The Crises of Democracy and Accountability in Planning, Design and Public Goods Decision Making
The Problem of Public Involvement in Public Goods Allocation
The increasing desire for public sector accountability on the part of taxpayers, and a desire on the part of public officials to open planning and design processes up to higher quality public input in many democratic societies, has created challenges for traditional, unstructured methods of public involvement. Particularly in large-scale and inevitably contentious public goods allocation questions, such as nuclear power station location, highway location, bridge design or transit system development, it is not sufficient to rely on estimates of public valuations nor can public involvement be suppressed or controlled. Such attempts at control lead to mistrust between civil leaders and those they represent. But it is widely agreed that handling large-scale public input into projects of this kind is challenging in the extreme. Better analytic systems are required. It is remarkable that so much money is spent on engineering optimizations and so little on advanced analytic research into more effective ways to gauge and improve quality of public involvement within legal, financial and engineering constraints.
What is Structured Public Involvement, or SPI?
Structured Public Involvement (SPI) is a public involvement and decision support framework developed in 1999 by Dr. Keiron Bailey of the University of Arizona and Dr. Ted Grossardt of the Kentucky Transportation Center. The aim of SPI is to increase stakeholder satisfaction with public goods decision making process and products in democratic societies. SPI features a strongly theorized approach to public involvement that integrates decision theory, facilitation and group process expertise, and advanced technologies such as visualization, GIS and electronic polling, into a collaborative decision support system.
Over the past ten years SPI protocols and their associated methods, Casewise Visual Evaluation (CAVE) and the Analytic Minimum Impedance Surface (AMIS), have been applied to a wide range of planning and design issues in collaboration with different stakeholder groups. These projects range in size from the $4.2 billion multi-State Ohio River Bridges project through regional interstate highway and electric power transmission line location all the way to neighborhood scale transit-oriented development and rural highway improvements.
What SPI does
Provides an analytic framework that allows public values to be better understood by professionals
Uses public and professional time more efficiently, resulting in less conflict
Allows professionals to generate solutions relevant to the community in question
Increases public satisfaction with process and product by handling public goods allocation in accord with the principles of a representative democracy – proven by large-scale, real-time, anonymous public satisfaction polling during the process.
Strengthens appreciation of democratic mechanisms for planning and risk allocation
What SPI does not do
Turn the complete design domain over to the public
Create more need for public involvement to solve problems created by poorly structured input
Force “consensus” in large-scale and contentious processes when this is practically unachievable
Allow individuals, either public demagogues or professionals with a predetermined “best” option, to dominate and shape outcomes in opposition to majorities
Eliminate all disagreement and objection to proposals
How does SPI work?
To apply SPI to a design or planning problem, the team forms an expert partnership with selected design professionals, such as civil engineers and landscape architects, under the direction of project sponsor such as a State Department of Transportation or a Corporation Commission. The team works with the professionals and sponsors to establish the framework within which public involvement should be conducted, and to exclude illegal, infeasible or unfundable design criteria from public consideration. Once this design envelope is established, the team then designs an SPI protocol to obtain useful information from the public. Typically we conduct a series of open public meetings at which valuations are gathered, or for design cases, feedback on visualizations or design options is obtained through real-time electronic polling. This information is then analyzed using our unique decision support systems, such as our Analytic Minimum Impedance Surface (AMIS) or Casewise Visual Evaluation (CAVE) methods, and the public evaluation is converted into planning or design guidance that can be interpreted by the relevant professionals. Iterative public feedback is then sought on detail designs and plans generated by this process.
SPI protocols demonstrate uniquely and consistently high levels of public satisfaction with the process. These evaluations are unique because they are obtained through anonymous real-time electronic polling at open public meetings. These evaluations are high because SPI is efficient in its use of participants’ and experts’ time and generates useful output with a minimum of conflict. It gives participants a real sense of inclusion as they literally see the design team responding to their input and incorporating their values into the product. SPI positions professionals, sponsors and the public in alliance on a design problem and helps produce truly context-sensitive solutions. SPI does not turn over control to the public, sell the public on a particular design, nor does it manipulate them into accepting options unsuitable for their communities.
Ongoing SPI projects include:
Collaborative nuclear power station location using GIS/multicriteria methods
Electric power transmission line corridor evaluation
Large bridge design using CAVE
Integrated transportation/land use modeling using CAVE
Context-sensitive highway design for safer operation
Impact of SPI
The most recent SPI project was awarded the Greg Herrington Award for Excellence in Visualization in Transportation at the TRB Annual Meeting this January. SPI findings have been published in a range of international peer-reviewed transportation, planning and decision analysis journals, such as the Transportation Research Record, Socio-Economic Planning Sciences, Geographic Information and Decision Analysis and Practicing Planner. SPI research has been funded by the National Science Foundation, Federal Transit Administration, Kentucky Transportation Cabinet, the Arizona Board of Regents and other organizations. SPI demonstrations have drawn high attendance and generated high impact at national and international conferences such as Transportation Research Board’s Annual Meeting, the Annual Meeting of the American Planning Association and CORP GeoMultimedia in Vienna.
For more on the pedigree of SPI, simply Google “Structured Public Involvement” and you will see some of the range of SPI work including publications, news, DoT press releases and other relevant information:
SPI Case Study: Large Bridge Design
The Louisville Southern Indiana Ohio River Bridges project, otherwise known as LSIORB, is the fifth largest publicly-funded infrastructure project currently underway in the United States. You can read more about this project at:
Dr. Ted Grossardt and I and our third team member John Ripy, and our partners from Michael Baker Associates, represented by Stephanie Brooks and John Dietrick, developed and applied a Structured Public Involvement protocol for this project. Like other SPI applications, this project has produced some remarkable results in terms of the quality of public input.
Over the last two years we worked with Indiana Department of Transportation and Kentucky Transportation Cabinet project managers and engineering partners at Michael Baker to develop the bridge design parameters that were available for public input. Infeasible design parameters were excluded. We then used our Structured Public Involvement protocol including electronic polling to gather data from hundreds of participants at open public meetings on both sides of the river. Our fuzzy logic method, called Casewise Visual Evaluation, was used to determine which combinations of design elements were most preferred by the respondents. Our engineering partners then created visualizations showing these preferred designs. As you may be aware, this process is much different than showing people three or four images and simply asking people which one they prefer. As a result of its CAVE typically results in much higher process satisfaction than other approaches.
The most significant project finding is that anonymous, real-time process evaluations by hundreds of participants at open public meetings yielded process satisfaction scores between 8.0 and 9.1 on a 10-point scale, where 1 is 'awful,' 5 is 'OK,' and 10 is 'wonderful.' The reasons for these very high process satisfaction ratings are that every design fits all technical, engineering and budgetary constraints, all designs are truly context-sensitive. People who attended the meetings saw how their feedback was incorporated into the final design candidates.
No other large structure design of this type has been handled in this way and no other large project has data from such a large number of participants validating the quality of the process. This project demonstrates how an analytic approach to public involvement can yield dividends especially in large, complex, potentially contested infrastructure design cases. The CAVE design support system is modular and can be applied to any design question that requires a component of visual evaluation. It has shown similar high performance when applied to noisewall design in humid and arid zones, landscaping of berms, rural highway improvement, and block-scale transit-oriented development in a low-income neighborhood in a wide range of contexts in states such as Arizona, Indiana, Kentucky and Ohio.
In an ongoing project we are using the CAVE method in conjunction with civil engineers to gauge driver response to highway design. The purpose of this is to investigate within the parameters specified by the AASHTO Green Book which highway design characteristics e.g. shoulder width, type, median type, fence type, height etc., influence driver operating speeds most strongly. Ultimately this research will generate context-sensitive designs that increase highway safety. With standard statistical approaches to this problem, a large number of samples is needed for reliable description. The fuzzy logic system we’ve developed, CAVE, requires less data and yields useful output with a small set of visualizations. This makes open public evaluation more practical and meaningful.
Collaborative nuclear plant remediation and power station location questions are being investigated by our team in collaboration with power engineering expert Dr. Ward Jewell of Wichita State University.
Authorities that have been skeptical of the capacity of SPI have been surprised and, in some cases astonished, by the efficiency of the protocols. Usually, based on poor previous experiences with public involvement, they at first have been reluctant to even allow our team to conduct this polling despite SPI’s remarkably consistent performance. Once they observe SPI in action, and see the results, they become enthusiastic proponents. More important, over the course of ten years of various SPI applications in the U.S., thousands of members of the public have repeatedly provided clear evidence of their high satisfaction with this way of gathering their input.
Citizens want better quality involvement in high-stakes decisions that affect them. They are tired of being patronized by unstructured public involvement, or worse, by architects, designers, engineers and project sponsors who desire to actively curtail legitimate expression of public values.
The following excuses/views are part of the problem, not the solution.
"It's too difficult." Why? If hundreds of citizens can participate in efficient, short, public meetings, providing useful quantitative data on their values and preferences that can be translated directly into planning or design guidance.
"It's more expensive." Than what? This argument is often hindered by the lack of hard data on how much public involvement costs. Hourly rates for public involvement specialists are buried in spreadsheets, or subcontracts, and worse, there's no accountability to measure the quality of involvement that this expenditure buys. Fast, efficient, processes such as SPI are a win-win for those who desire higher quality public involvement.
"The public are ignorant." See the Arnstein Gap. We've heard this statement, exactly as written here, from professional planners at conferences. This attitude perpetuates this gap and erodes credibility in democratic institutions. Whenever you hear this, call it out. Make those who believe this accountable for their processes.
We can, should, and must, do better. Performance metrics for public involvement are a necessity. Project sponsors and professionals should be held accountable for meaningful citizen inclusion in decisions that involve allocation of social risk or that require expenditure of public money.
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Copyright © 2009 Keiron Bailey