I had yet another call last week with a brilliant data scientist working inside of a Human Resources Department of a major business. This HR data scientist has both a strong analytics and predictive analytics background. She has a Bachelor’s degree in statistics and a Master’s degree in predictive analytics. She excels in R, math, predictive modeling, machine learning, and all things quantitative. She is also excited about applying data science from other domains, to solve interesting workforce optimization challenges.
She applied for a quantitative HR role that promised to let her use her skills and interest in solving difficult employee-based challenges. She was hired for this role. What’s the problem you ask? HR won’t let her do data science.
Over and over again she has suggested a data science approach to help solve employee-focused challenges that have plagued the organization for years, and have cost many millions to the organization’s bottom line. Over and over again she is denied the ability to move forward.
Her comment is that HR seems to be scared or hesitant in moving forward to a new way of solving solutions. The real concern is that the “reason” was not fully discussed so she could learn.
Instead, she is asked to work on generating monthly or weekly reports that the organization has grown addicted to. When she is allowed to solve an interesting problem using analytics, and brilliantly does so, the executive HR leadership won’t give it executive visibility or implement it in production. Results are found “interesting” but not deployed. Then she’s back to generating reports.
She isn’t alone. And this blog post isn’t about one unique HR data scientist. Not by a long shot. I hear this all the time — thus this post. As a result, I also see brilliant HR data scientists jumping from one company to another. I can see it on LinkedIn updates, and I hear it in the conversations I have with them about why they left and their angst before they leave.
My plea to HR (and to any other department hiring a data scientist)? Stop hiring real data scientists until you’re ready to do real data science.
I think I understand some of the problem. Perhaps the pressure on HR to begin using an analytical approach has led them to hire data scientists, but when it comes to actually using this approach it’s too foreign or scary or “not what we’ve done before.” HR needs to learn from these brilliant people they’re bringing into their domain or stop hiring them to begin with.
In the words of the data scientist I spoke with last week: “Anyone can hire a data scientist. Not every HR department or organization is ready for data science. Generating reports are not analytics — even if they’re prettier or faster reports. Dashboards are not analytics — even if they’re really pretty dashboards. More than anyone, HR should understand the devastating impact of changing job description on someone that’s been hired.”
Ironically, that data scientist hire is perhaps one of the most brilliant and strategic hires that HR department has ever made — perhaps ever. But only if they let her do what she was hired to do. HR data scientists can help move HR from being tactical to strategic, using an analytics approach to highlight never seen before patterns, make decisions based on data, and the like.
Tips on letting that brilliant HR data scientist you hired be one of your most brilliant hires:
1. Assign reporting to someone else. It’s a very important task, but it doesn’t require a data scientist. Reporting will quickly bore them to tears and they’ll resign.
2. Don’t block them from talking directly to your business areas. I often hear they have to go through the HR Business Partner who protects the business leader and blocks them from access. Working with the HR Business Partner of course makes sense. Being blocked by the HR Business Partner doesn’t.
3. Task HR Business Partners with finding either high turnover roles or low performance roles that your data scientist can work to help with.
4. Have them focus first on solving business challenges (like Financial Advisor turnover) not HR challenges like compliance issues. This will give visibility to the great work they do and introduce HR’s new expertise to solving business challenges that affect the bottom line.
5. When they complete an analytics project, give them a chance to talk and present the results, regardless of the outcomes. Did it help or not help? Don’t keep the results inside of HR.
6. Admit that you’re a little nervous about what they do. They’re nervous about what you do too.
7. Trust your data scientist. Stop being scared. You hired them because they have an area of expertise traditional HR doesn’t. Embrace their area of expertise. You need to trust their advice and approach, or, yes, they’ll leave.
And mostly, don’t hire a data scientist if you’re not ready for data science. If you thought you were and you find out later you really aren’t, let them know and let them go. Be honest. Don’t put them in a different role and block them as they keep trying to be successful.