DIVERSITY DATA & METRICS:
IMPACT AND ACCOUNTABILITY
Michele Minter
Princeton University
June 3, 2013
What gets measured, gets managed.
Peter Drucker
What are data and metrics used for?
• To answer questions
• To monitor activity and trends
• To create accountability
• To challenge assumptions and change behavior
• To manage compliance obligations
• To communicate to the community
Types of data and metrics
• Survey/focus group/interview
• Demographic
• Benchmarking
• Reporting activity
• Compliance data
Good data and metrics
• Capture the right things at the right level of granularity
• Create accountability
• Identify problems
• Incentivize good behavior
But…
Not everything that can be counted
counts, and not everything that counts
can be counted.
Albert Einstein
Goal setting: measuring against what?
• Before setting diversity goals, the definition and value of
diversity must be clear
• Diversity goals may measure:
• Desired level and quality of activity
• Aspirations to:
• Be in the top percentage on a given measure, when compared with
peers
• Show numerical improvement in representation
• Show improvement in measures of climate
Princeton’s diversity goal setting
• Explains why diversity matters for Princeton
• Asks departments to review their data and “diagnose”
•
•
•
•
•
their challenges
Asks departments to define activities for which they are
willing to be accountable
Imposes some priorities set by the central administration
Expects numerical improvement as a result of activity but
doesn’t mandate it
Provides many tools and resources to help departments
achieve goals
Asks departments to report on progress
In our lust for measurement, we
frequently measure that which we can
rather than that which we wish to
measure... and forget that there is a
difference.
George Udny Yule
The challenges of data and metrics
• “Garbage in, garbage out”
• Data and metrics may not measure what you think they
measure
• “Apples and oranges” confusions
• Correlation vs. causation confusions
• Wrong level of granularity smoothes data or masks problems
• Changing definitions create confusion
• FERPA constraints or statistical invalidity can compromise
the ability to measure
• Metrics can motivate the wrong behavior
• Metrics can become burdensome and bureaucratic
Elements of a Good Internal Dashboard
• Survey data regarding campus climate and perceptions
• Demographic snapshots + appropriate benchmarks
• Demographic trend data + appropriate benchmarks
• Flow data: hires, departures, candidate pools
• Activity highlights
• Ability to sort data in multiple ways, including at the
institutional level, at the unit level, and by sub-populations
Data are just summaries of thousands
of stories – tell a few of those stories to
help make the data meaningful.
Chip and Dan Heath
The External Dashboard
• Demographic snapshots
• Demographic trend data
• Activity highlights
• Climate snapshots
• Plus lots of contextual information, including institutional
values, why diversity matters, and voices of individual
constituents
Things get done only if the data we
gather can inform and inspire those in a
position to make a difference.
Mike Schmoker