Cross-Impact Analysis

A cross-impact analysis is a method that helps us identify how likely we believe various events, or uncertainties, are to take place in the future. It also helps us think about how the occurrence of one event may impact the probability of another event occurring as well.

When to use it?

A great time to use a cross-impact analysis is once you have articulated a number of uncertainties about the future, and are curious about the degree to which each event’s occurrence may change how likely it is that the other events might also take place. It is a good way of exploring how various events may unfold, or be sequenced, in the future.

How to do it?

There are a number of different ways to conduct a cross-impact analysis, some of which are based more in mathematical algorithms, and others that are based more on intuition and subject matter expertise. At the CoLab, we have tended to use a particular method that is more grounded in subject matter expertise and intuitive knowledge.

  1. Draw a chart listing all of your critical uncertainties in the left hand column and across the top, as shown in the diagram.

  2. In the next column to the right, rank how probable you believe these events are to occur in the future. For now, rank these separately from each other.

  3. Moving across each row from left to right, rank any changes in how likely you believe the event in the left hand column is to occur, if the event listed across the top were to also take place. Make sure to consistently move across the rows in the same direction.

  4. Events can be ranked in a number of ways, for example:

    1. They can be ranked from 0-3 (no possibility of occurrence – highly likely to occur),

    2. Or very simply as Low, Medium, and High.

People: 2-8

Time: Dependent on number of uncertainties being ranked. At least 30 minutes.

Pros and Cons

  • Helps identify how the occurrence of some events in the future have potential to change the likelihood of other events taking place.
  • Is a participatory approach that draws on the knowledge of a group.


  • Is subjective to the internal biases and perspectives of participants.
  • Can not determine what will actually happen, can only provide a sense of how we think the occurrence of some events might impact the future and what other events are likely to happen.