Solve Problems Backwards
We took our four-year old grandson to play miniature golf. He swung at the ball, missed, and then, brilliantly, he bent down (holding his golf club in his left hand) picked up the ball in his right hand, carried the ball to the hole, and carefully dropped it in the cup. Problem solved! Was he teaching me something or was I failing to teach him? Planning goals or “missions” in the public interest are never clear or well-defined. In planning there are no rules, the solution “cup” keeps moving, there is no “par” or scorecard, and winning is indeterminate.
Don’t Keep It Simple
As a planner, even after you understand your client , the options, the context, and the goals to advocate, you still need to find a good solution. It is not magic. Many planners turn to the mythology of methods and look for the “best” method. Of course there is no such concept as the “best” method for complex, ill-defined planning problems. Planners may know a method or process from a prior place, project, or colleague. For many complex, ill-defined problems, that approach is just not effective..
Many observers will say “keep it simple”. Planning newcomers will start by asking questions like “what’s the zoning?” Whenever I hear comments about simplicity or zoning I want to scream. The so-called “KISS” motto (“Keep It Simple Stupid!”) leads, in planning, to stupidity, not wisdom. More often than not, oversimplification misdirects planners and usually leads to solving the wrong “simple” problem. Continued reliance on zoning perpetuates some of the worst practices and ideologies in planning.
Planners need to visualize what the end game actually looks like – it is much more than just a hole in the ground. In practice, when everything seems simple and well understood it often turns out that (a) there is no real problem or (b) the planning situation has been misconstrued seriously. Meaningful planning requires finding the places where issues are not clear or simple and where compromise is not self-evident. Another way to think about these situations is to view them from an emotional or non-rational viewpoint. If it feels like you are no longer working with a black and white situation, but it’s an ambiguous field of “gray” you are probably correct.
“…Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information? …”
T. S. Eliot, the Rock (1934)
Mazes, for fun, must begin at the entrance. For planners, however, the best way to start solving complex, ill-defined “mazes” is to imagine you are at the end of the maze – What do you see? What do you think? What is your immediate vision of the answer? Your mind is never a blank – there is always some idea of the solution. This is where planners should start – it is not where you end, but it is the basis for beginning the search for solutions, finding ideas during the process and refining ideas that improve which each new iteration. The best way to engage in this type of quick thinking, first thoughts, and broad search of initial vision is through community engagement in charrettes and group brainstorming. This is not the same task as “public participation” – it is problem-solving 101 and it usually results ideas that help planners move in the right direction. These images so the charette and brainstorming process with other planners, the general public, with large meetings, with small groups, with open conversations and with well-crafted preparations.
First, Skip Over Data
A well-known complaint of academics and researchers is that planners take action with a great deal of data — a circumstance that often induces a coma of self-confidence but very little knowledge about appropriate actions. The data itself becomes the obstacle. Planners become frozen or, even worse, they decide to pursue more data and become desperate to see relevance when there is none. At times I think the mass of data is like quicksand where planners thrash about trying to stay “on top” only to succumb to sinking faster and faster.
When this type of data flood occurs, there may be no reasonable solutions that seem apparent. At this point, the data frenzy should be stopped and planners need to find other ways to find a useful course of action. This line of reasoning has ultimately led to the concepts of facing “ill-defined” problems, in which there is no a priori test for a solution. Some writers have said that the problem-solving landscape is not just ill-defined and without any valid criteria for evaluating propose solutions but much worse. That is, many planning problems should be thought of as “wicked problems”, defined by C. West Churchman as “wicked” in the sense that solutions are not only ill-defined, but once implemented, actually make the problem worse than before. A case in point is the many planners, who, with the best of intentions and the best data, clearly defined urban renewal as a solution to slums, only to find that the new development was worse and that the displaced population groups were had lost any social cohesion as well as economic opportunity.
As yet, there have not been very effective methodologies identified for addressing these circumstances. One of the approaches – perhaps akin to “black box” methods – would be to hire planners with recognized talent and skill. That is, if we (a) admit that the problem appears intractable, (b) not susceptible to the application of known, achievable methods, and (c) not likely to be addressed by the gathering of more data, then (d) perhaps the answer is to identify those people who, for whatever reason, have apparently come closest to good solutions – or at least solutions that are better than most. Recognizing and defining such “talent” among planners is, in itself, a difficult task. Seeking talent may be wiser than seeking validity.
Planners should not bemoan a lack of data or spend resources on technologies that promise almost infinite data. Planners should use strategies that leverage talent and wisdom. Sometimes these strategies have apologetic names like “muddling through” or “disjointed incrementalism”. Sometimes the names of these strategies sound energizing like “brainstorming” or “charettes”. These are age-old approaches, honed before the industrial revolution, that have always worked when planners face the inevitability of making choices under conditions of extreme uncertainty. These strategies skip the data and begin with a visualization at the end of the maze – here is a solution, will it work, how can we get there?
The replacement of the Park East freeway corridor largely succeeded although there are parts of the solution which clearly could have been improved. While the implementation of the physical replacement of the freeway began with the demolition of the old one, this is not where the solution began – it began with hours of discussion looking at dozens of solutions and possibilities. These solutions were visualizations of the end of the maze. Once that solution was clear, the issue became working back to the beginning of the maze: what should be demolished? When the demolition pictured above began the lines of action that would link to new development had already been drawn, the regulations had already been approved, and investors had already begun to start their projects.
Find The End Of The Maze
But how do you find that first visualization? Perhaps it is a solution from another time or place. Such visualizations are not magic and they do not come from magical thinking or intuition. Visualizations in planning are self-conscious thoughts that come from the mind of the problem solvers. Visualizations can be innovative, but they are never without history. They cannot be ahistorical because they do not come from a blank mind. They come from a sum of experience and wisdom in the minds of individuals and teams – not from ignorance and naivete.
We began this downtown plan for Kenosha in 1990. Our first step was to look at the current downtown with open land (upper left) and then imagine an extended grid system (the end of the maze) which grew into the final plan (upper right). As we worked back and forth (from speculative solution to existing conditions) we also wove in concepts from Harland Bartholomew’s historic 1925 plan based on concepts from the City Beautiful movement. Since 1990 this plan has provided a framework for subsequent developments. All of the subsequent plans built on this start-up visualization.
We began this downtown plan for Kenosha in 1990 our first move was to look at the current downtown with open land (upper left) and imagine an extended grid system which grew into the plan (upper right). The extended grid was, in fact, the end of the maze. As we worked backwards to the current conditions we also quickly discovered Harland Bartholomew’s 1925 plan based on concepts from the City Beautiful movement,
In practice, acts of visualization are labeled with different names. When visualizations come from a team collaboration, the tasks might be labeled as “brainstorming”, “ charrettes”, or “workshops”. When the visualizations come from individuals, the tasks are sometimes named as “sketching”, “noodling”, “playing”, “interpreting”, “searching”. I have never heard a planner or designer say that they visualized a solution by “looking at data”. Staring at truckloads of numbers (AKA big data) may produce some sort of pleasant hypnotic trance but it does not induce a subconscious memory of an otherwise well-hidden solution. I often see this type of trance occur when planners look at market analyses and get numbed by numbers into a somewhat hypnotic state. It is addictive. Data abuse might be the methodological equivalent of substance abuse.
Don’t Measure A Mirage
The numbers, for a predictive analysis, usually cannot be challenged easily. The conclusions can and should be challenged – not as accurate arithmetic but through the lens of a visualization. If a visualization and a predictive data set do not fit with each other, both must be reevaluated.
How can we evaluate a visualized solution? This is when planners often hear someone say, “it’s not a solution because we can’t measure it”. An even more problematic answer occurs when someone says, “everything is measurable” and planners proceed to deconstruct a vision into components they know how to measure thereby missing the point of the visualization. We have all heard the parable of four blind men examining an elephant — one touches the tusk, another a leg, one pulls the tail and another feels the ear. In planning the same lack of vision is even worse because all analysts can see the big picture yet they refuse to acknowledge their lack of understanding.
A thin line separates visualizations and delusions. We must evaluate a visualization in terms of implementation but, at the same time, we should not try to measure a mirage that we hope is real but can never be created. The potential for “measurement” is not a criterion for solving ill-defined problems. If one answer becomes a mirage, we still need to look for other visualizations, not for other systems of measurement.
For planners, our first visualization is critical. Did we visualize a great solution to be tested or just a mediocre, or even poor solution. This is not the same as “trial and error” – it is closer to “trial and learn” or “trial and improvement”. Such reiteration becomes commonplace in many design projects where a physical plan gets revised. As some designers have said – that is why pencils come with erasers or more commonly why we have “Ctrl+z” on our keyboards. If you have never used “Ctrl+z”, you probably do not think critically. With the advent of AI erasure of visualizations may become even more critical and unfortunately less common.
Visualizing a solution and then finding reasons to support that solution is sometimes called “post-rationalization” – you find what you want and make up an analysis to support your conclusion. This is not the same as the intention of starting with a visualization of a solution. An imagined solution is a hypothesis that you try to prove and disprove – not in a highly rigorous sense (as discussed in philosophies of induction and scientific method) but in a pragmatic, time limited, sense of decision making. In practice planning does not provide enough time, resources, or certainty to investigate options. Here again, planners must rely on talent and wisdom – the second charrette or workshop become critical.
Revise Faster
In graduate school my classmates and I played an educational game (“Cornell Land Use Game”). Occasionally, as part of the game, some players acted as planners trying to advocate decisions in which the sum of all community benefits would increase. By the time the planners had a “good” plan the relentless flow of community growth outpaced their ideas – planners were always planning in hindsight, making good plans that were useless. Planners must recommend better ideas at a faster pace. The re-visualization of solutions must occur rapidly in real time.
For example, as soon as you question the cost of a hypothetical solution you will probably change the solution to make it less costly or more economically beneficial. As we question a solution’s popularity planners will probably change the solution again to make it slightly more popular – on and on.
This process of reiteration is not a post rationalization. It is a viable process that can avoid failure if it is done at a pace that matches local decision-making. I call this simply a “solution oriented” method as opposed to a “problem oriented” method.
In actual problem solving behavior, for the complex or even so-called “wicked” problems in planning, we move back and forth from one end of the process to the other end, over and over. This type of reiteration allows planners to imagine both the implementation of a solution and the actions that will lead to that solution.
New Berlin Wisconsin wanted an urbanized city center around the juncture of two major arterials – West National Avenue and Moorland Road. The area was filled with multiple private property owners and abutting neighbors who all had different visions of a desired future. The City Center plan began with a single, clear vision. However, it had to change at least ten times over the decades in response to market conditions, investor turnover, law suits, elected officials, planning and development staff, engineering issues, environmental impacts and so on. The images above, in no special order, show some of the changes that were made. At each step of the way, the plan needed to be reiterated. While the plan started with a clear idea (at the end of the maze) it needed to be modified as implementation worked its way back to existing conditions. Today, the City Center is a clearly defined, successful component of the City’s fabric.
Working our way backwards and forwards, from a solution to a starting point and then back again, is not an abstract analytic, or measurable task. This process is based on concrete, tangible and specific knowledge (which may, or may not, be measurable). It is not a test based on theory, method, model, concepts, public opinions, or data – all of which may become relevant but not as the primary basis for evaluating a possible solution.
The test of early visualizations must come from the reality of the conditions surrounding and underpinning the proposed solution. This type of testing is not as formulaic or rigorous as the concept of “due diligence” in which planners delve the details to confirm or disconfirm a proposed project. Instead, the test of early visualization might include phrases like: “it’s just going to cost too much”; “the council will never approve that”; “they tried this in another city, and it was a complete failure”.
Often the phrase “look and feel” may apply. Ironically, the phrase “look and feel” became popular the design of computers, websites, and digital activity – all endeavors also filled with measurements that matter. The evaluation of the early visualizations should be considered more like a scouting expedition – filled with solid know-how, reliable experience, skilled observation, and trustworthy opinions. How does the proposed solution “look and feel?”
Go Back To The Future
The process of evaluating and revising visualizations is the process of starting at the end of the maze and moving back to the beginning. To do this efficiently, planners must recognize mistakes, analyze them and find corrective actions quickly. The faster we can do this, the better.
The idea of “solving problems backwards” can also be interpreted as starting with the past, not the future. Put another way, before we innovated with something “new” we must go back in time and understand what is “old’. These four illustrations all show “new” concepts based on old ideas: upper left is a plan for Caledonia Wisconsin derived from many historic concepts championed by “new urbanism”’ upper right is a plan for a new subdivision in Germantown based on some of the historic concepts for Greendale, WI; lower left is a small grouping of town homes based on historic urban “terraced” housing; lower right is a view of an historic mixed use setting of housing and parkland for Davenport.
While I dislike most sports analogies, one of the valid aspects of such thinking concerns timing. Athletes do not have all the time they might want to make decisions. We even use timers in a chess match. Why? Because the use of time is our most valuable resource, and we cannot squander it investigating details unlikely to help us complete the game successfully. Every time that someone in my team investigates an issue I always ask myself “is it worth the time?” If planners can start at the end of the process with a reasonably satisfactory solution, then they will be spending their time the right way.
Topic Summary
Don’t Keep It Simple
First, Skip Over Data
Find The End Of The Maze
Don’t Measure A Mirage
Revise Faster
Go Back To The Future