Key Takeaways
- Our latest EBITDA addback analysis continues to show a correlation between the magnitude of addbacks at deal inception and the severity of management projection misses.
- Data for the latest cohort of companies shows a slight improvement in earnings projection. Time will tell if this is an anomaly or an early sign of a fundamental shift toward more realizable projections at deal inception.
- Companies continue to overestimate debt repayment. The 2020 sample missed significantly on a relative basis, resulting in leverage misses on par with the six-year average despite improvement in projections.
- Actual leverage continues to be far in excess of management projections. The 2020 deals, on average, included median leverage 2.1 turns higher forecast for 2021 and three for 2022.
- In general, EBITDA addbacks remain elevated. Those for deals originated in 2022 represent over 29% of management projected EBITDA and almost 55% of last-12-months reported EBITDA in our latest sample of large mergers, acquisitions, and leveraged buyout transactions.
- Escalated addbacks create higher event risk and potential credit degradation as company-adjusted EBITDA often defines the size and flexibility companies have under debt agreements.
S&P Global Ratings' sixth annual analysis of EBITDA addbacks continues to show that:
- Addbacks represent a significant percentage of management-adjusted EBITDA at deal inception (30% on a median basis over the life of the study); and
- Management projections are aggressive, further substantiating that generally U.S. speculative-grade corporate issuers present earnings, debt, and leverage projections in their marketing materials at deal inception that they cannot realize, indicated by our study showing median leverage misses of 2.3 turns in year one following deal inception and 2.7 turns in year two.
As one would expect, these two factors are not mutually exclusive. Our data shows that, in general, aggressive addbacks correlate to increasingly unreliable projections. Our latest study reinforces our view that EBITDA adjustments do not generally provide a realistic view of future earnings.
We illustrate the relationship between the magnitude of addbacks--adjusted expenses to income and cash flow, such nonrecurring, unusual or discretionary costs--and projection performance as measured in terms of projected leverage misses in the two years following deal inception (Charts 1 and 2) for six years of performance data for transactions originated from 2015-2020 Focusing on the two extremes in both years of performance data (leverage misses of less than one turn and greater than five turns), which compose a significant portion of the sample, addbacks as a percentage of management-adjusted EBITDA (which we refer to as "marketing EBITDA") were approximately double for the worst performing transactions.
Chart 1
Chart 2
We are also introducing an interactive dashboard that enables readers to explore the data more immersively. It offers a deep analysis of the data from our six-year study here.
Our analysis consists of two main components:
- In the projection performance section of this report, we compare issuers' projected EBITDA at deal inception with actual reported EBITDA for the two fiscal years following the year of origination, accounting for the lag in measuring performance data in our study. Specifically, it provides time for one-time items to fall away and for management to realize most projected synergies. Given the difficulty and limited visibility in earnings breakouts, we are not in a position to parse out the specific components of addbacks to determine individual line-item realizations. As in our earlier addback studies, other factors besides overstatements may contribute to the difference between management-projected and reported EBITDA, such as unmaterialized growth or unforeseen operational issues.
- Part two of the study focuses on the magnitude and distribution of addbacks. We track and quantify the evolution of addbacks over time. Of the six categories of addbacks we track, synergies are the largest component by a wide margin. Often esoteric, synergies are also the most difficult to predict and model.
S&P Global Ratings' projections are independent
We derive ratings and financial risk analysis metrics from our own projections and judgments. While our findings clearly warn of the potential perils of buying into management forecasts, we base our ratings on S&P Global Ratings' independent projections of a company's expected earnings, a tempered view of its capacity and appetite for debt repayment, our analysis and assessment of business and financial factors such as management and board governance, and our view of potential synergies or operating efficiencies.
Specifically, marketing leverage and deal-specific language around addbacks--as defined in debt agreements--do not determine our view of credit risk (other than in assessing covenant headroom when reviewing debt instruments containing financial maintenance covenants). See an overview of our approach to EBITDA in our analysis in the About Our Analysis section below.
Part 1: The Validity And Accuracy Of EBITDA Addbacks
Addbacks can muddy the picture for future profitability and risk, and whether companies typically hit their forecasts
Deal arrangers, sponsors, and management teams remain aspirational in including various adjustments that they classify as EBITDA addbacks. This has increased the number, types, and ultimately magnitude of adjustments common in marketing materials and debt agreements. For example, while we have yet to see a literal addback for the "kitchen sink", the COVID-19 pandemic and related mitigation measures created a whole new category of adjustments related to cost and revenue impacts. In general, S&P Global Ratings views the ever-expanding definition of management-adjusted EBITDA as an inflation of profitability and an artificial deflation of leverage. This understates valuation multiples and improves the optics and marketability of a transaction. The absence of a standardized definition of EBITDA is critically important and can make it challenging for investors to directly compare transactions.
In practice, it is and has always been a negotiated definition, varying from agreement to agreement. The lack of lender negotiating leverage in the syndicated loan market has helped addbacks proliferate. While we understand anecdotally that lender pushback on certain adjustments and terms can sometimes be effective at the margin, this largely ebbs and flows with supply and demand. Terms are now generally more permissive.
While investors should make their own call about how best to gauge EBITDA and deal leverage, it is still critical that they understand the magnitude and persistence of the shortfall in projected versus actual EBITDA, which our study underscores. Further, investors should be sensitive to an expansive definition of EBITDA providing for myriad addbacks in debt agreements. This may well present significant incremental event risk because it often provides additional headroom under negative covenants and restricted payments (including dividends, debt, investments, and lien allowances). The expansive definition of EBITDA has contributed to the rise in aggressive out-of-court restructurings in recent years.
Summary of findings
Management teams almost universally claim there is ample upside to their projections at deal inception and that the base case they market is conservative. However, our six-year performance study suggests this is far from reality. According to our data, 95% of the companies failed to meet their first-year projections and over 50% missed earnings projections by more than 33% in the two years following inception.
Over-promised debt repayment also contributed to the overall leverage misses, but to a lesser degree. The median miss in projected debt in the six-year study is 2% in year one and 13% in year two following deal inception. For the more than 200 transactions, management missed leverage projections on a median basis by 2.3x in year one and 2.7x in year two. We delve into greater detail in this report.
Our Review Methodology
To assess the realization of addbacks and measure management projection performance, we compared projected marketing EBITDA presented at deal inception with actual reported EBITDA for the two fiscal years following deal inception. We compared at the aggregate level, given the difficulty in evaluating the various individual components of addbacks. For example, companies rarely disclose the actual achievement of a particular type of cost savings in their financials. Further, with mostly covenant-light loan structures, investors do not benefit from company compliance certificates that can provide line-item details on addback realization.
We include two years of actual performance data, allowing time to measure whether the companies in the sample have effectively realized projected synergies, and permit certain cost addbacks (such as transaction fees and expenses and restructuring costs) to roll off. It's relatively standard in company projection models to include 12-24 months for realizing anticipated synergies.
Further, as in our earlier reviews, we eliminate companies that underwent a transformative merger, acquisition, or leveraged buyout within two years of deal inception. This enables us to remove distortion following subsequent transformative events (new debt issuance, earnings affected by subsequent acquisitions, etc.), which render initial projections irrelevant. It also allows us to cleanly compare reported EBITDA, debt, and leverage with what was projected by the companies included in our sample at deal inception.
Lastly, we cannot disclose company names because management projections presented to S&P Global Ratings at deal inception are confidential.
Table 1
Transactions originated during 2015-2020 | ||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--Company projected vs. net reported-- | ||||||||||||||||||||||
--EBITDA*-- | --Debt-- | --Leverage**-- | ||||||||||||||||||||
Year 1 | Year 2 | Year 1 | Year 2 | Year 1 | Year 2 | |||||||||||||||||
% exceed projection | 5% | 16% | % exceed projection | 40% | 27% | % exceed projection | 13% | 14% | ||||||||||||||
% missed >0% | 95% | 84% | % missed > 0% | 60% | 73% | % missed >0x | 87% | 86% | ||||||||||||||
% missed >=10% | 85% | 75% | % missed >=10% | 33% | 59% | % missed >=1x | 76% | 76% | ||||||||||||||
% missed >=25% | 64% | 60% | % missed >=25% | 15% | 34% | % missed >=2x | 55% | 60% | ||||||||||||||
% missed >=33.3% | 51% | 55% | % missed >=33.3% | 11% | 31% | % missed >=3x | 38% | 43% | ||||||||||||||
% missed >=50% | 22% | 30% | % missed >=50% | 10% | 25% | % missed >=5x | 20% | 26% | ||||||||||||||
Average miss | 33% | 32% | Average miss | 6% | 25% | Average miss | 3.6x | 3.8x | ||||||||||||||
Median miss | 34% | 35% | Median miss | 2% | 13% | Median miss | 2.3x | 2.7x | ||||||||||||||
*Company projections are adjusted EBITDA. **Leverage calculation based on average of debt to EBITDA of each company in the sample. |
Table 2
Transactions originated during 2020 | ||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--Company projected vs. net reported-- | ||||||||||||||||||||||
--EBITDA*-- | --Debt-- | --Leverage**-- | ||||||||||||||||||||
2021 | 2022 | 2021 | 2022 | 2021 | 2022 | |||||||||||||||||
% exceed proj. | 11% | 30% | % exceed proj. | 19% | 4% | % exceed proj. | 4% | 15% | ||||||||||||||
% missed >0% | 89% | 70% | % missed > 0% | 81% | 96% | % missed >0x | 96% | 85% | ||||||||||||||
% missed >=10% | 78% | 59% | % missed >=10% | 56% | 93% | % missed >=1x | 74% | 78% | ||||||||||||||
% missed >=25% | 52% | 56% | % missed >=25% | 19% | 67% | % missed >=2x | 63% | 63% | ||||||||||||||
% missed >=33.3% | 37% | 41% | % missed >=33.3% | 15% | 52% | % missed >=3x | 44% | 48% | ||||||||||||||
% missed >=50% | 19% | 22% | % missed >=50% | 4% | 48% | % missed >=5x | 22% | 33% | ||||||||||||||
Average miss | 26% | 19% | Average miss | 12% | 36% | Average miss | 3.7x | 5.1x | ||||||||||||||
Median miss | 28% | 28% | Median miss | 12% | 34% | Median miss | 2.1x | 3.0x | ||||||||||||||
*Company projections are adjusted EBITDA. **Leverage calculation based on average of debt to EBITDA of each company in the sample. |
EBITDA misses are the primary driver behind large leverage misses
If management projections proved realistic, we would see a convergence between management-projected and actual reported results as companies realize anticipated earnings, one-time items fall away, and synergies are achieved. In actuality, our study continues to show a rather dramatic divergence. In addition to management-inflated EBITDA, we could attribute the deviation in part to several additional factors, including unmaterialized growth projections, operating challenges, unrealized synergies, or unattained cost savings.
Our six-year study shows that just 5% of companies met or exceeded projections in the first year following deal inception and 16% in year two. The median miss in year one was 34%, rising to 35% in year two (Table 3).
The 2020 cohort improved performance, with 11% of companies meeting or exceeding projections in 2021 and 30% in 2022. The median miss improved by 6% to 28% in 2021 versus the six-year median of 34% and improved by 7% in 2022 to 28% versus the six-year median miss of 35% in year two. The average miss improved 7% in year one and 13% in year two.
Still, while results for 2020 are encouraging, one year does not necessarily represent a fundamental shift toward more reasonable management forecasts.
Table 3
Company-projected vs. actual reported EBITDA | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--2015-2020 cohort-- | --2020 cohort-- | --2019 cohort-- | --2018 cohort-- | --2017 cohort-- | --2016 cohort-- | --2015 cohort-- | ||||||||
Year 1 | Year 2 | 2021 | 2022 | 2020 | 2021 | 2019 | 2020 | 2018 | 2019 | 2017 | 2018 | 2016 | 2017 | |
Average miss | 33% | 32% | 26% | 19% | 39% | 30% | 36% | 39% | 27% | 30% | 35% | 35% | 29% | 34% |
Median miss | 34% | 35% | 28% | 28% | 41% | 35% | 38% | 39% | 32% | 30% | 30% | 35% | 33% | 39% |
Highest miss | 97% | 220% | 70% | 79% | 83% | 90% | 97% | 81% | 83% | 79% | 70% | 77% | 83% | 74% |
Total count | 209 | 209 | 27 | 27 | 30 | 30 | 48 | 48 | 41 | 41 | 31 | 31 | 32 | 32 |
No. exceed proj. | 11 | 33 | 3 | 8 | 1 | 7 | 2 | 7 | 3 | 5 | 0 | 2 | 2 | 4 |
% exceed proj. | 5% | 16% | 11% | 30% | 3% | 23% | 4% | 15% | 7% | 12% | 0% | 6% | 6% | 13% |
No. missed > 0% | 198 | 176 | 24 | 19 | 29 | 23 | 46 | 41 | 38 | 36 | 31 | 29 | 30 | 28 |
% missed > 0% | 95% | 84% | 89% | 70% | 97% | 77% | 96% | 85% | 93% | 88% | 100% | 94% | 94% | 87% |
No. missed >=10% | 178 | 156 | 21 | 16 | 28 | 21 | 42 | 37 | 34 | 32 | 28 | 26 | 25 | 24 |
% missed >=10% | 85% | 75% | 78% | 59% | 93% | 70% | 88% | 77% | 83% | 78% | 90% | 84% | 78% | 75% |
No. missed >=25% | 134 | 126 | 14 | 15 | 24 | 18 | 35 | 32 | 23 | 22 | 20 | 17 | 18 | 22 |
% missed >=25% | 64% | 60% | 52% | 56% | 80% | 60% | 73% | 67% | 56% | 54% | 65% | 55% | 56% | 69% |
No. missed >=33.3% | 106 | 114 | 10 | 11 | 19 | 18 | 26 | 29 | 20 | 20 | 15 | 16 | 16 | 20 |
% missed >=33.3% | 51% | 55% | 37% | 41% | 63% | 60% | 54% | 60% | 49% | 49% | 48% | 52% | 50% | 63% |
No. missed >=50% | 47 | 63 | 5 | 6 | 8 | 10 | 14 | 17 | 6 | 10 | 10 | 10 | 4 | 10 |
% missed >=50% | 22% | 30% | 19% | 22% | 27% | 33% | 29% | 35% | 15% | 24% | 32% | 32% | 13% | 31% |
Chart 3
Debt reduction is lower than projected
Failure to meet projected debt also contributed to the significant miss of management-projected leverage, but to a much lesser extent than EBITDA misses. Virtually all issuers present a deleveraging story to the market at deal inception, stating intentions to sweep surplus cash to aggressively reduce debt. Relative to the six-year sample, the latest 2020 study cohort decreased projection accuracy with respect to anticipated debt. The median miss for the 2020 cohort was 12% in 2021 versus the six-year median miss of 2% in year one. That rose to 34% in 2002 versus the six-year median miss in year two of 13%. This actually almost fully offset the improvement in earnings projections, resulting in leverage misses that were almost on top of our six-year average.
In short, companies appear to have infrequently executed stated intentions to apply surplus cash to pay down debt. Indeed, they rarely, if ever, meet those indications. Across the six vintages, 60% of companies kept debt in check (by keeping below or within 10% of their targets) in the first year following origination. That share quickly deteriorated to less than 27% by the end of the second year across all cohorts. We net reported cash balances against reported debt to compute debt and leverage divergence for comparability.
The six-year median (across the 209 transactions from all six cohorts) debt repayment miss was 2% in year one and 13% in year two. The 2020 cohort performed significantly worse than the six-year median, missing by 12% in year one and 34% in year two due to several outliers.
Table 4
Company projected vs. actual reported net debt | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--2015-2020 cohort-- | --2020 cohort-- | --2019 cohort-- | --2018 cohort-- | --2017 cohort-- | --2016 cohort-- | --2015 cohort-- | ||||||||
Year 1 | Year 2 | 2021 | 2022 | 2020 | 2021 | 2019 | 2020 | 2018 | 2019 | 2017 | 2018 | 2016 | 2017 | |
Average miss | 6% | 25% | 12% | 36% | 1% | 11% | 4% | 22% | 3% | 12% | 6% | 40% | 7% | 19% |
Median miss | 2% | 13% | 12% | 34% | 1% | 11% | 2% | 11% | 11% | 25% | 3% | 11% | 1% | 12% |
Highest miss | 206% | 614% | 44% | 99% | 60% | 108% | 93% | 614% | 181% | 195% | 149% | 339% | 101% | 119% |
Total count | 209 | 209 | 27 | 27 | 30 | 30 | 48 | 48 | 41 | 41 | 31 | 31 | 32 | 32 |
No. exceed proj. | 83 | 56 | 5 | 1 | 17 | 11 | 22 | 18 | 15 | 10 | 10 | 8 | 14 | 8 |
% exceed proj. | 40% | 27% | 19% | 4% | 57% | 37% | 46% | 38% | 37% | 24% | 32% | 26% | 44% | 25% |
No. missed > 0% | 126 | 153 | 22 | 26 | 13 | 19 | 26 | 30 | 26 | 31 | 21 | 23 | 18 | 24 |
% missed > 0% | 60% | 73% | 81% | 96% | 43% | 63% | 54% | 63% | 63% | 76% | 68% | 74% | 56% | 75% |
No. missed >=10% | 68 | 124 | 15 | 25 | 7 | 15 | 15 | 25 | 13 | 24 | 10 | 16 | 8 | 19 |
% missed >=10% | 33% | 59% | 56% | 93% | 23% | 50% | 31% | 52% | 32% | 59% | 32% | 52% | 25% | 59% |
No. missed >=25% | 32 | 72 | 5 | 18 | 3 | 8 | 8 | 12 | 7 | 12 | 4 | 12 | 5 | 10 |
% missed >=25% | 15% | 34% | 19% | 67% | 10% | 27% | 17% | 25% | 17% | 29% | 13% | 39% | 16% | 31% |
No. missed >=33.3% | 22 | 65 | 4 | 14 | 2 | 8 | 6 | 11 | 5 | 10 | 1 | 12 | 4 | 10 |
% missed >=33.3% | 11% | 31% | 15% | 52% | 7% | 27% | 13% | 23% | 12% | 24% | 3% | 39% | 13% | 31% |
No. missed >=50% | 14 | 34 | 0 | 7 | 1 | 2 | 5 | 7 | 5 | 8 | 1 | 5 | 2 | 5 |
% missed >=50% | 7% | 16% | 0% | 26% | 3% | 7% | 10% | 15% | 12% | 20% | 3% | 16% | 6% | 16% |
Chart 4
The resulting leverage profile is much higher than projected
The combination of significant misses in earnings and debt projections, particularly earnings, creates a material discrepancy between projected and reported leverage across the six-year sample. Aspirational management-projected EBITDA creates a significant leverage cushion inconsistent with credit realities. By averaging the median gap across the six vintages, companies under-projected leverage by an average of 2.3 turns in the first year, increasing to 2.7 turns by the end of year two (Table 5).
For the 2020 cohort, the median leverage miss outperformed the six-year median in year one at 2.1 turns versus 2.3 turns. Conversely, in year two, the median miss was three turns, compared to the six-year median of 2.7. We primarily attribute this to the uncharacteristically large debt miss in 2022 for the 2020 cohort.
Table 5
Company-projected vs. actual reported net leverage | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--2015-2020 cohort-- | --2020 cohort-- | --2019 cohort-- | --2018 cohort-- | --2017 cohort-- | --2016 cohort-- | --2015 cohort-- | ||||||||
Year 1 | Year 2 | 2021 | 2022 | 2020 | 2021 | 2019 | 2020 | 2018 | 2019 | 2017 | 2018 | 2016 | 2017 | |
Average miss | 3.6x | 3.8x | 3.7x | 5.1x | 4.1x | 4.5x | 4.6x | 3.5x | 2.6x | 2.7x | 3.1x | 3.3x | 2.9x | 3.6x |
Median miss | 2.3x | 2.7x | 2.1x | 3.0x | 1.8x | 2.7x | 2.5x | 2.3x | 2.8x | 3.3x | 1.9x | 2.5x | 2.1x | 3.5x |
Highest miss | 30.3x | 37.6x | 15.5x | 20.3x | 22.4x | 37.6x | 30.3x | 21.5x | 17.0x | 10.9x | 15.2x | 19.4x | 20.9x | 10.0x |
Total count | 209 | 209 | 27 | 27 | 30 | 30 | 48 | 48 | 41 | 41 | 31 | 31 | 32 | 32 |
No. exceed proj. | 28 | 30 | 1 | 4 | 3 | 8 | 9 | 9 | 4 | 2 | 6 | 3 | 5 | 4 |
% exceed proj. | 13% | 14% | 4% | 15% | 10% | 27% | 19% | 19% | 10% | 5% | 19% | 10% | 16% | 13% |
No. missed >1x | 159 | 159 | 20 | 21 | 25 | 20 | 36 | 37 | 33 | 35 | 22 | 22 | 23 | 24 |
% missed >1x | 76% | 76% | 74% | 78% | 83% | 67% | 75% | 77% | 80% | 85% | 71% | 71% | 72% | 75% |
No. missed >=2x | 114 | 125 | 17 | 17 | 14 | 16 | 29 | 26 | 25 | 26 | 13 | 20 | 16 | 20 |
% missed >=2x | 55% | 60% | 63% | 63% | 47% | 53% | 60% | 54% | 61% | 63% | 42% | 65% | 50% | 63% |
No. missed >=3x | 79 | 90 | 12 | 13 | 9 | 13 | 21 | 18 | 16 | 16 | 9 | 13 | 12 | 17 |
% missed >=3x | 38% | 43% | 44% | 48% | 30% | 43% | 44% | 38% | 39% | 39% | 29% | 42% | 38% | 53% |
No. missed >=5x | 41 | 54 | 6 | 9 | 7 | 7 | 13 | 11 | 4 | 10 | 5 | 7 | 6 | 10 |
% missed >=5x | 20% | 26% | 22% | 33% | 23% | 23% | 27% | 23% | 10% | 24% | 16% | 23% | 19% | 31% |
Projected leverage (average) | 4.2x | 3.4x | 4.6x | 3.7x | 4.3x | 3.5x | 4.3x | 3.5x | 4.2x | 3.5x | 3.8x | 3.0x | 4.2x | 3.3x |
Actual leverage (average) | 7.8x | 7.2x | 8.3x | 8.8x | 8.4x | 8.0x | 8.8x | 7.0x | 7.1x | 6.7x | 6.8x | 6.3x | 7.1x | 7.0x |
Projected leverage (median) | 4.4x | 3.6x | 4.8x | 3.9x | 4.3x | 3.5x | 4.6x | 3.8x | 4.3x | 3.6x | 3.9x | 3.1x | 4.2x | 3.4x |
Actual leverage (median) | 6.7x | 6.4x | 7.1x | 6.7x | 6.7x | 6.1x | 7.6x | 6.4x | 7.0x | 6.4x | 5.7x | 5.9x | 6.1x | 6.5x |
Chart 5
Part 2: The Magnitude And Composition Of EBITDA Addbacks
Data set
The sample size for our EBITDA addback magnitude and composition analysis encompasses over 600 broadly syndicated mergers and acquisitions (M&A) and leveraged buyout (LBO) transactions that we rated, originating from 2015-2022. This includes only those transactions for which management provided us with a detailed bridge from reported EBITDA to marketing EBITDA (as is typically the case for large LBOs and M&A). This data set is substantially larger than the set for Part 1 because it includes:
- Transactions for 2021 and 2022 for which we don't yet have the two years of operating results to gauge projection performance.
- Transactions from prior years that we did not use for Part 1 due to a subsequent transformative transaction.
Of the total sample, 56% were M&A and 44% LBOs. We rated 87% in the 'B' category at inception, with the remaining 13% in the 'BB' category. With the expansion of the data set to include transactions from 2022, the proportionate share of 'B' category ratings continues to increase, reflecting the erosion of credit quality in the broader leveraged finance market. Finally, more than three-quarters of the transactions in the sample were sponsored and the remainder non-sponsored.
Chart 6A
Chart 6B
Chart 6C
We compared the magnitude of addbacks to both last-12-months reported EBITDA excluding addbacks and management-adjusted EBITDA including addbacks at deal inception. On average, in the eight years of EBITDA magnitude data in our study, addbacks made up over 29% of marketing EBITDA and about 53% of last-12-months reported EBITDA (Chart 7). The most recent 2022 cohort was right on top of the eight-year average of 29%. This forward-looking measure has marginally expanded each year, exceeding 30% in 2018 and beyond from 24% in 2015.
Our data across the eight-year sample shows the ratings distribution has shifted toward 'B' rated issuers. We found that regardless of transaction type, 'B' category credits lead 'BB' rated issuers in average adjustment. The line of demarcation is the 2018 cohort of transactions. In the 2015-2017 cohorts, 'BB' category ('BB-', 'BB', and 'BB+') transactions accounted for an average of 20% of the data set. From 2018-2022, 'BB' category credits averaged about 10% of the sample. The 2022 cohort contained only one 'BB' category issuance.
Correspondingly, average addbacks as a percentage of management adjusted EBITDA rose to over 30% from about 25% in 2015-2017.
Chart 7
Synergies and cost savings make up about a third of total addbacks
Expected synergies and cost savings are the largest components of addbacks. We sort the general addback adjustments into six broad categories (Chart 8). In every cohort but the latest, synergies and cost savings lead over other adjustment types. It peaked in 2016 at nearly 39%, with an eight-year average of 28%. Synergies are often the most difficult of the common addbacks to forecast accurately. As mentioned, we rarely factor all of management-anticipated synergies into our projections. Our assessment includes detailed discussions with management teams and their advisers regarding expected synergies and timelines for realization. Our adjustments often depend on the source of synergies and, when relevant, whether a company or sponsor has a track record of realizing similar synergies or cost savings.
While some are easier to execute--such as eliminating overlapping corporate overhead to achieve labor savings--others fall outside management's control. Pro forma saving on procurement offers one example, as it requires contract negotiations with various third-party vendors. Lastly, some synergies are costly to implement, requiring an upfront expense such as severance pay for which we also must account.
Restructuring costs are another area of disparity in treatment. We generally treat these ongoing charges as operating costs because most companies need to restructure their operations to adapt to changing environments and remain competitive. Similarly, as stated in our approach to EBITDA, management fees constitute a cash operating cost, and we treat them as such in our analysis. Therefore, we do not add back restructuring costs or management fees to our calculation of adjusted EBITDA. In addition, this body of data demonstrates how far off companies' original assumptions tend to be about the realization of addbacks. We include all negotiated addbacks in our study.
Chart 8
Technology, health care, and media, entertainment, and leisure stand out with high addbacks as a percentage of marketing EBITDA
These sectors consistently have high addback-inflated EBITDA, with an eight-year average of about 35% of total addbacks divided by company-adjusted pro forma EBITDA at inception. Addbacks for these sectors buoy the entire sample given the disproportionate representation of about 44% of the deal count.
Table 6
Average addbacks by sector | |||
---|---|---|---|
Sector | Companies | Average of total add backs/reported last-12-months EBITDA at inception | Average of total addbacks/company pro forma adjusted EBITDA at inception |
High technology | 124 | 66.1% | 35.9% |
Telecommunications | 6 | 62.6% | 34.6% |
Health care | 83 | 62.5% | 34.6% |
Media, entertainment, and leisure | 62 | 46.7% | 34.3% |
Chemicals | 15 | 66.8% | 33.8% |
Insurance services | 10 | 67.3% | 31.8% |
Finance | 3 | 48.8% | 29.7% |
Transportation | 18 | 46.4% | 27.8% |
Capital goods/machine and equipment | 71 | 68.6% | 27.0% |
Autos/trucks | 15 | 39.1% | 26.3% |
Consumer products | 49 | 67.3% | 25.5% |
Restaurants/retail | 27 | 43.1% | 23.4% |
Business and consumer services | 62 | 34.8% | 22.2% |
Aerospace/defense | 15 | 40.8% | 21.9% |
Oil | 3 | 25.3% | 20.1% |
Mining and minerals | 6 | 22.4% | 17.7% |
Forest products/building materials/packaging | 35 | 23.2% | 17.6% |
Total | 604 | 54.6% | 29.4% |
Chart 9
Table 7
Average addbacks by transaction type | |||||||||
---|---|---|---|---|---|---|---|---|---|
Companies | Transaction costs | Restructuring | Nonrecurring operating | Cost savings/synergies | Management fees/executive compensation | Other adjustments | Marketing EBITDA | Reported | |
B+/B/B- rating | 528 | 14.4% | 19.5% | 14.5% | 26.6% | 10.9% | 14.0% | 30.4% | 56.2% |
BB+/BB/BB- rating | 76 | 6.4% | 17.6% | 5.7% | 34.5% | 21.6% | 14.2% | 22.4% | 43.7% |
Leveraged buyout | 263 | 11.5% | 19.6% | 16.8% | 25.3% | 11.8% | 15.0% | 27.6% | 49.0% |
Mergers and acquisitions | 341 | 14.8% | 19.0% | 10.8% | 29.5% | 12.6% | 13.3% | 30.8% | 59.0% |
Not sponsored | 145 | 9.4% | 20.4% | 9.0% | 31.4% | 18.0% | 11.7% | 27.2% | 48.7% |
Sponsored | 459 | 14.6% | 18.9% | 14.8% | 26.4% | 10.5% | 14.7% | 30.1% | 56.5% |
Total | 604 | 13.4% | 19.3% | 13.4% | 27.6% | 12.3% | 14.0% | 29.4% | 54.6% |
Companies rated 'B' typically include more addbacks than those rated 'BB'
In our data set, we rated 87% companies in the 'B' category. Our study shows that these companies have consistently underperformed 'BB' category credits in projecting earnings. The need for aggressive adjustments to make a deal marketable is likely limited for 'BB' rated companies since their pro forma leverage is typically lower. In addition, an intuitive view could be that lower-rated credits tend to be smaller and have higher earnings volatility, making projections more difficult. Also, financial sponsor ownership is more common among lower-rated entities than those in the 'BB' category. Sponsor-owned companies tend to be more aggressive when projecting earnings.
Across the six-year sample, the median leverage miss in the 'B' category was 2.6 turns higher than projected in year one following deal inception, with the gap widening to 2.9 turns in year two. Credits in the 'BB' category performed significantly better, missing by 2.2 turns in year one and 2.3 turns in year two, further reinforcing the significant credit disparity between 'B' and 'BB' credits. The comparison for the latest 2020 cohort is not meaningful because the sample contains only one 'BB' category issuance.
Table 8
Average addbacks by issuer credit rating | ||
---|---|---|
Marketing EBITDA | Reported EBITDA | |
B+/B/B- | 30% | 56% |
BB+/BB/BB- | 22% | 44% |
Average | 29% | 55% |
Chart 10
Chart 11
LBO leverage projection misses are larger than for M&A transactions
Consistent with our prior studies, they are comparable in addbacks as a percentage of marketing EBITDA--28% for LBOs and 31% for M&A. However, the distribution of addbacks differs. M&A transactions show above-average addbacks for synergies and cost savings, since these are often a selling point of the transaction.
Regarding projection performance, LBOs have consistently underperformed M&A deals in projecting leverage for every cohort in our study. On a median basis, M&A transactions missed by 1.9 turns in year one and 2.2 turns in year two following deal inception; LBOs missed by 2.6 turns in year one and 3.3 turns in year two. The gap increased in the latest cohort with LBOs missing more than M&A transactions by 0.9 turns in 2021 and 1.3 turns in 2022. For comparison, within our financial risk categories, the difference between the midpoints of two categories (significant and aggressive, for example) is one turn of leverage.
Table 9
Average addbacks by transaction type | ||
---|---|---|
Marketing EBITDA | Reported EBITDA | |
Leveraged buytouts | 28% | 49% |
Mergers and acquisitions | 31% | 59% |
Average | 29% | 55% |
Chart 12
Chart 13
Sponsored transactions generally underperform non-sponsored transactions
They tend to be more aggressive, according to our data, but not by a significant margin. Projection performance is a different story, however (Chart 14). The eight-year average for sponsored deals was 29% versus 27% for non-sponsored deals. The latter were generally about 25% each year with little fluctuation, except for deals that originated in 2021 when non-sponsored transactions averaged 36% versus 31% for sponsored. We attribute this to one extreme outlier in the non-sponsored sample. Removing that transaction results in an average of 29%, which is more consistent with other cohorts. Of the 604 transactions in our data set, 459 were sponsored, 145 were not.
We also noted a significant disparity by individual sponsors regarding their aggressiveness in the use of addbacks. We looked at the 39 sponsors that had done at least four transactions. Of those, the 10 most aggressive firms (accounting for 75 transactions) had addbacks averaging 44% of marketing EBITDA. Conversely, the 10 least aggressive sponsors (accounting for 58 transactions) averaged 16%.
Chart 14
Sponsored transactions significantly underperformed non-sponsored transactions in the accuracy of their projections at deal inception (Tables 10 and 11). Our six cohorts of data show that the median miss for sponsored transactions was 2.7 turns in the year following deal inception, increasing to three turns in year two. This compares to a median miss for non-sponsored deals of 1.6 turns in year one and 1.7 turns in year two. For the 2020 cohort, the disparity was much wider than the historical median differential. Although the year one miss for sponsored transactions was slightly inside the longer-term median, the year two miss was 1.6 turns worse. Conversely, non-sponsored deals in the 2020 cohort outperformed the six-cohort median by a half turn in year one and 0.3 of a turn in year two.
Table 10
Company-projected vs. actual reported net leverage (sponsor-owned firms) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--2015-2020 cohort-- | --2020 cohort-- | --2019 cohort-- | --2018 cohort-- | --2017 cohort-- | --2016 cohort-- | --2015 cohort-- | ||||||||
Year 1 | Year 2 | 2021 | 2022 | 2020 | 2021 | 2019 | 2020 | 2018 | 2019 | 2017 | 2018 | 2016 | 2017 | |
Average miss | 4.1x | 4.3x | 4.0x | 5.7x | 5.1x | 4.6x | 4.9x | 3.9x | 3.2x | 4.2x | 3.6x | 3.5x | 3.5x | 4.3x |
Median miss | 2.7x | 3.0x | 2.9x | 4.0x | 2.6x | 2.7x | 3.0x | 2.3x | 2.8x | 3.2x | 2.0x | 3.6x | 2.7x | 4.2x |
Highest miss | 30.3x | 37.6x | 15.5x | 20.3x | 22.4x | 37.6x | 30.3x | 21.5x | 17.0x | 10.9x | 14.8x | 6.5x | 21.1x | 10.4x |
Total count | 142 | 142 | 23 | 23 | 20 | 20 | 33 | 33 | 28 | 28 | 18 | 18 | 30 | 30 |
No. exceed proj. | 13 | 16 | 1 | 3 | 1 | 5 | 6 | 7 | 1 | 0 | 2 | 0 | 1 | 2 |
% exceed proj. | 9% | 11% | 4% | 13% | 5% | 25% | 18% | 21% | 4% | 0% | 11% | 0% | 3% | 7% |
No. missed >0x | 129 | 126 | 22 | 20 | 19 | 15 | 27 | 26 | 27 | 28 | 16 | 18 | 29 | 28 |
% missed >0x | 91% | 89% | 96% | 87% | 95% | 75% | 82% | 79% | 96% | 100% | 89% | 100% | 97% | 93% |
No. missed >1x | 115 | 115 | 18 | 18 | 17 | 15 | 25 | 25 | 25 | 25 | 15 | 15 | 23 | 23 |
% missed >1x | 81% | 81% | 78% | 78% | 85% | 75% | 76% | 76% | 89% | 89% | 83% | 83% | 77% | 87% |
No. missed >=2x | 89 | 95 | 16 | 16 | 11 | 11 | 22 | 18 | 20 | 22 | 8 | 14 | 17 | 22 |
% missed >=2x | 63% | 67% | 70% | 70% | 55% | 55% | 67% | 55% | 71% | 79% | 44% | 78% | 57% | 73% |
No. missed >=3x | 63 | 71 | 11 | 13 | 8 | 9 | 16 | 13 | 12 | 15 | 6 | 9 | 14 | 17 |
% missed >=3x | 44% | 50% | 48% | 57% | 40% | 45% | 48% | 39% | 43% | 54% | 33% | 50% | 47% | 57% |
No. missed >=5x | 34 | 43 | 6 | 9 | 6 | 4 | 10 | 9 | 3 | 10 | 4 | 5 | 6 | 11 |
% missed >=5x | 0.2x | 0.3x | 0.3x | 0.4x | 0.3x | 0.2x | 30% | 27% | 11% | 36% | 22% | 28% | 20% | 37% |
Projected leverage (average) | 4.6x | 3.8x | 4.8x | 3.9x | 4.8x | 4.1x | 4.6x | 3.9x | 4.5x | 3.8x | 4.4x | 3.6x | 4.3x | 3.4x |
Actual leverage (average) | 8.8x | 8.1x | 8.8x | 9.6x | 9.9x | 8.6x | 9.5x | 7.7x | 7.7x | 7.9x | 8.0x | 7.1x | 7.8x | 7.7x |
Projected leverage (median) | 4.8x | 3.9x | 4.8x | 3.9x | 5.0x | 4.3x | 4.8x | 4.0x | 4.8x | 3.9x | 4.6x | 3.7x | 4.4x | 3.7x |
Actual leverage (median) | 7.6x | 6.9x | 7.8x | 7.8x | 7.8x | 6.3x | 3.1x | 2.4x | 7.3x | 7.1x | 6.7x | 6.9x | 7.2x | 7.3x |
Table 11
Company-projected vs. actual reported net leverage (no sponsor) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
--2015-2020 cohort-- | --2020 cohort-- | --2019 cohort-- | --2018 cohort-- | --2017 cohort-- | --2016 cohort-- | --2015 cohort-- | ||||||||
Year 1 | Year 2 | 2021 | 2022 | 2020 | 2021 | 2019 | 2020 | 2018 | 2019 | 2017 | 2018 | 2016 | 2017 | |
Average miss | 2.4x | 2.7x | 1.8x | 1.4x | 2.3x | 4.3x | 4.3x | 2.5x | 0.0x | 0.0x | 2.3x | 3.1x | 1.0x | 1.3x |
Median miss | 1.6x | 1.7x | 1.1x | 1.4x | 1.7x | 1.8x | 1.8x | 1.7x | 0.0x | 0.0x | 1.4x | 1.2x | 1.0x | 1.3x |
Highest miss | 29.3x | 19.4x | 4.5x | 3.0x | 10.2x | 12.8x | 29.3x | 11.2x | 0.0x | 0.0x | 15.2x | 19.4x | 1.8x | 2.4x |
Total count | 67 | 67 | 4 | 4 | 10 | 10 | 13 | 13 | 0 | 0 | 13 | 13 | 2 | 2 |
# exceed proj. | 15 | 14 | 0 | 1 | 2 | 3 | 2 | 2 | 0 | 0 | 4 | 3 | 0 | 0 |
% exceed proj. | 22% | 21% | 0% | 25% | 20% | 30% | 15% | 15% | 0% | 0% | 31% | 23% | 0% | 0% |
# missed >0x | 52 | 53 | 4 | 3 | 8 | 7 | 11 | 11 | 0 | 0 | 9 | 10 | 2 | 2 |
% missed >0x | 78% | 79% | 100% | 75% | 80% | 70% | 85% | 85% | 77% | 85% | 69% | 77% | 100% | 100% |
# missed >1x | 44 | 44 | 2 | 3 | 8 | 5 | 10 | 10 | 0 | 0 | 7 | 7 | 1 | 1 |
% missed >1x | 66% | 66% | 50% | 75% | 80% | 50% | 77% | 77% | 0% | 0% | 54% | 54% | 3% | 3% |
# missed >=2x | 25 | 30 | 1 | 1 | 3 | 5 | 6 | 6 | 0 | 0 | 5 | 6 | 0 | 1 |
% missed >=2x | 37% | 45% | 25% | 25% | 30% | 50% | 46% | 46% | 0% | 0% | 39% | 46% | 0% | 3% |
# missed >=3x | 16 | 19 | 1 | 0 | 1 | 4 | 4 | 4 | 0 | 0 | 3 | 4 | 0 | 0 |
% missed >=3x | 24% | 28% | 25% | 0% | 10% | 40% | 31% | 31% | 0% | 0% | 23% | 31% | 0% | 0% |
# missed >=5x | 7 | 11 | 0 | 0 | 1 | 3 | 3 | 2 | 0 | 0 | 1 | 2 | 0 | 0 |
% missed >=5x | 10% | 16% | 0% | 0% | 10% | 30% | 23% | 15% | 0% | 0% | 8% | 15% | 0% | 0% |
Projected leverage (average) | 3.3x | 2.6x | 3.4x | 2.7x | 3.2x | 2.5x | 3.3x | 2.6x | 3.6x | 2.9x | 4.4x | 3.6x | 3.0x | 2.6x |
Actual leverage (average) | 5.7x | 5.3x | 5.3x | 4.0x | 5.4x | 6.8x | 7.2x | 5.2x | 5.6x | 4.2x | 8.0x | 7.1x | 4.0x | 3.8x |
Projected leverage (median) | 3.3x | 2.5x | 3.4x | 2.5x | 3.0x | 2.3x | 3.2x | 2.6x | 3.5x | 3.0x | 4.6x | 3.7x | 3.0x | 2.6x |
Actual leverage (median) | 5.0x | 4.6x | 4.8x | 4.4x | 4.6x | 4.4x | 5.6x | 5.0x | 5.4x | 3.7x | 6.7x | 6.9x | 4.0x | 3.8x |
Conclusion: Inflated Addbacks Illustrate Overall Weak Creditor Protections
Weakened protections and loose loan documentation are front and center in almost all outreach discussions we have with investors. Expansive EBITDA definitions resulting in egregious addbacks are a significant contributing factor. Such addbacks can certainly create higher future event risk because company-adjusted EBITDA often defines the size and flexibility companies have to take actions under debt agreements. This may weaken credit quality through various free and clear baskets and incurrence tests that define a company's ability to add debt, pay dividends, transfer assets, etc., as well as the springing financial maintenance tests on revolving credit facilities. A company with negative reported EBITDA could incur significant incremental debt due to the definitional construct of EBITDA.
Our six-year study continues to underscore that addbacks and company-adjusted EBITDA are a poor predictor of profitability. Our substantial dataset makes it clear that management teams and equity sponsors regularly miss their projections by a large margin, and that the magnitude of the misses is positively correlated with addbacks and firms that we rate lower. This suggests that inflated addbacks may help companies with higher financial risk get deals done.
About Our Analysis
Our Approach To EBITDA
S&P Global Ratings defines EBITDA as revenue minus operating expenses plus depreciation and amortization (including noncurrent asset impairment and impairment reversals). This definition generally adheres to what EBITDA stands for: earnings before interest, taxes, depreciation, and amortization.
However, it excludes other income-statement activities that we view as nonoperating. We exclude adjustments for items such as management fees and restructuring costs. We include cash dividends from investments accounted for under the equity method and exclude the company's share of these investees' profits. We often give some credit to addbacks or synergies that we view as achievable, especially when a company--or a particular sponsor--has demonstrated such ability in past comparable transactions. Even then, we allocate this credit only during periods when we expect it to achieve the benefits (net of associated costs) rather than baking these factors into pro forma metrics as is the convention with marketing EBITDA.
Our projections reflect that we are almost always considerably less optimistic than management regarding some aspects of growth, such as realizable revenue and cost synergies. Our analysis goes much deeper than EBITDA and examines issuers' true cash flow characteristics.
This report does not constitute a rating action.
Primary Credit Analyst: | Olen Honeyman, New York + 1 (212) 438 4031; olen.honeyman@spglobal.com |
Secondary Contacts: | Steve H Wilkinson, CFA, New York + 1 (212) 438 5093; steve.wilkinson@spglobal.com |
Minesh Patel, CFA, New York + 1 (212) 438 6410; minesh.patel@spglobal.com | |
Research Assistants: | Evangelos Savaides, New York |
Bryan A Ayala, New York | |
Analytical Group Contact: | Ramki Muthukrishnan, New York + 1 (212) 438 1384; ramki.muthukrishnan@spglobal.com |
No content (including ratings, credit-related analyses and data, valuations, model, software, or other application or output therefrom) or any part thereof (Content) may be modified, reverse engineered, reproduced, or distributed in any form by any means, or stored in a database or retrieval system, without the prior written permission of Standard & Poor’s Financial Services LLC or its affiliates (collectively, S&P). The Content shall not be used for any unlawful or unauthorized purposes. S&P and any third-party providers, as well as their directors, officers, shareholders, employees, or agents (collectively S&P Parties) do not guarantee the accuracy, completeness, timeliness, or availability of the Content. S&P Parties are not responsible for any errors or omissions (negligent or otherwise), regardless of the cause, for the results obtained from the use of the Content, or for the security or maintenance of any data input by the user. The Content is provided on an “as is” basis. S&P PARTIES DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE OR USE, FREEDOM FROM BUGS, SOFTWARE ERRORS OR DEFECTS, THAT THE CONTENT’S FUNCTIONING WILL BE UNINTERRUPTED, OR THAT THE CONTENT WILL OPERATE WITH ANY SOFTWARE OR HARDWARE CONFIGURATION. In no event shall S&P Parties be liable to any party for any direct, indirect, incidental, exemplary, compensatory, punitive, special or consequential damages, costs, expenses, legal fees, or losses (including, without limitation, lost income or lost profits and opportunity costs or losses caused by negligence) in connection with any use of the Content even if advised of the possibility of such damages.
Credit-related and other analyses, including ratings, and statements in the Content are statements of opinion as of the date they are expressed and not statements of fact. S&P’s opinions, analyses, and rating acknowledgment decisions (described below) are not recommendations to purchase, hold, or sell any securities or to make any investment decisions, and do not address the suitability of any security. S&P assumes no obligation to update the Content following publication in any form or format. The Content should not be relied on and is not a substitute for the skill, judgment, and experience of the user, its management, employees, advisors, and/or clients when making investment and other business decisions. S&P does not act as a fiduciary or an investment advisor except where registered as such. While S&P has obtained information from sources it believes to be reliable, S&P does not perform an audit and undertakes no duty of due diligence or independent verification of any information it receives. Rating-related publications may be published for a variety of reasons that are not necessarily dependent on action by rating committees, including, but not limited to, the publication of a periodic update on a credit rating and related analyses.
To the extent that regulatory authorities allow a rating agency to acknowledge in one jurisdiction a rating issued in another jurisdiction for certain regulatory purposes, S&P reserves the right to assign, withdraw, or suspend such acknowledgement at any time and in its sole discretion. S&P Parties disclaim any duty whatsoever arising out of the assignment, withdrawal, or suspension of an acknowledgment as well as any liability for any damage alleged to have been suffered on account thereof.
S&P keeps certain activities of its business units separate from each other in order to preserve the independence and objectivity of their respective activities. As a result, certain business units of S&P may have information that is not available to other S&P business units. S&P has established policies and procedures to maintain the confidentiality of certain nonpublic information received in connection with each analytical process.
S&P may receive compensation for its ratings and certain analyses, normally from issuers or underwriters of securities or from obligors. S&P reserves the right to disseminate its opinions and analyses. S&P's public ratings and analyses are made available on its Web sites, www.spglobal.com/ratings (free of charge), and www.ratingsdirect.com (subscription), and may be distributed through other means, including via S&P publications and third-party redistributors. Additional information about our ratings fees is available at www.spglobal.com/usratingsfees.