LKRU14 and LKAPAC: Five Numbers
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Important process characteristics and how they can help improve your company Alexei Zheglov Lean Kanban Asia-Pacific Bangalore, December 2014 FIVE NUMBERS
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Transcript of LKRU14 and LKAPAC: Five Numbers
Important process characteristics andhow they can help improve your company
Alexei ZheglovLean Kanban Asia-Pacific
Bangalore, December 2014
FIVE NUMBERS
@az1#lkapac
“When a measure becomes a target,it ceases to be a good measure.”
Goodhart’s Law
Flow Efficiency
Readyto Test
#1. Flow Efficiency
F
E
J
GD
GYBG
DE NP
P1
АВ
Customer Lead Time
Wait Wait WaitWork
IdeasReadyto Dev
5IP
Development Testing
Done
3 35
UATReady
to Release
∞ ∞
Work WaitWork
Official training material of Lean Kanban University, used with permission
Readyto Test
Flow Efficiency
F
E
J
GD
GYBG
DE NP
P1
АВ
Customer Lead Time
Wait Wait WaitWork
IdeasReadyto Dev
5IP
Development Testing
Done
3 35
UATReady
to Release
∞ ∞
Work WaitWork
Official training material of Lean Kanban University, used with permission
Work is waitingWork often waits herebecause of multitasking
Readyto Test
Flow Efficiency
F
E
J
GD
GYBG
DE NP
P1
АВ
Customer Lead Time
Wait Wait WaitWork
IdeasReadyto Dev
5IP
Development Testing
Done
3 35
UATReady
to Release
∞ ∞
Work WaitWork
Official training material of Lean Kanban University, used with permission
%100time lead customer
time addingvalue-efficiencyflow
Discussion: Flow Efficiency
• How would you measure flow efficiency in your
company?
• Time tracking is an obvious method, but an
ineffective one. What other methods can you
think of?
• If you’ve already tried measuring it in your
company, what was the result?
Discussion: Flow Efficiency
• How would you measure flow efficiency in your
company?
• Time tracking is an obvious method, but an
ineffective one. What other methods can you
think of?
• If you’ve already tried measuring it in your
company, what was the result?
SamplingTotal available work time
Sum of all customer lead times
Rough estimates (±5%) are often enough
Discussion: Flow Efficiency
• How would you measure flow efficiency in your
company?
• Time tracking is an obvious method, but an
ineffective one. What other methods can you
think of?
• If you’ve already tried measuring it in your
company, what was the result?
*-Zsolt Fabok, Lean Agile Scotland 2012, LKFR12; Håkan Forss, LKFR13
The result is often between 1 and 5%*
The result is not only the number!What did you decide to do?
When the Flow Efficiency is 5%...
If... Before After Improvement
hire 10X engineers 100 95,5 +4,7%
effort turns out to be 3 times as much 100 110 -9.1%
effort turns out to be 3 times less 100 96,7 +3,4%
cut delays by half 100 52,5 +90%
Arrival Rate
Flow Efficiency
#2. Arrival Rate
Balance Demand and Capability
The pizza delivery experts(not baking or topping)
Variety not only in ingredients,but also in classes of service!
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Demand is not homogenous
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Заказчики не только вне компании...
...но и внутри
Заказчики не только вне компании...
Customers not only outside the company...
...but inside, too
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Arrival rate is a number!(how many
per unit of time)
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Arrivals may be uneven and form patterns
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Product
featuresMarket 5/month regular
Avg. 10 days,
95% in 20 days
Analytic
research and
reports
A few key
customers10/year irregular
Avg. 1 week,
max 2
Estimates/Feas
ibility analysisSales 150/year random 24-48 hours
(Escaped)
defectsMarket 250/year
Peak in
January
Sev 1 in 2
hours, others in
2 days
Tool and
process
improvement
Team1 every 2-week
sprintregular
Avg. 2 weeks,
95% in 4
weeks
Satisfaction criteria and risksmay vary significantly
from one work item type to the next
Multiple classes of servicemay be offered
for each work item type
Example: Demand Analysis
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
user storyProduct
OwnerThey’re already in the backlog Stable velocity
The picture as the manager saw it before Kanban...
Take Home: Demand Analysis
Template
Work item
type
Where it
arrives fromArrival rate
Nature of
demand
Delivery
expectations
Option Discard Rate
Arrival Rate
Flow Efficiency
Real Options
Options have value.
Options expire.
Don’t commit earlyunless you know why.
Upstream Kanban Prepares OptionsReadyTo Dev
Е
И
Committed
Г
4 in process
Development
done
3
К
12
Testing
testing
3
Commitment point
4 -
Reqs.
2412 -
Biz. Case
4824 -
Ideas
∞
Committed WorkOptions
Discarded
O
rejected
P Q
$$$ spent acquiring options
Official training material of Lean Kanban University, used with permission
Max and min limitsensure sufficient options are always available
LK
Upstream Kanban Prepares OptionsReadyTo Dev
Е
И
Committed
Г
4 in process
Development
done
3
К
12
Testing
testing
3
Commitment point
4 -
Reqs.
2412 -
Biz. Case
4824 -
Ideas
∞
Committed WorkOptions
Discarded
O
rejected
P Q
$$$ spent acquiring options
Official training material of Lean Kanban University, used with permission
Max and min limitsensure sufficient options are always available
LK
?acquiredrejected
Innovative products, high market risk
Stable products, low market risk
*******90%
Software users never use 45% of features, 19% rarely (Standish)
=> Should the average software company discard 45-65% of options?
≈0
But your company is not average!
Microsoft XIT: 48%
Option Discard Rate
Utilization
Arrival Rate
Flow Efficiency
#4. Utilization
Discussion: 20%?
• Does your company have a policy letting
employees spend 20% of their work time on their
own projects?
• Did your implementation of this practice
involve...?
• Cost accounting?
• A system to propose and approve 20% projects?
• A time tracking system?
• Innovations and new products as a motivator?
0
10
20
30
40
50
60
70
80
90
100
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Queu
e Len
gth
Utilization
The Cost of Queue Depends on Utilization
0
10
20
30
40
50
60
70
80
90
100
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Queu
e Len
gth
Utilization
The Elusive 20%
20%
Option Discard Rate
Utilization
Lead Time
Arrival Rate
Flow Efficiency
#5. Lead Time
Kanban System Lead Time
DoneOptions Activity 1InputQueue
Output Buffer
∞???
Activity 2 Activity 3
?
Lead Time
The 1st
Commitment Point AC
D
Deterministic approachto a probabilistic process?
probabilistic
!!!
0
2
4
6
8
10
12
14
16
18
20
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 95-99 100-104
Example
0
2
4
6
8
10
12
14
16
18
20
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 95-99 100-104
Example
The best fit distribution:Weibull with
shape parameter k=1.62
Drill by Work Item Type
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
0
2
4
6
8
10
12
14
16
18
20
The data set containsmore than onetype of project
Four Types of Projects,Four Different Distributions
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
0
2
4
6
8
10
12
14
16
18
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
75
-79
80
-84
85
-89
10
0-1
04
0
1
2
3
4
5
6
0-4
5-9
10
-14
15
-19
20
-24
25
-29
40
-44
55
-59
60
-64
65
-69
70
-74
75
-79
95
-99
...
...
Delivery Expectations
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
shape average in 98%
1.62
1.23
1.65
3.22
in 85% of cases
30 days
35 days
40 days
56 days
<51
<63
<68
<78
<83
<112*
<110*
<99
Delivery Expectations
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
0
5
10
15
20
0-4
5-9
10
-14
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
65
-69
70
-74
75
-79
80
-84
85
-89
95
-99
10
0-1
04
shape average in 98%
1.62
1.23
1.65
3.22
in 85% of cases
30 days
35 days
40 days
56 days
<51
<63
<68
<78
<83
<112*
<110*
<99
Averages are not enough to describedelivery capabilities!
Averages don’t communicate variability.
Needed:average + high percentile
(usually 80-99%)
Weibull Distributions Occur Frequently
Operations, customer care(k<1)
Product development(k>1)
Weibull Distributions Occur Frequently
Operations, customer care(k<1)
Product development(k>1)
Your process’unique signature
Your process’Unique signature
Forecasting Cards
t
Bias
Feedback
How to “Read” a Distribution
Scale
Control
Expectations
Forecast
How to “Read” a Distribution
Knowledge work is service, too
Let’s measure things such thatwe get insights and powerful questions
Good Books
Credits
• http://en.wikipedia.org/wiki/Charles_Goodhart (CC-BY 3.0)
• http://en.wikipedia.org/wiki/File:Hvalsey.jpg (CC-BY 3.0)
• http://zh.wikipedia.org/wiki/%E6%AF%94%E8%90%A8%E9%A5%BC (CC-BY 3.0)
• "Wien Cafe Central 2004" by Photo: Andreas Praefcke - Photographed by
User:AndreasPraefcke.. Licensed under Creative Commons Attribution 3.0 via
Wikimedia Commons -
http://commons.wikimedia.org/wiki/File:Wien_Cafe_Central_2004.jpg#mediaviewer/Fi
le:Wien_Cafe_Central_2004.jpg
• Other images: my own, public domain
• Book covers: fair use
![The Acquisition of Cardinal and Ordinal Numbers in Cantonesecardinal numbers) or [rank.number-numeral-classifier-noun] (for the five ordinal numbers), embedded in test sentences as](https://static.fdocuments.in/doc/165x107/5e76d91190e28a04481b1908/the-acquisition-of-cardinal-and-ordinal-numbers-in-cardinal-numbers-or-ranknumber-numeral-classifier-noun.jpg)
