Information processing device and program

Abstract

To provide an information processing device and a program that are capable of supporting creation of a key performance indicator (KPI) tree.SOLUTION: An information processing device supports creation of tree data in which a relationship of a node indicating a management problem and a node indicating measures concerning the problem is hierarchically set. The information processing device includes: a storage unit that stores the tree data; and output means that outputs, when required, support information indicating a relationship between the problem and the measures which is derived based on the tree data stored in the storage unit.SELECTED DRAWING: Figure 40

Description

Technical Field

[0001] Embodiments of the present invention relate to an information processing apparatus and a program.

Background Art

[0002] At a site such as a store, various business services (hereinafter also referred to as services) are being carried out. At such a site, by using methods such as the KPI (Key Performance Indicator) tree method and BPMN (Business Process Model and Notation), the processing procedures of each element related to the implementation of the service may be designed as a business process. For example, conventionally, a technique has been proposed that can automatically create a business process so that the input / output relationships between adjacent operations are continuous.

[0003] By the way, the KPI tree represents various elements as nodes, and arranges the nodes in a tree shape for visualization, and is used for relationships between elements, identification of elements, etc. Also, in the KPI tree, a user can set an arbitrary item (hereinafter also referred to as a node name) for a node. However, it is not easy to create a KPI tree, and a technique that can support the creation is desired.

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problem to be solved by the present invention is to provide an information processing apparatus and a program capable of supporting the creation of a KPI tree.

Means for Solving the Problems

[0005] The information processing apparatus according to the embodiment is an information processing apparatus that supports the creation of tree data in which the relationship between nodes indicating management issues and nodes indicating measures for the issues is hierarchically set in a tree structure, and includes a storage unit that stores the tree data, and output means that outputs support information indicating the relationship between issues and measures, derived based on the tree data stored in the storage unit in response to a request.

Brief Description of Drawings

[0006]

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Embodiments for Carrying Out the Invention

[0007] Hereinafter, embodiments will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments described below.

[0008] [First Embodiment] FIG. 1 is a diagram showing a configuration example of a business support system according to the present embodiment. As shown in FIG. 1, the business support system 1 includes a terminal device 10 and a server device 20. The terminal device 10 and the server device 20 are communicably connected via a network N such as a LAN (Local Area Network).

[0009] The terminal device 10 is a terminal device used by a user of the business support system 1. The terminal device 10 executes various processes according to a user's operation. For example, the user operates the terminal device 10 to access the server device 20, thereby using various functions provided by the server device 20. The terminal device 10 can be realized by a stationary terminal device such as a PC (Personal Computer), or a portable terminal device such as a notebook PC, a tablet terminal, or a smartphone.

[0010] The server device 20 is an example of an information processing device. The server device 20 provides various functions to the terminal device 10. For example, the server device 20 provides functions such as creating and browsing a KPI tree and a business flow, which will be described later.

[0011] In the present embodiment, an example in which the server device 20 is realized by a single information processing device will be described, but the present invention is not limited thereto. For example, the server device 20 may be realized by a plurality of information processing devices by means of technologies such as cloud computing.

[0012] Next, the configurations of the terminal device 10 and the server device 20 described above will be described.

[0013] FIG. 2 is a diagram showing an example of the hardware configuration of the terminal device 10. As shown in FIG. 2, the terminal device 10 includes computer components such as a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, and a RAM (Random Access Memory) 13.

[0014] The CPU 11 is an example of a processor and comprehensively controls each part of the terminal device 10. The ROM 12 stores various programs. The RAM 13 is a workspace for developing programs and various data.

[0015] In addition, the terminal device 10 includes a display unit 14, an operation unit 15, a storage unit 16, and a communication unit 17.

[0016] The display unit 14 is composed of a display device such as an LCD (Liquid Crystal Display). The display unit 14 displays various information under the control of the CPU 11. The operation unit 15 has a keyboard, a pointing device, etc. The operation unit 15 outputs the operation content received from the user to the CPU 11. Note that the operation unit 15 may be a touch panel provided on the display screen of the display unit 14.

[0017] The storage unit 16 is composed of a storage medium such as an HDD (Hard Disk Drive) or a flash memory, and maintains the stored content even when the power is turned off. The storage unit 16 stores programs that can be executed by the CPU 11 and various setting information. For example, the storage unit 16 stores application programs such as a web browser that can utilize various functions provided by the server device 20.

[0018] The CPU 11 operates according to the programs stored in the ROM 12 and the storage unit 16 and developed in the RAM 13, thereby executing various processes.

[0019] The communication unit 17 is a communication interface that can be connected to the network N. The communication unit 17 communicates with external devices such as the server device 20 via the network N.

[0020] Figure 3 is a diagram showing an example of the hardware configuration of the server device 20. As shown in Figure 3, the server device 20 includes a computer configuration such as a CPU 21, a ROM 22, and a RAM 23.

[0021] The CPU 21 is an example of a processor and comprehensively controls each part of the server device 20. The ROM 22 stores various programs. The RAM 23 is a workspace for expanding programs and various data.

[0022] In addition, the server device 20 includes a display unit 24, an operation unit 25, a storage unit 26, and a communication unit 27.

[0023] The display unit 24 is composed of a display device such as an LCD. The display unit 24 displays various information under the control of the CPU 21. The operation unit 25 has a keyboard, a pointing device, etc. The operation unit 25 outputs the operation content received from the user to the CPU 11. Note that the operation unit 25 may be a touch panel provided on the display screen of the display unit 24.

[0024] The storage unit 26 is composed of a storage medium such as an HDD or a flash memory, and maintains the stored content even when the power is turned off. The storage unit 26 stores programs that can be executed by the CPU 21 and various setting information. For example, the storage unit 26 stores web application programs and the like that can provide various functions to the terminal device 10. The CPU 21 operates according to the programs stored in the ROM 22 and the storage unit 26 and expanded in the RAM 23, thereby executing various processes.

[0025] In addition, the storage unit 26 stores a KPI tree DB 261, a business flow DB 262, a temporary registration table 263, an item master 264, and a grouping master 265, etc.

[0026] The KPI tree DB261 is an example of a storage unit. The KPI tree DB261 is a table or database for storing and managing a KPI tree. Here, the KPI tree is tree-structured data in which the relationship between the management goals of an organization or enterprise and the measures for achieving those goals is hierarchically set by nodes. Also, the KPI tree can be rephrased as tree data in which the relationship between the management issues of an organization or enterprise and the measures for those issues is hierarchically set by nodes. In this embodiment, the KPI tree will be described as defining the relationship between goals and measures, but it may be defined as defining the relationship between issues and measures.

[0027] FIG. 4 is a diagram showing an example of the data configuration of the KPI tree DB261. As shown in FIG. 4, the KPI tree DB261 stores a customer name and a KPI tree, etc., in association with a tree ID that can identify the KPI tree.

[0028] In the item of the customer name, information that can identify the customer to which the KPI tree is applied is registered. Also, in the item of the KPI tree, actual data of the KPI tree (hereinafter also referred to as a data file) or an address indicating the storage destination of the data file, etc. is registered.

[0029] The KPI tree is created using a method such as KPI (Key Performance Indicator). The KPI tree can be represented in a visualized state, for example, as shown in FIG. 5.

[0030] FIG. 5 is a diagram showing an example of a visualized state of the KPI tree. Note that FIG. 5 shows a visualized state of the KPI tree applied to the customer name "ABC Supermarket" shown in FIG. 4.

[0031] As shown in FIG. 5, the KPI tree is composed of a plurality of nodes connected in a tree structure. Here, the final target node A, which is the topmost root node, is a node for setting the target to be achieved. The final target node A corresponds to, for example, a KGI (Key Goal Indicator). For example, when the final target is to improve the sales of a store, the node name such as "sales" indicating the target content is set in the final target node A.

[0032] One or more intermediate target nodes B are connected to the final target node A. Also, it is possible to connect one or more intermediate target nodes B to the intermediate target node B. In the intermediate target node B, a node name representing an intermediate target for achieving the target (final target or intermediate target) set in the directly above node is set. The intermediate target node B corresponds to, for example, a KPI (Key Performance Indicators).

[0033] FIG. 5 shows an example in which, below the final target node A, an intermediate target node Ba with the improvement of the number of customers visiting the store set as the target content of the intermediate target and an intermediate target node Bb with the improvement of the average customer unit price set are arranged. Also, below the intermediate target node Bb, an example in which an intermediate target node Bc with the node name representing the improvement of the number of sales points set as the target content of the intermediate target and an intermediate target node Bd with the node name representing the improvement of the unit price of a single product set are arranged is shown.

[0034] Also, in the KPI tree, it is possible to arrange a factor node C representing a factor for realizing the intermediate target set in this intermediate target node B below the intermediate target node B. The factor node C corresponds to, for example, a KSF (Key Success Factor).

[0035] In Fig. 5, an example is shown in which factor nodes Ca to Cd with node names of "quality improvement", "product assortment", "sales floor", and "promotion" are arranged below the intermediate target node Ba as factors for realizing an increase in the number of customers visiting the store. Also shown is an example in which factor nodes Ce and Cf with node names of "sales promotion" and "impulse buying" are arranged below the intermediate target node Bc as factors for realizing an increase in the number of sales points. Further, an example is shown in which a factor node Cg with the node name of "improvement in customer understanding" is arranged below the intermediate target node Bb as a factor for realizing an increase in the average customer unit price.

[0036] Also, in the KPI tree, it is possible to arrange a solution node D representing a solution method for realizing (solving) the intermediate target or factor set in the immediately above node below the intermediate target node B or the factor node C.

[0037] In Fig. 5, an example is shown in which solution nodes Da and Db with node names of "store information visualization" and "product assortment optimization" are arranged below the factor nodes Ca to Cc. Also shown is an example in which solution nodes Dc to De with node names of "coupon issuance", "point management", and "POP creation" are arranged below the factor node Ce. Further, an example is shown in which a solution node Df with the node name of "CRM (Customer Relationship Management)" is arranged below the factor node Cg.

[0038] Also, in the KPI tree, it is possible to arrange a service node E representing a specific service for realizing the factor or solution method set in the immediately above node below the factor node C or the solution node D. Here, the service node E is located at the end of the tree structure and becomes a specific measure for realizing the factor or solution method set in the immediately above node.

[0039] FIG. 5 shows an example in which a service node Ea with the node name of "Service A" is arranged below the solution node Dc.

[0040] Each node constituting the KPI tree is assigned a node ID for identifying each of them. Also, information regarding the corresponding node is stored in association with the node ID. For example, for nodes such as the final target node A (KGI) and the intermediate target node B (KPI), a node name indicating the content of the target (or issue), a unit of the index value for measuring the achievement of the target, a calculation formula for deriving the index value, etc. are set. In addition, for the service node E, a node name indicating the content of the service to be implemented, a business flow related to the implementation of the service, a verification item related to the verification of the service effect, etc. are associated. Hereinafter, the node name, the unit of the index value, the calculation formula, etc. set for the node are also referred to as the attributes of the node.

[0041] The above-described KPI tree is stored in, for example, JSON (JavaScript Object Notation) format. Note that the storage format of the KPI tree is not limited to JSON, and it may be stored in other data formats such as XML (Extensible Markup Language).

[0042] Returning to FIG. 3, the business flow DB262 is a table or database for storing and managing business flows. A business flow is a data file described as a series of procedures in which each element related to the execution of a business and the execution content executed by the element are connected. Specifically, in the business flow, for each element related to the implementation of a service, the execution content and procedures executed by the element are described.

[0043] FIG. 6 is a diagram showing an example of the data configuration of the business flow DB262. As shown in FIG. 6, the business flow DB262 stores by associating a target service, a flow ID, a business flow name, and a data file.

[0044] In the item of the target service, information specifying the service corresponding to the business for which the business flow is to be described is registered. Specifically, the node ID of the service node E specified for the target service, the tree ID of the KPI tree to which the service node E belongs, etc. are registered. Note that the method of specifying the target service is not limited to this.

[0045] In the item of the flow ID, a flow ID that can identify the business flow is registered. In the item of the business flow name, information indicating the name of the business flow is registered. For example, in the business flow name, the name of the service implemented by the business flow (the node name of the service node E), etc. are set. Also, in the item of the data file, the data file of the business flow or an address indicating the storage destination of the data file, etc. are registered.

[0046] The business flow is created using methods such as a flowchart or BPMN (Business Process Modeling Notation). The business flow is created according to the service content, but when the service content is common or similar, it is also possible to use the same business flow even if the KPI trees are different. Fig. 6 shows an example in which the business flow with the flow ID "F01" is used in the service node Ea included in each of the KPI trees with the tree IDs T01 and T02.

[0047] The business flow is created using methods such as a flowchart or BPMN (Business Process Modeling Notation). The business flow can be represented in a visualized state, for example, as shown in Fig. 7.

[0048] Fig. 7 is a diagram showing an example of the visualized state of the business flow. Note that Fig. 7 is an example of the business flow related to the service node Ea (Service A) of the KPI tree shown in Fig. 5.

[0049] As shown in FIG. 7, in the business process, between the start event ST and the end event EN, a series of operation (or processing) contents related to the execution of Service A are described for each element that performs the operation. In the business process of FIG. 7, an example is shown in which "customers" who come to the store, "surveillance cameras" and "payment systems" installed in the store, and "store clerks" who work in the store are described as elements.

[0050] Here, the "surveillance camera" is an example of a hardware resource and is installed at multiple locations in the store, for example. Also, the "payment system" is an example of a software resource and is realized by the cooperation of a plurality of PCs (Personal Computers) such as POS and applications introduced into the PCs. Note that, for example, services additionally performed along with payment (for example, point services) may be included in the business process. Hereinafter, the hardware resources, software resources, and additionally performed services related to the execution of the target service are also collectively referred to as "elements".

[0051] In the business process of FIG. 7, first, as the flow of "customers", coming to the store (step Qa), selecting a product to be purchased (step Qb), and moving to the cashier (step Qc) are described. Also, as the flow of the "surveillance camera" installed in the store, photographing the "customers" heading to the cashier (step Qd) and transmitting the photographed data to the payment system installed in the store (step Qe) are described. Also, as the flow of the "payment system", receiving the photographed data from the "surveillance camera" (step Qf) and displaying customer information such as the attributes of the "customers" derived from the photographed data on the display device (step Qg) are described.

[0052] Also, as the flow of the "store clerk" operating the cashier, checking the customer information displayed by the "payment system" (step Qh) and performing the cashier operation for the products brought in by the "customers" (step Qi) are described. Also, along with the cashier operation of the "store clerk", it is described that the "payment system" executes the "payment process" (step Qj).

[0053] Also, it is described that the "customer" pays the price of the product according to the "payment process" of the "payment system" (step Qk) and leaves the store from the store (step Ql). And it is described that the "payment system" stores data indicating the breakdown of this transaction along with the payment of the price (step Qm).

[0054] In addition, when implementing the coupon service, for example, the payment system issues a coupon that gives a discount or reduction according to the product purchased in the payment process or the amount of the price, and stores the number of issued coupons daily. Also, for example, the payment system gives a discount or reduction from the price of the product according to the coupon presented during the payment process, and stores the number of used coupons daily.

[0055] Also, when implementing the point service, for example, the payment system identifies the member number of the "customer" represented in the captured data by comparing the captured data received in step Qf with the face images of each member registered in advance. Then, the payment system accumulatively stores the points issued according to the purchase amount in association with the identified member number.

[0056] The above-described business flow is stored in, for example, JSON format. Note that the storage format of the business flow is not limited to JSON, and it may be stored in other data formats such as XML.

[0057] Also, in this embodiment, the KPI tree and the business flow may be those created in advance, or may be those created via the terminal device 10 or the like with the server device 20 providing creation support. In the latter case, for example, the server device 20 provides a screen (GUI (Graphical User Interface)) for supporting the browsing, creation, and editing of the KPI tree and the business flow to the terminal device 10.

[0058] Specifically, the server device 20 provides a terminal device 10 with a screen that can be created and edited while visualizing various nodes and the relationships between the nodes. Then, when the creation or editing of the KPI tree is completed, the server device 20 stores the KPI tree in the KPI tree DB 261.

[0059] In addition, when any service node E included in the KPI tree is selected, the server device 20 provides a screen that enables the creation and editing of a business flow and a checklist for the service corresponding to the service node E. Then, when either the business flow or the checklist is created, the server device 20 stores it in the corresponding DB in association with the node ID and tree ID of the service node E.

[0060] Returning to FIG. 3, the provisional registration table 263 is a table or database for storing and managing combinations of node names and node types among the nodes included in the KPI tree that are not registered in either the item master 264 or the grouping master 265. The provisional registration table 263 has, for example, the data configuration shown in FIG. 8.

[0061] FIG. 8 is a diagram showing an example of the data configuration of the provisional registration table 263. As shown in FIG. 8, the provisional registration table 263 stores by associating a node name, a node type, a KPI tree link, a data creation date, and the like.

[0062] The node name and node type are registered with the node name and node type of the node (hereinafter also referred to as the target node) to be registered in the provisional registration table 263.

[0063] FIG. 8 shows an example in which a combination of a node name "Sales" and a node type "KGI" is registered. Similarly, examples in which combinations of a candidate node name "Average customer unit price" and a node type "KPI", a candidate node name "Attractive product lineup" and a node type "Factor (KSF)", and a candidate node name "Inventory turnover rate" and a node type "KPI" are registered are shown.

[0064] In the KPI tree link, information that can identify the KPI tree to which the target node belongs is registered. For example, in the KPI tree link, the tree ID of the KPI tree and the like are registered. Also, in the KPI tree link, together with the tree ID of the KPI tree to which the target node belongs, information that can identify the target node (for example, node ID) may be registered. On the data creation date, data indicating the year, month, and day registered in the temporary registration table 263 is stored.

[0065] Returning to FIG. 3, the item master 264 is a table or database for storing and managing the reference node name used as the basis for name matching. The item master 264 has, for example, the data configuration shown in FIG. 9.

[0066] FIG. 9 is a diagram showing an example of the data configuration of the item master 264. As shown in FIG. 9, the item master 264 stores by associating the reference node name, node type, KPI tree link, data creation date, and the like.

[0067] In the reference node name, the node name used as the basis for name matching (hereinafter also referred to as the reference node name) is registered. Also, in the node type, the node type of the node corresponding to the reference node name (hereinafter also referred to as the reference node) is registered.

[0068] FIG. 9 shows an example in which a set with the reference node name "sales" and the node type "KGI" is registered. Similarly, examples in which a set of the reference node name "number of customers visiting the store" and the node type "KPI", a set of the reference node name "average customer price" and the node type "KSI", and a set of the reference node name "product assortment" and the node type "Factor" are each registered are shown.

[0069] In the KPI tree link, information that can identify the KPI tree to which the reference node belongs is registered. For example, in the KPI tree link, the tree ID of the KPI tree and the like are registered. Also, in the KPI tree link, together with the tree ID of the KPI tree to which the reference node belongs, information that can identify the reference node (for example, node ID) may be registered. On the data creation date, data indicating the year, month, and day registered in the item master 264 is stored.

[0070] Returning to FIG. 3, the naming master 265 is a table or database for storing and managing the correspondence relationship between the naming source node name and the naming destination node name. The naming master 265 has, for example, the data configuration shown in FIG. 10.

[0071] FIG. 10 is a diagram showing an example of the data configuration of the naming master 265. As shown in FIG. 10, the naming master 265 stores by associating the node name, node type, reference node name, data creation date, etc.

[0072] The naming source node name is registered in the node name. The naming destination reference node name is registered in the reference node name. The node type for which naming is to be performed is registered in the node type. Data indicating the year, month, and day when registered in the naming master 265 is stored in the data creation date.

[0073] Here, the combination of the node name, node type, and reference node name functions as naming information that defines the naming rule. Specifically, the naming information defines that, under the conditions of the specified node type, the naming source node name is named (hereinafter also referred to as conversion) to the naming destination reference node name.

[0074] FIG. 10 shows an example in which a node with a node type of "KGI" and a node name of "sales amount" is set to be converted to a node name of "sales". Similarly, a node with a node type of "KPI" and a node name of "average customer unit price" is set to be converted to a node name of "customer unit price", a node with a node type of "Factor" and a node name of "attractive product lineup" is set to be converted to a node name of "product lineup", and a node with a node type of "KGI" and a node name of "sales" is set to be converted to a node name of "sales". Thereby, for example, nodes with node names of "sales amount" and "sales" can be treated as the same type of nodes as the node with the node name of "sales".

[0075] Note that the collating information may not be limited to the one-way conversion from the collation source to the collation destination, but may also define the reverse conversion of the node name from the collation destination to the collation source. In this case, for example, a node with a node type of "KGI" and a node name of "sales" is reversely converted to node names "total sales" and "revenue". That is, nodes with node names "sales", "total sales", and "revenue" can be treated as the same type of nodes.

[0076] Returning to FIG. 3, the communication unit 27 is a communication interface connectable to the network N. The communication unit 27 communicates with an external device such as the terminal device 10 via the network N.

[0077] Next, with reference to FIG. 11, the functional configurations of the terminal device 10 and the server device 20 will be described. FIG. 11 is a diagram showing an example of the functional configurations of the terminal device 10 and the server device 20.

[0078] As shown in FIG. 11, the terminal device 10 includes a display control unit 111 and an operation reception unit 112 as functional units.

[0079] Some or all of the functional units included in the terminal device 10 may be a software configuration realized by the cooperation of a processor (e.g., CPU 11) of the terminal device 10 and a program stored in a memory (e.g., ROM 12, storage unit 16). Also, some or all of the functional units included in the terminal device 10 may be a hardware configuration realized by a dedicated circuit or the like mounted on the terminal device 10.

[0080] The display control unit 111 of the terminal device 10 controls the display unit 14 to display various screens on the display unit 14. For example, the display control unit 111 causes the display unit 14 to display various operation screens based on the information provided from the server device 20.

[0081] The operation reception unit 112 of the terminal device 10 receives a user operation via the operation unit 15. For example, when the operation reception unit 112 receives an operation on the screen displayed on the display unit 14, it notifies the operation content to the server device 20.

[0082] On the other hand, the server device 20 includes a GUI providing unit 211, a design support unit 212, a name identification processing unit 213, a display control unit 214, an operation receiving unit 215, and a data analysis unit 216 as functional units.

[0083] A part or all of the functional units of the server device 20 may be a software configuration realized by cooperation between a processor (e.g., CPU 21) of the server device 20 and a program stored in a memory (e.g., ROM 22, storage unit 26). Also, a part or all of the functional units of the server device 20 may be a hardware configuration realized by a dedicated circuit or the like mounted on the server device 20.

[0084] The GUI providing unit 211 cooperates with other functional units to provide the terminal device 10 with information capable of displaying various operation screens (hereinafter also simply referred to as screens). Here, the GUI providing unit 211 may provide data representing the screens, or may provide various content data related to the display of the screens. Hereinafter, the provision of information related to the display of a screen by the GUI providing unit 211 to the terminal device 10 will also be expressed as "providing" the screen, or "displaying", "presenting", or "outputting" the screen.

[0085] The design support unit 212 cooperates with the GUI provision unit 211 to provide a screen for supporting the creation of a KPI tree and a business flow.

[0086] For example, the design support unit 212 provides a screen on which a KPI tree can be created by arranging various nodes, edges, and the like as drawing parts. On such a screen, a user can create or edit a tree-shaped KPI tree by arranging various nodes on the screen and arranging links that connect the nodes. When a KPI tree is created or edited, the design support unit 212 generates a data file representing the KPI tree and stores it in the KPI tree DB 261.

[0087] In addition, the Design Support Department 212 provides a screen that enables selection of a KPI tree to be viewed or edited based on the KPI tree DB 261. When a KPI tree is selected, the Design Support Department 212 reads out the data file of the KPI tree from the KPI tree DB 261 and provides a screen that visualizes the KPI tree.

[0088] In addition, the Design Support Department 212 provides a screen that enables creation of a business process by arranging drawing parts corresponding to the BPMN notation rules. For example, when the Design Support Department 212 receives an operation instruction to generate a business process (flow ID) for the service node E included in the KPI tree, it provides a screen for creating a business process. Then, when the Design Support Department 212 receives a completion operation for creating or editing a business process, it generates a data file representing the business process and stores it in the business process DB 262 in association with the target service.

[0089] In addition, the Design Support Department 212 displays a business process in response to a user operation. For example, when the service node E of the KPI tree is selected, the Design Support Department 212 visualizes the data file associated with the service node E to display the business process.

[0090] The Naming Process Department 213 executes processing related to naming of the node names of the nodes included in the KPI tree in cooperation with the GUI Provision Department 211 and the Design Support Department 212.

[0091] Specifically, when the KPI tree is created (or edited) with the support of the Design Support Department 212, the Naming Process Department 213 acquires the node name and node type from the nodes included in the KPI tree and registers them in the temporary registration table 263.

[0092] More specifically, the name matching processing unit 213 compares the set of node names and node types of each node included in the KPI tree with the set of node names and node types registered in the item master 264 and the name matching master 265. Next, the name matching processing unit 213 extracts, as target nodes, the nodes having the set of node names and node types not registered in the item master 264 and the name matching master 265 from the nodes of the KPI tree. Then, the name matching processing unit 213 acquires the node name and node type from the target nodes and registers them in the temporary registration table 263 together with the KPI tree link of the KPI tree to which the target nodes belong. Hereinafter, for the sake of convenience of explanation, the set of node names and node types registered in the temporary registration table 263 is also referred to as target nodes.

[0093] Here, the name matching processing unit 213 may limit the node type of the target nodes extracted from the KPI tree to the node types related to the specification of services such as KGI, KPI, and KSF. Thereby, since solution nodes and service nodes whose node names are represented by frequently used expressions can be excluded from the target of name matching, it is possible to prevent the name matching from being performed inadvertently.

[0094] Note that the timing for extracting the target nodes and registering them in the temporary registration table 263 is not particularly limited and can be arbitrarily set. For example, the name matching processing unit 213 may extract the target nodes from the KPI tree and register them in the temporary registration table 263 at the timing when the created (or edited) KPI tree is stored in the KPI tree DB 261. Also, for example, the name matching processing unit 213 may be configured to extract the target nodes from the KPI tree stored in the KPI tree DB 261 and register them in the temporary registration table 263 by batch processing such as once a day. Also, for example, the name matching processing unit 213 may be configured to extract the target nodes and register them in the temporary registration table 263 according to an instruction from a data administrator.

[0095] In addition, the name-matching processing unit 213 displays a screen (hereinafter also referred to as a provisional registration list screen) representing the registration status of the provisional registration table 263 at a predetermined timing. For example, the design support unit 212 displays the provisional registration list screen in response to an instruction from the data administrator.

[0096] FIG. 12 is a diagram showing an example of a screen provided by the server device 20, and shows an example of a provisional registration list screen. As shown in FIG. 12, the provisional registration list screen 30 has a display area 31 for list-displaying pairs of node names and node types registered in the provisional registration table 263.

[0097] The display area 31 has an ID, a node name, and a node type as data items. The ID is an identifier for managing each target node registered in the provisional registration table 263. For example, the ID is an ascending number assigned in the order of registration in the provisional registration table 263. The node name and node type display the node name and node type of the target node registered in the provisional registration table 263. Note that the provisional registration list screen 30 in FIG. 12 represents the registration status of the provisional registration table 263 described in FIG. 8.

[0098] In addition, a registration button 32 is provided on the provisional registration list screen 30. The registration button 32 is an operator for instructing registration to the item master 264 or the name-matching master 265. After a specific ID is selected from the display area 31 and the name-matching processing unit 213 receives an operation of the registration button 32, the name-matching processing unit 213 displays a screen (hereinafter also referred to as a registration screen) for registering the node name and node type of the target node corresponding to the selected ID in the item master 264 or the name-matching master 265.

[0099] FIG. 13 is a diagram showing an example of a screen provided by the server device 20, and shows an example of a registration screen. As shown in FIG. 13, the registration screen 40 has a first display area 41 and a second display area 42.

[0100] In the first display area 41, information about the target node selected on the provisional registration list screen 30 is displayed. Specifically, in the first display area 41, the node name and node type of the target node are displayed.

[0101] Also, in the first display area 41, a first display button 411 for instructing the display of the KPI tree is provided. When the name alignment processing unit 213 receives an operation of the first display button 411, it reads out the KPI tree to which the target node belongs from the KPI tree DB 261 based on the KPI tree link of the target node selected on the provisional registration list screen 30. Then, the name alignment processing unit 213, in cooperation with the design support unit 212 and the like, displays a screen representing the read KPI tree.

[0102] For example, the name alignment processing unit 213 may display the KPI tree with a screen configuration similar to that of FIG. 5. Also, the name alignment processing unit 213 may display the target node included in the KPI tree in an emphasized manner so as to be distinguishable from other nodes. Note that the screen representing the KPI tree may be switched and displayed with the registration screen 40, or may be displayed together with the registration screen 40.

[0103] In the second display area 42, information about the node names that are candidates for name alignment is displayed. Specifically, in the second display area 42, the reference node names of the name alignment candidates extracted from the item master 264 are displayed based on the node name and node type of the target node selected on the provisional registration list screen 30.

[0104] Here, the name-matching processing unit 213 extracts a reference node name of the name-matching candidate from the item master 264 based on the node type of the target node and the character string constituting the node name of the target node. Specifically, the name-matching processing unit 213 extracts a reference node name from the item master 264 that has the same node type as the target node and has a character string similar to the node name of the target node. For example, the name-matching processing unit 213 extracts, as a name-matching candidate, a reference node name whose similarity between character strings is equal to or higher than a threshold value (e.g., 80%). The method for calculating the similarity between character strings is not particularly limited, and for example, a known morphological analysis technique can be used.

[0105] In the above example, the extraction requirements for the name-matching candidate are that the node types are the same and the character strings of the node names are similar, but the extraction requirements are not limited to this.

[0106] For example, the structural similarity between the KPI tree to which the target node belongs and the KPI tree to which the reference node belongs may be used as an extraction requirement. As an example, the name-matching processing unit 213 may calculate the similarity between the characteristics of other nodes connected to the target node and the characteristics of other nodes connected to the reference node, and extract, as a name-matching candidate, the reference node name of the reference node whose similarity is equal to or higher than the threshold value. Here, the characteristics of other nodes may be either one or both of the node name and the node type. Also, the other nodes may be nodes connected to either one or both of the front and back of the target node and the reference node.

[0107] As another example, the name-matching processing unit 213 may calculate the similarity between the characteristics of other nodes existing from the target node to the KGI node and the characteristics of other nodes existing from the reference node to the KGI node, and extract, as a name-matching candidate, the reference node name whose similarity is equal to or higher than the threshold value.

[0108] As another example, the name-matching processing unit 213 may calculate the structural similarity between the entire KPI tree including the target node and the entire KPI tree including the reference node, and extract, as a name-matching candidate, the reference node name of the KPI tree whose similarity is equal to or higher than the threshold value.

[0109] In this way, by including the structural similarity of the KPI tree in the extraction requirements, it is possible to extract reference node names with similar roles within the KPI tree as name matching candidates. Therefore, the accuracy of the name matching candidates can be improved. Note that the above-mentioned extraction requirements may be applied individually or in combination. For example, together with the similarity in notation (string), the structural similarity of the KPI tree may be used as an extraction requirement to extract the reference node name.

[0110] FIG. 13 shows an example in which the reference node name "Sales" is extracted as a name matching candidate for the node name "Sales Amount" and node type "KGI" of the target node. Note that when the name matching processing unit 213 extracts a plurality of reference node names as name matching candidates, it displays them in a list in a selectable state. Also, when there is no reference node name corresponding to the name matching candidate, the name matching processing unit 213 leaves the second display area 42 blank as shown in FIG. 14.

[0111] Here, FIG. 14 is a diagram showing an example of a screen provided by the server device 20 and shows another example of the registration screen. The registration screen 40 in FIG. 14 shows a display example when there is no corresponding name matching candidate for the node name "Inventory Turnover Rate" and node type "KPI" of the target node.

[0112] Also, when a reference node name corresponding to the name matching candidate is extracted, a second display button 421 for instructing the display of the KPI tree is provided in the second display area 42. When the name matching processing unit 213 receives an operation of the second display button 421, it reads out the KPI tree to which the reference node belongs from the KPI tree DB 261 based on the KPI tree link stored in the item master 264 in association with the reference node name of the name matching candidate. Then, the name matching processing unit 213 collaborates with the design support unit 212 etc. to display a screen representing the read KPI tree.

[0113] For example, the clustering processing unit 213 causes a KPI tree to be displayed with the same screen configuration as that in FIG. 5. Further, the clustering processing unit 213 may display the reference nodes included in the KPI tree in a distinguishable state from other nodes by highlighting and representing them. Note that the screen representing the KPI tree may be switched and displayed with the registration screen 40, or may be displayed together with the registration screen 40. Further, it may be displayed in a state where it can be compared with the KPI tree of the target node.

[0114] In this way, on the registration screen 40, not only the reference node name of the clustering candidate is presented, but also there are operators for displaying the KPI tree of the target node and the KPI tree of the clustering candidate. Thereby, for example, the user of the terminal device 10 can determine a more appropriate reference node name as the clustering destination while comparing and checking the structures of the KPI tree of the target node and the KPI tree of the clustering candidate.

[0115] Further, the registration screen 40 has a pull-down menu 43 for selecting a registration destination and an execution button 44 for instructing the execution of registration. The pull-down menu 43 has the item master 264 and the clustering master 265 as selectable options and is an operator that can select either one of the masters.

[0116] When the clustering processing unit 213 receives the operation of the execution button 44 in a state where the item master 264 is selected from the pull-down menu 43, it registers the node name, node type, and KPI tree link of the target node in the item master 264. Thereby, the node name of the target node is registered in the item master 264 as a reference node name. For example, when the user assigns a new node name to the target node, by registering that node name as a reference node name in the item master 264, the reference node name can be used as a clustering candidate.

[0117] In addition, when the pinning processing unit 213 receives an operation of the execution button 44 in a state where the pinning master 265 is selected from the pull-down menu 43, the node name and node type of the target node are registered in the pinning master 265 in association with the reference node name of the pinning candidate. Specifically, the pinning processing unit 213 generates pinning information with the node name of the target node as the source node name for pinning and the reference node name of the pinning candidate as the destination reference node name for pinning. Then, the pinning processing unit 213 registers the generated pinning information in the pinning master 265. When there are a plurality of pinning candidates, the pinning processing unit 213 generates pinning information using the reference node name of one pinning candidate selected by the user.

[0118] Here, the pinning information registered in the pinning master 265 is used, for example, when analyzing the KPI tree based on the node name. That is, in the present embodiment, the node names set for each node of the KPI tree are maintained as they are, and the conversion of the node names based on the pinning information is performed in internal processing. Therefore, in the present embodiment, it is possible to eliminate fluctuations in the node names set in the KPI tree while maintaining the display form of the created KPI tree.

[0119] In the above description, the destination master can be selected via the pull-down menu 43. However, for example, when there are no pinning candidates (see FIG. 14), it is impossible to register in the pinning master 265. Therefore, when there are no pinning candidates, the registration destination selectable in the pull-down menu 43 may be only the item master 264.

[0120] Returning to FIG. 11, the display control unit 214 controls the display unit 24 to display various screens on the display unit 24. For example, the display control unit 214 causes the display unit 24 to display various screens provided by the GUI providing unit 211.

[0121] The operation reception unit 215 receives user operations via the operation unit 25. For example, when the operation reception unit 215 receives an operation on various operation support screens displayed on the display unit 24, it outputs the operation content to the CPU 21.

[0122] The data analysis unit 216 performs various analysis processes based on the KPI tree stored in the KPI tree DB 261.

[0123] For example, when a node name and a node type are specified by the user, the data analysis unit 216 searches the KPI tree DB 261 for a KPI tree including the specified combination of the node name and the node type, or aggregates the number of retrieved KPI trees (hereinafter also referred to as the tree number). Specifically, when a combination of a node name and a node type is specified, the data analysis unit 216 refers to the collation master 265 and determines whether collation information in which the specified combination of the node name and the node type is set exists.

[0124] Here, when collation information related to the specified combination of the node name and the node type exists and the specified node name is set as the collation destination, the data analysis unit 216 reads out the corresponding collation source node name from the collation information. Next, the data analysis unit 216 expands the node name to be searched by using the specified node name and the node name read from the collation information as search conditions. Next, the data analysis unit 216 searches the KPI tree DB 261 for a KPI tree including any of the expanded node names and including a node of the specified node type. Then, the data analysis unit 216 derives the tree ID and the tree number of the retrieved KPI tree as analysis results. For example, the data analysis unit 216 cooperates with the GUI providing unit 211 to display a screen showing the analysis results.

[0125] Also, when there is clustering information in which a specified set is set and the specified node name is set as the clustering source, the data analysis unit 216 reads the corresponding clustering destination node name from the clustering information. Also, when there is other clustering information including the specified node type and the set of the clustering destination node names, the data analysis unit 216 reads the clustering source node name set in the other clustering information, that is, other node names associated with the same reference node name. Next, the data analysis unit 216 expands the node name to be searched by using the specified node name and the node name read from the clustering information as search conditions. Next, the data analysis unit 216 searches the KPI tree DB 261 for a KPI tree that includes any of the expanded node names and includes nodes of the specified node type. Then, the data analysis unit 216 derives the tree ID and the number of trees of the searched KPI tree as analysis results.

[0126] In this way, even when there is a fluctuation in the node name, the data analysis unit 216 can analyze the KPI tree by using the node name of the corresponding relationship set in the clustering information of the clustering master 265, so that the analysis result can be obtained in a state where the fluctuation of the node name is eliminated.

[0127] Note that the analysis process performed by the data analysis unit 216 is not limited to the above example. However, when performing an analysis process based on the node name and the node type, the data analysis unit 216 shall perform the analysis process by using the node name in the corresponding relationship based on the clustering information of the clustering master 265.

[0128] Hereinafter, with reference to FIGS. 15 to 17, an operation example of the above-described server device 20 will be described. FIGS. 15 to 17 are flowcharts showing an example of a process executed by the server device 20.

[0129] First, with reference to FIG. 15, an example of a first registration process of registering a node name in the temporary registration table 263 will be described.

[0130] When the user creates (or edits) a KPI tree (step S11), the design support unit 212 stores the KPI tree in the KPI tree DB 261 (step S12).

[0131] Subsequently, the matching processing unit 213 compares the set of node names and node types of the nodes included in the KPI tree stored in the KPI tree DB 261 with the set of node names and node types registered in the item master 264 and the matching master 265. Next, the matching processing unit 213 extracts, as target nodes, the nodes having the set of node names and node types not registered in the item master 264 and the matching master 265 from the nodes included in the KPI tree (step S13).

[0132] Subsequently, when the matching processing unit 213 acquires the node name and the node type from the target node (step S14), it registers the acquired information in the temporary registration table 263 together with the KPI tree link of the KPI tree to which the target node belongs (step S15), and ends this processing.

[0133] Next, with reference to FIG. 16, an example of a second registration process for registering the node names registered in the temporary registration table 263 in the item master 264 or the matching master 265 will be described.

[0134] The matching processing unit 213 refers to the temporary registration table 263 according to an instruction from a data administrator or the like (step S21), and determines whether or not a node name is registered in the temporary registration table 263 (step S22).

[0135] When the node name of the target node is registered in the temporary registration table 263 (step S22; Yes), the matching processing unit 213 displays a temporary registration list screen 30 representing the registration state of the temporary registration table 263 (step S23). Next, the matching processing unit 213 waits until the registration button 32 is operated for any one of the target nodes from the temporary registration list screen 30 (step S24; No).

[0136] When the name matching processing unit 213 receives an operation of the registration button 32 (step S24; Yes), it extracts a reference node name that is a name matching candidate from the item master 264 based on the node name, node type, etc. of the selected target node (step S25). Next, the name matching processing unit 213 displays a registration screen 40 including the extraction result of step S25 (step S26).

[0137] Subsequently, the name matching processing unit 213 determines whether an instruction to register to the item master 264 has been received via the pull-down menu 43, the execution button 44, etc. (step S27). When an instruction to register to the item master 264 is received (step S27; Yes), the name matching processing unit 213 registers the node name, node type, and KPI tree link of the selected target node to the item master 264 (step S28), and proceeds to step S33.

[0138] Also, when the name matching processing unit 213 does not receive an instruction to register to the item master 264 (step S27; No), it determines whether an instruction to register to the name matching master 265 has been received (step S29). When an instruction to register to the name matching master 265 is received (step S29; Yes), the name matching processing unit 213 associates the node name and node type of the selected target node with the reference node name of the name matching candidate extracted in step S25 and registers them to the name matching master 265 (step S30), and proceeds to step S33. When there are multiple name matching candidates, the name matching processing unit 213 registers the reference node name of one selected name matching candidate to the name matching master 265.

[0139] Also, when the name matching processing unit 213 does not receive an instruction to register to the name matching master 265 (step S29; No), it determines whether display of the KPI tree has been instructed via the first display button 411, the second display button 421, etc. (step S31). When display of the KPI tree is instructed (step S31; Yes), the name matching processing unit 213 displays the corresponding KPI tree based on the KPI tree link related to the instructed node (step S32).

[0140] Next, for example, when the user instructs to stop the display of the KPI tree, the clustering processing unit 213 closes the display screen of the KPI tree and returns the processing to step S27. In the case of a configuration in which the registration screen 40 and the display screen of the KPI tree are displayed simultaneously, the processing may be returned to step S27 without waiting for an instruction to stop the display of the KPI tree. Also, when the display of the KPI tree is not instructed in step S31 (step S31; No), the clustering processing unit 213 returns the processing to step S27.

[0141] In the subsequent step S33, the clustering processing unit 213 deletes the data entry related to the target node registered in step S28 or step S30 from the temporary registration table 263 (step S33). Next, the clustering processing unit 213 returns the processing to step S22 to determine whether a node name is registered in the temporary registration table 263. Then, when the clustering processing unit 213 determines that the node name is not registered in the temporary registration table 263 (step S22; No), the present processing ends.

[0142] By the above processing, the node name and node type of the target node registered in the temporary registration table 263 will be registered in the item master 264 or the clustering master 265.

[0143] Next, with reference to FIG. 17, an example of the analysis processing of the KPI tree will be described. In this processing, an example in which the number of trees of the KPI tree including the specified node is output as an analysis result will be described, but the content of the analysis processing is not limited to this.

[0144] The data analysis unit 216 receives a designation of a node to be analyzed from the user (step S41). For example, when the KPI tree is displayed and any one of the nodes included in the KPI tree is designated as the analysis target, the data analysis unit 216 receives the designation of the node.

[0145] Subsequently, the data analysis unit 216 acquires the node name and node type from the designated node (hereinafter also referred to as the designated node) (step S42). Next, the data analysis unit 216 reads out the grouping information in which the acquired combination of the node name and node type is set from the grouping master 265 (step S43).

[0146] Subsequently, the data analysis unit 216 expands the search condition for the node name based on the alias of the designated node (the node name of the grouping source or destination) set in the grouping information (step S44). Next, the data analysis unit 216 searches the KPI tree DB 261 for a KPI tree including nodes that meet the condition based on the expanded node name and the node type of the designated node (step S45).

[0147] Then, the data analysis unit 216 outputs the number of trees of the KPI tree searched in step S45 as an analysis result (step S46), and ends this process.

[0148] As described above, the server device 20 of the present embodiment acquires the node name set for the node from the KPI tree and the node type of the node, and extracts a reference node name similar to the acquired combination of the node name and node type from the item master 264 that stores the set of the reference node name and node type serving as the grouping criterion. Then, the server device 20 generates grouping information in which the node name and node type acquired from the KPI tree are associated with the reference node name extracted from the item master 264, and registers it in the grouping master 265.

[0149] Thereby, in the server device 20, based on the grouping information stored in the grouping master 265, the node names of the nodes included in the KPI tree can be grouped. Further, thereby, in the server device 20, even if there is a variation in the node names between nodes intended to have the same content, for example, the analysis of the KPI tree can be performed in a state where the variation is eliminated, so that an accurate analysis result can be obtained. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0150] Further, the server device 20 extracts, as target nodes, nodes having a combination of a node name and a node type that are not registered in the item master 264 and the grouping master 265 among the nodes included in the KPI tree, and acquires the node name and the node type from the target nodes. Thereby, the server device 20 can hold existing settings registered as the reference node name or the name of the grouping source, and can also prevent duplicate registration, so that the generation of grouping information can be efficiently performed. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0151] Also, the server device 20 registers, in the item master 264, the combination of the node name and the node type selected by the user operation from among the combinations of the node name and the node type acquired from the KPI tree. Thereby, in the server device 20, since the reference node name can be added according to the instruction of the user, the convenience of the user can be improved. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0152] In addition, the server device 20 extracts from the item master 264 a reference node name having the same node type as that of the target node acquired from the KPI tree and a character string similar to the node name of the target node. Thereby, the server device 20 can extract a reference node name intended for the same content as the target node, so that the accuracy of grouping can be improved. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0153] In addition, the server device 20 compares the structure of the KPI tree to which the target node belongs with the structure of the KPI tree to which the node corresponding to the reference node name belongs, and extracts the reference node names related to the KPI trees with similar structures. As a result, the server device 20 can extract the reference node names of the nodes whose roles in the KPI tree are similar to those of the target node, so that the accuracy of name matching can be improved. Therefore, the server device 20 can improve the usability of the user related to the KPI tree.

[0154] [Second Embodiment] In the second embodiment, based on the configuration of the business support system 1 described above, a form capable of supporting the creation of nodes in the KPI tree will be described. In the following, the points different from the above-described embodiments will be mainly described, and detailed descriptions of the points common to the already described content will be omitted. In addition, in the present embodiment, the KPI tree will be described as defining the relationship between the goal and the measures, but it may be defined as defining the relationship between the problem and the measures.

[0155] FIG. 18 is a diagram showing an example of the hardware configuration of the server device 50 according to the present embodiment. As shown in FIG. 18, the server device 50 includes a computer configuration such as a CPU 21, a ROM 22, and a RAM 23, similar to the server device 20. In addition, the server device 50 includes a display unit 24, an operation unit 25, a storage unit 56, and a communication unit 27.

[0156] The storage unit 56 is composed of a storage medium such as an HDD or a flash memory, similar to the storage unit 26, and stores a KPI tree DB 261, a business flow DB 262, a temporary registration table 263, an item master 264, a name matching master 265, and the like. In addition, the storage unit 56 stores a node candidate table 561 and a temporary registration node candidate table 562.

[0157] The node candidate table 561 is a table or database for storing and managing information that defines the correspondence between the attributes of the upper nodes (hereinafter also referred to as upper nodes) in the KPI tree and the attributes of the lower nodes (hereinafter also referred to as lower nodes) connected to the upper nodes. The node candidate table 561 has, for example, the data configuration shown in FIG. 19.

[0158] FIG. 19 is a diagram showing an example of the data configuration of the node candidate table 561. As shown in FIG. 19, the node candidate table 561 stores by associating upper KPIs, units of upper KPIs, formula numbers, lower KPIs, units of lower KPIs, usage counts, and data creation dates, etc.

[0159] The node name of the upper node is registered in the upper KPI. Here, in the upper KPI, nodes of the node type of KGI or KPI, etc., which can quantitatively set the goals to be achieved such as KGI and KPI, are registered. Hereinafter, KGI and KPI are also collectively referred to as "KPI".

[0160] The unit of the upper KPI registers the unit of the goal set for the node of the upper KPI. For example, when the target indicator value is the monthly sales amount, "yen / month", etc. is registered as the unit.

[0161] An identifier that can specify the calculation formula for calculating the indicator value targeted by the upper KPI node is registered in the formula number. Specifically, a plurality of calculation formulas for calculating various indicator values are stored in the storage unit 56 in association with the formula numbers, and from among those calculation formulas, the formula number of the calculation formula to be used is set in the "formula number" item. For example, when the indicator value is the monthly sales amount, the formula number of the calculation formula for totaling the sales for one month is set in the "formula number" item.

[0162] More specifically, the KPI tree is created such that the relationship between the upper-level KPI and the lower-level KPIs is a predetermined relationship. For example, the KPI tree is created such that the upper-level KPI is the product of a plurality of lower-level KPIs. In this case, the upper-level KPI and the lower-level KPIs have a one-to-many relationship, and each of the lower-level KPIs is an element of the calculation formula corresponding to the formula No. set for the upper-level KPI. That is, the same formula No. as that of the upper-level KPI is assigned to the lower-level KPI. For example, in FIG. 19, for the upper-level KPI of "sales", the lower-level KPIs of "number of customers visiting the store" and "average customer purchase amount" are associated, and the same formula No. "1" is assigned.

[0163] Also for example, the KPI tree is created such that the upper-level KPI is the sum of a plurality of lower-level KPIs. In this case, the upper-level KPI and the lower-level KPIs have a one-to-many relationship, and each of the lower-level KPIs is an element of the calculation formula corresponding to the formula No. set for the upper-level KPI. That is, the same formula No. as that of the upper-level KPI is assigned to the lower-level KPI. For example, in FIG. 19, for the upper-level KPI of "sales", the lower-level KPIs of "sales of department A", "sales of department B", and "sales of department C" are associated, and the same formula No. "3" is assigned.

[0164] Candidate node names of the lower nodes connected to the lower level of the node of the upper-level KPI are registered for the lower-level KPIs. The unit of the lower-level KPI is registered with the unit of the target set for the node of the lower-level KPI. For example, when the target index value is the number of customers visiting the store per month, "persons / month" or the like is registered as the unit.

[0165] As shown in FIG. 19, in the node candidate table 561, it is possible to store a plurality of lower-level KPIs associated with the upper-level KPI under the same conditions. These plurality of lower-level KPIs are candidates for the nodes connected to the lower level of the node when a node corresponding to the node condition of the upper-level KPI is selected. Here, the node condition means a condition related to the attributes of the node. For example, the node condition may be the node name, or a combination of the node name and the unit, or a combination of the node name, the unit, and the formula No.

[0166] In addition, it is preferable that the subordinate KPIs memorized in association with the superior KPI be elements of the calculation formula corresponding to the formula No of the superior KPI. In other words, it is preferable that the superior KPI and the subordinate KPI have a relationship based on arithmetic operations.

[0167] The usage count is information indicating the number of times the subordinate KPI presented as a candidate was actually used. On the data creation date, data indicating the year, month, and day registered in the node candidate table 561 is stored.

[0168] Returning to FIG. 18, the provisional registration node candidate table 562 is a table or database for holding pairs of superior nodes and subordinate nodes that are candidates for registration in the node candidate table 561. The provisional registration node candidate table 562 has, for example, the data configuration shown in FIG. 20.

[0169] FIG. 20 is a diagram showing an example of the data configuration of the provisional registration node candidate table 562. As shown in FIG. 20, the provisional registration node candidate table 562 stores the superior KPI, the unit of the superior KPI, the formula No, the subordinate KPI, the unit of the subordinate KPI, the KPI tree link, and the data creation date in association with each other.

[0170] Here, the superior KPI, the unit of the superior KPI, the formula No, the subordinate KPI, and the subordinate KPI are the same as those in the node candidate table 561. In the KPI tree link, information capable of specifying the KPI tree to which the nodes of the superior KPI and the subordinate KPI belong is registered. On the data creation date, data indicating the year, month, and day registered in the provisional registration node candidate table 562 is stored.

[0171] Next, referring to FIG. 21, the functional configuration of the server device 50 according to the present embodiment will be described. FIG. 21 is a diagram showing an example of the functional configuration of the server device 50. As shown in FIG. 21, the server device 50 includes a GUI providing unit 211, a design support unit 512, a grouping process unit 213, a display control unit 214, an operation reception unit 215, a data analysis unit 216, and a node candidate management unit 517 as functional units.

[0172] The design support department 512 has the same functions as the design support department 212. In addition, the design support department 512 has functions specific to the present embodiment shown below.

[0173] Based on the node candidate table 561, the design support department 512 supports the creation of nodes in the KPI tree. When a node is created or selected by the user, the design support department 512 presents candidates for the subordinate nodes connected to the node.

[0174] Specifically, the design support department 512 uses the node created or selected by the user as the parent node, and searches the node candidate table 561 for the upper-level KPIs that meet the node conditions of the parent node. If there are upper-level KPIs that meet the node conditions of the parent node, the design support department 512 presents the lower-level KPIs associated with the upper-level KPIs to the user as candidates for the child nodes to be connected below the parent node.

[0175] Here, with reference to FIGS. 22 to 24, the creation screen of the KPI tree provided by the design support department 512 will be described. FIGS. 22 to 24 are diagrams showing an example of the screen provided by the server device 50, and show the creation screen related to the creation of the KPI tree.

[0176] As shown in FIG. 22, the creation screen 60 has a creation area 61 where various nodes can be arranged at arbitrary positions. The user can arrange various nodes in the creation area 61 and connect between the nodes.

[0177] FIG. 22 shows an example in which a node 611 (node name: sales) corresponding to KGI is arranged in the creation area 61. The design support department 512 collaborates with the name alignment processing unit 213 to compare the node name and node type set in the node 611 with the node name and node type registered in the name alignment master 265. If they match, the design support department 512 converts them to the corresponding reference node name and executes the following processing.

[0178] Note that the conversion to the reference node name is executed as internal processing without changing the notation. However, this is not the only case. For example, the node name displayed in the creation area 61 may be changed to the reference node name, or a message proposing to change it to the reference node name may be displayed. Further, the name alignment processing unit 213 may execute the first registration process described with reference to FIG. 15 in the background of node creation.

[0179] When the design support unit 512 receives an operation instruction to create a new child node while one node is selected, it sets the selected node as the parent node and searches the node candidate table 561 for the upper KPIs that meet the conditions of the node name of this parent node. When the node type of the child node to be created is instructed by the user, the design support unit 512 only needs to search the node candidate table 561 if the instructed node type is a KPI.

[0180] If there is an upper KPI corresponding to the node candidate table 561, the design support unit 512 extracts the data of the lower KPIs associated with the upper KPI and displays the extracted lower KPIs in a selectable state as candidates for the newly created child node.

[0181] For example, when the node 611 shown in FIG. 22 is selected, the design support unit 512 extracts from the node candidate table 561 the data of the lower KPIs associated with the upper KPI of the node name "sales" of the node 611. Then, as shown in FIG. 23, the design support unit 512 displays the attributes such as the node name of the extracted lower KPI in a selectable state as candidates for the newly created child node.

[0182] In FIG. 23, an example is shown where a support screen 62 for assisting in creating child nodes is displayed on the creation area 61. The support screen 62 is provided with, for example, a candidate display column 621, an OK button 622, and a cancel button 623. In the candidate display column 621, the node names of the lower-level KPIs extracted from the node candidate table 561 are displayed in a selectable state. The OK button 622 is an operator for instructing the application of the node name. Also, the cancel button 623 is an operator for instructing the deletion of the support screen 62. When the cancel button 623 is operated, the design support unit 512 deletes the support screen 62. In this case, it is assumed that the user can independently create a child node by inputting a desired node name. Note that in FIG. 23, a configuration is adopted in which the node names of the lower-level KPIs extracted are presented in the candidate display column 621, but other attributes such as the unit of the lower-level KPIs may be presented together or individually.

[0183] In the state of FIG. 23, when a user selects one node name from the candidate display column 621 and operates the OK button 622, the design support unit 512 creates a child node with the selected node name and displays it in the creation area 61. For example, when the node name "number of customers visiting the store" is selected from the candidate display column 621 and the OK button 622 is operated, as shown in FIG. 24, the candidate display column 621 creates and displays a node 612 with the node name "number of customers visiting the store" below the node 611. Also, the unit set for the node 612 preferably inherits the attributes of the selected lower-level KPI, but is not limited to this, and may be configured to be arbitrarily changeable.

[0184] Note that in the above, an example of searching for a higher-level KPI whose parent node and node name match among the node conditions of the higher-level KPI has been described, but it is not limited to this. For example, when attributes such as a unit or formula No. are set for the parent node, the higher-level KPI may be searched by including those attributes in the node conditions.

[0185] In addition, the design support department 512 may rearrange the order of the lower-level KPIs to be displayed in the candidate display column 621 or select the data of the lower-level KPIs to be extracted based on the usage counts registered in the node candidate table 561. For example, the design support department 512 may preferentially display in the candidate display column 621 the lower-level KPIs with higher usage counts. Also, the design support department 512 may exclude from the extraction targets the lower-level KPIs whose usage counts are less than the threshold value.

[0186] Also, when there are existing child nodes (hereinafter also referred to as sibling nodes) in the parent node, the design support department 512 may select the data of the lower-level KPIs to be extracted from the node candidate table 561 based on the combination of the parent node and the sibling nodes. For example, the design support department 512 searches the node candidate table 561 for the upper-level KPIs whose combinations of node names of the parent node and the sibling nodes match, and selects the data of the lower-level KPIs to be extracted based on the formula No. etc. of the matching upper-level KPIs. In this case, the lower-level KPIs to be extracted are the lower-level KPIs associated with the same formula No. as the combination of the parent node and the sibling nodes. It is preferable to exclude from the extraction targets the lower-level KPIs with the same node name as the existing sibling nodes and the lower-level KPIs associated with different formula Nos.

[0187] In addition, when the design support department 512 creates a child node by the user's selection, it may support the creation of a new sibling node based on the combination of the created child node and the parent node of the child node. For example, it may extract the data of the lower-level KPIs associated with the upper-level KPIs under the same conditions as the node name and formula No. of the parent node, and display them in a form similar to the above-described support screen 62 as candidates for the new sibling node. It is preferable to exclude from the extraction targets the lower-level KPIs with the same node name as the existing child nodes.

[0188] In addition, when the user creates a node independently, the design support department 512 registers, as registration candidates, the information indicating the correspondence between the attributes of the created node (child node) and the attributes of the parent node existing above the child node in the temporary registration node candidate table 562.

[0189] Specifically, the design support unit 512 associates the node names, units of index values, formula numbers, etc. set for the parent node and child nodes with the KPI tree link of the KPI tree in which the node exists, and registers them in the provisional registration node candidate table 562. In addition, when the pair of the node name of the child node created by the user and the node name of its parent node is not registered in either the node candidate table 561 or the provisional registration node candidate table 562, the design support unit 512 registers it in the provisional registration node candidate table 562.

[0190] Note that it is preferable to register the node name created by the user in the provisional registration node candidate table 562 with the converted name based on the naming master 265. Thereby, since the fluctuation of the node name can be suppressed, the data quality can be improved. Hereinafter, the information registered in the provisional registration node candidate table 562 is also referred to as provisional registration node candidate data.

[0191] The node candidate management unit 517 executes a process of updating the node candidate table 561 based on the provisional registration node candidate table 562. Specifically, the node candidate management unit 517 refers to the provisional registration node candidate table 562 at a predetermined timing, and when provisional registration node candidate data is registered, executes a process for confirming whether to transfer the data to the node candidate table 561. Here, the predetermined timing is not particularly limited, and it may be the timing when a predetermined operation is received from the user, or it may be a predetermined timing such as once a week.

[0192] For example, when provisional registration node candidate data is registered in the provisional registration node candidate table 562, the node candidate management unit 517 displays a screen (hereinafter, also referred to as a provisional registration node list screen) that displays the provisional registration node candidate data in a list as shown in FIG. 25.

[0193] Here, FIG. 25 is a diagram showing an example of a screen provided by the server device 50, and shows the provisional registration node list screen.

[0194] As shown in FIG. 25, the provisional registration node list screen 70 has a display area 71 for displaying a list of provisional registration node candidate data. The display area 71 has an ID, a node name, and a node type as data items. The ID is an identifier for managing the provisional registration node candidate data. For example, the ID is an ascending number assigned in the order in which the data is registered in the provisional registration node candidate table 562. The node name and node type display the node name and node type of the top KPI included in the provisional registration node candidate data. Note that FIG. 25 shows the registration status of the top KPI in the provisional registration node candidate table 562 described in FIG. 20.

[0195] In addition, a registration button 72 is provided on the provisional registration node list screen 70. The registration button 72 is an operator for instructing registration to the node candidate table 561. After a specific ID (node name of the top KPI) is selected from the display area 71 and the operation of the registration button 72 is received, the node candidate management unit 517 displays a screen (hereinafter also referred to as the second registration screen) representing the provisional registration node candidate data corresponding to the node name of the selected ID.

[0196] FIG. 26 is a diagram showing an example of a screen provided by the server device 20 and shows an example of the second registration screen. As shown in FIG. 26, the second registration screen 80 has a first display area 81 and a second display area 82.

[0197] Information regarding the top KPI selected on the provisional registration node list screen 70 is displayed in the first display area 81. Specifically, the node name, unit, and formula No. of the selected top KPI are displayed in the first display area 41. Note that FIG. 26 shows an example in which the calculation formula (sales - cost) corresponding to formula No. 1 is displayed.

[0198] In addition, a KPI tree display button 811 for instructing the display of the KPI tree is provided in the first display area 81. When the node candidate management unit 517 receives an operation of the KPI tree display button 811, based on the KPI tree link of the upper KPI selected on the provisional registration node list screen 70, the KPI tree to which the upper KPI belongs is read from the KPI tree DB 261. Then, the node candidate management unit 517 collaborates with the design support unit 212 and the like to display a screen representing the read KPI tree.

[0199] In the second display area 82, the node names and units of the lower KPIs associated with the upper KPI selected on the provisional registration node list screen 70 are displayed. FIG. 26 shows an example of display when the upper KPI "Profit" in the provisional registration node candidate table 562 shown in FIG. 20 is selected, and two lower KPIs "Sales" and "Cost" associated with the upper KPI "Profit" are displayed in the second display area 82.

[0200] In addition, a registration button 83 and a deletion button 84 are provided on the second registration screen 80. The registration button 83 is an operator for instructing registration to the node candidate table 561. The deletion button 84 is an operator for instructing data deletion.

[0201] A user who operates the second registration screen 80 can easily confirm the arithmetic relationship between the upper KPI and the lower KPI, the unit relationship between the upper KPI and the lower KPI, etc. by looking at the second registration screen 80. Then, when the user determines that it is a consistent relationship according to the rules of the KPI tree, such as that the lower KPI is in an arithmetic relationship with the upper KPI, the user operates the registration button 83. For example, in the case of FIG. 26, the two lower KPIs "Sales" and "Cost" are elements of the calculation formula of formula No. 1 set for the upper KPI, and the arithmetic relationship between the upper KPI and the lower KPI is also consistent. Therefore, it can be determined that it is a consistent relationship according to the rules of the KPI tree.

[0202] When the node candidate management unit 517 receives an operation of the registration button 83, it registers the provisional registration node candidate data related to the upper KPI and the lower KPI displayed on the second registration screen 80 in the node candidate table 561. Further, the node candidate management unit 517 deletes the provisional registration node candidate data registered in the node candidate table 561 from the provisional registration node candidate table 562.

[0203] On the other hand, when the user determines that the relationship between the upper KPI and the lower KPI is an inconsistent relationship deviating from the rules of the KPI tree, etc., the user operates the delete button 84. When the node candidate management unit 517 receives an operation of the delete button 84, it deletes the provisional registration node candidate data related to the upper KPI and the lower KPI displayed on the second registration screen 80 from the provisional registration node candidate table 562.

[0204] As a result, the provisional registration node candidate data determined to be useful by the user is registered in the node candidate table 561 and used to assist in creating the KPI tree (KPI node).

[0205] Hereinafter, with reference to FIGS. 27 and 28, an operation example of the above-described server device 50 will be described. FIGS. 27 and 28 are flowcharts showing an example of processing executed by the server device 50.

[0206] First, with reference to FIG. 27, an example of creation support processing related to creating a KPI tree will be described. It is assumed that the creation screen 60 is displayed as a premise of this processing.

[0207] When the design support unit 512 receives an operation instructing creation of a child node in a state where a parent node is selected (step S51), it determines whether the node type of the child node to be created is a KPI (step S52). For example, the design support unit 512 determines the node type of the child node to be created based on the node type explicitly instructed by the user. Further, for example, when the node type of the selected parent node is a KPI, the design support unit 512 may determine the node type of the child node as a KPI.

[0208] When it is determined that the node type of the child node to be created is other than KPI (step S52; No), the design support unit 512 accepts free input of attributes such as the node name from the user (step S53). Next, the design support unit 512 creates a child node with the input attributes (step S54) and ends this process.

[0209] Also, when it is determined that the node type of the child node to be created is KPI (step S52; Yes), the design support unit 512 determines whether there is a higher-level KPI corresponding to the node conditions of the parent node in the node candidate table 561 (step S55).

[0210] Here, when there is no higher-level KPI corresponding to the conditions (step S55; No), the design support unit 512 accepts free input of attributes such as the node name from the user (step S56). Next, when the design support unit 512 creates a child node with the input attributes (step S57), it registers information related to the pair of the created child node and the parent node in the temporary registration node candidate table 562 (step S58) and ends this process. Note that the design support unit 512 may be configured to perform name alignment of the node names of the parent node and the child node based on the name alignment master 265 and then register them in the temporary registration node candidate table 562 in the process of step S58.

[0211] Also, in step S55, when there is a higher-level KPI corresponding to the conditions (step S55; Yes), the design support unit 512 extracts the lower-level KPIs associated with the corresponding higher-level KPI as candidates and preferentially displays the lower-level KPIs with a large number of usages (step S59).

[0212] Subsequently, the design support unit 512 determines whether one lower-level KPI has been selected from the candidates displayed in step S59 (step S60). Here, for example, when the above-described cancel button 623 is operated, the design support unit 512 determines that none of the lower-level KPIs have been selected from the displayed candidates (step S60; No). In this case, the design support unit 512 executes the processes of steps S56 to S58 described above.

[0213] Also, for example, when one lower-level KPI is selected from the candidates displayed in step S59 and the above-described OK button 622 is operated, the design support unit 512 determines that one lower-level KPI has been selected from the displayed candidates (step S60; Yes). In this case, the design support unit 512 creates child nodes based on the attributes of the selected lower-level KPI (step S61), and records the usage count by adding 1 to the usage count of the selected lower-level KPI (step S62).

[0214] Subsequently, the design support unit 512 determines whether there are other lower-level KPIs associated with the same upper-level KPI based on the node conditions of the parent node related to the child nodes created in step S61 in the node candidate table 561 (step S63). Here, other lower-level KPIs mean lower-level KPIs different from the node conditions of the child nodes created in step S61.

[0215] If there are no other lower-level KPIs (step S63; No), the design support unit 512 ends this process. Also, if there are other lower-level KPIs (step S63; Yes), the design support unit 512 creates other child nodes (sibling nodes) based on the attributes of the other lower-level KPIs (step S64). Then, the design support unit 512 records the usage count by adding 1 to the usage count of the other lower-level KPI used to create the sibling nodes (step S65), and ends this process.

[0216] Note that in this process, the creation of sibling nodes is automatically performed, but it is not limited to this. For example, the process may be ended after step S62 by omitting the processes of steps S63 to S65. Also, for example, after determining in step S63 that there are other lower-level KPIs, the process may be returned to step S59 to display selectably other lower-level KPIs that are candidates for creating sibling nodes.

[0217] Next, with reference to FIG. 28, an example of data management processing related to the management of provisional registration node candidate data registered in the provisional registration node candidate table 562 will be described.

[0218] The node candidate management unit 517 refers to the provisional registration node candidate table 562 and determines whether provisional registration node candidate data is registered (step S71). Here, if it is determined that the provisional registration node candidate data is not registered (step S71; No), the node candidate management unit 517 ends this process.

[0219] Also, if it is determined that the provisional registration node candidate data is registered (step S71; Yes), the node candidate management unit 517 displays a provisional registration node list screen 70 in which the node names of the top KPI are listed based on the provisional registration node candidate data (step S72). Next, the node candidate management unit 517 waits until a node name is selected (step S73; No).

[0220] Here, when one node name is selected from the provisional registration node list screen 70 and the registration button 72 is operated, the node candidate management unit 517 determines that a node name has been selected (step S73; Yes). Next, the node candidate management unit 517 displays a second registration screen 80 representing the provisional registration node candidate data corresponding to the selected node name (step S74).

[0221] Next, the node candidate management unit 517 waits until the registration button 83 or the delete button 84 is operated (step S75; No → step S76; No). Here, when the operation of the registration button 83 is received (step S75; Yes), the node candidate management unit 517 registers the provisional registration node candidate data related to the selected node name in the node candidate table 561 (step S77). Next, the node candidate management unit 517 deletes the provisional registration node candidate data registered in the node candidate table 561 in step S77 from the provisional registration node candidate table 562 (step S78), and proceeds to step S71.

[0222] Also, when the node candidate management unit 517 receives the operation of the delete button 84 in step S76 (step S76; Yes), it deletes the temporarily registered node candidate data related to the selected node name from the temporarily registered node candidate table 562 (step S79), and proceeds to step S71.

[0223] Then, the node candidate management unit 517 executes the processes of steps S72 to S79 until there is no temporarily registered node candidate data in the temporarily registered node candidate table 562, and ends the process when there is no temporarily registered node candidate data.

[0224] As described above, when the server device 50 is instructed to create a new child node for the parent node, it extracts the attributes of the lower-level node corresponding to the attributes of the parent node from the node candidate table 561 that stores the information defining the correspondence relationship between the attributes of the upper-level node and the attributes of the lower-level node, and presents the attributes of the extracted lower-level node as candidates. Then, when one of the presented candidates is selected, the server device 50 creates a child node based on the selected attributes.

[0225] Thereby, the user who creates the KPI tree can efficiently create a child node corresponding to the node conditions of the parent node based on the presented candidates. Specifically, since the user can create a child node having a relationship that allows arithmetic operations with the parent node, the user can efficiently create a child node in accordance with the rules of the KPI tree. Therefore, the server device 50 can support the creation of the KPI tree.

[0226] In addition, since the server device 50 presents candidate lower-level nodes based on attributes such as the node name and the unit of the index value, and can create a child node based on the attribute, it can automatically set the node name and the index value of the newly created child node. Therefore, the server device 50 can omit the setting work of the node name and the unit by the user, and thus can support the creation of the KPI tree.

[0227] In addition, the server device 50 records the usage count for the lower-level nodes used to create child nodes, and when presenting them as candidates, preferentially presents the lower-level nodes with a higher usage count. As a result, the server device 50 can improve the convenience for the user when selecting candidates, and thus can efficiently support the creation of the KPI tree.

[0228] Also, when the user creates a child node independently, the server device 50 stores provisional registration node candidate data indicating the correspondence relationship between the attributes of the child node and the attributes of the parent node in the provisional registration node candidate table 562. Then, based on the provisional registration node candidate data, the server device 50 presents the correspondence relationship between the attributes of the upper-level node and the attributes of the lower-level node on the second registration screen 80, and registers or deletes them in the node candidate table 561 according to an instruction from the user. As a result, the server device 50 can update the node candidate table 561 based on the regulations related to the nodes created by the user, so that the regulations related to the existing nodes can be used for the creation of new nodes.

[0229] [Third Embodiment] Next, the third embodiment will be described. In the third embodiment, a form capable of supporting the creation of a KPI tree in a case where, for example, a KPI tree for a new customer is created will be described. Note that hereinafter, the points different from the above-described embodiments will be mainly described, and detailed descriptions of the points common to the already described content will be omitted. Also, in this embodiment, the KPI tree will be described as defining the relationship between problems and countermeasures, but it may be defined as defining the relationship between goals and countermeasures.

[0230] FIG. 29 is a diagram showing an example of the hardware configuration of the server device 90 according to this embodiment. As shown in FIG. 29, the server device 90 includes a computer configuration such as a CPU 21, a ROM 22, and a RAM 23, similar to the server device 20. The server device 90 also includes a display unit 24, an operation unit 25, a storage unit 96, and a communication unit 27.

[0231] The storage unit 96, similar to the storage unit 26, is composed of a storage medium such as an HDD or a flash memory, and stores the KPI tree DB 261, the business flow DB 262, the temporary registration table 263, the item master 264, the grouping master 265, etc. Also, the storage unit 96 stores a customer data table 961, a problem master table 962, a service master table 963, and a service design data table 964.

[0232] The customer data table 961 is a table or database for storing and managing information related to customers. The customer data table 961 has, for example, the data configuration shown in FIG. 30.

[0233] FIG. 30 is a diagram showing an example of the data configuration of the customer data table 961. As shown in FIG. 30, the customer data table 961 stores by associating a customer ID, a customer name, a major industry classification, a medium industry classification, a minor industry classification, sales, the number of employees, the number of stores, and the data creation date, etc. Here, the customer name, the major industry classification, the medium industry classification, the minor industry classification, sales, the number of employees, and the number of stores are examples of customer attributes.

[0234] The customer ID is an identifier for managing customers. Information that can identify the customer is registered in the customer name. Note that the customer name registered in the customer data table 961 corresponds to the customer name in the KPI tree DB 261.

[0235] The major industry classification, the medium industry classification, and the minor industry classification indicate classifications obtained by classifying the customer's industry according to a predetermined standard. Note that in FIG. 30, an example of classifying the customer's industry into three levels of large, medium, and small is shown, but the number of classification levels is not limited to this.

[0236] For sales, the sales amount of customers during a predetermined reference period is registered. The reference period is not particularly limited, for example, it can be in units of one month, etc., but it is preferably a reference period common to all customers. For the number of employees, the number of employees working at the stores operated by the customers is registered. Also, for the number of stores, the number of stores operated by the customers is registered. For the data creation date, data indicating the year, month, and day registered in the customer data table 961 is stored. Here, the items of sales, the number of employees, and the number of stores are used as indicators representing the scale of the customers.

[0237] The issue master table 962 is a table or database for classifying and managing the types of issues defined by the KPI tree (KGI node, KPI node, factor node). The issue master table 962 has, for example, the data configuration shown in FIG. 31.

[0238] FIG. 31 is a diagram showing an example of the data configuration of the issue master table 962. As shown in FIG. 31, the issue master table 962 stores the issue major classification, issue medium classification, first keyword, data creation date, etc. in association with each other.

[0239] The issue major classification and issue medium classification indicate classifications obtained by classifying the issues in the service according to a predetermined standard. Note that in FIG. 31, an example of classifying the issues into two levels of large and medium is shown, but the number of classification levels is not limited to this.

[0240] For the first keyword, keywords related to the issues defined in the KPI tree are registered. The first keyword can be set arbitrarily. For example, the first keyword may be set to the item name registered in either the issue major classification or the issue medium classification. Also, the first keyword may be set to a character string including the reference node name registered in the grouping master 265. Note that it is preferable to set a character string that clearly represents the object of the issue for the first keyword. For the data creation date, data indicating the year, month, and day registered in the issue master table 962 is stored.

[0241] The service master table 963 is a table or database for classifying and managing the types of services defined in the KPI tree (service nodes). The issue master table 962 has, for example, the data configuration shown in FIG. 32.

[0242] FIG. 32 is a diagram showing an example of the data configuration of the service master table 963. As shown in FIG. 32, the service master table 963 stores the second keyword, service name, data creation date, etc. in association with each other.

[0243] Keywords related to the services defined in the KPI tree are set as the second keyword. The second keyword can be set arbitrarily. It is preferable to set a character string that simply represents the content and features of the service as the second keyword. The name of the service corresponding to the second keyword is registered as the service name.

[0244] The service design data table 964 is a table or database for managing the relationship between the issues extracted from the customer's KPI tree and the services. The service design data table 964 has, for example, the data configuration shown in FIG. 33.

[0245] FIG. 33 is a diagram showing an example of the data configuration of the service design data table 964. As shown in FIG. 33, the service design data table 964 stores the customer ID, service design data address, type, name, data creation date, etc. in association with each other.

[0246] The customer ID is an identifier for managing customers. Note that the customers registered in the service design data table 964 are customers for whom the KPI tree has been created and correspond to the customer IDs in the customer data table 961.

[0247] Information that can identify the KPI tree corresponding to the customer ID, an address indicating the storage location of the data file, etc. are registered as the service design data address. In addition, the storage location of a business flow other than the KPI tree may be registered in the service design data address.

[0248] The category and name store the classification categories and names of the issues and services extracted from the KPI tree. Specifically, in the process described below, the classification of the issues set in the KPI tree (major issue classification, medium issue classification) and the classification of the services set to correspond to the issues are extracted. Then, the extracted classification categories and names of the issues and services (hereinafter also referred to as classification names) are registered in the "category" and "name" items, respectively. Note that one or more sets of issues and services are extracted from the KPI tree. Also, when there are multiple service nodes in the KPI tree, sets of issues and services can be extracted for each service node. Hereinafter, the set of issues and services stored in the service design data table 964 is also referred to as "service design data".

[0249] The data creation date stores data indicating the year, month, and day registered in the service design data table 964.

[0250] Next, with reference to FIG. 34, the functional configuration of the server device 90 according to the present embodiment will be described. FIG. 34 is a diagram showing an example of the functional configuration of the server device 90. As shown in FIG. 34, the server device 90 includes a GUI providing unit 211, a design support unit 912, a grouping processing unit 213, a display control unit 214, an operation reception unit 215, and a data analysis unit 916 as functional units.

[0251] The data analysis unit 916 is an example of an extraction means and a classification means. The data analysis unit 916 has the same functions as the data analysis unit 216 of the above-described embodiment. Also, the data analysis unit 916 has functions specific to the present embodiment shown below.

[0252] The data analysis unit 916 analyzes the KPI tree of each customer and extracts data (hereinafter also referred to as service design data) indicating the relationship between the issues set in the KPI tree and the services corresponding to the issues.

[0253] Specifically, when the data analysis unit 916 detects a service node from the KPI tree, it extracts the KGI nodes, KPI nodes, and factor nodes existing on the path by sequentially tracing the path from the service node to the KGI node. The data analysis unit 916 converts the node names of the extracted nodes into reference node names based on the clustering master 265. Note that the KGI nodes, KPI nodes, and factor nodes are examples of the first nodes. Also, the service node is an example of the second node.

[0254] Next, the data analysis unit 916 determines the classification (major issue classification, medium issue classification) of the issues set for each node by performing a match determination between the first keyword in the issue master table 962 and the converted node name of each node. Here, the match determination between the node name and the first keyword may be a partial match or a full match. The data analysis unit 916 determines the classification name of the major issue classification and the classification name of the medium issue classification associated with the matched first keyword as the classification of the issue.

[0255] Also, the data analysis unit 916 determines the classification of the service set for the service node by performing a match determination between the node name of the service node detected from the KPI tree and the second keyword in the service master table 963. Here, the match determination between the node name and the second keyword may be a partial match or a full match. For example, when the node name of the service node is "Coupon Issuance Service for Customer A" and the second keyword in the service master table 963 is "Coupon Issuance Service", the data analysis unit 916 determines that the second keyword "Coupon Issuance Service" matches. Then, the service name (classification name) associated with the matched second keyword is determined as the classification of the service.

[0256] Then, the data analysis unit 916 associates the issues and service classifications determined in the above processing, and stores them in the service design data table 964 together with the customer ID and service design data address related to the KPI tree of the derivation source. In this way, the data (service design data) registered in the service design data table 964 indicates the relationship between the issues set in the KPI tree of each customer and the service.

[0257] Note that in this embodiment, the data analysis unit 916 is configured to automatically classify the issues and services set in the KPI tree based on the predetermined first keyword and second keyword. However, the present invention is not limited to this, and the user may manually classify the issues and services. In this case, the data analysis unit 916 may assist in the selection of classification by displaying the candidate classification names in a selectable manner.

[0258] The design support unit 912 is an example of a reception unit, an output unit, and a storage control unit. The design support unit 912 has the same functions as the design support unit 212 (design support unit 512) in the above-described embodiment. In addition, the design support unit 912 has functions specific to this embodiment described below.

[0259] The design support unit 912 provides the user with support information for service design, such as creating a KPI tree, based on the service design data registered in the service design data table 964.

[0260] Specifically, the design support unit 912 provides the user with support information representing the relationship between the conditions related to the customer's business and the issues and services set by the customer of each condition in the KPI tree based on the customer data table 961 and the service design data table 964. For example, the design support unit 912 provides the user with support information via the screens shown in FIGS. 35 to 37 (hereinafter also referred to as support screens).

[0261] Here, the support screens provided by the design support unit 912 will be described with reference to FIGS. 35 to 37. FIGS. 35 to 37 are diagrams showing an example of the screens provided by the server device 90, and show the support screens.

[0262] As shown in FIG. 35, the first support screen 100 has a first display area 101, a second display area 102, and a third display area 103.

[0263] In the first display area 101, operators that can specify the attributes of the customer to be analyzed are displayed. Specifically, in the first display area 101, operators 1011 to 1016 that can specify desired conditions are provided for each item of major industry classification, medium industry classification, minor industry classification, sales, number of employees, and number of stores. Here, the items displayed in the first display area 101 correspond to the items in the customer data table 961. In FIG. 35, the operators 1011 to 1016 can specify the classification of the industry, the scale of sales, the number of employees, and the number of stores, etc. by a selection operation using a pull-down menu. Note that the number of items to be specified among the items in the first display area 101 is not particularly limited. For example, it may be the case that not all items are specified.

[0264] In the second display area 102, the analysis results of the issues related to the customers who meet the conditions of the attributes specified in the first display area 101 are displayed. Specifically, for each of the major issue classification and the medium issue classification, the composition ratio for each classification of the issues is displayed in the second display area 102 in the form of a pie chart or the like.

[0265] More specifically, when the conditions related to the customer attributes are specified in the first display area 101, the design support unit 912 extracts the customer IDs of the customers having the attributes corresponding to the conditions from the customer data table 961. Next, the design support unit 912 reads the service setting data related to the extracted customer IDs from the service design data table 964. Based on the read service setting data, the design support unit 912 derives the composition ratio for each classification (each classification name) of the major issue classification and the medium issue classification. Then, the design support unit 912 displays the derived composition ratio of the issues in the second display area 102 in the form of a pie chart or the like as the analysis result.

[0266] As a result, by looking at the second display area 102, the user can easily confirm what issues the customers with the attributes specified in the first display area 101 have set in the KPI tree and what the composition ratios of the set issues are. Note that each time the conditions related to the customer attributes are updated, the design support department 912 causes the composition ratios of the issues corresponding to the conditions to be displayed in the second display area 102.

[0267] In the third display area 103, operators are provided that can specify the classification names to be analyzed for the classification names of the issues displayed in the second display area 102. Specifically, in the third display area 103, operators 1031 and 1032 that can specify the classification names of the issues are provided for each of the major issue classification and the middle issue classification. In FIG. 35, the operators 1031 and 1032 can specify the classification names of the major issue classification and the middle issue classification respectively by a selection operation using a pull-down menu.

[0268] In addition, an OK button 1033 is provided in the third display area 103. The OK button 1033 is an operator for determining the conditions of the major issue classification and the middle issue classification selected in the pull-down menu. When the design support department 912 receives the operation of the OK button 1033, it displays the second support screen 200 shown in FIG. 36.

[0269] As shown in FIG. 36, the second support screen 200 has a first display area 201 and a second display area 202.

[0270] In the first display area 201, the number of uses (registration counts) for each service name of the services corresponding to the conditions of the issues selected in the third display area 103 of the first support screen 100 are displayed in the form of a bar graph or the like.

[0271] Here, the design support unit 912 counts the number of uses of the services corresponding to the conditions of the issues selected in the third display area 103 of the first support screen 100 for each service name based on the service setting data extracted from the customer data table 961. Then, the design support unit 912 displays the counted number of uses for each service name in the first display area 201 in the form of a bar graph or the like as the analysis result of the services.

[0272] As a result, by looking at the first display area 201, the user can easily confirm what services are set as the services corresponding to the conditions of the issues set in the third display area 103 of the first support screen 100 and the number of the set services. It is assumed that it is possible to return from the second support screen 200 to the first support screen 100 by a user operation. Also, every time the conditions of the issues are updated in the third display area 103 of the first support screen 100, the design support unit 912 displays a bar graph corresponding to the conditions in the first display area 201.

[0273] In the second display area 202, an operator 2021 is provided that can specify the service name to be analyzed for the service names displayed in the first display area 201. In FIG. 36, it is possible to select one service name by a pull-down menu.

[0274] Also, an OK button 2022 is provided in the second display area 202. The OK button 2022 is an operator for determining the conditions of the service name selected in the pull-down menu of the operator 2021. When the design support unit 912 receives the operation of the OK button 2022, it displays the third support screen 300 shown in FIG. 37.

[0275] As shown in FIG. 37, the third support screen 300 has a first display area 301 and a second display area 302.

[0276] In the first display area 301, the conditions of the major issue classification and the middle issue classification specified in the third display area 103 of the first support screen 100 and the conditions of the service specified in the second display area 202 of the second support screen 200 are displayed.

[0277] In the second display area 302, information regarding each of the service design data that meets the specified issues and service conditions is listed as past cases. For example, in the second display area 302, the customer name and data creation date of the customer related to the service design data are displayed. Also, information set in the KPI tree related to the service design data may be displayed in the second display area 302.

[0278] For example, in FIG. 37, an example is shown in which the name of the KPI node (operational efficiency) and the name of the service node (reduction of overall operations, etc.) that meet the specified issues and service conditions are displayed. Note that the name of the KPI node may be the reference node name after clustering or the node name before clustering. Also, the name of the service node may be the node name set in the KPI tree or the changed service name changed based on the service master table 963.

[0279] In this way, by showing the issues and service names set by the customer as past cases, the user can specifically imagine the content of the issues and services to be set in the KPI tree. Therefore, in the server device 90, for example, when newly creating a KPI tree for a new customer, the creation of the KPI tree can be efficiently supported.

[0280] Note that in FIG. 37, the form of displaying the customer name in the second display area 302 has been described, but it is not limited to this, and the customer name may be displayed in a non-displayed or anonymized state. Also, when one past case is selected from the list of past cases displayed in the second display area 302, it may be configured to visualize and display the KPI tree related to the selected past case. In this case, when one past case is selected from the second display area 302, the design support unit 912 reads the data file from the service design data address related to the selected past case and displays the KPI tree in a visualized state as shown in FIG. 5. Note that in this case, it is preferable to display the visualized KPI tree in a state where it cannot be edited.

[0281] Further, instead of displaying the actually used KPI tree, the design support unit 912 may display a template of the KPI tree and transition to a state where the KPI tree can be created using the template. In this case, the template preferably has a tree structure similar to the KPI tree of the selected customer. For example, the template may be obtained by removing information that can identify the customer from the KPI tree of the selected past case. Also, when there are a plurality of similar templates, a screen for selecting one template may be displayed, and the KPI tree may be created in a state where it is possible to create the KPI tree using the selected template.

[0282] Thereby, the user can create and design a newly created KPI tree with reference to past cases of the KPI tree. Therefore, the server device 90 can efficiently support the creation of the KPI tree.

[0283] Note that the support screen provided by the design support unit 912 is not limited to the above example and may have other screen configurations. Here, FIG. 38 is a diagram showing an example of a screen provided by the server device 90 and shows other screen configurations of the support screen.

[0284] As shown in FIG. 38, the fourth support screen 400 has a first display area 401 and a second display area 402.

[0285] Here, the first display area 401 is the same as the first display area 101 of the first support screen 100 described above, and operators 4011 to 4016 capable of setting conditions related to the business of the company are displayed.

[0286] In the second display area 402, the extraction results of service design data that meet the conditions specified by the operators 4011 to 4016 in the first display area 401 are displayed. Specifically, based on the customer data table 961 and the service design data table 964, when the design support unit 912 extracts the service design data of a customer that meets the conditions specified in the first display area 401, it aggregates the pairs of issues (major issue classification, medium issue classification) and services included in the service design data for each classification. Then, based on the aggregation results, the design support unit 912 displays the pairs of issues and services in descending order of the number of cases in the second display area 402.

[0287] Also in the fourth support screen 400, the user can easily confirm the relationship between the issues and services set in the KPI tree by an existing enterprise having the same business conditions as a new customer, for example. Thereby, even for a new customer, the user can assume issues suitable for the customer and proceed with the creation of the KPI tree, that is, service design. Therefore, the server device 90 can support the creation of the KPI tree.

[0288] Hereinafter, with reference to FIGS. 39 and 40, an operation example of the above-described server device 90 will be described. FIGS. 39 and 40 are flowcharts showing an example of the processing executed by the server device 90.

[0289] First, with reference to FIG. 39, an example of the processing related to the creation of the service design data table 964 will be described. Note that this processing is assumed to be executed at a predetermined timing, such as the timing when the KPI tree is created, for example, but is not limited thereto, and may be executed at the timing when execution is instructed by a manual operation.

[0290] The data analysis unit 916 refers to the customer data table 961 and determines the customer ID to be analyzed (step S81). For example, the data analysis unit 916 determines, as the analysis target, the customer ID of the customer related to the KPI tree triggered by the completion of the creation of the KPI tree. Also, for example, the data analysis unit 916 determines, as the analysis target, the customer ID of the customer related to the specified customer ID or KPI tree triggered by receiving an operation of specifying the customer ID or KPI tree to be analyzed from the user.

[0291] Next, the data analysis unit 916 refers to the KPI tree related to the customer ID to be analyzed stored in the KPI tree DB 261, and extracts various nodes (KGI node, KPI node, factor node) existing on the path between the service node and the KGI node by tracing from the service node set in the KPI tree to the KGI node (step S82). Next, the data analysis unit 916 converts the node names of the extracted nodes into reference node names based on the grouping master 265 (step S83).

[0292] Subsequently, the data analysis unit 916 determines the classification of the issues (major issue classification, medium issue classification) set for each node by performing a match determination between each of the first keywords registered in the issue master table 962 and the node names of the converted nodes (step S84).

[0293] Also, the data analysis unit 916 determines the classification of the services (service name) set for the service node by performing a match determination between each of the second keywords registered in the service master table 963 and the node name of the service node set in the KPI tree (step S85).

[0294] Subsequently, the data analysis unit 916 associates the data types and classifications of the issues (major issue classification, medium issue classification) and services determined in the above processing with the customer ID related to the KPI tree, the service design data address, etc., stores them in the service master table 963 (step S86), and ends this processing.

[0295] Next, with reference to FIG. 40, an example of a process related to assisting in creating a KPI tree based on the service design data table 964 will be described. In this process, a form of providing assistance in creation based on the above-described first to third support screens will be described.

[0296] First, the design support unit 912 displays the first support screen 100 (step S91). For example, the design support unit 912 triggers the display of the first support screen 100 when it receives an operation instructing the creation of a new KPI tree or an operation requesting assistance in creating a KPI tree from the user.

[0297] Next, the design support unit 912 waits until the customer's attributes are specified (step S92; No). When the customer's attributes are specified (step S92; Yes), the design support unit 912 extracts the customer ID of the customer corresponding to the specified attribute conditions from the customer data table 961 (step S93). Next, when the design support unit 912 reads the service design data related to the extracted customer ID from the service design data table 964, it derives the composition ratio for each classification of issues based on the service design data (step S94). Next, the design support unit 912 displays the composition ratio of the issues derived in step S94 as support information in the form of a pie chart or the like (step S95).

[0298] Next, the design support unit 912 determines whether or not one issue has been specified from among the issues displayed in step S95 (step S96). Here, when no issue is specified (step S96; No), the design support unit 912 returns the process to step S92.

[0299] Also, when one issue is specified (step S96; Yes), the design support unit 912 counts the number of registered services corresponding to the specified issue for each classification (for each service name) based on the service setting data read in step S94 (step S97). Next, the design support unit 912 displays the counted number of registered services for each service name as support information on the second support screen 200 or the like (step S98).

[0300] Subsequently, the design support unit 912 waits until one service name is specified from the service names displayed in step S98 (step S99; No). Here, when any one service name is specified (step S99; Yes), the design support unit 912 displays service design data and customer-related information that meet the conditions based on the issues specified in step S96 and the service name specified in step S99 as past cases on the third support screen 300 or the like (step S100).

[0301] Subsequently, the design support unit 912 waits until one past case is specified from the past cases displayed in step S100 (step S101; No). Here, when any one past case is selected (step S101; Yes), the design support unit 912 displays the KPI tree related to the specified past case in a visible state (step S102) and ends the process.

[0302] As described above, when the server device 90 extracts the issues shown in the KGI node, KPI node, and factor node and the services shown in the service node corresponding to the issues from the KPI tree, it classifies the extracted issues and services by type and stores them in the service design data table 964 as service design data. Further, the server device 90 provides the user with support information indicating the relationship between the issues and the services based on the service design data.

[0303] As a result, the user who creates the KPI tree can check the correspondence between the issues and the services in the KPI tree created so far or use it as a reference for service design in the KPI tree to be created by looking at the support information. Therefore, the server device 90 can support the creation of the KPI tree.

[0304] Further, the server device 90 traces the path from the service node set at the end of the KPI tree to the KGI node set at the top, and extracts the issues indicated by each of the KGI nodes, KPI nodes, and factor nodes existing on the path, and the service indicated by the service node. As a result, the server device 90 can efficiently and accurately extract the relationship between the issues and services set in the KPI tree, so that the accuracy of the support information provided to the user can be improved.

[0305] Also, the server device 90 manages the KPI tree in association with the attributes of the customers who use the KPI tree. When the attributes of a customer are specified, the server device 90 outputs support information based on the classification result of the issues and countermeasures extracted from the KPI tree of the customer having the specified attributes, that is, the service design data. Thereby, a user who creates a KPI tree can, for example, check or refer to the correspondence between the issues and services set in the KPI trees used by other customers having similar attributes based on the attributes of the customers in charge. Therefore, the server device 90 can support the creation of the KPI tree.

[0306] Also, the server device 90 outputs, as support information, support information representing the composition ratio for each classification of issues and the number of usage times for each classification of services. Thereby, a user who creates a KPI tree can easily check the usage status of the issues and services in the KPI trees created so far, and thus can use it as an index for service design. Therefore, the server device 90 can support the creation of the KPI tree.

[0307] In addition, the above-described multiple embodiments can be appropriately modified and implemented by changing a part of the configuration or function of each of the above-described apparatuses. Therefore, below, some modification examples according to the above-described embodiments will be described as other embodiments. Note that below, mainly the points different from the above-described embodiments will be described, and detailed descriptions of the points common to the already described content will be omitted. Also, the modification examples described below may be implemented individually or in appropriate combinations.

[0308] (Modification Example 1) In the above-described embodiment, an example in which the terminal device 10 and the server devices (server device 20, server device 50, server device 90) cooperate to display various screens provided from the server device on the terminal device 10 has been shown. However, it is not limited to this, and a form in which the terminal device 10 displays alone may also be used.

[0309] In this case, the terminal device 10 can display screens of various screens by including functional units such as, for example, the above-described GUI providing unit 211, design support unit 212 (design support unit 512, design support unit 912), grouping processing unit 213, data analysis unit 216 (data analysis unit 916), and node candidate management unit 517. Note that the terminal device 10 is assumed to be in a state where it can read from and write to various DBs or tables held by the server device.

[0310] Also, in this case, part or all of the DBs and tables held by the server device may be held by the terminal device 10, or may be held by another device (or cloud) accessible by the terminal device 10.

[0311] (Modification Example 2) In the above-described first embodiment, the server device 20 maintains the node names of the nodes included in the KPI tree. However, it is not limited to this, and a configuration may be adopted in which the node names are actually changed based on the grouping information registered in the grouping master 265.

[0312] In this case, for example, the clustering processing unit 213, in cooperation with the design support unit 212, during the process of creating the KPI tree, when a node that meets the conditions of the node name and node type of the clustering source in the clustering information is set, it clusters (changes) to the node name of the clustering destination. Note that it is preferable for the clustering processing unit 213 to display a screen for confirming the change to the node name of the clustering destination and change the node name after obtaining the user's consent.

[0313] As a result, the server device 20 can change to the node name based on the clustering information during the process of the user creating the KPI tree. Therefore, the server device 20 can suppress fluctuations in the node name and can support the creation of the KPI tree. In addition, since the server device 20 can also change the node name after confirming with the user, it is possible to improve the convenience of the user regarding the determination of the node name.

[0314] Note that the timing for changing the node name is not limited to the time of creating the KPI tree and may be other timings. For example, it may be configured to automatically change the node name of the KPI tree stored in the KPI tree DB 261 by batch processing such as once a day. Also, for example, it may be configured such that the change of the node name is manually started based on an instruction from a data administrator.

[0315] (Modification Example 3) In the above-described third embodiment, a service node is targeted as an example of the second node, but a solution node may also be targeted. For example, when the solution node is at the end, the data analysis unit 916 may perform extraction by tracing the path from the solution node toward the KGI node. In this case, the data analysis unit 916 can perform the same processing as the service node by classifying the node name set for the solution node as a service name.

[0316] The programs executed by the respective devices of the above-described embodiments are provided in a state pre-installed in a ROM, a storage unit, or the like. The programs executed by the respective devices of the above-described embodiments may be configured to be recorded and provided on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk), or the like, in an installable format or an executable format file.

[0317] Furthermore, the programs executed by the respective devices of the above-described embodiments may be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the programs executed by the respective devices of the above-described embodiments may be configured to be provided or distributed via a network such as the Internet.

[0318] As described above, the embodiments of the present invention have been described. However, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments and their modifications can be implemented in various other forms, and various omissions, replacements, changes, and combinations can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention and are also included in the invention described in the claims and its equivalent scope.

Explanation of Reference Numerals

[0319] 1 Business Support System 10 Terminal Device 20, 50, 90 Server Device 111 Display Control Unit 112 Operation Reception Unit 211 GUI Provision Unit 212, 512, 912 Design Support Unit 213 Grouping Processing Unit 214 Display Control Unit 215 Operation Reception Unit 216, 916 Data Analysis Unit 517 Node Candidate Management Unit 261 KPI Tree DB 262 Business Flow DB 263 Temporary Registration Table 264 Item Master 265 Grouping Master 561 Node Candidate Table 562 Temporary Registered Node Candidate Table 961 Customer Data Table 962 Problem Master Table 963 Service Master Table 964 Service Design Data Table

Prior Art Documents

Patent Documents

[0320]

Patent Document 1

Claims

1. An information processing apparatus for assisting in creating tree data in which the relationship between a node indicating a management issue and a node indicating a countermeasure for the issue is hierarchically set in a tree structure, a storage unit that stores the tree data, output means for outputting support information indicating the relationship between an issue and a countermeasure, derived based on the tree data stored in the storage unit in response to a request; An information processing apparatus comprising:

2. extraction means for extracting the issue and the countermeasure corresponding to the issue from the tree data stored in the storage unit; classification means for classifying the issues and countermeasures extracted by the extraction means for each type; further comprising, wherein the output means outputs the support information indicating the relationship between the issues and countermeasures classified by the classification means; The information processing apparatus according to claim 1.

3. The extraction means extracts the issues and countermeasures indicated by the nodes on the path by sequentially following the path from a predetermined node of the existing tree data to the nodes set above; The information processing apparatus according to claim 2.

4. The storage unit stores the tree data in association with the attributes of the user who uses the tree data, when the attributes of the user are specified, the output means outputs the support information based on the classification results of the classification means of the issues and countermeasures extracted from the tree data corresponding to the specified attributes; The information processing apparatus according to claim 2.

5. The output means outputs support information representing the composition ratio for each classification of the issues; The information processing apparatus according to claim 2.

6. The output means outputs support information representing the number of uses for each classification of the countermeasures. The information processing apparatus according to claim 2.

7. A computer of an information processing apparatus that supports creation of tree data in which the relationship between a node indicating a management issue and a node indicating a countermeasure for the issue is hierarchically set in a tree structure, Storage control means for storing the tree data in a storage unit, Output means for outputting support information indicating the relationship between an issue and a countermeasure, which is derived based on the tree data stored in the storage unit in response to a request, A program for causing the computer to function as such.

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