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Collaboration is an everyday practice that many people find to be a frustrating, even exhausting, experience. How to Make Collaboration Work provides a remedy: five principles of collaboration that have been tested and refined in organizations throughout the world. Author David Straus shows that these methods can help any group make better decisions and function more effectively. The five principles are: Involve the Relevant Stakeholders, Build Consensus Phase by Phase, Design a Process Map, Designate a Process ...
Collaboration is an everyday practice that many people find to be a frustrating, even exhausting, experience. How to Make Collaboration Work provides a remedy: five principles of collaboration that have been tested and refined in organizations throughout the world. Author David Straus shows that these methods can help any group make better decisions and function more effectively. The five principles are: Involve the Relevant Stakeholders, Build Consensus Phase by Phase, Design a Process Map, Designate a Process Facilitator, and Harness the Power of Group Memory. Each principle addresses the specific challenges people face when trying to work collaboratively, and each can be applied to any problem-solving scenario.
In 1965, I entered the architecture program at Harvard Graduate School of Design (HGSD). The basic method of teaching design at HGSD, it turned out, was to assign students to design a certain type of building or space and then critique the designs. The critiques were very formal and were modeled after the process an architect might go through in trying to sell an idea to a potential client. The students presented their designs to a panel of faculty members and professional architects. During these critiques, and during class, there was little discussion of the creative process—of how we came up with the designs. In fact, there was no accepted language to discuss design methodologies at all. Instead, the professors were mainly interested in the content of our designs.
About halfway through my first year, I began to think something was wrong with my eyes. The drawings on my drafting board looked blurred. I had trouble reading. Panicked, I made an appointment with a recommended optometrist.
After examining my eyes, the doctor led me into his office, motioned for me to sit in a comfortable chair, and then posed one of the most insightful questions I've ever been asked. "Your eyes are fine," he said. "What is it that you don't want to see?"
I suddenly realized what it was that I didn't want to see, that I was unconsciously denying. Even though I was paying for a graduate education in architecture, no one was going to teach me explicitly how to design. No one was going to identify and make visible the mental processes of design.
This flash of insight marked, for me, the beginning of my own process awareness. This moment was the first step in my lifelong journey to uncover and demystify the processes of individual and group problem-solving, and to transfer these concepts and tools to others.
In this chapter, I hope to shed some light on how individuals solve problems. This information is fundamental to an understanding of collaboration—of how individuals solve problems together. It's simply not possible to practice collaborative problem solving effectively if you have no understanding of human problem solving in general. This chapter is a bit heavier on theory than the other chapters in the book, because it serves as a basis for all that follows. To make it as accessible as possible, I use the story of my own experience discovering these concepts and learning their relevance to collaborative action.
In the Introduction, I defined collaborative problem solving as "the process people employ when working together in a group, organization, or community to plan, create, solve problems, and make decisions." I also talked about what I meant by collaboration. Here, I want to say more about the problem solving part of the term.
For some people, a problem implies something bad, a situation to avoid. In certain contexts, to focus on problems is seen as attending to the negative, the pathological. So some people substitute the word opportunity to emphasize the positive, to look at things on the bright side or to look at the possibilities of the future. But opportunity solving and opportunity finding are clumsy substitutes for problem solving, and there is already a whole literature on creative problem solving, so I'm going to continue to use the word problem in this book.
In any case, I don't view problems as negative. I define a problem as "a situation that someone wants to change." Problem solving, therefore, in its most general sense, is situation changing or taking action. It includes most of what we do all day long: communicating, learning, planning, working, and making decisions. At work, for example, you may need to make hiring and firing decisions, communicate with employees, fix quality-control problems, sell your products, and so forth. I would call all of these activities problems, since they are all situations you need to change—things you need to do something about.
These situations need not be bad. They include positive situations that you may want to reinforce or increase, like supporting employees to continue their education by offering matching funds to attend training programs. Creating a vision for your organization is also a problem-solving activity just as much as analyzing why the assembly line is causing defects in your products.
Also, under my definition, a problem is only a problem if there is an agent present—someone who cares and wants to take action. If you see your kids arguing and it doesn't bother you, you don't have a problem. Your kids may have a problem, but you don't.
Humans are designed for continual problem solving. If all stimuli are removed from a person's environment (as in an isolated prison cell), often that person will go mad. We are constantly making little changes in our environment, from shifting our sitting position to planning for the future. In this book, then, problem solving will refer to all the cognitive processes directed to purposeful action, from perceiving and innovating through planning and decision making.
My Intellectual Quest
Soon after the revelation that came during my eye exam, I set out to teach myself how to design—how to solve the design problems presented by my professors. I could find no useful books about how to design, and my professors were not very helpful. So I started keeping detailed design notebooks, in which I tried to track my own thought processes, to become more aware and at least "consciously incompetent" about the ways I was attacking a project. I found that when I tried a new design strategy, a different way of looking at a three-dimensional structure, I was suddenly able to do things I couldn't do before. For example, I learned how to draw a section perspective, which presents a "slice" through a building and a perspective of what you might see from that point. Through this drawing you see your design in a different way. I also learned how to build simple models out of Styrofoam blocks, with which I could arrange spaces in different ways without having to make new drawings.
In the design notebooks, I documented what I was thinking about when I was stumped, when I kept repeating the same mental process without success. Then, when I discovered another strategy from informal discussions with classmates or professors, I could consciously add it to my growing repertoire of design methodologies. I could also retrace my steps in my design notebooks and see how this new strategy might have helped me break fixation—how it might have served as a way out of a trap in which I had found myself.
I saw clearly that there was a relationship between the strategies I learned and my ability as a problem solver. Each design strategy provided a different way to attack an architectural problem, and the more I learned, the better a designer I became. And yet these strategies were not being explicitly taught.
To satisfy my own curiosity about design methodologies and problem solving, I began to audit courses at Harvard in cognitive psychology with professor Jerome Bruner. In these courses, I was introduced to the work of Allen Newell and Herbert A. Simon from Carnegie-Mellon University, as well as that of Ulrich Neisser.
Neisser (1967) was making a case for cognitive structures, or frameworks, about thinking processes. He maintained that it was possible to describe how you were solving a problem, and that it was helpful to do so. Without a framework to describe a subject, he said, it's hard to make distinctions and therefore to acquire and retain new information. For example, if you know nothing about general species of birds (e.g., flycatchers, warblers, wrens, thrushes), they all sort of look the same. When you see a small bird you have never seen before, you might not even know you've never seen it and you probably won't remember much about it. The same is true about problem solving. Without a language of process, without knowing something about the different strategies that can be used to solve problems, it is difficult to learn and acquire new ones.
There Is No One Right Way!
It was the work of Newell and Simon that provided me with the biggest "aha" of that time, however—one that was to guide my work for years to come. Their writings brought out the simple but powerful fact that human problem solving is an educated trial-and-error process (1972). Put another way, there is no one right way to solve problems. We can use a variety of strategies, but none of them will guarantee success. Some of them may be more useful in certain types of situations. But there is no single right way. The implications of this realization are profound. Over the years, my colleagues and I used this understanding as the basis for developing approaches to, and teaching, collaborative problem solving.
Heuristic vs. Algorithmic Problem Solving
What Newell and Simon (1972) did was to clarify the differences between heuristic problem solving and algorithmic problem solving. To illustrate, take the example of trying to find a lost contact lens. The algorithmic approach to searching might involve getting on your hands and knees and systematically crawling back and forth across the floor, trying to cover every square inch. If the contact lens is on the floor as opposed to on the sofa or in your clothes, and if you are very sharp-eyed, you will find your lens this way. However, it may take a very long time. The heuristic approach is to try different strategies in succession. You might start with the common "where were you last" approach. Then you might try to retrace your movements, shake out your clothes, get down on your knees and scan the floor, or turn up the lights to see if you can catch a reflection off the missing lens. Usually one of these heuristic strategies will work quite well and save a great deal of time compared to the algorithmic approach. In short, a heuristic is a strategy that is flexible and quick but doesn't guarantee success, while an algorithm is an approach that is systematic, rigid, and time consuming, but will ultimately guarantee success.
Newell and Simon discovered a great deal about human problem solving by trying to program computers to solve problems that are reasonably easy for humans. To greatly simplify, Newell and Simon found that there were no simple algorithms to deal with challenges like playing chess or recognizing a face. Such problems require heuristic strategies. What seems to characterize the human brain is our ability to think up heuristics and to be flexible and creative in our application of them.
Take, for example, the anagram of "TABLAERY," in which the challenge is to rearrange the letters so that they spell an English word. The algorithmic approach would be to try every combination of letters and test each to see if it is a word. There are 20,160 possible combinations of the letters, so at a rate of one new combination every ten seconds, it would take you up to fifty-six hours to find a solution this way. Using a heuristic approach, however, many people can come up with an answer in fifteen or twenty minutes. Take a moment and play with the problem, noticing what you do. Notice that you try different ways to solve it, different heuristics. Most people try, for example, rearranging the letters by consonants and vowels, looking for smaller words on which to build, avoiding letter combinations that aren't used in English, and even writing each letter on a separate piece of paper and physically rearranging them. Each of these heuristic strategies may lead you to a solution, but none of them will guarantee success. (See page 33 for the solution—but only after you've tried several heuristics!)
A Simple Model of Human Problem Solving
So Newell and Simon demonstrated that human problem solving is a trial-and-error process involving choosing a heuristic strategy, testing it, and, if it doesn't work, choosing another. This heuristic cycle is illustrated by the model in Figure 2.
The problem-solving cycle begins with what we call a strategic moment—that familiar point in time at which whatever you have been trying isn't working anymore. For example, in your search for your contact lens, you may try shaking out your clothes to see if the lens might be caught in the cuffs of your pants. If nothing falls out, you have to try something else. This is the moment at which you consult the repertoire of strategies you have learned, pick one, and implement it. Perhaps, for example, you decide to simply vary the implementation of your current heuristic (e.g., shake out your shirt rather than your pant cuffs), or you may change your approach and select a new strategy. Based on the results, the feedback from your efforts, you evaluate the success or failure of your trial and then you are back to another strategic moment.
This cycle of action/reaction usually happens so quickly that we're not aware of it. It's when we get stuck in a strategic moment that it's helpful to be able to assume conscious control of our problem solving. This is especially true in a group problem-solving situation, as we will see.
So, the great fact I learned in graduate school is that human problem solving is fundamentally a trial-and-error process employing heuristic strategies. There is no one right way. There are no simple algorithms for dealing with most of the open-ended problems we face every day. However, as I was soon to learn, there is a set of very useful heuristics that can be employed.
A Limited Set of Problem-Solving Heuristics
My own search for heuristics led me to the University of California at Berkeley during my thesis year (1968–69), while I was still registered at the Harvard Graduate School of Design. At this time, the School of Environmental Design at UC Berkeley was a world center for the study of design methodology—of how architects design. Berkeley professor Sim Van der Ryn had received a grant from the National Institute of Mental Health to review the literature on design methodology and try to make some sense of it. He hired me to assist him. It was a perfect opportunity for me to pursue my interest in human problem solving.
I began my research by asking some of Van der Ryn's renowned colleagues to share with me their different design tools. To my surprise, they strongly resisted getting involved in my project. Each of them was sure that he or she had discovered the right approach to design and was not interested in exploring the full range of design methods. So I turned to other sources, reviewing the literature and interviewing researchers from a variety of fields who were exploring the nature of human problem solving.
I began to make a list of the problem-solving methods I uncovered. I discovered that thinkers from very different fields often used essentially the same methods, although they sometimes used different terminology to describe these methods. Indeed, similar methods kept cropping up over and over. I realized that any given problem-solving method could be applied to many different contexts. For example, brainstorming, a common way of generating ideas, can be applied to different problems in many different fields. You can brainstorm ideas for creating an ad campaign or solving a calculus problem or finding a place to have dinner.
Like most problem-solving methods, brainstorming involves multiple steps—multiple heuristics. Brainstorming involves, first, purging or expressing out loud all the ideas that come into your head; then listing or recording them on a sheet of paper; and, at the same time, deferring evaluation, or not judging them until later. Brainstorming and other problem-solving methods, then, can be understood as "molecules" made up of smaller "atoms." These atoms, or heuristics, can be used by themselves or recombined into many other methods.
Excerpted from HOW TO MAKE COLLABORATION WORK by DAVID STRAUS Copyright © 2002 by David Straus . Excerpted by permission of Berrett-Koehler Publishers, Inc.. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
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|Introduction: The Power of Collaborative Action||1|
|Pt. I||The Fundamentals||15|
|1||The Process of Human Problem Solving||17|
|Pt. II||The Principles of Collaboration||35|
|2||Involve the Relevant Stakeholders||37|
|3||Build Consensus Phase by Phase||57|
|4||Design a Process Map||81|
|5||Designate a Process Facilitator||107|
|6||Harness the Power of Group Memory||129|
|Pt. III||Putting It All Together||143|
|10||Where to Go from Here||205|
|About Interaction Associates||230|
|About the Interaction Institute for Social Change||231|
|About the Author||247|
Posted October 30, 2004