Information processing device and program

Abstract

To provide an information processing device and program capable of improving usability related to a KPI tree.SOLUTION: A server device in a business support system is provided with a name identification processing part including acquisition means for acquiring node names and node types of nodes from tree data obtained by gradually setting relations showing nodes showing management goals and nodes showing measures for achieving the goals in a tree structure state, extraction means for extracting a reference node name of a set similar to sets of the node names and the node types acquired by the acquisition means from a first storage part for storing sets of reference node names and node types to be a name identification reference, and registration means for associating the node name and the node type acquired by the acquisition means with the reference node name extracted by the extraction means to register them in a second storage part, and executes processing relating to name identification of the node names of the nodes included in a KPI tree by cooperating with a GUI provision part and a design support part.SELECTED DRAWING: Figure 11

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 or 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 flow. For example, conventionally, a technique has been proposed that can automatically create a business flow so that the input / output relationships between adjacent operations are continuous.

[0003] By the way, the KPI tree represents various elements as nodes, 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.

[0004] However, in the above-described KPI tree, for example, if there is a variation in the node names between nodes intended to have the same content, it cannot be integrated and processed when analyzing and utilizing the KPI tree, and there is a possibility that an accurate processing result cannot be obtained.

Summary of the Invention

Problems to be Solved by the Invention

[0005] The problem to be solved by the present invention is to provide an information processing apparatus and a program capable of improving the usability related to the KPI tree.

Means for Solving the Problems

[0006] The information processing apparatus of the embodiment includes: an acquisition means for acquiring the node name and node type of a node from tree data in which the relationship between a node indicating a management objective and a node indicating a strategy for achieving that objective is set in a stepwise tree structure; an extraction means for extracting a set of reference node names similar to the set of node name and node type acquired by the acquisition means from a first storage unit that stores a set of reference node names and node types that serve as a basis for matching; and a registration means for associating the node name and node type acquired by the acquisition means with the reference node name extracted by the extraction means and registering it in a second storage unit. The acquisition means acquires the node name and the node type from among the nodes set in the tree data, from nodes that have a combination of node name and node type that is not registered in the first storage unit and the second storage unit. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a diagram showing an example configuration of a business support system according to an embodiment. [Figure 2] Figure 2 shows an example of the hardware configuration of a terminal device according to this embodiment. [Figure 3] Figure 3 shows an example of the hardware configuration of a server device according to this embodiment. [Figure 4] Figure 4 shows an example of the data structure of the KPI tree database according to the embodiment. [Figure 5] Figure 5 shows an example of a visualized KPI tree according to the embodiment. [Figure 6] Figure 6 shows an example of the data structure of the business flow database according to the embodiment. [Figure 7] Figure 7 shows an example of a visualized business flow according to the embodiment. [Figure 8] Figure 8 shows an example of the data structure of a provisional registration table according to the embodiment. [Figure 9] Figure 9 shows an example of the data structure of an item master according to an embodiment. [Figure 10] Figure 10 shows an example of the data structure of a name matching master according to the embodiment. [Figure 11]Figure 11 shows an example of the functional configuration of a terminal device and a server device according to an embodiment. [Figure 12] Figure 12 shows an example of a screen provided by the server device of the embodiment. [Figure 13] Figure 13 shows an example of a screen provided by the server device of the embodiment. [Figure 14] Figure 14 shows an example of a screen provided by the server device of the embodiment. [Figure 15] Figure 15 is a flowchart showing an example of the processing performed by the server device of the embodiment. [Figure 16] Figure 16 is a flowchart showing an example of the processing performed by the server device of the embodiment. [Figure 17] Figure 17 is a flowchart showing an example of the processing performed by the server device of the embodiment. [Modes for carrying out the invention]

[0008] The embodiments will be described in detail below with reference to the drawings. However, the invention is not limited to the embodiments described below.

[0009] Figure 1 shows an example configuration of a business support system according to an embodiment. As shown in Figure 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 connected to each other via a network N such as a LAN (Local Area Network).

[0010] Terminal device 10 is a terminal device used by users of the business support system 1. Terminal device 10 performs various processes in response to user operations. For example, a user can use various functions provided by server device 20 by operating terminal device 10 to access server device 20. Terminal device 10 can be implemented as a stationary terminal device such as a PC (Personal Computer), or a portable terminal device such as a notebook PC, tablet, or smartphone.

[0011] 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 viewing a KPI tree and a business process, which will be described later.

[0012] In this embodiment, an example in which the server device 20 is realized by a single information processing device will be described, but it is not limited to this. For example, the server device 20 may be realized by a plurality of information processing devices by means of technologies such as cloud computing.

[0013] Next, the configurations of the terminal device 10 and the server device 20 described above will be described.

[0014] 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 a computer configuration such as a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, and a RAM (Random Access Memory) 13.

[0015] 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.

[0016] The terminal device 10 also includes a display unit 14, an operation unit 15, a storage unit 16, and a communication unit 17.

[0017] 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.

[0018] The storage unit 16 is composed of a storage medium such as an HDD (Hard Disk Drive) or flash memory, and retains its contents even when the power is cut off. The storage unit 16 stores programs that the CPU 11 can execute 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.

[0019] The CPU 11 performs various processes by operating according to programs stored in the ROM 12 and memory unit 16 and loaded into the RAM 13.

[0020] 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.

[0021] Figure 3 shows 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, ROM 22, and RAM 23.

[0022] The CPU 21 is an example of a processor that comprehensively controls all parts of the server device 20. The ROM 22 stores various programs. The RAM 23 is a workspace for displaying programs and various data.

[0023] The server device 20 also includes a display unit 24, an operation unit 25, a storage unit 26, and a communication unit 27.

[0024] 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. The operation unit 25 may be a touch panel provided on the display screen of the display unit 24.

[0025] The memory unit 26 is composed of a storage medium such as an HDD or flash memory, and retains its contents even when the power is cut off. The memory unit 26 stores programs that the CPU 21 can execute and various setting information. For example, the memory unit 26 stores web application programs that can provide various functions to the terminal device 10. The CPU 21 executes various processes by operating according to programs stored in the ROM 22 and the memory unit 26 and loaded into the RAM 23.

[0026] Furthermore, the memory unit 26 stores the KPI tree DB 261, business flow DB 262, temporary registration table 263, item master 264, and data matching master 265, etc.

[0027] The KPI Tree DB261 is a table or database for storing and managing KPI trees. Here, a KPI tree is tree data in a tree structure where the relationship between an organization's or company's management goals (the final goal described later) and the measures to achieve those goals (intermediate goals, factors, solutions, services, etc. described later) is set stepwise by nodes.

[0028] Figure 4 shows an example of the data structure of the KPI tree DB261. As shown in Figure 4, the KPI tree DB261 stores customer names, KPI trees, etc., associating each KPI tree with an identifiable tree ID.

[0029] The "Customer Name" field contains information that identifies the customer to whom the KPI tree applies. The "KPI Tree" field contains the actual data for the KPI tree (hereinafter also referred to as the data file) or an address indicating the location where the data file is stored.

[0030] A KPI tree is created using methods such as KPIs (Key Performance Indicators). A KPI tree can be represented in a visualized form, as shown in Figure 5, for example.

[0031] Figure 5 shows an example of a visualized KPI tree. Specifically, Figure 5 shows the visualized KPI tree applied to the customer "ABC Supermarket" shown in Figure 4.

[0032] As shown in Figure 5, a KPI tree consists of multiple nodes connected in a tree structure. Here, the root node, Final Goal Node A, is the node for setting the achievement goal. Final Goal Node A corresponds to, for example, a KGI (Key Goal Indicator). For example, if the ultimate goal is to increase store sales, then Final Goal Node A will be set to a node name such as "Sales" that indicates the content of the goal.

[0033] The final target node A is connected to one or more intermediate target nodes B. It is also possible to connect one or more intermediate target nodes B to each intermediate target node B. Each intermediate target node B is assigned a node name that represents an intermediate goal needed to achieve the goal (final or intermediate target) set in the node directly above it. An intermediate target node B might correspond to a KPI (Key Performance Indicator), for example.

[0034] Figure 5 shows an example where, below the final target node A, intermediate target node Ba has an intermediate target content set to increase the number of customers, and intermediate target node Bb has an intermediate target content set to increase the average customer spending. Furthermore, below intermediate target node Bb, an example is shown where intermediate target node Bc has a node name that represents an increase in the number of items sold, and intermediate target node Bd has a node name that represents an increase in the average price per item.

[0035] Furthermore, in the KPI tree, it is possible to place factor nodes C below the intermediate goal node B, which represent the factors necessary to achieve the intermediate goal set in intermediate goal node B. Factor node C corresponds to, for example, a KSF (Key Success Factor).

[0036] Figure 5 shows an example where, under the intermediate target node Ba, factor nodes Ca to Cd are placed with the node names "Quality Improvement," "Product Assortment," "Sales Floor," and "Advertising" as factors for achieving an increase in the number of customers visiting the store. It also shows an example where, under the intermediate target node Bc, factor nodes Ce and Cf are placed with the node names "Sales Promotion" and "Impulse Buying" as factors for achieving an increase in the number of items sold. Furthermore, it shows an example where, under the intermediate target node Bb, factor node Cg is placed with the node name "Improved Customer Understanding" as a factor for achieving an increase in the average customer spending.

[0037] Furthermore, in the KPI tree, it is possible to place a Solution Node D below the Intermediate Target Node B or Factor Node C, which represents a solution that achieves (resolves) the intermediate objective or factor set in the node directly above it.

[0038] Figure 5 shows an example where solution nodes Da and Db, named "Store Information Visualization" and "Product Assortment Optimization," are placed under factor nodes Ca to Cc. It also shows an example where solution nodes Dc to De, named "Coupon Issuance," "Point Management," and "POP Creation," are placed under factor node Ce. Furthermore, it shows an example where solution node Df, named "CRM (Customer Relationship Management)," is placed under factor node Cg.

[0039] Furthermore, in the KPI tree, it is possible to place a service node E under a factor node C or solution node D, which represents a specific service for realizing the factor or solution set in the node directly above it. Here, service node E is located at the end of the tree structure and represents a specific measure for realizing the factor or solution set in the node directly above it.

[0040] Figure 5 shows an example where a service node Ea, named "Service A," is placed under the solution node Dc.

[0041] Each node in the KPI tree is assigned a node ID to identify it. Furthermore, information about the corresponding node is stored in association with the node ID. For example, service node E is associated with the business flow related to service implementation and verification items related to service effectiveness evaluation.

[0042] The KPI tree described above can be saved, for example, in JSON (JavaScript Object Notation) format. However, the KPI tree is not limited to JSON; it may also be saved in other data formats such as XML (Extensible Markup Language).

[0043] Returning to Figure 3, the business flow DB262 is a table or database for storing and managing business flows. A business flow is a data file that describes each element involved in the execution of a business and the execution content performed by that element as a series of procedures. Specifically, a business flow describes the execution content and procedures performed by each element involved in the implementation of a service.

[0044] Figure 6 shows an example of the data structure of the business flow DB262. As shown in Figure 6, the business flow DB262 stores the target service, flow ID, business flow name, and data file in association with each other.

[0045] The "Target Services" field registers information specifying the service corresponding to the business process described in the business flow. Specifically, it registers the node ID of the service node E designated as the target service, the tree ID of the KPI tree to which the service node E belongs, etc. However, this is not the only way to specify the target service.

[0046] The Flow ID field registers a Flow ID that identifies the business flow. The Business Flow Name field registers information indicating the name of the business flow. For example, the Business Flow Name may be the name of the service performed by the business flow (the node name of service node E). The Data File field registers the data file of the business flow or an address indicating the location where the data file is stored.

[0047] Business flows are created using methods such as flowcharts and BPMN (Business Process Modeling Notation). Business flows should be created according to the service content, but if the service content is common or similar, the same business flow can be used even if the KPI trees are different. Figure 6 shows an example in which the business flow with flow ID "F01" is used in service node Ea, which is included in the KPI trees with tree IDs T01 and T02, respectively.

[0048] Business processes are created using methods such as flowcharts and BPMN (Business Process Modeling Notation). Business processes can be represented in a visualized form, for example, as shown in Figure 7.

[0049] Figure 7 shows an example of a visualized business process flow. Note that Figure 7 is an example of the business process flow related to service node Ea (Service A) in the KPI tree shown in Figure 5.

[0050] As shown in Figure 7, in the business flow, the sequence of actions (or processes) related to the implementation of service A is described for each element that performs the action between the start event ST and the end event EN. The business flow in Figure 7 shows an example where the elements are described as "customers" visiting the store, "surveillance cameras" and "payment systems" installed in the store, and "store employees" working in the store.

[0051] Here, "surveillance cameras" are an example of hardware resources, and are installed, for example, at multiple locations within a store. Similarly, "payment systems" are an example of software resources, and are implemented through the collaboration of multiple PCs (Personal Computers), such as POS systems, and applications installed on those PCs. Furthermore, additional services provided in conjunction with payment (e.g., point services) may also be included in the business flow. Hereafter, the hardware resources, software resources, and additional services related to the implementation of the target services will be collectively referred to as "elements."

[0052] In the business flow diagram in Figure 7, the "customer" flow is first described as entering the store (step Qa), selecting the products to be purchased (step Qb), and proceeding to the cash register (step Qc). The "surveillance camera" flow installed in the store is described as taking a picture of the "customer" heading to the cash register (step Qd) and transmitting the captured image data to the payment system installed in the store (step Qe). The "payment system" flow is described as receiving the image data from the "surveillance camera" (step Qf) and displaying customer information such as the "customer's" attributes derived from the image data on a display device (step Qg).

[0053] Furthermore, the workflow for a "store clerk" operating the register is described as follows: confirming customer information displayed by the "payment system" (step Qh), and performing register operations for the items brought in by the "customer" (step Qi). In addition, it is described that the "payment system" executes the "payment processing" in conjunction with the "store clerk's" register operations (step Qj).

[0054] Furthermore, it is described that the "customer" pays for the goods (step Qk) in accordance with the "payment processing" of the "payment system" and leaves the store (step Ql). It is also described that the "payment system" stores data showing the details of this transaction upon payment (step Qm).

[0055] Furthermore, when implementing a coupon service, for example, the payment system may issue coupons that offer discounts or reductions based on the purchased goods or the amount of the payment, and store the number of coupons issued on a daily basis. In addition, for example, the payment system may apply discounts or reductions to the price of goods based on the coupons presented during the payment process, and store the number of coupons used on a daily basis.

[0056] Furthermore, when implementing a points service, for example, the payment system identifies the member number of the "customer" represented in the photographic data by comparing the photographic data received in step Qf with the facial image of each member that has been registered in advance. The payment system then accumulates and stores the points issued according to the purchase amount, associating them with the identified member number.

[0057] The business process flow described above is saved, for example, in JSON format. However, the business process flow is not limited to JSON; it may also be saved in other data formats such as XML.

[0058] Furthermore, in this embodiment, the KPI tree and business flow may be pre-created, or they may be created via the terminal device 10 or the like with assistance from the server device 20. In the latter case, for example, the server device 20 provides the terminal device 10 with a screen (GUI (Graphical User Interface)) to assist in viewing, creating, and editing the KPI tree and business flow.

[0059] Specifically, the server device 20 provides the terminal device 10 with a screen that allows creation and editing of various nodes and the relationships between nodes in a visualized state. Then, once the creation or editing of the KPI tree is complete, the server device 20 stores the KPI tree in the KPI tree DB 261.

[0060] Furthermore, when any service node E included in the KPI tree is selected, the server device 20 provides a screen that allows the creation and editing of business flows and checklists for the service corresponding to that service node E. When either a business flow or a checklist is created, the server device 20 stores it in the corresponding database, associating it with the node ID and tree ID of service node E.

[0061] Returning to Figure 3, the provisional registration table 263 is a table or database for storing and managing pairs 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 data matching master 265. The provisional registration table 263 has a data structure, for example, as shown in Figure 8.

[0062] Figure 8 shows an example of the data structure of the provisional registration table 263. As shown in Figure 8, the provisional registration table 263 stores information such as node name, node type, KPI tree link, and data creation date in association with each other.

[0063] The node name and node type are registered in the provisional registration table 263 with the node name and node type of the node that was selected for registration (hereinafter also referred to as the target node).

[0064] Figure 8 shows an example where a node named "Sales Revenue" and a node type named "KGI" has been registered. Similarly, it also shows examples where a candidate node named "Average Customer Spending" and a node type named "KPI" has been registered, a candidate node named "Attractive Product Assortment" and a node type named "Factor (KSF)" has been registered, and a candidate node named "Inventory Turnover Rate" and a node type named "KPI" has been registered.

[0065] The KPI tree link contains information that identifies the KPI tree to which the target node belongs. For example, the KPI tree link may contain the tree ID of the KPI tree. Alternatively, the KPI tree link may also contain information that identifies the target node (e.g., node ID) along with the tree ID to which the target node belongs. The data creation date stores data indicating the year, month, and day registered in the provisional registration table 263.

[0066] Returning to Figure 3, the item master 264 is an example of the first storage unit. The item master 264 is a table or database for storing and managing the reference node names used as the basis for data matching. The item master 264 has a data structure, for example, as shown in Figure 9.

[0067] Figure 9 shows an example of the data structure of item master 264. As shown in Figure 9, item master 264 stores the reference node name, node type, KPI tree link, and data creation date in association with each other.

[0068] The "Reference Node Name" field registers the node name to be used as the basis for data matching (hereinafter also referred to as the "Reference Node Name"). The "Node Type" field registers the node type of the node corresponding to the Reference Node Name (hereinafter also referred to as the "Reference Node").

[0069] Figure 9 shows an example where a set of base node names "Sales" and node types "KGI" is registered. Similarly, it also shows examples where sets of base node names "Number of Visitors" and node types "KPI", base node names "Average Customer Spending" and node types "KSI", and base node names "Product Assortment" and node types "Factor" are registered.

[0070] The KPI tree link contains information that identifies the KPI tree to which the reference node belongs. For example, the KPI tree link may contain the tree ID of the KPI tree. Alternatively, the KPI tree link may contain information that identifies the reference node (e.g., node ID) along with the tree ID of the KPI tree to which the reference node belongs. The data creation date stores data indicating the year, month, and day registered in item master 264.

[0071] Returning to Figure 3, the data matching master 265 is an example of the second storage unit. The data matching master 265 is a table or database for storing and managing the correspondence between the node names of the data matching source and the node names of the data matching destination. The data matching master 265 has a data structure, for example, as shown in Figure 10.

[0072] Figure 10 shows an example of the data structure of the data matching master 265. As shown in Figure 10, the data matching master 265 stores the node name, node type, base node name, and data creation date in association with each other.

[0073] The node name is registered as the source node for data matching. The reference node name is registered as the target reference node name for data matching. The node type is registered as the node type to be matched. The data creation date stores data indicating the year, month, and day it was registered in the data matching master 265.

[0074] Here, the combination of node name, node type, and base node name functions as name matching information that defines the name matching rules. Specifically, the name matching information specifies that, under the conditions of the defined node type, the source node name will be matched (hereinafter also referred to as conversion) to the target base node name.

[0075] Figure 10 shows an example where a node with the node type "KGI" and the node name "Sales Revenue" is configured to be changed to a node named "Sales Revenue". Similarly, it shows examples where a node with the node type "KPI" and the node name "Average Customer Spending" is configured to be changed to a node named "Average Customer Spending", a node with the node type "Factor" and the node name "Attractive Product Range" is configured to be changed to a node named "Product Range", and a node with the node type "KGI" and the node name "Sales Revenue" is configured to be changed to a node named "Sales Revenue". This allows, for example, nodes named "Sales Revenue" and "Sales Revenue" to be treated as the same type of node as a node named "Sales Revenue".

[0076] Furthermore, the data matching information may not be limited to a one-way conversion from the data matching source to the data matching destination, but may also specify a reverse conversion of node names from the data matching destination to the data matching source. In this case, for example, a node whose node type is "KGI" and whose node name is "Sales" will be reverse-converted to node names "Sales Revenue" and "Sales". In other words, nodes whose node names are "Sales", "Sales Revenue", and "Sales" can be treated as the same type of node.

[0077] Returning to Figure 3, the communication unit 27 is a communication interface that can connect to the network N. The communication unit 27 communicates with external devices such as the terminal device 10 via the network N.

[0078] Next, the functional configurations of the terminal device 10 and the server device 20 will be described with reference to Figure 11. Figure 11 is a diagram showing an example of the functional configurations of the terminal device 10 and the server device 20.

[0079] As shown in Figure 11, the terminal device 10 includes a display control unit 111 and an operation reception unit 112 as functional units.

[0080] Some or all of the functional components of the terminal device 10 may be implemented as software through the cooperation of the terminal device 10's processor (e.g., CPU 11) and a program stored in its memory (e.g., ROM 12, storage unit 16). Alternatively, some or all of the functional components of the terminal device 10 may be implemented as hardware through dedicated circuits or the like mounted on the terminal device 10.

[0081] 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 displays various operation screens on the display unit 14 based on information provided by the server device 20.

[0082] The operation reception unit 112 of the terminal device 10 receives user operations 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 server device 20 of the details of that operation.

[0083] On the other hand, the server device 20 includes a GUI provision unit 211, a design support unit 212, a name matching processing unit 213, a display control unit 214, an operation reception unit 215, and a data analysis unit 216 as functional units.

[0084] Some or all of the functional components of the server device 20 may be implemented as software through the cooperation of the server device 20's processor (e.g., CPU 21) and a program stored in its memory (e.g., ROM 22, storage unit 26). Alternatively, some or all of the functional components of the server device 20 may be implemented as hardware through dedicated circuits or the like mounted on the server device 20.

[0085] The GUI provider unit 211, in cooperation with other functional units, provides the terminal device 10 with information that enables the display of various operation screens (hereinafter also simply referred to as "screens"). Here, the GUI provider unit 211 may provide data representing a screen, or it may provide various content data related to the display of a screen. Hereinafter, the provision of information related to the display of a screen by the GUI provider unit 211 to the terminal device 10 will be referred to as "providing" a screen or "displaying" a screen.

[0086] The design support unit 212, in collaboration with the GUI provision unit 211, provides screens to support the creation of KPI trees and business flows.

[0087] For example, the design support unit 212 provides a screen that allows the user to create a KPI tree by arranging various nodes, edges, etc., as drawing parts. On this screen, the user can create and edit a tree-like KPI tree by arranging various nodes on the screen and arranging links to connect 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.

[0088] Furthermore, the design support unit 212 provides a screen that allows the user to select a KPI tree to be viewed or edited based on the KPI tree DB 261. When a KPI tree is selected, the design support unit 212 reads the data file of that KPI tree from the KPI tree DB 261 and provides a screen that visualizes the KPI tree.

[0089] Furthermore, the design support unit 212 provides a screen that allows the creation of business flows by arranging drawing parts and the like that correspond to the BPMN notation rules. For example, when the design support unit 212 receives an operation to instruct the service node E included in the KPI tree to generate a business flow (flow ID), it provides a screen for creating the business flow. Then, when the design support unit 212 receives an operation to complete the creation or editing of the business flow, it generates a data file representing the business flow and stores it in the business flow DB 262 in association with the target service.

[0090] Furthermore, the design support unit 212 displays the business flow in response to user operations. For example, when a service node E in the KPI tree is selected, the design support unit 212 displays the business flow by visualizing the data files associated with that service node E.

[0091] The name matching processing unit 213 is an example of an acquisition means, an extraction means, and a registration means. The name matching processing unit 213 works in cooperation with the GUI provisioning unit 211 and the design support unit 212 to perform processing related to the name matching of node names of nodes included in the KPI tree.

[0092] Specifically, when a KPI tree is created (or edited) with the assistance of the design support unit 212, the data matching processing unit 213 retrieves the node name and node type from the nodes included in the KPI tree and registers them in the temporary registration table 263.

[0093] More specifically, the data matching processing unit 213 compares the node name and node type pairs of each node included in the KPI tree with the node name and node type pairs registered in the item master 264 and the data matching master 265. Next, the data matching processing unit 213 extracts nodes from the KPI tree that have node name and node type pairs not registered in the item master 264 and the data matching master 265 as target nodes. Then, the data matching processing unit 213 obtains the node name and node type from the target nodes and registers them in the provisional registration table 263 along with the KPI tree link of the KPI tree to which the target node belongs. In the following, for the sake of explanation, the node name and node type pairs registered in the provisional registration table 263 will also be referred to as target nodes.

[0094] Here, the data matching processing unit 213 may limit the node types of target nodes extracted from the KPI tree to node types related to the identification of services such as KGI, KPI, and KSF. This makes it possible to exclude solution nodes and service nodes whose node names are expressed in a variety of ways from the data matching process, thereby preventing data matching from being performed unintentionally.

[0095] The timing of extracting target nodes and registering them in the temporary registration table 263 is not particularly restricted and can be set arbitrarily. For example, the data matching processing unit 213 may extract target nodes from the KPI tree and register them in the temporary registration table 263 when the created (or edited) KPI tree is stored in the KPI tree DB 261. Alternatively, the data matching processing unit 213 may be configured to extract target nodes from the KPI tree stored in the KPI tree DB 261 and register them in the temporary registration table 263 as a batch process, such as once a day. Furthermore, the data matching processing unit 213 may be configured to extract target nodes and register them in the temporary registration table 263 based on instructions from the data administrator.

[0096] Furthermore, the data matching processing unit 213 displays a screen showing the registration status of the temporary registration table 263 (hereinafter also referred to as the temporary registration list screen) at predetermined times. For example, the design support unit 212 displays the temporary registration list screen in response to instructions from the data administrator.

[0097] Figure 12 is a diagram showing an example of a screen provided by the server device 20, and shows an example of a temporary registration list screen. As shown in Figure 12, the temporary registration list screen 30 has a display area 31 for displaying a list of node name and node type pairs registered in the temporary registration table 263.

[0098] Display area 31 has ID, node name, and node type as data items. ID is an identifier used to manage each target node registered in the temporary registration table 263. For example, ID is an ascending number assigned in the order of registration in the temporary registration table 263. Node name and node type display the node name and node type of the target node registered in the temporary registration table 263. Note that the temporary registration list screen 30 in Figure 12 shows the registration status of the temporary registration table 263 as explained in Figure 8.

[0099] Furthermore, the temporary registration list screen 30 is provided with a registration button 32. The registration button 32 is an operator used to instruct registration to the item master 264 or the data matching master 265. After a specific ID is selected from the display area 31, the data matching processing unit 213 accepts the operation of the registration button 32 and displays a screen (hereinafter also referred to as the 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 data matching master 265.

[0100] Figure 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 Figure 13, the registration screen 40 has a first display area 41 and a second display area 42.

[0101] The first display area 41 displays information about the target node selected on the temporary registration list screen 30. Specifically, the first display area 41 displays the node name and node type of the target node.

[0102] Furthermore, the first display area 41 is provided with a first display button 411 for instructing the display of the KPI tree. When the data matching processing unit 213 receives an operation of the first display button 411, it reads 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 temporary registration list screen 30. Then, the data matching processing unit 213 works in cooperation with the design support unit 212, etc., to display a screen representing the read KPI tree.

[0103] For example, the data matching processing unit 213 displays the KPI tree with a screen configuration similar to that shown in Figure 5. Alternatively, the data matching processing unit 213 may highlight the target nodes included in the KPI tree to make them identifiable from other nodes. The screen displaying the KPI tree may be displayed separately from the registration screen 40, or it may be displayed together with the registration screen 40.

[0104] The second display area 42 displays information about node names that are candidates for data matching. Specifically, the second display area 42 displays the base node names of the data matching candidates extracted from the item master 264 based on the node name and node type of the target node selected on the provisional registration list screen 30.

[0105] Here, the name matching processing unit 213 extracts reference node names for name matching candidates from the item master 264 based on the node type of the target node and the string that constitutes the node name of the target node. Specifically, the name matching processing unit 213 extracts reference node names from the item master 264 that are the same as the target node and have a string similar to the node name of the target node. For example, the name matching processing unit 213 extracts reference node names as name matching candidates for which the similarity between strings is greater than or equal to a threshold (e.g., 80%). The method for calculating the similarity between strings is not particularly limited, and for example, known morphological analysis techniques can be used.

[0106] In the example above, the criteria for extracting candidates for name matching were that the node type was the same and the node names were similar, but the extraction criteria are not limited to these.

[0107] 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 criterion. 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 the reference node names of reference nodes whose similarity is above a threshold as name matching candidates. Here, the characteristics of other nodes may be either the node name or the node type, or both. Also, other nodes may be nodes connected to either the front or back of the target node and the reference node, or both.

[0108] 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 reference node names whose similarity is above a threshold as name matching candidates.

[0109] As another example, the name matching processing unit 213 may calculate the structural similarity between the entire KPI tree containing the target node and the entire KPI tree containing the reference node, and extract the reference node names of KPI trees whose similarity is above a threshold as name matching candidates.

[0110] In this way, by including structural similarity of KPI trees as an extraction criterion, it is possible to extract reference node names with similar roles within the KPI tree as candidates for name matching. Therefore, the accuracy of the name matching candidates can be improved. Note that the above extraction criteria may be applied individually or in combination. For example, reference node names may be extracted using structural similarity of the KPI tree along with similarity in notation (string).

[0111] Figure 13 shows an example where the target node's node name is "Sales" and node type is "KGI," and the base node name "Sales" is extracted as a candidate for matching. The matching processing unit 213 extracts multiple base node names as matching candidates and displays them in a list for selection. Furthermore, if no base node name matches the matching candidate, the matching processing unit 213 leaves the second display area 42 blank, as shown in Figure 14.

[0112] Here, Figure 14 shows an example of a screen provided by the server device 20, illustrating another example of a registration screen. In the registration screen 40 of Figure 14, an example of the display when no matching candidates exist for the target node's node name "Inventory Turnover Rate" and node type "KPI" is found.

[0113] Furthermore, if a reference node name corresponding to a candidate for name matching is extracted, a second display button 421 is provided in the second display area 42 to instruct the display of the KPI tree. When the name matching processing unit 213 receives an operation of the second display button 421, it reads 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 works in cooperation with the design support unit 212, etc., to display a screen representing the read KPI tree.

[0114] For example, the data matching processing unit 213 displays the KPI tree with a screen configuration similar to that shown in Figure 5. Alternatively, the data matching processing unit 213 may highlight the reference nodes included in the KPI tree to make them identifiable from other nodes. The screen displaying the KPI tree may be displayed separately from the registration screen 40, or it may be displayed together with the registration screen 40. It may also be displayed in a way that allows comparison with the KPI tree of the target node.

[0115] Thus, the registration screen 40 not only presents the base node name of the data matching candidate, but also has operators for displaying the KPI tree of the target node and the KPI tree of the data matching candidate. This allows, for example, the user of the terminal device 10 to compare and confirm the structure of the KPI tree of the target node and the KPI tree of the data matching candidate, and to determine a more appropriate base node name for data matching.

[0116] The registration screen 40 also includes a pull-down menu 43 for selecting a registration destination and an execution button 44 for instructing the user to perform the registration. The pull-down menu 43 has item master 264 and name matching master 265 as options, and is an operator that allows the user to select either one of the masters.

[0117] When the item master 264 is selected from the pull-down menu 43 and the execute button 44 is pressed, the data matching processing unit 213 registers the node name, node type, and KPI tree link of the target node in the item master 264. As a result, the node name of the target node is registered in the item master 264 as the base node name. For example, if a user assigns a new node name to a target node, they can register that node name as the base node name in the item master 264 and use that base node name as a candidate for data matching.

[0118] Furthermore, when the execution button 44 is pressed while the data matching master 265 is selected from the pull-down menu 43, the data matching processing unit 213 registers the node name and node type of the target node in the data matching master 265, associating them with the base node name of the data matching candidate. Specifically, the data matching processing unit 213 generates data matching information using the node name of the target node as the source node name and the base node name of the data matching candidate as the base node name of the data matching destination. The data matching processing unit 213 then registers the generated data matching information in the data matching master 265. If there are multiple data matching candidates, the data matching processing unit 213 generates data matching information using the base node name of one data matching candidate selected by the user.

[0119] Here, the data matching information registered in the data matching master 265 is used, for example, when analyzing the KPI tree based on node names. In other words, in this embodiment, the node names set for each node in the KPI tree are maintained as they are, and the conversion of node names based on the data matching information is performed internally. Therefore, in this embodiment, it is possible to eliminate inconsistencies in the node names set in the KPI tree while maintaining the display format of the created KPI tree.

[0120] In the above explanation, the destination master can be selected via the pull-down menu 43. However, if, for example, no matching candidates exist (see Figure 14), it will not be possible to register to the matching master 265. Therefore, if no matching candidates exist, the only registration destination selectable via the pull-down menu 43 may be the item master 264.

[0121] Returning to Figure 11, the display control unit 214 controls the display unit 24 to display various screens on it. For example, the display control unit 214 displays various screens provided by the GUI provider unit 211 on the display unit 24.

[0122] The operation reception unit 215 receives user input via the operation unit 25. For example, when the operation reception unit 215 receives an input for various operation support screens displayed on the display unit 24, it outputs the details of that input to the CPU 21.

[0123] The data analysis unit 216 is an example of an analysis method. The data analysis unit 216 performs various analysis processes based on the KPI tree stored in the KPI tree DB 261.

[0124] For example, when the data analysis unit 216 receives a node name and node type from a user, it searches the KPI tree DB 261 for KPI trees containing the specified node name and node type pair, and aggregates the number of KPI trees found (hereinafter also referred to as the number of trees). Specifically, when the data analysis unit 216 receives a node name and node type pair, it refers to the name matching master 265 and determines whether or not name matching information exists that contains the specified node name and node type pair.

[0125] If there is matching information for the specified node name and node type pair, and the specified node name is set as the matching destination, the data analysis unit 216 reads the corresponding node name from the matching source information. Next, the data analysis unit 216 expands the node names to be searched by using the specified node name and the node name read from the matching information as search conditions. Then, the data analysis unit 216 searches the KPI tree DB 261 for KPI trees that include any of the expanded node names and also include nodes of the specified node type. Finally, the data analysis unit 216 derives the tree ID and number of trees of the searched KPI trees as analysis results. For example, the data analysis unit 216 works in cooperation with the GUI provision unit 211 to display a screen showing the analysis results.

[0126] Furthermore, if there is data matching information with the specified pair set and the specified node name is set as the data matching source, the data analysis unit 216 reads the corresponding destination node name from the data matching information. Also, if there is other data matching information that includes the specified node type and destination node name pair, the data analysis unit 216 reads the source node name set in that other data matching information, i.e., other node names associated with the same base node name. Next, the data analysis unit 216 expands the node names to be searched by using the specified node name and the node name read from the data matching information as search conditions. Next, the data analysis unit 216 searches the KPI tree DB 261 for KPI trees that include any of the expanded node names and also include nodes of the specified node type. Finally, the data analysis unit 216 derives the tree ID and number of trees of the searched KPI trees as analysis results.

[0127] Thus, even if there are inconsistencies in node names, the data analysis unit 216 can analyze the KPI tree using the corresponding node names set in the matching information of the matching master 265, and can obtain analysis results with the inconsistencies in node names resolved.

[0128] The analysis processing performed by the data analysis unit 216 is not limited to the above example. However, when performing analysis processing based on node name and node type, the data analysis unit 216 shall perform analysis processing using the corresponding node names based on the matching information in the matching master 265.

[0129] The following describes an example of the operation of the server device 20, as described above, with reference to Figures 15 to 17. Figures 15 to 17 are flowcharts showing an example of the processing performed by the server device 20.

[0130] First, referring to Figure 15, we will explain an example of the first registration process, which registers node names in the provisional registration table 263.

[0131] When a 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).

[0132] Next, the data matching processing unit 213 compares the node name and node type pairs of the nodes included in the KPI tree stored in the KPI tree DB 261 with the node name and node type pairs registered in the item master 264 and the data matching master 265. Then, the data matching processing unit 213 extracts from the nodes included in the KPI tree that have node name and node type pairs not registered in the item master 264 and the data matching master 265 as target nodes (step S13).

[0133] Next, the data matching processing unit 213 obtains the node name and node type from the target node (step S14), registers the obtained information in the temporary registration table 263 along with the KPI tree link of the KPI tree to which the target node belongs (step S15), and then terminates this process.

[0134] Next, referring to Figure 16, an example of a second registration process in which the node names registered in the temporary registration table 263 are registered in the item master 264 or the name matching master 265 will be described.

[0135] The data matching processing unit 213, in response to instructions from the data administrator, etc., refers to the temporary registration table 263 (step S21) and determines whether or not the node name is registered in the temporary registration table 263 (step S22).

[0136] If the node name of the target node is registered in the temporary registration table 263 (step S22; Yes), the data matching processing unit 213 displays the temporary registration list screen 30, which shows the registration status of the temporary registration table 263 (step S23). Next, the data matching processing unit 213 waits until the registration button 32 is pressed for any one of the target nodes on the temporary registration list screen 30 (step S24; No).

[0137] When the data matching processing unit 213 receives an operation on the registration button 32 (step S24; Yes), it extracts a reference node name that will be a candidate for data matching from the item master 264 based on the node name and node type of the selected target node (step S25). Next, the data matching processing unit 213 displays the registration screen 40, which includes the extraction result from step S25 (step S26).

[0138] Next, the data matching processing unit 213 determines whether or not it has received a registration instruction to the item master 264 via the pull-down menu 43 and the execute button 44, etc. (step S27). If it has received a registration instruction to the item master 264 (step S27; Yes), the data matching processing unit 213 registers the node name, node type, and KPI tree link of the selected target node in the item master 264 (step S28), and proceeds to step S33.

[0139] Furthermore, if the data matching processing unit 213 does not accept a registration instruction to the item master 264 (step S27; No), it determines whether or not it has accepted a registration instruction to the data matching master 265 (step S29). If it accepts a registration instruction to the data matching master 265 (step S29; Yes), the data matching processing unit 213 associates the node name and node type of the selected target node with the base node name of the data matching candidate extracted in step S25 and registers them in the data matching master 265 (step S30), then proceeds to step S33. If there are multiple data matching candidates, the data matching processing unit 213 registers the base node name of one selected data matching candidate in the data matching master 265.

[0140] Furthermore, if the data matching processing unit 213 does not receive a registration instruction to the data matching master 265 (step S29; No), it determines whether or not an instruction to display the KPI tree has been received via the first display button 411 or the second display button 421, etc. (step S31). If an instruction to display the KPI tree has been received (step S31; Yes), the data matching processing unit 213 displays the corresponding KPI tree based on the KPI tree link related to the requested node (step S32).

[0141] Next, if the user instructs the data matching processing unit 213 to stop displaying the KPI tree, for example, the KPI tree display screen is closed and the process returns to step S27. In the case where the registration screen 40 and the KPI tree display screen are displayed simultaneously, the process may return to step S27 without waiting for an instruction to stop displaying the KPI tree. Also, if the KPI tree display is not instructed in step S31 (step S31; No), the data matching processing unit 213 returns to step S27.

[0142] In the following step S33, the data matching 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 data matching processing unit 213 returns to step S22 to determine whether or not the node name is registered in the temporary registration table 263. If the data matching processing unit 213 determines that the node name is not registered in the temporary registration table 263 (step S22; No), it terminates this process.

[0143] As a result of the above process, 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 name matching master 265.

[0144] Next, with reference to Figure 17, an example of KPI tree analysis processing will be explained. Note that this example demonstrates outputting the number of KPI trees containing a specified node as the analysis result, but the content of the analysis processing is not limited to this.

[0145] The data analysis unit 216 accepts the user's specification of the node to be analyzed (step S41). For example, when the KPI tree is displayed, if any node included in the KPI tree is specified as the target of analysis, the data analysis unit 216 accepts the specification of that node.

[0146] Next, the data analysis unit 216 obtains the node name and node type from the specified node (hereinafter also referred to as the specified node) (step S42). Then, the data analysis unit 216 reads the matching information containing the obtained node name and node type pair from the matching master 265 (step S43).

[0147] Next, the data analysis unit 216 expands the node name search conditions based on the alias of the specified node (the node name of the source or destination for data matching) set in the data matching information (step S44). Then, the data analysis unit 216 searches the KPI tree DB 261 for KPI trees containing nodes that meet the conditions based on the expanded node name and the node type of the specified node (step S45).

[0148] Then, the data analysis unit 216 outputs the number of trees in the KPI tree searched in step S45 as an analysis result (step S46), and terminates this process.

[0149] As described above, the server device 20 of this embodiment obtains the node name and node type set for a node from the KPI tree, and extracts a reference node name similar to the obtained node name and node type pair from the item master 264, which stores a set of reference node names and node types that serve as the basis for matching. The server device 20 then generates matching information that associates the node name and node type obtained from the KPI tree with the reference node name extracted from the item master 264, and registers it in the matching master 265.

[0150] As a result, the server device 20 can consolidate the node names of the nodes included in the KPI tree based on the name consolidation information stored in the name consolidation master 265. Furthermore, this allows the server device 20 to analyze the KPI tree even if there are variations in node names between nodes intended to represent similar content, thereby obtaining accurate analysis results. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0151] Furthermore, the server device 20 extracts nodes from the KPI tree that have a combination of node name and node type not registered in the item master 264 and the name matching master 265 as target nodes, and obtains the node name and node type from those target nodes. This allows the server device 20 to retain existing settings registered as the base node name and the node name from which the name matching is to be performed, and prevents duplicate registration, thereby enabling efficient generation of name matching information. Consequently, the server device 20 can improve the usability related to the KPI tree.

[0152] Furthermore, the server device 20 registers the node name and node type pairs selected by the user from the node name and node type pairs obtained from the KPI tree into the item master 264. This allows the server device 20 to add reference node names in response to user instructions, thereby improving user convenience. Consequently, the server device 20 can improve the usability related to the KPI tree.

[0153] Furthermore, the server device 20 extracts reference node names from the item master 264 that are identical in node type to the target node obtained from the KPI tree and have a string similar to the node name of the target node. This allows the server device 20 to extract reference node names intended to have the same content as the target node, thereby improving the accuracy of name matching. Consequently, the server device 20 can improve the usability related to the KPI tree.

[0154] Furthermore, 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 KPI trees with similar structures. As a result, the server device 20 can extract the reference node names of nodes whose roles within the KPI tree are similar to those of the target node, thereby improving the accuracy of name matching. Therefore, the server device 20 can improve the usability related to the KPI tree.

[0155] The embodiments described above can also be modified and implemented as appropriate by changing some of the configurations or functions of each of the devices described above. Therefore, several modifications of the embodiments described above will be described below as other embodiments. In the following, we will mainly describe the differences from the embodiments described above, and will omit detailed explanations of points that are common with what has already been described. Furthermore, the modifications described below may be implemented individually or in combination as appropriate.

[0156] (Variation 1) In the above embodiment, an example was shown in which the terminal device 10 and the server device 20 cooperate to display various screens provided by the server device 20 on the terminal device 10. However, the embodiment is not limited to this, and the terminal device 10 may also display the information on its own.

[0157] In this case, the terminal device 10 is equipped with functional units such as the GUI provision unit 211, design support unit 212, name matching processing unit 213, and data analysis unit 216 described above, and can display various screens related to the creation and editing of checklists, various screens related to the matching of node names, and various screens related to the analysis of KPI trees. The terminal device 10 is assumed to be in a state where it can read and write to various DBs or tables held by the server device 20.

[0158] In this case, some or all of the KPI tree DB261, business flow DB262, provisional registration table263, item master264, and data matching master265 may be held by the terminal device 10, or by another device (or cloud) that the terminal device 10 can access.

[0159] (Modification 2) In the embodiment described above, the server device 20 maintains the node names of the nodes included in the KPI tree, but it is not limited to this configuration, and the node names may actually be changed based on the name matching information registered in the name matching master 265.

[0160] In this case, for example, the name matching processing unit 213, in cooperation with the design support unit 212, will match (change) the name of the node to the destination node name when a node matching the conditions of the source node name and node type of the name matching information is set during the KPI tree creation process. It is preferable that the name matching processing unit 213 displays a screen to confirm the change to the destination node name and changes the node name after obtaining the user's consent.

[0161] This allows the server device 20 to change node names based on the name matching information during the user's KPI tree creation process. Therefore, the server device 20 can reduce fluctuations in node names and assist in the creation of KPI trees. Furthermore, the server device 20 can also change node names after confirmation with the user, thereby improving user convenience in determining node names.

[0162] Note that the timing of changing node names is not limited to when the KPI tree is created; it can be done at other times. For example, the node names of the KPI trees stored in the KPI tree DB261 can be automatically changed by a batch process, such as once a day. Alternatively, the node name change can be initiated manually, for example, by a data administrator.

[0163] The programs executed in each of the above-described embodiments are provided pre-installed in ROM, storage units, etc. Alternatively, the programs executed in each of the above-described embodiments may be provided as installable or executable files recorded on a computer-readable recording medium such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk).

[0164] Furthermore, the programs executed by each of the above-described embodiments may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Alternatively, the programs executed by each of the above-described embodiments may be provided or distributed via a network such as the Internet.

[0165] Although embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments and their variations can be implemented in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of symbols]

[0166] 1. Business support system 10 Terminal devices 20 Server Devices 111 Display Control Unit 112 Operation Reception Unit 211 GUI provision department 212 Design Support Department 213 Data matching processing unit 214 Display Control Unit 215 Operation Reception Section 216 Data Analysis Department 261 KPI Tree DB 262 Business Flow Database 263 Provisional Registration Table 264-item master 265 Data Matching Master [Prior art documents] [Patent Documents]

[0167] [Patent Document 1] Japanese Patent Publication No. 2014-235470

Claims

1. An acquisition means for acquiring the node name and node type of a node from tree data in which the relationship between nodes indicating management goals and nodes indicating measures to achieve those goals is set in a stepwise tree structure, An extraction means extracts from a first storage unit that stores a set of reference node names and node types that serve as the basis for matching reference node names, a set of reference node names similar to the set of node names and node types acquired by the acquisition means, A registration means that associates the node name and node type acquired by the acquisition means with the reference node name extracted by the extraction means and registers them in the second storage unit, Equipped with, The acquisition means is an information processing device that acquires the node name and the node type from among the nodes set in the tree data, from nodes that have a combination of node name and node type that is not registered in the first storage unit and the second storage unit.

2. The registration means registers in the first storage unit a set of node names and node types selected by the user from among the sets of node names and node types acquired by the acquisition means. The information processing apparatus according to claim 1.

3. The extraction means extracts a reference node name that is the same as the node type acquired by the acquisition means and has a string similar to the node name acquired by the acquisition means. The information processing apparatus according to claim 1.

4. The information processing apparatus according to claim 1 or 3, wherein the extraction means calculates the similarity between the characteristics of other nodes connected to the node corresponding to the node name acquired by the acquisition means and the characteristics of other nodes connected to the reference node corresponding to the reference node name, and extracts the reference node name for which the similarity is equal to or greater than a threshold.

5. The computer of the information processing device, An acquisition means for acquiring the node name and node type of a node from tree data in which the relationship between nodes indicating management goals and nodes indicating measures to achieve those goals is set in a stepwise tree structure, Extraction means extracts from a first storage unit that stores sets of reference node names and node types that serve as the basis for matching reference node names, sets of reference node names similar to the sets of node names and node types acquired by the acquisition means. A registration means that associates the node name and node type acquired by the acquisition means with the reference node name extracted by the extraction means and registers them in the second storage unit, and make it work The acquisition means is a program that acquires the node name and the node type from among the nodes set in the tree data, from nodes that have a combination of node name and node type that is not registered in the first storage unit and the second storage unit.

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