> Of course, the appearance of the situation, in the eyes of employees and the public, is not being helped by the fact amid IBM’s actions comes the board’s announcement on Friday of a big raise for CEO Ginni Rometty.
"The company has posted lower revenue for 11 quarters in a row."
She gets a raise for successfully shrinking the company?
If I could reduce and organisation to zarg-jelly by resigning I would extract similar geld I guess..
EDIT: yes, I used the wrong pronoun originally. The reaction... wow. No disrespect was intended, and I'd think that leeway would be given here on HN. Oh, well.
“The current study relies on a unique dataset of all CEO transitions in Fortune 500 companies over a 15-year period. We find that occupational minorities are more likely than white men to be promoted CEO of weakly performing firms; and when firm performance declines during their tenure, occupational minority CEOs are likely to be replaced by white men, a phenomenon we term the ‘savior effect.’”
http://onlinelibrary.wiley.com/doi/10.1002/smj.2161/abstract
Full copy: http://big.assets.huffingtonpost.com/glassceiling.pdf
Their evidence consists of:
1. A claim that the mean return on equity of the previous CEO of -0.68 in the "savior" case (white CEO following a minority CEO) is significantly different from a value of 0.11 in the control case (white CEO following a white CEO). This can't be true because the low number of samples implies standard errors of 0.66 and 0.05 for the means. I'm computing a z-score of 1.18, corresponding to a two-sided p-value of 0.24, far above the claimed p<0.01.
2. A claim that the mean return on equity of the previous CEO is correlated with a binary variable describing whether we are in the savior case. While their measured correlation coefficient of -0.13 would indeed be statistically significant if it were measuring a correlation of normally distributed data, the use of a binary variable describing unbalanced classes means that 95% of the variance is concentrated on just 5% of the data (28 samples). Bootstrapping based on the published mean and deviation of each class shows a 0.11 standard deviation of the correlation coefficient, and more importantly a p-value of 0.12 which is once again non-significant.
An interesting feature is that the standard deviation of the return on equity differs a lot between classes. I assume that this is because the returns on equity are far from being normally distributed, and indeed data from another class with just 4 samples shows an abnormally low standard deviation, letting us reject the normal distribution hypothesis with p<0.001. Most returns are very close to zero, so necessarily some are much greater than the standard deviation. A few or even just one large-magnitude return in the 28 "savior" samples would suffice to create a spurious correlation.
I would contact the authors about it, but I would like someone here to confirm if my analysis makes any sense.
She'll do the dirty work, get paid VERY WELL for it, so the firm itself can save face. She'll leave next year with a few mill in her pocket. AND IBM will blame their woes on "her" plan.
If you care about your employees, you don't let random people have a say in how your company is run for their own profit.
I guess I better start buying Charmin. The $0.37 of savings totally isn't worth that! I mean, who could possibly have a clear conscience about leaving thousands of people in the lurch over a little bit of money?