JP2004220178A - Knowledge management diagnostic system, its method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a policy for extracting a weak point of an organization and improving the organization, based on a concrete knowledge property to be owned by the organization. <P>SOLUTION: A knowledge management diagnostic system comprises a means for inputting organization defining information including a plurality of object businesses and business problems of the organization; a means for storing organization format information associated with assumed object businesses, assumed knowledge properties and assumed problems; a means for extracting partial information of the organization format information similar to the organization defining information; a means for prompting corrections of the partial information to information matched with the organization to be diagnosed; a means for storing the determination index information to determine whether or not the organization achieves levels by each knowledge utilized degree level; a means for prompting inputting the fact whether or not the determination index information matches with the organization; and a means for extracting knowledge property information and knowledge utilized degree level information corresponding to the determination index information. <P>COPYRIGHT: (C)2004,JPO&NCIPI

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a knowledge management diagnosis system, method, and program, and more particularly to a knowledge management diagnosis system, method, and program for diagnosing the utilization of knowledge assets to be possessed by an organization when diagnosing knowledge management.
[0002]
[Prior art]
As a method of diagnosing the knowledge management of an organization, a knowledge creation process (Knowledge Creation Support and a tool for grasping an organizational knowledge creation process based on a SECI model and a knowledge asset matrix that defines a knowledge creation process as a conversion process between tacit knowledge and formal knowledge). Organizational characteristics and awareness, such as the Knowledge Asset Management System (see, for example, Patent Document 1), the way of working and the characteristics of the organization that make up the organization, the interaction with communities and places, and the recognition gap for knowledge assets with management. Some are based on research (for example, see Non-Patent Document 1).
[0003]
[Patent Document 1]
US Patent Application Publication No. 2002/0062353
[0004]
[Non-patent document 1]
[Retrieved October 1, 2002], Internet <URL: http: // kdi. fusixerox. co. jp>
[0005]
[Problems to be solved by the invention]
However, the conventional knowledge management diagnosis system as described above only focuses on people, organizations, and processes, which are factors that promote knowledge management. It is difficult to connect to specific measures.
The Knowledge Audit described above performs a diagnosis using a knowledge asset matrix, but only classifies the properties of the knowledge asset into four types and diagnoses which type of knowledge asset the organization has in many cases. It is difficult to connect to specific measures to be taken.
[0006]
An object of the present invention is to provide a knowledge management diagnosis system, a method and a program for extracting weaknesses of an organization based on specific knowledge assets to be possessed by the organization and presenting measures for improving the organization. .
[0007]
[Means for Solving the Problems]
The knowledge management diagnosis system according to the present invention includes: a plurality of target tasks of an organization to be diagnosed; and definition information input means for inputting organization definition information including a task to be achieved by executing the target task; Corresponds to the assumed tasks of the expected tasks, assumed knowledge assets that are assumed to be owned by the organization in relation to the assumed tasks, and assumed tasks that are expected to be achieved by utilizing the knowledge assets. Based on the first storage means storing the stored organization template information, the target task and the assumed target task, and the input task definition information based on the task task and the assumed task. Presenting the first extraction means for extracting partial information of the organization template information from the organization template information, and the extracted partial information including the assumed task, the assumed knowledge asset, and the assumed task; First promoting means for prompting the user to correct the presented partial information into information suitable for the organization to be diagnosed; a knowledge utilization level corresponding to the assumed knowledge asset for each of the assumed knowledge assets; A second storage unit that stores determination index information for determining whether or not the tissue to be diagnosed has reached the level for each level, and the assumed knowledge asset from the corrected information. With reference to the modified knowledge asset information that has been modified, the determination index information corresponding to the modified knowledge asset information is extracted and presented, and whether the determination index information matches the organization to be diagnosed is determined. A second prompting means for prompting the user to input the information, and a second extracting means for extracting the knowledge asset information and the knowledge utilization level information corresponding to the judgment index information inputted as being suitable.
[0008]
Further, the knowledge management diagnosis method of the present invention inputs a plurality of target tasks of an organization to be diagnosed and organization definition information including a task to be achieved by executing the target task, and inputs a plurality of assumed targets. The business, the assumed knowledge asset assumed to be owned by the organization in relation to the assumed target business, and the assumed problem assumed to be achieved by utilizing the knowledge asset are associated with each other. Based on the target task and the assumed target task, and the task and the assumed task, partial information of the organization template information similar to the input organization definition information is stored in the organization template information. It is extracted from the template information, and the extracted partial information including the assumed task, the assumed knowledge asset, and the assumed task is presented, and the presented partial information is adapted to the organization to be diagnosed. The knowledge utilization level corresponding to the assumed knowledge asset for each of the assumed knowledge assets, and whether the organization to be diagnosed has reached that level for each of the knowledge utilization levels Is stored, and from the corrected information, referring to the corrected corrected knowledge asset information relating to the assumed knowledge asset, the determination index information corresponding to the corrected knowledge asset information is stored. Is extracted and presented, and it is urged to input whether or not the judgment index information matches the organization to be diagnosed, and the knowledge asset information and the knowledge utilization degree corresponding to the judgment index information input as being matched Extract level information.
[0009]
Further, the knowledge management diagnosis program according to the present invention provides a computer which executes a plurality of target tasks of an organization to be diagnosed and definition information for inputting organization definition information including task issues to be achieved by executing the target tasks. Input means, a plurality of assumed tasks, assumed knowledge assets assumed to be owned by the organization in relation to the assumed tasks, and assumed to be achieved by utilizing the knowledge assets A first storage unit that stores organization template information associated with the assumed task, the target task and the assumed task, and the input organization based on the task and the assumed task. First extraction means for extracting partial information of the organization template information similar to the definition information from the organization template information, and the extraction including the assumed task, the assumed knowledge asset, and the assumed task First promoting means for presenting the partial information provided and prompting the user to correct the presented partial information to information suitable for the organization to be diagnosed, and for each of the assumed knowledge assets, Second storage means for storing a knowledge utilization level, and determination index information for determining whether or not the organization to be diagnosed has reached the level for each knowledge utilization level; From the obtained information, referring to the corrected corrected knowledge asset information relating to the assumed knowledge asset, extracting and presenting the determination index information corresponding to the corrected knowledge asset information, and determining the determination index information by the diagnosis. A second promoting means for prompting the user to input whether or not the target organization is suitable; and a second extracting means for extracting the knowledge asset information and the knowledge utilization level information corresponding to the judgment index information input as the conformity. It is intended to function as detection means.
[0010]
According to the above configuration, a knowledge management measure procedure suitable for an organization or a task can be clarified, and a roadmap from a current state to a desired state can be clarified. Awareness of the organizational characteristics required to promote knowledge management is increased, and the weaknesses of one's own organization can be identified and measures taken to improve it. By presenting the forecast effects associated with the practice of the measures, specific achievement targets will be clarified. Therefore, it is possible to plan further improvement measures.
[0011]
In addition, it is possible to present specific measures for utilizing the knowledge assets handled by the organization, and to clarify concrete procedures for knowledge management that can be immediately practiced.
[0012]
In addition, customize the organization template information according to the target organization, diagnose the utilization of the important knowledge assets extracted by the organizational issues in the organization, and formulate knowledge management measures based on the results. Can be.
[0013]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, a knowledge management diagnosis system, method, and program according to an embodiment of the present invention will be described with reference to the accompanying drawings.
[0014]
FIG. 1 is a block diagram of the knowledge management diagnosis system according to the embodiment of the present invention.
[0015]
The organization definition means 1 defines a target business (sales, design, etc.), a business process, and an issue tree as a definition of an organization to be diagnosed. The defined target business, business process, and issue tree are output to the organization definition storage unit 12 as organization definition information.
[0016]
The knowledge map template storage means 8 stores a plurality of knowledge map templates, which are knowledge-based templates in which necessary knowledge assets are arranged for each organizational task, such as sales force enhancement, design quality improvement, and manufacturing quality improvement. It is stored as information.
[0017]
The knowledge asset editing means 2 inputs the organization definition information and the knowledge map template information, creates knowledge map information that matches the organization definition information, and outputs it to the knowledge map storage means 13. The knowledge asset editing means 2 inputs and processes information describing a correspondence relationship between a department of an organization which can be a diagnosis target described in the organization definition information and an organizational problem described in the knowledge map template information. Thus, knowledge asset list information necessary for an organizational task corresponding to the department to be diagnosed is extracted. The extracted specific knowledge asset information is used when formulating measures for actual knowledge management.
[0018]
The important knowledge asset extracting means 3 inputs the task tree information and the knowledge map information described in the organization definition information, extracts important knowledge asset information from the knowledge map information based on the task tree information, and 14 is stored.
[0019]
The knowledge utilization diagnostic index storage means 9 stores knowledge utilization level information, knowledge asset information corresponding to each level, and knowledge utilization diagnostic index information describing the activity to be performed. The knowledge utilization level indicates the degree of collection, accumulation, reuse, analysis utilization, and creation. The knowledge utilization diagnostic means 4 collates the important knowledge asset information stored in the important knowledge asset storage means 14 with the knowledge asset information stored in the knowledge utilization diagnostic index storage means 9.
[0020]
Further, the knowledge utilization diagnosing means 4 corresponds to the level information of the knowledge utilization level to which the knowledge asset information belongs for each important knowledge asset information extracted based on the knowledge utilization diagnostic index information and the knowledge asset information. The activity content information to be extracted is extracted and stored in the knowledge utilization diagnosis result storage unit 15. Diagnosis of the knowledge utilization level is performed with reference to the knowledge utilization level described in the knowledge utilization degree diagnostic index and an index describing the activity to be performed for each level.
[0021]
The organization characteristic diagnostic index storage means 10 associates information describing the factors of the organization characteristics with information indicating actions required by each member of the organization to achieve the factors as table information. I remember. The organization characteristic diagnosing means 5 presents information indicating the action to each member of the organization, and urges each member to input whether the action is performed. When each constituent inputs these actions, the tissue characteristic diagnosis unit 5 outputs the characteristic information of the tissue and stores the information in the tissue characteristic diagnosis result storage unit 16.
[0022]
The measure menu storage unit 11 classifies measure information for reaching each level of the knowledge utilization level for each level and stores it as table information. In addition, the measure menu storage unit 11 stores the table information stored in the organization characteristic diagnosis index storage unit 10 for each factor of the organization characteristic and the action required for each member of the organization to achieve the factor. Are stored in the form of table information with indices corresponding to the contents of the respective policy items associated with the contents of the respective items that are classified in association with each other.
[0023]
The measure design means 6 inputs the current knowledge utilization level information from the knowledge utilization diagnosis result information stored in the knowledge utilization diagnosis result storage means 15 and is further stored in the organization characteristic diagnosis result storage means 16. Based on the organization characteristic diagnosis result information, the current sufficiency and shortage factor information is input.
[0024]
Thereafter, the measure designing means 6 compares the utilization level information and the information on the cause of lack of satisfaction with the measure menu information registered in the measure menu storage means 11. As a result, the measure design means 6 outputs measure information for increasing the knowledge utilization level of the organization, and the measure template storage means 17 stores the measure information.
[0025]
Therefore, the manager of the organization can design knowledge management measures suited to the current level of knowledge utilization and organizational characteristics while recognizing the gap between the ideal form and the current state. In addition, the manager of the organization can clearly recognize the ideal use of knowledge assets in the organization, and can promote knowledge management in accordance with the measures designed here.
[0026]
The effect measurement knowledge storage unit 20 stores table information in which measures for each knowledge utilization level and items characterizing each knowledge utilization level for effect measurement are listed. The effect prediction means 7 compares the measure information stored in the measure template storage means 17 with the measure information stored in the effect measurement knowledge storage means 20. Then, the effect predicting means 7 urges each member to input whether or not each item is expected to be achieved for measuring the effect corresponding to each collated measure.
[0027]
The effect predicting unit 7 outputs the effect expected to be obtained to the predicted effect / actual effect storage unit 21 as predicted effect information based on the result input by each component. Further, the effect prediction unit 7 outputs effect measurement template information listing items serving as references for measuring whether or not the measure has been executed to the effect measurement template storage unit 18.
[0028]
The effect predicting means 7 presents a measure to the entire organization or a team within the organization, conducts a hearing or a questionnaire to the members or related parties of the organization or the team, and describes the problems and the degree of execution when implemented. Investigate the expected effects.
[0029]
The effect measuring unit 19 measures an effect actually obtained after a predetermined period has elapsed (for example, six months after the implementation of the measure) after the measure has been implemented. The effect measurement means 19 presents the contents of the effect measurement template information stored in the effect measurement template storage means 18 to the entire organization or a member or a related person of a team in the organization. Then, the effect measuring means 19 investigates the problems, the degree of execution, and the obtained effects after the measures are actually implemented for the entire organization or the team by interview or questionnaire, and uses the result of the investigation as actual effect information. Output to the predicted effect / actual effect storage means 21.
[0030]
The measure improvement means 22 refers to the knowledge utilization level by implementing the measure and the target knowledge utilization level based on the predicted effect information and the actual result information stored in the predicted result / actual effect storage means 21 to determine the effect. For a measure having a low measure, new measure plan information is extracted from the measure menu table information again with reference to the measure menu table information stored in the measure menu storage unit 11.
[0031]
After that, the measure improvement unit 22 outputs the effect that is expected to be obtained by the new effect plan by the effect prediction unit 7 again as effect prediction information. By repeating the measure improvement in this way, continuous effect measurement and measure improvement are performed, and the level of knowledge utilization can be improved. Furthermore, when deciding a measure to be implemented from the measure plan, the measure improvement means 22 may estimate the cost required for the measure and implement the measure in consideration of cost effectiveness.
[0032]
FIG. 2 is a diagram showing a flow of processing executed by the knowledge asset editing means 2 of FIG.
[0033]
The organization definition information is read from the organization definition storage unit 12 (S201), and the department information in the organization definition information is extracted (S202). The department information is information that describes what type of department exists in the organization to be diagnosed.
[0034]
The knowledge map template information corresponding to the section described in the section information is extracted from the knowledge map template storage unit 8 (S203). If the target business of the organization definition information is, for example, “sales”, the knowledge map template information of “enhance sales force” is further extracted from the knowledge map template information corresponding to the department extracted in step S203.
[0035]
Next, the extracted knowledge map template information is presented to a user such as an organization manager (S204), and urged to correct, for example, a department name, a term expressing a knowledge asset, etc. in order to match the diagnosis target organization ( S205). The user modifies the knowledge map information based on the prompt of the computer, which is the knowledge management diagnosis system of the present embodiment. Then, the knowledge map information optimized for the tissue to be diagnosed is output (S206).
[0036]
FIG. 3 is a diagram showing an example of the knowledge map template information stored in the knowledge map template storage unit 8 of FIG.
[0037]
FIG. 3 is an example of knowledge map template information, which is "knowledge map template information" whose task is to "enhance sales force." The knowledge map template storage means 8 also stores many other knowledge map template information having different tasks. The knowledge map template information includes the types 801 of knowledge assets required to achieve the task, information sources 802 where each knowledge asset is assumed to exist, related departments 803 sharing the knowledge assets for each knowledge asset, and It consists of item information of the utilization effect 804 corresponding to the knowledge asset. Here, the circles 関 連 in the related departments 803 sharing the knowledge assets indicate the related departments to share the types of the corresponding knowledge assets.
[0038]
FIG. 4 is a diagram showing an example of the knowledge map information stored in the knowledge map storage unit 13 of FIG.
[0039]
Based on the knowledge map template presented by the knowledge asset editing means 2, the user has edited the related department name 1303 and the type of knowledge asset 1301 according to the organization to be diagnosed. Further, the knowledge asset editing unit 2 refers to the business process described in the organization definition information, and performs a process indicated by an arrow on the flow 1305 of the knowledge information in the knowledge map.
[0040]
FIG. 5 is a diagram showing an example of input and output by the important knowledge asset extracting means 3 of FIG.
[0041]
The important knowledge asset extracting means 3 uses, for example, a QFD tool (Quality Function Deployment: Quality Function Deployment. Reference: Ohto et al., QFD Guidebook -Principles of Quality Function Deployment and Its Application-, Japan Standards Association). A binary table of the organizational task information 1201 stored in the organization definition storage unit 12 and the knowledge asset type 1301 stored in the knowledge map storage unit 13 is created. Further, the important knowledge asset extracting means 3 urges the manager of the organization or the like to input the organization task importance level 301.
[0042]
The important knowledge asset extracting means 3 urges a manager of the organization to assign a high value to the organizational task importance 301 for an organizational task considered to be important for the organization. After that, the important knowledge asset extracting means 3 urges a user such as a manager of the organization or a member of the organization to input the degree of association between the organization problem and the knowledge asset. That is, the important knowledge asset extracting means 3 prompts the manager of the organization to input a symbol in which each item of the binary table is given a predetermined weight. In the example of FIG. 4, the symbols are described with symbols of a black dot, a white dot, and a white triangle, and weights of 9, 6, and 3 are given thereto. The greater the degree of association, the greater the weight. When the manager finishes writing the symbols in the binary table, the important knowledge asset extracting means 3 refers to the organizational task importance and weight and displays the knowledge asset importance 302 for each knowledge asset. As the degree of each of the organizational task importance and the weight increases, the knowledge asset importance increases. The important knowledge asset extracting means 3 extracts important knowledge assets by extracting knowledge assets having a predetermined value or more from the knowledge asset importance. Further, it may be set so as to extract some higher-order knowledge asset importance.
[0043]
FIG. 6 is a diagram showing a flow of processing executed by the knowledge utilization degree diagnosing means 4 of FIG.
[0044]
The knowledge asset information is extracted from the important knowledge asset storage means 14 (S401). Next, at least one verb expression is extracted from the knowledge utilization diagnostic index storage means 9 at each knowledge utilization level. Index information is generated from the combination of the important knowledge asset extracted by the important knowledge asset extraction means 3 and the verb expression indicating the knowledge utilization level (S403). This is repeated for all important knowledge asset information (S404).
[0045]
If all important knowledge asset information is determined in step S403, the generated index information is edited into a question form, and questionnaire information is generated (S405). This questionnaire information is presented to members of the organization, and a questionnaire and an interview are performed (S406). That is, the computer, which is the knowledge management diagnosis system of the present embodiment, presents a question message to each member and prompts the user to input an answer corresponding to the question message. The knowledge utilization level for each knowledge asset is determined based on the questionnaire (S407), and knowledge utilization diagnosis result information is obtained. The knowledge utilization diagnosis result information is information indicating a knowledge utilization level for each important knowledge asset.
[0046]
Unlike the processing in FIG. 6, steps S402 to S404 may be executed in advance, and index information may be given for each knowledge utilization level. In this case, the knowledge utilization degree diagnosing unit 4 executes step S401, step S405, step S406, and step S407 in this order.
[0047]
FIG. 7 is a diagram showing an example of the knowledge utilization diagnostic index information stored in the knowledge utilization diagnostic index storage means 9 of FIG.
[0048]
The knowledge utilization diagnostic index information is information describing a diagnostic index for each task corresponding to the knowledge map template information. The knowledge utilization level 901 is divided into four levels, namely, an accumulation level, a sharing level, a definition level, and a creation level. It is composed of an index 904 defined and combined with a target knowledge asset 903 and a verb expression 902 indicating the level of knowledge utilization.
[0049]
Here, the index 904 may be generated by the knowledge utilization degree diagnosing unit 4 as shown in FIG.
[0050]
FIG. 8 is a diagram showing an example of the knowledge utilization diagnosis result information stored in the knowledge utilization diagnosis result storage means 15 of FIG.
[0051]
The knowledge utilization diagnosis result information includes the knowledge utilization level 1502 determined for each knowledge asset 1501. The example of FIG. 8 indicates that the customer's needs, customer dissatisfaction, and noticed information are at the accumulation level, and the product knowledge and market trends of other companies' products are at the shared level.
[0052]
Referring to the knowledge utilization diagnosis result information shown in FIG. 8, the means (6, 7, 19, and 22) following the measure designing means 6 formulate a concrete knowledge management measure. At this time, it is necessary to adopt measures that match not only the level of knowledge utilization but also the organizational structure that promotes knowledge utilization, human capabilities, information systems, and organizational characteristics of the environment such as offices. Then, next, the tissue characteristic is diagnosed by the tissue characteristic diagnosis means 5.
[0053]
FIG. 9 is a diagram showing an example of the tissue characteristic diagnostic index information stored in the tissue characteristic diagnostic index storage means 10 of FIG.
[0054]
The tissue characteristic diagnostic index information is expressed by a matrix of trust, empathy, curiosity as a characteristic 1001 as an enabler of the behavior, and a person, method, and environment as a factor 1002 of the tissue characteristic. For each factor, a characteristic diagnostic index 1003 for diagnosing the characteristic is described. The organization characteristic diagnosis means 5 transforms this index into a question form, presents it as a question item to the organization members as a questionnaire or an interview, and urges the user to respond to the questionnaire or the like. The tissue characteristic diagnosis means 5 makes a diagnosis based on the answers to the questionnaire and the like, and obtains the tissue characteristic diagnosis result information.
[0055]
FIG. 10 is a diagram showing an example of the tissue characteristic diagnosis result information stored in the tissue characteristic diagnosis result storage means 16 of FIG.
[0056]
As shown in FIG. 10, the tissue characteristic diagnosis result information is, for each factor (person, method, environment), for each characteristic (trust, empathy, curiosity), for each index performed by the tissue characteristic diagnosis unit 5. It includes the results of determining whether or not the index corresponds to the target organization for each index based on the contents of a questionnaire or the like.
[0057]
For example, for each index, if it is answered that 70% or more of the members of the organization correspond, then it is acceptable. If it is answered that 90% or more of the members correspond, (+) as shown in 1604 indicates the index. When less than 70% of the members respond, it is indicated by (-) as an index as shown in 1603. If each of the elements A to I (1605) of the matrix of the three characteristics and the three factors is minus half or more, it is determined that the organization characteristic should be strengthened.
[0058]
FIG. 11 is a diagram showing an example of a flow of a process executed by the measure designing means 6 of FIG.
[0059]
The knowledge utilization diagnosis result information stored in the knowledge utilization diagnosis result storage means 15 is read (S601). Here, for each level of the knowledge utilization level, a measure that is one step higher than the current knowledge utilization level, for example, is extracted from the measure menu list (S603, S605, S607, S609). That is, if the current knowledge utilization level is an initial level which is a level before the accumulation level, the accumulation level, if the current knowledge utilization level is the accumulation level, the sharing level, and if the current knowledge utilization level is the sharing level, the definition level. If the current knowledge utilization level is the definition level, the measures at the creation level are respectively extracted from the process of the measure menu list and set as the measure templates (S602 to S609). Next, the tissue characteristic diagnosis result information stored in the tissue characteristic diagnosis result storage means 16 is read (S610), and the elements to be strengthened into the tissue characteristic diagnosis result shown in FIG. If there is a symbol (S 611) (S 611), a measure corresponding to the organization characteristic to be strengthened is added to the measure template from the organization culture and environment of the measure menu list to further enhance the organization characteristic (S 612). Then, it is presented to a user such as an administrator of the organization as a measure template (S613). On the other hand, when there is no element to be strengthened in the tissue characteristic diagnosis result shown in FIG. 10 (the one to which (−) is added among 1605) (S611), there is no need to present a measure template, and thus the measure is taken. The processing of the design means 6 ends.
[0060]
The organization to be diagnosed designs a measure that can be implemented specifically for the organization with reference to the presented measure template. For example, a specific implementation means of the knowledge sharing database is designed according to the situation of the organization.
[0061]
FIG. 12 is a diagram showing an example of the measure menu list information stored in the measure menu storage means 11 of FIG.
[0062]
This example is an example of a measure menu list with the task of “enhancing sales force”. The measure menu list information indicates measures to reach each level of the knowledge utilization level 1101 by a process 1102, an organizational culture 1103, and an environment 1104. It is described in the classification of. The measure design means 6 selects a measure menu according to the knowledge utilization diagnosis result information. The symbols (A to I) given to the respective measures of the organization climate 1103 and the environment 1104 are respectively associated with the elements (A to I) to be strengthened in the tissue characteristic diagnosis result information of FIG.
[0063]
FIG. 13 is a diagram showing an example of the measure template information stored in the measure template storage means 17 of FIG. 1 and the effect measurement template information stored in the effect measurement template storage means 18 of FIG.
[0064]
Each item of the effect measurement template 1801 is set corresponding to the measure template 1701, and a phenomenon that appears as an effect when each item of the measure template 1701 is achieved is described corresponding to each item of the measure template 1701. Template.
[0065]
The example in FIG. 13 is an organization in which the knowledge utilization level is at the sharing level, and is an example in which the elements A and G are weak as shown in FIG. In the measure template, a level improvement measure 1702 for raising the sharing level to the definition level and a reinforcement measure 1703 for strengthening the elements A and G are presented.
[0066]
FIG. 14 is a diagram showing another example of the flow of the process executed by the measure designing means 6 of FIG. 1, different from FIG. 12.
[0067]
In this method, by comparing the organization characteristics required for each predefined classification of knowledge assets with the results of the organization characteristic diagnosis (S652), the strength of the organization characteristics can be identified, that is, the organization to be strengthened for each organization characteristic. It is determined whether or not it is a characteristic (S655). On the other hand, important knowledge assets are extracted (S651), and the extraction result is classified according to the knowledge asset classification 658 (S653). Further, based on the utilization diagnosis result (S654), a knowledge asset class having a low knowledge utilization level is extracted from the knowledge asset classes extracted in step S653 (S656). By referring to both the utilization diagnosis result and the strength of the organizational characteristics, extract from the policy menu measures to improve the level of knowledge utilization for knowledge assets determined to have low knowledge utilization levels and weak organizational characteristics. It is presented to a user such as a manager of the organization (S657). The organizational characteristics 658 required for each knowledge asset classification are determined by using, for example, AHP (hierarchical analysis), using the characteristic 1001 of the organizational characteristic index in FIG. It can be obtained by a method such as calculating a factor 1002 which is an element for increasing the knowledge utilization level.
[0068]
FIG. 15 is a diagram showing an example of the effect measurement knowledge information stored in the effect measurement knowledge storage means 20 of FIG.
[0069]
Each effect measurement knowledge information describes items to be measured for each level of the measure menu. In the example of FIG. 15, an item of the effect measurement 2003 for measuring whether or not the measure 2002 is effective for the measure 2002 for the measure 2002 for the process is described. The effect measuring means 19 presents the effect measurement 2003 corresponding to the knowledge utilization level to the user, and prompts the user to input whether or not the effect is actually obtained. This input result is input to the predicted effect / actual effect storage means 21. From the input result, it is determined whether or not the measure designed by the measure design means 6 is effective. Further, the effect predicted by the effect prediction means 7 is also stored in the predicted effect / actual effect storage means 21.
[0070]
The measure improvement unit 22 compares the predicted effect and the actual effect in the predicted effect / actual effect storage unit 21 and improves the measure for which the effect could not be obtained. The measure improvement unit 22 refers to the measure template when improving the measure.
[0071]
As described above, according to the above-described embodiment, knowledge assets required in the target task are arranged and presented from the viewpoint of utilization of knowledge based on the target task and organizational issues, so that the ideal form of knowledge asset utilization in the organization can be achieved. Be clear. Furthermore, the gap between the ideal form and the current state can be recognized by the knowledge utilization diagnosis, and measures for increasing the knowledge utilization level in stages from the current state can be presented.
[0072]
The procedures for knowledge management measures suited to the organization and issues will be clarified, and the roadmap from the current situation to the ideal situation will be clarified. Further, the diagnosis of the organizational characteristics increases the awareness of the organizational characteristics necessary for promoting knowledge management, so that the weaknesses of the organization can be known and measures for improving the organization can be strengthened. Furthermore, presenting the predicted effects of implementing the measures will clarify the concrete achievement targets, and measuring the actual effects of the results of actually implementing the measures and taking the difference from the predicted effects will further improve the results. It is possible to formulate measures.
[0073]
As described above, according to the embodiment of the present invention, unlike the conventional knowledge management diagnosis method of diagnosing the promotion factor of knowledge management, it is possible to present a specific policy for utilizing the knowledge assets handled by the organization, Clarify concrete procedures for knowledge management that can be practiced immediately.
[0074]
Note that the present invention is not limited to the above-described embodiment, and can be variously modified in an implementation stage without departing from the gist of the invention. Furthermore, the above embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, even if some components are deleted from all the components shown in the embodiment, at least one of the problems described in the column of the problem to be solved by the invention can be solved, and the problem described in the column of the effect of the invention can be solved. If at least one of the effects described above can be obtained, a configuration from which this configuration requirement is deleted can be extracted as an invention.
[0075]
【The invention's effect】
According to the knowledge management diagnosis system, method, and program of the present invention, unlike the conventional knowledge management diagnosis method for diagnosing the promotion factor of knowledge management, presenting a specific knowledge asset utilization measure handled by an organization. Can clarify concrete procedures for knowledge management that can be implemented immediately.
[Brief description of the drawings]
FIG. 1 is a block diagram of a knowledge management diagnosis system according to an embodiment of the present invention.
FIG. 2 is a view showing the flow of processing executed by the knowledge asset editing means of FIG. 1;
FIG. 3 is a diagram showing an example of knowledge map template information stored in a knowledge map template storage unit of FIG. 1;
FIG. 4 is a view showing an example of knowledge map information stored in the knowledge map storage means of FIG. 1;
FIG. 5 is a view showing an example of input and output by the important knowledge asset extracting means of FIG. 1;
FIG. 6 is a diagram showing a flow of processing executed by the knowledge utilization degree diagnosing means of FIG. 1;
FIG. 7 is a diagram showing an example of knowledge utilization diagnostic index information stored in the knowledge utilization diagnostic index storage means of FIG. 1;
FIG. 8 is a diagram showing an example of knowledge utilization diagnosis result information stored in the knowledge utilization diagnosis result storage means of FIG. 1;
FIG. 9 is a view showing an example of tissue characteristic diagnostic index information stored in the tissue characteristic diagnostic index storage means of FIG. 1;
FIG. 10 is a view showing an example of tissue characteristic diagnosis result information stored in the tissue characteristic diagnosis result storage means of FIG. 1;
FIG. 11 is a diagram showing an example of the flow of processing executed by the measure designing means of FIG. 1;
FIG. 12 is a diagram showing an example of list information stored in a measure menu storage means storage means of FIG. 1;
13 is a diagram showing an example of the measure template information stored in the measure template storage means of FIG. 1 and the effect measurement template information stored in the effect measurement template storage means of FIG. 1;
FIG. 14 is a diagram showing another example of the flow of the process executed by the measure designing means of FIG. 1 different from FIG. 12;
FIG. 15 is a view showing an example of effect measurement knowledge information stored in the effect measurement knowledge storage means of FIG. 1;
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Organization definition means, 2 ... Knowledge asset editing means, 3 ... Important knowledge asset extraction means, 4 ... Knowledge utilization diagnosis means, 5 ... Organization characteristic diagnosis means, 6 ... Policy design means, 7 ... Effect prediction means, 8 ... Knowledge map template storage means, 9: knowledge utilization diagnosis index storage means, 10: organization characteristic diagnosis index storage means, 11: policy menu storage means, 12: organization definition storage means, 13: knowledge map storage means, 14: important Knowledge asset storage means, 15: Knowledge utilization diagnosis result storage means, 16: Organization characteristic diagnosis result storage means, 17: Measure template storage means, 18: Effect measurement template storage means, 19: Effect measurement means, 20: Effect measurement knowledge Storage means, 21: Effective effect storage means, 22: Measure improvement means, 301: Importance of organizational issues, 302: Importance of knowledge assets, 801, 1301: Type of knowledge assets, 802 1302 ... information source, 803, 1303 ... related departments, 804, 1304 ... utilization effect, 901 ... knowledge utilization level, 902 ... verb expression, 903 ... knowledge asset, 904 ... index, 1001, 1601 ... characteristics, 1002, 1602 ... Factors, 1003, 1605: characteristic diagnostic index, 1101, 2001: knowledge utilization level, 1102, 2002: process, 1103: organization climate, 1104: environment, 1201: organization task information, 1305: flow of knowledge information, 1501: knowledge Asset, 1502: Knowledge utilization level, 1701: Measure template, 1702: Level improvement measure, 1703: Reinforcement measure, 1801: Effect measurement template, 2003: Effect measurement

Claims (7)

Definition information input means for inputting a plurality of target tasks of the organization to be diagnosed, and organization definition information including a task to be achieved by executing the target task;
Corresponds to a plurality of assumed tasks, assumed knowledge assets that are assumed to be owned by the organization in relation to the assumed tasks, and assumed tasks that are expected to be achieved by utilizing the knowledge assets First storage means for storing attached tissue template information;
Extracting, from the organization template information, partial information of organization template information similar to the input organization definition information based on the target task and the assumed target task, and the task task and the assumed task. Extraction means;
Presenting the extracted partial information including the assumed target task, the assumed knowledge asset, and the assumed task, and prompting the user to correct the presented partial information to information suitable for the organization to be diagnosed. First promoting means;
For each of the assumed knowledge assets, a knowledge utilization level corresponding to the assumed knowledge asset, and determination index information for determining whether or not the organization to be diagnosed has reached the level for each of the knowledge utilization levels Second storage means for storing
From the corrected information, referring to the corrected corrected knowledge asset information regarding the assumed knowledge asset, extracting and presenting the determination index information corresponding to the corrected knowledge asset information, the determination index information is Second promoting means for prompting the user to input whether or not the tissue to be diagnosed matches;
A knowledge management diagnosis system comprising a second extraction unit for extracting knowledge asset information and knowledge utilization level information corresponding to the judgment index information input as the match. Corrected assumed task in which the assumed task included in the corrected information has been corrected, and correction information input means for inputting information including a corrected knowledge asset included in the corrected information,
Third promoting means for prompting the user to input the importance of the corrected assumed task;
Fourth promoting means for prompting the user to input a degree of association indicating the degree of association between the modified assumed task and the modified knowledge asset;
2. The knowledge management diagnosis system according to claim 1, further comprising calculating means for calculating the importance of the knowledge asset based on the importance and the relevance. Third storage means for storing guideline information in which a guideline for reaching each level of the knowledge utilization level is described;
With reference to the extracted knowledge utilization level information, from the guideline information, for each knowledge utilization level included in the referenced knowledge utilization level information, guideline information corresponding to a higher level than that level The knowledge management diagnosis system according to claim 1, further comprising a third extraction unit configured to extract the information. Fourth storage means for storing a table in which a plurality of characteristic items characterizing the organization and an action standard for satisfying the characteristic items are stored;
A fifth promoting unit that presents the behavior standard and prompts the user to input execution information as to whether or not an item indicated in the behavior standard is being executed for each behavior standard;
4. The apparatus according to claim 1, further comprising: a determination unit configured to determine whether or not each of the plurality of characteristic items is recognized as a characteristic of the tissue to be diagnosed, based on the execution information. 5. Knowledge management diagnosis system. Fifth storage means for storing the extracted guideline information,
Sixth storage means for storing a guideline assumed effect assumed to be obtained when an action corresponding to the guideline included in the stored guideline information is performed,
After performing an action corresponding to the guideline, sixth promotion means for prompting to input whether or not the guideline expected effect has been obtained;
Changing means for changing the guideline for which the guideline expected effect was not obtained to a guideline different from the guideline and stored in the fifth storage means;
After performing the action corresponding to the changed guideline, the sixth prompting unit gives an instruction to the sixth prompting unit so as to prompt the user to input whether or not the expected effect of the pointer has been obtained. The knowledge management diagnosis system according to claim 3 or 4, further comprising means. Enter a plurality of target tasks of the organization to be diagnosed, and organization definition information including task issues to be achieved by executing the target tasks,
Corresponds to multiple assumed tasks, assumed knowledge assets assumed to be owned by the organization in relation to the assumed tasks, and assumed tasks expected to be achieved by utilizing the knowledge assets Memorize the attached organization template information,
The target task and the assumed target task, and, based on the task and the assumed task, extracting partial information of the organization template information similar to the input organization definition information from the organization template information,
Presenting the extracted partial information including the assumed task, the assumed knowledge asset, and the assumed task, and prompting the user to correct the presented partial information to information suitable for the organization to be diagnosed. ,
For each of the assumed knowledge assets, a knowledge utilization level corresponding to the assumed knowledge asset, and determination index information for determining whether or not the organization to be diagnosed has reached that level for each of the knowledge utilization levels Remember
From the corrected information, referring to the corrected corrected knowledge asset information regarding the assumed knowledge asset, extracting and presenting the determination index information corresponding to the corrected knowledge asset information, the determination index information is Prompts the user to enter whether or not it is compatible with the tissue being diagnosed,
A knowledge management diagnosis method for extracting knowledge asset information and knowledge utilization level information corresponding to the judgment index information input as being matched. Computer
Definition information input means for inputting a plurality of target tasks of the organization to be diagnosed, and organization definition information including a task to be achieved by executing the target task;
Corresponds to a plurality of assumed tasks, assumed knowledge assets that are assumed to be owned by the organization in relation to the assumed tasks, and assumed tasks that are expected to be achieved by utilizing the knowledge assets First storage means for storing attached tissue template information;
Extracting, from the organization template information, partial information of organization template information similar to the input organization definition information based on the target task and the assumed target task, and the task task and the assumed task. Extraction means;
Presenting the extracted partial information including the assumed target task, the assumed knowledge asset, and the assumed task, and prompting the user to correct the presented partial information to information suitable for the organization to be diagnosed. First promoting means;
For each of the assumed knowledge assets, a knowledge utilization level corresponding to the assumed knowledge asset, and determination index information for determining whether or not the organization to be diagnosed has reached the level for each of the knowledge utilization levels Second storage means for storing
From the corrected information, referring to the corrected corrected knowledge asset information regarding the assumed knowledge asset, extracting and presenting the determination index information corresponding to the corrected knowledge asset information, the determination index information is Second promoting means for prompting the user to input whether or not the tissue to be diagnosed matches;
A knowledge management diagnosis program for functioning as second extraction means for extracting knowledge asset information and knowledge utilization level information corresponding to the judgment index information input as being matched.

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