What Historical Data Can Tell You About Retention Risk

I was recently talking to a client when I heard them say something that brought me back to my corporate days.  They asked, “We are about to lose one of our best employees to a competitor and we need to offer a retention bonus; how much should that be?” I heard this question countless times in those days. Of course, each time I heard it my response was to look for survey data, understand whether that amount would be enough to keep them and what restrictions (if any) I would put on the bonus.  This all seemed pretty reasonable to me until I saw how regularly I was approached with these types of requests.

I’ll never forget one situation in particular.  My colleague, who was an HR Business Unit Lead, told me about the most recent candidate who we had to pay a retention bonus.  However, I knew the target of the bonus and something didn’t seem right.  This person was there just under 4 years (our full pension vesting was 5 years), they had a significant amount of unvested equity that was going to vest over the next 3 years, this person was above market by ~15% (near the top of their grade) and had a Manager who was widely regarded as an incredible leader and targeted for a leadership role in the company.  I asked myself, “Is this person really going to leave the company?”  I’m a pretty rational guy and I know I wouldn’t leave.  I decided to review the characteristics of those employees who previously left the company voluntarily – asking whether there were any common characteristics and whether that would be a window into the retention risk of our current population.  My assumption was that if we could understand the characteristics of people that left, that would help us retain those employees who are still here.

So, I started to turn over the data of those people who left voluntarily and there were some very interesting statistical trends against the following factors:

• Fully vested in our pension plan
• Below market salary (or low Compa-Ratio)
• Little unvested equity
• Direct manager who had consistently lower performance ratings
• Worked in a business unit (or function) that had recently been re-organized or downsized

Given these trends, I quantified and weighted those factors and established a 'score' that was:

• Statistically-based
• Based on our employee data (vs. normative data from outside of our business)
• Rank ordered so we could identify those employees who had more characteristics of our voluntary terminations (so we could rank their situation against others)

This worked out very well.  I started to use this scaling in all my conversations with the businesses and functions.  We weren’t so hard and fast that we said, “this person has a score of X, so they aren’t eligible for a retention bonus.”  Instead, we used it to set context around such activities as merit increases, share grants, developmental opportunities, training and yes – retention bonuses.   Our Retention Risk Score gave us a window into each employee’s rewards and better align their rewards in the proper context. Through data analysis we found a pretty impactful exercise!

If you’d like help discussing how reviewing your historical data can tell you about your retention risk or have any other compensation challenges, schedule a free 30-minute consultation with one of our experts.