If there is a difference between the results which you projected (or budgeted), and your actual results, you have a variance . Calculating the amount and composition ( isolating each of its contributing components) of that variance is important -- but the key to using it as an analytic tool for course correction is to understand how and why the disparity occurred. The most unproductive use of this data is to use it like a light switch , i.e., "This thing didn't work, so let's scrap it and start over with a different approach." Used properly, you can use the "how" and the "why" to minimize trail and error, minimize time and resources lost, and not, in essence sell your car because it has run out of gasoline. Incidentally, by "variance" I absolutely refer to deviation from the expected result , and not deviation from a statistical mean . This is not a statistics exercise in standard deviation or sampling. This is a briefing on how to use ...
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