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In the years since it was first published, this influential book based on the highly innovative findings of social psychologist Dr. The frontal cortex of the brain can monitor 3 to 4 strategies at a time, but favors creative thinking. Our ability to adapt to our environment often relies on considering multiple behavioral strategies and potentially creating a new strategy to succeed.
Publishing in the online journal PLoS Biology, Anne Collins and Etienne Koechlin of Ecole Normale Superieure and Institut National de la Sante et de la Recherche Medicale, France, examined frontal lobe function using behavioral experiments and computational models of human decision-making. Collins A, Koechlin E (2012) Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making.
When we’ve finally decided that it makes economic and otherwise practical sense to solve our problem, the next question to be decided is how to systematically and thoroughly go about actually developing its solution consistent with the principles identified earlier. We begin by discussing a generic idea generating technique, which can be applied together with any of the specific technically oriented techniques that follow it. In this innovative individual or group process, the objective is to deliberately generate as many unusual solution ideas as possible in a non-threatening, unstructured manner, and then to push each of those ideas as far as possible. One approach to brainstorming is to “seed' the session with one or more words pulled randomly from a dictionary, as starting points in the process of generating ideas.
Try to select participants from as wide a range of disciplines with as broad a range of experience and expertise as possible, to maximize the number and kind of creative ideas developed. Visually documenting the ideas developed on a blackboard, easel or similar device, so that all session participants can be “on the same page” at all times.
Maintaining a “permanent” written, tape or video record of the session, for later study and evaluation..
Refraining from any sort of criticism which would stifle creativity and cripple the free interchange of ideas essential to any brainstorming session’s success.
Individuals are always free to explore ideas on their own without any fear of criticism or possible domination by other group members. The result is that group brainstorming is usually superior, because when any individual’s limitations in the development of an idea are reached another’s creativity and experience may be available to overcome that barrier. Sometimes “the best of all possible worlds” can be achieved by a creative mix of both types of session. This is a powerful technique for considering potential decisions from a number of quite different perspectives, forcing you to transcend the limitations of your normal thinking style to obtain a more rounded view of the problem situation. The “Six Thinking Hats” technique is most often applied in group settings, where it has the benefit of blocking the confrontations that frequently occur when people with different thinking styles discuss a problem.
This perspective is one of the real benefits of de Bono's technique, because it avoids getting “blind sided” as a result of undue optimism which prevents you from seeing problems in advance. This is the optimistic viewpoint that helps you to see all the benefits of the decision and the value in pursuing it, even when everything looks gloomy and difficult. This is the creative approach, similar to brainstorming, in which there is little criticism of ideas. A variant of the “Six Hats” technique is to look at the problem from the point of view of different professions (e.g. The output from the “Six Hats” technique or its variants can also be quantified and then analyzed in precisely the same manner as we show in the techniques described next. These techniques are applicable to any type of problem, and therefore can be used in advance of, in conjunction with, or independent of heuristic and technological techniques. Publicly posting a request for help on a problem to coworkers, associates, friends, teachers, etc.
This is a form of the Public Solution technique which is useful for simultaneously engaging the minds of a large group in a problem. There were several inadequacies in this approach, but the main one was the unreasonably short time allowed for discussion.
Pretend to assume the opposite of what you want to prove and then look for facts that contradict that assumption.
Begin with a statement that is known to be absolutely incorrect, and then use it as a bridge to a new solution approach. Select a random word from the dictionary and juxtapose it with the problem statement, then brainstorm about possible relationships.
A heuristic is an empirical, learn-as-you-go procedure which can’t guarantee finding a solution, but which will increase the probability of finding a solution over what would be possible using a purely random or ad hoc approach. Different possible configurations are generated, and after a test of their "fitness" the good ones are retained and the bad ones eliminated. The search for a solution proceeds without any sense of choice or calculation of the likelihood that any path will be superior to another. In this strategy, the searcher looks one step ahead to see what next action will best move him toward the goal. This is a set of procedures designed to reduce the distance from the problem state to the goal state through a sequence of carefully identified steps, taking into consideration all of the many different dimensions of difference between those states.
This strategy involves alternating between a general overview of the situation and a close-up, detailed, precise examination of a subset of it. This method involves starting at the halfway point in a more or less linear system, and checking to see if the problem (or its symptoms) already appears there.
In selected situations, the presence of patterns may either suggest solutions themselves or remind you of prior cases in which useable solutions were found. Using as many of the techniques discussed below as are appropriate to the problem being worked on, create solution alternatives over the entire range of options, without concern for feasibility.
Question if the risks identified are serious enough for an alternative to be eliminated, or whether it’s possible to develop a plan which could remove risk or minimize its effect. If no proposed Solution provides sufficient satisfaction, recycle through the entire process again to look for more options!
When a Solution alternative is finally selected, review and evaluate the potential problems that may arise when this “solution” is implemented, and proceed only if that review is favorable.
It is particularly important to evaluate the proposed solution in light of the problem statement generated at the beginning of the process. Repeat the evaluation cycle to be sure that those problems previously identified and any new ones generated by the changes have all been satisfactorily resolved.
These steps are essential to arriving at a viable solution, but are insufficient in and of themselves because they are too general to be implementable. The techniques that follow are methods for turning what would otherwise be a completely subjective, basically “gut feel” decision-making process into one which has at least a semblance of objectivity. Not only does this mean that it is possible for the analyst to subconsciously influence the decision while maintaining a facade of objectivity, but that any decision reached as a result of such an analysis must be viewed with great caution and even skepticism. In the examples that follow, for the sake of simplicity in describing these techniques, only one “pass” is made. This is an adaptation of the simple “pros and cons” analysis that has almost universally been used for centuries.
A strongly positive score indicates that action is probably justified, a strongly negative score that it should be avoided. In its simplest adaptation, a table similar to that for PMI can be created, with 4 columns but in every other way identical. The questions that are appropriate for assessing each of the four SWOT factors will vary depending upon the type and context of the problem being analyzed, and will necessarily be very different for (say) a personal problem as opposed to one that is societal, technical, business or political, but certain common themes will exist.

The strictly qualitative output of the SWOT analysis can be quantified and analyzed in precisely the same manner as that of both the PMI and Force Field techniques, so they all really represent slightly different (and complementary) ways of achieving the same result. This method is conceptually very similar to both SWOT and PMI, especially the latter, with the important difference that rather than focusing on factors internal to the success or failure of a proposed solution it describes the external forces arrayed for or against it, so that a decision can be made which takes into account all interests.
The same caveat earlier noted in applying the other techniques regarding the subjectivity of the assigned scores again applies here. The result of this analysis is only slightly negative, so any decision regarding whether or not to proceed with the proposed move probably shouldn’t be made on the basis of it alone, but rather on the totality of this and any other forms of analysis performed. The preferred decision making process consists of a meta-analysis in which each of the various techniques presented herein is applied (as appropriate), and then the final decision summarizes their overall effect. Many real life problems contain several plausible alternative solution options, but little or no objective hard data which will allow you to objectively choose between them. Zero out the table diagonal in which each option is compared with itself, as well as all cells below that diagonal (= the converse duplicates of the above-diagonal cells).
A local community college student is trying to decide which of the options listed below will be in her best interest to pursue after she receives her Associate’s degree. In this case, the analysis has failed to provide a clear decision because our student is equally desirous of continuing on to obtain her Bachelor’s degree immediately or trying to begin a career with a Rock band.
This is not the kind of nice, neat answer we would prefer, but the real world is often messy so we shouldn’t really be surprised. Checking the table, we see that this direct comparison favored the College (A) option by the slimmest of margins. Its major virtue is that it quickly and simply allows the inclusion and evaluation of a wide array of factors while providing a rational decision basis in place of an outright guess or simple “gut feel”, and thus greatly increases the probability that the decision reached will be a good one.
One interesting fact to be noted here is that the comparisons upon which this technique is based are really the same ones we instinctively use in our normal, everyday decision making. Determine the relative importance of the factors in making the decision (= assign weights to the preferences). Multiply each score by its corresponding relative importance value (= weight) to calculate the correct overall decision weight. The options to be considered are the several major manufacturer’s various models on which the desired characteristics are available. As earlier noted, the key thing to be wary of here is that this is a strictly subjective process which represents the preferences of the individual assessing and specifying both the factors to be included and the weights assigned to each.
The relatively simple techniques we’ve just explored are applicable in a very wide set of circumstances, but unfortunately they’re not sufficient to handle situations in which complex financial or similar numeric calculations are required to adequately define the problem and its solution. Alternative decisions and the implications of taking each can be spelled out and evaluated. An accurate, balanced picture of the risks and rewards that can result from each alternative decision can be derived.
The best possible decisions can be objectively made, given the existing information and best available estimates.
Represent the decision that needs to be made by a small square at the left edge of a large sheet of paper. Draw a line toward the right for each possible solution, keeping them as far apart as possible to allow for later expansion of your thoughts. If you have completed the overall Problem Solution at the end of any line, just leave its termination blank. Starting from each new decision square on your diagram, again draw lines representing the options that could be taken. Repeat this process until you have included all of the possible outcomes and decisions you can visualize resulting from your original decision. Assign a cash or numeric value to each possible outcome, representing how much you think it would be worth to you. For each circle (representing an uncertainty point), estimate the probability of each outcome.
As the set of calculations for each node (decision square or uncertainty circle) is completed, simply record that result in the appropriate place on the right edge of the tree. Redraw the tree, eliminating all of the branches of the uncertain nodes and replacing each with the corresponding single node value just calculated. Subtract the cost from the node value just calculated, to find the benefit of that decision. When you have calculated the net benefit of each alternative decision, simply select the one which has the largest value. Similarly, we calculate the values for the two branches of the “Work” approach as $380,000 and $370,000, so of these the “use music skills” option is slightly better.
Our application of the Decision Tree technique in this situation produced the indicated decision that it would be best for this hypothetical student to go to work immediately after high school rather than to college, and that utilizing his music skills would be only marginally more productive (in terms of economic payoff) than not doing so.
But that decision was heavily dependent upon both the 10 year term chosen for the evaluation, and the probabilities assigned to the various outcomes, for which, unlike ones made in a business context where it’s often possible to use prior history to obtain somewhat more reliable estimates of the probabilities involved, in this context there is no realistic way of sharpening those estimates.
In this situation that’s especially necessary, because the application of this quantitatively oriented technique to a problem in which the most important payoff for many people is qualitative (e.g. So, as with any other technique, Decision Tree Analysis should always be applied in conjunction with a liberal helping of good old fashioned common sense!
The Developmental Psychology of Reasoning and Decision-Making ePub (Adobe DRM) can be read on any device that can open ePub (Adobe DRM) files. Rudnicka, Ewa A (2009) DEVELOPMENT AND EVALUATION OF A MODEL TO ASSESS ENGINEERING ETHICAL REASONING AND DECISION MAKING.
They found that human frontal function can simultaneously monitor no more than three or sometimes four strategies.
They then developed a computational model that predicted the responses produced by participants, which also revealed that participants made their choices by mentally constructing and monitoring up to three distinct behavioral strategies; flexibly associating digits, motor responses and expected auditory feedbacks. This suggests that this capacity limit is a hard constraint of human higher cognition,” said Dr.
To that end a number of related techniques have been developed for quickly and accurately focusing on those system aspects, parameters and constraints that are most likely to be important, and to which attention is most likely to pay off.
Conjure up different theories about the nature of the problem and how to solve it, and see where each leads. To break down preconceptions about the limits of the problem and assure the free flow of the participants’ imagination, during this process no criticism of the proposed ideas is permitted. On the other hand, group brainstorming can be inhibiting if quiet but creative people are allowed to be suppressed or overwhelmed by more aggressive ones, because of ineffective session leadership. This usually takes the form of allowing team members to individually generate a wide (but possibly shallow) range of solutions, and then developing and enhancing these ideas via group brainstorming. Rather than simply considering the situation rationally, it also requires you to view it emotionally, intuitively, creatively and even negatively.
Consider any gaps in that data as well as what you can learn from it, such as trends, anomalies, significant differences, etc.
Consider your own “gut reactions” as well as those of any other participants, especially the ones who may not fully understand or agree with your reasoning or position.
Review the proposed decision cautiously and defensively, considering all the reasons you can think of that it might not work. In its original form, the large group was divided into smaller groups of six people each, and each of those subgroups discussed the problem for six minutes, followed by formulating a single question or proposed solution by agreement.

By disproving all of the alternative explanations you automatically highlight (and “justify”) the sought after solution, but (unfortunately) you don’t necessarily prove it.
This technique can be made as efficient as possible by being systematic and keeping a record of attempts and their outcomes, so that no path or solution is tried more than once. It involves creating subgoals (the ends) to eliminate the differences between the current state and the condition for applying a desired operator (the means).
The first gives the solver a quick sense of the overall situation, even though that may be somewhat vague and general. Enough time should be spent on this activity to ensure that all plausible solutions are uncovered, including non-standard and creative ones. In addition to the expected technical considerations, affective, cognitive, and behavioral outcomes (the impact on the people involved) should be considered.
What we must do now to achieve the desired payoff is to actually delve into the specifics of the problem, and then go about developing a detailed solution which will allow us to realize that payoff. In this way, you can determine the sensitivity of the analysis to those input assumptions, and then treat the reliability (or non-reliability) of the resulting decisions accordingly. In this process you analyze a situation by identifying its Strengths, Weaknesses, Opportunities, and Threats. The same problem with the subjectivity of the values assigned to the relevant factors exists, with the same solution. As with the other methods, this is really nothing more than a specialized and highly refined way of comparing pros and cons.
For example, if each of the PMI, SWOT, and Force Field analyses were also slightly negative, then the overall conclusion would be fairly strongly negative. There’s no good way to accurately quantify their value, but by applying this technique it should still be possible to make a rational decision.
But what is painfully apparent is that any thought of attending night school is out, and that teaching is also not really an option worth further consideration!
But given this ambiguity, the student decides that perhaps the key direct comparison she made between the two dominant options of continuing on in college (A) and trying to establish a career in Rock music (D) should be used as a tie breaker - in effect giving that comparison more weight! But we also note that the college option was preferred over each of the other alternatives, so on balance a clear if narrow margin in favor of College (A) emerges as the student’s final decision! The difference here is that by explicitly listing and quantifying the factors involved we not only assure that all of the relevant ones are included, but that we also evaluate their relative importance correctly.
If these values aren’t immediately apparent, then a technique like Paired Comparison Analysis may be used to estimate them. But to keep our table simple for this example we’ll here pretend that only a few manufacturers make suitable models and that each of those manufacturers has only one such model, so that we need only give the manufacturer’s name in our table. So each and every individual conducting precisely this same analysis will almost necessarily obtain different totals, and thus may reach quite different decisions! If you discover any such, draw them in and redraft the tree as necessary (if parts of it have become too congested or untidy for clarity).
If you have data on past events you may be able to make fairly rigorous estimates of the probabilities. And overall it’s equally clear that it’s also best, so it and its net benefit of $380,000 become our final decision and value.
So the only feasible approach which can improve the probability that the decision reached is at least reasonably valid is to repeat the analysis using somewhat different probability estimates for the various outcomes, and using at least one other, substantially longer payoff period (e.g. Langer and her team of researchers at Harvard made its mark for its unique concept of mindfulness, thoroughly adapted to contemporary life in the West. Only later, when the results of the brainstorming session are analyzed, is it then permissible to evaluate the results and prune the proposed solutions for further brainstorming or the application of other techniques. By thus “touching all the bases”, the probability that any important aspect of the situation will either be overlooked or unnecessarily discounted will be greatly reduced, and the quality of the proposed solution accordingly enhanced. By thus finding the weak points in an approach you gain the opportunity to eliminate or alter them, or to prepare contingency plans to counter those weaknesses in advance of taking what otherwise might be a costly decision..
As is well known, this is certain to produce contrasting or even diametrically opposing viewpoints.
Then, given that context, it allows attention to individual parts in exact detail, permitting a close knowledge of pertinent areas to provide information about both potential or actual trouble spots, as well as a better basis for generalizing about the whole.
On this branch we therefore choose that as the most valuable option, and allocate its value of $280,000 to the decision node for the “college” branch of our decision tree. The problem that the incautious analyst encounters is that the mechanical application of the technique produces a nice, neat numerical result which has every appearance of both accuracy and validity, when in many cases it really possesses neither!
Langer s theory has been applied to a wide number of fields, including health, business, aging, prejudice, and learning. Consistently, the performance was significantly better in sessions including no more than three repeated codes. Interestingly, this ability to regulate creativity varied across participants and critically explains individual variations in performances. Next, the investigator goes to the half of the system where the problem is now known to occur and checks at its halfway point to see if the problem or symptom appears there. In most cases, because of the considerable impact on the system that would follow from a major change, an ambiguous result will almost always result in continuance of the status quo (= no change). Then combining this form of analysis with at least some of the others discussed to produce a meta-analysis is also wise.
Past research has attempted to evaluate these models by assessing numerous factors potentially linked to the decision process involving ethical issues.
There is now a new psychological assessment based on her work (called the Langer Mindfulness Scale) as well as an institute in Mexico founded to apply the concepts of mindfulness to health and wellness. We believe our study may also help to understand the biological foundations of individual differences in decision-making and adaptive behavior“. Each such iteration successively eliminates another half of what remains of the system as the source of the problem, and the process continues until the problem is located. In this problem, both PMI and Force Field analyses are in agreement, so the proposed move to the City is counter-indicated! Past research studying ethical decision making in organizations has focused on the business perspective and on individual decision making.
This is much faster than random checking or simply starting at one end of the system and then proceeding consistently toward the other end.
Little empirical research has focused on teams' ethical decision making in engineering and none (to the author's knowledge) have studied the process of ethical decision making by engineers.
For this research two primary models have been adopted: Jones's Synthesis of Ethical Decision Making model and the Harris, Pritchard, and Rabins (HPR) Model widely used in engineering. These models were combined along with factors cited in the literature to form a proposed Ethical Decision Making in Engineering Model. In general, students who have had an engineering ethics course perform better (in teams or as individuals) than students who did not have engineering ethics course for an engineering dilemma with moderate moral intensity; and teams outperformed individuals on the Resolution attribute and spent more time on Analysis and Recognition of Dilemma attributes.
Further, the derived regression analysis models showed that having had an engineering ethics course, working in teams, work experience, being female, the type of engineering major, and the dilemma's moral intensity are significant predictors of the overall Resolution as measured by the report quality.

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