Code Blue: Swift Trust and Team Dynamics of a Crash Cart Response

Swift Trust, much like it sounds, is the concept of rapidly coming to intra-team trust.  A doctor friend of mine who introduced me to the term, explained it with the context of the ad hoc team of MDs and nurses responding to a cardiac arrest, a code blue.

I have been thinking about this throughout a book I am reading now, Honest Signals, by Alex (Sandy) Pentland from the Human Dynamics group of the MIT Media Lab.  In it, Prof. Pentland discusses physiological social signaling, and one point particular to swift trust stood out:  with great accuracy, one can predict behavioral outcomes using a “thin slice” of observation.  One study was able to predict six-year marital success based on just the first three minutes of a marital conflict.  There are many more studies showing similar success including job interviews, therapist competency ratings, and courtroom judges’ expectations of trial outcomes. My guess is there are things about the crash cart scenario which take advantage of this.

Some thoughts about this applied to code blue teams:

  1. the roles are well defined, so the amount of politicking is reduced
  2. time pressure pushes you to trust your colleagues, as there is little other choice
  3. the desired outcome is constrained, so you are only asked to trust in this specific situation
  4. trust develops rapidly with success
  5. trust develops when you don’t have a choice about the team over the long term. (time frame is short, so don’t know if this comes into play).

If these are right, here are a few predictions about the crash response process:

  1. there are a number of quick steps taken as a group before administering to the patient.  That would help establish some trust right at the beginning.
  2. the team members know each other at least by reputation, that goes a long way to giving the benefit of the doubt.
  3. the outcome is critical, so everyone is pushed to excel. This works in the the trust/success feedback loop.
  4. team members talk about crashes with their non-team colleagues.  this helps the reputation feedback.

Are there any MD’s or RN’s out there who care comment?  I have only the most cursory knowledge about the way the team is conducted, not to mention the actions team members take.  Does this fly?

[Photo credit: Simon]

What we can learn about social networks from contract law

I am big fan of looking to outside fields for ideas and expertise. Case-in-point: I recently came across a reference to a great study about contract law – when people rely on the contract for enforcement during the course of business, and when they don’t. Hint: they usually don’t; they rely on the relationship.

Translating the findings to social network analysis, we come up with six great pieces of advice for all aspiring master networkers:

  1. Established relationships provide more value than new ones.

  2. Your reputation is critical to creating new relationships.

  3. The more your peer gets out of a relationship, the more you will get out of it: deliver excellence.

  4. If you are stuck together for the foreseeable future, you will both get more out of the relationship. This could be from getting forced to trust each other or pushing harder to get more out of the relationship.

  5. New relationships are easier through introductions as the introducer can punish the introducee, through reputation or otherwise, if he does not deliver.

  6. Your network is your asset and yours alone, no one is invested the way you are to maintain your relationships.

Paper discussed:

Johnson, Simon H., McMillan, John NMI1  Woodruff, Christopher M.,   (January 2002). MIT Sloan Working Paper No. 4338-02; Stanford Law  Economics Olin Working Paper No. 227. Which I found referenced in (and translated the summary from) Avinash K. Dixit’s Lawlessness and Ecomonics: Alternative Modes of Governance.

Bailouts: Understanding Risk in a Networked Economy

Individual power increases network risk. When the power goes, so does the network.

But, this risk can also mobilize everyone else to buoy up the network by supporting the powerful (AIG rescue) or group cooperation (bailout lobbying).  When a power fails, there will be painful redistribution of wealth (Lehman Brothers) and the market as new relationships are established.  The market redistribution remains to be seen, but JPMorgan’s buying up relationships (the network) left and right.

Recommendations to the survivors. It’s easier to buy existing relationships through M&A than to create them from scratch, so think specific geographies and buy local; that’s where you’ll find the majority of relationships. For all those new customers you acquire reach out to them early and often.  Build the relationships that kept them with your acquiring company.

Network risk is inherent to trading, and traders will never willingly open their books. The bulk of a trader’s value is in his judgment, not the actual trading.  If you knew what they were buying and selling, you could duplicate their portfolio without paying their fees.  But, there’s an opportunity for a new Moody’s: grade trading funds on network risk.