Employee Profiling in the Total Reward Management
The Human Resource departments are now facing a new challenge: how to contribute in the definition of incentive plans and professional development? The participation of the line managers in answering this question is fundamental, since they are those who best know the single individuals; but they do not have the necessary background. In this paper, we present the Team Advisor project, which goal is to enable the line managers to be in charge of their own development plans by providing them with a personalized and contextualized set of information about their teams. Several experiments are reported, together with a discussion of the results.
KeywordsLine Manager Incentive Plan Human Resource Department Team Advisor Personnel Development
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- 1.OD&M Consulting: Rapporto benefits 2005. In: Lavoro, Carriere (eds.) Collaborazione con, Il Sole 24 Ore (2005)Google Scholar
- 2.European Parliament and Council of the European Union: Directive 95/46/ec of October 24, 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data. Official Journal of the European Communities 31 (1995)Google Scholar
- 3.Licchelli, O.: Personalization in Digital Libraries for Education. Computer Science in the Graduate Division of the University of Bari, Italy (2005)Google Scholar
- 4.Semeraro, G., Abbattista, F., Degemmis, M., Licchelli, O., Lops, P., Zambetta, F.: Agents, personalisation and intelligent applications. In: Corchuelo, R., Cortés, A.R., Wrembel, R. (eds.) Technologies Supporting Business Solutions, Part IV: Data Analysis and Knowledge Discovery, ch. 7, pp. 141–160. Nova Sciences Publishers (2003)Google Scholar
- 5.Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers, San Francisco (2000)Google Scholar
- 6.Frank, E., Witten, I.: Generating accurate rule sets without global optimization. In: Proceedings of the 15th International Conference on Machine Learning, pp. 144–151. Morgan Kaufmann, San Francisco (1998)Google Scholar