“Realizable Pay” Could Be Making a Comeback – But The Devil’s In The Details
Disclosure of “realizable pay” seems to be less prevalent these days than it was when say-on-pay first hit the scene. But as I wrote a few months ago, ISS is considering making it a more prominent part of its pay-for-performance analysis – and CalPERS has already taken that step. And a recent WSJ article has me wondering whether it will get revived as a talking point by the many people who want to reign in executive pay. Here’s an excerpt:
The Wall Street Journal compared what S&P 500 companies reported paying their CEOs over three years with a measure of what that pay was worth at the end of the period, called realizable pay, using data from ISS Analytics, the data intelligence arm of proxy adviser Institutional Shareholder Services. (For more information, see the methodology note at the end of this article.)
On average, the value of the pay at the end of the period was 16% higher than originally disclosed. Pay rose at three out of five companies. And at a third of companies, pay rose by more than 25%.
That said, there was a big snafu with this article! A correction was subsequently issued to explain that the “realizable pay” at issue was miscalculated. This excerpt from an Equilar blog explains why that calculation is ripe for confusion:
It turns out that the change in value between reported and year-end pay was a result of differing option valuation models between the disclosed pay and realizable pay values used by the company versus the ISS model. Two commonly used models are the Black-Scholes option pricing model and the Monte Carlo simulation, both of which use a series of underlying assumptions to calculate the value an executive can expect to earn from an option grant. Changes in these assumptions can have significant impacts on the value of an option.
In the case of performance-based awards, the Monte Carlo simulation also takes performance considerations into account in order to come to a fair value based on the probable payout of the award. When more rigorous performance goals are set, a Monte Carlo simulation will produce a lower fair value.
Oracle originally determined the grant date value of Mr. Hurd’s largest option award during the evaluation period using a Monte Carlo simulation and valued the grant at $103.7 million. This is the disclosed value that was used in the study. Because a Monte Carlo simulation was used, it factored in the likelihood of achieving the rigorous performance goals placed on the option. At the end of the year, even though his options were underwater, the different option valuation model made it look like the award increased by 59.7% due to the exclusion of performance criteria. Given the decline in stock price, one would expect a realizable value lower than the disclosed value.
At a minimum, the takeaway here is that if more investors start to look at “realizable pay,” it’s worth understanding the specifics about their calculations (despite the fact that valuation models are mind-numbingly boring). Depending on your shareholder base and executive pay structure, you may need to revisit whether to get out in front of misunderstandings with conversations and/or company disclosure.
-Liz Dunshee, CompensationStandards.com October 11, 2019
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