Seeing What Others Don't

The remarkable ways we gain insights

Causal Landscape 2.0

How to sort out the cause of accidents and disturbances.

My previous piece on the Causal Landscape described a strategy for describing why events occurred. The Causal Landscape avoids simplistic single-cause explanations and it also avoids exhaustive catalogs of the entire field of relevant causal factors. 

The causal landscape is a 2-step method for highlighting the few causes worth addressing. We identify the causal field and then rate each cause twice, first an Impact score for how much it influenced the effect and second a Reversibility score for the ease of eliminating that cause. The causes that had the strongest impact and are the easiest to reverse are the ones we can act on to prevent future accidents or adverse events. They stand out from the rest of the causal field. The complexity of the causal field isn’t ignored — it just isn’t allowed to overwhelm and discourage us. 

I received a number of comments on this entry, including one from Scott Snook, the author of a wonderful book, Friendly Fire, about the causes leading to a fratricide event in northern Iraq. Snook is a retired Army Colonel and currently is on the faculty of the Harvard Business School. My previous Causal Landscape entry drew heavily on Snook’s work, and I was happy to get his reactions:

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“I always struggle with this: How far up-stream do we swim? And what's the phenomenological distinction between "general states" that "set the conditions" which increase the likelihood of the event v. necessary conditions for the event to actually occur (counterfactual approach). In this piece you seem to take a more pragmatic approach: Which nodes could we have actually altered or reasonably done something about? If I were King for a day, I'd prefer to attack the deeper-rooted general conditions (e.g. Inter-service rivalry, few joint training exercises, etc.) that increased the likelihood of not only this particular accident, but also an entire family of others.

“On the ten year anniversary [of the Blackhawk fratricide event], I received several communications from family members who are still haunted by this tragedy. No matter how far upstream we swim or how much we learn, it will never "make sense" to them.” [S. Snook, personal communication, April 23, 2014]

Snook’s comments echoed some of the reactions I have gotten from other audiences who like the idea of a causal landscape but want to direct it forwards, at preventing future accidents, not backwards at the previous accident. 

Several psychotherapists suggested using the Causal Landscape with their clients. For example, a client seeking relief from anxiety might describe a range of conditions and triggers that provoke anxiety reactions, as a starting point for reducing anxiety episodes in the future.

So I have modified the causal landscape in the following ways.

First, the Impact score should address, not just the current accident or outcome but this general type of problem. Thus, a military planner can use the friendly fire tragedy to see if there is a way to improve coordination between Army and Air Force. A psychotherapist can highlight the conditions and triggers that lead to a client’s anxiety episodes.   

Second, the Reversibility score, the ease-of-change ratings, can use a 4-point rating scale:

4 = Impossible to change. For the military shoot-down incident, these factors would include the fall of the Soviet Union, which contributed to the tragedy but cannot be undone. Similarly, for anxious clients wanting to understand why they are so easily overwhelmed, causes such as childhood neglect and heredity may play a role but can’t be undone.

3 = Very difficult to change. For the helicopter shoot-down, that would include a shrinking defense budget. For the anxious client, it might include financial problems and chronic pain.

2 = Changeable with some effort. Snook mentions two things he would like to alter — interservice rivalry and few joint training exercises. Making these changes could prevent or reduce lots of different problems. The benefits strongly outweigh the costs. Similarly, therapists might help anxious clients learn general strategies such as coping skills.

1 = Simple to change. The shoot=down would have been prevented if only the military did little things like arranging for helicopter representatives to attend the weekly coordination meetings. Simple fixes like this would have prevented the shoot-down but wouldn’t create more general benefits. Similarly, treating anxious clients with anti-anxiety medications is easy to implement but addresses only the immediate symptom.

Third, we should probably distinguish trigger causes from enabling causes. A trigger cause is immediate and obvious, like dropping a lighted match onto a stack of newspapers and setting a house on fire.  The lighted match is a trigger cause. The presence of oxygen in the house is an enabling cause. The trigger cause gets the attention, but isn’t always the best cause to address. Firefighters may spray foam on the fire to smother it — deprive it of oxygen. A psychotherapist may listen when a client complains that a recent arbitrary action by her domineering and insensitive husband made her feel helpless and anxious, but a therapist might want to spend time on an enabling cause — the client’s inability to assert herself, which has played out with her husband, her daughter, and with colleagues at work.

Fourth, we may sometimes find it useful to compare different causal landscapes. Thus, psychotherapists might contrast the causal landscape drawn up by a client with the therapist’s own causal landscape for that client’s difficulties. 

The Causal Landscape 2.0 retains the original goal of portraying a few actionable issues within the larger causal field.  By expanding it in the four ways described above, hopefully it will be more helpful in diagnosing problems and crafting plans. I will enjoy hearing your reactions and suggestions for developing the Causal Landscape into a more useful tool.                                                                                                   

 

Gary Klein is Senior Scientist at MacroCognition LLC; his most recent book is Seeing What Others Don't: The remarkable ways we gain insights.

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