Intelligence essentials for everyone

Lisa Krizan, Intelligence essentials for everyone
Joint Military Intelligence College, Washinghton DC, 1999



Intelligence sharing in a new light

National Intelligence meets Business Intelligence
Intelligence is traditionally a function of government organizations serving the decisionmaking needs of national security authorities. But innovative private firms are increasingly adapting the national security intelligence model to the business world to aid their own strategic planning.
Whereas “intelligence sharing” has traditionally been a government-to-government transaction, the environment is now receptive to government-private sector interaction.
As economic competition accelerates around the world, private businesses are initiating their own “business intelligence” (BI) or “competitive intelligence” services to advise their decisionmakers. Educators in business and academia are following suit, inserting BI concepts into professional training and college curricula.
Whereas businesses in the past have concentrated on knowing the market and making the best product, they are shifting their focus to include knowing, and staying ahead of, competitors. This emphasis on competitiveness requires the sophisticated production and use of carefully analyzed information tailored to specific users; in other words, intelligence. But the use of intelligence as a strategic planning tool, common in government, is a skill that few companies have perfected.
Although BI practitioners refer to the national security model of intelligence, they do not seek to conduct secret intelligence operations, which are limited by law to government authorities.
Large corporations are creating their own intelligence units, and a few are successful at performing analysis in support of strategic decisionmaking. Others are hiring BI contractors, or “out-sourcing” this function. However, the majority of businesses having some familiarity with BI are not able to conduct rigorous research and analysis for value-added reporting.
On the other hand, as businesses come to appreciate the value of intelligence about their competitors, they are increasingly realizing their own vulnerability to similar scrutiny. The private sector can therefore benefit from IC expertise in disciplines complementary to active intelligence production, namely defensive measures. The whole concept of openness regarding intelligence practices may hinge upon the counter-balancing effect of self-defense.



Intelligence process

"Intelligence is more than information. It is knowledge that has been specially prepared for a customer’s unique circumstances. The word knowledge highlights the need for human involvement. Intelligence collection systems produce... data, not intelligence; only the human mind can provide that special touch that makes sense of data for different customers’ requirements. The special processing that partially defines intelligence is the continual collection, verification, and analysis of information that allows us to understand the problem or situation in actionable terms and then tailor a product in the context of the customer’s circumstances. If any of these essential attributes is missing, then the product remains information rather than intelligence.
(W.Brei, Getting Intelligence Right: the power of logical procedure, 1996)

The intelligence process in government and business
Production of intelligence follows a cyclical process, a series of repeated and interrelated steps that add value to original inputs and create a substantially transformed product.
That transformation is what distinguishes intelligence from a simple cyclical activity. In government and private sector alike, analysis is the catalyst that converts information into intelligence for planners and decisionmakers.
Although the intelligence process is complex and dynamic, several component functions may be distinguished from the whole. Components are identified as Intelligence Needs, Collection Activities, Processing of Collected Information, Analysis and Production.






Converting customer needs into intelligence requirements

Defining the intelligence problem
Customer demands, or “needs,” require interpretation or analysis by the intelligence service before being expressed as intelligence requirements that drive the production process.
The “Five Ws” — "Who What When Where and Why" — are a good starting point for translating intelligence needs into requirements. A sixth related question, "How", may also be considered. In both government and business, these questions form the basic framework for decisionmakers and intelligence practitioners to follow in formulating intelligence requirements and devising a strategy to satisfy them.
The ability to establish a baseline and set in motion a collection and production strategy is crucial to conducting a successful intelligence effort.






Esample n.1 - A Government Scenario
The Severely Random problem type is one frequently encountered by the military in planning an operational strategy. This is the realm of wargaming. The initial intelligence problem is to identify all possible outcomes in an unbounded situation, so that commanders can generate plans for every contingency. The role of valid data is relatively minor, while the role of judgment is great, as history and current statistics may shed little light on how the adversary will behave in a hypothetical situation, and the progress and outcome of an operation against that adversary cannot be predicted with absolute accuracy. Therefore, the analytical task is to define and prepare for all potential outcomes. The analytical method is role playing and wargaming: placing oneself mentally in the imagined situation, and experiencing it in advance, even to the point of acting it out in a realistic setting.
After experiencing the various scenarios, the players subjectively evaluate the outcomes of the games, assessing which ones may be plausible or expected to occur in the real world. The probability of error in judgment here is inherently high, as no one can be certain that the future will occur exactly as events unfolded in the game. However, repeated exercises can help to establish a measure of confidence, for practice in living out these scenarios may enable the players to more quickly identify and execute desired behaviors, and avoid mistakes in a similar real situation.

Example n.2 - A Business Scenario
The Indeterminate problem type is one facing the entrepreneur in the modern telecommunications market. Predicting the future for a given proposed new technology or product is an extremely imprecise task fraught with potentially dire, or rewarding, consequences. The role of valid data is extremely minor here, whereas analytical judgments about the buying
public’s future — and changing — needs and desires are crucial. Defining the key factors influencing the future market is the analytical task, to be approached via the analytical method of setting up models and scenarios: the if/then/else process. Experts in the proposed technology or market are then employed to analyze these possibilities. Their output is a synthesized assessment of how the future will look under various conditions with regard to the proposed new product. The probability of error in judgment is extremely high, as the decision is based entirely on mental models rather than experience; after all, neither the new product nor the future environment exists yet. Continual reassessment of the changing factors influencing the future can help the analysts adjust their conclusions and better advise decisionmakers on whether, and how, to proceed with the new product.


Generating intelligence requirements
Once they have agreed upon the nature of the intelligence problem at hand, the intelligence service and the customer together can next generate intelligence requirements to drive the production process. The intelligence requirement translates customer needs into an intelligence action plan.
As a discipline, intelligence seeks to remain an independent, objective advisor to the decisionmaker. The realm of intelligence is that of “fact,” considered judgment, and probability, but not prescription. It does not tell the customer what to do to meet an agenda, but rather, identifies the factors at play, and how various actions may affect outcomes. Intelligence tends to be packaged in standard formats and, because of its methodical approach, may not be delivered within the user’s ideal timeframe. For all these reasons, the customer may not see intelligence as a useful service.
Understanding each other’s views on intelligence is the first step toward improving the relationship between them. The next step is communication.

Ensuring that requirements meet customer needs
Whether in business or government, six fundamental values or attributes underlie the core principles from which all the essential intelligence functions are derived. The corollary is that intelligence customers’ needs may be defined and engaged by intelligence professionals using these same values.
Interpretation of these values turns a customer’s need into a collection and production requirement that the intelligence service understands in the context of its own functions.






Collection

The collection function rests on research — on matching validated intelligence objectives to available sources of information, with the results to be transformed into usable intelligence. Just as within needs-definition, analysis is an integral function of collection.

Collection requirements
The collection requirement specifies exactly how the intelligence service will go about acquiring the intelligence information the customer needs. Any one, or any of several, players in the intelligence system may be involved in formulating collection requirements: the intelligence analyst, a dedicated staff officer, or a specialized collection unit.
In large intelligence services, collection requirements may be managed by a group of specialists acting as liaisons between customers and collectors.
Smaller services, especially in the private sector, may assign collection requirements management to one person or team within a multidisciplinary intelligence unit that serves a particular customer or that is arrayed against a particular topic area.
Regardless of how it is organized, the requirements management function entails much more than simple administrative duties. It requires analytic skill to evaluate how well the customer has expressed the intelligence need; whether, how and when the intelligence unit is able to obtain the required information through its available collection sources; and in what form to deliver the collected information to the intelligence analyst.


Collection sources
Four general categories serve to identify the types of information sources available to the intelligence analyst: people, objects, emanations, and records. Strictly speaking, the information offered by these sources may not be called
intelligence if the information has not yet been converted into a value-added product.






Processing collected information

From Raw Data to Intelligence Information
No matter what the setting or type of collection, gathered information must be packaged meaningfully before it can be used in the production of intelligence. Processing methods will vary depending on the form of the collected information and its intended use, but they include everything done to make the results of collection efforts usable by intelligence producers.
In the private sector, some processing activities are analogous to those of the government. Interpreting and annotating open-source information for a business intelligence service may include: marking locations of interest on a map or photograph, “translating” press releases or technical reports, transcribing the words of a speaker from video or audiotape into text, or drafting a detailed commentary from a personal interview.
Another term for processing, collation, encompasses many of the different operations that must be performed on collected information or data before further analysis and intelligence production can occur.
Collation organizes the information into a usable form, adding meaning where it was not evident in the original. Collation includes gathering, arranging, and annotating related information; drawing tentative conclusions about the relationship of "facts” to each other and their significance; evaluating the accuracy and reliability of each item; grouping items into logical categories; critically examining the information source; and assessing the meaning and usefulness of the content for further analysis.
Collation reveals information gaps, guides further collection and analysis, and provides a framework for selecting and organizing additional information

Evaluating and selecting evidence
To prepare collected information for further use, one must evaluate its relevance and value to the specific problem at hand.
Three aspects to consider in evaluating the relevance of information sources are reliability, proximity, and appropriateness.
Reliability of a source is determined through an evaluation of its past performance; if the source proved accurate in the past, then a reasonable estimate of its likely accuracy in a given case can be made.
Proximity refers to the source’s closeness to the information. The direct observer or participant in an event may gather and present evidence directly, but in the absence of such firsthand information, the analyst must rely on sources with varying degrees of proximity to the situation.
Appropriateness of the source rests upon whether the source speaks from a position of authority on the specific issue in question.



Analysis

Analysis is the breaking down of a large problem into a number of smaller problems and performing mental operations on the data in order to arrive at a conclusion or a generalization. It involves close examination of related items of information to determine the extent to which they confirm, supplement, or contradict each other and thus to establish probabilities and relationships. (Mathams)
The purpose of intelligence analysis is to reveal to a specific decisionmaker the underlying significance of selected target information.

Types of reasoning
Objectivity is the intelligence analyst’s primary asset in creating intelligence. More than simply a conscientious attitude, objectivity is “a professional ethic that celebrates tough-mindedness and clarity in applying rules of evidence, inference, and judgment.” To produce intelligence objectively, the analyst must employ a process tailored to the nature of the problem.
Four basic types of reasoning apply to intelligence analysis: induction, deduction, abduction and the scientific
method.
Induction: in the words of Clauser and Weir: "Induction is the intellectual process of drawing generalizations on the basis of observations or other evidence. Induction takes place when one learns from experience. For example, induction is the process by which a person learns to associate the color red with heat and heat with pain, and to generalize these associations to new situations.
Induction occurs when one is able to postulate causal relationships. Intelligence estimates are largely the result of inductive processes, and, of course, induction takes place in the formulation of every hypothesis. Unlike other types of intellectual activities such as deductive logic and mathematics, there are no established rules for induction."
Deduction: “Deduction is the process of reasoning from general rules to particular cases.
Abduction: is the process of generating a novel hypothesis to explain given evidence that does not readily suggest a familiar explanation. Abductive reasoning may also be called intuition, inspiration, or the “Ah-ha!” experi-
ence. It characterizes the analyst’s occasional ability to come to a conclusion spontaneously, often without a sense of having consciously taken definable steps to get there.
Scientific method: the scientific method combines deductive and inductive reasoning: Induction is used to develop the hypothesis, and deduction is used to test it.


Methods of analysis
Opportunity Analysis Opportunity analysis identifies for policy officials opportunities or vulnerabilities that the customer’s organization can exploit to advance a policy, as well as dangers that could undermine a policy.
Linchpin Analysis Is an anchoring tool that seeks to reduce the hazard of self-inflicted intelligence error as well as policymaker misinterpretation. At a minimum,
Analogy Analogies depend on the real or presumed similarities between two things.
Analogies serve as the basis for most hypotheses, and rightly or wrongly, underlie many generalizations about what the other side will do and how they will go about doing it.

Customer focus
As with the previous stages of the intelligence process, effective analysis depends upon a good working relationship between the intelligence customer and producer. A sig-
nificant difference exists between the public and private sectors with regard to this customer-producer relationship.
The government intelligence analyst is generally considered a legitimate and necessary policymaking resource.
Conversely, in the private sector, the intelligence analyst’s corporate rank is generally orders of magnitude lower than that of a company vice-president or CEO. The individual analyst may have little access to the ultimate customer, and the intelligence service as a whole may receive little favor from a senior echelon that makes little distinction between
so-called intelligence and the myriad of other decisionmaking inputs.

Analytic mindset : misperception and bias
Customer needs and collected information and data are not the only factors that influence the analytic process; the analyst brings his or her own unique thought patterns as well. This personal approach to problem-solving is “the distillation of the intelligence analyst’s cumulative factual and conceptual knowledge into a framework for making estimative judgments on a complex subject.”Mindset helps intelligence analysts to put a situation into context, providing a frame of reference for examining the subject. Analysis could not take place if thinking were not bounded by such constructs. However, mindset can also lead analysts to apply certain viewpoints inappropriately or exclusively while
neglecting other potentially enlightening perspectives on an issue. While no one can truly step outside his or her own mindset, becoming aware of potential analytic pitfalls can enable intelligence analysts to maximize the positive effects of mindset while minimizing the negatives.



Production

Creating intelligence
The previously-described steps of the intelligence process are necessary precursors to production, but it is only in this final step that functionality of the whole process is achieved.
Production results in the creation of intelligence, that is, value-added actionable information tailored to a specific customer. In practical terms, production refers to the creation, in any medium, of either interim or finished briefings or reports for other analysts, or for decisionmakers or policy officials.
In government parlance, the term “finished” intelligence is reserved for products issued by analysts responsible for synthesizing all available sources of intelligence, resulting in a comprehensive assessment of an issue or situation, for use by senior analysts or decisionmakers. Creating finished intelligence for national and military customers is the role of CIA and DIA analysts, respectively.
Similar designations for finished intelligence products may apply in the business world. Particularly in large corporations with multidisciplinary intelligence units, or in business intelligence consulting firms, some production personnel may specialize in the creation of intelligence from a single source, while others specialize in finished reporting.

Emphasizing the customer’s bottom line
The intelligence report or presentation must focus on the results of the analysis and make evident their significance through sound arguments geared to the customer’s interests.
Knowing the customer enables the producer to generate intelligence that highlights the bottom line. Some customers are “big picture” thinkers, seeking a general overview of the issue, and guidance on the implications for their own position and responsibilities. An appropriate intelligence product for such a customer will be clear, concise, conclusive,
and free of jargon or distracting detail.
Conversely, some customers are detail-oriented, seeing themselves as the ultimate expert on the subject area. This type of customer needs highly detailed and specialized intelligence to supplement and amplify known information.

Customer feedback and production evaluation
The production phase of the intelligence process does not end with delivering the product to the customer. Rather, it continues in the same manner in which it began: with dialogue between producer and customer.
If the product is really to be useful for policy-making and command, dissemination involves feedback, which is part of the marketing function.... Ideally, the “marketer” who delivers the product is the same individual who accepts and helps to refine the initial requirement.




24 Mar 2016 -- Written by SA Staff      Tweet