Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation...

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Workshop: Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Transcript of Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation...

Page 1: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Workshop: Scenarios, Communication, Mindmaps …

Urban Transportation PlanningMIT Course 1.252j/11.540j

Fall 2006Mikel Murga, MIT Lecturer and Research Associate

Page 2: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Scope

� Introduction from Meyer and Miller � Forecasting … and Scenarios � Demographics as an example � Communication tools � Working with Mindmaps

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Page 3: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Introduction from Meyer and Miller …

1. The world moves into the future as a result of decisions (orthe lack of decisions), not as result of plans

2. All decisions involve the evaluation of alternative images of the future, and the selection of the most highly valued offeasible alternatives

3. Evaluation and decisions are influenced by the degree ofuncertainty associated with expected consequences

4. The products of planning should be designed to increase thechance of making better decisions

5. The result of planning is some form of communication with decision makers

Chapter 1, pages 2-3

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Page 4: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Models and Forecasting… Forecasting

� Forecasting: Scenarios

� Short term extrapolation:The future on the basis of the past

� Applicable to slow incremental change

� We tend to believe that today’s status quo will continue for ever

uncertainty

predictability

� We often ignore … Time into the future

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Page 5: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

…And Scenarios

� A conceptual description of the future based on cause and effect

� Invent and analyze several stories of equally plausible futures to bring forward surprises and unexpected leaps of understanding

� Goal is not to create a future, nor to choose the most probable one, but to make strategic decisions that will be sound (or robust) under all plausible futures

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Page 6: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Scenarios

"Scenarios transform information into perceptions... It is a creative experience that generates an 'Aha!' ... and leads to strategic insights beyond the mind's previous reach."

Pierre Wack GBN

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Page 7: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Reading on Scenarios

� “The Art of the Long View” by Peter Schwartz

� “Scenarios: The Art of Strategic Conversation” by Kees van der Heijden

Both authors work for the Global Business Network (www.gbn.com) and come from the

Shell Planning Group

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Page 8: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Scenarios: Why?

� History is a continuum of pattern breaks � We react to uncertainty through denial

(that is why a quantitative model is so reassuring!)

� Mental models, and myths, control what you doand keep you from raising the right questions

� We cannot predict the future with certainty � By providing alternative images of the future:

� We go from facts into perceptions, and, � Open multiple perspectives

� Approach: Suspend disbelief in a story longenough to appreciate its potential impact

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Page 9: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Scenarios: How?

� Examine the environment in which your actions will take place and see how those actions will fit in the prevailing forces, trends, attitudes and influences

� Identify driving forces and critical uncertainties

� Challenge prevailing mental modes and be creative about the future of critical variables

� Rehearse the implications

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Page 10: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Scenarios: Stages

1. Identify focal issue or decision (ie Global warming)

2. Identify driving forces in the local environment 3. Identify driving forces in the macro environment 4. Rank the importance and uncertainty of each 5. Select scenario logics (so as to tell a story) 6. Flesh-out the scenario in terms of driving forces 7. Analyze implications 8. Define leading indicators for monitoring

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Urban Transportation Planning – Fall 2006

Scenarios: Rules

� Goal: � Required decisions under each scenario? Vulnerabilities?

Can we control the key driving forces?…

� Good scenarios should be plausible, but also surprising by breaking old stereotypes

� Do not assign probabilities to each scenario… � … But give a name to each scenario � A total of 3-4 scenarios: Not just two extremes

plus a probable one. Good to have a wildcard

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Page 12: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Demographics as an example

� Fertility rate:� Avg no. of children

born to women over their lifetime

� Birth rate:� Total no of births

divided by the size of the population

� Canada claims a low fertility rate (1.7) but a high birth rate

Workshop 1 From:Boom, Bust and Echo by Prof Foot 12

Canada's Population Pyramids, 1996

Population in Thousands

Female

3000

20

40

60

80

CANADAMale

Age

200 100 0 100 200 300

Figure by MIT OCW.

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Urban Transportation Planning – Fall 2006

Demographics: What do you make of this? Pirámide de Población 1981 - Población Ocupada 1981 (C.A.V)

-100000 -80000 -60000 -40000 -20000 0 20000 40000 60000 80000 100000

0-5 5-10

10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 >=75

Mujer Ocupada Hombre Ocupado Mujer Hombre

Pirámide de Población 1986 - Población Ocupada 1986 (C.A.V)

-100000 -80000 -60000 -40000 -20000 0 20000 40000 60000 80000 100000

0-5 5-10

10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 >=75

Mujer Ocupada Hombre Ocupado Mujer Hombre

Pirámide de Población 1996 - Población Ocupada 1996 (C.A.V)

-100000 -80000 -60000 -40000 -20000 0 20000 40000 60000 80000 100000

0-5 5-10

10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75

>=75

Mujer Ocupada Hombre Ocupado Mujer Hombre

Pirámide de Población 2001 - Población Ocupada 2001 (C.A.V)

-100000 -80000 -60000 -40000 -20000 0 20000 40000 60000 80000 100000

0-5 5-10

10-15

15-20 20-25 25-30 30-35 35-40

40-45 45-50 50-55 55-60 60-65

65-70 70-75 >=75

Mujer Ocupada Hombre Ocupado Mujer Hombre

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Pirámide de Población 1991 - Población Ocupada 1991 (C.A.V)

-100000 -80000 -60000 -40000 -20000 0 20000 40000 60000 80000 100000

0-5 5-10

10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75

>=75

Mujer Ocupada Hombre Ocupado Mujer Hombre

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Demographics

� Is age a good predictor for:

� Real estate?

� Transit use?

� Use of hard drugs?

� If age is a good predictor,

then:

� Establish number of

people in each age group

� Define probability for

each age group, of participation in a

given behavior or activity

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A 19 yr old has little money but plenty of time to wait for the bus

From:Boom, Bust and Echo by Prof Foot

Average Daily Trips per Person, Greater Toronto Area

0.00

Age5-9 15-19

Note: Statistics are for 1986.

20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70+10-14

1.00

1.50

2.00

2.50

0.50

TransitDrive

Figure by MIT OCW.

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Urban Transportation Planning – Fall 2006

Demographics

� According to Professor David K. Foot (“Boom, Bust and Echo”), future scenarios entail some certainty: In 10 yrs, we will all be 10 yrs older

� Demographics, not only predictable, but inevitable: The most powerful, yet underutilized tool, to understand the past and foretell the future

� Age is a good predictor of behavior… and therefore, a good forecasting tool

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Page 16: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Communication Tools

� Transportation Policy depends to a great extent on two-way communications:� Policy analysts ÕÖ elected officials� Elected officials ÕÖ other politicians� Elected officials ÕÖ mass media� Public at large ÕÖ elected officials� …………………. ÕÖ ………………….

� But impact of a message is based on: � words (7%), � how words are said (38%), and, � non verbal clues (55%)

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Page 17: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Communication Tools

learned used taught

Listening 1st Most (45%)

Least

Speaking 2nd Next most (30%)

Next least

Reading 3rd Next least (16%)

Next most

Writing 4th Least (9%) Most

Workshop 1 Listening Courses? Toastmasters? Speed reading?… 17

Page 18: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Communication Tools

“The Visual Display of Quantitative Information” by Edward R. Tufte plus the two follow-up books – a must-read reference

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Page 19: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Communication Tools

How Do you Visualize Change??? Remember that simulations could be critical

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Page 20: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Other tools of the trade

� Creativity: Lateral thinking, to think-out-of-the-box, thinkertoys…

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Page 21: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Out-of-the-box thinkers

� Edward de Bono: � Thinking Tools � Six thinking hats � Lateral Thinking

� Michael Michalko: � Cracking Creativity � ThinkerToys

� Many others

� The intelligence trap � The Everest effect � Plus.Minus.Interesting. � C.A.F. consider all factors � O.P.V. Other people view � To look for Alternatives –

beyond the obvious � Analyze Consequences � Problem Solving and Lateral

Thinking � Provocations

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Page 22: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mindmapping

See “MindMapping” by Tony Buzan et al

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Page 23: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mindmapping

� You see what you know and where the gaps are

� Clears your mind of mental clutter

� It works well for group brainstorming

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Page 24: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mindmapping

� A whole-brain alternative to linear thinking

� Retain both the overall picture and the details

� Promote associations

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Page 25: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mindmapping

� You see what you know and where the gaps are

� Clears your mind of mental clutter

� It works well for group brainstorming

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Page 26: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mindmapping

� Let us do a joint MindMap

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Page 27: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mind-Mapping

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Page 28: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mind-Mapping

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Page 29: Scenarios, Communication, Mindmaps Scenarios, Communication, Mindmaps … Urban Transportation Planning MIT Course 1.252j/11.540j Fall 2006 Mikel Murga, MIT Lecturer and Research Associate

Urban Transportation Planning – Fall 2006

Mind-Mapping www.mindjet.com

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