Human perception of variation and how we execute the methods of four data processes—measurement, collection, analysis, and interpretation—were discussed in part one of this column. Because human variation can compromise the quality of data and render any subsequent analysis virtually useless for project purposes, its effects must be anticipated and minimized. To deal with this, eight questions need to be addressed.

The first four questions: reducing human variation in design

• Why collect the data? Is there a clear objective for this collection?
• What method(s) will be used for the analysis? This should be known even before one piece of data is collected.
• What data will be collected? What specific process output(s) does one wish to capture?
• How will the data be measured? How will one evaluate any output to obtain a consistent number, regardless of who measures it? Remember, there is no “true value,” and it depends on the specific objective.

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