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. Draw a chart listing all of your critical uncertainties in the left hand
column and across the top, as shown in the diagram.
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.
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.
Events can be ranked in a number of ways, for example:
They can be ranked from 0-3 (no possibility of occurrence – highly likely to
occur),
Or very simply as Low, Medium, and High.
Requirements
People: 2-8 Time: Dependent on number of uncertainties being ranked. At least 30
minutes. Pros and Cons
Pros: - 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.
Cons: - 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.
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