Q&A: Janine Truitt on Talent Analytics and the Future of Data in HR

Q&A: Janine Truitt on Talent Analytics and the Future of Data in HR

Mike Roberts

From time to time, the Data Driven Recruiter asks pressing questions to the recruitment industry’s leading voices. Up today? Janine Truitt, Chief Innovations Officer at Talent Think Innovations.

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1. What does “big data” mean to you (and should recruiters believe the hype)?

The name “big data” makes it sound so out-of-reach and scary. For me, big data is the use of complex subsets of information and using them to derive business intelligence that can be used to monitor and forecast human behavior and business outcomes.

Should recruiters believe the hype? My answer is “yes” and “no.” On the one hand, there is an opportunity for recruiters to have better insight and direction for their work with the use of analytics. Using analytics can make them a more valuable partner not only to line management, but to upper management as they have the increased capability of extrapolating key insights from data that can inform decisions about how the business attracts, develops, and retains talent.

Additionally, if you examine what’s going on in the federal contractor space, being well-versed in the use of analytics could be a game-changing driver for your hiring process. The recent mandate of more stringent requirements by the OFCCP regarding contractors’ duty to prove the ROI of their referral sources makes big data a necessity in that space.

Conversely, there is a perception that businesses will somehow fail and recruiters will fail if they haven’t started using data in their work to date. I disagree with the approach of using big data as another HR doom and gloom tactic. Any new tool, method, or concept is an opportunity to be disruptive and do something different at best. I believe in businesses looking at things like “big data” in the context of their business and doing what works for them. I’m not saying businesses shouldn’t use it, but I am suggesting that HR’s shift to being data-driven will not happen overnight.

In addition, we will not achieve adoption and competence by promoting big data as a larger-than-life-concept.

2. What are some of the most common myths or misconceptions about analytics that recruiting and HR pros need to know?

The interesting problem with data is that it tells a story. If we know better, we have to do better. Data forces us to look at our companies, processes, and people. Good, bad, or indifferent we have to take an action. Companies and HR have done well to shy away from proactive data analysis so they don’t have to face their imperfections and ultimately fix them.

Moreover, there is good data and bad data; good analysis and bad analysis. Sometimes there is no story or the story the data is telling needs some further evaluation. Before we can become data-driven, we have to first be sure to use the data responsibly. It’s up to us to train our people to extract, synthesize, analyze, and sensibly utilize data for the optimization of our businesses.

Now is the time to look at those broken processes and finally get to the root of why things aren’t progressing as they should. It’s the time to know if your hiring process is applicant-friendly or a black hole. With data, the time is now to be accountable for business outcomes because we have the opportunity to understand how our processes and procedures affect them.

3. What are some of the greatest opportunities or outcomes employers should focus on in terms of utilizing data or analytics? Any advice for getting started?

Start small. Choose one critical focus area and look at the data you have available to you.

Ask yourself the following:

  • What is the reason this data is important to your business?
  • How will it help you modify or change what you do currently?
  • If you don’t have a specific, actionable purpose for this data–why bother?

If you don’t have much legacy data, plan to collect more going forward, so you can begin to analyze it and later utilize it to start forecasting and modeling. If you have been compiling legacy data and haven’t looked at it recently, then dust it off start to make some sense of it.

If you must choose, start with Talent Acquisition. If there are issues or concerns to be addressed in your process it pays to begin there. From a recruitment standpoint, you can start looking at analytics like: Recruitment Source to Quality of Hire correlations, New Hire Performance Rating Ratios, Recruitment Source to High Potential Ratio, New Hire to Internal Employee Pay Ratio, Time to Start factors, New Hire Productivity Ratio and/or factors, etc.

I’d even suggest looking at Recruiter Engagement Factors. How effective can a recruiter be if there are variables preventing them from remaining engaged? I’d like to think happy recruiters make for happy candidates.

Hopefully, the outcomes are productivity being maintained or increased, employees feeling like they had a valuable experience from hire through on-boarding and beyond. And lastly that internal customers feel they were serviced adequately.

Nothing else in the remainder of the talent management process matters, if we can’t get people through the door. Focusing on metrics that evaluate the quality of your hiring and on-boarding processes will allow you to mitigate any risks and address bottlenecks in real time.

4. When you look at using analytics to improve recruiting, who’s getting it right? Any specific examples you can share (personal or otherwise) as an example of someone who personifies a “data-driven recruiter?” 

I wish I could say I know a data-driven recruiter, but I don’t. I don’t know that we’ll see anyone “getting it right” for some time. Whatever steps companies are taking towards becoming data-driven is a step in the right direction.

My definition of being a data-driven recruiter means: using data to not only quality check your processes, but to hold yourself accountable for quality outcomes.

Hopefully, as we all evolve on our journey to being data-driven, we can continue to share our attempts so we all can benefit as a discipline collectively.

5. In short, why are analytics important? Give us your best elevator pitch.

Business is complex and HR is expected to greet these new organizational challenges with empirically-based solutions. Analytics is HR’s assurance that we are doing our due diligence any time we make a decision or hand off a suggestion to our internal partners that affect the workforce.

Follow Janine on Twitter and check out her site here.

Like reading about big data and the role of analytics in recruiting? Sign up for the Data-Driven Recruiter’s Newsletter here.

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