Interrelationship Digraph
The Interrelationship Digraph maps how a set of problems or factors drive and get driven by each other, by counting outgoing versus incoming arrows, so you can see which are root causes and which are just symptoms.
Reach for this when…
- A list of problems all feel connected but nobody can say which one to fix first.
- Fixing one issue keeps producing three new ones somewhere else.
- A root-cause exercise keeps circling without landing anywhere.
How to run it
- List every factor or issue relevant to the problem, eight to twenty works best.
- Draw an arrow from each factor to every other factor it directly causes or influences.
- Count each factor's outgoing and incoming arrows.
- Factors with more outgoing than incoming arrows are drivers, root causes.
- Factors with more incoming than outgoing are outcomes, symptoms worth watching but not the place to intervene.
A worked example
Situation. Aya Kouassi was operations head at Espoir Community Clinic in Abidjan, Cote d'Ivoire, where patient complaints, staff burnout, long waits and high no-show rates were all being discussed as separate problems.
Applied. She mapped twelve related factors with her team and drew the influence arrows between them; understaffed reception came out with nine outgoing arrows and one incoming, driving nearly everything else on the list, including the burnout.
Result. The clinic funded one extra reception role instead of five separate fixes, and the no-show rate dropped as booking calls got answered faster.
The catch
The digraph is only as good as the arrows drawn in the room, a dominant voice can steer which relationships get drawn and which get missed. With more than about twenty factors, counting arrows by hand becomes unreliable and the exercise loses rigour. It identifies root causes within the list you brought to the room, not causes you failed to think of.
A factor with no arrows in or out isn't neutral, it's usually one nobody wanted to argue about.