Should We Use Stack Ranking to Evaluate Staff Members?

Mike Donoghue is a member of a multinational information technology corporation where he collaborates on the communications guidelines and customer relationship strategies affecting the interactions with internal and external clients. He has analyzed, defined, designed and overseen processes for various engagements including product usability and customer satisfaction, best practice enterprise standardization, relationship/branding structures, and distribution effectiveness and direction. He has also established corporate library solutions to provide frameworks for sales, marketing, training, and support divisions.

  Career Development   Talent Management  

In a time when the economy is still struggling to get back to a more profitable stance--and workers and companies alike are trying to rebuild relationships that ensure mutual profitability--it’s unfortunate to hear that some tech firms are using a sort of Darwinian method to evaluate their personnel. Each is not actually a “survival of the fittest” scenario, where through a skewed version of the process known as natural selection the less desirable employees are weeded out of the workforce; but there are some similarities.

Referred to as “stack ranking” and sometimes as “rank and yank”, this employee-evaluation process is one where performance segments get created within an organization--ultimately leaving one group of individuals on the bottom that get terminated.

In a broad-stroked overview, you could say that it is a collaborative attempt where associates have the ability to rate each other’s performance with the understanding that 10% of the staff would be guaranteed to get a bad review--or one bad enough to warrant their termination. The theory behind the practice is that it would remove the “bottom feeders”--those less productive on a regular basis. Basically, for every 10 people hired in a unit, one of them would have to go--regardless of their skill and talent.

Some firms employ the technique as …

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