Our last pay-for-performance update for the S&P 1500 noted that the year-to-date performance trend was ahead of 2016. But performance trailed the investment analysts’ expectations slightly in a few key metrics. (For more details of our last analysis, see “Pay-for-performance update for the S&P 1500: a strong first half,” Executive Pay Matters, October 5, 2017.

Figure 1 shows results through the third quarter extended the trend. Virtually all performance measures are up or at least flat versus 2016, and the stock market is up markedly. When we looked at the constituents of the 1500 by market capitalization, we observed that revenue growth is strong across large, mid- and small-cap companies. But earnings before interest and taxes (EBIT) growth is notably weaker among the small-cap companies.

Figure 1. S&P 1500 scorecard

Figure 1. S&P 1500 scorecard

Figure 2 shows notable earnings growth in 2017 across the various economic sectors. Most sectors have improved materially in 2017. The top three are the materials, consumer discretionary and technology sectors. Only two sectors are trailing 2016 performance: health care and consumer staples.

Figure 2. S&P 1500 EBIT growth by sector

Figure 2. S&P 1500 EBIT growth by sector

Earlier this year, we reported that bonus payouts for 2016 performance increased from 2015 and trended above target. For more details, see “Pay-for-performance update for the S&P 1500: 2016 pay outcomes,” Executive Pay Matters, June 27, 2017.

On the surface, year-to-date results could indicate an even stronger year for annual incentive plan payouts. But if we go back to the beginning of 2017, we see that expectations for the year were high and, in most cases, higher than the trajectory of year-to-date results. Assuming incentive plan goals were set at or near the robust analysts’ expectations at the start of 2017, many plans could be tracking at or below target. So despite the ostensibly strong results through the first three quarters, bonuses could be less robust than suggested by the trend from 2016 to 2017, because expectations were so high when goals were set.

The stock market continues to hit new highs in 2017. Interestingly, in 2017 we observed a strong positive correlation between the strong EBIT growth results and TSR. Figure 3 shows that the majority of sectors in 2017 outperformed the shareholder returns generated in 2016. Through November, the S&P 1500 as a whole was up 20% compared to 11% over the prior period.

Figure 3. S&P 1500 TSR through November 30 by sector

Figure 3. S&P 1500 TSR through November 30 by sector

Looking ahead to 2018, Figure 4 shows that analysts’ earnings estimates are strong, and, in all cases, exceed 2017 growth results through the first three quarters. Earnings growth in 2018 by sector is expected to outperform 2017 by about six percentage points on average. And seven of the nine sectors expect EBIT growth in 2018 in excess of 10%. This suggests companies will be under unusual pressure to set aggressive incentive plans goals for 2018 in order to sustain their lofty stock valuations and shareholder returns.

Figure 4. S&P 1500 estimated 2018 EBIT growth vs. 2017 

Figure 4. S&P 1500 estimated 2018 EBIT growth vs. 2017

Setting aggressive goals in a booming economy is never an easy task. Robust expectations for 2018 present a real Goldilocks moment for incentive plan goal setting:

Now more than ever, it makes sense to consider how predictive analytics can aid in the calibration of challenging incentive plan goals. Using a quantitative method to establish financial performance targets and ranges (built from a combination of historical actual results, future analyst expectations and tempered with management plans), will build greater confidence in the ability to predict the future. In our work with clients, we find the following steps critical to ensure that incentive design, and goals and payouts in particular, are just right:

  1. Understand past biases around performance and pay, on a relative and absolute basis.
  2. Test the relative alignment of pay with performance.
  3. Benchmark incentive design, but choose metrics that are meaningful to your company, and customize the weightings based on the business context.
  4. Set target goals informed by prior steps (past, market, and plan).
  5. Use predictive analytics to customize the ranges around target goals and target payouts.
  6. Repeat next year.

Learn more about Willis Towers Watson’s predictive analytics tools here.


ABOUT THE AUTHORS

Ryan Lucki 

Ryan Lucki

Willis Towers Watson
Pittsburgh

Mike Biggane 

Mike Biggane

Willis Towers Watson
Cincinnati

Steve Kline 

Steve Kline

Willis Towers Watson
Pittsburgh


Ryan Lucki is an executive compensation consultant in Willis Towers Watson’s Pittsburgh office. Mike Biggane is an executive compensation consultant in Willis Towers Watson’s Cincinnati office. Steve Kline, CFA, is a director in Willis Towers Watson’s Pittsburgh office who leads the company’s efforts to develop innovative approaches to pay-for-performance measurement and analysis. Email ryan.lucki@willistowerswatson.com, michael.biggane@willistowerswatson.com, steve.kline@willistowerswatson.com or executive.pay.matters@willistowerswatson.com.