WIP constraints are a powerful way to gain control over cycle time in the presence of variability. This is particularly important for systems where variability accumulates, such as in product development. WIP constraints exploit the direct relationship between cycle time and inventory, which is known as Little’s Formula.
we commonly use five key economic objectives as measures of performance for a project. We vary each measure independently and assess its influence on life-cycle profits. In effect, we are trying to determine the transfer function between each measure of performance and life-cycle profitability. This method is known as sensitivity analysis.
For simple single variable decisions, we only need to know the direction of the change. For multivariable decisions, we also need to know the magnitude of the change, and most importantly, we need a method to express all changes, in all variables, in the same unit of measure. This is the only way we can evaluate the overall economic consequences of changing multiple proxy variables simultaneously.
We need COD to evaluate the cost of queues, the value of excess capacity, the benefit of smaller batch sizes, and value of variability reduction. Cost of delay is the golden key that unlocks many doors.
Unhappy with late deliveries, a project manager decides he can reduce variability by inserting a safety margin or buffer in his schedule. He reduces uncertainty in the schedule by committing to an 80 percent confidence schedule. But, what is the cost of this buffer? The project manager is actually trading cycle time for variability. We can only know if this is a good trade-off if we quantify both the value of cycle time and the economic benefit of reduced variability.
this is a blind spot for many modern managers who are heavily influenced by the concept of the Pareto Principle, which observes that 80 percent of the leverage lies in 20 percent of problems. The dark side of the Pareto Principle is that we tend to focus excessively on the high payoff 20 percent. We overmanage this 20 percent, and undermanage the other 80 percent. This leads to what we might call the Pareto Paradox: There is usually more actual opportunity in the undermanaged 80 percent than the overmanaged 20 percent.
Reducing risk, which is the primary mission of testing, clearly creates economic value for product developers. In fact, reducing risk is so centrally important to product development that it is indispensable for us to quantify its economic impact.
we should make each decision at the point where further delay no longer increases the expected economic outcome. By avoiding “front-loading,” we can take advantage of the fact that market and technical uncertainty decrease with time. Instead of waiting for the “last responsible moment,” we can recognize that the cost of certain decisions can rise steeply past a certain point, or that the value created by waiting may have stopped increasing. The timing of economic choices should be based on their economics, not broad philosophical concepts like “front-loading” or “responsible deferral.”
When economics change, we must reevaluate the economic wisdom of our choices. Remember Principle E1, our primary objective is to make good economic choices. To blindly conform to the original plan when it no longer represents the best economic choice is the act of a fool.
