9. Delivered to the customer
Delivered to the customerTech Team started working on it
Touch point between Product and Tech Team
10. What is Lead Time? “Lead time” is the period
between a new task’s
appearance in your workflow and
its final departure from the
system.
11. In our case, we want to
investigate on the time between
two Jira workflow transitions:
from “doing” status to “trying it in
prod” status.
This measure is called “cycle
time”.
12. What is Cycle
Time? Cycle time begins at the moment
when the new arrival enters “in
progress” stage and somebody is
actually working on it.
20. ● Only issues done and
resolved
● Exclude Wallman issues
● From 1st June 2020 to 15th
November 2020
● Start date is
min(transitions(“doing”))
● End date is
min(transitions(“trying it in
prod”))
Export criteria
22. ETL
Extract, transform
and load
● Normalize data
● Merge Jira export with
transitions data
● Calculate “Cycle time”
● Focus on on data from 1st
June 2020 to 15th November
2020
● Remove outliers and wrong
data
● Anonymize data
52. Recap
● Cycle time is about
responsiveness
● Throughput is about
performance
But...
53. When a measure becomes a target,
it ceases to be a good measure.
Goodhart's law
54. In other words, when we set one specific goal,
people will tend to optimize for that objective
regardless of the consequences.
Goodhart's law unintended consequences
63. L = 𝝺W
Little’s Law
L := average number of tasks in the queue system
64. L = 𝝺W
Little’s Law
L := average number of tasks in the queue system
𝝺 := average service time in the queue system for a task
65. L = 𝝺W
Little’s Law
L := average number of tasks in the queue system
𝝺 := average service time in the queue system for a task
W := average number of tasks arriving per unit time
66. The long-term average number L of customers in a
stationary system is equal to the long-term average
effective arrival rate λ multiplied by the average time W
that a customer spends in the system.
The relationship is “not influenced by the arrival process
distribution, the service distribution, the service order,
or practically anything else”.
67. L = 𝝺W
Little’s Law in Kanban World
L := WIP
𝝺 := Throughput
W := Cycle Time
68. In Kanban terms, Little’s Law is
expressed a little differently, but
the idea is the same:
WIP = Throughput * Cycle Time
If we imagine the Kanban board
as the store, WIP is equivalent to
the number of customers inside
at any time, throughput is the
rate of customers passing
through the store and cycle time
measures how long each one
spends inside the system.
Little’s Law
69. This means that if two of the
three values are known, the third
value can be calculated without
knowing anything else about the
tasks, team or project:
● WIP = Throughput * Cycle Time
● Cycle Time = WIP/Throughput
● Throughput = WIP/Cycle Time
Little’s Law
71. Let’s assume that:
Avg. WIP = Avg. Throughput * Avg.
Cycle Time
● Avg. Throughput (weeks) =
5.14
● Avg. Cycle Time (days) = 7.20
● Avg. Cycle Time (weeks) =
7.20/7 = 1.03
So that:
Avg. WIP = 5.14 * 1.03 = 5.29
Little’s Law
72. The power of Little’s Law to
Kanban teams is not its ability to
predict WIP, Thoughput or Cycle
Time.
The true power lies in its ability
to influence team behavior with
its underlying assumptions.
In other words, if you want to:
● increase Throughput then
limit WIP;
● speed up the process, i.e.
reduce Cycle Time, then
once again limit the WIP.
The power of
Little’s Law
79. Proposal for next steps
[1] Start using new Jira Workflow
[2] Improve Team metrics using Jira plugins
[3] Introduce new Team metrics (performance, quality, etc.)
[4] Define Team metrics goals
...
[..] Introduce team metrics on Product team side?
80. References
[1] Agile Reloaded, Ferdinando Santacroce, 2020.
[2] Throughput and Cycle Time [2020-09-27].
[3] Measure Your Lead Time And Cycle Time [2020-09-27].
[4] Understanding Agile Team Metrics: Measure Many Things [2020-09-27].
[5] Unintended Consequences and Goodhart's Law | by Will Koehrsen [2020-09-27].
[6] Stable Systems: Little's Law and Kanban [2020-09-27].
[7] Little’s Law – the basis of Lean and Kanban [2020-09-27].
[8] Chapter 5 Little's Law [2020-09-27].
[9] Accelerate. Nicole Forsgren, Jez Humble, Gene Kim.
[10] Estimates. Vasco Duarte.
81. Meeting OKR
Objective: Share our experiments about delivery metrics
as measured by
Key Result 1: Finish meeting on time
Key Result 2: Answer to all questions
Key Result 3: Discuss next steps