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How having this data
impacts understanding
of Customer
expectations?
How having this data
helps you improve your
Service?
What kind of
improvement does this
data help guide? What kind of decision is
this data helping with?
Little’s Law
Avg. Delivery Rate =
Avg. WIP
Avg. Lead Time
Predictable, yet not
deterministic
“easiest” to
control
• Average arrival rate = average departure
rate (constant WIP)
• All work that enters the system must
flow through to the end
• The average age of WIP is constant
Conservation of Flow
From the Customer’s perspective, what matters is flow of value.
3 “flow metrics”. They are in different “classes of risk”
Turns out that the one that Customers care about the most is the one that carries the most risk. That’s why we focus on measuring and managing Delivery Lead Times.
Those 3 metrics are related.
Of all 3, WIP is the one that it is “easy” to directly control. That’s why we use WIP constraints as the tool to manage the other two.
Aging of items may be a useful health indicator to monitor.
Mode: most seen (and remembered) value. High probability lead times will be over that.
Median: useful in establishing short feedback loops to continuously validate forecasting models and project and release plans.
63rd Percentile: used in estimating the scale parameter
80th Percentile: SLAs