---
title: "Cross impact analysis"
chunk: 2/2
source: "https://en.wikipedia.org/wiki/Cross_impact_analysis"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:43:30.297149+00:00"
instance: "kb-cron"
---

==== Relationship to Delphi technique ====
The accuracy of the math and specific events requires special expertise in the events or topic of discussion. In order to get the insight needed to get events and calculations, analysts typically contact a large number of experts and ask their opinions on events or probabilities in person as groups or through surveys.
These groupings often resemble the Delphi Technique, which is an analytic technique that gathers a group of experts on a subject together and asks their opinion on a scenario or prediction. Usually, analysts consider the average prediction or scenario as the most likely to occur. The two are so closely related, that analysts often use the two techniques in combination or as part of a larger methodology.

==== Strengths ====
The futurist forecasting style of cross-impact analysis carries a few key strengths. Its use of groups of experts ensures a number of opinions worth considering when calculating probabilities of events. The level of mathematics in calculating probabilities ensures that the results are as accurate as a researcher can make them. In addition, when used on consort with other analytic techniques, this type of cross-impact analysis can give greater quantitative results to an otherwise qualitative analysis. The relative conformity of methods ensures that analysts using different methods or simulations can come to similar results, making the results testable in a broader setting.

==== Weaknesses ====
Many of the strengths of the futurist forecasting style of cross-impact analysis give rise to many of its weaknesses. The conformity of the style generates a certain level of inflexibility when dealing with variables other than events, like environmental conditions or political issues. In addition, the severe level of mathematics involved in this style leads to long delays as scenarios must be run to ensure mathematical accuracy of probabilities, or particular issues with Bayes' theorem appear. The level of math also require researchers to either be knowledgeable in math or additional computer programs to deal with the scenarios and probabilities of the method.

=== Intelligence analysis style ===
Shortly after Theodore Gordon and Olaf Helmer developed the original cross-impact method, the United States intelligence community picked up the technique and has been using it for over thirty years.
While the basic premise of relationships and impacts between multiple variables remains the same, the intelligence community modified cross-impact analysis to meet its various needs.
The intelligence community has created a more flexible and variable system than the original methodology. Event relationships and impacts are still similar to the method incorporated by futurists. However, intelligence analysts have expanded the parameters of cross-impact analysis beyond comparing events to include variables like environment, political circumstances, and popular opinion to influence probabilities of certain events. In addition, intelligence analysts can choose to use more flexible measurements like "enhancing", "inhibiting", or "unrelated" instead of the rigid mathematics of the tradition methodology to include non-event variables.

==== Cross-impact matrix ====
A major part of the intelligence analysis style of cross-impact analysis is the cross-impact matrix. The matrix is a visualization of the cross-impact analysis and allows for modification. It also allows an analyst to find both the most influential variables and those variables that are impacted by the most other variables, not just direct, one-to-one relationships. While several traditional cross-impact analysis methods suggest the creation of a matrix, the priority still relies in probabilities, one-to-one relationships, and the order of events.
In the intelligence analysis style cross-impact matrix, analysts use pluses and minuses instead of numerical values allowing for non-event variables and allowing the analyst to compare variables directly to all other variables without calculations.

==== Strengths ====
Intelligence analysis style cross-impact analysis has several key advantages. The flexibility of the model allows for analysts to measure different types of variables against each other, not just probable events. In addition, the ability to discard stringent mathematical criteria means that researchers do not need extensive mathematics training or specialized software to use cross-impact analysis. This also enables experts in a topic to use the methodology relatively quickly without having to cross-check the numerous calculations faced by the Futurist Forecasting Style.

==== Weaknesses ====
The lack of stringent procedures of the intelligence analysis style also bring considerable drawbacks. The flexibility of the style relies heavily on the opinions and knowledge of the analysts involved, and is difficult to reproduce results with a different group. In addition, the option to remove mathematics can harm analysts by creating results that do not have numerical values to back them. This lack of mathematics may make the process easier at first, but the amount of specialized software is limited when compared to the Futurist Forecasting Style, making work more tedious as the number of variables increases.

== Applications ==
Researchers can use cross-impact analysis for a wide variety of applications. Futurists have already used the methodology for forecasting events in specific industries, politics, markets, and even entire communities.
In intelligence analysis, analysts can use the method to predict events, conditions, or decisions based on a wide variety of variables and conditions at local, national, and international levels.

== See also ==
Futures techniques
Probability
Analysis of competing hypotheses

== References ==