Log Cycle Time as a Predictor of Cost Reduction

From the time of Henry Ford it has been known that large reductions in cost result from radical reductions in process cycle time. In the case of a Model T, a reduction in cycle time from 14 days to 33hours (i.e. >90% reduction) allowed the same car to be sold at $345 vs. $850. It would be of great benefit if management could predict the cost reduction and resulting profit that would flow from investments in process improvement initiatives such as Lean, Six Sigma and Complexity reduction which reduce cycle time and improve quality. Empirical data indicates that cost reduction due to waste elimination is consistent with the log of the ratio of cycle time reduction. Little’s Law governs the average cycle time of any process, and is equal to the number of units of Work In Process divided by the Average Completion Rate. Little’s Law, when treated as a dynamical equation, results in an expression for process entropy which is also proportional to the log of the ratio of cycle time and WIP reduction at constant volume. Thus the entropy in an economic process follows the same log function as entropy and waste in a Carnot Heat engine. We hypothesize that the waste in an economic process is also proportional to entropy as in a Carnot engine. A practical procedure for necessary data collection is defined which will allow management to predict cost reduction due to process improvement. Additional case studies will test the validity of this Equation of Cost Reduction in which academics are invited to participate.