by the power of metrics
TRANSCRIPT
By the power of metrics
LeanKanban Central Europe 2014 - #LKCE14 Wolfgang Wiedenroth @wwiedenroth
Metrics in the Kanban MethodPractices
1.Visualize
2.Limit WIP
3.Manage Flow
4.Make Process Policies Explicit
5.Develop Feedback Loops
6.Improve Collaboratively, Evolve Experimentally (using models/scientific method)
Metrics in the Kanban Method
Sustainability
Service-Oriented
Survivability
Kanban’s 3 Agendas
1.Visualize
2.Limit WIP
3.Manage Flow
4.Make Process Policies Explicit
5.Develop Feedback Loops
6.Improve Collaboratively, Evolve Experimentally (using models/scientific method)
Practices
Sustainability
Service-Oriented
Survivability
Kanban’s 3 Agendas
Metrics in the Kanban Method
20#
25#
30#
35#
40#
45#
50#
55#
60#
65#
70#
75#
80#
85#
90#
95#
100#
105#
110#
115#
1#May#2012#
7#May#2012#
11#May#2012#
17#May#2012#
23#May#2012#
29#May#2012#
4#Jun#2012#
8#Jun#2012#
14#Jun#2012#
20#Jun#2012#
26#Jun#2012#
2#Jul#2012#
6#Jul#2012#
12#Jul#2012#
18#Jul#2012#
24#Jul#2012#
30#Jul#2012#
3#Aug#2012#
9#Aug#2012#
15#Aug#2012#
21#Aug#2012#
27#Aug#2012#
31#Aug#2012#
6#Sep#2012#
12#Sep#2012#
18#Sep#2012#
24#Sep#2012#
28#Sep#2012#
4#Oct#2012#
10#Oct#2012#
16#Oct#2012#
22#Oct#2012#
26#Oct#2012#
1#Nov#2012#
7#Nov#2012#
13#Nov#2012#
19#Nov#2012#
23#Nov#2012#
29#Nov#2012#
5#Dec#2012#
11#Dec#2012#
17#Dec#2012#
21#Dec#2012#
27#Dec#2012#
2#Jan#2013#
8#Jan#2013#
14#Jan#2013#
18#Jan#2013#
24#Jan#2013#
Analyse# Selected# Planning# Planning#Done# Dev# Dev#Done# TesDng# TesDng#Done/Endgame# to#be#released# Released#
Visualize Cumulative Flow Diagram
y = No. of Tickets
y = Time
Work piling up
Departure Rate
Arrival Rate
Visualize
Release Cycle is getting shorter Daily Deployments
Weekly Deployments
Biweekly Deployments
Visualize
That’s how Flow looks like
Visualize That’s the opposite of Flow!
we call it Christmas holidays
Visualize
0"
1"
2"
3"
4"
5"
6"
7"
8"
9"
10"
11"
12"
13"
14"
15"
16"
17"
18"
19"
20"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10"11"12"13"14"15"16"17"18"19"20"21"22"23"24"25"26"27"28"29"30"31"32"33"34"35"36"37"38"39"40"41"42"43"44"45"46"47"48"49"50"51"52"53"54"55"56"57"58"59"60"61"62"63"64"65"66"67"68"69"70"
Lead Time Distribution Chart
y = No. of Tickets finished with lead time x
x = Lead Time
Average Lead Time
0"
1"
2"
3"
4"
5"
6"
6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 1" 2" 3" 4" 5" 6" 7" 8" 9"
MEDIAN"
VisualizeThroughput
x = Calendar Weeks
y = No. of tickets finished in calendar week x
Visualize
Visualized metrics let you see things faster
Visualized metrics let you identify pattern
Visualized metrics give everyone the same picture
Visualized metrics are great feedback loops
Manage Flow
Manage Flow
Demand
Capability
Manage Flow
Demand Capability
Flow = Balance Demand against Capability
Manage Flow
Capability AnalysisDemand Analysis
How much demand do we have?
What are the sources of our
demand?
Do we have seasonal
variance in demand?
What are the risk profiles that are attached to
different types of work?
What skills are required for different types of demand?
What are our current lead times? What is our
delivery rate?
What skills do we have?
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 53"
Manage Flow using Weibull
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 53"
Manage Flow using Weibull
Weibull with shape parameter k = 1.5
Mode = most common lead time Median = 50% Average 80% of tickets finish in less time 95% of tickets finish in less time 98% of tickets finish in less time
Manage Flow using Weibull
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 53"
0"
1"
1"
2"
2"
3"
3"
4"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10"
0"
1"
1"
2"
2"
3"
3"
4"
4"
5"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15"
Features
Bugs
Expedites
Manage Flow using Weibull
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 53"
Features Q(p;k, λ) = λ( - ln(1 - p))1/k
Number of data points: 143 Shape parameter (k): 1.64Scale parameter (λ): 11.64Average: 10.76
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15" 16" 17" 18" 19" 20" 21" 22" 23" 24" 25" 26" 27" 28" 29" 30" 31" 32" 33" 34" 35" 36" 37" 38" 39" 40" 41" 42" 43" 44" 45" 46" 47" 48" 49" 50" 51" 52" 53"
Manage Flow using Weibull
85% of tickets finish in 13.2 days
95% of tickets finish in 20.9 days
Q(p;k, λ) = 11.64( - ln(1 - p))1/1.64
0"
1"
1"
2"
2"
3"
3"
4"
4"
5"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15"
Manage Flow using Weibull
Bugs
Number of data points: 8 Shape parameter:Scale parameter: Average: 3.88
not enough data points, but visualisation gives us
an idea of the shape
0"
1"
1"
2"
2"
3"
3"
4"
4"
5"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15"
Manage Flow using Weibull
Bugs
Number of data points: 8Shape parameter: looks like between 1.25 and 1.50 Scale parameter: Average: 3.88
Manage Flow using Weibull and Forecasting Cards
k = 0.75
k = 1.25
k = 1.50
Alexei Zheglov
Manage Flow using Weibull and Forecasting Cards
0"
1"
1"
2"
2"
3"
3"
4"
4"
5"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15"
98% of tickets finish in 12.4 days
Manage Flow using Weibull and Forecasting Cards
Manage Flow using Weibull
Service Level Expectations (SLE) we can communicate
85% of all features can be expected in 13 days
Bugs can be expected to be delivered in between 3 (average) and 12 days (98%)
Manage Project Flow
Average Lead Time
Average WIP
Project Scope
Average Throughput
WIPLead Time
Throughput =
Manage Project Flow using Little’s Law
Calculate Project Lead Time
Project Lead Time = No. of Tickets Average Lead Time Average WIP
= 450 1.2 15 = 36 weeks
Manage Project Flow using Little’s Law
Calculate Project Budget
Average WIP = Average Lead Time No. of Tickets Delivery date in weeks
= 1.2 450 36
= 15 WIP
Manage Project Flow using Little’s Law
20% 20%60%
Project ScopeEnd Date
2nd le
g
1st leg
3rd leg
Delivery Rate
Manage Project Flow using Little’s Law
Metrics help you to better understand your
demand and capability
Metrics help you calculate Service Level Expectations (SLE)
for different work items
Metrics help you forecast your projects#
without estimating
Metrics to secure survival
Sustainability
Service-Oriented
Survivability
Kanban’s 3 Agendas
Service-Oriented
Product Development
Maintenance
Online Marketing
Access Management
Change Management
Problem Management
Survivability
What’s the purpose of the services we provide?
What criteria need to be satisfied to call the service fit for this purpose?
Survivability“Fitness Criteria are metrics that measure things customer value when selecting a service again and again.”
- Delivery Time- Quality- Predictiability- Safety (or conformance to regulatory requirements
David J. Anderson
SurvivabilityBugs per Week
0
15
30
45
60
31 32 33 34
SLA Compliance in %
0
25
50
75
100
April May June July
Lead Times
0
5
10
15
20
0 5 10 15 20
Ask your customer what they care about!
Make it your core metric#you always measure!
Metrics supporting changes
Metrics help us to distinct between good and bad
changes from an objective point of view
Metrics for improvementsEmotions
Risk
Measuring
Metrics for improvements
"Sometimes, you just have to roll back with your chair to take a second look from the back and make a good guess how the curve will end up."
- Troy Magennis at LKCE13 reception
Metrics for improvements
"We do only this until we have enough data to provide better sample."
- Troy Magennis at LKCE13 reception
Always support change with
measurements!
Metrics for improvements
WIP limit breach
defect rate customer
satisfaction
employee satisfaction
number of blockers
time spent on “real quick” work
time tickets were blocked
time waiting for external suppliers
rework
time spent on white noise
…
Not like that! Keep it simple!
#Urheber Markus Beyer - Herzlichen Dank!
Joe from Marketing Wanted Y
Took me 30min
Sue from ProductWanted Y
Took me 15min
CEOWanted Y
Took me 6h
Bob from Operations Wanted Y
Took me 60min
Joe from Marketing Wanted Y
Took me 45min
Regularly check your metrics, whether they have become Chindōgu!
chindōgu are sometimes described as "unuseless" – that is, they
cannot be regarded as "useless" in an absolute sense, since they do
actually solve a problem; however, in practical terms, they cannot
positively be called "useful".
https://en.wikipedia.org/wiki/Chind%C5%8Dgu
to check if your service is fit for purpose
Metrics help you
to evaluate your changes
to manage your projects
to manage Flow
to check if your service is fit for purpose
Collect metrics now
to evaluate your changes
to manage your projects
to manage Flow
