Twenty-five years ago, Peter Senge wrote “The Fifth Discipline”, considered the seminal text for how to build a learning organization. With obvious benefits, and the recipe needed for success, why don't we see more learning organizations? That was twenty-five years ago!
As Ash Maurya pointed out in his new book, Scaling Lean, “The goal isn't learning, the goal is traction.” Without a process that helps us turn learning into momentum, a culture of learning gets us nowhere. Without a strategy to overcome the challenges of distributed decision-making, we still make most decisions in ignorance.
Let's dust off these old ideas in light of all the discoveries we've made over the last decade in Lean Startup, Agile, and Continuous Delivery.
What are the critical elements that are missing in our organizations that prevent us from building a learning organization? What are the key obstacles to success?
In this talk, we'll breakdown the concept of a learning organization into discrete system components and analyze the requirements like engineers. Then we'll discuss a strategy for overcoming the challenges and iteratively transforming our organizations into learning organizations. From the building blocks of culture, to the design of organizational architecture, we'll build a roadmap for learning how to learn together.
Want to learn your way to being an AWESOME company? Learn how to become a learning organization.
Once we make our pain visible with Idea Flow Mapping, we've got a data-driven feedback to learn what works. Objective data enables us to do something we've never been able to do before in our industry: science. This talk is about how to do science in software development.
The Lean Startup community has pioneered the art of everyday science to reduce the risk of building the wrong product by running customer experiments to learn what works. By mapping these same basic scientific principles to technical risk management, we can run experiments to learn our way to AWESOME!
Edit
Archive
Delete
In this talk we'll cover:
How science is used in the Lean Startup world to run business model experiments
How science is used in the Lean Manufacturing world to support process control & supply chain optimization
How we can apply science in software development to systematically learn what works.
If you want to start learning and improving faster than ever before, you won't want to miss this talk.
There’s a huge disconnect between the business world and the engineering world that drives our software projects into the ground. We rewrite our software over and over again, not because we lack the engineering skills to build great software, but because we fail to communicate, make decisions in ignorance, and don’t adapt when our current strategy is obviously failing.
What if we could measure the indirect costs of pain building up on a software project? What if we could measure the loss of productivity, the escalating costs and risks, and could steer our projects with a data-driven feedback loop?
Visibility changes everything. With visibility, we can bridge the gap between the business world and the engineering world, and get everyone pulling the same direction.
Find out how you can:
1. Identify the biggest causes of productivity loss on your software project
2. Translate the world of developer pain into explicit costs and risks
3. Collaborate with other industry professionals in the art of data-driven software mastery
Let's break down the challenges and learn our way to success, one small victory at a time.
Speaker: Janelle Klein
Janelle is a NFJS Tour Speaker and author of the book, Idea Flow: How to Measure the PAIN in Software Development: a modern strategy for systematically optimizing software productivity with a data-driven feedback loop.
What makes software development complex isn't the code, it's the humans. The most effective way to improve our capabilities in software development is to better understand ourselves.
In this talk, I'll introduce a conceptual model for human interaction, identity, culture, communication, relationships, and learning based on the foundational model of Idea Flow. If you were to write a simulator to describe the interaction of humans, this talk would describe the architecture.
Learn how to understand the humans on your team and fix the bugs in communication, by thinking about your teammates like code!
Edit
Archive
Delete
I'm not a scientist or a psychologist. These ideas are based on a combination of personal experience, reading lots of cognitive science books, and a couple years of running experiments on developers. As I struggled through the challenges of getting a software concept from my head to another developer's head (interpersonal Idea Flow), I learned a whole lot about human interaction.
As software developers, we have to work together, think together, and solve problems together to do our jobs. Code? We get it. Humans? WTF?!
Fortunately, humans are predictably irrational, predictably emotional, and predictably judgmental creatures. Of course those pesky humans will always do a few unexpected things, but once we know the algorithm for peace and harmony among humans, we can start debugging the communication problems on our team.
Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world. We try to explain our problems in terms of "technical debt", but somehow the message seems to get lost in translation, and we drive our projects into the ground, over and over again.
What if we could detect the earliest indicators of a project going off the rails, and had data to convince management to take action? What if we could bridge this communication gap once and for all?
In this session, we'll focus on a key paradigm shift for how we can measure the human factors in software development, and translate the "friction" we experience into explicit risk models for project decision-making.
Have you ever wondered whether your retrospective format was actually effective at fueling learning and improvement? Are you ready to try something different?
"FOCOL Point" is Idea Flow Learning Framework's 5-step learning and improvement protocol. It works great for software improvement, but it also works for team reflection, personal reflection, or mentorship. Rather than searching for answers, a FOCOL Point is all about finding the right questions.
Once I walk through the protocol as a group, we'll make a FOCOL Point together!
First, we'll identify the biggest software problems faced by the audience using the "flashstorming" technique. Then we'll focus on the top problems of the group and start digging into the details by walking through a group-adapted version of the stop and think protocol:
1. **Focus**: What's the journey we're trying to understand?
2. **Observe**: What patterns do we see? (for all journey pattern types)
3. **Conclude**: What obstacles seem to be causing the pain?
4. **Optimize**: How could we have avoided the obstacles?
5. **Learn**: What questions should we ask ourselves in the future?
Amplify your learning by reflecting more productively on your own or with your team! You can immediately apply this technique on your own projects.
Workshop on Root Cause Analysis tools: Ask Why five times and fishbone (Ishikawa) diagram. I use this to teach basic concepts and give people an experience of using the tools.
Digging one level deeper into the details of Idea Flow Learning Framework, we'll do this second session as a group troubleshooting game! After we play the game, we'll do an "Experience Review" and analyze the causes of diagnostic difficulty, the nature of decision-making, and discuss strategies for making better decisions.
**The Troubleshooting Game:** I'll split the audience into two teams. Team 1 will stealthily hide a bug in the code. Team 2 will have to track down the bug in as little time as possible. Then Team 2 will have their chance to stump Team 1. The team that troubleshoots the bug the fastest will walk away with an exciting prize!
After we play the troubleshooting game, we'll do an "Experience Review" with each team's coding experience. Rather than optimizing the code, we'll focus on optimizing the problem-solving process. We will:
1. Visualize and discuss the differences between code sandwiches
2. Identify the major factors that caused diagnostic difficulty
3. Discuss the troubleshooting strategies used by each team and what made them more or less effective.
While it's certainly challenging to understand how we think and make decisions, it's an incredible opportunity to learn. By recognizing the inputs to our decisions, and how we evaluate trade-offs, we can compare our internal decision-making logic with our peers. With objective feedback on the consequences of our decisions, we can systematically optimize developer experience.
Learn how to master the art of software development with Idea Flow Learning Framework!
Once we make our pain visible with Idea Flow Mapping, we've got a data-driven feedback to learn what works. Objective data enables us to do something we've never been able to do before in our industry: science. This talk is about how to do science in software development.
The Lean Startup community has pioneered the art of everyday science to reduce the risk of building the wrong product by running customer experiments to learn what works. By mapping these same basic scientific principles to technical risk management, we can run experiments to learn our way to AWESOME!
Edit
Archive
Delete
In this talk we'll cover:
How science is used in the Lean Startup world to run business model experiments
How science is used in the Lean Manufacturing world to support process control & supply chain optimization
How we can apply science in software development to systematically learn what works.
If you want to start learning and improving faster than ever before, you won't want to miss this talk.
There’s a huge disconnect between the business world and the engineering world that drives our software projects into the ground. We rewrite our software over and over again, not because we lack the engineering skills to build great software, but because we fail to communicate, make decisions in ignorance, and don’t adapt when our current strategy is obviously failing.
What if we could measure the indirect costs of pain building up on a software project? What if we could measure the loss of productivity, the escalating costs and risks, and could steer our projects with a data-driven feedback loop?
Visibility changes everything. With visibility, we can bridge the gap between the business world and the engineering world, and get everyone pulling the same direction.
Find out how you can:
1. Identify the biggest causes of productivity loss on your software project
2. Translate the world of developer pain into explicit costs and risks
3. Collaborate with other industry professionals in the art of data-driven software mastery
Let's break down the challenges and learn our way to success, one small victory at a time.
Speaker: Janelle Klein
Janelle is a NFJS Tour Speaker and author of the book, Idea Flow: How to Measure the PAIN in Software Development: a modern strategy for systematically optimizing software productivity with a data-driven feedback loop.
What makes software development complex isn't the code, it's the humans. The most effective way to improve our capabilities in software development is to better understand ourselves.
In this talk, I'll introduce a conceptual model for human interaction, identity, culture, communication, relationships, and learning based on the foundational model of Idea Flow. If you were to write a simulator to describe the interaction of humans, this talk would describe the architecture.
Learn how to understand the humans on your team and fix the bugs in communication, by thinking about your teammates like code!
Edit
Archive
Delete
I'm not a scientist or a psychologist. These ideas are based on a combination of personal experience, reading lots of cognitive science books, and a couple years of running experiments on developers. As I struggled through the challenges of getting a software concept from my head to another developer's head (interpersonal Idea Flow), I learned a whole lot about human interaction.
As software developers, we have to work together, think together, and solve problems together to do our jobs. Code? We get it. Humans? WTF?!
Fortunately, humans are predictably irrational, predictably emotional, and predictably judgmental creatures. Of course those pesky humans will always do a few unexpected things, but once we know the algorithm for peace and harmony among humans, we can start debugging the communication problems on our team.
Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world. We try to explain our problems in terms of "technical debt", but somehow the message seems to get lost in translation, and we drive our projects into the ground, over and over again.
What if we could detect the earliest indicators of a project going off the rails, and had data to convince management to take action? What if we could bridge this communication gap once and for all?
In this session, we'll focus on a key paradigm shift for how we can measure the human factors in software development, and translate the "friction" we experience into explicit risk models for project decision-making.
Have you ever wondered whether your retrospective format was actually effective at fueling learning and improvement? Are you ready to try something different?
"FOCOL Point" is Idea Flow Learning Framework's 5-step learning and improvement protocol. It works great for software improvement, but it also works for team reflection, personal reflection, or mentorship. Rather than searching for answers, a FOCOL Point is all about finding the right questions.
Once I walk through the protocol as a group, we'll make a FOCOL Point together!
First, we'll identify the biggest software problems faced by the audience using the "flashstorming" technique. Then we'll focus on the top problems of the group and start digging into the details by walking through a group-adapted version of the stop and think protocol:
1. **Focus**: What's the journey we're trying to understand?
2. **Observe**: What patterns do we see? (for all journey pattern types)
3. **Conclude**: What obstacles seem to be causing the pain?
4. **Optimize**: How could we have avoided the obstacles?
5. **Learn**: What questions should we ask ourselves in the future?
Amplify your learning by reflecting more productively on your own or with your team! You can immediately apply this technique on your own projects.
Workshop on Root Cause Analysis tools: Ask Why five times and fishbone (Ishikawa) diagram. I use this to teach basic concepts and give people an experience of using the tools.
Digging one level deeper into the details of Idea Flow Learning Framework, we'll do this second session as a group troubleshooting game! After we play the game, we'll do an "Experience Review" and analyze the causes of diagnostic difficulty, the nature of decision-making, and discuss strategies for making better decisions.
**The Troubleshooting Game:** I'll split the audience into two teams. Team 1 will stealthily hide a bug in the code. Team 2 will have to track down the bug in as little time as possible. Then Team 2 will have their chance to stump Team 1. The team that troubleshoots the bug the fastest will walk away with an exciting prize!
After we play the troubleshooting game, we'll do an "Experience Review" with each team's coding experience. Rather than optimizing the code, we'll focus on optimizing the problem-solving process. We will:
1. Visualize and discuss the differences between code sandwiches
2. Identify the major factors that caused diagnostic difficulty
3. Discuss the troubleshooting strategies used by each team and what made them more or less effective.
While it's certainly challenging to understand how we think and make decisions, it's an incredible opportunity to learn. By recognizing the inputs to our decisions, and how we evaluate trade-offs, we can compare our internal decision-making logic with our peers. With objective feedback on the consequences of our decisions, we can systematically optimize developer experience.
Learn how to master the art of software development with Idea Flow Learning Framework!
Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world. We try to explain our problems in terms of “technical debt”, but somehow the message seems to get lost in translation, and we drive our projects into the ground, over and over again.
What if we could detect the earliest indicators of a project going off the rails, and had data to convince management to take action? What if we could bridge this communication gap once and for all?
In this session, we'll focus on a key paradigm shift for how we can measure the human factors in software development, and translate the “friction” we experience into explicit risk models for project decision-making.
A test strategy is the set of ideas that guides your test design. It's what explains why you test this instead of that, and why you test this way instead of that way. Strategic thinking matters because testers must make quick decisions about what needs testing right now and what can be left alone. You must be able to work through major threads without being overwhelmed by tiny details. James Bach describes how test strategy is organized around risk but is not defined before testing begins. Rather, it evolves alongside testing as we learn more about the product. We start with a vague idea of our strategy, organize it quickly, and document as needed in a concise way. In the end, the strategy can be as formal and detailed as you want it to be. In the beginning, though, we start small. If you want to focus on testing and not paperwork, this approach is for you.
Sippin: A Mobile Application Case Study presented at Techfest LouisvilleDawn Yankeelov
"Sippin: A Mobile Application Case Study," was presented at Techfest Louisville 2017 hosted by the Technology Association of Louisville Kentucky on Aug. 16th-17th.
Leveraging the Latest in Brain Science to Deliver the Next Generation of E-Le...Human Capital Media
With the explosion in brain research during the past 10 years, scientists know more about the brain than ever before. Consumer brain training software designed to improve memory, attention, cognitive ability and more has hit the market with a vengeance. How is this same research set to change the world of corporate learning and e-learning solutions? What does the next generation of e-learning look like? Join Dr. Alice Kim from the Rotman Research Institute, a premier international center for the study of human brain, along with Carol Leaman, the CEO of Axonify, to learn about:
Three key areas of brain research that are expected to have the most impact on corporate e-learning.
How the latest research is being applied in e-learning tools in the workplace.
Real corporate examples of improvements in knowledge retention, learning transfer and the bottom line.
Fabian Scarano - Preparing Your Team for the FutureTEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Preparing Your Team for the Future by Fabian Scarano. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
An introduction to immediate-reward reinforcement learning. Covers introductions, motivation, challenges with full RL, contextual bandits, policy evaluation, and architectural considerations.
Herman- Pieter Nijhof - Where Do Old Testers Go?TEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Where Do Old Testers Go? by Herman- Pieter Nijhof. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
What if we could measure the indirect costs of pain building up on a software project? What if we could measure the loss of productivity, the escalating costs and risks, and could steer our projects with a data-driven feedback loop?
By measuring the friction in “Idea Flow”, the flow of ideas between the developer and the software, we can create a data-driven feedback loop for learning what works. Rather than making decisions based on anecdote and gut feel, we can start driving our improvement decisions with real data.
Data-Driven Software Mastery is about learning and improving faster than ever.
Find out how you can:
• Identify the biggest causes of productivity loss on your software project.
• Avoid spending tons of time solving the wrong problems
• Collaborate with other industry professionals in the art of data-driven software mastery
Idea Flow gives us a universal language for describing our experience, so we can share the patterns and principles of what works. With a feedback loop, we can run real experiments!
Idea Flow turns the development community into a scientific community.
How to manage web projects without setting your hair on fireKathy Gill
It seems like everyone in the organization believes they know what makes a website "work" despite having no design training. Managers insist that "their" pages look or act in ways directly contrary to the rest of the website. Or the web.
What are the unique characteristics of the web that make managing design a challenge? How can we empower stakeholders while also creating a seamless user experience? And how would an iterative, collaborative design process facilitate a responsive web, one where sites work well on phones, tablets and desktops?
A lecture given at the Conference Magmin 2012 @ Salzburg. This is the annual conference of the Magnesium industry. CO2 is gaining more attention in this industry. This was the first presentation of this topic for this industry. It gave rather new insights.
The reaction between Olivine and CO2 was presented as a example. Partially because of the reaction, but also because this reaction produces Magnesium Carbonate. This is the input stream for this industry. The retrieval of this Magnesium Carbonate is quite cumbersome and expensive. So besides CO2 savings, this could result in economic savings.
Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world. We try to explain our problems in terms of “technical debt”, but somehow the message seems to get lost in translation, and we drive our projects into the ground, over and over again.
What if we could detect the earliest indicators of a project going off the rails, and had data to convince management to take action? What if we could bridge this communication gap once and for all?
In this session, we'll focus on a key paradigm shift for how we can measure the human factors in software development, and translate the “friction” we experience into explicit risk models for project decision-making.
A test strategy is the set of ideas that guides your test design. It's what explains why you test this instead of that, and why you test this way instead of that way. Strategic thinking matters because testers must make quick decisions about what needs testing right now and what can be left alone. You must be able to work through major threads without being overwhelmed by tiny details. James Bach describes how test strategy is organized around risk but is not defined before testing begins. Rather, it evolves alongside testing as we learn more about the product. We start with a vague idea of our strategy, organize it quickly, and document as needed in a concise way. In the end, the strategy can be as formal and detailed as you want it to be. In the beginning, though, we start small. If you want to focus on testing and not paperwork, this approach is for you.
Sippin: A Mobile Application Case Study presented at Techfest LouisvilleDawn Yankeelov
"Sippin: A Mobile Application Case Study," was presented at Techfest Louisville 2017 hosted by the Technology Association of Louisville Kentucky on Aug. 16th-17th.
Leveraging the Latest in Brain Science to Deliver the Next Generation of E-Le...Human Capital Media
With the explosion in brain research during the past 10 years, scientists know more about the brain than ever before. Consumer brain training software designed to improve memory, attention, cognitive ability and more has hit the market with a vengeance. How is this same research set to change the world of corporate learning and e-learning solutions? What does the next generation of e-learning look like? Join Dr. Alice Kim from the Rotman Research Institute, a premier international center for the study of human brain, along with Carol Leaman, the CEO of Axonify, to learn about:
Three key areas of brain research that are expected to have the most impact on corporate e-learning.
How the latest research is being applied in e-learning tools in the workplace.
Real corporate examples of improvements in knowledge retention, learning transfer and the bottom line.
Fabian Scarano - Preparing Your Team for the FutureTEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Preparing Your Team for the Future by Fabian Scarano. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
An introduction to immediate-reward reinforcement learning. Covers introductions, motivation, challenges with full RL, contextual bandits, policy evaluation, and architectural considerations.
Herman- Pieter Nijhof - Where Do Old Testers Go?TEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Where Do Old Testers Go? by Herman- Pieter Nijhof. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
What if we could measure the indirect costs of pain building up on a software project? What if we could measure the loss of productivity, the escalating costs and risks, and could steer our projects with a data-driven feedback loop?
By measuring the friction in “Idea Flow”, the flow of ideas between the developer and the software, we can create a data-driven feedback loop for learning what works. Rather than making decisions based on anecdote and gut feel, we can start driving our improvement decisions with real data.
Data-Driven Software Mastery is about learning and improving faster than ever.
Find out how you can:
• Identify the biggest causes of productivity loss on your software project.
• Avoid spending tons of time solving the wrong problems
• Collaborate with other industry professionals in the art of data-driven software mastery
Idea Flow gives us a universal language for describing our experience, so we can share the patterns and principles of what works. With a feedback loop, we can run real experiments!
Idea Flow turns the development community into a scientific community.
How to manage web projects without setting your hair on fireKathy Gill
It seems like everyone in the organization believes they know what makes a website "work" despite having no design training. Managers insist that "their" pages look or act in ways directly contrary to the rest of the website. Or the web.
What are the unique characteristics of the web that make managing design a challenge? How can we empower stakeholders while also creating a seamless user experience? And how would an iterative, collaborative design process facilitate a responsive web, one where sites work well on phones, tablets and desktops?
A lecture given at the Conference Magmin 2012 @ Salzburg. This is the annual conference of the Magnesium industry. CO2 is gaining more attention in this industry. This was the first presentation of this topic for this industry. It gave rather new insights.
The reaction between Olivine and CO2 was presented as a example. Partially because of the reaction, but also because this reaction produces Magnesium Carbonate. This is the input stream for this industry. The retrieval of this Magnesium Carbonate is quite cumbersome and expensive. So besides CO2 savings, this could result in economic savings.
Passive mobile measurement: The next big thing in market research? - TNSMerlien Institute
Presented by James Fergusson, Managing Director, Global Technology Sector - TNS
& Remy Bleijendaa, Digital Consultant, TNS
at Market Research in the Mobile World Asia-Pacific
30-31 January 2013, Kuala Lumpur, Malaysia
This event is proudly organised by Merlien Institute
Check out our upcoming events by visiting http://www.mrmw.net
What does "better" really mean? If we eliminate duplication, is the code better? If we decide to skip the unit tests, are we doing worse? How do we decide if one design is better than another design?
About 8 years ago, my project failed, despite "doing all the right things", and shattered my faith in best practices. Since then, I've learned to measure developer experience, use *data* to learn what works, and I've been codifying "better" into patterns and decision principles for years. In this talk, I'll show you the paradigm shift that led to all my discoveries, and hopefully change your perspective on "better".
"Idea Flow" is an alternative to the Technical Debt metaphor that focuses on problems in human interaction rather than problems inside the code. By measuring the "friction" that occurs when developers interact with the code, we can identify the biggest causes of friction and systematically optimize developer experience.
Why go to all this trouble? From my experience, the biggest causes of pain are seldom what we think. When we try to make things "better", we can easily miss our biggest problems, or inadvertently make things worse. Visibility turned my beliefs about "better" upside-down.
First, I'll walk you through the conceptual metaphor of "Idea Flow" and how to recognize friction in developer experience.
Next, we'll write a little code and record the experience using the open source "Idea Flow Mapping" software.
Finally, we'll discuss a handful of "decision principles" for optimizing developer experience and analyze our coding experience as a group.
What if we could measure the indirect costs of pain building up on a software project? What if we could measure the effects of learning curves, collaboration pain, and problems building up in the code?
We could:
Identify the highest leverage opportunities for improvement
Make the case to management that budget should be allocated for a solution
Lead the organization in making better decisions with a data-driven feedback loop to guide the way
Several years ago, I stumbled into a solution for measuring the growing “friction” in developer experience. Visibility turned my world upside-down.
We've been trying to explain the pain of Technical Debt for generations, but we've never been able to measure it. Visibility introduces a whole new world of possibilities.
In this talk, I'll show you what I'm measuring, how exactly I'm measuring it, then we'll talk through the implications for our teams, our organizations, and our industry.
We can identify the highest leverage improvement opportunities and steer our projects with a data-driven feedback loop.
We can breakdown the "wall of ignorance" between developers and management by defining an explicit language for managing technical risk.
We can teach the art of software development with a data-driven feedback loop and codify our knowledge into sharable decision principles.
We can revolutionize our business accounting methods to take the pain of software development into account, so the costs and risks are visible at the highest levels of the organization.
We can conquer the challenges across the software industry by working together, learning together, and sharing our knowledge with the world.
With visibility, we can start a revolution in data-driven learning.
Top 5 Reasons Why Improvement Efforts FailArty Starr
This is my story of lessons learned on why our improvement efforts fail... I had a great team. We were disciplined about best practices and spent tons of time on improvements. Then I watched my team slam into a brick wall. We brought down a fully-ramped semiconductor factory three times in a row, then couldn't ship again for a year.
Despite our best efforts with CI, unit testing, design reviews, and code reviews, we lost our ability to understand the system. I discovered our mistakes weren't caused by technical debt. Most of the problems were caused by human factors. We failed to improve because we didn't solve the right problems.
To learn, we need a feedback loop. To improve, we need a feedback loop with a goal.
There's five different ways our project feedback loop can break:
* **Broken Target** - Our definition of "better" is broken.
* **Broken Visibility** - We don't see the pain, so we take no action.
* **Broken Clarity** - We don't understand what's causing the pain.
* **Broken Awareness** - We don't know how to avoid the pain.
* **Broken Focus** - We see the pain, but our attention is focused on something else.
Find out how to repair the broken feedback loops on your software project.
Stop Getting Crushed By Business PressureArty Starr
This is my story of lessons learned on how to stop the crushing effects of business pressure... I was team lead with full control of our green-field project. After a year, we had continuous delivery, a beautiful clean code base, and worked directly with our customers to design the features. Then our company split in two, we were moved under different management, and I watched my project get crushed.
As a consultant, I saw the same pattern of relentless business pressure everywhere, driving one project after another into the ground. I made it my mission to help the development teams solve this problem. This is my story of lessons learned on how to transform an organization from the bottom up. I'll show you how to lead the way.
**Warning:** This strategy won't work in all organizations. In some cases, management doesn't want to know the truth. However, in most organizations I've worked with, management wants to improve, but doesn't know how to fix the system.
The crushing business pressure is caused by a broken feedback loop that's baked into the organization's design. In this presentation, I'll show you how to fix the broken feedback loop. Learn how to:
* Gather evidence of developer productivity loss
* Identify the key organizational changes required for success
* Make the case to management for improvement
* Partner with your manager for long-term success
If the system is broken, we need to fix the system. You can *change* the system by making the decision to lead.
**Note:** *This talk is not strictly dependent on attending, "Top 5 Reasons Why Improvement Efforts Fail", but you'll get way more out of the session, if you attend both.*
Identify Development Pains and Resolve Them with Idea FlowTechWell
With the explosion of new frameworks, a mountain of automation, and our applications distributed across hundreds of services in the cloud, the level of complexity in software development is growing at an insane pace. With increased complexity comes increased costs and risks. When diagnosing unexpected behavior can take days, weeks, or sometimes months, all while our release is on the line, our projects plunge into chaos. In the invisible world of software development, how do we identify what's causing our pain? How do we escape the chaos? Janelle Klein presents a novel approach to measuring the chaos, identifying the causes, and systematically driving improvement with a data-driven feedback loop. Rather than measuring the problems in the code, Janelle suggests measuring the "friction in Idea Flow", the time it takes a developer to diagnose and resolve unexpected confusion, which disrupts the flow of progress during development. With visibility of the symptoms, we can identify the cause—whether it's bad architecture, collaboration problems, or technical debt. Janelle discusses how to measure Idea Flow, why it matters, and the implications for our teams, our organizations, and our industry.
Open Mastery: Let's Conquer the Challenges of the Industry!Arty Starr
What if you could get upper management to care about your technical developer problems? Would you be willing to measure and prioritize the problems?
What if **WE** could stop the relentless business pressure that drives our software projects into the ground *across the industry*? I know this probably sounds impossible, but before you dismiss the idea entirely, let me show you that it *is* possible.
We can start a cascade of changes across the industry with only a handful of people that are willing to work together to make it happen.
Open Mastery is a peer learning network focused on codifying open decision models and standards to solve industry-wide problems. This presentation is about the obstacles, the strategy, and the business model.
Lastly, I want your help in looking for gaps in my ideas. Let's identify where the strategy might break, and figure out how to make it work. I'm launching Open Mastery in early 2016. Let's make this dream a reality.
CYCLES course (5): Systems and System ThinkingBryan Cassady
A lot of research has shown that systems are the key to innovation success.
Systems are made up of interrelated components of people and processes with a clearly defined, shared destination or goal.
Systems work best when everyone shares an understanding and commitment to the aim or purpose of the system.
The foundations are clarity and a commitment to learn, and improve.
Great companies have 3 characteristics that set them apart from the rest. These characteristics are:1. An ability to see and build on strengths 2. A commitment to build innovation eco-systems and 3. A commitment to ongoing action
Deliverables: Simplifying the challenges, structuring the learning process, getting better internally and in your eco-system.
Enough information to update your objectives and start another cycle.
Leveraging Diversity to Find What Works and Amplify Mike Cardus
Academic & pragmatic ways to gather a wide variety of ideas, then create ways to implement the ideas. They are trying to shift the default mode of problem solving away from people who are senior or tenured within the organization.
A lot of research has shown that systems are the key to innovation success.
Systems are made up of interrelated components of people and processes with a clearly defined, shared destination or goal.
Systems work best when everyone shares an understanding and commitment to the aim or purpose of the system.
The foundations are clarity and a commitment to learn, and improve.
Great companies have 3 characteristics that set them apart from the rest. These characteristics are:
1. An ability to see and build on strengths
2. A commitment to build innovation eco-systems and
3. A commitment to ongoing action
Deliverables: Simplifying the challenges, structuring the learning process, getting better internally and in your eco-system.
Designing Healthcare Technologies: Motivating Users by Decreasing Cognitive L...UXPA International
Healthcare users are a demanding group. Multiple beeping and blinking devices, frequent interruptions, competing demands, and high-risk tasks overload their cognitive capacity, leaving them with little patience for ambiguity or inefficiency and - more importantly - at risk for making serious errors. We will introduce participants to the factors motivating healthcare technology users by offering a peek into the world of a busy nurse and showing examples of the tragic errors that can result when overload occurs. We then propose six design principles based in cognitive theory and illustrated with real world examples as a framework to help UX designers motivate healthcare technology users by minimizing cognitive load. Participants will leave the session with actionable knowledge they can apply to current projects.
* Don't we all want to be more effective communicators?
* As a coach, don't we all want our clients to change their behavior in certain situations based on what we teach, how we mentor and coach?
* Weren't we all in frustrating situations when we try to explain something and at first it seems that people are getting it, but then when we ask a relevant question, the audience is lost? There are very specific reasons for that.
* I would like to help the audience to develop an awareness of the possible impacts of their communication.
* The premise is that as soon as we are aware, we have a better idea to drive towards a desired outcome and not just leave it to pure chance.
Csaba Bereczki
A Great Idea Isn't Enough for Successful Change - FinalKaiNexus
Presented by Mark Jaben, M.D., author of the book "Free the Brain"
Maybe you had expected more. Maybe it went ok, but you’d like it to go smoother. Maybe its gone well and you want to understand about how that happened for next time. Maybe you’d like change to be less of a hassle.
If so, this webinar is for you.
As a result of this webinar, you will understand:
Change is a verb, not a noun
The fundamental unit of change
Why your belief about what’s going on is not the result of what you think.
Why conflict is what you should expect and what you actually need for successful change
The choice to resist or engage is not an analytical one, so why approach it that way.
We are not wired to resist; we are wired to succeed.
An ideal change must work AND be workable; judging each uses different functions in the brain.
Creating a culture that provokes failure and boosts improvementBen Dressler
Everyone fails - but not everyone uses failed attempts as a source of learning and improvement. This talk outlines a framework to turn failure into gaining knowledge by understanding IF, HOW and WHY something fails.
This course covers what is Innovation and why everything needs to start with alignment.
If you don’t know where you’re going... Chances are you won’t get where you want to go.
Alignment is the foundation of effective growth and Innovation. It is about finding what is important to you (MISSION) and matching this with what the market wants (NEEDS) and plan to deliver and extract value. It is also about an honest assessment of who you are. (CULTURE)
Deliverables: After this course you will be able to identify 3-4 True North priorities for your company /division (True north) priorities can be:
1. Changing what you are doing and why
2. Changing how you work to generate or extract more value
3. How to work smarter and / or get your culture supporting your innovation objectives
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
In the ever-evolving landscape of technology, enterprise software development is undergoing a significant transformation. Traditional coding methods are being challenged by innovative no-code solutions, which promise to streamline and democratize the software development process.
This shift is particularly impactful for enterprises, which require robust, scalable, and efficient software to manage their operations. In this article, we will explore the various facets of enterprise software development with no-code solutions, examining their benefits, challenges, and the future potential they hold.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
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
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
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!
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
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.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
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✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
7. News Flash!
For the first time in our industry,
we have all the tools necessary
to pull this off.
8. Data-Driven Software Mastery
Five Talks
Stop Getting Crushed By Business Pressure
How to Build a Learning Organization
Top 5 Reasons Why Improvement Efforts Fail
Make a F.O.C.O.L. Point!
10. Five Disciplines of a Learning Organization
Personal Mastery
Mental Models
Shared Vision
Team Learning
Systems Thinking
These disciplines are emergent with science.
11. , Developer & Consultant for 15+ years
Specialized in Statistical Process Control (SPC)
and Supply Chain Optimization from Lean Manufacturing (I <3 cool data)
Continuous Delivery infrastructure, design & automation strategies
Janelle Klein
Who Am I?
How to Measure the PAIN
in Software Development
Janelle Klein
leanpub.com/ideaflow
Data-Driven
Software Mastery
I’m also a hobbyist Cognitive Scientist
20. The amount of PAIN was caused by…
Likeliness(of((
Unexpected(
Behavior(
Cost(to(Troubleshoot(and(Repair(
High(Frequency(
Low(Impact(
Low(Frequency(
Low(Impact(
Low(Frequency(
High(Impact(
PAIN(
21. What Causes Unexpected
Behavior (likeliness)?
What Makes Troubleshooting
Time-Consuming (impact)?
Semantic Mistakes
Stale Memory Mistakes
Association Mistakes
Bad Input Assumption
Tedious Change Mistakes
Copy-Edit Mistakes
Transposition Mistakes
Failed Refactor Mistakes
False Alarm
Non-Deterministic Behavior
Ambiguous Clues
Lots of Code Changes
Noisy Output
Cryptic Output
Long Execution Time
Environment Cleanup
Test Data Creation
Using Debugger
Most of the pain was caused by human factors.
What causes PAIN?
22. What Causes Unexpected
Behavior (likeliness)?
What Makes Troubleshooting
Time-Consuming (impact)?
Non-Deterministic Behavior
Ambiguous Clues
Lots of Code Changes
Noisy Output
Cryptic Output
Long Execution Time
Environment Cleanup
Test Data Creation
Using Debugger
What causes PAIN?
Semantic Mistakes
Stale Memory Mistakes
Association Mistakes
Bad Input Assumption
Tedious Change Mistakes
Copy-Edit Mistakes
Transposition Mistakes
Failed Refactor Mistakes
False Alarm
Most of the pain was caused by human factors.
23. PAIN occurs during the process of
understanding and extending the software
Complex(
So*ware(
PAIN
Not the Code.
Optimize “Idea Flow”
24. My team spent tons of time working on
improvements that didn’t make much difference.
We had tons of automation, but the
automation didn’t catch our bugs.
25. My team spent tons of time working on
improvements that didn’t make much difference.
We had well-modularized code,
but it was still extremely time-consuming to troubleshoot defects.
26. The hard part isn’t solving the problems
it’s identifying the right problems to solve.
“What are the specific problems
that are causing the team’s pain?”
27. measures the time spent on:
Idea Flow
x
Troubleshooting
x
Learning
x
Rework
Quality Risk Familiarity Risk Assumption Risk
28. Idea Flow Mapping Tools
(Open Source, Supported GA ~June 2016)
github.com/ideaflow/tools
29. “What caused the pain
in this case?”
Categorize the Problems with #HashTags
#ReportingEngine
#Hibernate
#MergeHell
30. 1. Test Data Generation
2. Merging Problems
3. Repairing False Alarms
1000 hours/month
Add up the Pain by Category
31. 0%
100%
Release 1 Release 2 Release 3
Percentage Capacity spent on Troubleshooting (red) and Learning (blue)
Chaos Reigns
Unpredictable work stops
fitting in the timebox
Troubleshooting
Progress
Learning
Analyzing Long-Term Trends
42. Learn & Adapt
Just because we repair the car…
doesn’t mean we know how to drive.
43. Quality Target
Lower Control Limit
Upper Control Limit
X"
This is “Out of Control”
Lower Variability = Better Control
Steering Wheel = Process Control
44. “Pain Control” in Software Development
Optimal Friction
Upper Control Limit
X"
“Out of Control”
20min
0m
Average Pain per Incident
This is Better
Target
Control Limit
Categorize the Pain Type
45. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Improve Quality of Decisions
Idea Flow Learning Framework
46. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Target - The direction of “better”
Target: Optimize the Rate of Idea Flow
Idea Flow Learning Framework
47. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Input - The constraints that limit our short-term choices…
Idea Flow Learning Framework
48. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Output - The pain signal we’re trying to improve
Idea Flow Learning Framework
49. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Focus on the biggest pain…
F ocus!
Idea Flow Learning Framework
50. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
1. Visibility - Identify the specific patterns
1.
Visibility
Idea Flow Learning Framework
51. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
2. Clarity - Understand cause and effect
2.
Clarity
Idea Flow Learning Framework
52. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
3.
Awareness
3. Awareness - Stop and think to adjust habits
Idea Flow Learning Framework
53. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
4. Run Experiments to Learn What Works
Idea Flow Learning Framework
54. Optimal Friction
Upper Control Limit
X"
“Out of Control”
20min
0m
Average Pain per Incident
This is Mastery
Target
Control Limit
Categorize the Pain Type
This is the Process of Mastery
56. “The Art of the Scientist” Workshop, Ash Maurya
Ash:
“What’s the most important thing that scientists do?”
“Run Experiments!”
“Analyze Data!”
Getting Involved with Lean Startup
57. “The Art of the Scientist” Workshop, Ash Maurya
NO!
?
?
?
?
?
?
?
Getting Involved with Lean Startup
58. “The Art of the Scientist” Workshop, Ash Maurya
Ash:
“The most important things scientists do is build models.”
Getting Involved with Lean Startup
61. Test the Model
(Experiments)
Refine the Model
(Patterns)
False&
Predic,on&
Scien,fic&
Model&
Modeling
(Inductive)
Experimentation
(Deductive)
Empirical Data
The Scientific Method
We can’t ignore
this part.
62. Test the Model
(Experiments)
Refine the Model
(Patterns)
False&
Predic,on&
Scien,fic&
Model&
Modeling
(Inductive)
Experimentation
(Deductive)
Empirical Data
Science is a Feedback Loop
that Fuels Discovery
Creating an explicit model makes
our beliefs testable and our discoveries additive.
We can’t ignore
this part.
63. “The Art of the Scientist”
Lean Startup Workshop, Ash Maurya
Ash:
“The goal isn’t learning, the goal is traction.”
64. Optimize the Rate of Flow in a Supply Chain
Focus on
Limiting
Constraint
(Goldratt’s Theory of Constraints, “The Goal”)
66. Optimal Friction
Upper Control Limit
X"
“Out of Control”
20min
0m
Average Friction per Customer
This is Traction
This is the Process of Lean Startup
High
Friction
Min
Friction
“No”
Threshold
Customer
Happiness
Categorize the “No” Type
67. “The Idea Flow Factory”
(supply chain model)
Optimize the Rate of Idea Flow
Across the Software Supply Chain
69. Optimal Friction
Upper Control Limit
X"
“Out of Control”
20min
0m
Average Pain per Incident
This is Traction
Target Rate
Control Limit
Categorize the Pain Type
This is the Process of Idea Flow Mastery
70. We can apply the entire suite of cost & risk reduction tools
from Lean Manufacturing!!
Supply Chain Optimization
Statistical Process Control (SPC)
Optimal Friction
Upper Control Limit
X"
“Out of Control”
20min
0m
Average Pain per Incident
Target
Control
Limit
Throughput Accounting
71. Test the Model
(Experiments)
Refine the Model
(Patterns)
False&
Predic,on&
Scien,fic&
Model&
Clarity
(Why)
Awareness
(How)
Visibility
(What)
Use Science to Fuel “Explicit Mastery”
Model “Decision Principles”
72. What’s a Decision Principle?
1. How do I evaluate my situation?
2. What should I optimize for?
Answers Two Questions
73. The Haystack Principle
Lots of unvalidated changes
Easier to find the needle.
Decision Principle: The Haystack Effect
Optimize for small manageable haystacks.
74. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Use Science to Fuel “Explicit Mastery”
Systematically codify Decision Principles
from lessons learned
79. Observe Pattern
“Do I know this pattern?”
Metaphors are patterns of conceptual “Shapes”
80. Three Different Types of Metaphors
Object Patterns
(Thing)
Context/Relationship Patterns
(Space)
Process Patterns
(Time)
We “see” the world through a fabric of metaphor.
82. “This looks like
a tech debt thing.”
1. Categorize patterns by concept type
83. “This looks like
a painful tech debt thing.”
2. Categorize variations by intensity.
Pain level = 8
84. = Little Debt
= Medium Debt
= Big Debt
Our Beliefs about Developer Pain
85. PAIN occurs during the process of
understanding and extending the software
Complex(
So*ware(
PAIN
Pain occurs over TIME.
86. What do you think happens when we
make this transition?
Process Patterns
(Time)
Object Patterns
(Thing)
87. What Causes Unexpected
Behavior (likeliness)?
What Makes Troubleshooting
Time-Consuming (impact)?
Take a Closer Look at the Patterns
Familiarity Mistakes
Stale Memory Mistakes
Semantic Mistakes
Bad Input Assumption
Tedious Change Mistakes
Copy-Edit Mistakes
Transposition Mistakes
Failed Refactor Mistakes
False Alarm
Non-Deterministic Behavior
Ambiguous Clues
Lots of Code Changes
Noisy Output
Cryptic Output
Long Execution Time
Environment Cleanup
Test Data Creation
Using Debugger
Most of the pain was caused by human factors.
88. “What caused the pain
in this case?”
We Start to Experience the World Differently
#ReportingEngine
#Hibernate
#MergeHell
92. The Clarity Principle
Our understanding deepens when we explain
the similarities and differences of experiences
and the relationships of cause and effect
102. Circle Leader
Circle Member
Focus: What’s the problem to solve?
Observe: Ask questions about the facts
Conclude: What’s causing the pain?
Optimize: How do we reduce pain?
Learn: What questions does this raise?
Observation
Questions
Make a F.O.C.O.L Point!
Summarize lessons learned in a
#HashTagged Blog.
Deep Reflection in Open Mastery Circles
107. Me: "So first, George, can you describe what you were trying to do before you
encountered the conflict?”
George: "This was back when I was getting the token to work in the email. I
wrote the code to generate the token, edited the email template to include the
token in the email link, but the token wasn't showing up in the actual email."
Me: "So what did you do next?"
George: At first, I thought there was something wrong with the token variable
code, but the problem turned out to be a misspelled variable name in the
email template. Doh!"
Focus: What Major Factors Caused the Pain?
Observe: Ask Questions About the Facts.
109. Painful Consequences: Consequence
Conclusions: What Caused the Pain?
Ran experiments by sending emails over and over again
(23 emails with a missing tokenId)
Redeployed application when uncertain about the cause
Ambiguous Clue
Manual Execution (slow)
110. Optimize: How could we have avoided the pain?
What’s an alternative strategy
that could have mitigated these risks?
George: My main strategy was to do a small #VerticalSlice by getting the
“email send” part working, before adding the token logic for the security part. I
understand how the #ManualExecution and an #AmbiguousClue caused the
friction, but I'm not really sure what I would do differently if I could do it again.
Me: "George, can you describe your original strategy to mitigate risk?”
111. Optimize: How could we have avoided the pain?
What’s the strategy pattern we’re
trying to implement?
Alternative Strategy:
APIs for each email workflow
Wire up email last
Strategy
112. Optimize: How could we have avoided the pain?
What’s the strategy pattern we’re
trying to implement?
Alternative Strategy:
APIs for each email workflow
Wire up email last
Strategy
113. Optimize: How could we have avoided the pain?
Alternative Strategy:
APIs for each email workflow
Wire up email last
Situation
What’s the situation we need to recognize
in order to decide to use the strategy?
114. Situation Strategy Consequence
Developer Journeys
#HiddenOutputs
Create
#ObservableInterfaces
Avoid #AmbiguousClues &
#ManualExecution
Optimize: How could we have avoided the pain?
115. Learn: What questions does this raise?
What questions
should we ask ourselves in the future?
In what situations
should we ask the question?
119. Experiment
Time
Our Perception of Time is WAY OFF
Setup Experiment Analyze Results &
Decide Next Experiment
Execute
waiting - time goes slow
doing - time zooms by
121. The Code Sandwich Principle
The thickness of the
sandwich increases
troubleshooting
difficulty
Behavior Complexity
Observability
Ease of Manipulation
Optimize for experimentation.
123. The bigger the cloud of possibilities,
the more we need a strategy.
124. The Clarity Principle
Our understanding deepens when we explain
the similarities and differences of experiences
and the relationships of cause and effect
127. The Awareness Principle
We can only avoid a mistake
if we predict the consequences
of the decision in the moment.
128. 18:120:00
George’s Painful Experience
I know I made a big haystack,
I’ll do better next time.
This is hindsight bias, it’s not that easy!
The Experience Review
129. The Challenge
We tend to make auto-pilot decisions and do what’s familiar
How do we break decision habits?
130. Imagine your brain is a
decision-making engine
written in code.
Breakpoint
Stop and Think!
Changing Decision Habits
132. The Checklist Manifesto
Atul Gawande
Scaling Lean (Lean Startup)
Ash Maurya
+
Change Decision Habits with Strategy Experiments
133. 14:230:00
I want to avoid this…
Thinking Checklist
Is my current approach likely to cause a big haystack?
Situation: start of subtask
Let’s Make a Checklist!
“What question could I ask my future self to
recognize similar risks in the future?”
“In what situation would I ask the question?”
134. 0:00
Stop and Think:
Is my current approach likely to
cause a big haystack?
Predict: Small haystack
Strategy Experiments
135. 18:120:00
Stop and Think:
Is my current approach likely to
cause a big haystack?
Predict: Small haystack
False Prediction
Strategy Experiments
136. 18:120:00
Stop and Think:
Is my current approach likely to
cause a big haystack?
False Prediction
Strategy Experiments
High-Risk Situations
1. Unraveling sweater
2. Integration-heavy change
3. High state variation
4. Minimum scope is big
Q: Is my current approach likely to
cause a big haystack?
Start of Subtask
139. The Awareness Principle
We can only avoid a mistake
if we predict the consequences
of the decision in the moment.
140. Three Stages of Mastery
Visibility
Clarity
Awareness
See
Explain
Predict
141. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
Use Science to Fuel “Explicit Mastery”
Systematically codify Decision Principles
from lessons learned
142. Five Disciplines of a Learning Organization
Personal Mastery
Mental Models
Shared Vision
Team Learning
Systems Thinking
These disciplines are emergent with science.
143. How to Measure the PAIN
in Software Development
Janelle Klein
These are the Blueprints!
++
146. Input:
Decision Constraints
Target: Optimize the Rate of Idea Flow
short-term looplong-term
loop
1.
Visibility
2.
Clarity
3.
Awareness
F ocus!
Output: “Friction” in Idea Flow
How do my decisions affect your experience?
Use Science to Fuel “Explicit Mastery”
148. Bigger Social Network of Brains
Collaboration to Perform a Bigger Function (Organization)
Component
Component
Hub
Hub
Hub
The Challenge: Knowledge & Decision-Making are Distributed
155. 4. Optimize the Whole
2. Design the Strategy
1. Identify Obstacles
(Focus)
3. Learn What Works
(Traction)
Steering
Wheel
Create a Steering Wheel to Drive the Organization!
$$ $$
156. Focus: Quality of Improvement Decisions
Focus Traction
$$$ $$
Focus: Quality of Investment Decisions
Risk
Translator
(interface)
Management
(Coordination)
Engineering
(Execution)
Open Mastery Learning Framework
Idea Flow Pain Sensor
157. If your Interested in doing this:
Free Support Network for
Data-Driven Software Mastery
158. Open Mastery Learning Platform
Idea Flow Mapping Tools
Team Mastery Platform
Team
Joe
Sally
Mark
Eric
Community
Collaboration Platform
Anonymized
Data
Project
Tiger
Project
Bear
(REST)
Shared #HashTag Glossary
of Patterns & Principles
with Examples
159. The Conversation
is on Slack
We’re debating the patterns
and principles of Idea Flow in Wikipedia
It’s a Developer Party!
We’re sharing our ideas
over Blogs
(and managers are invited)
160. Industry Peer Mentorship Network
Companies
Community
Groups
HQ in
Austin
Open Mastery
Austin
meetup.com/Open-Mastery-Austin
161. Janelle Klein
openmastery.org @janellekz
Check out openmastery.org for details.
Read my Book.
Think About It.
FREE with
Reading GroupBuy It
How to Measure the PAIN
in Software Development
Janelle Klein