Part 3 -- What Is Intelligence And What Is The Role Of Intelligence In The Formulation Of Strategy? (Teaching Strategic Intel Through Games)

Image via Wikipedia

Part 1 -- Introduction

Part 2 -- What Is Strategy And What Are Strategic Decisions?

"Well is the Game called great! I was four days a scullion at Quetta, waiting on the wife of the man whose book I stole. And that was part of the Great Game! From the South—God knows how far—came up the Mahratta, playing the Great Game in fear of his life. Now I shall go far and far into the North playing the Great Game. Truly, it runs like a shuttle throughout all Hind. -- Rudyard Kipling, Kim, Chapter 12

For many people, “intelligence” is an even more misunderstood word than “strategy”.  Conjuring up images of James Bond or, at least, George Smiley, intelligence, for many, is exclusively about secrets and spying.  

This has been patently untrue for some time, however.  As early as 1949, Sherman Kent, one of the earliest and most influential thinkers about  intelligence analysis at the Central Intelligence Agency, claimed that as much as 80% of information needed in intelligence work came from open, non-secret, sources.[1]  In a world that moves 21 exabytes of information via the internet each month, the role of both secrets and spying in intelligence, while still important, is clearly further diminished.

In recent years, in fact, intelligence has moved from a narrow government function to a broad reaching discipline.  Intelligence-led policing is a highly regarded public safety strategy while competitive intelligence has, for many years, been a driver for some successful businesses.  Likewise, commercial intelligence agencies, such as IJet and Stratfor, provide intelligence analysis services to private clients.  Even non-governmental organizations, such as the Southern Poverty Law Center, have established intelligence organizations to cover issues of interest to them.  In addition, intelligence studies programs, like the one at Mercyhurst have sprung up all over the US and abroad.  The International Association For Intelligence Education now boasts some 20 colleges and universities among it members.

There are several common themes running through these activities that help define intelligence[2]:  First, intelligence is about the things that are outside your control but are relevant to your entity's success or failure.  In short, intelligence is externally focused.  Ever since Moses sent scouts "through the Negev and on into the hill country" of Canaan to see "what the land is like and whether the people who live there are strong or weak, few or many” intelligence has been about "the other guy"; the enemy, the criminal or the competitor.

Second, intelligence uses information from all sources and, more than that, most of this information is unstructured.  Very few disciplines truly deal with information from all sources.  Intelligence analysts, however, routinely have to integrate economic, political, military, cultural and other types of data into a forecast for decisionmakers within an organization.

In addition, much of the information used by intelligence analysts is incomplete or unverified and may even be the result of a deliberate attempt to deceive.  This messy, dirty, unstructured data requires a unique set of analytic methodologies.  Traditional statistical methods often don't work, for example, with the kinds of anecdotal data normal in intelligence work.

Third, intelligence is designed to reduce the level of uncertainty for a decisionmaker.  It is part of the decisionmaking process.  If intelligence is about the question, "What is going on out there and how is it likely to change?" then the other half of the decisionmaking question (the so-called operational half) is "What can we/should we/will we do about it?"

Finally, intelligence is a process.  It is something that happens, that is both iterative and reflexive; not something that just is.  While emphasis is typically placed on the output of this process, the intelligence product, the quality and utility of this product (as with any product) is a direct function of the process used to create it.  More importantly, since intelligence is a process, it can be improved upon through careful and intelligent change, improving, in turn, the quality and utility of the final intelligence product.

Intelligence products come in many flavors but one of the most useful distinctions is between descriptive and estimative products.  Descriptive products outline the relevant facts, figure, personalities and issues surrounding a topic of interest.  Estimative products, on the other hand, attempt to forecast what will likely happen because of the intersection of those facts, figures, personalities, etc.

Of the two, decisionmakers typically value quality estimative intelligence over even the very best descriptive products.  In a world dominated by a 24/7 news cycle and supported by the vast resources available on the internet, providing mere facts and figures is rarely enough to justify the expense of a dedicated intelligence unit.

In short, strategic intelligence should be the foundation for all strategic planning.  Without some sense of how the external world will likely change to support or hinder attempts to achieve a person’s or organization’s strategic goals, any allocation of resources in support of those goals will likely be sub-optimal.

Next:
Why Games?

---

[1] Kent, Sherman, Strategic Intelligence for American World Policy. Princeton, NJ: Princeton University Press, 1949.

[2] For a more exhaustive discussion of these themes and how they lead to this definition of intelligence, see Wheaton and Beerbower, Towards A New Definition Of Intelligence, Stanford Law and Policy Review, Vol. 17, Issue 2 (2006),  p. 319-330.

Part 2 -- To Kent And Beyond (What Do Words Of Estimative Probability Mean?)

Part 1 -- Introduction

The discussion of Words of Estimative Probability (WEPs) starts with Sherman Kent’s seminal essay on the topic but hardly ends there. Linguistics experts have done a large number of studies on what they refer to (among other things) as “verbal expressions of probability”, “verbally expressed uncertainties” or “verbal probability expressions”. Others, in the fields of finance, health (Thanks, Rob!) and meteorology have also wrestled with this question.

I am advising one of our graduate students, Rachel Kesselman, on her thesis which will address all these literatures at some length. She is scheduled to present her preliminary findings at the ISA conference at the end of March and will likely complete her thesis (which focuses on the historical use of WEPs in National Intelligence Estimates) sometime in May or June. I won’t steal her thunder, then, but suffice it to say that this is a well studied topic outside the IC.

Within the IC, though, there appears to be a limited number of studies on the topic. Steve Rieber presented his own paper on the meaning of WEPs a couple of years ago at the ISA conference. At the time, he cited only two studies as major research findings within the realm of intelligence analysis: One in Dick Heuer’s classic, The Psychology Of Intelligence Analysis, and one (at least part of the basis for Rieber's paper) from a study of Kent School analysts. In the study cited from Heuer, analysts gave a single numerical probability for each word. For example, one analyst might claim that the word “likely” suggests a 75% probability while another might claim that it suggests only a 60% probability. Kent School analysts, on the other hand, were asked to give a range of values for each word. The charts showing both results are below (Heuer's is on top and Rieber's is on bottom).

The conclusion from both studies was that the level of agreement was rough, to say the least. There was a distinct difference between words at either end of the spectrum (such as “highly unlikely” and “highly likely”) but differences between words that were closer together in meaning (such as “probably” and “likely”) hardly seemed to be differences at all.

Other writers have tried to more or less establish statistical meanings to the words by simply declaring that certain words have certain probabilistic meanings. Kent's own attempt fell much along these lines as does the recent attempt (Thanks, Ted!) by the authors of Joint Publication 2-0, "Joint Intelligence", Appendix A (published 22 JUN 07). The fundamental problem with dictating these intervals is that it ignores the considerable evidence (including the two studies cited above) suggesting that people don't think about these words in these rigid ways (The problems with the Joint Pub run even deeper as it unnecessarily confuses the ideas of probability and confidence and is, as a consequence, 180 degrees out from what the National Intelligence Council was promulgating at approximately the same time! All this argues, I might add, for a need for more research into intelligence theory and, in the interim, some standardized estimative language that reflects the current best practice.)

What is clear, however, is that decisionmakers want clarity and consistency in the language of intelligence estimates. One of our former grad students, Jen Wozny, did a very strong thesis on this subject a number of years ago (Available, unfortunately only through inter-library loan at Mercyhurst's Hammermill Library). She looked at what over 40 decisionmakers, from the national security, business and law enforcement fields, wanted from intelligence. Two of the items that consistently popped up were clarity and consistency in the language that intelligence analysts used to communicate the results of their analysis. Peter Butterfield, in a comment to yesterday's introductory post, indicated similar concerns on the part of his decisionmakers.

Tomorrow -- The Exercise And Its Learning Objectives