Download - The Data Never Lie
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The Data Never LieBut, Do We?
Los datos nunca mientenpero, ¿y nosotros?
Eric N. Schreffler, ESTC13 May 2009
ECOMM 2009, San Sebastian, Spain
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The Data Never LieBut, Do We?
The Politics and Policy Implications of Mobility Management Evaluation
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OverviewWhy Evaluate?
Why Do I Care?
How Can Evaluation be Manipulated?
How Can We Avoid the “Dark Side?”
A Challenge
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A Disclaimer… This is my opinion I am being a bit harsh to
make a point Most people here do very good
evaluations We will learn a lot more this
week I am an American… we know
it all
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Why Evaluate?Satisfy funders?Satisfy policy-makers?Sound management practice?Measure progress against objectives?Refine program or project?
Don’t you really want to know?
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Why are We Scared to Evaluate? It costs money It takes a lot of time Need to plan before
project starts Behavior change takes a
long time We are not researchers or
academics
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Why Really Are We Scared to Evaluate? What if the results are
not favorable?
Will it make me look bad?
What if I FAIL?
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Why Do I Care? I have been evaluating
Mobility and Demand Management programs for almost 30 years
I have seen the good, the bad, and the ugly
I know MM gets marginalized I believe in the overall
effectiveness and cost effectiveness of MM/TDM
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Manipulating ResultsCan Evaluations be Manipulated?
How Can Evaluations be Manipulated?
How Are Evaluations Manipulated?
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Manipulating Evaluation Focus only on “before” forecasts,
not “after” results;
assuming forecasts =results
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Manipulating Evaluation Focus only on “before” forecasts, not “after”
results
Use “rules of thumb” or expected results
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Manipulating Evaluation Focus only on “before” forecasts, not “after”
results Use “rules of thumb” or expected results Focus data collection only on the
“converted”
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Manipulating Evaluation Focus only on “before” forecasts, not “after”
results Use “rules of thumb” or expected results Focus data collection only on the “converted” Use anecdotal
stories; qualitative findings
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Manipulating Evaluation Focus only on “before” forecasts, not “after”
results Use “rules of thumb” or expected results Focus only on the “converted” Use anecdotal stories;
qualitative findings Spin results
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Manipulating Evaluation Focus only on “before” forecasts, not “after”
results Use “rules of thumb” or expected results Focus data collection only on the “converted” Use anecdotal stories; qualitative findings Spin results Omit results
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Avoiding the Dark Side
TrafficEngineer
Funding SourceMobility Manager
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Avoiding the Dark SideBuild evaluation into funding processEstablish credibility through scientific rigorPool resources and resultsUse guidance offeredUse local academics
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Advice: know your weaponKnow your evaluation,
love your evaluation,
for one day, your evaluation just might save your life
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The Results May Surprise YouAccording to
Congressionally-mandated study of principle funding source used in US, TDM and MM are among the most cost effective strategies for reducing emissions
TRB Special Report 264
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Just Do It!!!
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contactEric N. SchrefferTransport ConsultantSan DiegoCalifornia
001.858.538.9430
muchas gracias para su atenciōn