This website covers topics on knowledge management, personal effectiveness, theory of constraints, amongst other topics. Opinions expressed here are strictly those of the owner, Jack Vinson, and those of the commenters.

We All Fall Down

I took We All Fall Down by Julie Wright and Russ King with me on a business trip and found that I couldn't put it down, once I had started it.  And I've continued thinking about the ideas and the central problem discussed in the book - it seems to show up everywhere.  That sounds like a ringing endorsement to me.

The book is a business novel that tells the story of how a hospital administrator discovered the Theory of Constraints and applied what she learned to the operation of her hospital -- and in classic business novel style, she applies some of the principles to her personal life. 

The novel walks through the use of several TOC "thinking processes," such as the conflict cloud and the current reality tree.  One thing that was interesting to me was the way in which the central character developed these tools and then turned them around for use in conversation with people with whom she was trying to come to agreement about a course of action.  There was a methodical process of developing the logic, and then just as methodically turning it around for use in discussion.  The way this worked out in the novel was the demonstration of how each subsystem interacts with the others - and that when the subsystems act locally, they can easily make a mess of things for the system as a whole.  This is the classic local optimization problem.

In my life today, I see application of the lessons of the book.  I frequently hear from our users that there are barriers to extending the use of the software beyond a certain point, even though many people agree in general that the software could be worthwhile.  I think there are some elements of the plan missing between the general agreement of value and actual implementation.  And as the vendor, we need to help our customers see where that resistance might be and look for mechanisms to help them devise the best solutions possible.

How do you know when you are effective?

Prove your data