Stock performance following the 2016 presidential election has been strong throughout the S&P 1500. Yet financial results have recorded low single-digit growth and less than stellar cash flow (see Figure 1 for a summary of financial performance last year: for more details see “Year-end 2016 pay-for-performance update for the S&P 1500: wrapping up 2016,” Executive Pay Matters, March 24, 2017). In this update, we’ll examine how these performance results impacted 2016 incentive/bonus payouts as well as long term incentive plan (LTIP) outcomes based on proxy statement disclosures filed this spring.
Figure 1. Recap of 2016 S&P 1500 scorecard
The median payout for S&P 1500 CEOs (with the same incumbent year over year) was 109% of target for 2016 performance, compared to 105% of target last year when summary financial results were similar. Of the 650 CEOs in our sample, 49% earned above the target range (more than 110% of target) payouts for 2016. This contrasts to only 31% earning below the target range (90% or less). Figure 2 compares the distribution of bonus payments for 2016 versus 2015.
Figure 2. Distribution of CEO bonus payouts in the S&P 1500
The full distribution of bonuses for 2016 was substantially in line with last year. But there’s more to this than meets the eye. If we look at how individual company payouts changed from 2015 to 2016, we see there is more volatility than Figure 2 suggests.
- Only 29% of companies stayed in the same payout range in 2016
- Nearly half (49%) moved (up or down) by one or two ranges
- 22% moved substantially (up or down) by three or more ranges
The fact that over 70% of the payouts changed materially suggests that the pay-for-performance model is working, as we would expect to see payouts fluctuating annually with differing performance.
For the first time in our pay-for-performance blogs we’ve captured long-term incentive plan payouts for the awards that ended in 2016. Figure 3 shows LTIP payouts ending in 2016 with and without the impact of the stock price over the performance period (typically three years).
Figure 3. LTIP payouts ending in 2016 as a percent of target
Without consideration for the impact of stock price there is a bell-shaped payout curve, and the distribution is similar to that for annual bonus payouts. The median LTIP payout was 101% of target, and 42% of companies paid out above target (more than 110%). But when we take into account stock price changes, more than half of the results are at the extremes; “winners” win bigger, and those below target fall further, and there is a smaller frequency of payouts in the target range.
Calibrating incentive plan goals, especially over multiple years, can be challenging for most companies. A rising U.S. currency, political changes, and increasing labor costs all contribute to a level of uncertainty, complicating goal-setting even further. The risk in setting soft goals is the potential compensation windfall that could lead to a pay-for-performance disconnect and a troublesome say-on-pay vote. On the other hand, the risk of setting goals that are too challenging is that plan participants disengage and contemplate leaving if low or no payouts persist.
In response to market demand for better tools to calibrate incentive plan goals, Willis Towers Watson has developed a proprietary predictive analytics model that aids the goal-setting process. Our Predictive Performance Model (PPM) simulates future financial and stock performance, using consensus investment analysts’ estimates, to shed light on the likelihood of goal achievement and the corresponding payouts in annual and long-term incentive plans. PPM has been instrumental in helping companies determine the proper range around target goals by financial measure. To learn more about our model, follow the link here.
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Ryan Lucki is an executive compensation consultant in Willis Towers Watson’s Pittsburgh office. Chris Kozlowski an executive compensation consultant in the company’s Pittsburgh office. Steve Kline, CFA, is a director in the Pittsburgh office who leads Willis Towers Watson’s efforts to develop innovative approaches to pay-for-performance measurement and analysis. Email firstname.lastname@example.org, email@example.com, firstname.lastname@example.org or email@example.com.