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2 Ways to Know Your Work Is Actually Done Some people think a good indication that a piece of work is done is if it's been tested. But by whom, and how? Testing alone doesn’t specifically determine whether you are done—especially when we probably don’t mean the same thing when we all talk about testing. Here are two ways to know when your work is truly done. |
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Beware of Success Stories The tendency to look back and think you know what contributed to a success is called survivorship bias. It occurs when you make a decision or take some action based on past successes while ignoring past failures. That's why it's important to approach reports of successful projects with a healthy dose of skepticism. |
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Superior Leaders Ask the Tough Questions Inspiring quotes can be motivating, but there's more to good leadership. New leaders may feel compelled to find clever and memorable things to say, when in reality, they should probably focus less on what they’re saying and more on what they’re hearing. The best leaders ask good questions and listen to the answers. |
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Building Good Scrum Habits Building good habits is an important part of an effective Scrum team. Habits are a form of automation: The more basic processes we can automate, the more we can focus our energy on hard things. The Scrum process, with its focus on rituals, helps us by providing a framework for collaboration and making it second nature. |
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Tips for Getting an Agile Transformation Off the Ground Many agile transformations are doomed before they even begin. Organizations focus on the wrong things up front, resulting in a poorly planned effort that doesn’t deliver business value. Here are some tips to get things started the right way, including how to communicate well, define roles, and change your culture. |
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Before Data Analysis, You Need Data Preparation One of the prerequisites for any type of analytics in data science is data preparation. Raw data usually has several shortcomings in structure, format, and consistency, so first it has to be converted to a usable form. These are some types of data preparation you can conduct to make your data useful for analysis. |
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2 Ways to Standardize QA Practices Testing can get complicated when each project is using a completely different toolset, language, and reporting status, with different measurements and formats. Testing is a reaction to context and what we encounter, so how we test cannot be standardized. What we can standardize is the stuff that surrounds the testing. |
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Rethinking Your Measurement and Metrics for Agile and DevOps In their transition to agile and DevOps, many teams forget they also need to update their measurement and metrics plan. Some measurements and metrics from the traditional waterfall software development lifecycle may remain useful, but many may not provide value—and some may even adversely impact progress toward goals. |
