The selection of appropriate incentive metrics is a critical decision for compensation committees and management teams. While a company’s business plan and strategy should be the primary factor when selecting incentive plan measures, most companies consider many other factors. This article discusses:
- The factors that companies consider when selecting incentive metrics
- A detailed discussion of one these factors – the role of correlation analysis in assessing the relationship of incentive metrics and a company’s total shareholder return
Factors that many companies consider when selecting incentive metrics
Incentives are the core element of the executive pay programme. Short- and long-term incentives, particularly the performance measures and goals, are intended to directly connect employees to the company’s business strategy. Given this criticality, it is imperative to be specific and clear in selecting and defining incentive plan performance measures. While there are many measures that are important for a company to monitor, companies typically find the best design – to maximise motivation and line of sight to drive results – limits the number of measures to less than five (the preference is often two or three measures in each plan, but practices vary by industry, business situation and other factors). In selecting performance measures, companies consider the factors detailed below.
1. Business strategy
Focussing on business strategy is the starting point for incentive measure selection. Long-range business strategies can provide basis for selecting long-term incentive goals while annual operating plans provide basis for selecting goals for annual incentive plans. The incentive metrics should relate to key measures of success as defined by the board and management team. For publicly traded companies, the metrics should align with messages provided in the company’s investor presentations and internal communication of performance. For private companies, the metrics should align with the company’s internal communication of performance.
2. Peer group and broader market practices
Reviewing peer and broader market practices helps identify which performance measures are common, including the types and mix of measures, and the overall incentive plan design structures used by other companies. While this assessment should be secondary to aligning with the company’s business strategy, it does provide information related to trends and potential ideas that companies should consider. In addition to which incentive metrics peers use, other related design information can be gathered and reviewed, including: weighting of metrics, definition of metrics, adjustments made to metrics, year-over-year changes to actual incentive goals, and performance range of actual incentive goals.
3. Analyst commentary
Identifying what areas of financial statements that key analysts are focussed on will help gauge the importance of potential types of incentive metrics and the specific measures used by directly comparable companies. This step includes understanding which specific measures are most heavily scrutinised by key analysts, particularly with companies at a similar stage in their life cycle (e.g. high-growth, repositioning, etc). Undertaking this review will ensure selected measures are reasonable relative to analysts’ areas of focus and the specific target goals are appropriate if the company provides investor guidance, recognising that metric definitions are often customised to focus on continuing operations or otherwise adjusted to ensure accountability, and guidance is often provided as a range.
4. Proxy advisory firms
For US publicly traded companies, the two leading proxy advisory firms test a company’s financial performance and total shareholder return (TSR) relative to other companies. These ‘tests’ focus on generally accepted accounting principles (GAAP) financial metrics, such as return on assets, return on equity, return on invested capital and earnings before interest, tax, depreciation and amortisation (EBITDA). The comparator groups used by the proxy advisory firms may vary from the company’s pay peer group and, if these differences our significant, it is often useful to simulate the proxy advisory firms’ likely views on pay-performance alignment.
The proxy advisory firms’ views regarding incentive metrics have evolved and will likely continue to be adjusted in the future. Companies should understand how their incentive metrics relate to the proxy advisory firms’ likely views and provide clear proxy disclosure regarding the company’s rationale and application of metrics. For companies that use metrics that advisory firms test against, it is important to understand differences in GAAP versus non-GAAP to minimise surprises. For example, it would be embarrassing if a company paid out incentive for outperforming return on invested capital (ROIC) – e.g. above the 75th percentile – when a proxy advisory firm’s test indicated ROIC performance is in the bottom quartile on a relative basis.
5. Investor feedback
We expect to see continued dialogue about executive compensation between company representatives and major investors. These discussions are more likely to occur when companies have been receiving relatively lower say-on-pay vote support from shareholders or during periods of significant change. When dedicated discussions about the executive officer pay programmes occur, typically, the top human resources and investor relations executives will lead the discussion about executive compensation with investors. Depending on the situation, the lead director and chair of compensation committee will also participate.
A major part of these discussions is often about incentive design/metric, goals and pay-for-performance alignment. Investors often have specific metrics they want to see for incentive plans, as well as the underlying focus on recent total shareholder returns – both absolute and relative to a relevant comparator group. However, if management has clear rationale for specific incentive metrics, investors are generally supportive. Having a defined process for goal setting as summarised above is helpful when meeting with investors.
6. TSR correlation analysis.
TSR correlation analysis assesses the historical relationship between financial metrics and TSR. This analysis answers the important question – what incentive metrics historically have positively correlated with TSR? As detailed below, this type of analysis is intended to provide a directional perspective and not a definitive answer. However, TSR correlation analysis can indicate which incentive metrics:
- Have historically had the strongest correlation to value creation (for the company and peers)
- Are the most volatile
- Are reasonable relative to key value drivers and metrics used by companies in similar businesses
Role of TSR correlation analysis
TSR correlation analysis assesses the historical relationship between financial metrics and TSR. This can be measured using a company’s own history (internal perspective) and a peer set (external perspective). These analyses assess the degree to which one variable (i.e. TSR) is affected by changes in a second variable (i.e. the chosen financial performance metric) over time.
By examining rolling three- and five-year periods over the past decade, we have identified financial measures that have a relatively strong positive correlation to TSR changes. However, since there are many company-specific and macroeconomic factors that impact performance over time, these analyses are intended to provide a directional perspective and not a definitive answer.
To provide context, we analysed 50 large industrial companies and found that the strongest TSR correlations were observed for return on invested capital and two margin metrics. For a set of 50 service companies, we found that revenue growth had the strongest correlation with TSR, followed closely by gross profit, margin and return on assets measures.
Key inputs
There are several key inputs to define when conducting TSR correlation analyses. For purposes of these illustrative analyses, we applied the following inputs:
- Measures Sample of financial performance measures spanning the income statement, balance sheet, and cash flow statement. If a standardised database is used, the financial measure definitions will often vary from the specific incentive plan measures used by a company
- Comparisons Change in dollar amounts for income statement measures and the absolute margin or return for other measures (the per cent change may also be analysed)
- Time period Three- and five-year rolling time periods over 10 years
- Correlation strength Relatively stronger correlations were highlighted at greater than or equal to 25 per cent, reflecting the wide range of companies that comprise the two data sets. We note that in smaller data sets of similar companies, correlations of near or greater than 50 per cent have been observed
Example output
The charts above illustrate the correlation of various financial metrics to TSR over three- and five-year periods. Metrics with correlations of greater than or equal to 25 per cent are highlighted. Financial performance data reflect standardised definitions provided by S&P Capital IQ (they have not been customised or adjusted).
Using TSR correlation analysis
TSR correlation analysis provides companies with another perspective as they confirm or reevaluate the appropriateness of their incentive plan performance measures. For example, assume a company in the service industry uses the following incentive metrics:
While these performance measures may be aligned with the company’s business plan and strategy, EPS and gross profit margin are not correlated with TSR based on historical relationships. Due to certain limitations, including the use of historical data at various points in time and the uniqueness of individual companies in a given peer set, TSR correlation analysis should be considered directional. A general correlation analysis, as illustrated herein, is a starting point. As a next step, a company may decide that further refinement is warranted in order to determine the most appropriate form of the metric to be used. In the end, companies should select incentive plan performance measures that best align to their business strategy to drive long-term shareholder value.
Putting it all together
There are many factors to consider in developing and administering a well-designed executive compensation programme. At the core, executive compensation has its foundation on incentive compensation opportunities – annual and long-term incentives – that provide a direct connection to the relevant metrics. In today’s say-on-pay environment, with a substantial potential negative impact on vote outcomes if proxy advisory firms perceive there is misalignment in pay-performance or underlying subpar designs, it is critical for companies to have the utmost confidence in their plan designs. While public companies have as a priority to increase total company value over time, there is typically a disconnect in using stock price or total shareholder return as the primary incentive metric. Yes, stock price and TSR are important. However, they are outputs of management’s execution of the strategy and the markets’ perceptions thereof, not a tangible day-to-day operating plan for the management team. While most companies readily note their business is unique – this observation may be more accurate now in today’s highly competitive, technology- and innovation-driven business models, game-changing challenges and opportunities that are prevalent. The result is the need for nuance, considering various tradeoffs, to arrive at the best designs for a particular company, not a ‘one size fits all’.
Companies with a long-term perspective and other astute companies review a wide range of inputs, including recent past, current and future projections for the industry, relevant direct peers and the company itself, to help determine their performance metrics for the new incentive cycles. Correlation analysis should be one of these perspectives that is, at least, periodically, reviewed. In the end, the company’s strategy, near-term realities and other internal factors should be the primary drivers in selecting the appropriate incentive metrics.
