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Workshop on Human Resources Management and Training in Statistical Offices 14-16 September 2010

Workshop on Human Resources Management and Training in Statistical Offices 14-16 September 2010. Setting up in-house training: Some issues to consider By Dag Roll-Hansen (dag.roll-hansen@ssb.no), Division for international development cooperation in Statistics Norway. Co-operation countries.

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Workshop on Human Resources Management and Training in Statistical Offices 14-16 September 2010

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  1. Workshop on Human Resources Management and Training in Statistical Offices 14-16 September 2010 Setting up in-house training: Some issues to consider By Dag Roll-Hansen (dag.roll-hansen@ssb.no), Division for international development cooperation in Statistics Norway

  2. Co-operation countries

  3. Technology is not enough • Employees work harder as a result of more involvement, commitment and affection, resulting from a high degree of autonomy and control over work processes. • Employees work smarter because they are encouraged to develop their skills and competence in general. • Employees work more responsibly, because more responsibility is in their hands. Pfeffer, J., and Veiga, J. F. (1999), "Putting people first for organizational success", Academy of Management Executive, Vol. 13 No. 2, pp. 37-48.

  4. Why train in-house? • We are not producing maize or building houses. Our raw material is human beings. That is what we have to develop. 4 The quality of a National Statistical Institute (NSI) to a large degree depends on the performance of the employees. The skills needed in a national statistical institute are a mix of theoretical knowledge and practical skills.

  5. Training must do two things: 5 “First it must move your attitude. Second the skills you gain can only be seen in your work. If work has not changed, then training has done nothing. And remember, the knowledge you gain is not yours. You have to pass it on to others.” Mr. Isaiah Chol Aruai, Chairperson of SSCCSE, Southern Sudan

  6. Using the statistics business process model to identify training needs

  7. Gap analysis

  8. Mapping competence with a survey

  9. Sustainable in-house training • Focus on an up-coming task • Draw on existing skills in the organisation • Use local assistant teachers • Giving training in-house makes it possible to tailor it to the needs of an NSO and have it at a convenient time • Skills are forgotten if not used

  10. Training the “untrainables” Competence Training input

  11. Evaluate training • Questionnaires • Interview employees • Test skills • Monitor improvements • Performance appraisal/development talk

  12. Four programs • Program for new employees: Basic level • Training of statisticians: Intermediate level • Training and certification of senior statisticians: High level • User seminars

  13. Program for new employees: Basic level Receive new employees in a way that makes them understand the organisation, the statistical process, their tasks and that integrates them socially as fast as possible. Core topics: • Basic skills • Organisational issues • Statistical thinking • Practical information on HR-issues, IT-systems and tools • The relation to users and international cooperation • Career development

  14. Training of statisticians: Intermediate level The needed skills may be quite specialised and vary depending on the statistics in question. • The statistical production process • Training in economic statistics • Training in demography and social statistics • General topics

  15. Training and certification of senior statisticians: Developing leading professionals The over all aim of training Senior statisticians is to improve the quality of statistics produced by building on colleagues with a thorough knowledge of: • The statistical system; the legal ground, statistical methodology, standards, data security and user needs. • The statistical production process; data gathering, data processing, analysis and dissemination.

  16. User seminars We do not make statistics for ourselves. To be used, it must be perceived as useful. Measures should be taken to ensure that statistics are usable for making policy based on evidence. • Identifying data to collect - defining the questions we are trying to answer • Making use of statistics - learning about the interpretation and use of statistics, including its limitations.

  17. Future challenges • Building commitment • Training material • Motivation to teach

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