Abstract: We depend upon explanation in order to "make sense" out of our
world. And, making sense is all the more important when dealing with change.
But, what happens if our explanations are wrong? This question is examined with
respect to two types of explanatory model. Models based on labels and
categories we shall refer to as "representations". More complex models
involving stories, multiple algorithms, rules of thumb, questions, ambiguity we
shall refer to as "compressions". Both compressions and representations are
reductions. But representations are far more reductive than compressions.
Representations can be treated as a set of defined meanings – coherence with
regard to a representation is the degree of fidelity between the item in
question and the definition of the representation, of the label. By contrast,
compressions contain enough degrees of freedom and ambiguity to allow us to
make internal predictions so that we may determine our potential actions in the
possibility space. Compressions are explanatory via mechanism. Representations
are explanatory via category. Managers are often confusing their evocation of a
representation (category inclusion) as the creation of a context of compression
(description of mechanism). When this type of explanatory error occurs, more
errors follow. In the drive for efficiency such substitutions are all too often
proclaimed – at the manager's peril.