What is Bayesian Analysis?

http://www.bayesian.org/bayesexp/bayesexp.html

This article is a summary of the International Society for Bayesian Analysis's (ISBA) definition of the basics of the Bayesian theorem and analysis. The according to the ISBA website, the organization "was founded in 1992 to promote the development and application of Bayesian analysis useful in the solution of theoretical and applied problems in science, industry and government. By sponsoring and organizing meetings, publishing the electronic journal of Bayesian statistics Bayesian Analysis, and other activities ISBA provides a focal point for those interested in Bayesian analysis and its applications".

Summary
Bayesian analysis, a statistical tool for handling probability distributions, got its start in the mid 18th century. It was not, however, until the 1980s when modern computers were able to handle the complex computations that made Bayesian implementation difficult, that Bayesian analysis gained more widespread acceptance. Since then, its use has increased in popularity, being used in many different applications--from healthcare, to weather, to criminal justice. Despite the many nuanced manifestations of Bayesian analysis, it serves a common application: to analyze the probability of unknown and uncertain occurences.



How To:

The left side of the equation expresses the known quantities--"parameters"--as a probability of the current data--"prior distribution". 'y' represents the new data that enters into the calculation. Thus, the "'likelihood,' [is] proportional to the distribution of the observed data given the model parameters.

On the right, the equation's new probablity distribution (posterior distribution) is read: "posterior is proportional to the prior times the likelihood".

Strengths:

• Many diverse applications
• "Philosophical consistency"
• Lacks problems that are associated with other 'frequentist' methods
• Produce clear answers, products
• Reformulates for each variable

Weaknesses:

• Subjective nature of prior probabilities-"your prior information is different from mine".
• More complex problems require more powerful computational tools

Game theory, simulated interaction, and unaided judgement for forecasting decisions in conflicts: Further evidence

Kesten C. Green

Summary
Green's article, published in the International Journal of Forcasting (2005), is a validity study that compares the accuracy of game theory, simulated interactions (role playing), and unaided judgment as methods in forecasting decisions in conflicts. It provides further evidence to support his earlier research, which indicated that expert game theorists' forecasts had less accuracy than those of novice (student) role players.

It is important to note here that these methods were tested in experiments involving specific conflict situations only. Not all game theorists recommend game theory for generating forecasts in specific situations.

Green's 2002 study reflected the accuracy of the three methods for forecasting conflict decisions. Participants in the study were asked to select the most likely decision (in 5 conflict situations) from a list. The results of the study did not bode well for the game theory experts (participants, % accuracy):

• University Students (using unaided judgment), 27%
• Game Theory Experts, 28%
• University Students (using role playing/simulated interactions), 61%

Green's 2002 study drew some attention from his peers and game theorists, who commented that perhaps some conflict situations are more appropriate for use with game theory than others. The 2005 study utilized the same basic process, and was administered to participants representing the aforementioned three methods. It was directed at three (actual) conflicts, unrelated to the five used in the 2002 study:

1. Personal Grievance. An employee of a New Zealand student association felt there was a disparity between her work and the level of pay she was receiving. Upon the administration's evaluation of her situation, it was discovered that she was being compensated above the top-level of pay in her salary bracket. While her manager did not consider cutting her salary, she did arrange for a mediator to set up a meeting between the parties, as it was obvious she would not be elligible for a pay increase in the near future. Participants were to choose from several decisions.
2. Telco Takeover. This situation presented the participants with the conflict stemming from a corporate takeover battle between Alltel and CenturyTel. In 2001, executives from the much smaller CenturyTel company presented an offer that involved the sale of their mobile phone division to Alltel, which Alltel declined. Soon after, Alltel returned to CenturyTel with an offer to buy all of the company at 40% more than the share price. The board of CenturyTel fought to prevent an Alltel takeover. Participants were to forecast the execution of the deal and predict the basis of terms.
3. Water Dispute. This conflict raged over Syria's and Iraq's claims to access of the Euphrates River in 1975. The flow of water into Iraq had been slowed following Syria's construction of a dam across the Euphrates to create a reservoir in Syria. Both sides mobilized for war, and Saudi Arabia called both parties together for mediation. Participants in the study were to forecast whether Syria would increase water flow from the dam or whether Iraq would declare war and bomb Syria's dam.

Since the findings of this research were to be compared with those of the 2002 study, Green took steps to evenly match the conflict situations with game theorists' and other decision makers' interests, i.e. types of organizations involved, nature of the disputes, and familiarity of situations.

Results
The findings of this follow-up study are entirely consistent with the 2002 study. Game theory experts and unaided novices had a much lower forecast accuracy than novices who implemented role playing (simulated interactions) in predicting the eight conflict decisions.

Working Smarter With Decision Trees

Summary

This article provides an introduction to using and creating a decision tree to visually demonstrate the process of a particular decision. This tool allows the user to create a model of the relationship of a decision, strategy, and possible outcomes. Decision trees are not only a useful asset to analysts, but are also good tools for presenters and audiences.

At the most basic level, decision trees begin with a goal and the strategy that is most likely to achieve it. The analyst should begin by formulating the main problem, then logically structuring alternative strategies and their projected results. Once the problem and the alternatives are determined, it is now time to construct a decision tree diagram.

There are four main components used in creating a decision tree.

1. Trigger Event or Decision Statement (Nodes)
2. Decision Paths
   
3. Chance Points or Nodes
   
4. Leaf or Terminating Nodes

**For each node, the article recommends using a different shape or color to distinguish between decisions, chance points, and leaf nodes.

Outcomes may flow from either left-to-right, or from top-to-bottom, so when creating a decision tree, begin from the top or the left-hand side. The first step is to identify the trigger event, or decision statement, and place it on the top or left side of the page. The article uses a Product Line Decision as a sample for this exercise and "Extend or Consolidate" as the decision statement. Since there are two separate options for this decision, both pathways branch out from the statement. The decision paths then run into subsequent decision points, resulting in the development of more options. The decision points continue to fan out all probable pathways until they reach the leaf or terminating node. Here is the Product Line Decision Tree Example:

Use a decision tree analysis to systematically arrive at your smartest choice

Summary

Decision tree analysis is a structured, systematic method used in complex decision making problems. It consists of a diagram of the decisions, external events, and likely outcomes involved in a decision.

The article provides a schematic of the basic parts of a decision tree diagram:

In this diagram, the squares represent the possible decisions, with the extending lines representing the opposing options at the point of decision. Circles represent the external events, or points of uncertainty. The lines extending from circles indicate external, uncontrollable events and/or circumstances. The analyst can choose to list a probability above these lines to indicate the likelihood of the outcomes.

The article recommends assigning a quantitative measurement of the perceived benefit of each outcome (desirability). Once all of the outcomes are listed and contain a measure of value, it is time to evaluate the decision. Add the benefit measures of the end outcomes that trace back to a particular choice via a specific path. The preferred pathway is that which results in the highest level of desirability.

In the event where a tree has more than one decision point, it is best to calculate the latest stages first. "Identify the choice that gives the highest overall desirability and leave only that branch (removing the decision point). Do the same with the remaining squares, working your way to the left (to the first decision point in the sequence)."

Argument Mapping (Efebia)

Summary
Argument mapping is a logical sequencing method that employs box-and-line diagrams to "map" a course of possible decisions for a given "argument" and the ramifications of each option. The purpose of the map is to provide a visual depiction of the relationships between the overall contention and the logical (evidential) claims supporting or opposing it. Upon examination of the supporting and opposing claims, an argument map should serve as a useful tool for use in the decision making process, by reducing the complexity of a dilemma, conflict, or argument. Since argument mapping distinguishes itself from other box-and-line methods by utilizing different shapes, colors, and positioning, it appeals to the strong visual comprehension abilities of humans, allowing for improved processing and understanding, ultimately simplifying the complexity of an argument.

Basic Construction of an Argument Map
The components of an argument map are listed below with a brief explanation. Those pieces of the map are identified in the example below (click on the map to link to the source and to access a higher resolution map).

• The main claim: referred to in this article as the "position" or "contention" -is the hypothesis to be logically examined. The argument map's purpose is to help the decision maker accept or reject this hypothesis.
  
• Reason: a positive claim, or one that directly supports the main claim. Reasons not only support the main position, they may also support another reason.
• Objection: a negative claim, or one that opposes the overall main claim.
• Rebuttal: opposes an objection directly above it; or, "objection against an objection".

Strengths of Argument Mapping
According to the article, by using colors, shapes, etc. in argument mapping, the mind can better process the complexity and abstract nature of a difficult argument. Additionally, the logical structure of argument mapping is easier to present than traditional prose, which requires the reader to deconstruct the argument for himself, demanding a large investment in time and cognition.

The article also cites "extensive research" conducted by the University of Melbourne to gauge the effectiveness of argument mapping in the context of critical thinking. The study compared the achieved critical thinking abilities of students who utilized the Reason!able (Rationale) argument mapping tool versus those who used traditional prose. The study determined that, in a 12-week course, students who used argument mapping gained 12 IQ points.

Author's Comment:
Since this article may have commercial implications (as it names a particular brand of software), it is obviously a strong advocate for argument mapping, and does not approach the method with much objectivity. While there may be some obvious disadvantages to using argument mapping in certain situations, none are provided here. Moreover, the only other method this article discussed was traditional prose, which is not an analytic method by itself, but a medium of production or dissemination. Despite a mere mention of conceptual modeling and flow charts, there was no substantive, formal comparative discussion on them.

Argument Mapping and Analysis of Competing Hypotheses (AM vs ACH)

Summary

This article presents a comparative assessment of argument mapping (AM) and Analysis of Competing Hypotheses (ACH) as analytic diagramming techniques. While the paper focuses primarily on the differing techniques in diagramming a decision making pathway, the author considers both as "complementary analytical frameworks".

Comparing the Techniques

Both techniques involve analyzing a given proposition (hypotheses in ACH; conclusions in AM), evaluating the evidence (evidence in ACH; reasons and objections in AM), and diagramming a visual representation of the relationships (matrices in ACH; box-and-line diagrams in AM). In ACH, the letters C, I, and N represent positive (consistent), negative (inconsistent), or nuetral relationships, respectively. In AM, arrows indicate a relationship between the reasons supporting or opposing the conclusion; color indicates whether the evidence is a reason (green) or an objection (red) for the argument. When a piece of evidence is neither a reason nor an objection (neutral or irrelevant), the creator of the AM may choose either to eliminate it from the map or to make it a different color (typically gray).

Multiple Propositions
Due to the manner in which each of these methods handles multiple propositions, ACH gets the advantage over AM. ACH incorporates multiple propositions simply by adding another column in the matrix. However, adding any additional propositions to an AM may result in a cluttered diagram with crossed lines and complicated pathways. To resolve this issue, it may be more appropriate to duplicate pieces of evidence, or even create an additional map, making it less efficient.

Multi-tiered Evidence
The paper uses an example from Psychology of Intelligence Analysis to demonstrate a situation in which AM may be a more efficient method. The chosen proposition is "Iraq will not retaliate forUS bombing of its intelligence headquarters," and the piece of evidence in question is "Saddam [has made a] public statement of intent not to retaliate". Often, as cited in this example, an additional piece of evidence may be necessary to establish a piece of evidence. When using an ACH, the analyst may need to construct another matrix to validate evidence. The AM technique allows for the addition another level of evidence within the same map. The paper refers to the multi-tiered evidence as "granularity". Granularity allows evidence of differing levels of abstraction to be present on the same map; "the higher the level on map, the more general or abstract the reason or objection".

Assumptions
AM also allows the user to add assumptions or warrants alongside the pieces of evidence. Incorporating an assumption into an ACH would force the user either to add a justification with the conclusion in its cell in the matrix, or combine multiple pieces of evidence together.

Moral choice and dialectic failure.

Myers, Robert J.. Society, Jul/Aug94, Vol. 31 Issue 5, p37-42, 6p; (AN 9407251855)

Summary
Myers calls dialectics a "logical term, used today for abstract disputation, devoid of any practical value". Plato contributes its invention to Zeno of Elea, intended to resolve dilemmas through a series of questions and answers. Myers cites its use within the Socratic Dialogue to identify shortcomings in conventional wisdom, and its later use by Hegel to show the reality of history as only that of ideas--"every idea, as it is affirmed by its truth, brings with it the idea that is its negation." Marx extended this concept into the debate of economic systems. The major historical uses of the dialectic incorporate three important components, which Myers calls the trinity of dialectics:

1. Thesis
2. Antithesis
3. Synthesis

Myers published this paper in 1994, when the fall of the Soviet Union (and, to him, Communism in general) was still a new phenomenon. Thus, his main point of contention was the Hegelian dialectic versus Marxist dialectic. Myers is highly critical of the dialectic explanation of history and its use to forecast the future. Instead, he advocates for an empirical explanation. He flippantly closes the paper, suggesting that "it (dialectics) has come from nowhere and will return to nowhere, allowing the human mind and associated intelligence to continue the search for truth in the abstract and to sort out empirically the good from the bad, the better from the worse, and to construct an ethical scale, weighed with democratic values". It is his contention that the dialectic was "simply a mental construct" and it has reached the end of its importance in "democratic" thought.

Dialectics – a commentary to Singer: “Global business and the dialectic”

Sørensen, Asger. Human Systems Management, 2002, Vol. 21 Issue 4, p267, 3p; (AN 9330655).

Summary

Sørensen uses this commentary on dialectics to build upon a case previously presented by Alan Singer, which considers the use of philosophy, particularly dialectic reasoning, in developing business and political strategy. He believes that the use of dialectics to examine dilemmas, tensions, and contradictions has not been widely used, largely due to its "guilt by association" with marxists and totalitarians.

He begins by providing an overview of the development of dialectics in the realm of philosophy. The main focus of the historical overview is to examine the development and opposing viewpoints of dialectics, from Plato (ideas), Aristotle (deduction), Kant, Hegel, Marx, and Engels (dialectical materialism).

Sørensen further points out that Singer sided with Hegel and Engels, who advocated its application to nature and culture. While Singer endorsed its use as a scheme of thought, he did not fully commit to its necessity in examining tensions.

This examination of dialectics closes with a brief mention of its implications in the realm of business and political strategy. By nature, dialectics is concerned with the truth of reality in its entirety, and is therefore at odds with basing political decisions on the wants and needs of the individual. He adds to this by hypothesizing that "introducing dialectics into business strategy might signal a shift in focus from the market to the organization, i.e., from coping with universal competition outside the firm to handling internal affairs, just as it is relevant in an economy dominated by the monopolies of multinational corporations."

Conducting a Proper SWOT Analysis: Going Beyond the Book

Conducting a Proper SWOT Analysis: Going Beyond the Book

At the most basic level, a SWOT analysis involves collecting data and information about one's organization and industry (competitors, etc.), processing and assessing the relevant data, and creating four lists. The four lists (usually the ultimate product of a SWOT analysis) are comprised of the answers to four separate questions:

• Strengths: "What does the firm do well?"
• Weaknesses: "What does the firm lack or do badly?"
• Opportunities: "What are the factors that can be exploited to the firm's advantage?"
• Threats: "What are the factors that can potentially reduce a firm's performanc, strengths or reason for existence?"

There are four critical factors that analysts should consider prior to executing a SWOT analysis:

1. Frequency. When and how often is it appropriate to carry out this type of analysis? Because of SWOT's inherent practicality and ease of use, it may be executed daily. An effective SWOT analysis would have to be continuosly modified, as elements in the organization's internal and external environments are constantly changing. Revising SWOT analyses on a daily basis would force analysts into a tedious routine of executing SWOT whenever new information emerges. Thus, it is necessary to conduct an analysis on when its use is most effective and appropriate for the organization. Opportunities to conduct SWOT include: periods of strategic review and planning; in reaction to competitors' launching of a new product; to assess and seize opportunities within the industry to remain competitive.
2. Information. It is important to consider what information is relevant, and how it is being obtained. Analysts conducting an effective SWOT analysis must assess the organization's strengths and weaknesses largely based upon relevant internal information; obtained from sources such as management or the organization's consultant. Additionally, analysts should exploit market research, industry literature, press releases (from competitors and other industry reporting), and growing or declining industry trends. All information relevant to the analysis must be reviewed, verified, and updated before dissemination of the final SWOT analysis findings.
3. Personnel. Who, and how many people are involved in the process? Because of its relative simplicity to execute, one individual may conduct a SWOT analysis. However, to guarantee a "balanced perspective," a minimum of four people should conduct a SWOT. The candidates with the most seniority are in the best position to assess the organization's strengths. Those assigned to assess the organization's weaknesses should be objective and able to maintain an impartial position when identifying internal flaws and shortcomings. Opportunities should be evaluated by creative thinkers and positive individuals who are able to consider and evaluate consequences in the long-term scope. Those tasked with addressing threats must be extremely knowledgeable about both the organization and the overall industry. In order to prevent bias and a group's influence over the others, those tasked with assessing seperate components should work in separate physical locations.
4. Dissemination. How should the results of a SWOT analysis be presented to executives? Analysts may present the findings in the form of a "shopping list" of internal and external factors that will likely impact the organization in the short or long-term. This product may include a multi-page document. Analysts may also create a 3-by-3 matrix with internal factors (strengths and weaknesses) listed on the left-hand side, and external factors listed across the top of the matrix. This product can be presented on one page, allowing the decision maker to visually match the elements being analyzed.

Strategy: Create and Implement the Best Strategy for Your Business (Ch. 1&2)

Harvard Business School. Strategy: Create and Implement the Best Strategy for Your Business. Boston: Harvard Business School Publishing, 2005.

The Strategy volume of Harvard's Business Essentials dedicates the opening two chapters to SWOT analysis. This reading serves as a primer to strategic thinking for business students and leaders. The authors imply that SWOT should be the basis for goal and strategy development within a firm. The first chapter focuses on the external analysis of factors that influence analysis and, ultimately, strategic goals of a company; the second focuses on the analysis of internal factors.

External factors are the threats and opportunities that exist throughout the company's external environment. This portion of the SWOT analysis considers factors such as customers (current and future), competition, supply chains, regulations, potential mergers, pricing, uncertainty, technology, and macroeconomic trends. These factors may be perceived as either threats or opportunities, depending on their level of impact to the company, as evidenced by the analysis. The product here is the ability to evaluate potential strategic options. Additionally, the key to an effective analysis is to be cognizant of the company's relative position in the competitive arena. This chapter reinforces these notions about the external environment with a brief discussion of the importance of incorporating Porter's Five Forces Model in order to gauge one's position in the competitive arena.

The Strengths and Weaknesses component of the SWOT analysis is an internal assessment of the company. Strengths and weaknesses can be identified by evaluating the company's brand power, employee and management culture, financial condition, cost structure, and technical skills, among others.

The book provides a nine-step guide to executing and organizing the collective information:

1. Select a well-respected person to head the analysis. He or she should be expected to remain objective.
2. Establish a SWOT team of individuals from throughout the company.
3. Collectively brainstorm the strengths of the company.
4. Record strengths on a flip chart, avoiding duplication.
5. Consolidate ideas together on a wall. Combine possible duplicated answers under common headings.
6. Define the strengths (remain focused on strengths and not solutions).
7. Identify the top 3.
8. Summarize on a single flip chart page.
9. Repeat steps 2-6 for weaknesses.
   

The book suggests following the same steps for conducting the external analysis of the firm, but it recommends integrating some individuals (suppliers, consultants, etc.) from outside the company to help identify the opportunities and threats. Once the findings are completed, the team should construct a consolidated report for executives and management personnel to consider when modifying strategy.