The Advisors' Blog

I blogged a couple weeks ago about using the information disclosed under Item 402(v) – the SEC’s “pay versus performance” rule – to structure compensation programs. This paper from ISS Corporate (available for download) also extols the benefits of statistical modeling for goal setting. Here’s an excerpt:

A goal-setting approach that incorporates statistical analysis can help ensure that goals are challenging but achievable and present payout opportunities that are fair for both executives and shareholders. By modeling incentive programs at the outset with statistical assumptions such as metric growth rate, volatility, and correlations, companies can better assess potential performance and payout levels according to their probabilities of achievement.

Such quantitative analyses may consider uncertainties including looming recession fears, unintended trade war repercussions or changing dynamics from the introduction of AI. A data-driven approach to goal setting, such as using Monte Carlo simulations, can aid in developing well-designed and rigorous incentive programs that won’t create problems down the road. 

For compensation committees that aren’t already using modeling and think the “juice isn’t worth the squeeze,” the paper discusses how a data-driven approach can help avoid at least three pitfalls:

– “Softball” goals

– “Feast or famine” scenarios

– Unbalanced payouts

– Liz Dunshee