5 Idea Generation
5.5 CROSS-IMPACT MATRIX
T
he Cross-Impact Matrix helps analysts deal with complex problems when “everything is related to everything else.” By using this technique, analysts and decision makers can systematically examine how each factor in a particular context influences all other factors to which it appears to be related.When to Use It
The Cross-Impact Matrix is useful early in a project when a group is still in a learning mode trying to sort out a complex situation. Whenever a brainstorming session or other meeting is held to identify all the variables, drivers, or players that may influence the outcome of a situation, the next logical step is to use a Cross-Impact Matrix to examine the interrelationships among each of these variables. A group discussion of how each pair of variables interacts can be an enlightening learning experience and a good basis on which to build ongoing collaboration. How far one goes in actually filling in the matrix and writing up a description of the impacts associated with each variable may vary depending upon the nature and significance of the project. At times, just the discussion is sufficient. Writing up the interactions with the summary for each pair of variables can be done effectively in a wiki.
Analysis of cross-impacts is also useful when:
* A situation is in flux, and there is a need to understand all the factors that might influence the outcome. This also requires understanding how all the factors relate to each other, and how they might
influence each other.
* A situation is stable, and there is a need to identify and monitor all the factors that could upset that stability. This, too, requires understanding how the various factors might interact to influence each other.
* A significant event has just occurred, and there is a need to understand the implications of the event. What other significant forces are influenced by the event, and what are the implications of this influence?
Value Added
When analysts are estimating or forecasting future events, they consider the dominant forces and potential future events that might influence an outcome. They then weigh the relative influence or likelihood of these forces or events, often considering them individually without regard to sometimes significant interactions that might occur. The Cross-Impact Matrix provides a context for the
discussion of these interactions. This discussion often reveals that variables or issues once believed to be simple and independent are, in reality, interrelated. The information sharing that occurs during a small-group discussion of each potential cross-impact can be an invaluable learning experience. For this reason alone, the Cross-Impact Matrix is a useful tool that can be applied at some point in almost any study that seeks to explain current events or forecast future outcomes.
The Cross-Impact Matrix provides a structure for managing the complexity that makes intelligence analysis so difficult. It requires that all assumptions about the relationships between variables be clearly articulated. Thus, any conclusions reached through this technique can be
defended or critiqued by tracing the analytical argument back through a path of underlying premises.
The Method
Assemble a group of analysts knowledgeable on various aspects of the subject. The group
brainstorms a list of variables or events that would likely have some effect on the issue being studied.
The project coordinator then creates a matrix and puts the list of variables or events down the left side of the matrix and the same variables or events across the top.
The matrix is then used to consider and record the relationship between each variable or event and every other variable or event. For example, does the presence of Variable 1 increase or diminish the influence of Variables 2, 3, 4, etc.? Or does the occurrence of Event 1 increase or decrease the likelihood of Events 2, 3, 4, etc.? If one variable does affect the other, the positive or negative magnitude of this effect can be recorded in the matrix by entering a large or small + or a large or small – in the appropriate cell (or by making no marking at all if there is no significant effect). The terminology used to describe each relationship between a pair of variables or events is that it is
“enhancing,” “inhibiting,” or “unrelated.”
The matrix shown in Figure 5.5 has six variables, with thirty possible interactions. Note that the relationship between each pair of variables is assessed twice, as the relationship may not be
symmetric. That is, the influence of Variable 1 on Variable 2 may not be the same as the impact of Variable 2 on Variable 1. It is not unusual for a Cross-Impact Matrix to have substantially more than thirty possible interactions, in which case careful consideration of each interaction can be time consuming.
Analysts should use the Cross-Impact technique to focus on significant interactions between
variables or events that may have been overlooked, or combinations of variables that might reinforce each other. Combinations of variables that reinforce each other can lead to surprisingly rapid changes in a predictable direction. On the other hand, for some problems it may be sufficient simply to
recognize that there is a relationship and the direction of that relationship.
Figure 5.5 Cross-Impact Matrix
The depth of discussion and the method used for recording the results are discretionary. Each depends upon how much you are learning from the discussion, and that will vary from one application of this matrix to another. If the group discussion of the likelihood of these variables or events and their relationships to each other is a productive learning experience, keep it going. If key
relationships are identified that are likely to influence the analytic judgment, fill in all cells in the matrix and take good notes. If the group does not seem to be learning much, cut the discussion short.
As a collaborative effort, team members can conduct their discussion online with input recorded in a wiki. Set up a wiki with space to enter information about each cross-impact. Analysts can then, as time permits, enter new information or edit previously entered information about the interaction between each pair of variables. This record will serve as a point of reference or a memory jogger throughout the project.
Relationship to Other Techniques
Matrices as a generic technique with many types of applications are discussed in chapter 4. The use of a Cross-Impact Matrix as described here frequently follows some form of brainstorming at the start of an analytic project to elicit the further assistance of other knowledgeable analysts in exploring all the relationships among the relevant factors identified by the brainstorming. It can be a good idea to build on the discussion of the Cross-Impact Matrix by developing a visual Mind Map or Concept Map of all the relationships.
See also Complexity Manager (chapter 11). An integral part of the Complexity Manager
technique is a form of Cross-Impact Analysis that takes the analysis a step further toward an informed conclusion.
Origins of This Technique
The Cross-Impact Matrix technique was developed in the 1960s as one element of a quantitative futures analysis methodology called Cross-Impact Analysis. Richards Heuer became familiar with it when the CIA was testing the Cross-Impact Analysis methodology. He started using it as an
intelligence analysis technique, as described here, more than thirty years ago.