π‘

Earlier when I first introduced Equation (1) I had stated that there was really only one assumption that needed to be in place for it to work. Well, in the interest of completeness, technically there were three. For Equation (1) we need: A steady state (i.e., that the underlying stochastic processes are stationary) An arbitrarily long period of time under observation (to guarantee the stationarity of the underlying stochastic processes) That the calculation be performed using consistent units (e.g., if wait time is stated in days, then Arrival Rate must also be stated in terms of days).

π

823

823

π

.littleslaw steady state,same units and long pleriod of time

β‘οΈ

π‘

Average Cycle Time = Average Work In Progress / Average Throughput If you have ever seen Little's Law before, you have probably seen it in the form of the above equation. What few Agile practitioners realize, however, is that Little's Law was originally stated in a slightly different form: Average Items In Queue = Average Arrival Rate * Average Wait Time

π

1266

1266

π

.flow .littleslaw .queueing

β‘οΈ

π‘

there are five assumptions necessary for Little's Law to work, they are: The average input or Arrival Rate (l) should equal the average Throughput (Departure Rate). All work that is started will eventually be completed and exit the system. The amount of WIP should be roughly the same at the beginning and at the end of the time interval chosen for the calculation. The average age of the WIP is neither increasing nor decreasing. Cycle Time, WIP, and Throughput must all be measured using consistent units.

π

1486

1486

π

.kanban .littleslaw

β‘οΈ