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a must-read for anyone interested in the world 2010-07-29

Reviewer: kp

for anyone interested in psychology, sociology, politics, economics, history, government...

Highly recommended! A good place to start building one's foundation in any of the above interests.

I gave it to my 15 years old son to read it. 2010-03-24

Reviewer: Azamat Abdymomunov

Great book written in 1989 by West German Professor Dorner. This is a good introduction into System dynamics and System thinking. The book gives several mental models of how people "attack" complex problems and why they often fail. Dorner describes several psychological experiments that help to differentiate "bad decision maker" form "good decision makers," as well as mental traps that lead to failures. Based on this analysis he presents his model of decomposition and planning. At the end of the book Dorner quotes Clausewitz that "...War is not an infinite mass of minor events... War consists rather of single, great, decisive actions, each of which needs to be handled individually." Such "strategic thinking" requires far greater expenditure of mental energy argues Dorner.

Dorner ends his book with the thought that "...If we cannot form a picture of a temporal configuration, we cannot adjust our thinking and actions to take that temporal pattern into account... We human being are creature of the present. But the world today must learn to think in temporal configuration."

The book is easy to read and comprehend. I gave it to my 15 years old son to read it. Hopefully he will use my advise to read it earlier in his life.

Necessary reading for aspiring planners 2009-12-30

Reviewer: N. Helmholdt

Any person working as a so-called "change agent" should read this book. In the 1980s, Dörner and other German researchers conducted experimental simulations to investigate how people handle complex tasks. In the same vein as SimCity or Civilization, these experiments put people in a leadership role where they could affect many variables. The simulations range from rural African tribes to English factory towns to ecological balancing acts. What Dietrich does not do is assemble a step-by-step approach to tackling complex problems. Instead, this book analyzes the multiple ways that individuals failed to anticipate problems, understand complex systems, and manage time throughout the process.

One area where this book shines is the detailed analysis of how people analyze complex models. Participants in the simulations described above were recorded as they interacted with the researchers. The common tactics that led to failure were an inability to address multiple issues simultaneously, assumption that success depends on a single variable, and willful ignorance of the effects of past decisions. By contrast, the successful participants created dynamic models of the simulation, constantly gathered information, and did not rely on reductive hypotheses.

The chapter on goal setting was surprisingly interesting. The taxonomy he uses for goals includes five dimensions and the complications inherit to goals on these spectrum. For instance, a _clear, specific, and positive_ goal might be predicated on a _general and implicit_ goal (in the case of a firm seeking to reduce its carbon footprint by 20% in 2 years the general, implicit goal is that it intends to fight climate change). Dörner does an excellent job of identifying the ways that goals can conflict with one another along with the various options that exist for addressing these conflicts.

The book is a thorough anatomy of the failure of human intelligence to grasp complexity and dynamic interactions. One silver lining, and optimistic touch is that practitioners (people working in project management) did better at the simulations than laymen. The most plausible critique that I see is that informal buffers to systemic failures exist in most situations. For example, if Herman Haworth is promoted to the role of Senior Planner for a town, it seems likely that his colleagues will assist him in identifying the best strategies from their past experiences. As any non-hermit clearly knows, groups can make terrible mistakes. (Dörner cites the case of Chernobyl where a team of nuclear scientists failed to realize the mistakes that led to a meltdown.) If I were teaching a course on planning theory I would make this book mandatory reading.

Computer simulations 2009-12-10

Reviewer: Kevin Dietz

At first I found the book interesting, but then I realized that i wasn't really offering up much in the way of solutions. The conclusions are sometimes contradictory and confusing. In one computer simulation experiment, the author concludes that, in general, the participants that made more decisions were more successful. In another similar experiment later, the participants that made fewer decisions were more successful. The author tries to explain why that finding might have been the case, but to me, the explanation wasn't all that satisfactory.

The book is based on the results of experiments with participants being asked to make decisions that determined the outcome of computer simulations. Participants who were best able to predict and control the simulations are branded as successes, and likewise, those who couldn't are failures. There are a couple of problems I saw with this approach:

First, the definition of success seemed ill-defined. In the Tanaland example in Chapter One, for example, anyone who create a rise in population followed by a decline in population is branded as a failure. In an attempt to improve living conditions, participants create overpopulation, which led to famines. The book claims that this should have been obvious, but participants couldn't predict the complex interaction of multiple, simulated variables, and thus failed. I wonder what would happen if the participants took no action at all? I think what may really be going on here is that the authors have set a trap for the participants, whereby an inherently unstable environment was created, and small changes to input variables created large, unstable swings in the output variables. The only person who succeeded in controlling the population made lots and lots of small corrections that would be impossible to implement in any real-world scenario. The simulation doesn't seem to have much bearing on real-life.

Second, as a computer scientist, I know from computer science theory that computer programs are inherently unpredictable. You can't, for example, write a computer program that will take as input another computer program, and produce as output a value of "true" or "false" as to whether the given computer program will ever finish running. This is famously known as the Halting Problem. If you want to know what happens in a simulated world after 10 simulated years, with a tsetse fly control program introduced in year 1, the only way to find the answer is to run the simulation for 10 years, with a tsetse fly control program introduced in year one. There are special cases where predictability is possible, but in the most general sense, the only way to know what a computer program will do is to run the computer program and see what it does.

The same thing is true of the real world. The future is inherently unpredictable. Want to know what will happen in 10 years? Wait 10 years, and you'll find out.

So in a sense, what the author is basically saying is "The reason why even really smart people can't predict the future is because the future can't be predicted."

A book that will make you wiser 2009-08-26

Reviewer: Likes to listen to radio

I read this book years ago and have been recommending it ever since. I always think it is better to learn from other's mistakes instead of your own and this book goes a long way in achieving this. This book has given me new insights to problems I have faced. I have relied too much on logic to solve problems in the past and now take the time to get all of the facts before I go ahead with a solution. The book also does a great job in explaining people's actions which at times make no sense.