Knowledge Management in Housing and Transportation Policy: How to Connect Performance Measurement and Decision Making


Nov 6, 2013 (4 years and 6 months ago)


Knowledge Management in Housing and
Transportation Policy: How to Connect
Performance Measurement and Decision


Milan J. Dluhy

Professor of Public Administration

University of North Carolina Wilmington


Over 200 Community Indicator Projects in the U.S.

“Bottoms up” projects, developed at local level

No common structure or template for measures

Literature shows Quality of Life Projects, Benchmarking Projects,
Economic Indicators, Social Indicators, Health Communities and
Cities, Sustainable Cities Projects

Diversity in purpose and focus

All projects appeared aimed at influencing policy agendas

Common theme is to emphasize a “results oriented management

Little literature on the actual utilization of PM by decision makers

Purposes of Paper

How to Develop more comprehensive
Performance Measures in Community Based
Decision Making (in housing and transportation)

How to get Decision Makers and other
Community Stakeholders to use Performance
Measures more frequently (in housing and

How to provide better advice to Decision Makers
at the Local Level (in housing and transportation)


A performance measure is a quantifiable,enduring
measure of outcomes, outputs, efficiency, or cost
effectiveness. In general, measures should be related
to an agency’s/ community’s mission and programs,
and they should not merely measure one
time or
short term activities.

Uses of PMs

Track projects in a strategic plan

Track accomplishment of goals in planning/policy

Track policy and program outcomes over time

Report community progress to decsion makers and

Benchmark with other jurisdictions to gauge
effectiveness of effort

Track performance over time to determine trends,
progress, and priorities

How to Improve Connections
between Knowledge and Policy

Always use (and include) a wide range of
measures when deciding what data will be

Emphasize outcomes and outputs whenever
possible, but do not ignore efficiency, inputs,
and productivity

Also try to use readily available data online if
possible so inter
jurisdictional comparisons can
be made

Selected Housing Measures

Housing Affordability

Financial Burden or

Unit over 30 yrs old

Median Value of unit
(Output, Outcome)

% Ownership (Output,

Avj. Square Ft per unit
(Output, Outcome)

Neighborhood Crime
(Output, Outcome)

No transit accessible
(Output, Outcome)

Amenities nearby (Output,

Tax burden (Outcome)

Commute time to work

Fraction/Acre per resident

Rating of Schools

Selected Transportation Measures

Travel Congestion

Mean travel time to work

Rides public transit
(Output and Outcome)

Live within one fourth of
mile of transit (Output and

Operating expenses per
passenger mile
(Efficiency, Outcome)

% of population owning
vehicle (Efficiency and

Vehicle miles driven per
capita (Output, Outcome)

Accidents per thousand

affordability (Outcome)

How to Improve Connections between
Knowledge and Policy

When designing the data sets for the community make sure
there are measures for all major
constituencies/stakeholders interested in progress and

Stakeholders have preferences for Outputs, Outcomes,
Efficiency, Inputs, and Productivity

Stakeholder Preferences for PMs

Elected Officials more
interested in

Property tax burden


Quality of Schools

Neighborhood Crime

Age of unit (over 30 years)

Rides public transit to work

Accidents per thousand

Consumers more interested in

Financial burden (rent/income

Structural quality of house/apt

Property tax burden

Commute time to work

Quality of Schools

Neighborhood Crime

Housing affordability

Traffic Affordability

Cost of gasoline

Commute time to work

Stakeholder Preferences for PMs



Commute time to work

People per square mile

Amenities nearby

Traffic congestion

Energy use per capita

Per capita emissions


Age of units (over 30 years)

Median value of unit

% Ownership

Use carpool

Rides public transit to work

Traffic congestion

How to improve the connections between
Knowledge and Policy


Use stakeholders to develop measures and then fully
integrate the measures into the planning and decision
making processes

There are a number of communities in the U.S. with a
long history of using a civic engagement approach to
develop PMs which reflect a “bottoms up” consensus
building process

Examples include Asheville, N.C., Austin, Tx.,
Jacksonville, Fl., San Francisco, Ca., Seattle, Wash.,

Examples of Civic Engagement Strategies

Community Steering or Advisory Committees represented
public, private, and non
profit sectors

Community forums/Retreats

Regular surveys and focus groups

Annual agenda setting conferences

Occasionally setting up a new 501 c3 organization to
manage the “bottoms up” community building process

Use of white papers on issues of the day

Interactive web
sites and email surveys

TV and radio programs

How to improve the connection between
knowledge and policy

Present reports of measures to interested parties on a
regular basis and work with media to disseminate results

Institutionalize annual report and conference

Become legitimate reporter on the “state of the region”

Develop working groups to follow up on cross cutting issues and
have them focus on implementation of recommendations

Keep the public sector, private sector, and non
profit sector working
together, do not let one sector dominate

Establish political action committees if needed for political lobbying

In first 3
5 years, focus on a small number of cross cutting issues

How to improve the connection
between knowledge and policy

5. Whenever possible make cross
community or cross jurisdiction

Benchmarking against other areas helps to identify
priorities and other approaches that might work
better for the community doing the comparison

Public Transit Rider
Ship Rates in North Carolina


Ship Rate

Chapel Hill


















Results from a 50 city inter

In the 50 city analysis, housing homeownership rates are the highest in
the smallest areas and considerably less in the biggest areas

Smaller areas also have shorter commute times, are less likely to use
transit, and people are more likely to drive alone

Smaller areas also have lower value homes and are less dense

Larger areas consistently are more dense, have longer commutes to
work, have higher home prices, have less homeownership, and have
more people carpooling and taking transit.

From a positive policy perspective and benchmarking perspective,
decision makers would seem to prefer higher value homes, more
homeownership, more carpooling and transit rider
ship, and fewer
people driving to work alone. Each size community seems to have its
unique advantage and disadvantage (when benchmarking)


Some Challenges for PM
utilization at the local level

Keep same core indicators, do not keep changing them

Monitor trends over time so changes in policy can be assessed, you
need at least a decade to see most changes

If consensus on a measure of success or failure breakdown, develop a
new measure

Make sure all three sectors come to the table and agree upon measures

Pick bench
marking or “best practice” comparisons very carefully and
very politically