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.
  

A Bayesian Approach To Modeling Binary Data: The Case Of High-Intensity Crime Areas

Law, Jane & Haining, Robert
Geographical Analysis, Vol. 36. No 3 (July 2004) Ohio State University

Summary
The purpose of this paper is to apply Bayesian logistic models to binary data in order to explain how high-intensity crime areas (HIAs) are distributed in Sheffeild, England.

The article defines an HIA as an urban area experiencing high levels of violent crime. Perpetrators of crimes in HIAs often reside in the neighbors where they committ crimes, resulting in high levels of witness intimidation making it difficult to identify an HIA with full accuracy.

The article argues that Bayesian approaches are useful for spatial data analysis because of its emphasis on randomness, prior beliefs about values, and WinBUGS software that enables analysts to test hypothese with spatial elements.

Prior to using Bayesian analysis, Sheffeild was divided into Basic Command Units (BCUs). Within the BCUs were HIAs. Within both BCUs and HIAs were Enumeration Districts (EDs). EDs were then classified in terms of if they were in an HIA or not. According to the article several EDs were miscategorized because the original statistics used the standard logistic model, that did not analyze the spatial relationship between EDs. The article continues by discussing the use of Logistic Regression with WinBUGS software, to analyze random elements and spatial analysis to redesignate the EDs.

Figure 1, shows what is known as the logit function, including random effects. However it does not include spatial relationships of EDs.

In Figure 3A spatial relationships are shown with the links to W which is known as the contingency matrix. The contingency matrix is used to show the likelyhood of EDs neighboring HIAs and being at risk of spill-over crime from the HIAs making the EDs likley to become HIAs.

The paper's conclusion is that using a three stage Bayesian hierarchal model, can give estimated probabilities of EDs being HIAs, because it takes into account spatial elements between EDs. The paper also argues for "map decomposition" as another relevant way for analyzing spatial models along with Bayesian hierarchal models.

Why I Don't Like Bayesian Statistics

Gelman, Andrew, Professor of statistics and political science and director of the Applied Statistics Center at Columbia University

Summary



Professor Gelman refers to Bayesian inference as a "coherent mathematical theory," but does not trust it for scientific applications. Gelman believes that it is too easy to apply subjective beliefs about a given situation to Bayesian theory; because people want to believe their own preconceived notions and reject results statistical results they do not want to agree with. Bayesian methods according Gelman, encourage this kind of thinking.



Gelman takes special issue with political scientists like himself adopting Bayesian methods. Bayesian approaches tend to assume exchangeability of variables. However in political science it is impossible to exchange each of the 50 states, they cannot be used randomly or as samples.



Gelman continues by saying that he is not hostile to mathematics of Bayesianism, but its "philosophical foundations, that the goal of statistics is to make an optimal decision." Gelman believes that statistics are for doing "estimation and hypothesis testing," not to "minimize the average risk." He also faults the Bayesian philosophy of axiomatic reasoning because it implies that random sampling should not be done which Gelman considers to be "strike against the theory right there." He also accuses Bayesians of believing in "the irrelevance of stopping times," which means that stopping an experiment it will not change your inference. Gelman concludes by saying "the p-value does change when you alter the stopping rule, and no amount of philosophical reasoning will get you around that point."

Bayes' Formula

Author's Note: This is a great video for teaching Bayes' Theorem in its simplest form.

Summary
In order to illustrate the utility of Bayes’ Theorem, the author draws upon two simple scenarios. First, suppose someone faces the decision of needing to choose between three doors. If the person making the decision does not have any prior knowledge about the situation, the scenario creates an unconditional probability. But, once the person receives new information about the scenario, the rational person should reconsider his/her decision and subsequent probabilities.

Bayes’ Theorem is about the introduction of new information used to adjust probabilities and create conditional probabilities. In the formula, P(G/U), P is the probability that G will occur, if U happens.

To illustrate the application of Bayes’ Theorem and conditional probabilities, the author illustrates a second scenario. Pretend that there is a 70% probability that the economy will grow and a 30% probability that the economy will slow (an unconditional probability). The author owns a stock that has an 80% chance of increasing if the economy grows. That same stock, however, only has a 30% chance of increasing if the economy slows. The 80% and the second 30% are conditional probabilities; they are based on the condition that the economy will grow or slow.

The author can then determine the scenario’s four conditional probabilities:
1) What is the probability that the economy will grow and the stock will increase?
2) What is the probability that the economy will grow and the stock will decrease?
3) What is the probability that the economy will slow and the stock will increase?
4) What is the probability that the economy will slow and the stock will decrease?

To answer these questions and determine their probabilities, the author uses the equation: P(UG) = P(U/G)P(G). Notice that this equation is longer than the first because this one incorporates two conditions: the economy will grow/slow and the stock will increase/decrease.

Bayes' Theorem for Intelligence Analysis

Jack Zlotnick
CIA Historical Review Program

Author’s Note: Released by the CIA’s Historical Program in the early 1990’s, Jack Zlotnick wrote this piece in the 1970’s. At the time, the CIA was still in the process of testing Bayes’ Theorem. Due to the ongoing testing period (at that time), Zlotnick does not offer a position on the utility and validity of the Bayesian method with regards to intelligence. In fact, Zlotnick spends a considerable amount of time in the article discussing the ways the theorem should continue to be tested.

Summary
Due to the very nature of intelligence, analysts should be naturally interested in the Bayesian Theorem. Intelligence is probabilistic in nature. Intelligence analysts usually conduct their analysis based on incomplete evidence in which they must address probabilities (thus WOEP’s).

For intelligence applications, Bayes’ Theorem is represented by the equation R=PL. “R” is the revised estimate of the odds favoring one hypothesis over another competing hypothesis (the odds of a particular hypothesis occurring after new evidence is entered into the equation). “P” is the prior estimate on the hypotheses probabilities (the odds before considering the new evidence entered into the equation). The analyst must offer judgments about “L” or the likelihood ratio. This variable is the analyst’s evaluation of the “diagnosticity” of an item of evidence. For instance, if a foreign power mobilizes its troops, what are the chances that “X” will happen over “Y”.

The principle features of the Bayes Theorem distinguish it from conventional intelligence analysis in three ways. First, it forces analysts to quantify judgments that are not ordinarily expressed in numeric terms. Second, the analyst does not take the available evidence as given and draw conclusions. And third, the analyst makes his/her own judgments about the bits and pieces of evidence. He/she does not sum up the evidence as he/she would if he/she had to judge its meaning for a final conclusion. The mathematics does the summing up.

The author is skeptical that the complex tasks analysts are forced to consider can be reduced to numeric values. Bayes’ Theorem, however, may be useful for examining strategic warning by uncovering patterns of activity by foreign powers.

Summary Of Findings: Gap Analysis (3 Out Of 5 Stars)

Note: This post represents the synthesis of the thoughts, procedures and experiences of others as represented in the 12 articles read in advance of (see previous posts) and the discussion among the students and instructor during the Advanced Analytic Techniques class at Mercyhurst College on 29 APR 2009 regarding Gap Analysis specifically. This technique was evaluated based on its overall validity, simplicity, flexibility and its ability to effectively use unstructured data.

Description:
Traditionally, "gap analysis" is a method used to conduct an internal operational analysis, whereas the gap analysis identifies the "gap" between a current state and a desired endstate within a company or agency. From an intelligence analysis perspective, "gap analysis" can be used as a tool to identify the likely pathway or pathways a target may take to arrive at a given endstate from a known position. Thus, "gap analysis" does not necessarily provide an estimate, but rather provides the analyst with a list of possible actions a target may likely take. Gap analysis as an analytic technique bears a striking resemblance to several other methods, such as Indicators & Warnings and Decision Trees.

Strengths:

1) Identify the target

2) Characterize the current status of the target as well as the target's goals

3) Identify what you want to know about the target

4) List the pieces of information that you have

5) Use a systematic approach to infer what the target is likely to do in order for the target to reach its goals

Weaknesses:

* No structured method to conduct the analysis

* May not leave you with a clear estimate

* Open to bias and other cognitive downfalls (satisficing, mirror imaging, etc.)

* Overlaps with the process of other methods and modifiers (i.e. decision treees, I&W, Brainstorming, SWOT, etc.)

* Susceptible to deception

* Danger of pitfalls

How-To:

1) Identify the target

2) Characterize the current status of the target as well as the target's goals

3) Identify what you want to know about the target

4) List the pieces of information that you have

5) Use a systematic approach to infer what the target is likely to do in order for the target to reach its goals

Experience:

For the first application, the group tried to determine what thesis topic Mary, a fictional first year graduate, would write about. Professor Wheaton acted in place of Mary, and we role played in questions and answer format. The group determined the gaps needing filled would be what intelligence track she was most interested in (national security, law enforcement, or competitive), what area or topic in her previous classes interested her the most, the choice of her primary reader, and the reader's academic interests. Upon filling these gaps, the group ascertained a plausible topic for Mary's thesis.

For the second application, the group discussed Russia's long held ambitions for a warm water port, preferably on the Mediterranean. The first part of the discussion centered on hostilities between Georgia and Russia, and actions Russia could take against Georgia to maintain their sphere of influence in the Black Sea. Additionally, the group discussed what actions may be necessary in their diplomatic relations with other nations bordering the sea. After discussing how Russia could potentially gain a Black Sea port by bringing Georgia into their sphere of influence, the group discussed how Russia could proceed toward gaining access to Mediterranean ports. The group determined that Turkey would be central in future Russian objectives for ports in the Mediterranean. The group put together lists of things the Russians could do that they are not doing now that would indicate their goals of extending their influence in Georgia and Turkey.

These applications illustrated the following:

* Helped in thinking through the steps that lead to a decision

* Allowed for open discussion and debate, helping the critical thinking process

* At some points it felt like stabbing in the dark, but the estimates later became more clear as the group discussed the options

* Eliminated peripheral influences not directly related to the topic, such as administrative processes.

Forecasting for Success: The Power of Regulatory Gap Analysis

http://www.amarexcro.com/articles/docs/RAPS_Focus_Gap_Dec2008.pdf

This paper offers a broad plan for conducting a regulatory gap analysis for biomedical products, a definition of gap analysis, when and how to use gap analysis, and the benefits of conducting a gap analysis.

"Fewer than 1% of all biomedical products conceived move beyond preclinical testing, and fewer than 10% of those products make it onto the market." Thus biomedical product developers need to harness their time wisely to improve these statistics. Conducting a gap analysis is one way to cut down on both preclinical and clinical testing times.

The paper defines gap analysis as "the process of reviewing all available information for a candidate product to assess current development status, identify potential gaps in information required for subsequent steps, and develop a strategy to fill those holes."

According to the authors, the ideal time for performing a gap analysis is in the preclinical stages. This will allow for an understanding of the products unique nature. A particular focus of the information collection step needs to be on regulatory thresholds, precedents, and milestones. Once the developers know where their gaps are located, they can formulate a strategy for developing the product according to the standards set forth by regulatory bodies. The authors suggest sharing the action plan with the regulatory board to understand their concerns over the future developmental stages.

Aside from forming the basis for a developmental plan, their are other benefits to conducting gap analysis. First, it eliminates unnecessary developmental research and development testing. With the biomedical industry in particular, time is a precious commodity. Also, the gap analysis will aid in the speed in which regulatory agencies review and approve the product, since it knows the steps the developers are following. Troubleshooting these concerns will save a lot of headache later.

Gap analysis methodology for identifying future ICT related eGovernment research topics – case of “ontology and semantic web” in the context of eGover

http://ecom.fov.uni-mb.si/proceedings.nsf/Proceedings/874F789164F6DD6DC12572EE007A6BB2/$File/Paper95.pdf

This study evaluates the the gaps between the current state of government e-services to those proposed by numerous European conventions. The authors review how they defined and identified those gaps, how they were interrelated, and the methodology used to draw conclusions.

The use of information and communication technologies (ICT) currently employed by governments is poor. The future needs demands placed on governments to meet constituent demands require the streamlined implementation of ICT. The results of this study are part of the eGovRTD2020 project for which this work was commissioned.

For the sake of the study, a gap was identified as either expressing a mismatch between issues of consideration, or an issue of research currently not under consideration. There are five main steps the authors undertook to identify gaps and actions toward future scenarios. Generally speaking, they are:

• where are we at?
• where can we go?
• how do we get there from here?
• this is how we get there.
• this is what we need to do to get there

The researchers then grouped the gap areas together and conducted conclusions on how they were interrelated (the later via a SWOT-esque approach).

The authors highlight four key steps they considered while conducting their gap analysis. They are:

• understand the current environment
• understand the broader context of the environment (for a holistic view)
• base the results on a clear assessment framework
• support the analysis quantitatively
  

Gap Analysis As A Tool For Community Economic Development

Suzette D. Barta and Mike D Woods
Oklahoma State University

Author’s Note: This article is about “sales gap analysis.” The article focuses on a project in Oklahoma in which small cities are trying to determine the health of their local economies. Particularly, the cities are trying to determine whether local buyers are spending their money within the local community or outside the community. Although this article is slightly off topic, the discussion on gap analysis does contain a couple nuggets of valuable insight.

The purpose of this article is to help community leaders understand that there are some tools available that can help local merchants better understand the weaknesses of their local retail market. Once the leaders understand the local market’s weaknesses, a competitive response plan can be drafted.

The Oklahoma projects aims to determine whether local markets have a retail surplus or a leakage of retail (Are local customers shopping within the local market? Are external customers shopping within the local market?) This determination of a retail surplus or leakage is called a sales gap analysis.

Gap analysis is a technique for identifying the strengths and weaknesses in a local retail market. In this situation, the analysis estimates how many shoppers are coming to a community to purchase retail items.

Local residents must decide for themselves whether a retail gap is acceptable, not acceptable, or even preferable. If it is deemed not acceptable, then community leaders should devise a competitive strategy to meet the needs of the community. A common misperception however, is to assume that if a gap exists, then it must be filled.

A gap analysis only indicates the possible areas of leakage. The analysis does not indicate why the leakage exists, whether or not the leakage is acceptable, or how to stop the leakage from occurring. Gap analysis is only a starting point. The information generated from a gap analysis is only valuable if it is used to stimulate further discussion and to devise an appropriate competitive strategy for action.

Gap Analysis Strengthens Link Between Requirements And Verification

Brian Hooper and Bill St. Clair
COTS Journal

Author's Note: This article primarily discusses ways in which requirements traceability may be improved, specifically in companies working on military projects that require safety certifications. The authors highlight gap analysis as the means in which the weaknesses in requirements traceability are discovered.

Summary
Gap analysis is a technique routinely used in business to measure the development/maturity of working processes and to identify potential areas for improvement. Gap analysis provides an opportunity to examine operating processes and products typically by employing a third party to conduct the assessment. The valuable information offered by the gap analysis helps to improve a company’s processes so that when a formal assessment or certification of products is conducted, the assessment is much more likely to be passed on the first attempt.

Companies are looking outside their own market sector for best practices and approaches, techniques, and standards. Gap analysis provides a framework to isolate areas in which they need to improve. The results from a gap analysis also aid companies in efficiently refocusing their resources in order to achieve the desired improvement.

With the increased need for software control, a gap analysis of safety-critical projects (particularly military related projects) regularly flags the field of requirements traceability. Many development standards require a Requirements Traceability Matrix (RTM). Requirements traceability is a widely accepted best practice in the development industry to ensure that all requirements are implemented and that all products can be traced back to one or more requirements.

More often than not, however, traceability matrices are performed as a low-priority task. Constructing a RTM requires an enormous amount of time and money. Failure to construct an accurate RTM may result in a product failing its certification assessment.

Teaching the New Competencies Using the Gap Analysis Approach

http://www.stfm.org/fmhub/fm2006/April/Hershey238.pdf

Summary:

Doctors Bell and Kozakowski recommend using gap analysis to aid students (in this case medical students at all levels) in evaluating their current competency levels and developing a plan for improvement.

Medical schools typically define the core competencies that their students must meet upon the completion of classes, and at the end of the program. At the residency level, physicians must demonstrate achievement in the general competency categories, as identified by the Accreditation Council for Graduate Medical Education:

• Patient Care
• Medical Knowledge
• Practice-Based Learning and Improvement
• Interpersonal/Communication Skills
• Professionalism
• Systems-based practice.

Additionally, the authors describe the process of faculty-conducted assessments of the learners' achieved competencies. They provide a questionnaire used by faculty at the Lake Erie College of Osteopathic Medicine as an example.

Using gap analysis.
The authors describe the process of incorporating gap analysis into this type of self-evaluation. They mention four main steps:

1. "Articulate a desired future state"
2. "Describe the current state"
3. "Examine internal and external issues that must be addressed to progress from the current state to the desired future state"
4. "Delineate strategies and tactics that will ensure that the 'gap' between current state and desired future state is narrowed"

Gap analysis has been used in this application at the Hunterdon Medical Center Family Medicine Residency Program. Meetings are held between faculty and residents in which the residents are to score where they think fall, on a scale of 0-100, when performing a specific competency. The resident is then asked to name a practicing physician who he or she views as a 100 on the same scale. The faculty member asks the resident to identify those specific behaviors and characteristics that make the physician a 100. The last step involves the faculty member asking the resident to describe his or her own behaviors in relation to those of the 100-level physician, identifying specifics steps and learning issues that can reduce that gap between their own score and the 100-level score.

In the article's summary, the authors indicate that, at the time of publication, there had been no formal evaluation of this technique's effectiveness in this application.

Applied Strategic Planning

Goodstein, Leonard D., Timothy M. Nolan, and J. W. Pfeiffer. Applied Strategic Planning: how to develop a plan that really works. New York: McGraw-Hill, 1993. Ch.11.

Much of this chapter is dedicated to addressing the results of a gap analysis. This summary will primarily focus on the information relevant to the process of conducting a gap analysis, and any associated advantages or pitfalls.

Summary:
Goodstein calls gap analysis the "moment of truth" for a strategic planning team. This analysis provides the team with the opportunity to identify specific gaps that exist between the organization's current status and the "performance required for the successful realization of its strategic business model." The organization's current status and level of performance is the product of an internal performance audit.

Probably the most important product of a gap analysis is the estimate of the size of the gap and whether or not the strategies and tools at hand are enough to reduce the size of the gap. Every effort must be taken to close each perceived gap, and the team's responsibility is to reevaluate the desired future, business model, and solutions until all gaps are closed. This may require the team to repeat the process several times, or even revisit the mission statement or business model periodically.

There are two basic approaches to reducing gaps:

1. Transactional Solution: Requires a modification or reduction of goals
2. Transformation Solution: Requires a reduction of the obstacles causing the gap

The authors offer some words of caution to the strategic planning team. They recommend a strong consultant in the gap analysis phase to reduce the chances of the team falling into a group think frame of mind. Additionally, it is important to ask whether or not it is realistic to assume that a particular gap even has the potential be closed. Identifying a gap in one area can result in the realization of other gaps in different areas. The team must also assess the feasibility of change when assessing the scope and nature of existing gaps.

Human Performance Improvement For Tactical Teams

Hathaway, D.J. FBI Law Enforcement Bulletin. June 2008 Volume 77 Number 6

Summary:
This article uses gap analysis, among other methods such as performance and business analysis, in order to reassess the effectiveness of the FBI's tactical teams. The article explains how in today's world, any disparity between a tactical teams standard operating procedure (SOP) and real world actions may have legal ramifications, as well as embarrass and/or damage the credibility of the agency. By using methods such as gap analysis, these shortcomings can be identified and avoided.

According to the article, a performance analysis, "explains the current state of the department's tactical team and defines the desired one...Performance analysis incorporates organizational, environmental, and gap analysis. " Thus the gap analysis is only one component of an overall performance analysis. "As the name implies, gap analysis defines the area between actual performance of the team and the desired level and, as such, constitutes the second stage of performance analysis."


"Whereas performance analysis identifies the problem or area of concern, gap analysis brings the issue to the forefront, begins to frame it in terms of human behaviors and expected outcomes, and addresses the complex issue of consequences." Tactical teams may identify a gap in shooting accuracy, which would be a performance state, and seek to correct that problem to align with the desired performance state. Consequences and outcomes addressed with this particular performance may be unnecessary loss of life and/or inability to stop a criminal.

Once the gap is identified, it needs to be prioritized. Some questions to ask are, "How often does the gap occur? How costly will it be to fix? Or, how important is the gap? What if the team did nothing? Discovering a gap does not mean that it can, should, or will be addressed." Once gaps are prioritized, they can be dealt with on a basis of whats more critical to success, and keep the analysis systematic and appropriate. As a complete method, gap analysis is only identified as a "critical step" in the "human performance improvement model" (see image above). This critical step serves to identify the performance issues and facilitate the next step, which is the investigation and correction of those issues.

Authors Comment: The article further highlights each step within the "human performance improvement model, however they were not addressed in this summary due to the focus solely on gap analysis.

Gap Analysis

Encyclopedia of Management

Summary:
According to the article, gap analysis is defined as, "studying the difference between standards and the delivery of those standards." As a method of analyzing a business model, it is important to conduct a "before-and-after" analysis prior to conducting the actual gap analysis. The before-stage is identified, such as customer expectation, and then the after-stage is identified, such as actual customer experience. The difference between the two is the "gap", and once identified the gap can be addressed.

According to the article, "Gap analysis involves internal and external analysis." In the business model, this means that a business must address the customer's needs and expectations, as well as the appropriate business response to those needs and expectations. In order to implement the external analysis, the article represents the use of focus group interviews, consisting of ten to twelve customers, who are invited to share their experiences with a business. After recording the experiences of the focus group, the article recommends the implementation of a quantitative method to rank order the identified expectations and experiences, such as a 1-10 scale. The gaps can then be easily identified according to the gaps on the scale between experiences and expectations.

Gap analysis is a useful method to identify shortcomings within a business model. The article applies to the gap analysis method exclusively to the development of better customer relations, however gap analysis can be also be applied exclusively for internal analysis as well, such as what employees may expect from employers, and vice versa.

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.
   

Gartley's Gap Theory Explained

Bobbit Steven G. Futures December 2008

Retrieved From: FindArticles.com. 27 Apr, 2009. http://findarticles.com/p/articles/mi_qa5282/is_20081201/ai_n31108517/


Bobbit's goal in the article to explain to traders how to deal price gaps in the stock market. Gaps in prices of a stock happen when "the current bar opens above the high or below the low of the previous bar." The term "gap" is often used as a verb throughout the article. Human emotion manipulates markets and cause frequent "gapping."


Bobbit explains the "natural sequence of gaps" in a Gap Succession Chart. The sequence begins with the "breakaway gap" which indicate a change in pricing trends of a given stock. Next is the "measuring gap," according to Bobbit who cites H.M. Gartley measuring gaps are the most difficult for an analyst to spot but also the most important because spotting them can lead to better predictions of where the price is going to go. Next is the "exhaustion gap" which according to the article is the easiest to spot because they happen during significant "up or down" moves of a stock's price. Bobbit concludes the article with several mathematical equations to help determine where gaps may occur while charting prices.

Benchmark Your CI Capabilities: Using A Self Diagnosis Framework

By Singh, Arjan & Beurschgens, Andrew, Fuld & Company
Competitive Intelligence Magazine Volume 9, Number 1, January-February 2006

This article discusses the Self-Diagnostic Framework (SDF). SDF is a tool for analysts and proprietary Competitive Intelligence (CI) professionals to benchmark the current level of their CI capabilities compared to "world class CI capability." SDF incorporates gap analysis to provide recommendations for companies to improve their CI functions.

The authors explain how there are four development stages a CI department can go through. The first stage is known as "stick fetching." This is when CI is used by decision makers (DM) after they are well into their decision making process. DMs will request information from a CI department who have been at a distance from the decision making process and therefore have little understanding as to why certain information is needed. The next stage is the "pilot stage." This happens when an organization expresses a committment to further develop a CI function and give it a "mandate" to help in the decision making process. After the pilot stage is the "proficient stage" where an organization's CI team is proficient in most of the elements in the SDF. Once they have all the elements in SDF covered they are considered to have achieved the "world-class" stage.

The SDF is broken down into eleven attributes. An analyst or team of analysts, look at each attribute and determine which stage they are in for that attribute.

The article describes how two european companies used the SDF to finds gaps and inedaquacies in their CI functions. Both companies were successful in further developing value added CI functions in their organizations.

Summary Of Findings: Game Theory (4 out of 5 Stars)

Note: This post represents the synthesis of the thoughts, procedures and experiences of others as represented in the 12 articles read in advance of (see previous posts) and the discussion among the students and instructor during the Advanced Analytic Techniques class at Mercyhurst College on 22 APR 2009 regarding Game Theory specifically. This technique was evaluated based on its overall validity, simplicity, flexibility and its ability to effectively use unstructured data.

Description:

Game theory is a method based on applied mathematics and economic theory. It can be useful when attempting to analyze (and ultimately predict) the strategic interactions between two or more actors and the way in which their actions influence future decisions. Game theory assumes that all actors are rational, and can be influenced by various individuals and factors. Games typically involve five common elements: players, strategies, rules, outcomes, and payoffs.

Strengths:

-assumes rational actors

-assumes actors will adjust their actions based on the actions of other actors

-not clearly differentiated from role-playing, simulations, and/or decision trees

-very mathematically based (can be intimidating)

-difficult to quantify options, strategies, and motivations

-may not be a valid method to produce an accurate estimation (see Game Theory, Simulated Interaction, and Unaided Judgment For Forecasting Decisions in Conflict: Further Evidence)

--In real world applications, identifying all of the key players and outcomes can be difficult

Weaknesses:

-Visual step-by-step trail to a conclusion/estimate

-Ability to quantify variables in play

-Emphasis on mathematics and scientifc method

-Applicable to multiple fields (economics, conflict, etc)

-90% rate of success according to BDM

How-To:

Game Theory varies in complexity and in application, however, each application has the following in common:

*Establish the players and the complexity of the game being played, so as to understand the rules which govern the players and the game.

*Identify the possible outcomes for the choices the players can make (although this is particularly difficult as not all decisions can be predicted)

*Establish measurable values for predicted outcomes.

*Eliminate dominated strategies and employ dominate strategies. Repeat this step until a clear, singular strategy emerges or equilibrium is reached between the players.

*Employ selected strategy.

Experience:

As a class, we visited www.gametheory.net and played the repeatable version of Prisoner's Delemma under the "Interactive Materials" tab. Each student played the game at their personal computers. Our objective as we played against the five "personalities" was to identify the particular strategies employed by the computer (in addition to scoring the most utility points). Some of the strategies employed by the computers personalities included "tit-for-tat" and "tit-for-two tats."

Game Theory, Political Economy, and the Evolving Study of War and Peace

By Bruce Bueno de Mesquita

http://www.apsanet.org/imgtest/APSRNov06BuenoDeMesquita.pdf

Summary:

Studies of war and peace increasingly center around domestic interests and institutions for clues on how to shape international affairs. This change in thinking coincides with advances made in non-cooperative game theory and political economy modeling.

De Mesquita refutes realism and state-centric theories as logical explanations for the causes of war. He simultaneously enhances the validity of the liberal peace theory by examining the influences which democrats need to consider when threatening or declaring war.

Realism's claim about a balance of power needed to maintain international stability is refuted by the political economy approach. Simply put, the political economy approach states that the causes of and solutions to international conflict can best be understood by looking within states. It treats leaders as the object of study, not the states as realism does.

A game-theoretic focus concludes that war conducted by rationally acting states is always ex post inefficient. Leaders conduct wars at times to maintain a hold on power, since their domestic constituencies would likely vote them out of office (for democratic states). Autocracies have the advantage of not needing to concern itself with the well-being of their citizenry since they do not face election.

Game theory also validates the liberal peace theory. It claims that leaders (as the object of the political-economy approach to international relations) will only wage war when the outcome is victory, as a 93% success rate for wars initiated by democracies indicate. Since both sides need to consider their reelection prospects, a negotiated settlement to the conflict is the preferred method for resolving conflicts between democratic nations.