HR Metrics, Analytics, and Data: 7 Rules to Remember




Numbers seem to be at the top of everyone’s priorities right now. And when I say numbers, I mean metrics, big data, and analytics. But before we go any further, it’s important to understand that these terms are different. I know they are sometimes used interchangeably. I’m guilty of it myself. Here are the definitions:

Metrics are focused on tracking past performance.

Analytics is about using past data to generate predictions or insights.

Data are statistics collected for use in analytics. The term big data refers to data sets that are too large and complex to manipulate with standard tools.

I’ve always been a numbers person, but even so, I’ve really been paying attention lately to the numbers conversation. Human resources professionals need to develop an affinity for the numbers. It’s a part of the SHRM competency model both in the areas of business acumen and critical evaluation. One of the things I’m very conscious of is that metrics and data aren’t soley about the calculation. It’s also about interpreting the findings. That’s not a math issue. It’s a critical thinking issue. Here are some of the rules I’ve found helpful when it comes to dealing with metrics, analytics and data.

  1. Define the metrics of success. Every organization has their own numerical definition of success. For example, I’ve worked in industries where triple digit turnover was the norm. So, getting turnover to 75 percent was a small miracle. In other industries, that would be totally unacceptable.
  2. Establish targets, including acceptable ranges. Speaking of defining success, it might make more sense to think of success “ranges” versus a single number. External and internal factors can impact numbers. We can still be successful even when factors change the metric.
  3. Capturing data versus using data. There is a difference between capturing data and actually using it. Companies should focus on capturing data that will have an impact on the business. It makes no sense to capture data just for the sake of it.
  4. There will be exceptions. As much as we should focus on the analytics, there will be moments when someone says “Forget the numbers. THIS is what we’re going to do.” And you will have to figure out how to deal with it.
  5. Create a dashboard, including "at a glance” data with visual indicators. If your department or organization is new to using metrics and analytics to make business decisions, having a dashboard can be very helpful. It provides people with one place to view the information.
  6. Look for patterns, trends and relationships in the data. Sometimes a single number will tell you something. But more often, the relationship between numbers will tell you a lot. A metrics dashboard (see # 5) can help individuals see the connections and make good decisions.
  7. Take action. This is the most important rule. There’s no reason to spend time calculating and analyzing numbers if you’re not going to do anything with them. Organizations need to commit to using the information they are gathering to benefit the business.

The reply “I’m not a numbers person.” isn’t acceptable – for any profession. Numbers have always been a part of business. Add to that the role technology is playing to push the conversation about metrics, analytics and data down the organizational hierarchy. A conversation that once was reserved for the C-Suite is now a skill that every manager needs to have.


Originally posted on HR Bartender blog.



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