real value of people analytics

The Real Value Behind People Analytics

Having HR change to a data-driven mindset is easier said than done, most HR leaders aren’t experienced with analytics. They got into HR to deal with people, not numbers.

But being data-driven will help you make better decisions.

It’s time to stop making decisions based on gut feelings, and start using data to back up your hypotheses.

People analytics is the use of data to analyze and improve the talent in your organization.

The potential for people analytics to help your organization is huge (just wait until artificial intelligence comes into the mix), you just need to know what to look for.
Imagine if you could:

  • Increase your quality of hire by knowing what success looks like (and remove bias from the process).
  • Predict which employees are about to leave.
  • Discover what traits make a great customer service agent.
  • Analyze employee engagement levels across different teams.

People analytics makes all of this possible. HR departments are sitting on a treasure chest of data about their employees that they should start utilizing.

Analytics can easily become overwhelming, especially if you’re not used to it, we’re here to help.

In this post, you’ll see examples from companies using analytics to optimize their people processes, and simple tips for beginners to get started.

Want to dive deeper into HR Analytics? Our eBook “The Ultimate Guide To HR Analytics” will help you make your HR department more data-driven.

People Analytics Is Growing

From Deloitte’s article People Analytics Gaining Speed:

“The people analytics revolution is gaining speed. While HR organizations have been talking about building analytics teams for several years, in 2016 we see a major leap forward in capabilities. Businesses have recognized they need data to figure out what makes people join, perform well in, and stay with an organization; who will likely be successful; who will make the best leaders; and what is required to deliver the highest-quality customer service and innovation.”

Their research found that in 2015, only 24% of companies felt ready or somewhat ready for analytics, but in 2016, that number jumped to 32%.

We still have a long way to go. They found that in 2015, only 4% of companies believed they were “fully capable of developing predictive models” and that number doubled to 8 percent in 2016 (still pretty low nonetheless).

Key stats on people analytics

Deloitte issues an important warning to keep in mind when using analytics:

“However, providing great data and insights is only part of the solution. The real value is in turning these insights into change that delivers business value. The hardest part of people analytics is implementing the changes recommended by the models, which call for people analytics to be accompanied by sound change management practices.”

Companies Using People Analytics

Let’s look at a few examples of companies that are using people analytics to drive business results. Hopefully these examples inspire you.

  1. Google

    All people decisions at Google are based on data and analytics. The goal is to bring the same level of rigour to people decisions that we do to engineering decisions. – Laszlo Bock

    Naturally, we had to start with Google on the list of companies that are data-driven in their people operations department.

    This quote from Google shows that they understand the value of their most important asset – their people.

    This video with Prasad Setty, Google’s VP of People Analytics explains how they do it:

    One of their most popular initiatives is called Project Oxygen, an initiative to see if managers really matter in an organization (they do).

    Their People Team analyzed tons of internal data like employee surveys and performance reviews to find what makes a great manager.

    It identified eight characteristics of great leaders, and they now use this data to train other managers to make sure they’re all performing their best.

    It’s worth noting that frequent one-on-one coaching and frequent personalized feedback ranked as the number one thing to being a successful leader.

  2. Gap

    Clothing retailer Gap Inc, which owns brands like Banana Republic, Old Navy, and Gap, wanted to use data to compare performance within the different companies.

    Google wrote a great case study on exactly how they set up their process. It goes into detail about how they created a multi-year program to get HR to be more data-driven, through training, empowering employees, and standardizing all of their systems.

    The case study gives some great tips on which metrics they were tracking that should help you.

  3. Microsoft

    In this case study on how Microsoft uses analytics to optimize their processes, Dawn Klinghoffer, Senior Director of HR Business Insights, talks about the four-step process they use to create actionable insights out of their data:

    1. Data collection
    2. Applying definitions
    3. Analyze
    4. Take action

    “Data gets involved in pretty much every programmatic decision we make in HR. If we are going to change our performance management system, we do tons of analysis and the data really helps drive that decision. Any type of benefit changes we make we do extensive analysis. We have used data to explore whether we are paying our top performers the right amount of money. We spend a lot of time on quality of hire – the people we have hired. We examine them across a scale from a high-quality, medium quality or low-quality hire.” – Dawn Klinghoffer, Senior Director of HR Business Insights

  4. LinkedIn

    Rebecca White, Senior Manager of Talent Analytics at LinkedIn, talks about how when she first joined the team, they were growing at 40% every year and the talent acquisition team couldn’t predict the number of hires needed.

    By using analytics, Rebecca and the team were able to predict new hires so accurately, that they saved the company 15% of its recruiting budget in the first year.

Getting Started With People Analytics

Like most things in life, when you’re just starting out, you want to start small to not get too overwhelmed.

Here are four simple things you can do to get started with people analytics:

  1. Develop A Data-Driven Mindset

    Just thinking about how you could start using data is a good place to start.

    What you want to think about, is how you could make your life easier, or what value you could bring to the organization through data.

    So if you’re in recruiting, asking questions like:

    • “Are we hiring the right people?”
    • “On average, how long do our employees stay with us?”
    • “What’s our turnover rate? Is that better or worse than last year?”
  2. Pick One Metric

    Like BJ Fogg’s idea of flossing one tooth to build a habit, start by picking one metric to focus on.

    This will largely depend on your company goals, but a good place to start if you’re in HR is with employee turnover.

    Pro tip: read this post about how to calculate employee turnover.
  3. Survey Your Employees

    Surveying your employees is one of the simplest and most common ways to start collecting data about your workforce.

    Officevibe makes this process incredibly simple by automating most of the work. We automatically collect and analyze data, and then suggest improvements based on what we see.

    Survey question in Officevibe

  4. Involve Others

    Don’t be scared to ask for help.

    Chances are, you’re not the only one interested in becoming more data-driven, so involve your colleagues and learn together.

    Also, feel free to reach out to other departments, like marketing, that have been data-driven for a long time. It’s likely that they’ll be able to help you, and it will give you an opportunity to connect with others in the organization.

Want to dive deeper into HR Analytics? Our eBook “The Ultimate Guide To HR Analytics” will help you make your HR department more data-driven.

Is Your Organization Data-Driven?

If yes, then let us know how you do it in the comments below! If not, then let us know what might be holding you back.

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