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Framing the discussion:
Key considerations for
strategic internationalization
Rhonda Friesen
University of Manitoba
Universities Canada ILO Day
February 19, 2016
Measuring Internationalization:
Naming the ‘elephants’
Comparative
data &
benchmarking
Unique
institutional
context
1. Data provides context not targets
2. Encourages ‘healthy’ competition
& cooperation
Cooperation Competition
Sets
performance
expectations
Pushes beyond
complacency
Differences,
similarities more
visible
Sharing best
practice
3. Highlights the ugly as well as the good
Identifies gaps and
assumptions
Shows (un)intended
impacts
Points out where we are
going
Collecting data at the institutional level:
Sizing up the elephant
What
do we
know?
What
do we
need to
know?
What
are the
gaps?
Why do we need data?
Age of “intelligent internationalization” – need for
information to guide decisions
Strategic
decisions
• Aggregate
numbers
• Broad trends
• Institutional
priorities
Management
decisions
• Descriptive
data
• Program
adjustments
• Manage Risk
Impact &
progress
• Qualitative
data, stories
• Outcomes
• Community
engagement
How do we gather data? Building a
strategy from diverse perspectives
Perspectives
Drivers
DATA
Strategy
Starting
point for long
term success
Typical
starting point
Developing a measurement framework
Governance
Student
Faculty Curriculum
Research
EngagementComprehensive
International
Data
Remembering data limitations
 Does it tell the ‘complete’
story?
 Does it tell a ‘relevant’
story?
 What conclusions can it
reasonably draw?
 What assumption does it
expose?
In summary:
Using data to shape strategy
Be aware of the challenges
Plan for diversity
View critically, use carefully
Start somewhere!
Thank you!
https://ca.linkedin.com/in/rhonda-friesen

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Strategic internationalisation - ILO Mtgs Feb 2016 (2)

  • 1. Framing the discussion: Key considerations for strategic internationalization Rhonda Friesen University of Manitoba Universities Canada ILO Day February 19, 2016
  • 4. 2. Encourages ‘healthy’ competition & cooperation Cooperation Competition Sets performance expectations Pushes beyond complacency Differences, similarities more visible Sharing best practice
  • 5. 3. Highlights the ugly as well as the good Identifies gaps and assumptions Shows (un)intended impacts Points out where we are going
  • 6. Collecting data at the institutional level: Sizing up the elephant What do we know? What do we need to know? What are the gaps?
  • 7. Why do we need data? Age of “intelligent internationalization” – need for information to guide decisions Strategic decisions • Aggregate numbers • Broad trends • Institutional priorities Management decisions • Descriptive data • Program adjustments • Manage Risk Impact & progress • Qualitative data, stories • Outcomes • Community engagement
  • 8. How do we gather data? Building a strategy from diverse perspectives Perspectives Drivers DATA Strategy Starting point for long term success Typical starting point
  • 9. Developing a measurement framework Governance Student Faculty Curriculum Research EngagementComprehensive International Data
  • 10. Remembering data limitations  Does it tell the ‘complete’ story?  Does it tell a ‘relevant’ story?  What conclusions can it reasonably draw?  What assumption does it expose?
  • 11. In summary: Using data to shape strategy Be aware of the challenges Plan for diversity View critically, use carefully Start somewhere!

Notas del editor

  1. Reporting structure Data base software