It's all too easy to embrace metrics so fully that your job consists entirely of coding, tracking, analyzing, and defending your metrics. Whoa! Pick a few meaningful ones and let the rest go.

A good metric is one that provides decision makers with the data they need to make fact-based decisions.

Take a look at one example of a metric—measuring turnover—to see how to make it more meaningful for decision makers.

• The baseline measure is percent of employees who left the company during the year. That's useful information.

• However, it is probably more useful to know how many of those people left voluntarily as opposed to those who left involuntarily

• Even more useful might be a metric that also measures the number of employees who left voluntarily who were among the company's top performers.

• Going one step further, if the company is losing top performers, management will want to know if the turnover is companywide or concentrated in one department.

• Now, you've got data that can drive decision making. The company can act to identify the reasons top people are leaving and take steps to correct the situation.

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Often, a metric isn't meaningful without a yardstick. For example, let's assume you hired 50 people during the year with an average time to fill of 6 weeks and a cost per hire (CPH) of $5,000.

It is difficult to know what this means without a benchmark. What was the quality of the people hired? Is a CPH of $5,000 better or worse than you have done in the past? Better or worse than industry averages? Better or worse than your chief competitors'?

To really understand the story behind the numbers, metrics themselves need a benchmark or standard, either internal or external. Keep these tips in mind:

• Use data that are readily available and can be gathered at regular intervals.

• Avoid soft metrics based on feelings or intuition.

• Use the cost/benefit ratios, formulas, key performance measures, and language your business leaders use.

• Tie metrics directly to the key challenges facing the business.

• Include measures of results and quality; don't limit the focus to costs.

• Keep it simple; metrics don't have to be complicated.