Even structurally simple manufacturing systems can be operationally complex. This operational complexity can be colloquially defined as the uncertainty associated with managing the dynamic variations, in time or quantity, across information and material flows at the manufacturing systems interface. This paper proposes a means of measuring the information demands placed on cellular manufacturing systems, as a result of this uncertainty. A utility function for complexity is proposed according to the relationships between the complexity and utility in a manufacturing system and the underlying trend that the system becomes more and more complex in an ever-changing environment is analyzed. This paper mathematically models the static entropy and the dynamic entropy of cellular manufacturing systems from an information-theoretic perspective. A unique feature of this measure is that it captures, in relative terms, the expected amount of information required to describe the state of the system. The measure provides flexibility in the scope and detail of analysis. Finally, an example is used to demonstrate the validity of the proposed methodology.