The Art (and Science?) of Designing Urban Planning Processes

In June I published an op-ed in the Detroit News describing my research on urban renewal in Detroit in the 1940s. I concluded with the observation:

The voices of citizens affected by renewal must be heard. Dramatic, large-scale projects can have harmful and unexpected consequences. The history of urban planning has shown success occurs through a careful process of building consensus, detailed analysis and cooperative action.

In response Marja Winters, the city’s deputy director of planning and development, wrote an editorial arguing the process has been highly participatory, involving 28 city-wide meetings and 10,000 citizens, and large numbers of participants said they agreed they had had the opportunity to share ideas and opinions.

(As an aside: She objected to a line which read “The plan calls for closing neighborhoods, cutting services and cultivating new industries.” I agree with her criticism: the words aren’t mine, but those of a Detroit News editor. The manuscript I submitted read: “The Detroit Works Project — Mayor Bing’s roadmap for the city’s future — has proposed dramatic solutions: closing neighborhoods, cutting services, and cultivating new industries.”)

I have not attended the Detroit Works public meetings or examined the process, so I cannot critique it in detail. The first major policy initiative coming out of the process was announced in July, but amounted to the selection of some priority areas for city services. The proposal left some puzzled. Where was the grand vision, or bold proposals? Perhaps there is no need for “planning” at all, just better urban management? (See “Questions dog Detroit Works plan: Advocates want to see long-term strategy“)

This situation and Winters’ article raises interesting questions: is all participation alike? Can the design of the process affect the outcome? What models exist for planning for “shrinking cities”?

It is common for major urban plans or policies to be developed through quite elaborate processes. For example, I collected this diagram that was circulated in the early stages of the Imagine Austin Comprehensive Plan:

In general, their design is left up to professionals who draw upon professional experience. Most process designs characterize several aspects: problem definition, deliberation and participation, analysis, policy design, and decision-making. Under each of these, details include:
- The number, type, mission, membership and missions of committees
- What expertise and analysis is required, and how they are involved
- The timing, nature, and purpose of broader participation such as meetings, surveys, and online engagement
- How decisions will be made.

One of the cleares descriptions of how processes are designed for local contexts comes from Barbara Faga’s book Designing Public Consensus. After several case studies, the book presents the following public process plan as a starting point:

This way of thinking is not unique to urban planning. As the field of risk assessment has become embroiled in value-laden controversies, experts have had to re-assess their approached. In 1996, leaders in the field proposed an analytic-deliberative model that seeks to tightly link the needed analysis with involvement from affected parties.

Perhaps the most common process theory for large-scale planning is scenario planning (PDF), adopted from methodologies invented by the private sector for corporate planning. Although providing guidance for how thoughtful “scenarios” can be used to consider options for the future, scenario planning’s participatory logic is underdeveloped.

The crowning achievement of process thinking in public policy may be the consensus building approach (CBA), a method for resolving dilemmas often associated with Larry Susskind, a MIT professor of urban studies and planning. This negotiation methodology has strict requirements for the nature of the problems where it can be applied, how stakeholders are identified and included, and how negotiation should move forward. However it’s not clear how this approach — designed to intervene in acrimonious public debates about clear problems or decisions — applies to the problem of urban planning.

If there is an art to process design, can there be a science? It is rarely studied for a variety of reasons. First is the argument that process doesn’t matter. It could be that the outcome is the same regardless of what is done, or the real decisions that matter are being made elsewhere — by powerful elected officials or market actors. Second, from a social science perspective, studying them is maddeningly difficult. There are too many confounding variables and no clear to measure. What would you measure, and how? For this reason there are many descriptive case studies that steer clear of specific details. Lastly, analyzing processes requires a different form of knowledge than found in most research. Instead of theory that describes reality, we need a theory of what would happen given a certain sequence of events or actions.

Theory aside, how do you plan for Detroit? A good process would focus first on the goal. What is the “problem” in Detroit, anyway? It could be too much land, too few jobs, high crime, or a lack of revenue for government services. Although they are related, tackling any one means clarifying what the priorities are.

The most direct case for Detroit is the Youngstown 2010 project in Youngstown, Ohio. This process involved large-scale participation and a vision and plan adopted by the city council which anticipates significant changes to accommodate a permanently reduced population. Here is the process diagram from Faga’s book:

Where Detroit Works — or any other large-scale planning in Detroit — should go depends on what the local stakeholders seek to accomplish. Although any process must be locally tailored, the process designers aren’t starting from scratch. The models described above can be used to design a process that reflects both values and practical needs to involve the public, detailed analysis, and come to agreement on a solution to public problems.

‘Cybernetics in City Hall’ and the Challenge of Real-Time Urban Management

Periodically I come across an old article that seems very relevant to the present, such as the article about public sector innovation I posted in January.

The ongoing expanded use — and declining cost — of sensors and computing technologies has sparked a renewed interest in using them to solve persistent urban problems. A similar wave of interest occurred during the early history of digital computing. In his influential 1950 book, Norbert Wiener popularized the term “cybernetics” to refer to the emerging science of communication and control of organized systems. If the city is an organized system, then cybernetics in city hall would involve creating information feedback loops to be used by the manager (or “actuator”) to minimize the effects of disturbances and maximize achievement of urban goals. Sound familiar? It should: IBM inked a multimillion dollar deal to open a real-time “public information management center” in Rio de Janeiro (right) as part of their smarter cities initiative, and Wired magazine is keeping up a drumbeat about the power of feedback loops.

In an astute article published in Science in 1970, E.S. Savas considered the challenges this approach might face in the real world of New York City government. I don’t doubt the importance of real-time control for management tasks like transportation system management and emergency response, but the article describes some important challenges such a system would face if applied more broadly. Savas described how the five elements of the cybernetic loop would play out in the city: (1) dynamics of urban government, (2) information system, (3) administration, (4) goal setting, and (5) disturbances.

1. Dynamics of city government: The election cycle faced by big city mayors would limit the range of solutions considered, resulting in smaller goals and visible acts, which “may be more symbolic than effective.” Government itself is very slow-moving and one solution — delegating power — may have unintended consequences.

2. Information system: Arguably today much more information is available than was in 1970 about what’s happening in the city. But another crucial input is as tricky as ever — gauging the will of the people.

3. Administration: Making a decision is one thing, but implementing it requires an administration with appropriate personnel and structure, a well-known weakness of big-city bureaucracies.

4. Structure of government: Not only are city governments organized in anachronistic ways, the article omits another key fact: the fragmentation of powers. In Boston, for example, in addition to municipal fragmentation itself, separate entities manage many utilities, the transit system, parks, etc.

4. Goal setting: Identifying a common set of goals may be impossible. The chief executive can use judgement, but it is for good reason that power is delegated to elaborate systems of commissions, boards, and advisers on many topics.

5. Disturbances: These are unpredictable, often external to the city, and often not visible to the public (who sets the goals) until it is too late to prevent their impact. (e.g., climate change)

There are, in general, two responses to most of these concerns. Savas himself took one approach: give up on city government and advocate for privatization of service delivery. Presumably the cold logic of the profit motive would sweep away administrative, regulatory, and decision-making quirks of city governments. The other approach is to attempt to reform the government. In fact, IBM staff have admitted the “challenges” that will face a contemporary agenda for cybernetics. I think the need for contemporary urban government reorganization and reform is acute in many cities, but interest in it seems limited.

Notably, neither of these approaches truly addresses the challenges posed by the short time-horizon of elected officials, difficulty setting goals or forming consensus, and unpredictable disturbances. These three point to the need for planning to solve urban problems: a multi-stakeholder process involving analysis, deliberation, and solution design that both forges a consensus about the definition of a public problem and crafts a desired solution. It seems to me that in the face of the enormity of the challenges we face we need both smart planning and an efficiency-driven smart cities movement willing to push for reform but respectful of democratic systems.

> E.S. Savas in Science magazine, 1970: “Cybernetics in City Hall“

Back to the Future for Modeling Urban Systems: Research Mirage or New Frontier?

In June I took the general exams for my PhD program, which involved a one-week written and oral test on topics related to my chosen fields — urban information systems and democratic land use planning. This means over the past year I’ve plowed through much of the literature on urban modeling from the 1950s to the present day. As a result, I’ve been feeling acute déjà vu reading about the latest efforts by IBM and others to model “smart” cities, presented as a new frontier for cities devoid of any previous research.

For example, here is a description of an IBM project announced this week:

This problem–if you can’t measure it, you can’t manage it–combined with the impulse to improve cities by models, is driving both IBM’s “smarter city” strategy and the nascent “urban systems” movement, which seek to apply complexity science to cities. IBM … today announced the latest plank in its smarter city platform: an “app” containing 3,000 equations which collectively seek to model cities’ emergent behavior. IBM also revealed its first customer, the City of Portland, Oregon. Systems Dynamics for Smarter Cities, as the app is called, tries to quantify the cause-and-effect relationships between seemingly uncorrelated urban phenomena. What’s the connection, for example, between public transit fares and high school graduation rates? Or obesity rates and carbon emissions? To find out, simply round up experts to hash out the linkages, translate them into algorithms, and upload enough historical data to populate the model.

Here is a description of Jay Forrester’s 1969 book Urban Dynamics. (A MIT professor emeritus, Forrester is known as the founder of System Dynamics.)

In this controversial book, Jay Forrester presents a computer model describing the major internal forces controlling the balance of population, housing, and industry within an urban area. He then simulates the life cycle of a city and predicts the impact of proposed remedies on the system. Startling in its conclusions, this book became the basis of a major research effort that has influenced many government urban-policy decisions.

The contemporary smarter cities discourse seemed to start as merely a marketing ploy, but recently its proponents have sought a more substantial foundation. Although maybe there is more under the surface, so far all I have seen is warmed-over systems modeling or system optimization of the type invented in the 1950s and 1960s. If the promoters of these methods hope for contemporary relevance they must explain why — and how — the severe challenges these approaches face in a democratic society can be overcome.

Perhaps the most well-known article in this field is Douglass Lee’s 1973 article “Requiem for Large-scale Models” (PDF) where Lee, then a freshly minted Berkeley PhD, laid out the “seven sins” of the early generation of large-scale models (which included Forresters’ urban dynamics model): hypercomprehensiveness, grossness, hungriness, wrongheadedness, complicatedness, mechanicalness, and expensiveness. Importantly, he described desirable characteristics for city models:

• Transparency (“‘Black-box’ models will never have an impact on policy other than possibly through mystique, and this will be short lived and self-defeating.”)
• Balance between theory, objectivity, and intuition (“large-scale modeling has been significantly lacking in theory”)
• Start with a particular policy problem that needs solving, not a methodology that needs applying
• Build only very simple models

These recommendations reflect two fundamental differences between cities and other complex systems: randomness and democracy. These underlying theoretical challenges face any would-be urban modeler, from hacktivist to corporate consultant, engaged in the “battle for control of smart cities,” described by Anthony Townsend in a 2010 report and in his forthcoming book.

Urban systems aren’t just complex systems, they’re highly random ones subject to internal and exogenous shocks almost impossible to model, let alone predict. (e.g., gas prices, hurricanes, Justin Bieber concerts, etc) Most concerning, contradictory theories describe these models’ most most important variable, human behavior. These theories all have limited explanatory power but some validity, e.g., economics’ utility maximization and sociology’s social norms.

Secondly, the promise of urban optimization must be reconciled with democratic government. IBM has been running ads where the their employees boast of all the good things they are doing — tracking food for safety or reducing crime. Every time I see them, I think about priorities and trade-offs. Who decided these were the right priorities for resources? Individually they are achieving laudable goals, but they can only be judged in context. Only a democratically legitimate government can determine whether money is well spent on a food or crime tracking systems, versus other pressing concerns like education, health care, and infrastructure.

This post is not a critique of using data and analytical methods for urban policy. To the contrary, I think they’re as needed as ever and have been working with MAPC on a scenario modeling platform. There very well may be analytical innovations, like cellular automata, genetic algorithms, or complexity theories, which could be applied to create useful urban models. However new technology and new buzzwords does not eliminate the long-running theoretical and practical challenges of using models to improve urban life, or the importance of learning from history.

How Should Detroit Plan for the Future?

The Detroit News published an op-ed I wrote about lessons learned about urban renewal from my undergraduate thesis.

Detroit is facing big problems: declining population, budget deficits and a stagnant economy.

Discussions about fixing the city has generated dramatic ideas, including the Detroit Works Project — Mayor Bing’s roadmap for the city’s future. The plan calls for closing neighborhoods, cutting services and cultivating new industries. But even with the best of intentions, if city leaders don’t learn from the city’s urban renewal mistakes of the past, Detroit will be doomed to repeat them.

Although Detroit’s population has declined by more than 1.3 million since 1950, the problems of how to make tough decisions remain unchanged.

The Detroit News: “Citizens Need Voice in Renewal“Detroit_News_RGoodspeed

New ‘Planning and Technology Today’ Out for APA Conference

The Spring issue of the newsletter of the the Technology Division of the American Planning Association, which I edit, was just published. The issue was timed to coincide with the American Planning Association conference here in Boston next week. The issue includes articles on the following topics:

• Technology-related sessions at the APA conference
• Social media and local food systems
• A new measure of housing affordability by Chicago’s Center for Neighborhood Technology
• Urban planners and open data

Or, read the entire issue in PDF format.

Urban Planning as Computer Game in Boston’s Chinatown

Computer games like Sim City and Grand Theft Auto feature expansive, photorealistic urban environments and compelling storylines that engross players for hours. In contrast, public meetings about planning issues feature dry, technical information presented through static presentations and reports. It’s little wonder these meetings generally attract the “usual suspects,” with the skills and patience to digest complex data and follow the arcane legalize of local planning.

A new interactive game about Boston’s Chinatown neighborhood seeks to merge the interactivity of games with the real problems of planning. Why shouldn’t games reflect realistic challenges, such as finding housing, jobs, and places to hang out in the city? Can a game both solicit community input and provoke inter-generational dialog? The game, called Participatory Chinatown, is an exciting example of how new technology can do just this. Developed by the Asian Community Development Corporation, the Metropolitan Area Planning Council (my former employer, although I was not involved in this project), and Professor Eric Gordon and collaborators at Emerson College, the game as unveiled at two community meetings this week.

Participatory Chinatown has two iterations: an online single-player version, and a collaborative version that groups can play in real-time through networked computers. In each, the game’s 15 characters explore a 3D version of Chinatown, collecting information about opportunities and interacting with other players they find. At the end of the game, players must decide which choices best fill their quest for housing, jobs, or social spaces. Whether they succeed depends on how much information they are able to collect and how much competition exists. In a second phase, players can walk through one of three hypothetical redevelopment proposals for a part of the neighborhood, earning points for leaving comments about their opinions and concerns it provokes.

Integrating a community-created 3D environment, player profiles, and redevelopment scenarios, the project is notable for the close collaboration between community members, governments, and game creators it required. The quests illustrate the choices available in the neighborhood, and the obstacles — such as language barriers and limited income — residents face. At the demonstration exercise I attended on Wednesday, generational gaps were quickly apparent as the younger players most easily navigated the exercise while older players struggled with the game interface. The local youth who helped create the game were on hand to guide players through the exercise. Although not feasible for every neighborhood (it was partially funded by a $170,000 MacArthur Foundation grant), the game represents a tremendous resource for the neighborhood, especially when deployed strategically to stimulate conversation. In fact, much more than replacing the public meeting, the game meetings this week were successful partly because of the careful preparation and facilitation used to present the game and draw out comments after.

From a technical point of view, the game could become a flexible platform for other uses, such as more free-form exercises like exploring the visual effects of proposed developments. Already, some of the game’s 3D models are available for download through the Google 3D Warehouse. Although excellent at buildings, realistic traffic and street conditions were clearly missing. This makes it best suited for physical planning around buildings and public amenities, not discussing parking reform or “complete streets” philosophy.

Most importantly, the game presents planning decisions from the street-level view of community members, not the God’s eye view adopted by systems-optimization games like Sim City or Chevron’s Energyville. Although, like all games, Participatory Chinatown must contain simplifications and assumptions, it succeeds because it portrays planning in a realistic light: as complex trade-offs that can only be evaluated from the perspectives of specific urban residents. After all, there is no perfect urban form, and planning is the ongoing process of considering the future in the light of how well the current city serves our needs and reflects our values. If the game can help encourage this perspective in the community, it will be a success.

> Participatory Chinatown
> Globe: “Chinatown Planners Hope Game Draws Crowd” and editorial “Chinatown, the Video Game.

Is Urban Planning Dead?

At the American Planning Association National Conference in New Orleans a couple weeks back, I participated in a session on the provocative question: “is planning dead?” The event was organized by the staff of the Colorado-based organization PlaceMatters. A small group met to discuss the question at an “unconference” session near the convention center. They were kind enough to post a live blog and summary post about the event. I thought I’d take the opportunity to share a slightly more developed version of what I discussed.

First, in one sense, conventional planning is alive and well. U.S. cities continue to create and implement comprehensive plans and zoning regulations in the same ways they have since the advent of planning in the 1920s. There have been two notable changes. First, the size and complexity of plans and regulations has increased. As an example, the city of Austin, Texas has identified 67 plans, policies, and regulations adopted in the city since completing their last comprehensive plan in 1978. Secondly, although it’s not commonly recognized as part of planning, the historic preservation movement has had a tremendous impact on planning in urban areas. Preservation regulations are generally modeled on planning and zoning controls. New planning tools such as form-based codes, design review, inclusionary zoning, and other innovations share the same regulatory approach dating back to the 1920s, one that is rooted in the city’s “police powers” to create regulations for the health, safety, and welfare of the population.

Outside of this creeping expansion of proscriptive, regulatory planning, there have been alternative developments. Community development organizations and bottom-up initiatives have introduced new models of participatory planning. They should not be overlooked, but in most places city governments retain their central role in urban development. Although the process of creating plans has changed substantially, elected officials retain the final authority to modify or reject plans and development proposals. In its most advanced forms, the community development movement relies on government resources and permission to achieve their goals. (Cobbling together grants and subsidies, “pushing through” projects, etc)

Planning theorists have proposed several new models for the field, however none have significantly effected professional practice.

• Paul Davidoff’s concept of advocacy planning is still widely discussed and taught. He proposed planners should follow the approach of the legal profession, providing each community with resources to create their own plan. However, the model has many well-known criticisms. Who gets a planner, and how are they paid? How does the government decide which plan will prevail? How should large-scale investment decisions be made?
• John Friedman articulated a philosophy he referred to as “non-Euclidean” planning. He argued planning should be iterative, normative, creative, and based in social learning. Although this certainly describes some of the most innovative examples of planning, it is unclear how it could be followed to reform the role of government. Although containing provocative ideas, it requires further development and integration with a broader theory of governance before it can be readily applied.
• Finally, one of the most influential developments has been the ‘communicative turn’ advocated by a variety of planning theorists. Adopting the theories of Habermas, this group focuses on the work of planning as shaping views and collecting information through processes of dialog. It also forms the theoretical basis for the consensus building approach, where stakeholders are brought together to discuss contested policy issues. In their new book Planning With Complexity, Judith Innes and David Booher provide a comprehensive statement of this philosophy and attempt to integrate it with theories of governance. They advocate for an adaptive, collaborative, distributed, and nonlinear government. Just published earlier this year, it remains to be seen in what ways these ideas can be translated into concrete practices.

I think planning can take two — perhaps contradictory — directions.

First, planning can celebrate the dynamism of the private city. Under this scenario, the field would pull back from detailed plans and regulations, seeking ways to encourage private actors to produce the desired ends. The strategy need not concede to private interests, but would seek to make public benefits predictable, transparent, and simple. It would entail the courage to voluntarily limit what powers planners would exercise. In turn, governments would take an even bolder approach to the framework of urbanization: shaping streets, lots, infrastructure, and markets.

Second, planning could re-assert government’s role in shaping the city through empowerment, not regulation. Experiments in participatory governance and budgeting could point the way towards a future where governments function as miniature development states. In this context, planning would be focused on structuring processes to involve citizens and organizations in governance in new ways, and sparking entrepreneurship and innovation.

After the intellectual fall of the rational-comprehensive model of policy analysis, critics have often held the problem with planning lay with its methods. If planners didn’t posses any special skills or methods, the argument goes, what claim to legitimacy do they have? I argue this collapse of a sphere of professional authority unveiled a deeper, more fundamental crisis: of democratic legitimacy. Both of my “directions” share a critical evaluation of the legitimate power and structure of government. As a field embedded in structures of governance, planning cannot be reformed without a vision for a reformed and revitalized urban democracy.