As Yahoo’s business evolves into whatever it will become, the stories of Q.P.R. (quarterly performance reviews), stack rankings and mismanagement become the social fad of the day (unless your BusinessInsider.com, with a reporting obsession with all things Yahoo and Marissa Mayer).
It’s also an example of Data making people feel small while a company got smaller – in one sense it’s the painful business that has to be done…still, is this the best we can do?
In a time where reviewing your performance reviews is common, the emerging Yahoo story also gives a glimpse into the links (and resulting dependencies) between performance and compensation – how we manage people and pay them without making them feel like data.
The performance reviews caused people to lose jobs and compensation; whether this was intentional or part of a layoff plan is for the courts to figure out.
From a compensation point of view, Yahoo’s scenario is about much more than the review system.
It’s about how we use data as businesses to manage, and pay, people the right way – without creating sinkholes that suck down confused and angry employees leaving or worst, who sometimes stay and begin playing “survival of the fittest” games.
After the review, people get paid. If it’s in your good interest to not help another employee, you don’t help. Not just because of the performance review, because of the compensation.
1. Compensation costs stack up.
Yahoo has many employees. Stack rankings like Yahoo used are also called forced rankings – because they force the choice. Someone has to be at the one who misses, and it’s obvious for a company at Yahoo’s stage, at best that meant getting paid less for the employee.
People leave slowly. Stack ranking has managers place their employees into “buckets”: 10% in “greatly exceeds,” 25% in “exceeds,” 50% in “achieves,” 10% in “occasionally misses,” and 5% in “misses.”
This manager was left with choosing one of 2 good alternatives and sent this critical feedback from an invitation by Mayer to the company at a 2013 meeting:
“I was forced to give an employee an occasionally misses, [and] was very uncomfortable with it. Now I have to have a discussion about it when I have my QPR meetings. I feel so uncomfortable because in order to meet the bell curve, I have to tell the employee that they missed when I truly don’t believe it to be the case. I understand we want to weed out mis-hires/people not meeting their goals, but this practice is concerning. I don’t want to lose the person mentally. How do we justify?” October 2013 Yahoo Meeting
She never got an answer, or perhaps the lack of the answer is the answer. Lots of people got lost, mentally and financially, at Yahoo.
2. The performance reviews and the resulting compensation mix creates the culture here; we can all learn (and many have been there) when actions create a culture of negative interest – the zero sum game no business wants to create.
Did their performance review justify their compensation? In at least one case every time, the answer would be no.
If as alleged, data is used to reduce a company’s size without notifying employees of pending layoffs ahead of time as required by law, that’s a huge violation and one that is difficult to prove.
The fact is this data, based on stack rankings, caused people to lose their jobs or leave. That’s what it has done for years. It doesn’t have to, but it’s a good tool to do it.
Employees become competitors on the same team, and less a company. For a company at Yahoo’s stage, it wasn’t a question of people losing jobs, it was when. While brutal, the Q.P.R. did the weeding.
3. Which comes back to the issue, for a compensation software company like us.
Resolving the data issues between performance review data and compensation data are part of what we do every day.
What makes this important to virtually every business, big or small, are the negative effects of a poorly planned and executed performance review. It doesn’t have to contain the absolutes of the Yahoo story to cause pain.
Balancing the performance review and compensation involves more than data if you want to grow a company.
- Yahoo’s situation was not good when Marissa Mayer came on, so some of these changes are part of a business evolving from a leader to either a smaller player, or many smaller parts, or being swallowed up and acquired. By design the Q.P.R. would have to make the company smaller; Yahoo is/was too big.
- Part of Mayer’s job coming in was to reduce the workforce and the compensation costs; stack rankings come from an earlier age that culled by making absolute choices when needed.
- Data did the culling, programmatic in a way. If you have to reduce your workforce by 5%, the easiest way to evaluate who? Stack rankings that give you the 5% who miss. The cold math and business vision is never clearer then when things get small – numbers are used to prove a point.
Imagine if we could create ways and compensation plans to model ways compensation data can grow a business, as easy as it is to use to make a business smaller?
That’s what a good compensation plan is all about, and part of what we’re working on here.