See how metrics can be used with your Kanban System for managing flow, your project and changes.
At least three practices of the Kanban Method imply the use of metrics. Metrics can be powerful tools. Sadly most kanban systems don’t make use of them and miss out on a big chance to make things easier. Metrics can help us with lots of different things we encounter in business like finishing projects on budget and on time, fighting for survival in the market, and continuous change to adapt in this complex world. Learn how metrics can help you and how to choose the right metric for your situation.
Most teams need to answer questions like “When will it be done? What can I get by date X?”. However, common estimation approaches often fail to give us the predictability we want, and tend to introduce bad behaviours like hard deadlines and hiding uncertainty.
In this session, I’ll show you how, step by step and with real life examples, my team uses their historical data and metrics to forecast the future and answer these questions with confidence.
Download slides at: http://bit.ly/2pD9rfQ
Book discount link: http://leanpub.com/metricsforbusinessdecisions/c/MATTIA20-BZXib2F
Kanban Metrics in practice for leading Continuous ImprovementMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can drive continuous improvement and forecast the future and take your Kanban system to the next level! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/4CkKJd
PDF: https://goo.gl/VDW93U
Kanban Metrics in practice at Sky Network ServicesMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can really take your Kanban system to the next level - drive continuous improvement and forecast the future! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/19wOjU
PDF: https://goo.gl/AM69MF
Prioritization – 10 different techniques for optimizing what to start next ...Troy Magennis
10 different prioritization techniques to help understand what to START next. Shows the evolution between choosing at random up to full economic analysis. First presented at Agile 2017 in Florida.
Most teams need to answer questions like “When will it be done? What can I get by date X?”. However, common estimation approaches often fail to give us the predictability we want, and tend to introduce bad behaviours like hard deadlines and hiding uncertainty.
In this session, I’ll show you how, step by step and with real life examples, my team uses their historical data and metrics to forecast the future and answer these questions with confidence.
Download slides at: http://bit.ly/2pD9rfQ
Book discount link: http://leanpub.com/metricsforbusinessdecisions/c/MATTIA20-BZXib2F
Kanban Metrics in practice for leading Continuous ImprovementMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can drive continuous improvement and forecast the future and take your Kanban system to the next level! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/4CkKJd
PDF: https://goo.gl/VDW93U
Kanban Metrics in practice at Sky Network ServicesMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can really take your Kanban system to the next level - drive continuous improvement and forecast the future! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/19wOjU
PDF: https://goo.gl/AM69MF
Prioritization – 10 different techniques for optimizing what to start next ...Troy Magennis
10 different prioritization techniques to help understand what to START next. Shows the evolution between choosing at random up to full economic analysis. First presented at Agile 2017 in Florida.
Practical Agile Analytics: Reduce uncertainty and stop making such a big deal...Steven J. Peters, PhD
These slides focus on analyzing user story size estimates of and actual task hours scrum teams to gauge the uncertainty around those estimates. An approach is suggested for reducing uncertainty and improving user story size estimation accuracy.
One of the powerful aspects of Kanban is the statistical analysis of its metrics. This presentation talks about common Kanban metrics and how to interpret them.
Planning is incredibly important for businesses to reduce risk and create value, but what happens when the plan is almost always wrong? Software development is inherently hard to plan, but there are some great Agile tools available to help us plan effectively. This brown bag explores some of these Scrum ceremonies and tools available in the Agile world.
Agile is all about focus on creating value for the customer in a sustainable way. Actions that lead to business results and happier customers are a consequence of the behaviour of people. Agile coaching supports this by providing insights to people and the organization so they can choose what behaviour to change and how. This new behaviour will lead to improved business results and satisfied customers, or it leads to a more sustainable way - for the organisation - to achieve the business results.
How effective is the coaching and does it ultimately lead to changed improved business results? In this session Pieter demonstrates one way of linking the team actions to observed change in result as seen by the customer. This is demonstrated using data and methods taken from data science.
Welcome to the data-driven world.
39% of executives say their companies are already highly data-driven, but mentioning data can often result in concerned faces. Why is this? Is it the toxic nature that 'metrics' have become synonymous with or is it because we view using data as a dangerous flirtation with placing more value in tools and processes?
This session will showcase how you can bring to life the scientific method in your coaching arsenal. I will share stories of data-based coaching in PwC and how we leverage it to have open, transparent conversations and more informed decision making.
Cycle times and the Evolution From Story PointsScott Aucoin
Deck from a talk on cycle times and how to apply them for informed decision making (forecasting, team building, balance, process improvement) and evolution from traditional estimation approaches.
KANBAN AT SCALE: A SIEMENS HEALTH SERVICES CASE STUDY (BENNET VALLET & DAN VA...Lean Kanban Central Europe
This presentation will describe the approach taken for one of the world’s largest Kanban implementations at Siemens Health Services. It will describe how Kanban augmented existing agile practices there, and it will examine the achieved benefits of “flow” as demonstrated by real project data. Through a careful consideration of successes, challenges, and ongoing opportunities, this case study should be very meaningful to software product/development management organizations of any size whose funding, business operations, and profitability are dependent upon achieving a high degree of operational efficiency, transparency, and predictability.
Statistics for UX Professionals - Jessica CameronUser Vision
Are you looking to expand your research toolkit to include some quantitative methods, such as survey research or A/B testing? Have you been asked to collect some usability metrics, but aren’t sure how best to go about that? Or do you just want to be more aware of all of the UX research possibilities? If your answer to any of those questions is yes, then this session is for you.
You may know that without statistics, you won’t know if A is really better than B, if users are truly more satisfied with your new site than with your old one, or which changes to your site have actually impacted conversion rates. However, statistics can also help you figure out how to report satisfaction and other metrics you collect during usability tests. And they’re essential for making sense of the results of quantitative usability tests.
This session will focus on the statistical concepts that are most useful for UX researchers. It won’t make you a quant, but it will give you a good grounding in quantitative methods and reporting. (For example, you will learn what a margin of error is, how to report quantitative data collected during a usability test - and how not to - and how many people you really need to fill out a survey.)
Are you looking to expand your research toolkit to include some quantitative methods, such as survey research or A/B testing? Have you been asked to collect some usability metrics, but aren’t sure how best to go about that? Or do you just want to be more aware of all of the UX research possibilities? If your answer to any of those questions is yes, then this session is for you.
You may know that without statistics, you won’t know if A is really better than B, if users are truly more satisfied with your new site than with your old one, or which changes to your site have actually impacted conversion rates. However, statistics can also help you figure out how to report satisfaction and other metrics you collect during usability tests. And they’re essential for making sense of the results of quantitative usability tests.
This session will focus on the statistical concepts that are most useful for UX researchers. It won’t make you a quant, but it will give you a good grounding in quantitative methods and reporting. (For example, you will learn what a margin of error is, how to report quantitative data collected during a usability test - and how not to - and how many people you really need to fill out a survey.)
An agile development process is designed to allow us to respond to change, but this process depends on the people using it. As participants in an agile process, do we think and behave in a way that helps or harms our process? As individuals, are we actually as tolerant of change and randomness as our manifesto says we are, or do we subscribe to our methodology of choice in hopes of a smooth, predictable project? One can easily fall into the trap of being a tourist in his or her professional life--someone whose day gets worse when things don't go as planned. This talk will illustrate what it means to do the opposite and wander through our development process by fighting our bias toward stability and predictability. We'll see how "wandering" through some of our typical activities--like testing, planning, and organizing teams--can help us take full advantage of changing requirements and volatility, improve our agile process, and make our days get better with randomness.
Estimating with MAGIC Approach – Measure, Analyze, Improve and Control without ‘Guess’ work
#) Measure & Analyze using ‘Story Point Matrix’ based on Functional & Technical Analysis
#)Improve & Control using Statistical Data Modeling based on Empirical Data extracted from agile project management tool
Presentation for the Nexus Conference on the Internet of Things and the Evolu...Lora Cecere
Presentation prepared for the Nexus conference on the Internet of Things and the factors that drive Technology Adoption. Focus on Big Data, Digital Supply Chains and Internet of Things.
TQM QCC / SGA BY DURAISAMY R - M/s SHRISHTI CONSULTANTS CHENNAI ( www.shrisht...Duraisamy R
TOTAL QUALITY MANAGEMENT (TQM ), QUALITY CONTROL CIRCLES ( QCC ), SMALL GROUP ACTIVITIES ( SGA ), PROBLEM SOLVING TOOLS ( PST ), TOTAL EMPLOYEE INVOLVEMENT ( TEI ) MODEL,
Practical Agile Analytics: Reduce uncertainty and stop making such a big deal...Steven J. Peters, PhD
These slides focus on analyzing user story size estimates of and actual task hours scrum teams to gauge the uncertainty around those estimates. An approach is suggested for reducing uncertainty and improving user story size estimation accuracy.
One of the powerful aspects of Kanban is the statistical analysis of its metrics. This presentation talks about common Kanban metrics and how to interpret them.
Planning is incredibly important for businesses to reduce risk and create value, but what happens when the plan is almost always wrong? Software development is inherently hard to plan, but there are some great Agile tools available to help us plan effectively. This brown bag explores some of these Scrum ceremonies and tools available in the Agile world.
Agile is all about focus on creating value for the customer in a sustainable way. Actions that lead to business results and happier customers are a consequence of the behaviour of people. Agile coaching supports this by providing insights to people and the organization so they can choose what behaviour to change and how. This new behaviour will lead to improved business results and satisfied customers, or it leads to a more sustainable way - for the organisation - to achieve the business results.
How effective is the coaching and does it ultimately lead to changed improved business results? In this session Pieter demonstrates one way of linking the team actions to observed change in result as seen by the customer. This is demonstrated using data and methods taken from data science.
Welcome to the data-driven world.
39% of executives say their companies are already highly data-driven, but mentioning data can often result in concerned faces. Why is this? Is it the toxic nature that 'metrics' have become synonymous with or is it because we view using data as a dangerous flirtation with placing more value in tools and processes?
This session will showcase how you can bring to life the scientific method in your coaching arsenal. I will share stories of data-based coaching in PwC and how we leverage it to have open, transparent conversations and more informed decision making.
Cycle times and the Evolution From Story PointsScott Aucoin
Deck from a talk on cycle times and how to apply them for informed decision making (forecasting, team building, balance, process improvement) and evolution from traditional estimation approaches.
KANBAN AT SCALE: A SIEMENS HEALTH SERVICES CASE STUDY (BENNET VALLET & DAN VA...Lean Kanban Central Europe
This presentation will describe the approach taken for one of the world’s largest Kanban implementations at Siemens Health Services. It will describe how Kanban augmented existing agile practices there, and it will examine the achieved benefits of “flow” as demonstrated by real project data. Through a careful consideration of successes, challenges, and ongoing opportunities, this case study should be very meaningful to software product/development management organizations of any size whose funding, business operations, and profitability are dependent upon achieving a high degree of operational efficiency, transparency, and predictability.
Statistics for UX Professionals - Jessica CameronUser Vision
Are you looking to expand your research toolkit to include some quantitative methods, such as survey research or A/B testing? Have you been asked to collect some usability metrics, but aren’t sure how best to go about that? Or do you just want to be more aware of all of the UX research possibilities? If your answer to any of those questions is yes, then this session is for you.
You may know that without statistics, you won’t know if A is really better than B, if users are truly more satisfied with your new site than with your old one, or which changes to your site have actually impacted conversion rates. However, statistics can also help you figure out how to report satisfaction and other metrics you collect during usability tests. And they’re essential for making sense of the results of quantitative usability tests.
This session will focus on the statistical concepts that are most useful for UX researchers. It won’t make you a quant, but it will give you a good grounding in quantitative methods and reporting. (For example, you will learn what a margin of error is, how to report quantitative data collected during a usability test - and how not to - and how many people you really need to fill out a survey.)
Are you looking to expand your research toolkit to include some quantitative methods, such as survey research or A/B testing? Have you been asked to collect some usability metrics, but aren’t sure how best to go about that? Or do you just want to be more aware of all of the UX research possibilities? If your answer to any of those questions is yes, then this session is for you.
You may know that without statistics, you won’t know if A is really better than B, if users are truly more satisfied with your new site than with your old one, or which changes to your site have actually impacted conversion rates. However, statistics can also help you figure out how to report satisfaction and other metrics you collect during usability tests. And they’re essential for making sense of the results of quantitative usability tests.
This session will focus on the statistical concepts that are most useful for UX researchers. It won’t make you a quant, but it will give you a good grounding in quantitative methods and reporting. (For example, you will learn what a margin of error is, how to report quantitative data collected during a usability test - and how not to - and how many people you really need to fill out a survey.)
An agile development process is designed to allow us to respond to change, but this process depends on the people using it. As participants in an agile process, do we think and behave in a way that helps or harms our process? As individuals, are we actually as tolerant of change and randomness as our manifesto says we are, or do we subscribe to our methodology of choice in hopes of a smooth, predictable project? One can easily fall into the trap of being a tourist in his or her professional life--someone whose day gets worse when things don't go as planned. This talk will illustrate what it means to do the opposite and wander through our development process by fighting our bias toward stability and predictability. We'll see how "wandering" through some of our typical activities--like testing, planning, and organizing teams--can help us take full advantage of changing requirements and volatility, improve our agile process, and make our days get better with randomness.
Estimating with MAGIC Approach – Measure, Analyze, Improve and Control without ‘Guess’ work
#) Measure & Analyze using ‘Story Point Matrix’ based on Functional & Technical Analysis
#)Improve & Control using Statistical Data Modeling based on Empirical Data extracted from agile project management tool
Presentation for the Nexus Conference on the Internet of Things and the Evolu...Lora Cecere
Presentation prepared for the Nexus conference on the Internet of Things and the factors that drive Technology Adoption. Focus on Big Data, Digital Supply Chains and Internet of Things.
TQM QCC / SGA BY DURAISAMY R - M/s SHRISHTI CONSULTANTS CHENNAI ( www.shrisht...Duraisamy R
TOTAL QUALITY MANAGEMENT (TQM ), QUALITY CONTROL CIRCLES ( QCC ), SMALL GROUP ACTIVITIES ( SGA ), PROBLEM SOLVING TOOLS ( PST ), TOTAL EMPLOYEE INVOLVEMENT ( TEI ) MODEL,
Human Resources Performance Management Metrics PowerPoint Presentation Slides SlideTeam
Looking to take up your HR performance metrics PowerPoint show to next level? Just check out our readymade deck Human Resources Performance Management Metrics PowerPoint Presentation Slides with 61 slides precisely showcase the data. Our Human Resources Performance Management Metrics PPT presentation supports to underline the important aspects related to HR performance metrics like performance review the role of HR, metrics model, most common HR metrics, employee turnover, profit per employee, revenue per employee, revenue-cost per employee comparison, workforce diversity by gender, staff with professional qualification, competency rating and many more such designs examples. With help of our PowerPoint presentation deck HR teams and managers can easily present the content and reports to the target management. Furthermore, using this visually impactful PPT slide sample, you can brief employees about employee absence schedule, employee absenteeism, employee attendance tracker, performance review scoring, training hours per employee etc. Above all, exclusive presentation slides like employee satisfaction, staff engagement model, David Zinger or Aon Hewitt employee engagement, HR Dashboard etc. are included to touch all aspects of a brilliant human resources PPT presentation. So, what’s holding you back? Click and download our readymade Human Resources Performance Management Metrics Presentation sample and show your PowerPoint skills. Enlighten folks on baseless intolerance with our Human Resources Performance Management Metrics PowerPoint Presentation Slides. Condemn any acts of bigotry.
Human Resources Performance Management Metrics Powerpoint Presentation SlidesSlideTeam
Looking to take up your HR performance metrics PowerPoint show to next level? Just check out our readymade deck Human Resources Performance Management Metrics PowerPoint Presentation Slides with 61 slides precisely showcase the data. Our Human Resources Performance Management Metrics PPT presentation supports to underline the important aspects related to HR performance metrics like performance review the role of HR, metrics model, most common HR metrics, employee turnover, profit per employee, revenue per employee, revenue-cost per employee comparison, workforce diversity by gender, staff with professional qualification, competency rating and many more such designs examples. With help of our PowerPoint presentation deck HR teams and managers can easily present the content and reports to the target management. Furthermore, using this visually impactful PPT slide sample, you can brief employees about employee absence schedule, employee absenteeism, employee attendance tracker, performance review scoring, training hours per employee etc. Above all, exclusive presentation slides like employee satisfaction, staff engagement model, David Zinger or Aon Hewitt employee engagement, HR Dashboard etc. are included to touch all aspects of a brilliant human resources PPT presentation. So, what’s holding you back? Click and download our readymade Human Resources Performance Management Metrics Presentation sample and show your PowerPoint skills. Enlighten folks on baseless intolerance with our Human Resources Performance Management Metrics Powerpoint Presentation Slides. Condemn any acts of bigotry. https://bit.ly/3AwuYGE
Speak To The Business! Agile Metrics That Inform Rather Confuse the Businesstroytuttle
Given to PMI KC Professional Development Days 2014 Conference.
In this session, we will investigate the challenges with the popular Agile planning and reporting concepts like story points, planning poker, and average velocity. We will explore some practical alternative planning and reporting practices that the business can understand. And we will look at metrics that are less of an abstraction from reality and more actionable by teams and management.
With the current expected credit loss (CECL) model for the Allowance on the horizon, bankers will be asked to create future-looking methodologies that adjust for reasonable and supportable forecasts. Without adequate modeling experience, that can be a challenge for community banks and credit unions.
Watch the full webinar here: http://web.sageworks.com/forward-looking-alll-adjustments/
Agile metrics: Measure and Improve:
Mattia Battiston (SKY) and David Leach (Reed Online) share their expert views on velocity, agile ROI, reporting and measuring impact.
Sponsored by Wemanity - www.wemanity.com - the agile driving force
This is a presentation and workshop that Data for Good delivered during the Regina Food Summit put on by the City of Regina and the Regina Foodbank, on December 10, 2021.
Digicrome Data Science & AI 11 Month Course PDF.pdfitsmeankitkhan
Dive into the world of Artificial Intelligence and Data Science with Digicrome's dynamic Postgraduate Program (PGP). Our uniquely crafted curriculum blends theory with hands-on projects, led by industry experts. From cutting-edge algorithms to practical applications Artificial Intelligence Certification, elevate your skills and career prospects in today's data-driven landscape.
The last couple of years have been full of discussions on how to scale agile methods. Frameworks promising to know the answer on how to scale are plenty, well known, and it feels like new frameworks keep entering the market on a monthly basis. Most, if not all come with a nice big picture showing managers how an (big) agile organizations needs to look like. They got it all wrong.
Creating an agile organization is not about introducing new titles and roles, not about cross-functional teams and especially not about trains. Agile organizations are about respecting people, delivering value to customers, and being able to constantly adapt to change. To achieve all this you need is stress, reflections mechanisms and leadership.
This talk will show you, how the Kanban method can help you to get exactly those three things to successfully foster an organization that is delivering value to their customers, is able to adapt to changes, while respecting its people and without turning everything upside down.
My Kanban introductory talk from Lean Kanban North America 2017, short LKNA17. Learn how Kanban is more than sticky notes on a wall. Learn how Kanban's 3 Agendas can help you to steer change in the right direction. Presented with help of the Kanbunny by it-agile.
As a trainer and coach I'm very often asked, if certain tools or practiced should be introduced. Well, I don't know as I don't know enough about the situation and the problem you want to solve. This is where 'brain on' mode comes into action.
Agile respectively Scrum offers a model to learn on an individual and group/team level. It misses methods to learn on an organizational level. The talk explains how tacit knowledge is transformed into explicit knowledge, what Ikujiro Nonaka's und Hirotaka Takeuchi's knowledge spiral is and how to get from an individual and team level learning to organizational learning
Eine kurze Einführung in das Agile Fluency™ Modell von Diana Larsen und James Shore. Der Vortrag erklärt das Modell, welche Praktiken zum erreichen der verschiedenen Stufen hilfreich sind und welche Investition nötig sind. Außerdem gehe ich kurz darauf ein, wie die Kanban Methode zum erreichen von 4-Sternen helfen kann.
Ein Vortrag über die Werte von Kanban. Der Vortrag erklärt Kanban anhand seiner Werte und gibt so eine etwas andere Art der Einführung. Grundlage ist das Buch "Kanban - Verstehen, einführen, anwenden" von Mike Burrows.
Why should I measure my changes and where should I start to do so? - LKNA14Wolfgang Wiedenroth
This talk tells you why you should measure the changes you do and gives you advice where to start. This talk has been a lightning talk at Lean Kanban North America 2014(LKNA14).
8. That’s the opposite of Flow
it’s called Christmas holidays
Cumulative Flow Diagram
9. 0"
2"
4"
6"
8"
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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"
y = No. of Tickets finished
with lead time x
x = Lead Time in days
Average Lead Time
Lead Time Distribution Chart
19. Capability Analysis
Demand 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?
22. How fast can we deliver?
0"
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4"
6"
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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"
Mode = most common lead time
Median = 50%
Average = 11 days
80% of all tickets will finish in x
90% of all tickets will finish in x
98% of all tickets will finish in x
Weibull with
shape parameter k = 1.5
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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"71"72"73"74"75"
How fast can we deliver features?
25. Features Q(p;k, λ) = λ( - ln(1 - p))1/k
Number of data points: 59
Shape parameter (k): 1.54
Scale parameter (λ): 12.69
Average: 11.92
0"
1"
2"
3"
4"
5"
6"
7"
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"71"72"73"74"75"
How fast can we deliver features?
26. 0"
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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"71"72"73"74"75"
How fast can we deliver features? Weibull with
shape parameter k = 1.5
Mode = most common lead time
Median = 50%
Average = 11 days
80% of all tickets will be finished in around 17 days
90% of all tickets will be finished in around 22 days
98% of all tickets will be finished in around 30 days
27. How fast can we fix bugs?
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1" 2" 3" 4" 5" 6" 7" 8" 9" 10" 11" 12" 13" 14" 15"
28. 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"
How fast can we fix bugs?
between 1.25 and 1.50
31. 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"
How fast can we fix bugs?
98% of bugs
are fixed in 12.4 days
Weibull with
shape parameter k = 1.25
32. Features are expected to be finished in 17 days with probability
of 80%
Bugs are expected to be fixed in between
3 (average) and 12 days (98%)
SLEs you can communicate to your customer
46. What do customers using this service
care about?
Make these your fitness criteria!
47. Fitness Criteria
“Fitness Criteria are metrics that measure things
customer value when selecting a service again and
again.”
- Delivery Time
- Quality
- Predictiability
- Safety (conformance to regulatory requirements)
David J. Anderson
58. Troy Magennis at LKCE13’s speaker dinner
"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."
59. "We do this only until we have
enough data to provide better
sample."
Troy Magennis at LKCE13’s speaker dinner
61. Example metrics to evaluate change
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
…
your fitness
criteria