Presentation on Agile Estimation from Agile:MK user group on 7 October 2019 by Rien Sach and John Donoghue https://www.meetup.com/Agile-MK-Agile-User-Group/events/262193686/
These are the slides from the Agile Estimation Workshop I gave at AgileChina 2015. The morning session covered opinion-based techniques. The afternoon covered empirical techniques based on cycle time, Little's Law, and Monte Carlo simulation.
Ever wonder why Agile teams swear by relative estimation? My teams improved sprint planning efforts by a factor or 3, once we started using relative estimation.
Without understanding Agile relative estimation, teams tend to fall back to using time-based methods. This often leads them to spend way too much time on obsolete estimates that will be made even more complex with all the unknowns and constant emergent requirements of an Agile world!
“It's better to be roughly right, than precisely wrong!”
~ John Maynard Keyenes
The Solution is simple: understand that relative estimation is only a rough order of magnitude estimate to quickly organize the product backlog. This empowers your product owners (PO) to quickly make value based trade-offs on backlog items and decide on what stories the team should work next. This gives the business the highest bang for their buck!
PROBLEMS WITH TIME-BASED ESTIMATES
-Teams spend too much time trying to get it right
-Lack of confidence/experience can lead to people being either optimistic or pessimistic
-Timeline you are estimating may be too far in the future
-Due to long timeline, there are too many risks, unknowns, changes or dependencies!
WHY USE RELATIVE ESTIMATION?
-Allows a quick comparison of stories in the backlog
-Allows you to select a predictable volume of work to do in a sprint
-Uses a simple arbitrary scale
-Allows PO to make trade-offs and take on the most valuable stories next
ESTIMATION TIPS
-Relative points or equivalent Tshirt sizes are used to estimate stories, leveraging the Fibonacci sequence modified for Agile.
-The team estimates the story, not management nor the customer.
-Story estimates account for three things: effort, complexity, and unknowns. Don’t short sell yourself by estimating effort alone, that’s where waterfall projects face issues.
-Remember to estimate all Stories, user stories or technical stories. Even estimate research or discovery spikes.
-Refine your backlog as a team on a continuous basis, to get your stories to meet the Definition of Ready.
-Only pull into your sprint, stories that are refined and estimated.
-Break down stories that are large, into smaller slivers of value to optimize your flow.
-Don’t sweat it if you get it wrong, teams often do early on but improve over time.
This document discusses the importance of estimating and tracking time for documentation projects. It recommends tracking all time spent on tasks like meetings, writing, editing, and more to build a basis for accurate estimating. Both bottom-up and top-down estimating methods are described. Tracking time allows learning from past projects to improve estimates using techniques like comparative, parametric, and matrix-based estimating. Correlating estimates with tracking provides feedback to refine estimates. Risks should be identified and stakeholders agree on estimates upfront to manage scope changes.
London Kanban Coaching Exchange
Flow Systems - like developments being run with a process like Scrum or Kanban - provide us a lot of data, and, if we know how to look at it, a lot of information about the health of our processes and projects. Start and end dates for example provide Throughput, Time in Process, Work in Progress as well as more exotic metrics such as Flow Debt, WiP-Aging and Delivery Bias indicators. Adding in Target Dates and historic distribution data for Lead Times provides Buffer Consumption measures, and the simple application of Monte Carlo models (plug it into the spreadsheet!) gives completion probabilities over a range of dates. We'll review what these metrics mean and who's writing about them. Then look at concise, concrete and pragmatic advice for how you can use them on your projects. Whether you've never seen a Control Chart or a Cumulative Flow Diagram - or if you're using flow metrics every day and bring along some diagrams and insights to share, this will be an entertaining evening of the whys and hows of project numbers.
About the Speaker
Andy Carmichael: Whether as a manager, developer, coach or author, a common theme to what I’ve done throughout my career has been helping teams make “better software… faster”. Working with a wide variety of clients on very small to impossibly large projects, remains my principal source of education - certainly outweighing various degrees and certifications I’ve also picked up along the way! Thinking deeply about business problems and finding the intersection with how people best work together, is where I find the fun - and the value - lies.
Twitter: @andycarmich Blog: Improving Projects
Scrum uses relative estimation and velocity to aid in planning and making trade-off decisions. Relative estimation involves comparing the effort of new requirements to previously estimated ones, which humans are better at than absolute estimates. Velocity is the amount of work completed in an iteration, measured in story points or hours, and varies over time so is useful for longer-term planning. There are two types of Scrum planning: fixed-date planning estimates how much can be completed by a date based on velocity, while fixed-scope planning estimates the timeframe to complete all backlog items based on velocity. Both use velocity as a range rather than a precise prediction.
Xanpan is a hybrid agile methodology that combines elements of Kanban and Extreme Programming (XP). It is described as team-centric and emphasizes continuous flow, small batch sizes, visualizing work, and quality. Some key practices include using XP technical practices like test-driven development, breaking stories into tasks, estimating in story points, applying work-in-progress limits, and having regular iteration cycles with deadlines. The methodology aims to take the best of Kanban and XP while allowing teams flexibility in customizing their process.
Kanban vs Scrum: What's the difference, and which should you use?Arun Kumar
Originally presented at the 207 Lean Transformation Conference, this presentation provides a practical introduction to Scrum, particularly for public sector employees, and guides you to deciding whether Kanban or Scrum will work best for your teams and projects.
1. The document discusses best practices for estimating projects and tasks. It emphasizes using ranges rather than specific numbers for estimates since estimation involves uncertainty.
2. Ten key principles of estimation are outlined, including always asking how the estimate will be used, not negotiating estimates, and using measured past performance to calibrate estimates. Aggregating independent estimates and decomposing work into around 15 tasks can improve accuracy by reducing risk.
3. Two short exercises are presented where participants estimate values and dates. Correct answers are then provided along with commentary on estimation techniques. The document promotes solving problems collaboratively and being transparent about assumptions in estimates.
These are the slides from the Agile Estimation Workshop I gave at AgileChina 2015. The morning session covered opinion-based techniques. The afternoon covered empirical techniques based on cycle time, Little's Law, and Monte Carlo simulation.
Ever wonder why Agile teams swear by relative estimation? My teams improved sprint planning efforts by a factor or 3, once we started using relative estimation.
Without understanding Agile relative estimation, teams tend to fall back to using time-based methods. This often leads them to spend way too much time on obsolete estimates that will be made even more complex with all the unknowns and constant emergent requirements of an Agile world!
“It's better to be roughly right, than precisely wrong!”
~ John Maynard Keyenes
The Solution is simple: understand that relative estimation is only a rough order of magnitude estimate to quickly organize the product backlog. This empowers your product owners (PO) to quickly make value based trade-offs on backlog items and decide on what stories the team should work next. This gives the business the highest bang for their buck!
PROBLEMS WITH TIME-BASED ESTIMATES
-Teams spend too much time trying to get it right
-Lack of confidence/experience can lead to people being either optimistic or pessimistic
-Timeline you are estimating may be too far in the future
-Due to long timeline, there are too many risks, unknowns, changes or dependencies!
WHY USE RELATIVE ESTIMATION?
-Allows a quick comparison of stories in the backlog
-Allows you to select a predictable volume of work to do in a sprint
-Uses a simple arbitrary scale
-Allows PO to make trade-offs and take on the most valuable stories next
ESTIMATION TIPS
-Relative points or equivalent Tshirt sizes are used to estimate stories, leveraging the Fibonacci sequence modified for Agile.
-The team estimates the story, not management nor the customer.
-Story estimates account for three things: effort, complexity, and unknowns. Don’t short sell yourself by estimating effort alone, that’s where waterfall projects face issues.
-Remember to estimate all Stories, user stories or technical stories. Even estimate research or discovery spikes.
-Refine your backlog as a team on a continuous basis, to get your stories to meet the Definition of Ready.
-Only pull into your sprint, stories that are refined and estimated.
-Break down stories that are large, into smaller slivers of value to optimize your flow.
-Don’t sweat it if you get it wrong, teams often do early on but improve over time.
This document discusses the importance of estimating and tracking time for documentation projects. It recommends tracking all time spent on tasks like meetings, writing, editing, and more to build a basis for accurate estimating. Both bottom-up and top-down estimating methods are described. Tracking time allows learning from past projects to improve estimates using techniques like comparative, parametric, and matrix-based estimating. Correlating estimates with tracking provides feedback to refine estimates. Risks should be identified and stakeholders agree on estimates upfront to manage scope changes.
London Kanban Coaching Exchange
Flow Systems - like developments being run with a process like Scrum or Kanban - provide us a lot of data, and, if we know how to look at it, a lot of information about the health of our processes and projects. Start and end dates for example provide Throughput, Time in Process, Work in Progress as well as more exotic metrics such as Flow Debt, WiP-Aging and Delivery Bias indicators. Adding in Target Dates and historic distribution data for Lead Times provides Buffer Consumption measures, and the simple application of Monte Carlo models (plug it into the spreadsheet!) gives completion probabilities over a range of dates. We'll review what these metrics mean and who's writing about them. Then look at concise, concrete and pragmatic advice for how you can use them on your projects. Whether you've never seen a Control Chart or a Cumulative Flow Diagram - or if you're using flow metrics every day and bring along some diagrams and insights to share, this will be an entertaining evening of the whys and hows of project numbers.
About the Speaker
Andy Carmichael: Whether as a manager, developer, coach or author, a common theme to what I’ve done throughout my career has been helping teams make “better software… faster”. Working with a wide variety of clients on very small to impossibly large projects, remains my principal source of education - certainly outweighing various degrees and certifications I’ve also picked up along the way! Thinking deeply about business problems and finding the intersection with how people best work together, is where I find the fun - and the value - lies.
Twitter: @andycarmich Blog: Improving Projects
Scrum uses relative estimation and velocity to aid in planning and making trade-off decisions. Relative estimation involves comparing the effort of new requirements to previously estimated ones, which humans are better at than absolute estimates. Velocity is the amount of work completed in an iteration, measured in story points or hours, and varies over time so is useful for longer-term planning. There are two types of Scrum planning: fixed-date planning estimates how much can be completed by a date based on velocity, while fixed-scope planning estimates the timeframe to complete all backlog items based on velocity. Both use velocity as a range rather than a precise prediction.
Xanpan is a hybrid agile methodology that combines elements of Kanban and Extreme Programming (XP). It is described as team-centric and emphasizes continuous flow, small batch sizes, visualizing work, and quality. Some key practices include using XP technical practices like test-driven development, breaking stories into tasks, estimating in story points, applying work-in-progress limits, and having regular iteration cycles with deadlines. The methodology aims to take the best of Kanban and XP while allowing teams flexibility in customizing their process.
Kanban vs Scrum: What's the difference, and which should you use?Arun Kumar
Originally presented at the 207 Lean Transformation Conference, this presentation provides a practical introduction to Scrum, particularly for public sector employees, and guides you to deciding whether Kanban or Scrum will work best for your teams and projects.
1. The document discusses best practices for estimating projects and tasks. It emphasizes using ranges rather than specific numbers for estimates since estimation involves uncertainty.
2. Ten key principles of estimation are outlined, including always asking how the estimate will be used, not negotiating estimates, and using measured past performance to calibrate estimates. Aggregating independent estimates and decomposing work into around 15 tasks can improve accuracy by reducing risk.
3. Two short exercises are presented where participants estimate values and dates. Correct answers are then provided along with commentary on estimation techniques. The document promotes solving problems collaboratively and being transparent about assumptions in estimates.
Unlike traditional projects, Agile teams provide their estimates using a “top-down” approach; where they use current available information to produce gross-level estimation, and this estimation is less accurate and has less details.
============== Follow us ==============
Website: http://xpdays.org
Linked In: https://www.linkedin.com/company/xpdays
Facebook: https://www.facebook.com/xpdaysorg
Twitter: https://twitter.com/xpdaysorg
Introduction to agile and Scrum.
Using Vera Peeters and Pascal Van Cauwenberghe's XP game as a basis, we have adapted it to explain and demonstrate agile and Scrum. The second half of the presentation is largely repetitive because it is used at each stage in the game.
The document discusses different approaches to estimation in waterfall and Scrum methodologies. In Scrum, teams estimate their own work in story points, which are relative units based on size and complexity. Story points help drive cross-functional behavior and do not decay over time. Ideal days estimates involve determining how long a task would take with ideal conditions and no interruptions. Planning poker uses story point cards to facilitate discussion and reach consensus on estimates. Release planning in Scrum involves estimating velocity over sprints to determine how many product backlog items can be completed.
Estimation is associated with Fear, Uncertainty and Death marches. Most of us would rather not estimate. Yet, sometimes we do need estimates and commitments, even on "estimation-less" projects. Play a series of estimation games to experience how different techniques deliver very different results. Learn a few simple rules that turn you into a reliable estimator. But correct estimates aren't enough. See what else is required to deliver on your promises. Learn to deal with the destructive games people play with estimates. Estimating can be Fun, embracing Uncertainty and Delivering.
This document discusses challenges with estimating velocity for the initial sprint of a new Scrum team. It notes that using past data from other teams is not accurate for a new team. While management wants estimates upfront, the best approach is to wait for real data from the first sprint. The document recommends a risk mitigation approach of estimating tasks in hours to approximate a velocity range for the first sprint. Additional challenges can arise from delivering a minimum viable product that does not match architectural needs.
Lean conference 2014 Open Market - how we have benefited from the application...Invest Northern Ireland
This document describes one company's journey to implement Lean Kanban principles to improve their workflow. They initially had concerns that modeling all work items the same, imposing strict work-in-progress limits, and basing predictions on past measurements would not work for their needs. However, after trying it, they found that modeling work at a higher level, limiting work-in-progress improved predictability without reducing output, and past measurements could accurately inform predictions. They also discuss some initial challenges faced and lessons learned around understanding their current process and communicating changes. Overall, they found the Lean Kanban approach provided a more consistent, predictable and reactive workflow with low overhead.
This document discusses the NoEstimates approach to software development. It begins by defining estimates and explaining that NoEstimates is about minimizing estimates rather than eliminating them entirely. The main goals of NoEstimates are to evaluate progress in a concrete way and force teams to slice work into smaller stories. Key benefits include being faster, easier iteration planning, and minimal time spent estimating. Progress is measured by the number of "Running Tested Stories" completed. The document also covers challenges, case studies, and debates around using NoEstimates versus more traditional estimating approaches.
This document summarizes how one agile team implements Scrum. It discusses how the team manages their product backlog, preparing and planning for sprints. The team focuses on getting work done over theoretical practices. They prioritize customer needs and concrete deliverables in the product backlog. Estimates are relative and in story points to focus on the work rather than timelines.
The document discusses various techniques for estimating testing efforts, including work breakdown structure, function point analysis, three point estimation, planning poker, and story points. It emphasizes dividing projects into smaller tasks, estimating the time and resources needed for each, and allowing for contingencies in timelines and budgets. Accurate estimation requires considering factors like team skills, complexity of the software, and lessons learned from past projects.
To Estimate or Not To Estimate + #(No)Estimates GameAgile Humans
The document discusses the debate around estimating in software development. It presents arguments for and against estimating, as well as different approaches to estimating such as using story points, t-shirt sizes, and the #NoEstimates method. The document also explores reasons for estimating like planning, forecasting, and facilitating meaningful discussions, as well as techniques for estimating like planning poker, decomposition into subtasks, and using the Fibonacci sequence. Overall, it examines the tradeoffs of different estimating approaches and emphasizes focusing on complexity and uncertainty over precise hours or dates.
The document discusses various techniques for estimating work in Agile projects, including story points and feature points. It explains that story points are used to estimate user stories and provide a relative measure of complexity, while feature points are used to estimate larger features. The document also describes planning poker, where teams discuss estimates and converge on a shared value through discussion. Finally, it notes that estimates may need adjusting over time based on team experience and environment factors.
This document provides an overview of concepts related to practical Scrum. It discusses roles like the Product Owner and how they define features, priorities, and work for each iteration. It covers topics like requirements gathering, user story writing, estimating effort using planning poker, calculating team velocity, and long-term release planning. The document also explains Scrum ceremonies like sprint planning, daily stand-ups, sprint reviews, and retrospectives. Finally, it discusses agile engineering practices like pair programming, test-driven development, refactoring, and continuous integration.
This document discusses how to interpret data from Kanban retrospectives to identify opportunities for optimizing workflow. It provides examples of metrics like lead time, cycle time, and work in progress that can be analyzed to address issues like bottlenecks, piles of work in specific states, outliers in work completion times, frequent blockers, the impact of unplanned work, and ensuring team well-being and sustainability. The document advocates using a structured process of planning improvements, implementing changes, measuring their impact, and adjusting as needed.
This document discusses concepts related to estimation and velocity in Scrum projects. It describes how to estimate product backlog items using story points or ideal days with relative sizing. Velocity is defined as the amount of work completed each sprint by totaling the sizes of completed backlog items. A team's velocity range is used for planning and process improvement. Planning poker is presented as a consensus-based technique for sizing items through discussion.
Estimating the size and effort required for projects and tasks is important for planning purposes but difficult to do with precision. Estimates are informed guesses that can vary due to factors like unclear requirements, lack of historical data, and scope changes. While estimates are not perfect, they provide value by enabling prioritization, collaboration, and iterative planning. Effective estimation techniques include using ranges rather than single points, factoring in assumptions, combining expert judgement with data-driven methods, and refining estimates over time as understanding improves.
When is Scrum the right methodology and why? What are the most important parts of the process, the discipline it takes to make it work, a whole bunch of protips from someone who has been helping teams do their best work for over 15 years
Agile: the Good, the Bad and the Ugly - Webinar by Clarke Ching Agile - Septe...MARRIS Consulting
Webinar by Clarke Ching Agile and ToC expert. Agile: the Good, the Bad and the Ugly. If your Agile is broken then this is how to fix it!
Your Agile teams are busy. Busy delivering. Busy improving. Your quality is amazing. Rework is low. The product looks great. Your users love it. You are a high performing team!
But your internal customers say your teams are slow. This session will teach you how to use the Theory of Constraints to figure out how to speed up, by finding the one thing that’s slowing them down.
This webinar will cover how, in an Agile environment:
- to better control scope creep,
- to reinforce your relationship with the I.T. Development team’s client,
- to be able to make commitments and honour them and
- to decide where your bottleneck should be.
About the speaker
Clarke Ching is a computer scientist with an MBA who discovered Goldratt’s Theory of Constraints (ToC) in 2003 and has been using it ever since to accelerate Agile initiatives. He is fascinated by Agile and obsessed with ToC.
He wrote the amazon best-sellers Rolling Rocks Downhill and The Bottleneck Rules. Rolling Rocks Downhill teaches 3 things: the fundamentals of Agile combined with ToC; how to use those fundamentals to deliver big projects faster and on time; and how to deliver quietly huge transformations. It’s been featured in The Guardian newspaper and The Spectator magazine. It was one of Barbara Oakley’s top 10 books of 2019. It was the #2 best-selling Leadership book on amazon.com, just behind Steven Covey’s 7-habits book.
He has been Agile / Lean / ToC expert in: GE Energy, Dell, Royal London (life insurance & pensions), Gazprom and Standard Life Aberdeen among other organizations. He is the past Chairperson of Agile Scotland. He is a lecturer at Victoria University School Of Management in New Zealand where he now lives.
Today he is the founder and Chief Productivity Officer of Odd Socks Consulting
This document summarizes an agile presentation about predictability. It discusses forming cross-functional teams, relative sizing to estimate work, and using the right metrics like throughput and cycle time. It also describes an exercise where teams work on "dot game" tasks to experience concepts like work in progress limits and single piece flow. The presenter believes in understanding team dynamics, relative sizing, and using metrics appropriately to increase predictability.
Estimates are not promises
Your gut lies
Premature estimation is sabotage
Big teams are slower than small ones
Beware unwarranted precision
Count all the things!
When in a pinch, use a proxy
You can’t negotiate math
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Unlike traditional projects, Agile teams provide their estimates using a “top-down” approach; where they use current available information to produce gross-level estimation, and this estimation is less accurate and has less details.
============== Follow us ==============
Website: http://xpdays.org
Linked In: https://www.linkedin.com/company/xpdays
Facebook: https://www.facebook.com/xpdaysorg
Twitter: https://twitter.com/xpdaysorg
Introduction to agile and Scrum.
Using Vera Peeters and Pascal Van Cauwenberghe's XP game as a basis, we have adapted it to explain and demonstrate agile and Scrum. The second half of the presentation is largely repetitive because it is used at each stage in the game.
The document discusses different approaches to estimation in waterfall and Scrum methodologies. In Scrum, teams estimate their own work in story points, which are relative units based on size and complexity. Story points help drive cross-functional behavior and do not decay over time. Ideal days estimates involve determining how long a task would take with ideal conditions and no interruptions. Planning poker uses story point cards to facilitate discussion and reach consensus on estimates. Release planning in Scrum involves estimating velocity over sprints to determine how many product backlog items can be completed.
Estimation is associated with Fear, Uncertainty and Death marches. Most of us would rather not estimate. Yet, sometimes we do need estimates and commitments, even on "estimation-less" projects. Play a series of estimation games to experience how different techniques deliver very different results. Learn a few simple rules that turn you into a reliable estimator. But correct estimates aren't enough. See what else is required to deliver on your promises. Learn to deal with the destructive games people play with estimates. Estimating can be Fun, embracing Uncertainty and Delivering.
This document discusses challenges with estimating velocity for the initial sprint of a new Scrum team. It notes that using past data from other teams is not accurate for a new team. While management wants estimates upfront, the best approach is to wait for real data from the first sprint. The document recommends a risk mitigation approach of estimating tasks in hours to approximate a velocity range for the first sprint. Additional challenges can arise from delivering a minimum viable product that does not match architectural needs.
Lean conference 2014 Open Market - how we have benefited from the application...Invest Northern Ireland
This document describes one company's journey to implement Lean Kanban principles to improve their workflow. They initially had concerns that modeling all work items the same, imposing strict work-in-progress limits, and basing predictions on past measurements would not work for their needs. However, after trying it, they found that modeling work at a higher level, limiting work-in-progress improved predictability without reducing output, and past measurements could accurately inform predictions. They also discuss some initial challenges faced and lessons learned around understanding their current process and communicating changes. Overall, they found the Lean Kanban approach provided a more consistent, predictable and reactive workflow with low overhead.
This document discusses the NoEstimates approach to software development. It begins by defining estimates and explaining that NoEstimates is about minimizing estimates rather than eliminating them entirely. The main goals of NoEstimates are to evaluate progress in a concrete way and force teams to slice work into smaller stories. Key benefits include being faster, easier iteration planning, and minimal time spent estimating. Progress is measured by the number of "Running Tested Stories" completed. The document also covers challenges, case studies, and debates around using NoEstimates versus more traditional estimating approaches.
This document summarizes how one agile team implements Scrum. It discusses how the team manages their product backlog, preparing and planning for sprints. The team focuses on getting work done over theoretical practices. They prioritize customer needs and concrete deliverables in the product backlog. Estimates are relative and in story points to focus on the work rather than timelines.
The document discusses various techniques for estimating testing efforts, including work breakdown structure, function point analysis, three point estimation, planning poker, and story points. It emphasizes dividing projects into smaller tasks, estimating the time and resources needed for each, and allowing for contingencies in timelines and budgets. Accurate estimation requires considering factors like team skills, complexity of the software, and lessons learned from past projects.
To Estimate or Not To Estimate + #(No)Estimates GameAgile Humans
The document discusses the debate around estimating in software development. It presents arguments for and against estimating, as well as different approaches to estimating such as using story points, t-shirt sizes, and the #NoEstimates method. The document also explores reasons for estimating like planning, forecasting, and facilitating meaningful discussions, as well as techniques for estimating like planning poker, decomposition into subtasks, and using the Fibonacci sequence. Overall, it examines the tradeoffs of different estimating approaches and emphasizes focusing on complexity and uncertainty over precise hours or dates.
The document discusses various techniques for estimating work in Agile projects, including story points and feature points. It explains that story points are used to estimate user stories and provide a relative measure of complexity, while feature points are used to estimate larger features. The document also describes planning poker, where teams discuss estimates and converge on a shared value through discussion. Finally, it notes that estimates may need adjusting over time based on team experience and environment factors.
This document provides an overview of concepts related to practical Scrum. It discusses roles like the Product Owner and how they define features, priorities, and work for each iteration. It covers topics like requirements gathering, user story writing, estimating effort using planning poker, calculating team velocity, and long-term release planning. The document also explains Scrum ceremonies like sprint planning, daily stand-ups, sprint reviews, and retrospectives. Finally, it discusses agile engineering practices like pair programming, test-driven development, refactoring, and continuous integration.
This document discusses how to interpret data from Kanban retrospectives to identify opportunities for optimizing workflow. It provides examples of metrics like lead time, cycle time, and work in progress that can be analyzed to address issues like bottlenecks, piles of work in specific states, outliers in work completion times, frequent blockers, the impact of unplanned work, and ensuring team well-being and sustainability. The document advocates using a structured process of planning improvements, implementing changes, measuring their impact, and adjusting as needed.
This document discusses concepts related to estimation and velocity in Scrum projects. It describes how to estimate product backlog items using story points or ideal days with relative sizing. Velocity is defined as the amount of work completed each sprint by totaling the sizes of completed backlog items. A team's velocity range is used for planning and process improvement. Planning poker is presented as a consensus-based technique for sizing items through discussion.
Estimating the size and effort required for projects and tasks is important for planning purposes but difficult to do with precision. Estimates are informed guesses that can vary due to factors like unclear requirements, lack of historical data, and scope changes. While estimates are not perfect, they provide value by enabling prioritization, collaboration, and iterative planning. Effective estimation techniques include using ranges rather than single points, factoring in assumptions, combining expert judgement with data-driven methods, and refining estimates over time as understanding improves.
When is Scrum the right methodology and why? What are the most important parts of the process, the discipline it takes to make it work, a whole bunch of protips from someone who has been helping teams do their best work for over 15 years
Agile: the Good, the Bad and the Ugly - Webinar by Clarke Ching Agile - Septe...MARRIS Consulting
Webinar by Clarke Ching Agile and ToC expert. Agile: the Good, the Bad and the Ugly. If your Agile is broken then this is how to fix it!
Your Agile teams are busy. Busy delivering. Busy improving. Your quality is amazing. Rework is low. The product looks great. Your users love it. You are a high performing team!
But your internal customers say your teams are slow. This session will teach you how to use the Theory of Constraints to figure out how to speed up, by finding the one thing that’s slowing them down.
This webinar will cover how, in an Agile environment:
- to better control scope creep,
- to reinforce your relationship with the I.T. Development team’s client,
- to be able to make commitments and honour them and
- to decide where your bottleneck should be.
About the speaker
Clarke Ching is a computer scientist with an MBA who discovered Goldratt’s Theory of Constraints (ToC) in 2003 and has been using it ever since to accelerate Agile initiatives. He is fascinated by Agile and obsessed with ToC.
He wrote the amazon best-sellers Rolling Rocks Downhill and The Bottleneck Rules. Rolling Rocks Downhill teaches 3 things: the fundamentals of Agile combined with ToC; how to use those fundamentals to deliver big projects faster and on time; and how to deliver quietly huge transformations. It’s been featured in The Guardian newspaper and The Spectator magazine. It was one of Barbara Oakley’s top 10 books of 2019. It was the #2 best-selling Leadership book on amazon.com, just behind Steven Covey’s 7-habits book.
He has been Agile / Lean / ToC expert in: GE Energy, Dell, Royal London (life insurance & pensions), Gazprom and Standard Life Aberdeen among other organizations. He is the past Chairperson of Agile Scotland. He is a lecturer at Victoria University School Of Management in New Zealand where he now lives.
Today he is the founder and Chief Productivity Officer of Odd Socks Consulting
This document summarizes an agile presentation about predictability. It discusses forming cross-functional teams, relative sizing to estimate work, and using the right metrics like throughput and cycle time. It also describes an exercise where teams work on "dot game" tasks to experience concepts like work in progress limits and single piece flow. The presenter believes in understanding team dynamics, relative sizing, and using metrics appropriately to increase predictability.
Estimates are not promises
Your gut lies
Premature estimation is sabotage
Big teams are slower than small ones
Beware unwarranted precision
Count all the things!
When in a pinch, use a proxy
You can’t negotiate math
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SMS API Integration in Saudi Arabia| Best SMS API ServiceYara Milbes
Discover the benefits and implementation of SMS API integration in the UAE and Middle East. This comprehensive guide covers the importance of SMS messaging APIs, the advantages of bulk SMS APIs, and real-world case studies. Learn how CEQUENS, a leader in communication solutions, can help your business enhance customer engagement and streamline operations with innovative CPaaS, reliable SMS APIs, and omnichannel solutions, including WhatsApp Business. Perfect for businesses seeking to optimize their communication strategies in the digital age.
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
Fundamentals of Programming and Language Processors
So when will it be done
1. So When Will It Be Done?
John Donoghue and Rien Sach
Agile:MK – Oct 2019
2. Areas to cover
• “Agile estimating”
• The realistic compromise
• The Iron Triangle (and that important middle bit)
– Fixing Date
– Fixing Scope
• REAR
3. • First question – what is agile estimating?
– What does “by the book” mean?
– What do we consider when making an estimate?
– How do we measure/record estimates?
– How do we communicate the outcome of our
refinement/estimation?
Agile Estimating
4. • Starts with a prioritised backlog
• Items are refined and estimated in priority order
• More attention is given to the higher priority items
• Anticipated that you’ll review and refine items as they
progress up the backlog
• Likely re-estimate backlog items as things become clearer
Agile Estimating (take two)
5. • Prioritised, refined, estimated (to a degree) backlog
– Higher clarity on items and estimates at the top
– More vagueness and questions as we go down
• We answer “When will it be done?” by considering:
– Teams velocity
– Backlog status
– Confidence in the definition & estimate of the backlog items
• What that means is we say “Given what we know at this point, if
nothing changes we forecast that we will be able to complete this
item between X and Y dates/releases”
Agile Estimating – The Outcome
6. • People don’t tend to like the word forecast. At least, they often exchange it with
the word “commitment”
• Even if they do accept the word forecast, customers often don’t
• Even if customers accept the word forecast, that doesn’t stop people being
unhappy as things change – software delivery is usually only a small piece of a
larger project
• Things always change.
• You -always- have more work to do than available capacity
• Backlog items will almost always grow in size as it gets closer to being prioritised or
while it’s being delivered
Agile Estimating – What’s the problem here?
7. The stakeholders say they need to know what will be
delivered, what it will cost, and when they can expect
it.
So:
• Give them a date with plenty of contingency built in
• Do highest-value-thing-first (Agile, right!?) so if you
run out of contingency you might not get fired
Let’s Get Realistic
9. • Choose a date for release and announce high level
feature list
• Flex scope within high level definitions
e.g. “when we announced support for Word, we meant just the latest version”
• Work on highest value parts of each feature, what
makes the date is released
• If the chosen date is “every two weeks” it looks a bit like
Scrum!
Fixed Date, Flexible Scope
10. • Announce feature list (aka Roadmap)
• Doesn’t matter what order things are worked on, it all
needs to be done
• When it’s all done, release it
• If you can get away with announcing one small feature
per team, it’s might be getting close to being Agile
Flexible Date, Fixed Scope
11. Context: this is an approach being considered (not yet
adopted) in a company where:
• Need to set customer expectation of delivery dates a long
way in advance of really knowing
• Don’t want to give commitments that set teams up to fail
• Don’t want to just “pad the estimates” – work grows to fill
the time allowed!
• Want to empower teams to own the whole problem
Something new...
12. • Create prioritised list of high level features
• Have team(s) provide range estimate for each
– State assumptions being made about scope etc.
– Estimate based on "I'll be surprised if...“
– Estimate in whatever unit you prefer (Number of Stories, Story
Points, Ideal Days, etc.)
• Each sprint the team works to reduce the estimate of
remaining work; methods to do this could include
– Build some of it
– Find a library that does it
– Get scope reduced
• Latest expected dates can be communicated
Range Estimates And Reduce
13. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team completes 5 stories, and feel a bit
more confident they understand the scope
• Remaining estimate is 45 – 100 stories
Example Scenario 1
14. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team does some research and finds a
library that meets most of the requirements, and agrees
with stakeholders the other requirements can be
skipped
• Remaining estimate is 10 – 20 stories to integrate the
library
• Great job!
Example Scenario 2
15. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team does some research but doesn't
find anything that will help
• Remaining estimate is 50 – 120 stories
• Looks like the team did nothing for a sprint
• PROBLEM: if we're not prepared to accept scenario 3,
then we never get scenario 2
Example Scenario 3
16. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team discovers missing assumptions
which mean the work is larger than they thought
• Remaining estimate is 60 – 140 stories
• This is good – we understand the work better
• PROBLEM if managers just look at the number and not
the reason for the number this looks bad
Example Scenario 4
17. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team doesn't find missing
requirements or assumptions, but just decides work is
bigger than they thought
• Remaining estimate is 60 – 140 stories
• Team should try getting better at estimating
• PROBLEM if managers give team a hard time over this
they'll learn to pad their estimate next time
Example Scenario 5
18. • Team estimates work as 50 – 120 stories (it's a big
initiative)
• In first sprint the team doesn't change requirements or
assumptions, but just decides work is smaller than they
thought
• Remaining estimate is 30 – 90 stories
• Team should try getting better at estimating
• PROBLEM team might be worried that managers think
they were padding the earlier estimate
Example Scenario 6