The yellow hat must, however, avoid getting caught up in pessimistic thoughts. They must also avoid bringing to mind hopeful solutions based on hypothetical facts, feelings, and opinions. Throughout the problem-solving process, the yellow hat has a set of predefined objectives that it seeks to accomplish. The yellow hat persistently seeks out benefits. It sees a problem and brings to mind effective contingency plans and solutions that help pave the way forward. Its primary objective is to search for answers that lead to a higher array of opportunities. It wholeheartedly understands that within every problem there is an equivalent seed of opportunity that is waiting to be discovered.
It, therefore, realistically assesses these risks and draws up a practical plan that counteracts, minimizes, and eliminates them. Another primary objective of the yellow hat is to assess the feasibility of ideas based on the resources skills, knowledge, time, and support you have available.
The final objective of the yellow hat is to instill a sense of positive expectation that moves the problem-solving process forward. It, therefore, tackles every challenge with optimism, patience , determination , and resolve. Additional questions that you formulate by yourself should take into account each of the roles and objectives that are critical to the mindset of a yellow hat thinker.
An effective problem solver needs a means of processing problems in an open, flexible, and unconstrained way. Moreover, they must become a possibility thinker who persistently thinks outside the box and bends the rules of problem-solving. Furthermore, they must do this free from judgment and self-criticism. We will then conclude with a set of questions that will encourage you to think through your problems in creative ways. A seedling sprouts from the ground and grows persistently over time.
It expands its leaves and branches in many unexpected directions. In exactly the same way, a green hat instills an ever-growing and expanding sense of unpredictability into the thought process. With this in mind, it brings forth a myriad of creative and mind-bending ideas that expand the possibilities and bring to light unique and seemingly unexpected solutions. The primary role of the green hat is to open the doors to unique creative ideas and perspectives that shatter the boundaries of reality and unlock new understandings and opportunities.
Throughout the problem-solving process, the green hat has a set of predefined objectives that it seeks to accomplish. The primary role of the green hat is to expand the possibilities of reality in surprising and unexpected ways beyond box-like thinking methods. It understands that rules are made to be broken. And so, it completely disregards all rules and guidelines. This is what the other hats do very well.
The green hat uses numerous creative problem-solving techniques that help to expand its awareness and understanding of the problem. These methods bring to mind unique ideas and solutions that challenge the other thinking hats to think in original ways. This successfully breaks down the boundaries of understanding and opens the doors to new solutions. Additional questions that you formulate by yourself should take into account each of the roles and objectives that are critical to the mindset of a green hat thinker.
Okay, so, the process begins when the managerial blue hat Director allocates thinking time to each of the six hats, including itself. Often the order of thinking would progress in the following way:. Its objective is to bring to light an ideal solution to the problem. However, its use goes well beyond just problem-solving. Whether your objective is to solve a problem , to overcome an obstacle , to brainstorm a new idea , to improve your decision-making or for academic purposes, the Six Thinking Hats will help you find the solutions, answers, and the opportunities you need to keep you ahead of the game.
Now the choice is yours. You can either just leave your hats hanging on the coat-hanger collecting dust, or you can consistently and persistently use them to improve the quality of your life.
Measurement in Science
Did you gain value from this article? Is it important that you know and understand this topic? Would you like to optimize how you think about this topic? Would you like a method for applying these ideas to your life? This mind map provides you with a quick visual overview of the article you just read. The branches, interlinking ideas, and images model how the brain thinks and processes information.
If, on the other hand, you want access to an ever-growing library of s of visual tools and resources, then check out our Premium Membership Packages. These packages provide you with the ultimate visual reference library for all your personal development needs. Every problem contains within itself the seeds of its own solution. To explore additional articles in this series, please click through on the links below: Here is a breakdown of the roles the blue hat typically plays: To think about thinking.
To define the problem. To gather global perspectives about the problem and the solution. To manage the other thinking hats. To manage the flow of ideas. To manage the implementation of ideas. The primary role of the blue hat is to think about the process of thinking. The Objectives of the Blue Hat Throughout the problem-solving process, the blue hat has a set of predefined objectives that it seeks to accomplish. Improving efficiency and effectiveness of the thinking process.
Formulating suitable questions to help direct thinking. Outlining an agenda, rules, goals, and tasks for problem-solving. Organizing ideas and drawing up plans for action.
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What problem am I facing? How can I best define this problem? What is my goal and outcome? What do I seek to achieve by solving this problem? The Neutral White Hat Thinker An effective problem solver needs a means of collecting, collating, organizing, and presenting information in a neutral and unbiased way. Bringing forward stats, facts, and data that can be used to solve the problem.
Prioritizing facts over opinions and beliefs. Highlighting gaps in knowledge, perspective, and awareness. Bringing forth logical solutions to the problem at hand. What do I know about this problem? What can I learn from this problem? What more would I like to learn about this problem? The Intuitive Red Hat Thinker An effective problem solver needs a means of intuitively making sense of each problem and the possible solutions that could arise.
50. On Becoming a Leader
The Objectives of the Red Hat Throughout the problem-solving process, the red hat has a set of predefined objectives that it seeks to accomplish. Bringing to light intuitive insights. Exploring the emotional point of view. Revealing hidden strengths behind ideas. Identifying weaknesses based on hunches. Uncovering hidden internal conflicts. What is my gut telling me about this solution? Intuitively, is this the right solution to this problem? The Pessimistic Black Hat Thinker An effective problem solver needs a means of proactively identifying the pitfalls, dangers, and flaws of possible solutions.
The Objectives of the Black Hat Throughout the problem-solving process, the black hat has a set of predefined objectives that it seeks to accomplish. Specifically, they proved that ordering and concatenation are together sufficient for the construction of an additive numerical representation of the relevant magnitudes. An additive representation is one in which addition is empirically meaningful, and hence also multiplication, division etc.
A hallmark of such magnitudes is that it is possible to generate them by concatenating a standard sequence of equal units, as in the example of a series of equally spaced marks on a ruler. Although they viewed additivity as the hallmark of measurement, most early measurement theorists acknowledged that additivity is not necessary for measuring. Examples are temperature, which may be measured by determining the volume of a mercury column, and density, which may be measured as the ratio of mass and volume.
Nonetheless, it is important to note that the two distinctions are based on significantly different criteria of measurability. As discussed in Section 2 , the extensive-intensive distinction focused on the intrinsic structure of the quantity in question, i. The fundamental-derived distinction, by contrast, focuses on the properties of measurement operations. A fundamentally measurable magnitude is one for which a fundamental measurement operation has been found. Consequently, fundamentality is not an intrinsic property of a magnitude: Moreover, in fundamental measurement the numerical assignment need not mirror the structure of spatio-temporal parts.
Electrical resistance, for example, can be fundamentally measured by connecting resistors in a series Campbell This is considered a fundamental measurement operation because it has a shared structure with numerical addition, even though objects with equal resistance are not generally equal in size.
The distinction between fundamental and derived measurement was revised by subsequent authors. Fundamental measurement requires ordering and concatenation operations satisfying the same conditions specified by Campbell. Associative measurement procedures are based on a correlation of two ordering relationships, e. Derived measurement procedures consist in the determination of the value of a constant in a physical law. The constant may be local, as in the determination of the specific density of water from mass and volume, or universal, as in the determination of the Newtonian gravitational constant from force, mass and distance.
Duncan Luce and John Tukey in their work on conjoint measurement, which will be discussed in Section 3. The previous subsection discussed the axiomatization of empirical structures, a line of inquiry that dates back to the early days of measurement theory. A complementary line of inquiry within measurement theory concerns the classification of measurement scales.
Stevens , distinguished among four types of scales: Nominal scales represent objects as belonging to classes that have no particular order, e. Ordinal scales represent order but no further algebraic structure. For example, the Mohs scale of mineral hardness represents minerals with numbers ranging from 1 softest to 10 hardest , but there is no empirical significance to equality among intervals or ratios of those numbers.
The Kelvin scale, by contrast, is a ratio scale, as are the familiar scales representing mass in kilograms, length in meters and duration in seconds. Stevens later refined this classification and distinguished between linear and logarithmic interval scales As Stevens notes, scale types are individuated by the families of transformations they can undergo without loss of empirical information.
Empirical relations represented on ratio scales, for example, are invariant under multiplication by a positive number, e. Linear interval scales allow both multiplication by a positive number and a constant shift, e. Ordinal scales admit of any transformation function as long as it is monotonic and increasing, and nominal scales admit of any one-to-one substitution. Absolute scales admit of no transformation other than identity. Two issues were especially contested.
Several physicists, including Campbell, argued that classification and ordering operations did not provide a sufficiently rich structure to warrant the use of numbers, and hence should not count as measurement operations. The second contested issue was whether a concatenation operation had to be found for a magnitude before it could be fundamentally measured on a ratio scale. The debate became especially heated when it re-ignited a longer controversy surrounding the measurability of intensities of sensation.
It is to this debate we now turn. One of the main catalysts for the development of mathematical theories of measurement was an ongoing debate surrounding measurability in psychology. These differences were assumed to be equal increments of intensity of sensation. This law in turn provides a method for indirectly measuring the intensity of sensation by measuring the intensity of the stimulus, and hence, Fechner argued, provides justification for measuring intensities of sensation on the real numbers.
Those objecting to the measurability of sensation, such as Campbell, stressed the necessity of an empirical concatenation operation for fundamental measurement. Since intensities of sensation cannot be concatenated to each other in the manner afforded by lengths and weights, there could be no fundamental measurement of sensation intensity. Moreover, Campbell claimed that none of the psychophysical regularities discovered thus far are sufficiently universal to count as laws in the sense required for derived measurement Campbell in Ferguson et al.
All that psychophysicists have shown is that intensities of sensation can be consistently ordered, but order by itself does not yet warrant the use of numerical relations such as sums and ratios to express empirical results. The central opponent of Campbell in this debate was Stevens, whose distinction between types of measurement scale was discussed above.
In useful cases of scientific inquiry, Stevens claimed, measurement can be construed somewhat more narrowly as a numerical assignment that is based on the results of matching operations, such as the coupling of temperature to mercury volume or the matching of sensations to each other.
Stevens argued against the view that relations among numbers need to mirror qualitative empirical structures, claiming instead that measurement scales should be regarded as arbitrary formal schemas and adopted in accordance with their usefulness for describing empirical data. For example, adopting a ratio scale for measuring the sensations of loudness, volume and density of sounds leads to the formulation of a simple linear relation among the reports of experimental subjects: Such assignment of numbers to sensations counts as measurement because it is consistent and non-random, because it is based on the matching operations performed by experimental subjects, and because it captures regularities in the experimental results.
In the mid-twentieth century the two main lines of inquiry in measurement theory, the one dedicated to the empirical conditions of quantification and the one concerning the classification of scales, converged in the work of Patrick Suppes ; Scott and Suppes ; for historical surveys see Savage and Ehrlich ; Diez a,b.
RTM defines measurement as the construction of mappings from empirical relational structures into numerical relational structures Krantz et al. An empirical relational structure consists of a set of empirical objects e. Simply put, a measurement scale is a many-to-one mapping—a homomorphism—from an empirical to a numerical relational structure, and measurement is the construction of scales. Each type of scale is associated with a set of assumptions about the qualitative relations obtaining among objects represented on that type of scale. From these assumptions, or axioms, the authors of RTM derive the representational adequacy of each scale type, as well as the family of permissible transformations making that type of scale unique.
In this way RTM provides a conceptual link between the empirical basis of measurement and the typology of scales. On the issue of measurability, the Representational Theory takes a middle path between the liberal approach adopted by Stevens and the strict emphasis on concatenation operations espoused by Campbell. Like Campbell, RTM accepts that rules of quantification must be grounded in known empirical structures and should not be chosen arbitrarily to fit the data. However, RTM rejects the idea that additive scales are adequate only when concatenation operations are available Luce and Suppes Instead, RTM argues for the existence of fundamental measurement operations that do not involve concatenation.
How to Solve Problems Using the Six Thinking Hats Method
Here, measurements of two or more different types of attribute, such as the temperature and pressure of a gas, are obtained by observing their joint effect, such as the volume of the gas. Luce and Tukey showed that by establishing certain qualitative relations among volumes under variations of temperature and pressure, one can construct additive representations of temperature and pressure, without invoking any antecedent method of measuring volume. This sort of procedure is generalizable to any suitably related triplet of attributes, such as the loudness, intensity and frequency of pure tones, or the preference for a reward, it size and the delay in receiving it Luce and Suppes The discovery of additive conjoint measurement led the authors of RTM to divide fundamental measurement into two kinds: Under this new conception of fundamentality, all the traditional physical attributes can be measured fundamentally, as well as many psychological attributes Krantz et al.
Above we saw that mathematical theories of measurement are primarily concerned with the mathematical properties of measurement scales and the conditions of their application. A related but distinct strand of scholarship concerns the meaning and use of quantity terms. A realist about one of these terms would argue that it refers to a set of properties or relations that exist independently of being measured.
An operationalist or conventionalist would argue that the way such quantity-terms apply to concrete particulars depends on nontrivial choices made by humans, and specifically on choices that have to do with the way the relevant quantity is measured. Note that under this broad construal, realism is compatible with operationalism and conventionalism. That is, it is conceivable that choices of measurement method regulate the use of a quantity-term and that, given the correct choice, this term succeeds in referring to a mind-independent property or relation.
Nonetheless, many operationalists and conventionalists adopted stronger views, according to which there are no facts of the matter as to which of several and nontrivially different operations is correct for applying a given quantity-term. These stronger variants are inconsistent with realism about measurement.
This section will be dedicated to operationalism and conventionalism, and the next to realism about measurement. The strongest expression of operationalism appears in the early work of Percy Bridgman , who argued that. Length, for example, would be defined as the result of the operation of concatenating rigid rods. According to this extreme version of operationalism, different operations measure different quantities.
49. Financial Intelligence
Nevertheless, Bridgman conceded that as long as the results of different operations agree within experimental error it is pragmatically justified to label the corresponding quantities with the same name Operationalism became influential in psychology, where it was well-received by behaviorists like Edwin Boring and B. As long as the assignment of numbers to objects is performed in accordance with concrete and consistent rules, Stevens maintained that such assignment has empirical meaning and does not need to satisfy any additional constraints.
Nonetheless, Stevens probably did not embrace an anti-realist view about psychological attributes. Instead, there are good reasons to think that he understood operationalism as a methodological attitude that was valuable to the extent that it allowed psychologists to justify the conclusions they drew from experiments Feest For example, Stevens did not treat operational definitions as a priori but as amenable to improvement in light of empirical discoveries, implying that he took psychological attributes to exist independently of such definitions Stevens Operationalism met with initial enthusiasm by logical positivists, who viewed it as akin to verificationism.
Nonetheless, it was soon revealed that any attempt to base a theory of meaning on operationalist principles was riddled with problems. Among such problems were the automatic reliability operationalism conferred on measurement operations, the ambiguities surrounding the notion of operation, the overly restrictive operational criterion of meaningfulness, and the fact that many useful theoretical concepts lack clear operational definitions Chang Accordingly, most writers on the semantics of quantity-terms have avoided espousing an operational analysis.
A more widely advocated approach admitted a conventional element to the use of quantity-terms, while resisting attempts to reduce the meaning of quantity terms to measurement operations. Mach noted that different types of thermometric fluid expand at different and nonlinearly related rates when heated, raising the question: According to Mach, there is no fact of the matter as to which fluid expands more uniformly, since the very notion of equality among temperature intervals has no determinate application prior to a conventional choice of standard thermometric fluid.
Conventionalism with respect to measurement reached its most sophisticated expression in logical positivism. These a priori , definition-like statements were intended to regulate the use of theoretical terms by connecting them with empirical procedures Reichenbach An example of a coordinative definition is the statement: In accordance with verificationism, statements that are unverifiable are neither true nor false.
Instead, Reichenbach took this statement to expresses an arbitrary rule for regulating the use of the concept of equality of length, namely, for determining whether particular instances of length are equal Reichenbach At the same time, coordinative definitions were not seen as replacements, but rather as necessary additions, to the familiar sort of theoretical definitions of concepts in terms of other concepts Under the conventionalist viewpoint, then, the specification of measurement operations did not exhaust the meaning of concepts such as length or length-equality, thereby avoiding many of the problems associated with operationalism.
Realists about measurement maintain that measurement is best understood as the empirical estimation of an objective property or relation. A few clarificatory remarks are in order with respect to this characterization of measurement. Rather, measurable properties or relations are taken to be objective inasmuch as they are independent of the beliefs and conventions of the humans performing the measurement and of the methods used for measuring. For example, a realist would argue that the ratio of the length of a given solid rod to the standard meter has an objective value regardless of whether and how it is measured.
Third, according to realists, measurement is aimed at obtaining knowledge about properties and relations, rather than at assigning values directly to individual objects. This is significant because observable objects e. Knowledge claims about such properties and relations must presuppose some background theory. By shifting the emphasis from objects to properties and relations, realists highlight the theory-laden character of measurements.
Realism about measurement should not be confused with realism about entities e. Nor does realism about measurement necessarily entail realism about properties e. Nonetheless, most philosophers who have defended realism about measurement have done so by arguing for some form of realism about properties Byerly and Lazara ; Swoyer ; Mundy ; Trout , These realists argue that at least some measurable properties exist independently of the beliefs and conventions of the humans who measure them, and that the existence and structure of these properties provides the best explanation for key features of measurement, including the usefulness of numbers in expressing measurement results and the reliability of measuring instruments.
The existence of an extensive property structure means that lengths share much of their structure with the positive real numbers, and this explains the usefulness of the positive reals in representing lengths. Moreover, if measurable properties are analyzed in dispositional terms, it becomes easy to explain why some measuring instruments are reliable.
A different argument for realism about measurement is due to Joel Michell , , who proposes a realist theory of number based on the Euclidean concept of ratio. According to Michell, numbers are ratios between quantities, and therefore exist in space and time. Specifically, real numbers are ratios between pairs of infinite standard sequences, e.
Measurement is the discovery and estimation of such ratios. An interesting consequence of this empirical realism about numbers is that measurement is not a representational activity, but rather the activity of approximating mind-independent numbers Michell Realist accounts of measurement are largely formulated in opposition to strong versions of operationalism and conventionalism, which dominated philosophical discussions of measurement from the s until the s. In addition to the drawbacks of operationalism already discussed in the previous section, realists point out that anti-realism about measurable quantities fails to make sense of scientific practice.
How to Solve Problems Using the Six Thinking Hats Method
By contrast, realists can easily make sense of the notions of accuracy and error in terms of the distance between real and measured values Byerly and Lazara A closely related point is the fact that newer measurement procedures tend to improve on the accuracy of older ones. If choices of measurement procedure were merely conventional it would be difficult to make sense of such progress. In addition, realism provides an intuitive explanation for why different measurement procedures often yield similar results, namely, because they are sensitive to the same facts Swoyer Finally, realists note that the construction of measurement apparatus and the analysis of measurement results are guided by theoretical assumptions concerning causal relationships among quantities.
The ability of such causal assumptions to guide measurement suggests that quantities are ontologically prior to the procedures that measure them. While their stance towards operationalism and conventionalism is largely critical, realists are more charitable in their assessment of mathematical theories of measurement.
Brent Mundy and Chris Swoyer both accept the axiomatic treatment of measurement scales, but object to the empiricist interpretation given to the axioms by prominent measurement theorists like Campbell and Ernest Nagel ; Cohen and Nagel Rather than interpreting the axioms as pertaining to concrete objects or to observable relations among such objects, Mundy and Swoyer reinterpret the axioms as pertaining to universal magnitudes, e.
Moreover, under their interpretation measurement theory becomes a genuine scientific theory, with explanatory hypotheses and testable predictions. Despite these virtues, the realist interpretation has been largely ignored in the wider literature on measurement theory. Information-theoretic accounts of measurement are based on an analogy between measuring systems and communication systems. The accuracy of the transmission depends on features of the communication system as well as on features of the environment, i.
The accuracy of a measurement similarly depends on the instrument as well as on the level of noise in its environment. Conceived as a special sort of information transmission, measurement becomes analyzable in terms of the conceptual apparatus of information theory Hartley ; Shannon ; Shannon and Weaver Ludwik Finkelstein , and Luca Mari suggested the possibility of a synthesis between Shannon-Weaver information theory and measurement theory. As they argue, both theories centrally appeal to the idea of mapping: However, irrespective of the problems you face, your issues do actually serve a purpose.
Every problem you experience has a purpose. That purpose can come in the form of an opportunity. For instance, an opportunity for growth, for improving efficiency, for learning from a mistake , for expanding your perspective, etc. Problems are typically opportunities that can help improve how you think about your life, yourself, and about your circumstances.
They can serve to optimize how you work and live in remarkable ways. However, you need to first embrace these problems with an open heart and mind. It presents an efficient method for problem-solving that can be used individually or in a team environment.
It can help guide you through these problems in more optimal ways. To explore additional articles in this series, please click through on the links below:. An effective problem solver has to have a method for directing their thoughts in proactive ways.
Moreover, they must understand how to guide each of their thoughts in a neutral and unbiased manner with the primary intention of improving the effectiveness and efficiency of the process. We will then conclude with a set of questions that can help you to think through your problems in rational ways.
A movie director manages actors, cameramen, shooting angles, props, and scripts that are critical for creating a successful blockbuster movie experience. In precisely the same way, a blue hat manages the thinking process — allowing for better synergy between the thought patterns and habits of the other thinking hats.
Every thought that it has is focused on improving the effectiveness and efficiency of the thinking process. This subsequently filters through to the other five hats. The smoother, faster, and more efficient the process, the higher the probability that a practical solution can be found. The blue hat must, however, clearly describe the problem in writing.
If it fails to define the problem clearly, then it will waste precious time directing its energies on irrelevant thoughts, activities, and tasks. It prefers to sit back and play the role of the court judge who oversees events from a global perspective. It then uses these insights to decide on a suitable plan of action.
Another role that the blue hat plays is that of a manager. In this role, the blue hat helps to improve the flow of communication between all the hats , thereby encouraging better insights and ideas that bring about ideal solutions to the problem at hand. The blue hat understands the importance of time and how critical it is for problem-solving. With this in mind, the blue hat plays the role of the timekeeper. It allocates precise chunks of time to the other hats and to specific topics under discussion. The blue hat is well aware that time should be spent wisely on areas that will bring about the highest returns on investment.
The blue hat also manages the flow of ideas between the hats. It attempts to piece together all the scattered thoughts to help generate an ideal solution to the problem. Each thinking hat has a unique set of ideas, approaches, and perspectives. The blue hat must constructively merge these unique thoughts, otherwise, the thought process will stumble and stagnate in the face of adversity. Unique and creative ideas are, of course, wonderful. However, unless we find a means of integrating them into our physical reality, then we will, unfortunately, fail to grasp the opportunities they present us with.
Throughout the problem-solving process, the blue hat has a set of predefined objectives that it seeks to accomplish. This subsequently leads to a more efficient and effective process of thinking that brings to light a greater array of solutions and opportunities. The blue hat understands that asking the right kinds of questions can generate helpful insights and potential solutions.
However, it must ask these questions cautiously. The blue hat must pose questions that help stimulate the thinking process. However, it must do so in a way that minimizes the personal biases and limitations that each hat brings to the table. The blue hat initiates this process by setting an agenda, by outlining rules for discussion, and by setting tasks and objectives that continuously drive the thinking process forward. It then uses that information to structure a practical plan of action for solving the problem.
What is the most effective method of proceeding from this position? How can I best organize and arrange my thinking to help move me beyond my present circumstances? Keep in mind that this list of questions is only a starting point that will help guide you in the right direction. Additional questions that you formulate by yourself should take into account each of the roles and objectives that are critical to the mindset of a blue hat thinker. An effective problem solver needs a means of collecting, collating, organizing, and presenting information in a neutral and unbiased way.
Moreover, they must have a method for reaching effective logical solutions based on the data they have collected. We will then conclude with a set of questions that can help you to think through your problems in objective ways. A detective searches for clues, for evidence, and for facts that help them solve a case. They openly acknowledge that a piece of evidence can be misleading. They, instead wait for all the facts to be presented before reaching a conclusion.
It collects this evidence to help the other thinking hats work through the problem more effectively. The white hat must, however, avoid making conclusions or judgments about the information it has collected. Jumping to conclusions or making unjustified assumption could potentially derail the problem-solving process. This is designed to help open new avenues for brainstorming possible solutions. These facts are based on questions that address the what, when, where, and how of problem-solving. In the realm of white hat thinking, there are no beliefs or opinions, there are just solid concrete facts and evidence.
These facts, therefore, take precedence over everything else. Through its exposition of key facts and data, the white hat goes to work unlocking valuable titbits of information about the problem. Its key objective is to bring forth a set of logical, but neutral solutions that will help stimulate further thinking and exploration.
All this, of course, sets the foundations for the reflective thinking that is about to take place. How will I go about acquiring the facts, stats and data that will help me resolve this problem? What potential solutions exist based on the facts, stats, and data I have collected? Additional questions that you formulate by yourself should take into account each of the roles and objectives that are critical to the mindset of a white hat thinker.
An effective problem solver needs a means of intuitively making sense of each problem and the possible solutions that could arise. Moreover, they must have a method for adequately filtering out any preconceived biases that may sway their intuitive feelings and opinions. We will then conclude with a set of questions that can help you to think through your problems in intuitive ways. A heart is a very intuitive organ that senses subtle changes in feeling and emotion when circumstances change. In precisely the same way, a red hat brings to light its intuitive feelings and opinions to help guide the problem-solving process.
It intuitively presents effective solutions and direction for further action based on its personal feelings and hunches. The red hat must, however, avoid rationalizing or trying to justify its feelings. There is no logic here. It must primarily follow its gut instinct. Throughout the problem-solving process, the red hat has a set of predefined objectives that it seeks to accomplish. Our feelings are very interesting and somewhat mysterious chemical processes that stimulate mental activity in the brain. When they are pure and removed from personal emotion and bias, they can lead us in unexpected directions towards solutions we logically would never have considered.
They then intuitively relate that back to the problem at hand. The red hat can, however, be swayed by their emotional tendencies. They often seek an emotional understanding of the problem, and, therefore, bring to mind solutions based on their unconscious emotional tendencies. However, when the red hat is in-tune with their feelings, that is when they truly shine. For instance, sometimes ideas and potential solutions to problems may seem weak and somewhat impractical at first.