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Using Sales Revenue as a Performance Measure

Abstract

• This study examines the relevance of sales revenue in compensation contracts.

• It documents an increasing trend in the explicit use of sales revenue in CEO annual bonus contracts.

• This trend is mirrored by an increase in the relative pay-sensitivity of revenues versus earnings over time.

• Sales revenue is more likely to be used when it's more informative about firm value than accounting earnings and when firms prioritize growth.

• The pay-sensitivity of revenue is significantly more positive for firms that explicitly reward revenue performance.

• Earnings pay-sensitivity is not significantly different from zero for these firms.

• The paper enhances the current understanding of performance measure selection in compensation contract design.

Introduction

• This study investigates the use of sales revenue as a performance measure in CEO compensation contracts.

• Prior research indicates that sales revenue significantly impacts equity pricing, especially when accounting earnings is less informative about firm value.

• Investors react more strongly to revenue surprises during firms' early growth stages.

• The market places greater valuation weight on sales revenue for technology and loss firms.

• Revenue's ability to substitute for accounting earnings is due to:

  • Greater persistence

  • Greater difficulty in managing revenues compared to costs

  • Easier understanding by financial statement users

• Bushman and Smith (2001) suggested that firms have shifted toward alternative performance measures as accounting profits become progressively less important in evaluating top executives.

• Sales revenue has become the most frequently used explicit performance measure in executive annual incentive plans (Towers Watson 2001, 2005, 2010).

• A Towers Watson survey in 2001 found that 25% of respondents used revenue as a performance measure, increasing to 31% in 2005 and 34% in 2010.

Research Design and Predictions

• The study employs two research design approaches:

  • Explicit contract approach: Examines factors influencing firms' decisions to contract on sales revenue performance.

  • Implicit contract approach: Examines the pay-sensitivity of sales revenue.

• Firms are more likely to supplement accounting earnings with sales revenue when sales revenue is more informative about firm value (Holmstrom 1979; Banker and Datar 1989; Lambert and Larcker 1987).

• The informativeness of sales revenue and accounting earnings is proxied using empirical measures from prior literature.

• The performance measures in executive bonus contracts for S&P 500 firms from 1993-2007 were hand-collected from SEC filings.

• Firms are more likely to employ sales revenue when sales value relevance is higher, sales variability is lower, special items are reported more frequently, and accrual management and earnings variability are greater.

• Firms are more likely to reward revenue performance when following a “prospector” business strategy (Miles and Snow 1978; Porter 1980).

• Prospectors prioritize being first-to-market through innovation and market share gains, while defenders emphasize operating efficiencies and cost reduction.

• A composite STRATEGY measure, along with R&D, intangible asset intensity, firm age, firm size, and M&A activity, is used to proxy for firms’ organizational strategy.

• The composite STRATEGY measure, R&D, intangible intensity, M&A activity, and industry competitiveness are positively associated with the use of sales revenue.

• Firm size and firm age are negatively associated with the contracting relevance of sales revenue.

• The pay-sensitivity of sales revenue is examined using the implicit contract approach, regressing changes in CEO cash compensation on changes in sales revenue, earnings, and stock return performance.

• The average pay-sensitivity for sales revenue performance is significantly positive after controlling for earnings and returns.

• The pay-sensitivity of earnings is declining over time, while the pay-sensitivity of revenue remains constant.

• The relative pay-sensitivity of revenues to earnings is significantly increasing over time.

• The pay-sensitivities of earnings and stock return performance are significantly positive for the average firm.

• The average pay-sensitivity for sales revenue performance is significantly positive.

• Revenue pay-sensitivity is significantly higher for firms that explicitly reward revenue performance.

• Earnings have no significant explanatory power in predicting CEO cash compensation after controlling for sales performance and stock returns.

• Chandra and Ro (2008) document that the value relevance of earnings drops significantly over the 1973-2003 period but the value relevance of revenues is not diminished.

• Dichev and Tang (2008) report that earnings volatility has increased significantly over 1967-2003 but that revenue volatility over the same time period has either remained unchanged or decreased slightly, depending upon the length of the reporting period.

Contributions

• This study offers the first systematic examination of the contracting relevance of sales revenue.

• It documents a significant increase in the frequency of using sales revenue as an explicit performance measure over time.

• This increase is mirrored by a similar increase in the relative pay-sensitivity of sales revenues to earnings.

• The explicit use of revenue is associated with the informativeness of revenue as a measure of firm value (Holmstrom 1979).

• Revenue is more likely to be used in firms that follow a “prospector” organizational strategy.

• The findings augment the understanding of compensation contract design and contribute to the literature on explicit performance measures (Gong, Li, and Shin 2011; Chen, Matsumura, Shin, and Wu 2015).

• The study provides new evidence on the validity of the implicit contract approach.

• Accounting earnings is not a significant determinant of compensation for firms that explicitly reward revenue performance.

• This contrasts with the widespread assumption in the implicit contracting literature.

• The findings complement Gong et al. (2011), who find that the explicit and implicit contract approaches yield varying inferences regarding firms’ use of relative performance evaluation in compensation contracts.

Literature Review and Hypothesis Development

• Top-line sales revenue is a key value driver of shareholder value (FASB 2000; Zhang 2005; Ghosh et al. 2005; Penman 2004; Srivastava 2014).

• The stock market reacts to revenue surprises (Jegadeesh and Livnat 2006).

• Meeting revenue forecasts leads to a distinct equity premium (Rees and Sivaramakrishan 2007).

• Managers voluntarily disclose projected revenue performance (Han and Wild 1991; Wasley and Wu 2006).

• The frequency of analysts' revenue forecasts has increased (Ertimur, Mayew, and Stubben 2011; Jegadeesh and Livnat 2006).

• Investors may place a higher valuation weight on sales than on earnings.

• For Internet firms with losses, revenue and revenue growth are highly important.

• Analysts tend to follow the price-to-sales ratio (Hand 2000; Trueman et al. 2000, 2001; Bagnoli, Penno, and Watts 2001; Demers and Lev 2001; Davis 2002; Bowen, Davis, and Rajgopal 2002; Callen et al. 2008).

• For software companies, the value-relevant information in earnings has declined while that of revenue has increased (Srivastava 2014).

• This is attributed to revenue’s greater persistence and the greater difficulty in managing revenues than expenses (Ertimur et al. 2003; Marquardt and Wiedman 2004; Ghosh et al. 2005).

• Despite the importance of sales revenue in firm valuation, its use in compensation contracting has been largely ignored.

• Existing research has focused on earnings as the primary accounting performance measure.

• The usefulness of accounting earnings in evaluating top executives has declined (Bushman and Smith 2001).

• The explicit use of sales revenue has significantly increased (Towers Watson 2001, 2005, 2010).

• The implicit contract approach involves regressing measures of executive pay on accounting-based and stock price-based performance measures (Bushman and Smith 2001).

• This approach assumes the performance measures used in contracts are known, which can lead to errors (Bushman and Smith 2001; Demski and Sappington 1999; Murphy 1999).

• It also makes it difficult to investigate the factors determining the choices of various performance measures (Ittner and Larcker 2002).

• The explicit contract approach provides detailed information on actual performance measures used.

• This reduces econometric problems and allows researchers to understand the signals the board communicates (Murphy and Jensen 2011; Armstrong, Guay, and Weber 2010).

• Agency theory suggests a performance measure is useful only if it provides incremental information regarding the agent’s unobserved actions (Holmstrom 1979; Banker and Datar 1989; Feltham and Xie 1994).

Hypothesis 1

• Firms are more likely to explicitly contract on sales revenue when sales revenue is more informative about firm value.

• H1: Firms are more likely to explicitly reward revenue performance in bonus compensation contracts when revenue (earnings) is relatively more (less) informative about firm value.

Hypothesis 2

• Performance measures should be closely tied to corporate strategies (Ittner et al. 1997).

• Corporate strategy is often a determinant of executive compensation design (e.g., Balkin and Gomez-Mejia 1990; Dow and Raposo 2005; Gomez-Mejia 1992; Ittner et al. 1997; Sanders and Carpenter 1998).

• Firms pursuing innovation- and quality-oriented strategies place more weight on non-financial metrics.

• The Miles-Snow (1978) typology characterizes firms as “prospectors” or “defenders.”

• Prospectors search for new markets and emphasize firm growth, investing heavily in research and development (Porter 1980; White 1986; Ward and Duray 2000).

• Defenders focus on defined markets and emphasize operating efficiencies to lower costs (Porter 1980; White 1986: Zahra and Covin 1993: Ward and Duray 2000).

• Firms following a prospector strategy are more likely to place greater importance on revenue growth.

• H2: Firms following a “prospector” corporate strategy are more likely to explicitly reward sales revenue performance in CEO annual bonus contracts than other firms.

Hypothesis 3

• Sales revenue is relevant in determining the magnitude of bonus compensation because of its greater persistence and the relatively greater difficulty in managing revenues than costs.

• H3: The pay-sensitivity of sales revenue is positive for the average firm.

Hypothesis 4

• The value relevance of sales revenue has not declined like that of accounting earnings.

• The ratio of the pay-sensitivity of sales revenue to the pay-sensitivity of earnings is increasing over time.

• H4: The relative pay-sensitivity of sales revenue to earnings is increasing over time.

Hypothesis 5

• If firms explicitly contracting on sales revenue place a higher weight on sales revenue performance, the pay-sensitivity of sales revenue is higher for these firms.

• H5: Revenue (earnings) pay-sensitivity is significantly higher (lower) for firms that explicitly reward revenue performance compared with firms that do not explicitly reward revenue performance.

Sample Description

• Data was hand-collected from firms’ proxy statements filed with the SEC from 1993 to 2007.

• The focus is on firms in the S&P 500.

• Sample firms must:

  1. Be identified as an S&P 500 firm between 1993-2007.

  2. Have available proxy statements on the SEC website.

  3. Have an annual bonus plan.

  4. Base executive bonus compensation on at least one performance measure.

  5. Disclose the explicit performance measures used in the bonus plan.

• Financial firms (SIC codes 6000-6999) and utilities (SIC codes 4900-4999) are excluded.

• Financial data is obtained from Compustat and stock price information from CRSP.

• The probit estimation of the decision to explicitly contract on sales revenue performance (H1 and H2) includes 3,909 firm-years.

• CEO compensation data from ExecuComp is used to test H3, H4, and H5.

• All available ExecuComp data is used to test H3 and H4 (N = 18,246 firm-years).

• ExecuComp data for S&P 500 firms is used to test H5 (N = 4,358 firm-years).

• EPS is the most commonly used measure (38%), followed by sales revenue (31%).

• Other financial performance measures include operating income/pretax income/EBITDA (26%), net income (21%), accounting returns (18%), cash flow/free cash flow (17%), return on shareholders’ equity (9%), economic profits (9%), stock returns (7%), operating margin (6%), and cost controls (3%).

• Firms often employ more than one performance measure; the mean (median) number of measures used is 2.79 (2.00).

• Firms using revenue as a performance measure are more likely to also adopt EPS, operating income/pretax income/EBITDA, cash flow/free cash flow, or operating margin.

• They are less likely to use accounting return measures, ROE, or EVA/Economic profit.

• Firms that adopt sales revenue as a performance measure tend to use significantly more performance measures than other firms.

• There is an increasing temporal trend in the frequency of firms using sales as a performance measure.

• High-tech industries exhibit high frequencies of firms using sales as a performance measure.

• Manufacturing industries generally have low frequencies of firms contracting on sales.

Empirical Tests

Determinants of Explicit Use of Sales Revenue

• To test H1 and H2, the following probit model is estimated:

  • P(SALES){i,t} = β0 + β1SALESVR{i,t-1} + β2SALESNOISE{i,t-1} + β3EARNINGSVR{i,t-1} + β4EARNINGSNOISE{i,t} + β5DDICHEV{i,t-1} + β6SIFREQ{i,t-1} + β7LOSSFREQ{i,t-1} + β8STRATEGY{i,t-1} + β9R&D{i,t-1} + β{10}INTANGIBLE{i,t-1} + β{11}AGE{i,t-1} + β{12}LOGTA{i,t-1} + β{13}M&A{i,t-1} + β{14}HHI{j,t-1} + β{15}HITECH{i,t-1} + δ_{i,t}

• SALES is an indicator variable that equals one when CEOs’ annual bonus contracts are tied to sales revenue performance, and zero otherwise.

• Higher compensation weights are placed on performance measures that are more value-relevant to investors.

• SALESVR is included to proxy for value relevance of revenue, obtained by using an 8-quarter rolling window estimation of the following model:

  • $CAR<em>{i,q} = α</em>0 + α<em>1ΔRPS</em>{i,q} + α<em>2ΔEPS</em>{i,q} + ε_{i,q}$

  • CAR is the raw stock return minus the CRSP value-weighted market portfolio return.

  • ΔRPS (ΔEPS) is changes in revenue per share (changes in earnings per share).

  • The estimated coefficient on ΔRPS (ΔEPS) is used as a proxy for the incremental value relevance of revenue (earnings).

• Performance measure volatility is another informativeness measure.

• SALESNOISE is included, measured by estimating the firm’s standard deviation of sales revenue deflated by common shares outstanding over previous eight quarters.

• EARNINGSVR and EARNINGSNOISE, defined as the standard deviation of return on assets over previous eight quarters, are included.

• The Dechow and Dichev (2002) measure of accruals quality (DDICHEV) is used as a proxy for earnings quality.

  • $ΔWC<em>t = r</em>0 + r<em>1CFO</em>{t-1} + r<em>2CFO</em>t + r<em>3CFO</em>{t+1} + r<em>4ΔREV</em>t + r<em>5PPE</em>t + ε_t$

  • DDICHEV is the standard deviation of firm-level residuals.

• Special item frequency (SIFREQ) and the incidence of losses (LOSSFREQ) are used as other proxies for earnings quality.

• To test H2, the variable STRATEGY is constructed based on five measures: the ratio of employees to total sales; the market-to-book ratio; the ratio of SG&A expenses to total sales; the standard deviation of the total number of employees; and the ratio of net PPE to total assets.

• R&D (R&D) and intangible assets (INTANGIBLE) are included.

• Firm age (AGE) and firm size (LOGTA) are included.

• A merger and acquisition variable (M&A) is included.

• Industry competition is controlled for using the Herfindahl-Hirschman Index (HHI).

• HITECH, an indicator variable that equals one if a firm operates in high-tech industry, and zero otherwise, is included.

• Return on assets (ROA) is included, controlling for firm performance.

• The usage of cash flow performance measures (CAHFLOWPM) is controlled for.

• The adoption of nonfinancial performance measure (NONFINANCIALPM) is controlled for.

Pay-Sensitivity of Sales Revenue

• To test predictions, the following model is estimated:

  • $CHGCASHCOMP<em>t = σ</em>0 + σ<em>1CHGREV</em>t + σ<em>2CHGEPS</em>t + σ<em>3RET</em>t + ε_t$

  • CEO cash compensation (CHGCASHCOMP) is measured by the annual percentage change in CEO salary and bonus compensation.

  • Change in sales revenue (CHGREV) is the change in annual sales revenue deflated by the prior year’s ending market value of equity.

  • Change in earnings (CHGEPS) is the change in annual earnings per share over lagged price.

  • Stock return (RET) is raw return over the fiscal year.

• To test H4, the estimated coefficients from equation (4) are regressed on the time-trend variable, calendar YEAR, as follows:

  • $σ<em>1 (σ</em>2, σ<em>3, or σ</em>1 /σ<em>2 ) = α</em>0 + α<em>1YEAR + ε</em>t$

Conclusion

• The use of revenue as an explicit performance metric is positively associated with the informativeness of sales revenue and the corporate strategy of the firm.

• Firms operating in high-tech and more competitive industries are more likely to adopt sales as an explicit performance measure.

• Sales pay-sensitivity is significantly positive for the average firms and that the relative implicit weight of sales revenue to earnings is increasing over time.

• Sales pay-sensitivity is significantly higher for firms that explicitly reward revenue performance, and earnings has no significant explanatory power in predicting CEO cash compensation after controlling sales and stock return performance.

• There are limitations to our study. First, the main sample consists of S&P 500 firms, which may limit the generalizability of our findings.

• Second, our main results are based on hand-collected data obtained from firms’ proxy statements filed with the SEC.

The article makes several arguments for the value and usefulness of revenue as a performance outcome measure:

1. Impact on Equity Pricing: Sales revenue significantly impacts equity pricing, especially when accounting earnings are less informative about firm value. Investors react more strongly to revenue surprises during firms' early growth stages, and the market places greater valuation weight on sales revenue for technology and loss firms.

2. Persistence: Revenue has greater persistence compared to accounting earnings, making it a more reliable indicator of future performance.

3. Manageability: It's more difficult to manage revenues compared to costs, making revenue a less susceptible target for manipulation and thus a more trustworthy metric.

4. Understandability: Revenue is easier to understand by financial statement users than accounting earnings, which can be complex and subject to various accounting treatments.

5. Increased Usage: Sales revenue has become the most frequently used explicit performance measure in executive annual incentive plans, indicating its growing acceptance and relevance.

6. Corporate Strategy Alignment: Firms following a “prospector” corporate strategy, which prioritizes innovation and market share gains, are more likely to emphasize revenue growth. This aligns performance measures with corporate strategies.

7. Value Relevance: The value relevance of sales revenue has not declined like that of accounting earnings, maintaining its importance over time.

The article makes several arguments for the value and usefulness of revenue as a performance outcome measure:

1. Impact on Equity Pricing: Sales revenue significantly impacts equity pricing, especially when accounting earnings are less informative about firm value. Investors react more strongly to revenue surprises during firms' early growth stages, and the market places greater valuation weight on sales revenue for technology and loss firms.

2. Persistence: Revenue has greater persistence compared to accounting earnings, making it a more reliable indicator of future performance.

3. Manageability: It's more difficult to manage revenues compared to costs, making revenue a less susceptible target for manipulation and thus a more trustworthy metric.

4. Understandability: Revenue is easier to understand by financial statement users than accounting earnings, which can be complex and subject to various accounting treatments.

5. Increased Usage: Sales revenue has become the most frequently used explicit performance measure in executive annual incentive plans, indicating its growing acceptance and relevance.

6. Corporate Strategy Alignment: Firms following a “prospector” corporate strategy, which prioritizes innovation and market share gains, are more likely to emphasize revenue growth. This aligns performance measures with corporate strategies.

7. Value Relevance: The value relevance of sales revenue has not declined like that of accounting earnings, maintaining its importance over time.