In part one, we looked at the importance of understanding findings in order to make better decisions. To do this we and our decision-making leaders must become adept at data investigation and analysis so we can ask critical questions.

In part two I want to emphasize another truth that will prevent us from being fooled or misled by data analyses and findings: Metrics don’t necessarily make meaningful data. The truth may be far more complex than our metrics will show.

In general, there’s a big difference between data and the metrics we use. Metrics are measures or indicators of status or progress. Data are diagnostic. This distinction requires some explanation.

Metrics are often derived or calculated from a multitude of measurements or from data. Metrics give us a progress report or a status level of some type of performance. Data are the raw output of a process, test, or experiment. Usually data aren’t useful until they are turned into some form of information by an analysis of some kind.

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