Basics of 6-Sigma and Shewhart Control Charts (Slidecast)
Recently, I got around to turning my AgileKitchen recording into a full-fledged slidecast.
In my experience, in Agile-teams, the percentage of metrics used to make management decisions is noticeably higher than in teams that follow more conservative development models. However, it must be understood that each dimension inevitably contains an error. Before making a decision based on “anomalies” in the observed values, it would not be bad to understand what is behind this “anomaly”: some special reason that requires management response, or this behavior is normal for the system in question ?
The slideshow hints at how to separate the properties of the system from the special causes of deviations in the measurement results, and describes the main mistakes in using the measurement data when making management decisions.
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In my experience, in Agile-teams, the percentage of metrics used to make management decisions is noticeably higher than in teams that follow more conservative development models. However, it must be understood that each dimension inevitably contains an error. Before making a decision based on “anomalies” in the observed values, it would not be bad to understand what is behind this “anomaly”: some special reason that requires management response, or this behavior is normal for the system in question ?
The slideshow hints at how to separate the properties of the system from the special causes of deviations in the measurement results, and describes the main mistakes in using the measurement data when making management decisions.
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Source: https://habr.com/ru/post/136193/
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