Thinking in Parallel (Part Three - Testing The Mercyhurst Model Against The Real World)

Part 1 -- Introduction
Part 2 -- The Mercyhurst Model

For the last 11 years, I have been using the model described in Part 2 to structure my Strategic Intelligence class at Mercyhurst University.  This is a capstone class for seniors and 2nd year graduate students within the Intelligence Studies program at Mercyhurst.  This class is centered on a real world project for a real-world decisionmaker, often within the US National Security Community.  To date, I have overseen 133 of these types of projects.

The broad parameters of the projects have remain unchanged since 2003.  Students in the class are divided into teams and are assigned by the instructor to one of 4-5 projects available during that term.  Each project is sponsored by a national security, business, or law enforcement organization that has a strategic intelligence question.  To date, sponsors of these questions have included organizations such as the National Geospatial-intelligence Agency, the Defense Intelligence Agency, the National Intelligence Council, the National Security Agency, 66th Military Intelligence Group, and the Navy’s Criminal Investigative Service to name just a few.  To give readers a sense of the wide variety of questions intelligence studies students are expected to answer in this course, I have listed a few recent examples of them below:

1. What role will non-state actors (NSAs) play and what impact will NSAs have in Sub-Saharan Africa over the next five years?o What is the likely importance of NSAs vs. State Actors, Supra-State Actors and other relevant categories of actors in sub Saharan Africa?o What are the roles of these actors in key countries, such as Niger?o Are there geographic, cultural, economic or other patterns of activity along which the roles of these actors are either very different or strikingly similar?o What analytical processes and methodologies were applied to the questions above and which proved to be effective or ineffective? 

2. What are the most important and most likely impacts on, and threats to, US national interests (including but not limited to political, military, economic and social interests) resulting from infectious and chronic human disease originating outside the US over the next 10-15 years?  

3. What are the likely trends in Brazil’s oil/liquid fuel market and electric power sector in the next ten years?  Where will these trends likely manifest themselves?o What energy capacity and security issues are likely to be the most significant to Brazil’s economy in the next ten years?o How will Brazil likely address current and/or future energy security issues over the next ten years?o Where will Brazil address these energy shortfalls?

In each case, students had only 10 weeks to conduct the research, write the analysis and present the final product to the decisionmaker.  The students had no additional financial resources available to them and, other than the question itself, received no support directly from the decisionmaker.  Students rarely had any subject matter expertise in the area under question and were only allowed to use open sources.  Students were expected to integrate lessons learned from all previous intelligence studies classes and to manage all aspects of the project without significant supervision.  Finally, all the students, in addition to this project, were taking a full academic load at the same time.  

After all of the deliverables had been produced and disseminated, the decisionmakers sponsoring the projects were asked to provide objective feedback directly to the course instructor.  This feedback, in turn, was evaluated on a five point scale correlated with traditional grading practices and professional expectations.  In short, a 3 on this scale is roughly equivalent to a "B" and a “4” on this scale is roughly equal to “A” work in a university setting.  A “5”, on the other hand, is the kind of work that would be expected from a working (albeit junior) intelligence professional.  The chart below indicates how the annual averages have changed over time.

(Note:   While this chart may appear to reflect grade inflation more than any other suggested effect, it should be noted that “A” is essentially “average” among Mercyhurst University Intelligence Studies seniors and 2nd Year graduate students and has been for the entire time frame shown above.  The current dropout rate from the program is approximately 50% and much of that is due to a strict 3.0 minimum GPA in order to stay in the program.  As a result, seniors and second year graduate students (the only students allowed to take the class), typically have GPAs that average 3.6 or above.  For example, two years ago, 18 of the top 20 GPA’s in the entire University belonged to Intelligence Studies students.)

Anecdotally, it is possible to state the exact impact of these reports within national security agencies in only a few cases.  For example, the report that answered the question on global health mentioned earlier earned this praise from the National Intelligence Council: 

“Although the Mercyhurst "NIE" should not be construed as an official U.S. government publication, we consider this product an invaluable contribution to the NIC's global disease project: not only in terms of content, but also for the insights it provides into methodological approaches. The Mercyhurst experience was also an important lesson in how wikis can be successfully deployed to facilitate such a multifaceted and participatory research project.”

Likewise, in David Moore’s book Sensemaking:  A Structure for an Intelligence Revolution (published by the National Defense Intelligence College in 2011), the study on non-state actors in sub-Saharan actors produced in answer to the question mentioned above was judged more rigorous than a similar study conducted by the National Intelligence Council (in cooperation with the Eurasia Group).

Beyond the national security community, however, the impact of these reports on various businesses and other organizations is often easier to determine.  For example, senior managers at Composiflex, a mid-sized composites manufacturer, indicated, “We used this project as a seed for our new marketing plan in 2007 and now an industry that we had not even tapped before is 30% of our business.” 

Likewise, Joel Deuterman, the CEO of Velocity.net, an Internet Service Provider, stated, “The analysts discovered that our approach was actually a cutting-edge, developing standard in our industry…What really substantiated the data for us was to see many of our existing customers on the list. Then we knew we could rely on the validity of the ones they had found for us.”  

Even foreign organizations have seen the benefit of these products including Ben Rawlence, the Advisor for Foreign Affairs and Defense in the Whip’s Office of the Liberal Democrat Party in the UK, stating, “The research carried out by your students was first class, and has been of substantial use to Members of Parliament…  It was comprehensive, well sourced and intelligently put together.  I have had no hesitation recommending it to our MPs and Lords in the same way that I recommend briefings provided for us by professional research organisations…” 

While it is possible to imagine more rigorous testing of this model of the intelligence process, the long term success of the process in generating actionable intelligence for a wide variety of customers on a range of difficult problems in a very short time using limited resources is hard to ignore.  More importantly, not only has the process proven itself successful but this success has trended upwards as improvements have been made over the years in terms of structuring the course and teaching material consistent with this approach to the intelligence process.

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Intelligence in the 21st century is best thought of as a series of sub-processes operating interactively and in parallel.  

This conclusion, by itself, has significant implications for the training and education of intelligence professionals.  In the first place, it suggests that it is no longer possible to specialize in one area to the exclusion of another.  Intelligence professionals will have to be trained to think more broadly, to be able to jump more fluidly from modeling to collection to analysis to production and back as the process of creating intelligence moves forward over time.  

Likewise, hardware and software support systems will need to be designed that facilitate this leaping back and forth between the various sub-processes.  Designing products that work sequentially in a parallel world will not only frustrate but will also slow down the process of generating intelligence – a result that is absolutely counter to the intelligence needs of modern decisionmakers.  

Finally, as dramatic as this type of change might appear to be, it is, perhaps, better thought of as merely aligning the training and education of intelligence professionals with what it is they already do.