This report does not constitute a rating action.

S&P Global Ratings' seventh annual analysis of EBITDA addbacks continues to show that these costs or future earnings, which companies claim will either roll off or occur in the future, and thus add to their measure of EBITDA while marketing to investors, represent a big chunk of management-adjusted EBITDA at deal inception (28% on a median basis over the life of the study) and that management projections in marketing materials have proven aggressive. This further substantiates that most U.S. speculative-grade corporate issuers present unrealistic earnings, debt, and leverage projections in their marketing materials at deal inception.

Our study supports this, showing a median leverage miss of 2.3x in the first year following deal inception and 2.6x in the second. These two factors--the magnitude of addbacks and severity of projection misses--are not mutually exclusive. Our data shows that aggressive addbacks generally correlate to unreliable projections and that, generally, EBITDA adjustments do not provide an accurate picture of future earnings.

We explored the relationship between the magnitude of addbacks and projection performance, measured by projected leverage misses in the two years following deal inception (see charts 1 and 2). The two extremes in both years of performance data (leverage miss of <1 turn and >5 turns) comprise a significant portion of the sample, and by focusing on them, our data shows that addbacks as a percentage of management-adjusted EBITDA (which we refer to as “marketing EBITDA”) were 30%-35% for the worst performing transactions.

Chart 1

Chart 2

View our interactive dashboard for a deeper, more immersive view of from our seven-year study.

Our analysis consists of three main components:

• Part 1 of the study focused on the validity and accuracy of addbacks by comparing issuers' projected, adjusted EBITDA at deal inception with actual reported EBITDA for the two fiscal years following the year of deal origination, accounting for the lag in measuring performance data in our study. Specifically, the two-year performance measurement period provides time for one-time items to fall away and provides management ample opportunity to deliver on the vast majority of projected synergies. Given the difficulty and limited visibility in earnings breakouts, we cannot parse out the specific components of addbacks to determine individual line-item realizations. As we noted in our earlier studies, other factors besides overstated addbacks may contribute to the difference between management projected and reported EBITDA, such as unmaterialized growth, integration missteps for mergers and acquisitions (M&A), unforeseen operational issues, and more.
• The second part of the study focused on the magnitude and distribution of addbacks. Here, we tracked and quantified the evolution of addbacks since 2015. Of the six categories of addbacks we tracked, synergies have been the largest component by a wide margin. Often esoteric, synergies are also the most difficult to predict and model.
• Finally, we present insights from combining the data from both study sections, given the correlation between projection performance and the magnitude of addbacks.

S&P Global Ratings projections are independent

We derive our ratings and financial risk analysis metrics from our projections and analytical judgments. While our findings serve as a warning of the potential perils of uncritically accepting management forecasts, we base our ratings on S&P Global Ratings independent projections of a company's expected earnings, a balanced view of their capacity and appetite for debt repayment, and our assessment of business and financial factors such as management and board governance, as well as 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).

The Validity And Accuracy Of EBITDA Addbacks

Marketing EBITDA definitions are increasingly inconsistent and bloated

Sponsors, deal arrangers, and management teams remain inventive in engineering and marketing what qualifies as an addback in deal documentation. This has led to a rise in the number, types, and overall magnitude of adjustments, thereby increasing the complexity of analyzing and assessing addbacks. For example, the COVID-19 crisis created a new category of adjustments related to cost and revenue impacts stemming from the pandemic and related mitigation measures. Additionally, we could see a myriad of future addbacks relating to the current tariff dynamic. For example, sectors that could face international trade disruptions might include addbacks for supply chain optimization.

In many of these cases, S&P Global Ratings views the ever-expanding definition of marketing EBITDA as an inflation of profitability and an artificial deflation of leverage. This results in understated valuation multiples, thus improving the optics and marketability of a transaction. The lack of a standardized definition of EBITDA is of critical importance, making it quite challenging for investors to compare transactions on a like-for-like basis absent dissecting and comparing what may be two-page definitions of EBITDA. In practice, it is and has always been a negotiated definition, varying from agreement to agreement. Compounding this, lender negotiating power to demand specific provisions is generally weak in the syndicated debt markets.

While investors should determine how best to gauge EBITDA and deal leverage, it is still critical that debt investors understand the magnitude and persistence of the shortfall in marketing versus actual EBITDA and its resulting impact on leverage, as our study underscores. Further, an expansive definition of EBITDA--providing a myriad of addbacks in a company's debt agreements--may well present incremental event risk because it often provides additional headroom under negative covenants and restricted payments (including dividends, debt, investments, and lien allowances). The credit quality of any given company could deteriorate dramatically as a result of expanded debt capacity, given somewhat suspect EBITDA definitions over the life cycle of an investment.

Overview of findings

At deal inception, management teams almost universally contend there is considerable upside to their base-case projections and limited downside risk. We also frequently hear that projected realizable synergy estimates are conservative. According to our data, only 8% of the companies in our sample exceeded earnings projections in the year following deal inception, meaning 92% failed to meet those first-year projections. In our seven-year performance study, almost 50% of the companies missed earnings projections by more than 33%.

Overstated debt repayment also contributes to the overall leverage miss, but to a lesser degree. The median miss in projected debt levels in the seven-year study was 3% in the first year following deal conception, growing to 15% in the second.

For the 250 transactions in our seven-year study, management missed leverage projections on a median basis by 2.3x in year one and 2.6x in year two following deal inception.

The latest cohort of transactions that originated in 2021 performed somewhat better, missing by 2.1x in the first year and 2.2x in the second. This is primarily attributable to improved earnings projection performance, partially offset by weaker-than-average debt projection performance.

Table 1

Transactions originated during 2015-2021
Company projected vs. net reported
EBITDA*			Debt					Leverage§
	Year 1	Year 2		Year 1	Year 2		Year 1	Year 2
Exceeded projection	8%	17%	Exceeded projection	36%	24%	Exceeded projection	16%	15%
Missed >0%	92%	83%	Missed >0%	64%	76%	Missed >0x	84%	85%
Missed >=10%	82%	73%	Missed >=10%	35%	62%	Missed >=1x	74%	75%
Missed >=25%	60%	59%	Missed >=25%	18%	36%	Missed >=2x	54%	59%
Missed >=33.3%	48%	52%	Missed >=33.3%	13%	33%	Missed >=3x	38%	42%
Missed >=50%	23%	28%	Missed >=50%	12%	27%	Missed >=5x	21%	26%
Average miss	30%	30%	Average miss	8%	26%	Average miss	3.6x	3.8x
Median miss	32%	34%	Median miss	3%	15%	Median miss	2.3x	2.7x
*Company projections are adjusted EBITDA. §The leverage calculation is based on average debt to EBITDA of each company in the sample.

Table 2

Transactions originated during 2021
Company projected vs. net reported
EBITDA*			Debt			Leverage§
	2022	2023		2022	2023		2022	2023
Exceeded projection	24%	22%	Exceeded projection	20%	12%	Exceeded projection	27%	20%
Missed >0%	76%	78%	Missed >0%	80%	88%	Missed >0x	73%	80%
Missed >=10%	68%	66%	Missed >=10%	46%	73%	Missed >=1x	66%	71%
Missed >=25%	41%	51%	Missed >=25%	32%	46%	Missed >=2x	51%	54%
Missed >=33.3%	37%	39%	Missed >=33.3%	24%	44%	Missed >=3x	41%	39%
Missed >=50%	24%	15%	Missed >=50%	22%	34%	Missed >=5x	27%	24%
Average miss	14%	21%	Average miss	16%	33%	Average miss	3.7x	3.8x
Median miss	21%	25%	Median miss	9%	21%	Median miss	2.1x	2.2x
*Company's projections are adjusted EBITDA. §The leverage calculation is based on average debt to EBITDA of each company in the sample.

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 for each cohort. 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, in a covenant-lite loan environment, 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 been effective in realizing projected synergies. This permits certain cost addbacks (such as transaction fees and expenses, as well as restructuring costs) to roll off. This timeframe is relatively standard in company projection models for realizing anticipated synergies.

Further, just like in our earlier reviews, we eliminated companies that underwent a material/transformative M&A or leveraged buyout (LBO) within two years of deal inception. This enabled us to remove distortion following subsequent transformative events (e.g., new debt issuance or earnings affected by subsequent acquisitions), 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.

In addition, we cannot disclose company names because management projections presented to S&P Global Ratings at deal inception are confidential.

Aggressive EBITDA projections drive underestimated leverage

If management projections proved realistic, we would expect to see reported results catching up to projected results as companies realize anticipated earnings, one-time items fall away, and synergies are achieved. In actuality, as opposed to a convergence in results, our study continues to show a rather dramatic divergence. In addition to management-inflated EBITDA, the deviation could be in part attributable to other factors, including unmaterialized growth projections, operating challenges, and unrealized synergies or unattained cost savings.

Our seven-year study shows that just 8% of companies met or exceeded earnings projections in the first year following deal inception and 17% in the second year. The median miss in the first year was 32%, growing to 34% in the second (see table 3).

However, recent data suggests that aggressive projections may be tempering. The latest two cohorts in our performance study have shown an improvement in earnings projections. For the 2020 cohort, first-year projections outperformed the average of the five preceding cohorts by 22%, with the average miss declining to 26% compared to the long-term average of 33% for the five preceding cohorts. Performance in the second year was significantly better, with earnings projections improving by 43% compared to the prior cohorts. The median miss improved against the long-term average by 14% in year one and 19% in year two.

Improvements in earning projections continue to accelerate with the 2021 cohort. The first year of projections bested the average of the six preceding cohorts by 56%, with the average miss declining to 14% against the long-term average of 31% for the six preceding cohorts. The improvement in year two was less pronounced, with the average miss improving by 33%. The median miss compared to the long-term average improved by 29% in the first year and 22% in the second.

Table 3

Company projected vs. actual reported EBITDA
Cohort	2015-2021		2021		2020		2019		2018		2017		2016		2015
	Year 1	Year 2	2022	2023	2021	2022	2020	2021	2019	2020	2018	2019	2017	2018	2016	2017
Average miss (%)	30%	30%	14%	21%	26%	19%	39%	30%	36%	39%	27%	30%	35%	35%	29%	34%
Median miss (%)	32%	34%	21%	25%	28%	28%	41%	35%	38%	39%	32%	30%	30%	35%	33%	39%
Highest miss (%)	97%	220%	77%	78%	70%	79%	83%	90%	97%	81%	83%	79%	70%	77%	83%	74%
Total count (no.)	250	250	41	41	27	27	30	30	48	48	41	41	31	31	32	32
Exceeded projections (no.)	21	42	10	9	3	8	1	7	2	7	3	5	0	2	2	4
Exceeded projections (%)	8%	17%	24%	22%	11%	30%	3%	23%	4%	15%	7%	12%	0%	6%	6%	13%
Missed > 0% (no.)	229	208	31	32	24	19	29	23	46	41	38	36	31	29	30	28
Missed > 0% (%)	92%	83%	76%	78%	89%	70%	97%	77%	96%	85%	93%	88%	100%	94%	94%	87%
Missed >=10% (no.)	206	183	28	27	21	16	28	21	42	37	34	32	28	26	25	24
Missed >=10% (%)	82%	73%	68%	66%	78%	59%	93%	70%	88%	77%	83%	78%	90%	84%	78%	75%
Missed >=25% (no.)	151	147	17	21	14	15	24	18	35	32	23	22	20	17	18	22
Missed >=25% (%)	60%	59%	41%	51%	52%	56%	80%	60%	73%	67%	56%	54%	65%	55%	56%	69%
Missed >=33.3% (no.)	121	130	15	16	10	11	19	18	26	29	20	20	15	16	16	20
Missed >=33.3% (%)	48%	52%	37%	39%	37%	41%	63%	60%	54%	60%	49%	49%	48%	52%	50%	63%
Missed >=50% (no.)	57	69	10	6	5	6	8	10	14	17	6	10	10	10	4	10
Missed >=50% (%)	23%	28%	24%	15%	19%	22%	27%	33%	29%	35%	15%	24%	32%	32%	13%	31%

Chart 3

Stated debt reduction rarely realized

Failure to meet projected debt levels also contributed to the significant miss of management-projected leverage, but to a lesser extent than EBITDA misses. Virtually all issuers present a deleveraging story to market participants at deal inception, stating intentions to aggressively sweep surplus cash to reduce debt. Relative to the seven-year sample, the latest 2021 cohort showed a decrease in projection accuracy with respect to anticipated debt levels. This almost fully offset the improvement in earnings projections, resulting in leverage misses that were only slightly better than our seven-year average.

In short, companies' stated intentions to apply surplus cash to pay down debt appear to be infrequently executed. Indeed, companies rarely, if ever, pay down debt to the extent modeled in their projections. Across the seven vintages, 65% of companies kept debt levels in check (by keeping them below projections or within 10% of targets for projected debt) in the first year following origination. That share quickly deteriorated to less 38% by the end of the second year across all cohorts. We netted reported cash balances against reported debt to compute debt and leverage divergence for comparability.

The seven-year median miss in the first year was 3%, and 15% in the second. The substantial misses for the 2020 and 2021 cohorts were comparable to the 2017 cohort and attributable to several outliers that missed debt projections significantly.

Table 4

Company projected vs. actual reported net debt
Cohort	2015-2021		2021		2020		2019		2018		2017		2016		2015
	Year 1	Year 2	2022	2023	2021	2022	2020	2021	2019	2020	2018	2019	2017	2018	2016	2017
Average miss (%)	8%	26%	16%	33%	12%	36%	1%	11%	4%	22%	3%	12%	6%	40%	7%	19%
Median miss (%)	3%	15%	9%	21%	12%	34%	1%	11%	2%	11%	11%	25%	3%	11%	1%	12%
Highest miss (%)	206%	614%	97%	131%	44%	99%	60%	108%	93%	614%	181%	195%	149%	339%	101%	119%
Total count (no.)	250	250	41	41	27	27	30	30	48	48	41	41	31	31	32	32
Exceeded projections (no.)	91	61	8	5	5	1	17	11	22	18	15	10	10	8	14	8
Exceeded projections (%)	36%	24%	20%	12%	19%	4%	57%	37%	46%	38%	37%	24%	32%	26%	44%	25%
Missed > 0% (no.)	159	189	33	36	22	26	13	19	26	30	26	31	21	23	18	24
Missed > 0% (%)	64%	76%	80%	88%	81%	96%	43%	63%	54%	63%	63%	76%	68%	74%	56%	75%
Missed >=10% (no.)	87	154	19	30	15	25	7	15	15	25	13	24	10	16	8	19
Missed >=10% (%)	35%	62%	46%	73%	56%	93%	23%	50%	31%	52%	32%	59%	32%	52%	25%	59%
Missed >=25% (no.)	45	91	13	19	5	18	3	8	8	12	7	12	4	12	5	10
Missed >=25% (%)	18%	36%	32%	46%	19%	67%	10%	27%	17%	25%	17%	29%	13%	39%	16%	31%
Missed >=33.3% (no.)	32	83	10	18	4	14	2	8	6	11	5	10	1	12	4	10
Missed >=33.3% (%)	13%	33%	24%	44%	15%	52%	7%	27%	13%	23%	12%	24%	3%	39%	13%	31%
Missed >=50% (no.)	22	47	8	13	0	7	1	2	5	7	5	8	1	5	2	5
Missed >=50% (%)	9%	19%	20%	32%	0%	26%	3%	7%	10%	15%	12%	20%	3%	16%	6%	16%

Chart 4

Leverage projections have major misses

The combination of the significant misses, particularly in earnings, results in a discrepancy between projected and reported leverage across the seven-year sample. Overly aspirational management-projected EBITDA results in a fictional leverage cushion inconsistent with credit realities. By averaging the median gap across the seven vintages, companies under-projected leverage by an average of over two turns (2.3x) in the first year, increasing to 2.6x by the end of the second (see table 5).

For the 2021 cohort, the median leverage miss outperformed the seven-year median in year one at 2.1x compared to 2.3x. Performance also improved in the second year with a median miss of 2.2x against the long-term average of 2.6x. Again, this is attributable to improved earnings projections, partially offset by overstated debt repayment projections.

Table 5

Company projected vs. actual reported net leverage
Cohort	2015-2021		2021		2020		2019		2018		2017		2016		2015
	Year 1	Year 2	2022	2023	2021	2022	2020	2021	2019	2020	2018	2019	2017	2018	2016	2017
Average miss (x)	3.6x	3.8x	3.7x	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 (x)	2.3x	2.6x	2.1x	2.2x	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 (x)	30.3x	37.6x	22.1x	20.5x	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 (no.)	250	250	41	41	27	27	30	30	48	48	41	41	31	31	32	32
Exceeded projections	39	38	11	8	1	4	3	8	9	9	4	2	6	3	5	4
Exceeded projections (%)	16%	15%	27%	20%	4%	15%	10%	27%	19%	19%	10%	5%	19%	10%	16%	13%
Missed >1x (no.)	186	188	27	29	20	21	25	20	36	37	33	35	22	22	23	24
Missed >1x (%)	74%	75%	66%	71%	74%	78%	83%	67%	75%	77%	80%	85%	71%	71%	72%	75%
Missed >=2x (no.)	135	147	21	22	17	17	14	16	29	26	25	26	13	20	16	20
Missed >=2x (%)	54%	59%	51%	54%	63%	63%	47%	53%	60%	54%	61%	63%	42%	65%	50.0%	62.5%
Missed >=3x (no.)	96	106	17	16	12	13	9	13	21	18	16	16	9	13	12	17
Missed >=3x (%)	38%	42%	41%	39%	44%	48%	30%	43%	44%	38%	39%	39%	29%	42%	38%	53%
Missed >=5x (no.)	52	64	11	10	6	9	7	7	13	11	4	10	5	7	6	10
Missed >=5x (%)	21%	26%	27%	24%	22%	33%	23%	23%	27%	23%	10%	24%	16%	23%	19%	31%
Avg. projected leverage (x)	4.3x	3.5x	4.6x	3.8x	4.6x	3.7x	4.3x	3.5x	4.3x	3.5x	4.2x	3.5x	3.8x	3.0x	4.2x	3.3x
Avg. actual leverage (x)	7.9x	7.3x	8.3x	7.6x	8.3x	8.8x	8.4x	8.0x	8.8x	7.0x	7.1x	6.7x	6.8x	6.3x	7.1x	7.0x
Median projected leverage (x)	4.4x	3.6x	4.5x	3.9x	4.8x	3.9x	4.3x	3.5x	4.6x	3.8x	4.3x	3.6x	3.9x	3.1x	4.2x	3.4x
Median actual leverage (x)	6.7x	6.4x	6.9x	6.7x	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

Magnitude And Composition Of EBITDA Addbacks

The data set

The sample size for our analysis' magnitude and composition is more extensive, encompassing over 650 M&A and LBO transactions that we rated, originated between 2015 and 2023 with deal sizes exceeding $50 million. The set includes only transactions where management provided us with a detailed bridge from reported EBITDA to marketing EBITDA (as is typically the case for large LBO and M&A transactions), such that we can quantify the addbacks and allocate them to six defined categories.

This data set is substantially larger than the first set for two reasons. First, it includes transactions for 2022 and 2023, where we don't yet have the two years of operating results to gauge projection performance. Second, it includes transactions from prior years that we did not use for part one of this study due to a subsequent transformative transaction.

Of the total sample, 57% were M&A transactions and 43% LBO transactions, and 87% by deal count were rated in the 'B' category ('B-', 'B', and 'B+’) at inception, with the remaining 13% in the 'BB' rating category ('BB-', 'BB', and 'BB+'). Finally, more than three-quarters of the transactions in the sample were sponsor-owned.

Chart 6a

Chart 6b

Chart 6c

We compared the magnitude of addbacks to both last-12-months reported EBITDA excluding addbacks, as well as management-adjusted EBITDA inclusive of addbacks at deal inception. On average, in the nine years of EBITDA magnitude data in our study, addbacks made up over 28% of marketing EBITDA, and about 52% of last-12-months reported EBITDA (see chart 7). Over nine years, this forward-looking measure of addbacks as a percent of marketing EBITDA trended up for the first seven years, growing to 32% in 2021 from 24% in 2015. The upward trend reversed in 2022, with addbacks comprising 29% of management-adjusted EBITDA, further decreasing to 26% in 2023.

At the outset of this study, we illustrated the correlation between the magnitude of addbacks and the accuracy of management projections. The recent decrease in addback percentage may be a leading indicator of continued improvement in management projection performance.

Across the nine-year sample, the ratings distribution has shifted toward issuers rated 'B'. We found that regardless of transaction type, credits in the 'B' ratings category led their higher-rated 'BB' category counterparts in the average adjustment amount. The line of demarcation in our data set is the 2018 cohort of transactions. In the 2015-2017 cohorts, 'BB' category transactions comprised an average of 20% of the data set. From 2018-2023, 'BB' category credits averaged about 10% of the sample.

Chart 7

Synergies are the largest component of addbacks

Expected synergies and projected cost savings are the largest components of addbacks. We sorted general addback adjustments into six broad categories (see chart 8). In every cohort but one, synergies and cost savings led over other adjustment types. It peaked in 2016 at nearly 39%, with a nine-year average of 28%.

Synergies are often the most difficult of the common addbacks to forecast accurately. We rarely factor the full amount of management-anticipated synergies into our projections, and we never factor this in prospectively before such benefits might be achieved. Instead, we have detailed discussions with management teams and their advisors regarding expected synergies and adjust for what we believe to be achievable and under what timeframe. It often depends on the source of synergy and, when relevant, whether a company or sponsor has a demonstrated track record in realizing similar synergies or cost savings from past transactions.

While some synergies 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. Also, some synergies are costly to implement, requiring an upfront expense, such as severance pay.

Restructuring costs are another area of disparity in treatment. We generally treat ongoing restructuring charges as operating costs because most companies need to restructure their operations to adapt to changing environments and remain competitive. Similarly, as in our approach to EBITDA, management fees constitute a cash operating cost and we treat them as such. For this reason, we do not add back restructuring costs or management fees in our calculation of adjusted EBITDA. In addition, this data demonstrates how far off companies' original assumptions tend to be about the future realization of addbacks. That said, we include all negotiated addbacks in our study.

Chart 8

Technology, health care, and media lead the pack

The technology, health care, and media, entertainment, and leisure sectors had the most addback-inflated EBITDA--around 35%--when comparing the nine-year average of total addbacks to company marketing EBITDA at deal inception. This compares to the average of all other sectors combined of about 25%. These sectors have consistently topped the list and buoy the entire sample, given the disproportionate representation of about 44% of the deal count.

Table 6

Average addback by sector
Sector	No. of companies	Average of total addbacks/reported LTM EBITDA at inception (%)	Average of total addbacks/company pro forma adjusted EBITDA at inception (%)
High technology	132	67.4	35.6
Health care	92	61.3	34.0
Media, entertainment, and leisure	64	46.3	34.0
Telecommunications	7	57.0	32.3
Insurance services	10	67.3	31.8
Chemicals	17	60.0	30.8
Finance company	3	48.8	29.7
Transportation	20	47.1	28.5
Auto/trucks	22	42.7	27.7
Capital goods/machine and equipment	76	65.6	26.4
Consumer products	50	66.0	25.1
Restaurants/retailing	30	44.0	24.4
Business and consumer services	65	34.5	22.2
Aerospace/defense	17	40.6	22.2
Oil	3	25.3	20.1
Forest products/building materials/packaging	37	23.8	18.0
Mining and minerals	6	22.4	17.7
Total	651	54.1	29.2
LTM--Last 12 months.

Chart 9

Table 7

Addbacks by transaction type, ICR, and ownership
	Count (no.)	Transaction costs (%)	Restructuring (%)	Non-recurring operating (%)	Cost savings, synergies (%)	Mgmt fee, exec comp (%)	Other adj. (%)	Addback to marketing EBITDA (%)	Addback to reported EBITDA (%)
ICR
'B' ratings category	566	14	20	15	27	11	14	30	56
'BB' ratings category	85	6	18	6	34	19	16	23	44
Total	651	13	20	14	28	12	14	29	54
Transaction type
LBO	278	11	20	17	26	11	15	27	49
M&A	373	15	19	11	29	12	14	30	58
Total	651	13	20	14	28	12	14	29	54
Ownership
Not sponsored	164	9	21	9	31	16	14	27	48
sponsored	487	15	19	15	27	10	14	30	56
Total	651	13	20	14	28	12	14	29	54
ICR--Issuer credit rating. Mgmt--Management. Exec comp--Executive compensation. Adj.--Adjusted. LBO--Leveraged buyout. M&A--Mergers and acquisitions.

Lower credit quality generally corresponds to higher addbacks

In our sample of over 650 transactions that originated between 2015 and 2023, 87% were rated in the 'B' ratings category. Our study shows that these companies have consistently underperformed 'BB' category issuers in projecting earnings. The need for aggressive adjustments to make a deal saleable is likely diminished for companies rated in the 'BB' category as their pro forma leverage is typically lower, so addbacks tend to be less aggressive or aspirational. In addition, lower-rated issuers tend to be smaller and have higher earnings volatility, which could make projections more difficult.

Furthermore, financial sponsor ownership is more common among lower-rated entities than those in the 'BB' category. Our data shows that sponsor-owned companies tend to be more aggressive, particularly when projecting earnings (see table 8).

Across the seven-year sample, the median leverage miss in the ‘B’ category was 2.6 turns higher than projected in the first year following deal inception, with the gap widening to 2.7 turns in the second. 'BB' category issuers performed significantly better, missing by 1.3 turns in year one and 1.7 turns in year two, further reinforcing the large credit disparity between issuers in the 'B' and 'BB' categories.

Table 8

Average addback by issuer credit rating
	Addback to marketing EBITDA	Addback to reported EBITDA
'B' ratings category	30%	56%
'BB' ratings category	23%	44%
Average	29%	54%

Chart 10

Chart 11

Projections for LBOs perform worse than M&As

Consistent with our prior studies, LBO and M&A transactions are comparable in the amount of addbacks as a percentage of marketing EBITDA, at 27% and 30%, respectively. However, the distribution of addbacks differs. As expected, M&A transactions showed above-average addbacks for synergies and cost savings because these are often a selling point of the transaction.

LBO transactions have consistently underperformed M&A deals in projecting leverage for every cohort in our study. In our seven-year study, on a median basis, M&A transactions missed by 1.9 turns in the first year following deal inception and 2.2 turns in the second. This compares to LBOs missing by 2.6 and 2.9 turns, respectively. For comparison, within our financial risk categories, the difference between the midpoints of two different categories (e.g., significant and aggressive) is 1.0 turn of leverage.

Table 9

Average addback by transaction type
	Addback to marketing EBITDA	Addback to reported EBITDA
LBO	27%	49%
M&A	30%	58%
Average	29%	54%
LBO--Leveraged buyout. M&A--Mergers and acquisitions.

Chart 12

Chart 13

Sponsored deals significantly underperform nonsponsored

Sponsored transactions tend to be more aggressive than nonsponsored with respect to the magnitude of addbacks, but not by a significant margin. Projection performance is a vastly different story, however.

The nine-year average of addbacks as a percentage of management projected EBITDA for sponsored deals was 29% versus 27% for nonsponsored. Nonsponsored deals were generally about 25% each year with little fluctuation, except for deals that originated in 2021, when nonsponsored transactions averaged 36% versus 31% for sponsored. This stemmed from one extreme outlier in the nonsponsored sample. Removing that transaction results in an average of 29%, which is more consistent with the other cohorts. Of the 651 transactions in our data set, 487 were sponsored, while 164 were not.

We also noted a significant disparity by individual sponsors in terms of their aggressiveness in the use of addbacks. We looked at the 40 sponsors that had completed at least four transactions in our data set. Of those, the 10 most aggressive firms (accounting for 79 transactions) had addbacks averaging 43% of marketing EBITDA. Conversely, the 10 least aggressive sponsors (62 transactions) averaged 16%.

Chart 14

Sponsored transactions significantly underperformed nonsponsored transactions, with respect to the accuracy of the projections at deal inception (see tables 12 and 13). Our seven data cohorts show the median miss for sponsored transactions was 2.7 turns in the first year following deal inception, increasing to 2.9 turns in the second. This compares to a median miss for nonsponsored deals of 1.5 turns in year one and 1.6 turns in year two. The performance gap for the 2021 cohort was significantly wider than the long-term historical median differential. While sponsored deals’ median miss of 2.7x equaled the long-term average in year one, nonsponsored transactions outperformed leverage projections by 0.3x--a first in the history of this study.

Table 10

Company-projected vs. actual reported net leverage, sponsor-owned
Cohort	2015-2021		2021		2020		2019		2018		2017		2016		2015
	Year 1	Year 2	2022	2023	2021	2022	2020	2021	2019	2020	2018	2019	2017	2018	2016	2017
Average miss (x)	4.2x	4.3x	4.4x	4.4x	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 (x)	2.7x	2.9x	2.7x	2.4x	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 (x)	30.3x	37.6x	22.1x	20.5x	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 (no.)	176	176	34	34	23	23	20	20	33	33	28	28	18	18	30	30
Exceeded projection (no.)	19	21	6	5	1	3	1	5	6	7	1	0	2	0	1	2
Exceeded projections (%)	11%	12%	18%	15%	4%	13%	5%	25%	18%	21%	4%	0%	11%	0%	3%	7%
Missed >0x (no.)	157	155	28	29	22	20	19	15	27	26	27	28	16	18	29	28
Missed >0x (%)	89%	88%	82%	85%	96%	87%	95%	75%	82%	79%	96%	100%	89%	100%	97%	93%
Missed >1x (no.)	140	142	25	27	18	18	17	15	25	25	25	25	15	15	23	23
Missed >1x (%)	80%	81%	74%	79%	78%	78%	85%	75%	76%	76%	89%	89%	83%	83%	77%	87%
Missed >=2x (no.)	109	115	20	20	16	16	11	11	22	18	20	22	8	14	17	22
Missed >=2x (%)	62%	65%	59%	59%	70%	70%	55%	55%	67%	55%	71%	79%	44%	78%	57%	73%
Missed >=3x (no.)	79	85	16	14	11	13	8	9	16	13	12	15	6	9	14	17
Missed >=3x (%)	45%	48%	47%	41%	48%	57%	40%	45%	48%	39%	43%	54%	33%	50%	47%	57%
Missed >=5x (no.)	45	53	11	10	6	9	6	4	10	9	3	10	4	5	6	11
Missed >=5x (%)	0.3%	0.3%	0.3%	0.3%	0.3%	0.4%	0.3%	0.2%	30%	27%	11%	36%	22%	28%	20%	37%
Avg. projected leverage (x)	4.7x	3.9x	4.8x	4.0x	4.8x	3.9x	4.8x	4.1x	4.6x	3.9x	4.5x	3.8x	4.4x	3.6x	4.3x	3.4x
Avg. actual leverage (x)	8.9x	8.2x	9.3x	8.4x	8.8x	9.6x	9.9x	8.6x	9.5x	7.7x	7.7x	7.9x	8.0x	7.1x	7.8x	7.7x
Median projected leverage (x)	4.8x	3.9x	5.0x	4.2x	4.8x	3.9x	5.0x	4.3x	4.8x	4.0x	4.8x	3.9x	4.6x	3.7x	4.4x	3.7x
Median actual leverage (x)	7.6x	7.0x	7.8x	7.3x	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
Cohort	2015-2021		2021		2020		2019		2018		2017		2016		2015
	Year 1	Year 2	2022	2023	2021	2022	2020	2021	2019	2020	2018	2019	2017	2018	2016	2017
Average miss (x)	2.2x	2.5x	0.2x	0.9x	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 (x)	1.5x	1.7x	-0.3x	0.9x	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 (x)	29.3x	19.4x	3.9x	4.8x	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 (no.)	74	74	7	7	4	4	10	10	13	13	0	0	13	13	2	2
Exceeded projection (no.)	20	17	5	3	0	1	2	3	2	2	0	0	4	3	0	0
Exceeded projections (%)	27%	23%	71%	43%	0%	25%	20%	30%	15%	15%	0%	0%	31%	23%	0%	0%
Missed >0x (no.)	54	57	2	4	4	3	8	7	11	11	0	0	9	10	2	2
Missed >0x (%)	73%	77%	29%	57%	100%	75%	80%	70%	85%	85%	77%	85%	69%	77%	100%	100%
Missed >1x (no.)	46	46	2	2	2	3	8	5	10	10	0	0	7	7	1	1
Missed >1x (%)	62%	62%	29%	29%	50%	75%	80%	50%	77%	77%	0%	0%	54%	54%	3%	3%
Missed >=2x (no.)	26	32	1	2	1	1	3	5	6	6	0	0	5	6	0	1
Missed >=2x (%)	35%	43%	14%	29%	25%	25%	30%	50%	46%	46%	0%	0%	39%	46%	0%	3%
Missed >=3x (no.)	17	21	1	2	1	0	1	4	4	4	0	0	3	4	0	0
Missed >=3x (%)	23%	28%	14%	29%	25%	0%	10%	40%	31%	31%	0%	0%	23%	31%	0%	0%
Missed >=5x (no.)	7	11	0	0	0	0	1	3	3	2	0	0	1	2	0	0
Missed >=5x (%)	0.1%	0.1%	0.0%	0.0%	0.0%	0.0%	0.1%	0.3%	23%	15%	0%	0%	8%	15%	0%	0%
Avg. projected leverage (x)	3.3x	2.6x	3.6x	2.9x	3.4x	2.7x	3.2x	2.5x	3.3x	2.6x	3.6x	2.9x	4.4x	3.6x	3.0x	2.6x
Avg. actual leverage (x)	5.5x	5.1x	3.8x	3.8x	5.3x	4.0x	5.4x	6.8x	7.2x	5.2x	5.6x	4.2x	8.0x	7.1x	4.0x	3.8x
Median projected leverage (x)	3.3x	2.6x	4.1x	3.0x	3.4x	2.5x	3.0x	2.3x	3.2x	2.6x	3.5x	3.0x	4.6x	3.7x	3.0x	2.6x
Median actual leverage (x)	4.7x	4.2x	2.7x	3.1x	4.8x	4.4x	4.6x	4.4x	5.6x	5.0x	5.4x	3.7x	6.7x	6.9x	4.0x	3.8x

Improved Performance, Shrinking Addbacks: Blip Or Shift?

Our study continues to underscore that addbacks and company-adjusted EBITDA are poor predictors of profitability. Our substantial dataset makes it clear that management teams and equity sponsors regularly miss their projections by a large margin and the magnitude of the misses is positively correlated with addbacks and loans, which we rate lower. This suggests that inflated addbacks may help companies with higher financial risk get deals done.

That said, we have seen some positive trends in the data in the last two cohorts. Improving projection performance coupled with a decrease in the magnitude of addbacks could well be a harbinger of more realistic management projections going forward--but only time will tell.

Primary Contact:	Olen Honeyman, New York 1-212-438-4031; olen.honeyman@spglobal.com
Secondary Contacts:	Shannan R Murphy, Boston 1-617-530-8337; shannan.murphy@spglobal.com
	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
	Evangelos Savaides, New York 1-212-438-2251; evangelos.savaides@spglobal.com
	Bryan A Ayala, New York 1-212-438-9012; bryan.ayala@spglobal.com