Barring one semester in third grade when I was moved to the Advanced Math class due to my weird love of long division, numbers have long felt like a necessary evil in my life. Objectively, I understood their value, but when faced with spreadsheets encapsulating hundreds – if not thousands - of data points, I suffered the common ailment of “analysis paralysis.”
And through my research at HCI, I know I am not alone.
The very nature of people management is ambiguous, and yet organizations and leaders know that ambiguity does not easily lend itself to evidence-based research or decision-making. As HR practitioners, we must find ways to quantify metrics that are historically squishy and also extremely important – metrics like employee engagement, manager satisfaction, and emotional intelligence.
To be clear, there are a multitude of measures within talent management that can be more easily quantified – rates of turnover, development and training participation, rotational assignments, manager stability, etc. But the role of the HR practitioner has evolved in the past decade from reporting such metrics to digging beneath the surface of those figures and determining what they really mean to the business. What drives employee engagement? How does manager stability impact employee performance? What is the quantifiable impact of providing employees with additional training?
This is where the numbers come in.
As I worked with colleagues developing HCI’s new Analytics for Talent Management (ATM) course, I had to face this antagonist head-on. And as I took a deep breath and dove into the spreadsheets and statistics, I realized something profound. For nearly my whole life, I rebelled against numbers because I am intimidated by their perceived perfection (who hasn’t heard someone utter the phrase, “I love math because there’s always a right answer”)? But that assumption is wrong. The language of numbers is not perfect; data sets and spreadsheets are messy, sometimes they have typos and errors, and need editing and rewording. These are things I can do.
This is where the HR practitioner comes in.
With this realization, I changed my perspective. Managing data and running analyses is not a skill I am innately good at, but it is one I can learn. By applying a mindset of curiosity to these numbers, I can evolve from merely reporting figures like number of high potentials to determining what the characteristics of high potentials are in my organization. Do they share similar work experiences? Do they come from specific regions of the country? Armed with that knowledge, I can educate our Talent Acquisition function on how they might amend their practices to recruit more high potentials, resulting in a positive – and perhaps even predictable - outcome for the business.
This is the heart of analytics for talent management.
For too long, HR has functioned in siloed isolation, slowly but surely jeopardizing its ‘seat at the table’ next to other highly-regarded departments like finance and marketing (it is no small coincidence that those functions have been using evidence-based strategies for years). Data and analytics is the opportunity to valiantly change this course for HR.
I will not ever become a statistician, and I am certain I will never be part of an advanced math class again, but HCI’s new course on analytics has shown me that numbers are not the enemy. Fear of failure, incorrect assumptions, and an inability to see the value that I can create with those numbers is. Let’s fight that battle together.