Outperform Slopes in a Relative TSR Plan
Performance shares earned contingent on a performance metric of Relative Total Shareholder Return (“RTSR”) is the most prevalent globally as seen in the marketplace. There are several forms in which a Relative TSR plan can be designed (for example, a percentile rank plan or an outperform plan), as seen in the Alternative Types of RTSR Plan. The most prevalent type of plan is a Percentile Rank style plan. However, one of the more compelling types of plan is an “Outperform” Plan, in which the earnout is determined as the magnitude that a company’s TSR compares against a benchmark TSR (could be an Index or the median of a peer group).
Example: Company X grants performance stock units that are earned based on relative TSR over the three-year period following the grant date. The payout is determined as a Component Outperform Plan against the members of the S&P 500, with an additional 3% vesting for each 1% that the company TSR exceeds the RTSR benchmark (the median TSR of the companies in the Index).
|△ Between TSR and Benchmark TSR||Payout Percentage|
|>=33.3% (+3300 bp)||200%|
|For each +1% (+100 bp)||103% (an additional 3%)|
|RTSR Benchmark (Delta from TSR of Median of S&P 500)||100%|
|For each -1% (-100 bp)||97% (less 3%)|
|<-33.3% (-3300 bp)||0%|
As discussed, there are benefits of each type of plan, but this approach better replicates the return an investor would yield as smaller changes in TSR would not create large changes in earnout. However, in selecting to use an “Outperform” plan, one of the important considerations is the methodology for determining the additional incremental vesting for excess RTSR (or lesser vesting when underperforming the benchmark), which in the example above is 3%.
Mathematics for Reverse-Engineering Slope of an Outperform Plan
Percentile rank plans are more common in the marketplace, and more intuitive to understand what the risk of forfeiture is (for example, when Threshold is set at the 25th Percentile, then the risk of forfeiture can broadly be anticipated to be 25%).
Through historical back-testing of TSR performance, the slope can be reverse engineered based upon empirical data. Typically, a company would study historical data for its peer group over the last 10 hypothetical 3-year performance periods. To illustrate this, let’s define the following data points based on 10 overlapping 3-year performance periods. The company is trying to define the slope between Threshold (50% earnout at the 25th Percentile) to Target (100% earnout at the 50th Percentile) and Target to Maximum (200% earnout at the 75th Percentile):
For outperformance against the benchmark, the slope can be determined as:
Similarly (under)performance against the benchmark, the slope can be determined as:
Alternatively, the entire slope can be determined from Threshold to Maximum can be determined in a single calculation:
This allows for a single slope on the upside and the downside.
In our experience designing and administering “outperform” style plans, we have compiled the following considerations:
- More volatile securities should have a smaller slope. Since more volatility means that a company is more likely to significantly exceed or underperform, it is important to have a lower slope so that earnouts don’t frequently end up in the extreme. Similarly, less volatile securities should have higher slopes.
- We generally recommend that the slope be the same on both the upside and the downside. For example, a TSR in Cycle 1 of 100 basis points (1%) in excess of the benchmark TSR, then followed by a TSR in Cycle 2 of 100 basis points (-1%) under the benchmark TSR, should ultimately yield an earnout at target. There shouldn’t be incentives for excess risk, and individuals should be equally rewarded for overperformance as they are punished for underperformance.
companies that would be a best fit for Outperform style plans are the
- Companies that are using Multi-Sector Indices (i.e. S&P 500 or the Russell 2000), which can help them align with investor results
- Very small homogenous industries that have clustered TSRs. This ensures that small changes in TSR don’t have significant changes in earnout.