Integrating Knowledge Management and Human Resources via Skills Management

Integrating Knowledge Management and Human Resources via Skills Management

Authors:
Mathias Uslar
OFFIS, Germany
mathias.uslar@informatik.uni-oldenburg.de
Prof Norbert Gronau
University of Potsdam, Germany
ngronau@rz.uni-potsdam.de

14 February 2007
Reproduced with the authorization of the authors, originally published as: Integrating Knowledge Management and Human Resources via Skill Management. In: Tochtermann, Klaus and Hermann Maurer (Editors): Journal of Universal Computer Science (J.UCS): Proceedings of the I-Know ’04, pp. 135–142. Springer, Heidelberg, 2004.

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Abstract:
Knowledge is more and more becoming a key factor within companies. Nearly 40 percent of all employees today are so called "knowledge workers". Distribution and acquisition of knowledge within companies is supported by skills management systems. Although not all aspects and potentials of this instrument are yet utilized by current skills management systems, they have spread within business organizations. This paper summarizes the requirements, scopes and problems for skills management systems within the company.

1 Main fields of application

Skills management as a knowledge management instrument deals with the knowledge of the company's employees at different levels [Bohme 2001]. Mainly addressed issues of skills management are qualifications and skills that are important for production, knowledge work and , in general, the surplus for the company. To track those skills, the company uses business information systems to keep profiles with the latest rated skills in hand. Because skills management is not an entirely IT-based approach, it is based on cultural and organizational changes within the company. The main areas of its application are expert finding, personnel recruitment, personnel development and project management.

Expert finding is the functionality which is easiest to implement by the use of a skills management system. Expert finding makes it possible to find and search for employees with certain present and needed future skills (e.g. for projects).

Recruiting personnel is strongly supported by skills management systems. The human resources department can search for certain skills documented within the database and compare the skills of an employee with the needed rating of certain job opportunities . Those inquiries create the possibility to start internal promotion [Kreitmeier et al. 2000]. The company is able to save costs which otherwise would occur by placing adverts for job opportunities in journals and magazines, sighting the application of all candidates and losing working time because of application audits.

The personnel development department can also benefit from skills management [Blandin 2003]. The system documents the qualifications and skills of each employee in a transparent manner. Gaps and needs for personal development of employees become more and more visible, the lack of important skills will be made visible. Within a project-oriented organization, employees can be scheduled like any other resources for projects [Deiters et al. 1999]. Comparing job description and skill document of an employee creates the possibility to find the most appropriate employee for a certain vacancy. Anyway, the fact that a successful team is much more than just adding the best skills should not be omitted (e.g. human factor in team-building).

2 Costs and Savings

When doing knowledge management oriented projects, there is often a problem concerning the return on investment. The money saved by the skills management system cannot be directly quantified. The developing and implementing costs do not have direct return on investment. Newer trends dealing with the mapping of human capital might have an effect on skills management. There are certain questions which have to be asked [Ackerman et al. 1999]:

• What overall costs does the skills management system cause?
• Which potential costs can be saved using the system?
• Which costs occur when skills management is not implemented by the company?

The capital outlays for the system are determined particularly by the system realized at the beginning of the introduction of the skills management program:

• Is the system introduced just for a certain range, for example for the project management?
• How many HR specialists have to be trained?
• What is estimated in terms of work days for the project?

Further, the type of the initial data acquisition method is a significant cost factor. The development of targets/actual goals costs time and is important for the success from the very beginning. Running costs play only a small role compared with the initial capital outlays [Kreitmeier et al. 2000]. The resulting costs of updating the data profiles and current server costs and HR expenditure are the biggest. Those costs are quantifiable, however, savings are not. A skills management system creates free monetary values by the optimization of the personnel employment [Faix et al. 1991].

3 Improvements by skills management

Simplifying the search for experts, problems can be discussed (and solved) faster with the most appropriate employee. The system supports the project manager in preventing wasting valuable amounts of work time from experts doing too simple tasks and to assign appropriate tasks to them. Improvement potential lies in adjusting the staff to the requirements of the job market: the enterprize recognizes positions by the collection of the abilities of the employees, which are no longer vital to the company and can be omitted. [Faix et al. 1991]. Training of the employees can be directed to correct and needed knowledge topics; expensive and redundant training courses do not occur. The last large potential lies in saving costs for employee procurement. Enormous amounts are saved through aligning current employees by internal recruitment and advertising/training programs [Kreitmeier et al. 2000]. Internal recruitment and aligning is favorable for the working climate and costs are only half as high as costs using external personnel recruitment.

There may be negative effects if skills management is not realized. Fluctuation costs by personnel changes are lowered by internal promotion and recruitment, this minimizes probability of core knowledge carriers to be pulled out of business by providing them insufficient career possibilities. The damage by insufficiently qualified and skilled employees is difficult to be quantified, just like costs, which result from needed double qualifications, if employees regard knowledge as their private property and do not share it in the overall organisation.

4 Problem areas and scopes of skills management

Structuring the skill catalogue: It is a crucial decision how the data is indeed tracked. If data is tracked using continuous text, we will be able to support individuals properly. They can describe their project experience and personal record in detail. The data tracked has to be structured and categorized in clear categories and/or afterwards categorized in further smaller multi-hierarchical categories. Apart from content advantages by structuring, there are also technical advantages, since the data can be fed more easily into the database [Huneke and Zimmermann 2000].

Equal chances for each employee using the system: Normally, there is no problem with exaggerated self-portrayal when tracking competencies and skills in a strongly structured database. Which skill is tracked and which isn't is very important to the employee. It is, in fact, essential. If some skills of an employee cannot be tracked using the system, the employee might not show up in the expert directory [Deiters et al. 1999]. No other user can ask for his expertise and the HR department and project managers cannot find him by using the system.

Different types of skills: The skills catalogue first of all only clarifies which skills are tracked, but not their type. One has to distinguish between hard and soft skills [Ackerman et al. 1999]. The so called hard skills are proven skills and competencies, workings areas, educational ways and skills, certified degrees et al. Soft skills include more or less capability of teamwork, leadership qualities or toughness. This information is considered sensible and diffuse.

Tracking and judging the competencies: The problem of tracking the competencies is not easy to solve. Yet there are few known solutions to solve this problem [Gronau 2003]. An appropriate way is to use software engineering methods for system analysis to create a repository of known skills and to estimate needed skills for the future processes. The employee maintains and tracks his data on his own. If an employee rates himself too good, he gets more questions from other users, if he cannot supply his expertise, his reputation within the company will suffer. The tracked skills therefore are more trustworthy [Dingsoyr and Royrvik 2000].

Data protection and security: The skills management system tracks personal data, which is often subject to a special protection in terms of laws. Special rights of codetermination are entitled to workers unions due to this fact. This problem area is of crucial importance during the introduction and usage of skills management.

Up-to-datedness of the data tracked: The lifespan of knowledge in enterprizes is small, the data topicality over projects and advanced training of the employees even smaller. Data quality must be correct for the acceptance of the system. The data must be, again and again, maintained and updated, which naturally causes costs in the form of work time [Deiters et al. 1999]. Skills management systems are only useful if the data, on which expert information is based, is not several years old and the experts meanwhile possess only historical knowledge.

Acceptance of the system: If the problem of acceptance is not solved, then skills management will fail. Both the management, the personnel department and the staff can bring the project to failure, if the respective group does not feel represented enough [Gebert and Kutsch 2003]. Teams may not only be arranged with the help of the system, an employee discussion may not be replaced, since frequently the desired developments of the employee are not seized and tracked by the skills management system [Deiters et al. 1999].

5 Requirements for skills management systems

5.1 Requirements regarding content

Meaningful structuring of the data: The skills management system has to save data in a structured way, so it can be entered by the employees more easily [Ackerman et al. 1999].

Meaningful skills catalogue: The skills catalogue must be carefully provided. In addition, the requirement catalogue should be derived from modeled enterprize processes and not from job descriptions provided by the HR department, since information from daily business could be omitted.

Semantic match of skills catalogues: The job requirements should offer the same categories as the skill profiles of the employees.

Granularity of the skill catalogue: The catalogue should be fine granular, in order to offer equal chances during the collection of the abilities.

New competencies for the catalogue: The employee should be allowed to submit new competency terms and categories for the overall skill catalogue.

Collection of sensitive competencies: Personal and social competencies should not be tracked because of their sensitive character. This is critical because they are not objective or representable.

Necessity for a rating: In order to use a skills management system purposefully, a rating of the competencies should be utilized.

Data acquisition and evaluation by self-assessment: The data of the system should be determined by self-assessment. It saves time in the HR department and can provide an introduction to self-development for most employees.

5.2 Requirements regarding technical factors

Flexible update of the data: The employee should be able to update the data at any time whenever he wants and needs to. There should be a possibility of storing and further processing of incomplete filled profiles later.

Continuous text fields: Specialized knowledge should be entered using continuous text fields and thus can be searched for keywords.

Ratings: should at least cover 5 levels using a scale. If it is an ordinal scale, an explanation with examples for the user to decide what is expected to fill in should be provided . If the system does not use an ordinal scale, there should be a possibility of indicating intervals for abilities if the user is not sure about his rating [Deiters et al. 1999].

Topicality of the data: The topicality of the data is of crucial importance. Each profile and/or each skill document should contain a time stamp to examine when the data was updated. If data should have become outdated, an agent could not simply delete the data, but also send a message to the document owner that his data had become outdated and he may update them before deletion [Gebert and Kutsch 2003], [Deiters et al. 1999].

Complex search functions: The system should provide a complex search for skills of the users and offer a complex search logic. Furthermore, extensive functions are necessary for the target/actual comparison and should provide general overviews of the data contained by the system, which should correspond to the most frequently formulated searches.

Simple operability and configuration: The system is not only used by personnel specialists or IT developers, therefore, it should offer a simple and fast understandable user interface, which can be used without larger training for each employee. This applies both to the data input and to the search.

Integration into the system environment: The skills management system should be integrated as good and neat as possible into the IT environment of the enterprize and provide connections to at least the intranet, the personnel system, the e-Learning environment [Blandin 2003], training course planning, the project management system and the knowledge management system.

5.3 Requirements regarding organizational change

Participation: During the system development and conception, all groups should take part to introduce their needs and requirements. This leads to an increased acceptance and support for the project.

System introduction: The system should be developed with a meaningful procedural model and be introduced using such a model. A test operation should take place before starting, using a critical mass. This later secures the initial data quality at the start of the skills management system.

Motivation for the care of the data: The data quality is essential to the system. Therefore, incentives must be created for distributing knowledge. This should be easier than with other knowledge management measures, which often want to externalize knowledge, since the expenditure of time is smaller when just trying to find out which knowledge is indeed present in the organization. It must be examined how often profiles are updated or looked for and one must provide a form for feedback if meaningful assistance was provided by one of the employees previously found utilizing the system.

Frequency of the actualization of skills documents: The frequency of the actualization should not be set too high, so the employee feels not overly burdened, additional work time should be defined or officially declared for knowledge management measures.

Capital outlays: The management's acceptance of the fact that immediate quantifiable yields for initial investments are not provided must be created. Skills management must be understood as a long-term enterprize-strategic measure.

6 Conclusion and perspectives

To introduce a skills management system effectively, it is necessary to have a meaningful model for the system introduction. The enterprize must get accustomed slowly to knowledge management and the pertinent techniques. Not much time can be invested in the daily business [Gebert and Kutsch 2003]. A recommendation is to implement the aspects of skills management, which show most and immediate advantages in the operational business with priority i.e. to introduce the expert search with evaluation possibility [Ackerman et al. 1999].

The skill catalogue for the enterprize should be constructed with the help of a process analysis, as it is possible to create the foundation for further knowledge management measures [Gronau 2003]. The system should be as expandable as possible, favorable and well administrable.

The aspect of costs for the technical measures such as hardware and licenses should always be considered. Established standard software has to be preferred, expandability and further extensibility of the skill management approach should always be kept in mind. Testing with a critical mass should precede the start of the system in the enterprize, those users will finally supply the productive data for the initial going-public of the system. Official work time for taking care of the data should be granted to employees, so they do not associate the introduction to knowledge management with a lot of work. In case of an successful introduction, the employees should recognize the advantages of using further knowledge management measures in daily business and later further knowledge management measures [Kreitmeier et al. 2000]. Regular examinations of the skills catalogue, topicality of the data and feedback to the employee will secure the success of the system after the starting phase. If these factors are considered, skills management can contribute to the entrepreneurial success in the future.

References

[Ackerman et al. 1999] Ackerman, Mark S; McDonald, David; Lutters, Wayne; Muramatsu, Jack: Recommenders for Expertise Management. 1999.

[Blandin 2003] Blandin, B.: From Skills Management to e-Learning to Knowledge Management: A virtuous loop to support performance. Congresso HUMAN 2003, 2003.

[Bohme 2001] Bohme, Ingeborg: In (Sommerlatte, T./Antoni, C.H.) Report Knowledge management: How German companies organize their profit centers, Chapter Potential of employee profiles (in German), Pages 119-127. symposion Publishing, Dusseldorf, 2001, Online: http://www.symposion.de/wm-hb/wm/_21.htm.

[Deiters et al. 1999] Deiters, Wolfgang; Lucas, Reinhard; Weber, Thorsten: Skill-Management: a building block for project management with flexible teams. ISST-Bericht,Dortmund,1999. Online: http://www.do.isst.fhg.de/wm/veroeffentlichungen/

[Dingsoyr and Royrvik 2000] Dingsoyr, Torgeier; Royrvik, Emil: Skill Management as Knowledge Technology in a software consulting company. 2000.

[Faix et al. 1991] Faix, Werner G.; Buchwald, Christa; Wetzler, Rainer: Skill Management: Human resources development in companies (in German). Gabler Verlag, Frankfurt, 1991.

[Gronau 2003] Gronau, Norbert: Modelling knowledge intensive engineering processes with the Knowledge Modeler Declaration Language KMDL, Proceedings of ICE 2003 Espoo, Finland, 2003

[Gebert and Kutsch 2003] Gebert, Henning; Kutsch, Oliver: Potentials of skill management (in German). Wirtschaftsinformatik, Ausgabe 45, Pages 227-229, 2003. Online: http://verdi.unisg.ch/

[Hamel and Prahalad 1990] Hamel, Gary; Prahalad, C.K.: The core competence of the corporation. Harvard Business Review, (May-June), 1990.

[Huneke and Zimmermann 2000] Huneke, Knut; Zimmermann, Bernd: Skill-Databases (in German). Computer-Fachwissen, 8-9/2000. Online: http://www.khueneke.link-m.de/

[Kreitmeier et al. 2000] Kreitmeier, Ingrid; Rady, Bettina; Krauter, Markus: Potential of Skill-Management-Systems (in German). http://www.hr-solutions.de/, 2000.

Mathias Uslar graduated from Oldenburg University in 2004 with a major in Computer Science and
a minor in Legal Informatics. Currently, he is with the OFFIS in Oldenburg, a third-party funded
institute affiliated with the university. His major work deals with interoperability and enterprise
application integration in the utilities domain using the Common Information Model CIM (IEC 61970).
He furthermore focuses on knowledge management and electronic democracy. Mr. Uslar is member of the
GI, ACM and IEEE. You can contact him at uslar@offis.de.

Norbert Gronau (born 1964) studied engineering and business administration at the Berlin University of Technology. In 2000 he completed his thesis in sustainable frameworks for architectures of industrial information systems. From 2000 to 2004, he was full professor for Business Information Systems at the University of Oldenburg . Currently he holds thechair of Business Information Systems and Electronic Government at the University of Potsdam. His main research activities are in Knowledge Management and Business Resource Management. Prof. Gronau is editor of different scientific journals, author of more than 90 papers and of books. E-Mail: ngronau@wi.uni-potsdam.de

Short description
Distribution and acquisition of knowledge within companies is supported by skills management systems. This paper summarizes the requirements, scopes and problems for skills management systems within the company.

Keywords and relevant phrases
Acquisition, competencies, critical mass, data acquisition, distribution, expert, integration, knowledge resources, motivation, participation, personnel development, rating, recruitment, skills catalogue, skills management, system.

Back to ... Workinfo.com Human Resources Magazine Volume 1 Issue 5, 2007