How to calculate variance (and why it’s important in business)

For a product manager seeking to evaluate the potential of different product features based on customer satisfaction, understanding and calculating variance and standard deviation are crucial. Variance measures the dispersion of data points from their mean, while standard deviation provides a more interpretable metric by taking the square root of variance. The article illustrates how variance and standard deviation can be calculated using customer satisfaction scores (CSAT) for product features, and how these measures can indicate feature stability and customer satisfaction consistency. For example, a low standard deviation suggests consistent customer satisfaction, while higher values indicate variability and potential issues requiring attention. The text also highlights the pros and cons of using variance, such as its sensitivity to outliers and complexity in calculation, while recommending tools like Excel, Google Sheets, and programming languages like Python and R for automation. Understanding these statistical measures helps in making informed decisions to improve product features and enhance customer satisfaction.

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