Higher Education Statistics collection and processing Discussion

Higher Education Statistics – collection and processing Discussion on the Swedish Case Anna Gärdqvist and Mats Haglund Statistics Sweden Reflection on the Austrian Case Michaela Schaffhauser-Linzatti University of Vienna May 11, 2006, Graz

Presentation Sweden: students Presentation • Data flow Paper • Organisational responsibilities Austria: Overall Information Reporting on performance Monitoring of data • Data flow • Organisational responsibilities • Selected reporting tools • General aspects of reporting on Higher Education • Possible answers from the Austrian experience

Data Flow S: A: Swedish National Board of Student Aid; Ministry of Education, Research and Culture; Statistics Sweden Register of Higher Education Public Universities Federal Ministry for Education, Science and Culture University Report Vocational Universities (FH) FH-Council Private Universities Theological Universities Others Statistics Austria Report on Higher Education

From Basic Data to Statistics Sweden: Statistics Sweden Austria: Universities (Example: University of Vienna) i 3 v Administrative register Le Salaire SAP R/3 - Editing and coding Register-statistical processing - Handling of missing objects and values - Matching and selections - Processing of time references Statistical register ETL Data Warehouse - Creating derived objects and variables Reports Federal Ministry

External Reports (Public Universities) Internal reports External reports To the public Income and expenditure accounting Others To political decision-makers Performance Report University Report Intellectual Capital Statement Report of the University Council Financial Statement Others Evaluation report Others according to UG 2002 further: f. e. Uni. St. EVO, Bi. Dok. V-Univ

Performance Report • Aims – Report on the qualitative and quantitative development of the university – Forecast on the future performance and financial situation – Basis for the university report • Definition – Information on the performance agreement – Published annually by the rectorate – Including past two years, forecast for the following year

Performance Agreement • Aims – Budgeting – Performance based controlling instrument • Definition – Performance agreement by public law between each university and the Federal Ministry – According to the aims of the university – Regulates budget allocation by the Federal Ministry on basis of the performance of each university – For periods of 3 years – Indicators and details regulated by the order “Formelbudget. Verordnung”

Intellectual Capital Report (I) • Aims – Measurement, evaluation und publication of • Intellectual assets • Knowledge based processes • Knowledge based results – Instrument for • Communication between university, Federal Ministry and the House of Parliament • Control for the university by separate bodies and through responsible bodies of the state owner • Marketing of the university

Intellectual Capital Report (II) • Definition – Demonstration of • The university’s activities, social activities, and self-imposed objectives and strategies • Intellectual capital, broken down into human, structural and relationship capital • The processes set out in the performance agreement, including their outputs and impacts – Published annually – Indicators and details regulated by the order “Wissensbilanz. Verordnung”

Intellectual Capital Report Model Visions, objectives, strategies Additional topics Narratives Intellectual Capital + Core processes + Outcome and results of core processes Indicators Resumee and perspectives Narratives Indicators

Contents • Basis of data acquisition – Personalised – Aggregated • Dimension of indicators – Qualitative indicators – Quantitative indicators • Monetary • Non-monetary • Number of indicators – 53 “global” indicators – Refer to 5 different reporting periods / key dates – Structured into • Fields of Study • Curricula

Pros and Cons of the New Austrian Reporting System on Public Universities • Pros • Cons – New reporting system with international archetypes – Transparency – Communication • External • Internal – Management orientation • Comprehensive data acquisition • Planning basis • Aid for decision making – – – Overlappings of reports Volume Standardisation Data validity Costs of implementation, preparation and auditing

Possible Consequences • • • Performance orientation Competition between the universities Competition within the universities New emphases of universities New allocation of resources

More information • Federal Ministry for Education, Science and Culture www. bmbwk. gv. at www. weltklasse. at • Fachhochschulrat www. fhr. ac. at • Statistik Austria www. statistik. at