I don’t write about my work life on this blog. I have a blog about my work (which is actually school) just for that. But this post started with an article about work that I read in The Wall Street Journal. and moved in an interesting way. Here’s how that article opened:
Concerned a brain drain could hurt its long-term ability to compete, Google Inc. is tackling the problem with its typical tool: an algorithm.
The Internet search giant recently began crunching data from employee reviews and promotion and pay histories in a mathematical formula Google says can identify which of its 20,000 employees are most likely to quit.
Google officials are reluctant to share details of the formula, which is still being tested. The inputs include information from surveys and peer reviews, and Google says the algorithm already has identified employees who felt underused, a key complaint among those who contemplate leaving.
Wow. An algorithim to determine if employees are dissatisfied with their jobs. This from a company that I thought was the place everyone wanted to be. Apparently, Google is no longer the best or only place for tech types and future entrepreneurs to learn. New kids like Twitter and Facebook and getting Google people to come on board.
Can you really pull together a bunch of data and tell whether I am happy or not in my work? Will stats more accurately reveal how I feel than sitting down and talking to me? True, I may not want to say to my boss that I am unhappy. So, could you pull it out of my sick days, performance reports and such?
My last two jobs were big on performance reviews. Personal improvement plans. Merit pay.
The got some of it from the idea of “forced ranking.” Lots of pages of qualities and It’s almost like a kinder, gentler version of the “forced ranking.” It’s pretty harsh. It encourages companies to fire the bottom 10 percent of their employees to get rid of the malcontents. Companies may call it a “talent management process” or “leadership assessment procedure” instead of forced ranking.
Identify your best employees, shock others out of complacency, reduce favoritism. Take your top performers and reward, keep, and train them to be your new leaders of the business.
Fans of forced ranking say that 40% of your “C” players will voluntarily resign.
Wait. What about the happiness algorithm?
I did some web searching and, as is often the case these days, my ideas are not original. People have thought about a happiness algorithm. Psychologist Barbara Frederickson wrote a book called (one of those simple titles with a colon and a long explanation that academics love) Positivity: Groundbreaking Research Reveals How to Embrace the Hidden Strength of Positive Emotions, Overcome Negativity, and Thrive.
Turns out her theories have been mixed in with those of others, like Marcial Losada who looks at high-performing teams in business and says: “…high-performing teams had about a six-to-one ratio of positive to negative statements, whereas the low-performing teams had ratios of less than one to one, meaning that more than half of what was said was negative.”
Losada is into mathematical modeling – data from observations of business teams, algebraic equations.
Now, here is where the connections turned around on me. He finds that his equations matched the Lorenz system – that chaos theory and “butterfly effect” that I just wrote about last week. Spooky action at a distance. Positivity creates positivity. What Fredeickson calls a “complex chaotic attractor.”
Those high-performing teams produce novel creative results. A ratio of three positive events to one negative event is the tipping point where good chaos begins.
Try doing or saying or just thinking three positive things for every negative one. A very simple algorithm for happiness.
