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An interesting situation developed at one organization where the CFO looked at the time-to-fill metric and wanted an explanation from the HR director about why it was taking so long to fill jobs compared to other companies. During the period measured, there was one position that was very difficult to fill due to the special skills requiredthe time to fill for that position was 78 days. In another situation, the hiring manager was out for 3 months on leave, and the position was effectively on hold during the measured period. These numbers skewed the data because they were outliers. The same could happen with any data set that looks very strong at the aggregate level. The take-away? Keep in mind that a metric really only identifies an area that may warrant further investigation, as it did in these cases.