Reading this article (Doctor Panels Urge Fewer Tests for Patients), two Structural Dynamics concepts immediately come to mind—Moral Decision-Making and effective Cross-Model Conversation (see below).  The article recommending that “doctors curb the use of 45 common and often unnecessary medical tests and procedures” is encouraging since most previous attempts to rein in unnecessary care have faltered for the obvious reason: a loss of income.  Doctors asking other doctors within their ranks to sacrifice material gain is all but astonishing.  Arguably, to achieve these recommendations, members of the panel must have engaged in cross-model conversation, one—perhaps the best—means for resolving differences.


(Moral Decision-Making At the core of leadership is the act of making decisions.  All decisions have a moral component, but moral decision-making is a special class of decision making, for at its core is a moral action.  We define moral action as a willingness to sacrifice something—money, place or advantage—in order to do the right thing.  Most moral decisions result in a winner and a loser.  In Moral Decision-Making there is compassion for the other, and a willingness to set aside self-interest to a larger cause.

Cross-model conversation is a very specific process for dialogue, grounded in the idea that the difference between the ways two people view the world is not a problem if they have a way to constructively explore these differences. Cross-model conversation is a two-way reflective conversation dominated by sincere inquiry into how the other views the world. It aims at deepening the discourse by offering the other an opportunity to substantiate or supplement his or her model and by doing the same with one’s own. Two principles underlie the process: 1) that difference is a key source of learning about ourselves and our models, and 2) that it is pointless to assert that one model is “better” than another. Every model has its limits, which we must face in order to be able to grow. The only “bad” model is one that does not recognize its own limits, wrongly assumes it is complete, and presumes itself better than other models.

A complete Glossary of Terms will be available coming soon.)