Lately many pages on the internet, including Exabyzness, have covered the recent growing trend among human resources and management departments to abandon the classical year-end review. The reasoning was that the annual review basically lets too much time pass between seriously sitting down with employees and telling them where they need improvement. This is not to suggest that every employee needs improvement but for those who do waiting a year to inform them can be costly. With more frequent reviews, the employee can start correcting the errors in their ways possibly leading to higher productivity and lower costs. Further, giving critiques sooner allows management to find out much quicker if the employee is even capable of making the needed changes. After this reasoning one wonder why we ever did only annual performance reviews in the first place. Well to argue the other side, Paul Hebert of FoT asked this question and came to the belief that the annual reviews are still better than the new proposed trend sweeping the internet. His main argument consists of what he calls “signal vs. noise”. Basically he argues that constant real-time reviewing of your employees’ performance is easy with technology and provides lots and lots of data but the quality of the data diminishes as the timescale shrinks. This data is more attributable to statistical noise than real information that sheds light on the employee’s work ethic and potential. Paul continues, “There is a big difference between information and data.  Data is what it is.  There is no real value in data.  Data becomes valuable when it becomes information.  The problem is you never know when that happens.  Data is noise.  Information is signal.

I direct you to an article on the blog Elezea posted back in May about being careful who you listen to.  In that post the author brings in some information from Nassim Taleb (The Black Swan, Fooled by Randomness – two MUST reads btw.)  The post references information from a post on Taleb’s new book (Antifragile: Things That Gain from Disorder.)  Paraphrased and edited from that post: The more frequently you look at data, the more noise you are disproportionally likely to get (rather than the valuable part called the signal); hence the higher the noise to signal ratio. Say you look at information on a yearly basis, for stock prices or the fertilizer sales of your father-in-law’s factory, or inflation numbers in Vladivostock. Assume further that for what you are observing, at the yearly frequency the ratio of signal to noise is about one to one (say half noise, half signal) it means that about half of changes are real improvements or degradations, the other half comes from randomness…”

Click on the link below to see the rest of the very long defense of the annual performance review.