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You Can’t Rush Agile Change Too often, organizations try to rush agile change. It is usually because they want to see the business benefits of agile as quickly as possible. Unfortunately, change doesn’t work like that—you can’t rush it. In fact, trying to change too fast often results in no change at all. Here are some examples to avoid. |
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How Failed Agile Transformations Can Still Have Value Not all agile transformations are successful in the same way; in fact, it’s possible to get tremendous value out of a failed attempt. A team that doesn't end up fully transitioning to an agile framework can still borrow some lessons from agile development methods to improve their processes. |
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Agile for Everything: Taking the Manifesto beyond Software The values of the Agile Manifesto, while written to apply to software, can form a basis for an adaptive approach to any project. Going from specific to general and inspecting and adapting along the way are great design ideas, no matter what you’re working on. Here's how to use feedback to take agile beyond software. |
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Why the Minimum Viable Product Matters The MVP brings tremendous value to a team’s ability to effectively implement agile practices. It also allows us to better understand what “value” actually means to our users and how context changes the meaning. Your MVP must move through your validation and release cycles while still being valuable to your users. |
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Learn Agile Principles Indirectly through Practice One of the primary questions for agile teams adopting a new approach such as Scrum is whether to start with principles or practices. Sometimes the best way to learn principles is indirectly, through practice. Experiences are a great way to learn, and sometimes they even teach you skills without your realizing it. |
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The Testing Practices and Metrics That Really Matter in Agile and DevOps Scaled agile and DevOps change the game for software testing. It’s not just a matter of accelerating testing; it’s also about fundamentally altering the way we measure quality. The test outcomes required to drive a fully automated release pipeline are dramatically different from the ones most teams measure today. |
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Predictive Analytics to Give Quality Engineering a Facelift Test automation is only as smart as we design it to be, but automation combined with artificial intelligence and machine learning is what can enable predictive analytics to produce smart outcomes—and that is the facelift quality engineering will soon receive. |
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If You Want Training to Take, Explore Experiential Learning People typically think of training classes as passive activities, where the instructor talks and the others listen. But experiential learning, where you learn through hands-on activities and then reflect on the experience, often gets the lesson to stick in people's brains better. Consider using interactive lessons. |
