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Sprinting Past the NIMBY-Climate Impasse

Elite portions of the Bay Area (Palo Alto, Menlo Park, Pleasanton, and Marin County) adopt many leading-edge green policies but stumble when it comes to accommodating regional population growth. These areas fear the impacts of growth within their own boundaries and have difficulty empathizing with regional objectives. Their plodding multi-year comprehensive plan processes yield unimaginative results hampered by small and skewed public input.

“Design sprints” (week-long intensive problem-solving and brainstorming) and high-tech participatory democracy (a la California Lieutenant Governor Gavin Newsome’s book Citizenville) can shrink 48-month public processes down to one week, with more innovative outcomes, higher impact mitigation, richer quantitative analyses, and increased public participation, all at much lower cost.

Regional planning to protect the climate

In the past, states, regions, and cities passively experienced population growth without proactively shaping that growth. One-half of US states now have modest laws to reduce sprawl or promote infill development. The early outlier was Oregon’s 1973 law, that spurred impressive results in the Portland metro area. Maryland’s 1997 Smart Growth Areas Act (SGAA) spurred a wave of states to adopt regional smart growth policies, but these laws lacked an enforcement mechanism for cities. In 2011, Florida repealed their law. California may be starting another SGAA-sized wave, only this time with modest enforcement mechanisms.

In the past 20 years, California has gradually adopted commendable, if sometimes unpopular, planning policies to minimize GHG and traffic congestion.  The two main planks are: 1) maximize mixed-use transit village apartments/condos (to produce one-fourth the carbon footprint and driving of single family homes), and 2) add housing where there is a jobs imbalance. Taken together, these two planks reconfigure the geometry of human settlement patterns, minimizing the distance/energy between home, work, and activities. Compared to single family homes, apartments and condos reduce “housing square footage per person,” reducing household energy consumption. UC Berkeley research finds adding housing next to jobs is a very effective strategy to reduce driving.

California State Housing and Community Development Department created a process for regions to forecast population growth and allocate growth to cities. Every seven years, cities are required by law to update their Comprehensive Plans and Housing Elements to plan for that growth. Some cities view this process, the Regional Housing Needs Allocation, as a profane four-letter word: RHNA (pronounced “reena”). Local slow-growth advocates anonymously comment “RHNA is central planning authoritarianism run amok cloaked in the language of compassion” and “The next time someone calls you a NIMBY, you can call him a DUMBTWIG — Developer Undermining My Beautiful Town With Insatiable Greed.”

State Senate Bill SB375 strengthened RHNA by further linking land use to climate protection.  “Californians need to rethink how we design our communities.” Regions must “prepare a Sustainable Communities Strategy to reduce the amount of vehicle miles traveled and to demonstrate the region’s ability to attain its GHG reduction targets. Spending less time on the road is the single-most powerful way for California to reduce its carbon footprint.”

Specifically for Palo Alto, Palo Alto Weekly Editor Emeritus Jay Thorwaldson wrote a 1968 article on Palo Alto’s jobs/housing imbalance, with 2.4 jobs for every household in those days.  Jay’s comment on Palo Alto’s current jobs/housing imbalance:  “Well-intentioned and environmentally conscious Palo Alto has restricted housing to create a terrible environmental situation with long commutes wasting fuel.  It’s an insoluble situation.  Long commutes damage the social fabric and create lower quality of life.  Workers are forced to commute (77 miles) from Manteca, etc.  Palo Alto has a drawbridge mentality. Compounding the insolubility, objections raised by neighborhood associations are legitimate.”

The impasse is passionate and somewhat “religious” in nature. Both the pro regional climate protection and pro slow-growth sides perceive themselves as virtuous saviors battling the other side.

A comprehensive plan design sprint

City Comprehensive Plan updates to accommodate significant new residential growth are similar in complexity to algebraic systems of N equations (planning constraints) with N unknowns, requiring iterative calculations to generate optimized outcomes. Old-fashioned planning processes incorrectly compartmentalize analyses whereas modern processes treat planning scenarios holistically, allowing tradeoffs to be made between different planning variables. Modern processes can be characterized as “a massively parallel problem-solving supercomputer networking hundreds of human brains.”

In Citizenville, Gavin Newsome draws on his frustrations from his term as San Francisco’s Mayor. Within public processes, loud citizen voices drown out others. Feedback is monopolized by a small, passionate group of people with hours of free weeknight time to spend sitting through plodding public meetings. At these meetings, staff/electeds spend four times longer than normal to say half as much, in order to not to offend anyone. The views of the too-busy-to-attend silent majority are ignored in favor of more extreme views. Old-fashioned processes enable defensive, obstacle-seeking strategies, dampening problem-solving creativity.

According to Newsome, “new digital tools can dissolve political gridlock and transform democracy.” These tools address complex, messy, seemingly-intractable issues and augment citizen capacity to find ways through messy situations. Rapid-fire processes break down creative barriers.

According to Google Ventures Design Staff, “design sprints” produce predictably good results for startups and new products in only one week. Such sprints also promise to revolutionize city planning processes.  Envision an elite city such as Palo Alto holding an intensive sprint week with objectives: 1) Create one or more “maximally mitigated” scenarios to add 12,000 new housing units to Palo Alto’s existing 27,000 by 2030.  2) Quantify impacts on city budget, school district budget, traffic, spillover parking, real-estate market segments, affordable housing, public facilities needs, infrastructure needs, quality of life, and regional GHG/VMT.  3) After exhausting all potential innovations, analyze whether the resultant numbers add up to a feasible or infeasible scenario. Determine if the region’s request can be accommodated or quantify the shortfalls.

Given such objectives, a planning sprint flow is provided below:

Before the sprint: Prepare

Prime your citizenry for innovation-seeking creativity by showcasing best practices and radical new ideas from other cities. Partner with local media to spread the word. Generate buzz in advance of the sprint week.

Get the people and things you need. Assemble a sprint team composed of multiple disciplines and perspectives: City/school/regional staff, planning commissioners, academics, neighborhood association members, local architects, large real-estate interests, design professionals, etc. By far the key person is a strong facilitator who can guide the Loud Voices into productive contributions, converting their “show stopper objections” into “constraints for creative problem solving.”  Innovation-dampening voices (such as some City Attorneys) should not be allowed onto the team.

Develop cloud spreadsheets for sketch plan “what if” impact analysis. Share these spreadsheets with the public  Newsome urges greater transparency combined with pushing data to hackers.

Develop 3D SketchUp models for quick visualization of new apartments/condos of different heights in different locations.

Mass participation

At 7PM each day of the sprint, the team should quickly “report out” results to a live video stream, soliciting mass smartphone vote-back on key issues. The daily report out shall also be packaged for 8PM to 9AM interaction featuring a youtube of the report out, a web survey for additional vote-back, and social network discussion. The discussion should require registered, real-name users and should be moderated to ensure respectful, facts-seeking discourse. A staffer shall prepare a next-day 9AM team briefing on the overnight feedback, ensuring 24 productive hours in each sprint day.

Package up the most unsolvable problems and submit to worldwide “community of practice” forums, to maximize creative solution input.

Day 1: Understand

Dig into the planning problem through staff reports, review of best practices from other cities, and team input. The first step is to get all of this latent knowledge out of people’s heads and into a visual representation so everyone can understand the extent of the problem. Next, dive in and get to work. Day 1 success can be characterized as “citizens favoring slow growth agree that their concerns have been integrated as constraints-to-be-solved within the process.”

Day 2: Diverge

Rapidly develop as many solutions/scenarios as possible.

Day 3: Select and Prototype

Choose the best scenarios and hammer out a “2030 resident experience” story. Build something quick and dirty that can be shown to citizens/users: A) Translate scenarios into quantified impacts that are shared via cloud spreadsheets. B) Render scenarios into 3D model birds eye views.

Day 4: Validate

Show the scenarios to folks outside of the sprint team and probe about what works and what doesn’t work.

Day 5: Refine and re-validate

Week 2: Report to Planning Commission and Council

The next step

Problem-solving to address the constraints from the Loud Voices will produce transformative innovations. Such breakthroughs can only occur if an elite area agrees to undertake an innovation-seeking design sprint. Success of this planning sprint with motivate future sprints in other locations.

Crowd-sourced city planning examples

San Francisco Gray Area for the Arts’ (GAFFTA) September 2012 Urban Prototyping Festival (‘teams create replicable digital and physical urban interventions that explore new possibilities in public space. Every project produced is open source, publicly documented, and replicable in any city in the world.’) applied the ‘maker ethos’ to city planning.”

Using Futurescaper, a Swedish project examines important trends and issues facing the future of mobility in cities, combining social gaming with crowdsourcing to create collaborative futures scenarios.
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Calculations and references

Google Ventures Design Sprint: http://www.designstaff.org/articles/product-design-sprint-2012-10-02.html

Gavin Newsome’s Citizenville: http://citizenville.com/
A Guide to California’s SB 375, NRDC, June 2009, 32 pages. Includes chapters on Sustainable Communities Strategy and Regional Housing Needs Allocation.  http://www.nrdc.org/globalwarming/sb375/files/sb375.pdf

Smart growth: 1/4 the per capita energy consumption of single family homes:
http://www.cities21.org/HH_NRG_consumption.htm

A 2006 study by Robert Cervero and Michael Duncan of the University of California, Berkeley, concludes that locating housing next to jobs is the most effective strategy in reducing vehicle mileage (and generation of carbon dioxide). Their conclusions are detailed in an article, “Which Reduces Vehicle Travel More: Jobs-Housing Balance or Retail-Housing Mixing?” in the Autumn 2006 Journal of the American Planning Association.

Jerry Brown to Pleasanton: Housing and Climate Change Are Connected
http://transbayblog.com/2009/06/25/jerry-brown-to-pleasanton-housing-and-climate-change-are-connected/

Menlo Park settles housing lawsuit: City commits to updating plan, finding affordable housing sites. http://almanacnews.com/news/show_story.php?id=11251

Palo Alto Planning Commission Slams ABAG’s Initial Vision Scenario of adding 12,000 new households by 2035, without empathy for regional objectives. http://paloalto.patch.com/articles/planning-commission-slams-abags-initial-vision-scenario

ClimateOne Slams Palo Alto on Housing: http://www.cities21.org/cms/index.php?page=climateone-zings-palo-alto-on-housing.  Palo Alto is characterized as “murderous to future populations.”

Affordable housing is again a red flag in ‘green’ Marin County: The issue has long produced conflict in the eco-friendly county, California’s wealthiest. Officials are being urged to help workers find housing in a place where the median home price is $650,000. http://articles.latimes.com/2013/mar/31/local/la-me-affordable-marin-20130401 . “Marin is near the back of the pack in the nine-county Bay Area region when it comes to absorbing predicted population growth — and is the most unwilling, said Ezra Rapport, executive director of the Association of Bay Area Governments.”

Steve Raney

About the Author : Steve RaneySteve Raney heads Palo Alto-based Cities21, a smart mobility consultancy. Steve’s project history includes: Google self-driving cars, Ultra personal rapid transit (self-driving electric vehicles), smartphone instant ridesharing, smart parking, the US EPA’s "Transforming Office Parks into Transit Villages" study, BART’s Group Rapid Transit Study, and conceiving Bay Area MTC’s $33M Climate Innovations Grant Program. He is the author of 18 transportation papers. Steve holds three masters: business, software, and transportation from Columbia, RPI, and Berkeley.View all posts by Steve Raney

  1. Steve Raney
    Steve RaneyApril 22,13

    A comment from a professional designer:

    This sounds like a very interesting challenge to solve. I think that design sprints might be valuable to break through the impasse and get people to restructure their thinking.

    You might want to check out: http://www.helsinkidesignlab.org/ – “Helsinki Design Lab helps government leaders see the ‘architecture of problems.’ We assist decision-makers to view challenges from a big-picture perspective, and provide guidance toward more complete solutions that consider all aspects of a problem.”

    They cover strategic design cases where they basically try to solve problem similar to what you describe with creative methods. There’s a lot of info on the website as well as a downloadable book with background info, methodology, etc.

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