The Computer Aided Competence Management Business Essay

These days due to the high competition between in the industrial sector, companies tend to investigate new ways of using the human resources more efficient which could lead to lower costs. More specifically and in order to do that, the human competencies and the knowledge should be analyzed.

The scope of Competency Management is the significance of measuring and predicting of a set of indoor attributes that could react on the performance and success in executing a particular role inside a system and map to a diagnostic target [1]

The result of these attributes could be skills, abilities, capacity, motivation, knowledge and more. Based on a research between many studies and publications [2], [3], [4], and [5], Competence Management is a result of 7 different steps. The step that comes first is the "identification and audit of current competencies"[6]. The second step is the ability to define the new competencies. The third step is about the analysis of the gaps. In the forth step the main component of Competency Management, competency mapping is fulfilled. If the above steps were completed in a successful way, it will lead in a recommendation tool and Learning Management Component (LMC). Recommendation tool gives a computerized recommendations to the users based on their competencies that have been measured.

Computer Aided Competence Management

In a world that is changing quickly, lifelong learning is important in employment, the economic success and also to the integration in the society. Education and training are institutionally recognized in European Union by the Lesbon Strategy(2000)[1] and its successor Europe 2020(2010)[2] as very important. The Lisbon Strategy(2000) is mainly regarded as a failure, but sure not because of the concept of learning economy.

This concept, learning economy, assumes that in modern economies knowledge is considered as crucial resource and as one of the most important process, the learning. The Europe 2010 that is parted in 7 initiatives, one of the most important focuses to provide to the people the necessary skills for jobs of today but also for feature jobs.[2]. The strategies that Europe adopted for economic growth have conducted concepts that have been proven already successful in enterprises. The past 20 years, human resources management in enterprises have shifted to strategic management of human resources from the now obsolete measuring of individual productivity. [3]. Competence Management includes the implementation, evaluation and planning of the initiatives and in that way is able to guarantee sufficient competencies of the employees and also the ability of the company to reach the objectives[4]. With the help of the Web, there is the ability to redistribute the human resources activities with the competence management from the HR department to the entire company.

An Analytical Model of E-Recruiting Investment Decision: An Economic Employment Approach

The late 90’s was the decade that the economy saw great growth also the technology of e-recruiting had an increasing demand while the demand of highly qualified employees could not satisfied by the labor market[1],[2]. The companies had to redesign their recruiting procedures in order to move as fast as they could to web-based integrated human resource systems in order to benefit from the standardized frameworks for key personnel procedures [3].

According to IDC(www.idc.com), $260 billion was the corporate investment on e-commerce in 2000. From Brick and mortar companies came more than 85% of this investment. Information Technology is one of the most important costs in most businesses and as also the statistics shows, IT must have an extra attention from the management. Many businesses, despite their size had to realize that the key is to put their funds on business opportunities through the development of Information Systems. Cost savings, information richness and efficiency were some of the most important advantages that contributed to the rapid and also successful adoption of e-recruiting system in advantage of both recruiters and job seekers [4]-[7]. E-recruiting also gives the ability of instant and almost costless global dissemination of available jobs to the entire world without any geographical constraints. Nevertheless, business should pay attention in not overinvest in e-recruiting systems. The majority of the companies face e-recruiting systems as a resource critical to their strategy allthouth they should focus in developing a mathematic based model of online recruiting system in order to be able to analyze and evaluate different ways of e-recruiting.

LM-DTM: An Environment for XML-Based, LIP/PAPI-Compliant Deployment, Transformation and Matching of Learner Models

Despite the growing usage of learner profiles around the world and after many efforts, learner profiles are not yet standardized. Learner profiles consist mainly from 2 specifications. One is the IEEE Personal and Private Information(PAPI) [13] and the other also important specification is the IMS Learner Information Package(LIP)[14]. In order to make the indormation of learner profiles flexible to store them, there e of PAPI and LIP take action to determine a standard exchange protocol, this will give the ability of easy manipulation of the data such as advanced search, flexible storage and fast access. Despite that both standards are about the same scope there are significant differences. Personal And Private Information( PAPI) mainly focuses in a way that could give the ability to track the learners performance as quick as possible using categories such as performance, relation to other learners and portfolio and in order to do so keeps the information set to minimum. Keeping the information to minimum have the disadvantage that the PAPI protocol is not able to cover some learner’s features that could be useful to make recommendations or filtering in adaptive systems[15]

On the other hand, Learner Information Package(LIP) make use of a much more rich information set and takes into account much more features and interest in order to describe the learner’s characteristics and it is extensible.

Human Resource Management and Semantic Web Technologies

Another project that focuses on the problems of e-recruiting and tries to deal with them by introducing a new approach that is based on the competency management is CommOnCV (CompetencyOntology CV). The scope of the CommOnCV is to allow a job seeker or a recruiter to acknowledge and represent any competencies that may underlie in its resume or the CV. Competencies like skills, abilities, knowledge, motives and traits that are acquired by the job seeker and can be made explicit are also used in order to refine the process the relies between "supply and demand". All the competencies correspond to ontology-based annotations which basically can be represented by the semantic web languages. The CommOnCV project in order to achieve this first is based on a competency model and then to the management of competencies.

Automating Competence Management through

non-standard Reasoning

Knowledge Management (KM) focuses on the competitive advantage in human resources so it is reasonable that knowledge intensive companies may pay attention to the advantage of human resources by taking benefit of Knowledge management. To use efficient the Knowledge Management there are many methodologies that have been proposed whose effect on the company’s investments is considered as valuable as any other material assets. An extra attention has been provided to identify the capabilities that lead many companies to business success and some approaches have been introduced and classified to undertake a particular problem.[1]

Some difficulties may be caused when using automated management of knowledge despite material assets. One of the most significant drawbacks is due to the subjectivity and intangibility typical of knowledge: the information of the personnel competence needs to also take negative information into account and to clearly interpret the domain vocabulary.

By using formal languages and ontologies merged with semantics gives the ability to automatic systems to overcome some limits peculiar to less expressive sorts of knowledge representation. Furthermore, defining and adopting reasoning services exploiting explicit information description to infer new knowledge is enabled by the right choice of formal languages.

Using ontology for resume annotation

Europass is a Curriculum Vitae(CV) is a standardized form that enables users to document their qualification development profile systematically and chronologically. It also gives the ability to the user to store information about their skills, work experience, personal details and competencies that each one has in a standarised document that they could use across Europe without any national constraints. The job seeker can fill the form of the Europass online in any European language and in different formats like PDF,XML etc. This makes the Europass a great tool with great transparency of the competencies and the qualifications of the job seekers or the recruiters.

Some of the categories of information that Europass contains are:

Personal Information: This section Contains the name of the applicant and their contact information

Job applied for: Allows the applicant to specify his job target

Work Experience: The user can describe his work experience

Education and training: Here the applicant can describe his qualification, education and tanning and principal/occupation skills.

Personal skills: The user can fill in the languages and his skills on them

Communication skills: The user can describe his communication skils

Orginizational/managerial skills: The applicant is able to describe his organizational and managerial skills.

Job Related Skills: Describes the job related skills

Computer Skills: Describes the computer skills of the applicant

Additional Information: In this section the applicant is able to fill in any other relevant information

Annexes: Inventories any items attached