Data collection

In public administration and in other organizations, many different data are collected:

• personal data
• financial data such as production costs (cost-benefit calculation)
• data in the context of evaluations (monitoring)

In the following, you can find information on the collection of personal data, i.e. both internal data on staff and external personal data.


Collection of internal data on staff

In order to be able to utilize the potential of staff in a optimal way and increase their job satisfaction, it is necessary to remove possible discrimination and actively promote equal treatment of women and of men. Successful staff development therefore requires more precise information on the current situation of women and men in an organization. This is only possible if personal data are collected consistently and systematically in a way that is differentiated in terms of gender.

This has now been prescribed by law for the German Federal Civil Service, as the collection of data on Civil Service staff has been harmonized with the provisions of the Federal Equal Treatment Act (cf. Ordinance on Statistics Relating to Equal Treatment [German] of June 18, 2003). On the basis of this legislation, data of central importance for staff development oriented to gender equality are collected in a way that is differentiated in terms of gender. This includes

• Training: attendance of training events (Section 1 subsection 1 No. 6)
• Promotion: Assigning of management functions (...) by comparing relevant applications and proposals for selection (Section 1 subsection 1 No. 7)
• Staff evaluation: 8. Total number of (...) staff evaluated compared with the number of staff who have gained top marks, classified by pay group and according to the nature and scope of duties; (...)(Section 1 subsection 1 No. 8)

For optimal staff development, the data should moreover be collected in a way taking account of differences in age and family situation. The breakdown of personal data with regard to other structural criteria has to be limited, however, at the point where individual people can be identified. Exclusively anonymous data are required for specialist work dealing with differentiation by target group and orientation to gender equality.


Collection of external personal data

Many administrative authorities and other organizations collect external data in order better to be able to steer their specialist work. For example, the number of people using public facilities such as libraries is statistically recorded. If such data are collected in a way that is differentiated in terms of gender and possibly also of other structural criteria, it can then be determined on the basis of this information which women and which men use the offer in question and who is as yet not being reached by the offer. When collection criteria are being determined, care should be taken that they cover various forms of life in our society. For instance, the question of marital status (single, widowed, divorced) says less than the question of partnership (ISOE 2005:9). On the basis of this information it is possible for instance to develop public relations for specific target groups in order to increase the number of visitors.

Most officially collected data are process-produced, such as the internal data on staff already mentioned or employment details collected within the framework of official statistics. Within the scope of such statistical collection of data, only observable characteristics of people can be clearly counted, such as the number and composition of the users of an amenity, differentiated according to gender or age. Other characteristics can only be measured indirectly, e.g. the attitude of the users to the services offered by the amenity. This may include their acceptance of them, their expectations and motivations. But on the basis of such findings, more precisely optimised tailor-made measures and services can be offered. So, alongside process-produced data, much information is gathered by way of empirical research.

• Here you can find information on GM in research projects.