regional needs: forecasting and targeting university actions
DESCRIPTION
Issues in forecasting regional needs and targeting university actions to address those needs; particularly from a Nordic perspective.TRANSCRIPT
www.laurea.fi
Director of Regional Services Dr Teemu Ylikoski
Regional needs: Forecasting and targeting university actions
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Regional Services & the UAS field
Improving the depth and width of regional cooperation
Partnership management
Systematic cooperation
Quality management
and feedback
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PERSONNEL
NETWORK
PROJECTS
NEEDS
PresentationPro
finding adaptable solutions
coordination
one-stop shopping
common goals
Regional Services
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A win-win-win equation
Regional cooperation
needs to benefit all
parties
Regional partner Laurea
Student Authenticity; Employability
Competitive position in the
educational field
Improved processes; new
skills
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Needs and capabilities
L
R
S
Capabilities: L = Learning; R = Research; S = Services
uni
S
I
C
region
Needs: S = Skills;
I = Innovation; C = Community
Modified from Goddard & Chatterton 1999 Goddard, J. B., & Chatterton, P. (1999). Regional Development Agencies and the knowledge economy: harnessing the potential of universities. Environment and Planning C, 17, 685-700.
What are the capabilities needed
for assessing: - The region’s needs
in terms of skills gaps, innovation
needs, community interests?
- The Uni’s ability to produce learning,
research and services to match the above needs?
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Regi
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Capabilities in data acquisition: Forecasting regional development needs in the Uusimaa region
Country level soc-dem data
Matching Proxy for regional needs
Total students / projects / etc
required
Education to occupation
match: FNBE
workforce demand
forecasts by industry: GIER
Workforce structural
forecasts by industry: GIER
Employment forecast: STAT
Labor market exit forecast:
GIER*
Regional socio-dem trends: STAT
Legend: GIER = Government Institute for Economic Research (VATT) STAT = Statistics Finland FNBE = Finnish National Board of Education (OPH) *future of forecast uncertain as of 9/14
Extrapolation to regional
level
Loosely based on the ”Mitenna” forecasting model (FNBE)
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Data acquisition: other perspectives
" Towards a dynamic, future-oriented view " Aggregate country level data is updated infrequently
and lags 12mths or more " Stiff trends do not allow for agile responses " In terms of emergent regional needs, primary data
collection may be necessary " Primary data collection: considerations
" Due to the diversity of the population (regional clusters) and actor size dispersion (SMEs), a potential survey faces severe complexities
" For certain selected subgroups, other approaches may be available (regional forums, industry panels, associations), however, this will likely result in non-standardized data
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Capabilities in forecasting system deployment
" Data interfaces: multiple, non-standard data sources; non-standard update procedures, non-standard update frequencies. Manual entry likely needed.
" User interfaces: an open, online platform with low entry threshold likely needed – ensuring low barriers for regional public sector, private sector, third sector " User adoption rate has a positive return loop to data
quality " Privacy issues should be avoidable by focusing on an
aggregated, semi-public level in the raw data
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An opportunity to learn
Best practices benchmarking various approaches
comparison of current options
New approaches compensating for missing data
dynamic capabilities; towards a real-time view