Confessions of a Hiring Manager: Why It's Hard to Care about Talent Analytics

Posted by Chris Daniels on Jun 10, 2016 5:24:00 PM
Chris Daniels
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Talent analytics is the process of using employee-related data to improve business outcomes in Human Resources. In 2016, Deloitte University Press issued a report that found companies are aggressively building people analytics teams. 8 percent of the surveyed executives agreed that they are “fully capable of developing predictive models,” up from just 4 percent in 2015. Deloitte claims we are entering the golden age of talent analytics, and HR is coming along with it.


Now, as a hiring manager, I know I am supposed to care about data, but sometimes it's hard. Here’s why. From what I’ve observed, it is challenging for many recruiters and hiring managers to listen to hard data, especially when their gut is telling them otherwise. We need a way to leverage big data while staying aware of the real benefits it can provide. Here is how HR professionals came to an agreement regarding big data.

Embrace Only the Most Important KPIs

As managers, we care about producing solid results, and sometimes we don’t have the time to evaluate data to predict the traits of the next best hire. We simply want to have the best possible team. The solution is to not become overwhelmed with the amount of data. That's why I recommend sticking only to the most important key performance indicators;  time-time-to hire, Quality of Hire, Hiring Speed, Offer Acceptance Rate, and Candidate Satisfaction. When you nail down these metrics, you'll know exactly how long it takes to hire quality candidates and what that quality means.

Let Your End Users Determine the Metrics You’ll Measure

Many data scientists have little to no background in human resources and may wrongly provide irrelevant metrics to managers. The solution is to have your end users (in this case your HR team) determine the right metrics for every position. Pinpoint the challenges of each department, and then determine which metrics deliver the most insight into these challenges.

Train Your Staff to Use “Real” Data

It’s hard to reach goals if you don’t understand what’s being asked of you. Members of my team sometimes don’t understand company goals and departmental KPIs. Make sure every team member understands what's being asked of them. Managers often don’t have the time to set the goals and explain them to the team members, but investing effort in this matter is worthwhile. Why? Because it brings clarity to your decision-making process and makes it easier to reach the goals.

Change What You Can, Leave the Rest for Later

Some things are hard to change, and therefore are difficult to measure. The solution is to focus on things you can change. Begin with the KPIs and goals most crucial to your business and enact small, measurable changes instead of large, broad programs. 

Be In It For The Long Haul

It’s hard to predict changes. One article estimates that “predictive insight requires at least 24 months of data”. The solution is to look for trends that will help you determine when the change takes place for the first time. It’s important to have a repository of historical data so that the changes you predic­­t with people analytics are valid.

The main purpose of utilizing data is to simplify hiring decisions based on the information obtained about the existing candidates and the hiring process itself. Like many passing business trends, talent analytics claims to be the Holy Grail in regards to creating usability and forecasting value. Unfortunately, if not used correctly, much of the data we gather cannot be used properly. By following these steps you'll come closer to maximizing your data platforms, and will be able to use data that enacts real change. 

Learn more about useful HR metrics by downloading our free ebook, The Ultimate Guide to Talent Analytics.

download 10 metrics for talent acquisition guide

Topics: hiring, big data software, data analytics in hr

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