When you merge onto a freeway and are stuck in bumper-to-bumper traffic, you know right away that its going to be a long trip. Similarly, you can predict the cycle time of your work before it is finished without time consuming, and often incorrect, estimation. Sound like magic? Fortunately for all of us, it’s not.
This talk explains the basics of queueing theory; demonstrates how allocation models and pull policies affect the cycle time of work; discusses the effects of batch size and variability on queues; and teaches how to successfully monitor your workflow to get leading indicators of effectiveness. With this information, you’ll be doing better forecasting, and achieving better outcomes, in no time!