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The times for multiples: Five situations when multiples need more than a second
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THE TIMES FOR MULTIPLES: FIVE SITUATIONS WHEN MULTIPLES NEED MORE THAN A SECOND
LOOK
May 4, 2023 | Article
By Peeyush Karnani and Werner Rehm
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Multiples can be a useful tool for valuation. But in some situations, they can
wind up missing or even distorting the real picture.
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Article (7 pages)
For more than 60 years, Bob Dylan’s “Don’t Think Twice, It’s All Right” has
endured as a brilliant song and a terrible principle for valuation—especially
when it comes to multiples. Managers and finance practitioners should always
think twice about multiples. When multiples are used properly and the correct
peer groups are selected, they can provide a quick estimation, serve as a
reality check against a traditional discounted cash flow model, and slot into
common shorthand. But investment or financial decisions should never be made
based primarily, let alone solely, on multiples.1Marc Goedhart, Vartika Gupta,
Peeyush Karnani, and Werner Rehm, “The times for multiples: Why value creation
always comes first,” McKinsey, March 17, 2023.
In some cases, multiples can be particularly misleading. In this article, we’ll
look at five of the most common situations where multiples can provide an
incomplete or distorted picture.
1. SHOCKS TO AN INDUSTRY OR THE BROADER MARKET
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It’s easiest to compare multiples when conditions hold steady over time: each
12- or 24-month earnings forecast is an iterative prediction of a company’s
earnings over a very long horizon. But during short periods of turbulent change,
the current or 12-month forward multiples can lead to nonsense results; the
short term (informed by current, highly atypical performance) tells investors or
managers little about what cash flow will be after broad turbulence has passed.
Likewise, any future comparison between how a company performed during a crisis
and how its consensus earnings appear after a crisis can be wildly inapt. We’d
expect, for example, that some retailers would sell more at times when people
were “just stocking up before the hoarders get here,”2Gokhan Dogan and John
Sterman, “‘I’m not hoarding, I’m just stocking up before the hoarders get
here.’: Behavioral causes of phantom ordering in supply chains,” Journal of
Operations Management, 2015, Volumes 39–40. or that physical fitness chains
would have lower earnings during pandemic lockdowns. But unless these occasions
are regular and not one-offs, they tell us little to nothing about a company’s
prospects to create value over the longer term.
Market reactions during the initial phase of the COVID-19 pandemic provide a
case in point. Consider the multiples of one biotech company. In the months
leading up to the global pandemic, the company’s forward EBITDA expectations
were negative. When the worldwide health crisis became evident, however, the
company shifted toward developing COVID-19 vaccines. Investors applauded,
sending the company’s two-year3In this case, two fiscal years. enterprise value
(EV) multiple to a dizzying 33-times EBITDA. Over the following months, however,
as the analysts caught up and adjusted their forecasts, the company’s EV/EBITDA
multiple fell and then flattened out to between four and seven times consensus
earnings.
The COVID-19 pandemic’s economic effects, of course, were not limited to single
companies; the crisis affected entire industries. For example, airlines’
earnings declined significantly (Exhibit 1). As a result, earnings multiples for
all major airlines expanded. Why? Because EV incorporates cash flow during and
well after a crisis has passed; when the pandemic first hit, the airlines’
earnings denominator shrank much more than its EV numerator. When travel resumed
a little over a year after the pandemic, multiples quickly corrected to
historical levels. Now, if one were to look back and consider an airline’s
historical multiples during the first year or so of the pandemic, that period
would stand out as an aberration. And conducting a multiples analysis during
those fraught times invited massive error; minor differences in small earnings
estimates led to a wide distribution of one-off multiples.
Exhibit 1
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2. PERIODS OF HEAVY INVESTMENT
Multiples also get distorted when companies incur very large capital
expenditures within a very short span. That may seem counterintuitive, since
capital expenditures are not explicitly included in a typical multiple. However,
consider the following example: Company A, a refinery, has just completed a
major technological upgrade. Its competitor, Company B, will begin investing
tomorrow and continue investing over the next two years for the same technology.
Since the cost of the upgrade is known, all else equal, Company B’s observed net
enterprise value (enterprise value before excess cash) will be lower by the
present value of the upgrade cost. Consequently, the observed EV/EBITDA multiple
will shrink, even though the two refineries will have the same capabilities to
generate cash flows in the long term. The lower multiple doesn’t mean lower
growth. But it would be impossible to know that unless one were to take a closer
look.
The differences between current state and future state are particularly acute
for green start-ups or high-tech companies. They can have very high growth
expectations and mostly negative near-term earnings. Because of the challenge
and expense of scaling up, multiples won’t be a useful way to compare
early-stage companies with peers that are only a few years older. The best
approach for assessing high-growth companies is to go back to discounted cash
flow basics—“back from the potential future”—using probability-weighted
scenarios to arrive at value today.4See Tim Koller, Marc Goedhart, and David
Wessels, Valuation: Measuring and Managing the Value of Companies, Hoboken, NJ:
John Wiley & Sons, 2015.
3. CYCLICAL COMPANIES
A typical commodity company, precisely because it is subject to cycles, will not
have a stable EBITDA. Yet its enterprise value changes much less over time.
That’s because sophisticated investors price in the cycles. As a result, we
typically see marked shifts in forward multiples at different stages during the
commodity cycle. For example, forward multiples at the top of a cycle tend to be
high because of an expected downturn, even though little to no growth is
expected. Consequently, a point-in-time multiple for cyclical companies can be
very deceptive (Exhibit 2). To gain greater insight, we recommend using a
through-cycle multiple or a two- to three-year forward multiple. Practitioners
can also use multiples such as EV over installed capacity, EV per barrel (in the
case of an oil and gas company), or EV over mine reserves (in the case of a
mining company).
Exhibit 2
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4. M&A
When a company announces an acquisition, its market value should reflect its own
value plus any synergies, net of any premium being paid to the target—after
pricing in the possibility that the deal will not close. However, even when a
deal closes and uncertainty is effectively reduced to zero,5In rare situations,
a merger or acquisition can be unwound after closing. forward-multiples will
likely still not be adequately reflected in analysts’ forecasts. Many analysts
do not even adjust numbers reported to typical data aggregators until after
closing, which leads to a distorted “mechanical” multiple. This is especially
the case for deals with a long time lag between announcement and closing.
Consider one large acquisition in the consumer-packaged-goods industry. At
closing, its EV/EBITDA multiple sharply increased to approximately 20 times
EBITDA. In the year before closing, the EV multiple had been 15 times EBITDA,
and two years before closing, it had been 13 times. Soon after the deal closed,
though, the 20-times multiple began to regress to prior levels. Analysts were
now including both the initial earnings impact of the acquisition and a more
informed perspective about expected synergies.
For deals in which the target’s earnings and historical financials are publicly
available, we recommend always double-checking the multiple. This is relatively
easy to do: combine the acquirer’s expected earnings with those of the target
and make a rough forecast to start. You can then refine your analysis from
there, based on changes to EBITDA that one could reasonably expect.
5. CHANGES IN STRATEGY OR BUSINESS MODEL
Companies that announce a new growth or portfolio strategy that shifts their
business mix typically see some change in market expectations. However, given
the disconnect between current profitability and short-term expectations
compared with where the company is headed over a longer time, enterprise value
multiples may not fully represent the company’s long-term trajectory (Exhibit
3).
Exhibit 3
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For example, from 2003 to 2005, one industrial company traded at an EV multiple
of ten to 12 times two-year forward EBITDA. In 2006, the company began to expand
into medtech and life sciences. Yet it took a full decade for the company to
fully transition and its underlying multiples (16 to 20 times earnings) to
reflect the profitability of its new business model. Since the market hadn’t
fully grasped how the company was changing, it also failed to appreciate which
companies were its peers. Indeed, any peer comparison based on its 2006 model
would have been a poor predictor indeed. That’s why it is always best to use
different multiples for each business segment—particularly when a corporation is
changing its businesses.
A current manifestation of this challenge is in the energy sector. One
traditional energy company, for example, has been aggressively transitioning its
portfolio to include renewables. For the first several years of its transition,
the company’s multiple was consistently in line with those of traditional energy
companies, even though it determinedly pushed into alternative energy. Only
after a decade of making the transition—when its renewable portfolio exceeded
more than 20 percent of its business—did the market adjust the company’s
multiples.
Market misses are particularly likely when a company moves more sharply away
from its long-time core businesses. Because a new business model has different
fundamentals, a point-in-time model (for example, EV to one-year forward
earnings) won’t give a full picture of the corporation’s underlying economics
for a longer term. The more a company changes its business mix, the weirder its
multiples may appear—at least before disaggregating into segments. Even in the
age of large databases and AI, practitioners need to look at company details,
economic circumstances, and facts on the ground to correctly apply multiples.
Common sense and a little legwork go a long way.
--------------------------------------------------------------------------------
Used properly, multiples can be an effective supplemental tool. But traditional
EV multiples can provide an incomplete picture or inapposite results during
industry- or market-wide shocks, periods of heavy investment, single points in
time over a longer commodity cycle, after a merger or acquisition has just
closed, and when a company is making profound changes to its business portfolio.
In those cases, it’s always best to think twice about multiples—and sometimes,
more than that.
ABOUT THE AUTHOR(S)
Peeyush Karnani is an associate partner in McKinsey’s New York office, and
Werner Rehm is a partner in the New Jersey office.
The authors wish to thank Satvik Bansal, Marc Goedhart, and Avineet Sadani for
their contributions to this article.
--------------------------------------------------------------------------------
This article was edited by David Schwartz, an executive editor in the Tel Aviv
office.
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