Using Search Engine Optimization For Intelligence Analysis

SEO Analysis Now - A Site For Using SEO in Intelligence Analysis
Rated: 4 Stars out of 5

As a final requirement of this course, I had to research and report findings on an analytical technique of my choosing. In addition, I had to test-out and apply the technique in order to reveal its true strengths and shortcomings; as well as come up with a how-to guide to use the technique. For my project, I chose to conduct a Search Engine Optimization (SEO) Analysis on the Websites of two popular coffee shops, Starbucks (which is well established) and Caribou Coffee (which is slowly gaining popularity) and reflect on how this process can be applied to Competitive Intelligence (CI), to Law Enforcement Intelligence (LEI), or to the National Security sector. I chose SEO not only because it is an emerging analytical process and can be useful to intelligence analysts, but also because I found it quite intriguing and fun.

SEO provides a way to gain insight into a Website’s audience.

If we know who an audience is (age, gender, ethnicity, education, affluence, etc), how they behave (what other Websites, or types of Websites, they visit), from where they log on, when they visit, and what other sites direct their traffic (as well as what their general interests are), then we can make assessments and predictions about how to either promote their behavior (steering them toward a particular site – useful for CI & marketing purposes) or how to counter that behavior (keeping them away from sites – useful for LEI & N’tl Sec purposes).

For more detailed information about how SEO can be used for Intel analysis, please check out my project:

SEO Analysis Now - A Site For Using SEO in Intelligence Analysis

(The image below is a geographical search index comparison of online users searching for Caribou Coffee [left] and Starbucks [right]. Images provided by Google Insights for Search)

Bayesian Statistics In The Real World Of Intelligence Analysis: Lessons Learned

Bayesian Statistics In The Real World Of Intelligence Analysis: Lessons Learned
By Kristan Wheaton, Jennifer Lee, & Hemangini Deshmukh
Journal of Strategic Studies, vol. 2 n.1
February 2009

Summary:
In this article, Kris Wheaton, in collaboration with Jennifer Lee and Hemangini Deshmukh, agree that alternative methods, ones that are more structured, should be applied to the intelligence process in order to improve intelligence analysis. Recognizing the potential that Bayesian Statistics can bring to the field of intelligence, the author questions the ease in which entry-level intelligence analysts can apply and use this advanced statistical method.

Following the model of an experiment conducted by Gerd Gigenrenzer to test the accuracy of a diagnosis by two groups of doctors (with one group using traditional statistic formulations [5% or .05] and the other using natural frequencies [5 times out of 100]), the author tested 67 Senior Intelligence Studies students at Mercyhurst College. The findings of Wheaton’s experiment were extremely similar to that of Gigenrenzer’s, showing that groups who receive natural frequencies have a much higher rate of being accurate when using Bayesian statistics (79% versus 18% accuracy). This accuracy is attributed to the power of ‘framing’ questions. The author concludes, “natural frequencies are an effective method for encouraging Bayesian reasoning.”

In addition to the experiment, the article covers a brief how-to and overview of Bayesian Analysis. In short, Bayesian statistics is particularly useful due to its ability to take-in-account probabilities of one event affecting another, allowing the analyst to rationally update a prior assessment in light of new evidence. This process also helps in the reduction of two very common cognitive biases, the vividness and recency biases. See article for relevant examples of how the Bayes Theorem can be applied to intelligence-related issues.

The Bayes Theorem is illustrated below:

Bayesian Analysis For Intelligence: Some Focus on the Middle East

Bayesian Analysis For Intelligence: Some Focus on the Middle East
By Nicholas Schweitzer
Approved For Release 1994
CIA Historical Review Program
02 July 96

Summary:
Nicholas Schweitzer suggests that advanced analytical methods, such as Bayesian analysis, should be used to aid analysts in an age where information flows continue to rise. In an effort to test Bayesian Analysis as a tool for intelligence analysts, he used the technique among a group of intelligence analysts to assess complex political-military problems. The Middle East was chosen as a discussion point because of the level regional complexities.

Schweitzer defines Bayesian Analysis as “a tool of statistical inference used to deduce the probabilities of various hypothetical causes from the observation of a real event. It also provides a convenient method for recalculating those probabilities in the light of a continuing flow of new events…the ‘rule of Bayes’ states that the probability of an underlying cause (hypothesis) equals its previous probability multiplied by the probability that the observed event was caused by that hypothesis.”

How to:

Because of limitations, the Bayesian technique can only be applied where certain criteria are met. First, the question to be answered must lend itself to formulation in mutually exclusive categories (i.e. war vs. no war); the insertion of overlapping possibilities reduces accuracy of the Bayesian technique. Second, the question must be expressed as a specific set of hypothetical outcomes. Third, there should be a fairly rich flow of data that is at least peripherally related to the question. Lastly, the question must revolve around the type of activity that produces preliminary signs and is not largely a chance or random event. If this criteria is met then:

1. Assign numeric probabilities to hypotheses. The sum of the values must equal .1 or 100%. Because the examination of political/military affairs and events do not automatically yield quantified results, the possible outcomes (hypotheses) have to be quantified. Schweitzer asserts that implementing a Delphi method is the best solution to quantify possible outcomes. He suggests the following procedure to do this:

• Use analysts who are experts on the subject matter (preferably ones who are working on the situation with you)
• Establish a periodic routine for reporting
• On the first day of the period, each of a number of participating analysts submits the items of evidence they have seen since the last round.
• Submissions should be in the form of 1-2 sentences summarizing the item, along with the date, source, & classification.
• The inclusion of relevant items and exclusion of irrelevant items is up to the discretion of the analyst.
• A coordinator consolidates the items, resolving differences of wording, emphasis, and meaning, and returns the complete list of items to the participants.
• On the following day, the analysts (working individually) evaluate the items and return the numerical assessments
• *the use of a group of analysts, as opposed to a single expert, is highly recommended*
  

2. Assess and quantify the evidence that supports/negates the hypotheses.
3. Calculate the new probabilities according to the rule of Bayes:

E is an event, an “item” of intelligence
H is a hypothesis, a hypothetical cause of events
Hi is one of a set of n mutually exclusive hypotheses
P(Hi) is the starting, or “prior” probability of a hypothesis
P(E/Hi) is the probability of an event given Hi, of an event occurring, given a particular underlying cause
P(Hi/E) is the probability of a hypothesis given E, the “revised” probability of a hypothesis, given that a particular event has occurred.

Strengths (please see article for further explanation):

• Allows for the weighting of evidence
• Provides transparency in intelligence assessments
• Forces the consideration of alternative possibilities
• Quantifies analysis instead of using words of estimative probability
• Displays the trend toward an outcome quicker than the analyst can typically realize it on their own
• Incorporating the Delphi method adds credibility to the assessment when presented to managers and decision makers.
  

Weaknesses (please see article for further explanation):

• Limited applicability
• Data problems – can exist in deciding which information is relevant and should be included, as well as what weight values should be given to evidence.
• Source reliability – what is the best practice to account for this
• “Negative evidence”- the absence of any positive evidence may in itself be highly indicative of something
• Problems over time – problems in using this method in a project continuing over many months
• Problem with numbers – cannot use the probability of ‘zero’ (doesn’t work mathematically or analytically) therefore extremely low probabilities must be indicated by a very small number. Also, some people have difficulty thinking in, and assigning, probabilities.
• Subject to bias and manipulation – this is one of the reasons for which the author suggests using a group of experts/analysts to assign probabilities.
  

Intelligence Requirements and Threat Assessment

Intelligence Requirements and Threat Assessment
Ch. 10 in
Law Enforcement Intelligence: A Guide For State, Local, and Tribal Law Enforcement Agencies
by, David L. Carter, Ph.D.
School of Criminal Justice
Michigan State University

Summary:
Chapter 10 of the Law Enforcement Intelligence: A Guide For State, Local, and Tribal Law Enforcement Agencies defines an intelligence gap as an unanswered question during the analytical process where “critical information is missing that prevents a complete and accurate assessment of an issue.”

In the past, a “dragnet” approach was the traditional method for filling information gaps. This approach set out to collect mass amounts of data in the hopes that the desired data was collected. The requirements-based approach to filling gaps seeks to make collection more objective, more efficacious, and less problematic. Dr. Carter asserts that this approach is scientific in nature and that “the intelligence function can use a qualitative protocol to collect the information that is needed to fulfill requirements. This protocol is an overlay for the complete information collection processes of the intelligence cycle.” The diagram below compares the Tradition-based and the Requirements-based approaches to filling intelligence gaps:


Carter states that organization (or even intelligence need) may have to develop its own unique process to filling information gaps, however the following acts as a good guide to follow:

1. Understand your intelligence goal
2. Build an analytic strategy. (What types of information are needed? How can the information be collected?)
3. Define the social network. (Who is in the network? How does their business cycle function? Who has access to the information needed? What is the social behavior?)
4. Define logical networks. (How does the organization operate? Funding sources. Communications sources. Logistics and supply.)
5. Define physical networks.
6. Task the collection process. (Determine the best methods of getting the information)
7. Get the information.
8. Analyze the information.
   

Gap Analysis: As Is or To Be, What is the Question?

Gap Analysis: As Is or To Be, What is the Question?
By Dorothy Ball,
Four Thought Group

Summary:
This article describes how to use gap analysis in Business Process Improvement (BPI) strategies, relating the method to Health Care organizations. In this summary, I have attempted to relate the gap analysis process, as the author uses it, to the intelligence field - identifying and overcoming intelligence gaps.

Dorothy Ball, a senior policy and business consultant at Four Thought Group, Inc., states that gap analysis is an effective solution for businesses and organizations that have a service orientation (which includes for-profits, non-profits, and government agencies). To paraphrase, gap analysis is a method for an organization to improve performance or make gains by identifying the potential needs for that organization to move from where they are (or what intelligence you have) to where they want to be (or what intelligence is still needed). Ball describes gap analysis as a method to develop a roadmap that gets you from “where you are now (As Is) to where you want to be (To Be).”

How to:

1. Identify what your organization looks like now (or what intelligence/information you currently have available) and what you want your organization to look like (or what intelligence/information you desire). Needs for improvement (more intelligence) is often indicated by changes such as policy, resources, environment (or events that spark inquiry). Changes may be event-driven, or ongoing.
2. Understand the Business Process (or collection process). Ball describes the business process as “a collection of related, structured activities, or chain of business functions, activities and tasks, that produce each specific service or product… Each business process consists of inputs, method, and outputs. The inputs are required before the method can be put into practice to achieve the outcome. When the method is applied to the inputs then certain outputs will be created.”
3. Use comparative analysis techniques to identify what is needed to get you from where you are (the Intel you have) to where you want to be (the Intel desired). Examination of the current process, and the modeling of the new process, may be necessary in order to discover the interrelationships/interconnectedness of how the current process can get you the desired results.
4. Create a plan for implementation.
   

Introduction to Game Theory

Introduction to Game Theory
by Open Options Corporation - 2007

Summary:
Open Options Corporation defines Game Theory as "a branch of applied mathematics and economics that studies strategic situations where there are several stakeholders, each with different goals, whose actions can affect one another." According to the author, the benefit of conducting a Game Theory analysis is that it reveals the interactions of likely outcomes in situations where the end result is dependent on the actions of others, giving the analyst a better understanding of the situation and courses of action.

After a brief Game Theory history and credential check, Open Options discusses how Game Theory is applicable in business. Since the world of business focuses on competing against others with the goal of maximizing your own rewards, Game Theory is a natural fit to analyze possible business strategies.
"However, real business decisions have significant complications that are often ignored by abstract, academic game theory":

1. Real business decisions almost always have many players, a challenge for classical game theory.
   
2. Complex relationships among the players sometimes exist (i.e. some common and some competing issues exist between players).
   
3. Business outcomes are often not easy to reduce to a common measure for value such as dollars or expected utility. Rather, strategic interests, long term relationships and the personal goals of the CEO or founder can be critically influential.

Other advanced Game Theory options exist to help model and solve complexities within business strategies, these include: n-player, non-cooperative, nonzero-sum, non-simultaneous, asymmetric, & ordinal game theories.

Nash in Najaf: Game Theory and Its Applicability to the Iraqi Conflict

Nash in Najaf: Game Theory and Its Applicability to the Iraqi Conflict
Brightman, Hank J. 2007. "Nash in Najaf: Game Theory and Its Applicability to the Iraqi Conflict." Air & Space Power Journal 21, no. 3: 35-41. Military & Government Collection, EBSCOhost (accessed April 20, 2009).

* Actual article was accessed through Mercyhurst College's EBSCOhost subscription - link to article was found as a Google cached site.

Summary:
The 2007 article written by Dr. Hank Brightman, an associate Criminal Justice professor at Saint Peter's College and a USN Information Warfare Officer at the US Naval War College's War Gaming Department, posits that game theory suggests that US and Coalition forces stationed in Iraq will suffer an increasing rate of casualties the longer they remain in Iraq. The reasoning behind this statement is that both Domestic Insurgents (DI) and Indigenous Security Forces (ISF) will "turn away from attacking each other towards a point of mathematical corruption." It is at this theoretical point that US and Coalition forces will be the target of ISF intelligence-fed DI attacks. ISF refers to Iraqi military as well as state and local police; DI refers to various domestic insurgent groups within Iraq.

Brightman reviews the "prisoner's dilemma" and zero-sum game theory, and states that the prisoner's dilemma is an example of a simple form game (SFG). SFGs have two players that strive for the highest payoff at the end of a move or event (known as the Pareto Optimal position). As SFG applies to the Iraqi conflict, ISFs and DIs are the two players.
Extensive Form Games (EFG) are more complex than SFGs as they feature two or more players that are engaged in move-for-move exchanges, leaving the players less concerned with intermediate payoffs and focused on the ultimate payoff. EFGs are typically not zero-sum games and are distinguished by multiple moves, leaving players not only focused on broad strategy, but also smaller sub-strategies that counter the other players' moves. However, as time progresses in EFGs, the model becomes susceptible to "strange attractors" that "affect the players' willingness to adhere to previously stated rules and therefore decrease the overall stability of the game." US and Coalition forces would be considered strange actors in both the SFG and EFG models.

As time elapses the players (ISF & DI) become more frustrated and ultimately begin to reduce their expectation for the ultimate payoff. As this happens, each player considers negotiating with the opponent as a means of reducing losses - this is known as bargaining toward equilibrium, or a Pareto Improvement). "When both players have reached a point at which they can achieve the highest aggregate payoff, the game ends in preferred equilibrium."

"However, the influence of strange attractors in a model that will become increasingly unstable (bifurcated) over time often induces the players to hasten their desire for a Pareto Improvement position instead of a superior (Pareto Optimal) position - even though doing so may lessen their ultimate payoff." The strange attractors cause frustration which preempts the players from achieving the preferred equilibrium (the point in the prisoner's dilemma where both prisoners remain silent and gain the most) and instead yield the inchoate or Nash equilibrium (the point in the prisoner's dilemma where both prisoners confess to the crime).

*Author's note: the article delves further into the SFG and EFG situations as they relate to the Iraq Conflict, however, due to length they have been cut from this summary.

Seeing Red: Creating a Red-Team Capability for the Blue Force

Seeing Red: Creating a Red-Team Capability for the Blue Force
By Colonel Gregory Fontenot, U.S. Army, Retired
Military Review, September-October 2005

Summary:
In response to the difficulties the US Army was having in the Operational Environment in Operation Iraqi Freedom, Colonel Gregory Fontenot suggested that Red Teaming could better prepare the Army for the challenges they faced. He states that red teaming is “uniquely suited” for critical analysis when “executed by trained, educated, and practiced team members with access to relevant subject matter expertise.” Red teaming will also provide the soldier with a better understanding of the adversary through the adversary’s cultural lens.

Click on image for a more-clear view

Red Team Best Practices:

• Political and military cultures must embrace Red Teaming
• Embracing criticism is foremost among the internal cultural challenges
• Political and military organizations must prize intellectual assessments and value intellectual preparation as seriously as physical preparation
• All services must institutionalize red teaming by way of a doctrinal foundation and organizational support structure
• Leaders must provide the top cover to protect and mentor red teamers, charter the red team and the organization to solve problems, and encourage robust interaction between red and blue (in which blue learns).
• Leaders must balance red team independent action with accountability to the command
• Red teaming must be employed throughout the decision making process but with calculated application – not too heavy, not too light – so promising ideas can thrive without prejudging
• Red teams must be chartered to continue to learn and adapt
• Red team members must be highly qualified experts in their fields and have sound reputations and even temperaments
• Individuals and teams must be educated, trained, and certified in the context of doctrine on a recurring basis
• The red team member presenting the opposing or alternate view must be credible, perceptive, and articulate
• Red team members must be intellectually honest with a heavy dose of ego suppressant

Red Teaming for Law Enforcement

Red Teaming for Law Enforcement
By Michael K. Meehan, Captain, Seattle Police Department

Summary:
Michael Meehan posits that, just as the military and private industry use red-teaming techniques to discover abilities, vulnerabilities, and limitations; the law enforcement community can do the same in order to reduce threats and improve responses to issues of homeland security. The author states that red teaming refers to a variety of exercises, but the “most basic level of red teaming is to conduct peer review of plans and policies to detect vulnerabilities or perhaps to simply offer alternative views of scenarios.” Meehan also lists a variety of definitions given by other experts and organizations including the DHS Exercise and Evaluation Program which states that red teaming is, a “group of subject matter experts with various appropriate disciplinary backgrounds, that provides an independent peer review of plans and processes, acts as a devil’s advocate, and knowledgably role-plays the enemy using a controlled, realistic, interactive process during operations planning, training, and exercising."

The role of the red team is to “evaluate a target or tactic, but not the likelihood that a particular target will be attacked. Red team members are strategists who identify what to attack and domain experts who identify how to attack.” They are adaptive to the strategies of the blue team, allowing the blue team to engage in both prevention- and protection-related activities.

The role of the blue team is to “think about how surprise attacks might occur, identify indicators and warnings of those attacks, collect intelligence on those indicators, and adopt defenses against the most likely possibilities or at least provide early warning.”

Meehan describes two very common types of red teaming – analytical red teaming and physical red teaming. Analytical red teaming “provides a potential adversary’s view of threats, vulnerabilities, and countermeasures. Without testing the physical limitations of antiterrorism measures, analytical red teaming can challenge prevailing views, prevent surprise, allocate resources, and expand the bounds of imagination. Analytical red teaming can occur as part of a discussion-based exercise or as a standalone activity.”
Physical red teaming involves the physical portrayal of an actual adversary executing the tactics and strategies carried out by enemies.

Strengths:

• Offers an element of surprise
• Tests the fusion of policy, operations, and intelligence
• Highlights deviations from doctrine
• Improves blue team capabilities through practice
• Improves information sharing

Weaknesses:

• Preparation needed to plan scenarios
• Interpretation , distribution, reception of lessons learned can vary

How to:

1. Determine the objectives or desired results
2. Communicate with government and private partners
3. Determine the scale and type of exercise, the type of scenario, the method of evaluation, and the documentation plan
4. Develop the scenario
5. Identify and train the appropriate participants
6. Conduct and evaluate the exercise
7. Prepare thorough documentation
8. Evaluate the performance
9. Develop the improvement plan
10. Make required and desired improvements
11. Exercise again

Countering Terrorism: Integration of Practice and Theory

Countering Terrorism: Integration of Practice and Theory
An Invitational Conference
FBI Academy, Quantico, VA
Feb 28, 2002
Sponsored by the FBI Behavioral Science Unit

Summary:

The FBI's Behavioral Science Unit identifies decision tree techniques and data mining as "highly efficient methods for processing large volumes of data." However, they add that they need to be "tailored to the unique cultures in which they would be used," and that their use depends on a cooperative effort by those that design such methods with those who have to analyze them. The decision tree decision-making methodology is recognized by the FBI as one method to standardize responses to threats and to understand the seriousness of those threats.

After collaboration efforts to receive and organize incoming information have been established with a technical advisor and a decision tree has been created, using the decision tree can be broadly applied due to it's low technical skill demands. The FBI also adds that decision trees should serve only to report information to a decision maker, reinforcing the idea that decision trees should be suggestive - not to actually state the decision to be made.

Appendix 6 gives the most useful information regarding decision tree analysis. In this appendix, it defines decision trees as a tool to aid decision making. "The idea is to concretely identify the choice points and map the sequence of decisions from beginning to end."

Steps:

1. Started with a decision that must be made - the FBI uses the example of whether or not to arrest a suspect. Represent this decision with a square. This should be drawn on the left-most side of the paper/screen.
   
2. Using lines drawn outward and to the right, identify each possible solution. Write each solution on each line.
3. At the end of each line, the results are considered. Use a circle is drawn at the end of the line to identify if choices are available
   
4. If another decision is possible, draw a square with that decision listed.
   
5. If there is a final consequence, a solid dot is drawn with a filled-in circle at its end.

Evaluating the decisions:

The FBI identifies the procedure for choosing a decision as backward induction analysis. In order to do this first assign a number that represents the worth or utility of the final consequence (filled-in circle). Use a 0.0 to 1.0 scale to identify worth. Next, assign a sum to each event node (the circles) that represents the expected utility of the node - this is the weighted average utility for that event node. "Finally, each decision node is a assigned a number that is the maximum value of the nodes that branch out from it."

According to the Behavioral Science Unit the benefits of using decision tree analyses are: 1) that the possible choices are explicitly made; 2) the choices are evaluated by the importance of the outcome as well as quantified with the probability for that outcome; and, 3) displays communication flow.
The FBI, once again, states that "decision trees can be used to guide decisions, not make them. The final decision is left up to the operator."

Decision Tree Analysis: Drawing Some of the Uncertainty Out of Decision Making

Decision Tree Analysis: Drawing Some of the Uncertainty Out of Decision Making
by William E. Marsh, PhD

Summary:

This article was written primarily to describe the benefits and how-to's of using decision trees (which Marsh commonly refers to as 'decision analysis') to make decisions in the livestock business - particularly swine veterinary practice. Although Marsh's target audience is obviously for those who either own swines or practice medicine on them, his article draws out the basics information needed to conduct a decision tree analysis; and he does so in a easy-to-understand and practical manner. For the purposes of this blog post, and out of respect of my targeted audience, I will leave out all swine references, examples, and jokes.

Marsh essentially defines a decision tree as a visual representation that logically depicts a time-sequenced flow of events with the purpose of informing a decision maker with the probability of various outcomes. It is a structured approach to making decisions when uncertainty exists that helps us to quantify and "consider the effects of chance on the outcome of a given decision." Marsh bluntly states that, "In using decision analysis, it is important to understand that the objective is not to make a prediction...[but rather, it] uses probabilities...to provide a guide for what should be done."

Steps to conducting a decision tree analysis:

1. Define the problem - what is it that we are trying to make a decision about. This will be represented visually using a rectangle (or box) around the decision to be made. Marsh refers to this as the "decision node."
   
2. Identify a "mutually exclusive, exhaustive list of all possible courses of action to address the problem." Each course of action should have a "branch" stemming out from the decision node.
   
3. Create a "chance node" (represented with circles) that represent the possible outcomes of a course of action. Different outcomes should stem out from this chance node.
4. Sometimes branches emanating from decision and chance nodes can lead to other decision nodes - repeat steps 2 & 3 if this occurs.
5. Indicate the associated probability (likelihood) that a particular outcome stemming from a chance node will occur. Probabilities are quantified with a value ranging from zero to 1. Therefore a probability of 0.6 would be the equivalent of a 60% chance. Use your experience and knowledge, as well as any conclusions from literature or other supporting data to assign a probability value.
   
6. The sum of the probabilities of all outcome branches stemming from a single chance node must equal 1.

Marsh does not clearly identify any cons to conducting a decision tree analysis, however, it is quite obvious that he is a strong proponent of using this technique to strengthen the decisions he makes.

Argument Mapping - The Basics

Argument Mapping - The Basics
based on the heuristics and Rationale software developed by Austhink

*Author's Note: Although this guideline does not delve into the pros and cons of argument mapping, it does give a good idea of how to construct an argument map - whether you are using this particular software, or if you are making an argument map with pencil and paper.

Summary:

The "Argument Mapping - The Basics" sheets provide the reader with a outline of understanding for what argument mapping is, the terms used in argument mapping and logic, as well as some important rules of logic that you must keep in mind when structuring an argument map. Argument maps start with a conclusion, which is at the tip of the pyramidal hierarchy, with reasons and objections listed below the conclusion. Reasons can have co-premises, and co-premises can have other reasons to support the claim listed above. Co-premises can also work together to support particular reasoning. Objections are listed to oppose the conclusion or reason and can have rebuttals listed underneath the objections.

Similar to games of strategy (chess, risk, etc.), there appears to be a learning curve with argument mapping. It takes some time to get the 'feel' of the game and to fully understand the rules, but with time, the process become quick and effortless.

Important information within the document:

Definition of Argument Mapping: "Argument mapping is a way to visually show the logical structure of arguments. You break up an argument into its constituent claims, and use lines, boxes, colors and location to indicate the relationships between the various parts. The resulting map allows us to see exactly how each part of an argument is related to every other part."

Other important definitions to know when creating argument maps:

• Argument: a claim and reason(s) to believe that that claim is true.
• Simple argument: the building block of all arguments, consisting of one claim and one reason (with two or more co-premises).
  
• Complex argument: has several simple arguments linked together (the diagram below illustrates a complex argument)
  
• Conclusion: the main point an argument is trying to prove, usually a belief. Also called the position, the main claim, the issue at hand.
• Reason: evidence given to support the conclusion.
• Co-premise: the subset of a reason. Every reason has at least two co-premises, and each of these co-premises must be true for the reason to support the claim.
• Objection: a ‘reason’ that a claim is false; evidence against a claim
• Rebuttal: an objection to an objection.

Syntax of an Argument Map:


Of note:

• Arguments can have many claims, many reasons, many objections and rebuttals, but only one conclusion.
• Distinguish a claim with a single reason (made up of two co-premises) from a claim with two independent reasons.
• The exact structure of an argument is very important. For example, if side A has two good reasons to conclude something, and their opponent (side B) thinks one of those reasons is bad, then A’s conclusion may still be true/warranted if the remaining, unobjected-to reason is convincing.
• An argument map can represent a debate by showing exactly where two sides disagree on the issue.
  
• Argument maps show the structure of the argument/debate – every box is not necessarily true, but the first step is to understand the structure of the argument.

Rules within each box:

• Declarative Sentence: Each box should have a full sentence (not a phrase) and should be declaring something, taking a position (whether it is true or false).
• No Reasoning: No box should have reasoning going on inside it, only single claims. The reasoning is represented by the arrows and locations in the map. Look for words that indicate reasoning (e.g. because) and translate the reasoning into the map.
• Two Terms: Each box can only have two main terms, so that each box is either true or false, not both. If you have more than two terms in a single box, separate them into multiple boxes.

Rules within each simple argument:

• Assertibility Question: All reasons for claims must answer the question: “How do we know that [insert specific claim here] is true/warranted?” You are asking what evidence allows one to assert that the claim is true. Every claim box should have a reason box below it that answers this question.
• Holding Hands: Applied horizontally within each simple argument. Within each reason, a term stated in one co-premise must be mentioned in one of the other co-premises in that same reason (if it is not in the claim above it – see the Rabbit Rule below). The terms must ‘hold hands’ within a single reason if they are not already accounted for by the Rabbit Rule.
• Rabbit Rule: Applied vertically, between a claim and each of its reasons, and is combined with the Holding Hands rule. “You can’t pull a rabbit out of a hat.” Using these two rules for each simple argument, you make sure that every term mentioned in each box is found in one of the others.
  

Enhancing our Grasp of Complex Arguments

Enhancing our Grasp of Complex Arguments
By Paul Monk and Tim van Gelder
This paper was presented by Paul Monk as a plenary address to the 2004 Fenner Conference on the Environment, Australian Academy of Science, Canberra, 24 May 2004

Summary:

What argument mapping is used for:

• To structure, communicate, and correct arguments of any degree of complexity
• To govern deliberation, keeping it on task, target use of evidence, specify disagreements, and make the process more efficient
  

Verbiage tends to make people miss what is being said and asked and encourages people to grasp tightly to their own thoughts. Monk and van Gelder posit that the use of only language, writing processes, and mental cues are too primitive to completely understand the complex arguments that people are now faced with. They continue by stating, “We conduct complex arguments as if a combination of holistic apprehension, intuitive judgment and natural language were sufficient for handling them [arguments]. None of us, I think, would consciously make that claim. We do what we do by tradition and by default, not because we have thought through why we do it, how it works and whether it serves us well.”

Playing the game of tic-tac-toe (on a 4x4 grid or larger) without using actual gridlines is used to illustrate the point that our working memory struggles without the presence of a visual aid (the grid). Cognitive blind spots and biases, the methods used to record and communicate arguments, and separation of disciplines due to different idiolects all accentuate the problem of our limited working memory.

Just as maps and charts allow us to navigate land and sea with more ease than an oral explanation, a map can help us visualize and navigate through problems and arguments. To map an argument, you must start with a proposition, or chief contention – this contention is entered into a white box and placed at the top of an argument map. Supporting claims are color-coded green, while objections are coded red. Claims are organized in a pyramidal hierarchy to maximize the appearance of evidential and logical relationships. The first set of claims (top level) begs the question “what are the distinct arguments provided for the main point (the chief contention)?” Subsequent levels are asked, “Do they support all of these primary arguments with further evidence? [and] Do they countenance any objections to their argument and rebut them?

The authors use the article Coalition of the Willing? Make That War Criminals, which discusses whether or not a preemptive strike on Iraq would constitute a crime against humanity, to demonstrate how argument mapping is useful. (See Image Below)


Advantages of argument mapping over prose:

1. It makes explicit logical relationships that the linearity and abstractness of prose cannot help but obscure.
2. The map offers an instant and effortless scan-ability of the overall structure of the argument, which you simply cannot derive from prose.
3. There is an ease of movement from the detail to the overview that is far more difficult in the case of prose.
   
4. There are unambiguous visual clues as to the significance that particular details have, due to the hierarchical ordering of the structure, the color-coding of the individual boxes and the inferential relations between boxes.
5. A map offers a visual clarity as to the limits of a debate, whereas prose obscures these limits or labors to spell them out.
6. The cognitive burden imposed on us by the task of analyzing a piece of prose is drastically reduced in the case of a map, for the same reasons that it is reduced in moving from a prose description of London to a map.
7. For any given proposition, all claims are integrated into a single structure, instead of consisting of various component parts, which then have to be assembled by whoever happens to be trying to comprehend the argument in question.
   

*Author’s Note: Tim van Gelder has done extensive research in the field of argument mapping and is the leading mind behind Reason!Able, a computer program designed for argument mapping. Reason!Able has now evolved into Rationale. See Video Below.

The Socratic Method: Leveraging Questions to Increase Performance

The Socratic Method: Leveraging Questions to Increase Performance
by Maj. Norman H. Patnode, USAF

Summary:

Explaining the Socratic method:
Maj. Patnode describes the Socratic method as a means for “moving people along.” In essence, is a method that uses questions to challenge the beliefs, experiences, and paradigms that that people hold in an effort to reexamine the possibilities that may exist. The ultimate goal of this method is to achieve “greater understanding and increased performance.”

How to:
Maj. Patnode describes the Socratic method as having two elements:
1. Questions
2. Knowing where you want the conversation to go (or move)

Patnode states that the most important aspect of this method is to remain focused on your goal. The questions you ask must lead others to your desired end state. He suggests using a vision story as a way to “capture and communicate the desired outcome.” The most difficult part of this method is trying to figure out what questions are the right questions to ask. Once the questions are formed, it is important to remain quiet after you ask them – even if there is an awkward silence afterward. It is important to ensure that you do not answer your own questions – if someone is unable to answer the question, he suggests backing up and breaking the question into smaller bits.

Responses to the question will come in the form of answers and statements. Patnode states that both responses contain valuable information which should guide you in the next step: “Knowing where the group (or individual) needs to go next, and how big a step that group (individual) is capable of taking will help you form the question that will move them forward.” Patnode suggests that using Bloom’s Hierarchy of Learning will aid you in determining what the likely next step is. It is also helpful to have a understanding of the concrete data and facts to help guide your questions toward your goal.

What is the Socratic Method?

What is the Socratic Method?
excerpted from Socrates Café (pgs. 18-24) by Christopher Phillips

Summary:
Gregory Vlastos, a Socrates scholar and philosophy professor at Princeton, asserts that the Socratic Method (AKA the dialectics method or elenchus) is “among the greatest achievements of humanity…[it is] a common human enterprise, open to every man…[that] calls for common sense and common speech.” Christopher Phillips takes this assertion a step further by adding that the Socratic method goes beyond common sense through the examination of what sense is.

The foundation of the Socratic method is to seek out truth through the use of dialogue – commonsensible reasoning and fact seeking will ultimately strip out any prejudices and biases, leaving only truths and realities. It is designed to “reveal people to themselves.” The author suggests that this use of honesty would require us to constantly scrutinize our own convictions. In addition, Phillip posits that the use of a Socratic dialogue will reveal just how pluralistic people are. It will iron-out abstract concepts and bizarre questions, revealing the relationships between relevant human experiences. “What distinguishes the Socratic method from mere nonsystematic inquiry is the sustained attempt to explore the ramifications of certain opinions and then offer compelling objectives and alternatives.” Phillips compares this method to the scientific method, but unlike the scientific method, Socratic dialogue can investigate immeasurable beliefs like love, joy, suffering, and sorrow.

While the Socratic method is designed to reveal truth, oftentimes it leaves us with a sense of uncertainty that makes us question our original positions, and quite possibly, it leaves us more troubled than where we started.

*Authors Note: I believe the above statement points out both the pros and cons of this method. Using the Socratic method can apparently lead two parties to come to a common agreement about a subject or concept – or it can leave the parties both questioning their original viewpoints. The positive aspect is that questioning can leave one open to new possibilities outside the original frames they’ve constructed – thus limiting cognitive biases. In addition, the uncertainty will surely reduce analytic confidence, which can be a good thing if it reflects the true ambiguity of a concept or subject. However, the detriment is that this sense of uncertainty may ultimately confuse the analyst. If the analyst feels as if he/she is seeking one truth while ignoring the possibility that multiple truths may exist, an analysis may be further sidetracked after a time-consuming Socratic debate. In addition, using the Socratic method for purposes for forecasting is problematic in itself – if the Socratic method is to seek truth, truths of future events do not yet exist. It is for this reason analysts use (or should use) words of estimative probability. Alternative possibilities always exist in matters of predictive analysis and forecasting. Therefore it may be safe to say that this method would only be applicable to the examination of past and present concepts and subjects. If a truth is found, an analyst can then use that truth as a starting point for predictive analysis.

*There are also many forms of dialectics: Socratic, Hegelian, Marxist, Brahmin/Hindu/Vedic, Jain, Buddhist, etc.

From Business Intelligence to Scenario Building

Martelli, Antonio. "FROM BUSINESS INTELLIGENCE TO SCENARIO BUILDING. (Cover story)." Futures Research Quarterly 23, no. 4 (Winter2007 2007): 5-22. Academic Search Complete, EBSCOhost (accessed March 12, 2009).

Summary:
Antonio Martelli’s article, From Business Intelligence to Scenario Building, starts off stating that, “Business intelligence and scenario building and planning are both fundamental tools of strategic analysis.” He asserts that these two tools have a mutual relationship; in order to create a scenario, you must have information – something that stems from intelligence. In return, scenarios and information assist in the planning process. He continues on by defining and discussing the purpose of intelligence and uses a comparison of military intelligence to business strategy.

Martelli posits that SWOT analysis is used as a good starting point for putting intelligence into the competitive strategy context. Furthermore, intelligence can be used to examine both the internal (SW) and external (OT) framework of the SWOT analysis. He mentions that although there is some overlap between the SW and OT, the two as a whole are quite different.

In this article, Martelli foregoes discussion on the internal framework and focuses primarily on the external framework due to its difficulty to obtain.
Within the external framework of SWOT analysis, opportunities can tend to be somewhat nebulous. They can arrive in the form of changes in the industry structure that causes a potential for competitive advantage or from changes within the intra-industry structure of value systems that potentially increase global advantage. These opportunities involve the competitive position or the corporate position of the company respectively.

Since Threats tend to be more specific, Martelli states that it is important for businesses to use an early warning system to clearly identify potential threats before to develop. Since early warning recognition relies on indications, indication lists can be used in examining what threats exist in the present and help to formulate possible future threats.

Although Martelli does not explicitly state the pros and cons of SWOT analysis, it is apparent to the reader that Martelli is a big proponent for using SWOT analysis. More obvious is Martelli’s assertion that the intelligence process should be applied when examining the internal and external framework of a company. The benefit of conducting SWOT analysis primarily lies in the clarification of the business environment, while the detriment of the process is ensuring that the intelligence collected is truly accurate. Inaccuracies will ultimately flaw any strategic plan.

European Commission Joint Research Centre (JRC): SWOT Analysis

JRC's FOR-LEARN: SWOT Analysis

Summary:
The European Commission Joint Research Centre’s Online Foresight Guide summarizes SWOT (Strengths, Weaknesses, Opportunities, Threats) Analysis as an analytical method that is used to illustrate and prioritize internal factors (strengths & weaknesses) and external factors (opportunities & threats) within an organization or territory. The main purpose of conducting a SWOT analysis is to improve the competitiveness of a company or territory. Improving an organization’s competitive edge is achieved by collecting and portraying the internal and external factors that may, in one way or another, have an impact on that organization. The list of strengths and weaknesses is typically derived through an analysis of the organizations resources and capabilities while the opportunities and threats emerge through an analysis of the organizational environment/culture. To successfully improve competitiveness, strengths should be paired with opportunities while simultaneously warding off threats and overcoming weaknesses.

After strengths, weaknesses, opportunities, and threats are identified and listed, they are organized in a matrix. The matrix allows for the most important factors to be displayed and compared against the other categorical factors.

The JRC states that SWOT analysis is not necessarily a forecasting method; however, this particular analytical method is a good starting point for discussions concerning foresight.

The Pros:

• Simple & flexible
• Does not require technical knowledge or skill to implement
• Allows for synthesis and integration of general knowledge and developing knowledge
• Demonstrates a correlation the internal factors (SW) and external factors (OT)
• Allows for clearer contingency plans for an organization to overcome threats and weaknesses

The Cons:

• The list of factors (which are oftentimes lengthy) must be taken into account when analyzing
• Can be time consuming
• No method for prioritizing the factors
• No method for solving disagreements if conducting SWOT analysis in a team
• Single level analysis – not multi-level
• Can be risky if factors are too vague and ill-defined, or if compiler bias is inserted into the process