One HR Metric, Interpreted 5 Ways (fail!) - bettHR

One of the most overlooked realities when it comes to HR metrics, is the importance of the story around the number you share. This is why so many of our HR dashboards and metrics updates, live a very quick death never to be looked at or referred to as useful material ever again.

When you share numbers, particularly to leaders outside of your own area of focus – let’s say you’re in HR and you’re sharing metrics with the C-suite comprised of Finance, Marketing, R&D, etc. – your metrics are always going to be confusing because each person at the table, and each person will view the number in a different way.

When we look at numbers, no matter who we are, we come with our own perceptions, biases, and lens through which we see that number. So we basically aren’t sharing anything of any value.

The data is fine, but if it’s not understood exactly the same way by each reader, if it’s not able to stand up to the five year test (we can refer back to it and understand what it means, even if every person who worked on that number is in a new role) – it is a waste of your time.

The story you tell around your HR metrics, which is a step that most data scientist and data analytic experts skip completely – HELLO: opportunity for you!!! – is the only thing adding actual value to the numbers. To show you how this works, we’re going to use one common HR metric, through the perspective of five leaders taken from a real-life experience.

One Metric, Interpreted 5 ways at One Company

For this example, we’ll be using this metric: 16% Turnover Rate

Person 1: HR Manager Point of View

The HR Manager prepares this metric to be shared to the leaders across the organization – providing them with the numbers only. She was asked for the turnover rate, so that’s exactly what (and all) she shared.

Her take on the number – honestly, she didn’t read much into it, just noted that it was 16% in her mind and that seemed to be fairly good – less than 25% of the employee population turned over in the previous 12 months, so it seemed fine.

Let’s see what the others think when she shared this.

Person 2: Director of HR

“Eek – we have a 16% turnover rate? Is this for year-to-date or something different? Do we know where these employees are leaving from – is it a specific group or leader? Do we know where they’re going or why they’re leaving? Have we looked at the correlation between turnover and our employee engagement scores?”

She’s left with a lot of unanswered questions with this metric. Her view is that this number seems higher than it should be, but she doesn’t have a point of reference and it isn’t clear where this number comes from and/or who it impacts.

With lots of questions and incomplete data – she’ll do one of two things. One, she’ll push back on the HR manager until all of her questions are answered, and she understands the number from her perspective in case anyone asks; or two, she’ll be annoyed with how much is left unanswered and chuck it to the side as just another number.

Person 3: VP of Marketing

“Ok, so that’s the turnover rate… is that good? How does that relate to my team’s turnover rate? And how does my turnover rate compare to other groups? I know that we were having some issues with performance and we had some turnover that would be considered smart/healthy for our department, is that taken into account with this number? Is there a goal around this I should be aiming to get to?”

The VP of Marketing had many questions as well, but notice they were different from the Director of HR’s questions. Instead, his questions were focused on what was interesting to him and how the number applied to his organization and scope of influence.

Without that information or those answers, his response? Push it aside and forget about it. He figured that if there was an issue, HR would reach out to him and they could go from there.

Person 4: Director of Finance

“This can’t possibly be applicable to my team. We have had very little turnover, so I’m not sure why I’m seeing this. We’re doing everything we can to retain our employees and we’ve been doing so. What is this about? There isn’t really more I can do here from a turnover perspective.”

The leader in Finance was basically… annoyed. Her team was “all good” in her view, so this number was, frankly, a waste of time in her book. Yes, she was pleased to see something more objective come out of HR, but it was completely worthless to her.

She also noted separately, that after seeing a few metrics like this shared from HR, she stopped looking at them altogether because she didn’t believe they added any value or had anything actionable for her to do to improve her team.

Person 5: Senior Manager of Sales

“OMG, that’s amazing! Only 16% – I thought for sure our turnover rate would be in the 40s or something. We have been hemorrhaging our sales talent, but obviously it isn’t as bad as it’s felt like it has been. We can definitely use this number as a point of strength in our sales materials – that low of turnover is completely unheard of in our industry. Amazing – I can’t wait to share the great news!”

Sales was stoked. The problem though, it was absolutely not reflective of their organization. Their turnover rate was closer to the 40s/50s – so sharing that number in their new sales materials can be construed as misleading or even, perhaps, unethical. This senior manager was beyond ecstatic with this number – a far cry from some other leader’s concerns and questions.

What Needs to Happen

The above five people are just a snapshot of the reactions by leaders across the organization. As you can see, but just sharing numbers, you are leaving so much up to interpretation and misunderstanding.

And more importantly, you’re not able to get your own point – the facts behind the data – across to your colleagues, making the metric not useful.

When you tell the story behind the metric and highlight exactly what needs to happen, change, the highlight of why you’re sharing the metric, how it connects with the company’s annual goals, the business’s bottom line and so on – only then, does the metric deliver any real value.

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