Friday, December 12, 2008

Top 5 Intelligence Analysis Methods: Multi-Criteria Decision Making Matrices/Multi-Criteria Intelligence Matrices (#2)

Part 1 -- Introduction
Part 2 -- What Makes A Good Method?
Part 3 -- Bayesian Analysis (#5)
Part 4 -- Intelligence Preparaton Of The Battlefield/Environment (#4)
Part 5 -- Social Network Analysis (#3)

Multi Criteria Decision Making (MCDM) is a well-known and widely studied decision support method within the business and military communities. Some of the most popular variants of this method include the analytic heirarchy process, multi-attribute utility analysis and, in the US Army, at least, the staff study (see Annex D). There is even an International Society on Multiple Criteria Decision Making.

At its most basic level, MCDM is used to evaluate a variety of courses of action against a set of established criteria (see the image below for what a simple matrix might look like). One can imagine, for example, considering three different types of car and evaluating them for criteria such as speed, cost and fuel efficiency. MCDM would suggest that the car that has the highest total rating across those three categories would be the best car to buy. In fact, Consumer Reports uses exactly this type of method in its famous "circle charts" of everything from cars to hair care products.


MCDM is flexible and works with a wide variety of data but there are numerous devils in the details of its implementation. The simple example above gets increasingly complicated when we start to examine the many other criteria that someone might use to evaluate a car. Likewise, there are problems with rating each of these criteria (Is a car that gets 27 miles to the gallon really worse than a car that gets 27.1 miles to the gallon?). Even worse is when the analyst starts to think about abstract evaluation criteria such as which of the three cars is "coolest"? You start thinking like this and you begin to understand why they have an international society dedicated to this method...

MCDM is, at its heart, an operational methodology, not an intelligence method, however. That said, we have had very good luck “translating” it into an intelligence analysis method (i.e. MCIM) in our strategic intelligence projects. These projects have covered the gamut from large-scale national security studies to small-scale business studies. The matrices can be simple (I actually used such a matrix to evaluate the 5 methods mentioned in this series) or enormously complex (The MCIM matrix on the likely impact of chronic and infectious disease on US national security interests clocks in at 15 feet long when printed).

The key difference between the operational variant and the intelligence variant is perspective. In the operatonal variant, the analyst is trying to figure out his or her organization's best course of action. In the intelligence variant, the analyst puts him or herself in the shoes of the adversary and attempts to envision how the other side might see both the courses of action available and the criteria with which the adversary will evaluate them. The intelligence variant has not, to the best of my knowledge, been validated but we have a grad student working on it.

The research agenda for this method (as with many of the other methods discussed so far) is straightforward. First, it has to be validated as an intelligence specific methodology. The anecdotal evidence and the evidence in the operational literature is good but further testing needs to be done. Second, analysts need to figure out which variants of MCIM work best in which types of intelligence situations. Finally, we need to get the method out of the school house and into the field.

Next Week: #1!

1 comment:

William said...

You must not forget to include MCDA methods that apply when the criteria are not independent, but rather superadditive or subadditive (i.e., synergistic). While I am not aware of any tools that explicitly capture this behavior (via Choquet or Sugeno integrals), it is fairly straightforward stuff.

For interested readers, check out the pdf file at http://ces.univ-paris1.fr/membre/Grabisch/articles/figueira_greco_ehrgott.pdf (section 3, in particular for a motivating example).