KPI information 42. This model is expressed as a graph composed of KPI nodes and edges indicating the relationship between KPIs.

  The KPI information 35 is a collection of information related to each KPI, the KPI name 36 for the user to identify the content indicated by the KPI, the related data presence flag 37 indicating whether or not the user is associated with the business data, and the related data presence flag. 37, the related data location information 38 including information such as a server name, a database name and a field name, or a file name in which related business data is stored, a cause KPI that affects the KPI A name 39, a calculation method 40 indicating a method of calculating the value of the KPI using related business data or the cause KPI value, and other information 41 necessary for performing the business are included.

  All the information included in the KPI information 35 is not essential, and is stored in the storage unit 5 only when the corresponding information exists. If there is a plurality of pieces of information corresponding to one KPI, a plurality of pieces of information are held.

  The inter-KPI information 42 holds the relationship between two KPIs in which a causal relationship exists. When there is a correlation between the cause KPI name 43, the result KPI name 44, and the cause KPI and the result KPI, Includes correlation information 45 including a correlation coefficient indicating whether the correlation is a positive correlation or an inverse correlation, a correlation coefficient indicating the strength of the correlation, and a relational expression 46 when the relationship between KPIs can be formulated.

  FIG. 3 is an example of a KPI causal model diagram drawn by the KPI causal model display control unit 22 in the causal model area 62 in the screen 60 using the KPI causal model information 20. Each KPI is drawn as a node 50, and the relationship between KPIs is drawn as an arrow 51 (edge) from the cause KPI to the result KPI. Note that the KPI in the KPI causal model of the present embodiment is not only a business evaluation index such as shipping labor cost and shipping man-hours, but also shelf arrangement and shipping instruction contents that cause these indexes. The concept includes an index that indicates the business status of the company.

  The KPI causal model information 20 is information representing the causal relationship of the KPI, and an on-site manager or a data analyst who knows the details of the work regarding the KPI related to the work for verifying the effect using the work data can display the image display device. 1 is created in advance using the function of the KPI causal model editing processing unit 25 or the KPI causal model creation device 12, the storage unit 5 of the image display device 1, the storage unit of the KPI causal model creation device 12, and the business data server 10. Save to etc.

  FIG. 4 shows an example of a screen 60 displayed on the display unit 3. In the screen 60, a toolbar area 61 having a menu list and icons for a user to operate, a causal model area 62 displaying a KPI causal model, a parallel coordinate plot area 63 displaying a parallel coordinate plot, and other arbitrary information. The information display area 64 is displayed. The screen layout control unit 24 manages the necessity and layout of these areas.

  Next, an example of a flow in which a user makes a business determination based on business data using the image display apparatus 1 according to the present embodiment will be described with reference to FIG. Here, the user is assumed to be a site manager who verifies the effect of the business improvement measures. In addition, as a specific content of the effect verification, it is assumed that the work improvement measure of changing the shelf arrangement of the work target space evaluates the effect given to the goal of work man-hour reduction.

  The user selects a KPI causal model to be analyzed from the list of KPI causal model information 20 stored in the storage unit 5 of the image display device 1 (S100). Next, based on the selected KPI causal model information 20, the KPI causal model display control unit 22 draws a KPI causal model in the causal model region 62 in the screen 60 of the display unit 3 (S102).

  The displayed KPI causal model is a KPI (hereinafter referred to as “KPI 70 of interest”) that is directly modified by the user using a device such as a mouse of the input unit 2 and an evaluation target KPI (hereinafter referred to as evaluation). KPI 71 ”is selected (S104). Based on this selection, the KPI classification processing unit classifies the KPI group into three groups of A, B, and C (S106), and the KPI causal model display control unit 22 changes the color of the corresponding node according to the classification, The display on the screen is updated (S108) (FIG. 6). Here, group A is a group of KPIs that exist on the causal path from 72 attention KPI 70 to evaluation KPI 71, and group B73 is not on the result path that originates from attention KPI 70, but the cause that leads to evaluation KPI 71. A group of KPIs existing on the route, and a group C74 is a group of other KPIs not belonging to the group A and the group B. The classification process in S106 will be described in detail later.

  Next, in order to visualize the effect of the noticed KPI 70 on the evaluation KPI 71, a KPI to be drawn as an axis on the parallel coordinate plot is selected from the group A 72 on the causal path from the notice KPI 70 to the evaluation KPI 71. Group A'88. Further, in order to particularly suppress the influence on the evaluation KPI, the KPI to be drawn as an axis on the parallel coordinate plot is selected from the group B73 having no causal relationship with the attention KPI, and is set as a group B′89 (S110). At this time, the selection method of the group A ′ 88 may be selection by the user, or may be automatic selection by the KPI classification processing unit 27 using some criteria such as the strength of correlation with the evaluation KPI 71 and the magnitude of fluctuation of the KPI value. The selection method for the group B'89 may be to select a terminal KPI that is not the result of another KPI as an initial value, and to change the selection by a user operation.

  Further, referring to the KPI information 35 relating to each KPI, KPIs that have no associated data presence flag 37 and cannot be plotted on the axes of the parallel coordinate plot are removed from the group A'88 and the group B'89. Further, the KPIs of the group B′89 are sorted in the order of the strength of correlation with the evaluation KPI 71 (S112), and the data narrowing operation is performed in accordance with the order.

  Next, the parallel coordinate plot display control unit 23 draws an axis corresponding to each KPI in the parallel coordinate plot area in the order of the attention KPI 70, group A'88, evaluation KPI 71, and group B'89 (S114). As data to be plotted on this axis, the user selects a plurality of data sets from the business data, and automatically or manually assigns the color of the plot line corresponding to each data set (S116).

  In this embodiment, one plot line is drawn per day using the daily business data. Data sets of two different periods are prepared before and after the business improvement measures, and the period designation and color assignment work of each data set by the user is performed in an interactive manner using the information display area 64 in the screen 60 and the like.

  For each plot line, the values on each KPI axis refer to the related data presence / absence flag 37, the related data location information 38, the cause KPI name 39, and the calculation method 40 included in the KPI information 35. The data selection processing unit 28 calculates using The calculated value is plotted on each KPI axis based on a predetermined scale such as a nominal scale or a proportional scale.

  FIG. 7 shows an example of the parallel coordinate plot drawn in the parallel coordinate plot area 63 in the screen 60 by the parallel coordinate plot display control unit 23 as a result of performing the processing so far. Each axis 82 of the parallel coordinate plot corresponds to the target KPI 70, the KPI of the group A'88, the evaluation KPI 71, and the KPI of the group B'89. In the upper part, a node corresponding to each KPI and an arrow 80 indicating a causal relationship between the KPIs are displayed. If there is no direct causal relationship at this time, but the connection is indirectly made through a causal route, the appearance of the arrow 81 is changed to indicate that there is an indirect causal relationship.

  In FIG. 7, the shelf arrangement which is the attention KPI 70 at the left end is different before and after the implementation of the business improvement measures, and whether the distribution of the value on the axis of the shipping work manpower which is the evaluation KPI 71 is different before and after the implementation. To verify. At this time, the distribution on the axis of the evaluation KPI may include a difference caused by the variation of the KPI belonging to the group B′89 on the right side of the evaluation KPI. In order to suppress this, the group B′89 Each data set is narrowed down by setting a restriction on the range of KPI values.

  As an initial value of the narrowing range of the data set, the data selection processing unit 28 determines a range centered on the median or mode in descending order of correlation with the evaluation KPI 71 in the group B′89 (S118). The parallel coordinate plot display processing unit 23 updates the drawing content of the parallel coordinate plot area 63 on the screen 60 using only the data included in the range (S120). At this time, an appropriate range is determined so that the minimum number of data set in advance for each data set remains.

  An example of a parallel coordinate plot after narrowing down is shown in FIG. The rectangle 85 on the axis of the KPI belonging to the group B′89 is the data range after the narrowing down, and data outside this range is not displayed on the screen.

  Next, for each data set, the statistic calculation processing unit 29 calculates a statistic indicating a distribution state of values on the axis of the evaluation KPI 71 (S122). Here, the statistic includes an average value, variance, median value, mode value, minimum value, maximum value, quartile, and the like. In FIG. 8, the ellipses 86 and 87 on the evaluation KPI axis indicate the distribution range surrounded by the minimum value and the maximum value of each data set.

  The user may change the range of the data range 85 after the narrowing on the KPI axis included in the group B′89 in the screen by using a device such as a mouse of the input unit 2 (S124). ). When the range is changed, the parallel coordinate plot display update (S120) and the statistic calculation (S122) are performed again.

  Finally, the user confirms whether there is a difference between the data sets from the statistics of the data on the evaluation KPI axis and the shapes of the plot lines 82 and 83 with respect to the KPI axes included in the group A ′ (S126).

  In the case of the present embodiment, the distribution range on the evaluation KPI axis of the data set after the implementation is different from the distribution range on the KPI axis of the data set before the implementation for the data set before and after the implementation of the business improvement measure, If the average value, median value, or mode value moves in the desired direction, it is determined that the business improvement measures have been effective.

  Next, a method of classifying KPIs of the KPI causal model into three groups will be described in detail with reference to FIG. When the user selects the attention KPI 70 and the evaluation KPI 71 (S104), the KPI classification processing unit 27 selects the attention KPI 70, and then selects one KPI whose group is not classified by the KPI that is the result of the attention KPI 70 (S132, S134). Next, the KPIs resulting from the selected KPI are sequentially traced to determine whether or not the evaluation KPI 71 is reached (S136). At this time, if the evaluation KPI 71 is reached, the KPI is classified as a group A 72 as being on the causal path of the attention KPI 70 and the evaluation KPI 71 (S138). Classification into group D, which is a typical provisional classification (S140). Further, if there is an unclassified KPI resulting from the selected KPI, that KPI is selected (S132, S134), and the same processing is performed.

  After all the KPIs on the path of the result of the attention KPI 70 have been classified, all the unclassified KPIs included in the KPI causal model are classified into the group D (S142). Next, one KPI belonging to group D is selected (S144, S146), and it is determined whether or not the evaluation KPI 71 is reached by following the route of the result of the selected KPI (S148). At this time, when the evaluation KPI 71 is reached, the KPI is not on the route of the result of the attention KPI 70, but is classified as a cause of the evaluation KPI 71 into the group B73 (S150). Are classified into group C (S152). The processing from S144 to S152 is performed until there is no KPI classified into the group D. When all the KPIs are classified into any one of the groups A, B, and C, each KPI in the causal model area 62 in the screen 60 is displayed. The nodes indicating are color-coded according to the classification, and the display contents are updated (S108).

  Next, another embodiment of the present invention will be described with reference to FIG. The image display client 93 is a computer system having the input unit 2, the display unit 3, and the communication unit 4, and is connected to the image display server 90 via the network 13.

  The image display server 90 also has a function as a so-called Web server, and includes a communication unit 4, a storage unit 5, and a control unit 6 having the same functions as the image display device 1, but the input unit 2 in the image display device 1. The display unit 3 is not essential, and the screen layout control unit 91 has a function of outputting information necessary for the user to generate the screen 60 for performing data analysis using the image display client 93. The communication unit 4 performs processing corresponding to HHTP communication. Further, the operation information performed by the user using the input unit 94 of the image display client 93 is received by the communication unit 4 of the image display server 90 via the network 13, and the control unit 6 performs calculation processing and screen processing, and the image display client 93. The information for updating the screen 60 is output from the communication unit 4 to the image display client 93.

  With the above configuration and processing, the user visually grasps the effect of the attention KPI on the value of the evaluation KPI using multiple data sets with different conditions, such as before and after the implementation of the business improvement measure, and determines the effect of the measure This makes it easier to make business decisions.

1: Image display device 3: Display unit 4: Communication unit 5: Storage unit 6: Control unit 20: KPI causal model information 21: Screen processing unit 22: KPI causal model display control unit 23: Parallel coordinate plot display control unit 24: Screen layout control unit 26: calculation processing unit 27: KPI classification processing unit 28: data selection processing unit 29: statistic calculation processing unit 35: KPI information 42: inter-KPI information 60: screen 62: causal model area 63: parallel coordinate plot Area 70: Featured KPI
71: Evaluation KPI
85: Data narrowing range 90: Image display server 93: Image display client

Claims (8)

A storage unit that records graph data composed of nodes of index values related to business and edges indicating relationships between the plurality of index values, and actual value data composed of actual values of the plurality of index values;
An input unit that receives input of information for selecting a first index value and a second index value among the plurality of index values;
A first group of one or more index values located on a path between the first index value and the second index value; and an index value not belonging to the first group, A controller that is connected to one index value at one or more edges and determines a second group of one or more index values that affect the determination of the first index value;
In the coordinate system in which the coordinate axes of the first and second index values and the coordinate axes of some or all of the index values belonging to the first and second groups are arranged in parallel, the second An image display system comprising: a display unit for displaying a parallel coordinate plot diagram in which the actual value data whose index value indicates a first value and a second value is plotted. The image display system according to claim 1,
The input unit accepts an input of a possible range of index values belonging to the second group;
The display unit plots the actual value data in which the actual values of the index values belonging to the second group belong to the range. The image display system according to claim 2,
The image display system, wherein the input unit receives an input of a range that the index value can take within a range in which the number of the actual value data plotted by the display unit does not become a predetermined value or less. The image display system according to claim 2,
The image display system, wherein the display unit determines an arrangement order of the coordinate axes based on a strength of correlation between the index values. An image display method for displaying a parallel coordinate plot diagram,
Record graph data composed of index value nodes related to business and edges indicating the relationship between the plurality of index values, and actual value data composed of actual values of the plurality of index values;
Receiving an input of information for selecting a first index value and a second index value among the plurality of index values;
A first group of one or more index values located on a path between the first index value and the second index value; and an index value not belonging to the first group, Determining a second group of one or more index values connected to one index value at one or more edges and affecting the determination of the first index value;
In the coordinate system in which the coordinate axes of the first and second index values and the coordinate axes of some or all of the index values belonging to the first and second groups are arranged in parallel, the second An image display method characterized by displaying a parallel coordinate plot diagram in which the actual value data whose index values indicate a first value and a second value are plotted. The image display method according to claim 5,
Receiving an input of a possible range of index values belonging to the second group;
The image display method characterized by plotting the actual value data in which the actual values of the index values belonging to the second group belong to the range. The image display method according to claim 6,
The image display system, wherein the input unit receives an input of a range that the index value can take within a range in which the number of the actual value data plotted by the display unit does not become a predetermined value or less. The image display method according to claim 6,
The image display method, wherein the display unit determines an arrangement order of the coordinate axes based on a correlation strength between the index values.

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