From Power To Profit, Part II

Helmer's Road Best Traveled With Damodaran and Mauboussin

In Part I of From Power To Profit, Helmer’s 7 Powers were introduced and viewed in light of a corporation’s life cycle (Power Progression) but also its potential mathematical value (The Fundamental Equation of Strategy). As a review:

The Fundamental Equation of Strategy was introduced:

It had been derived from a Net Present Value equation, such that:

To revisit the point of the “Where’s The Value?” post . . . this is where I think it is at. Notice, there is no P/E or EBITDA ratio because AT BEST, those are just shorthand notations and does not communicate the actual value drivers. Moreover, the market tends to assign premiums within these multiples that are relative to the company, industry, macro conditions and/or various variables that are difficult to specifically distill. This equation gives you a clear focus.

In Part II, after using Helmer’s construct to identify whether a company can offer true long term value, the next critical step is to know where it is in its life cycle. Even though Helmer describes a 3 stage life cycle as a road map for Power, it obviously does not encompass all the stages an investor needs to know. It does not include when a company enters a period of decline and later, death or other ending (M&A etc.). This is because his focus is on identifying younger, higher performers whose life cycles best demonstrate the effect of the Powers. Even after realizing when we want to be invested, we also have to know when the risk-return profile is less opportune. Thus I will show that is just as important to know what life cycle to invest in after we have found which company fits our multi-bagger profile.

When tackling a challenge, it is often wise to get the best minds and ideas into the mix. Michael Mauboussin’s career has been built around the idea of “consilience” or the unification of knowledge from various disciplines that give us a deeper understanding of a complex topic. Here it is a bit more narrow as we are (only) melding financial models though Mauboussin’s contributions often use seemingly disparate fields such as science, philosophy, epistemology and literature, to name a few, in his investing frameworks.

Here is our next financial model, Aswath Damodaran’s (aka “The Dean of Valuation”) construct on Corporate Finance Across The Life Cycle:

Notice that Damodaran’s layout is similar to Helmer’s, both with timelines, events and expected “sign posts” that can locate where one is. The “Dean of Valuation” instead lists how a company’s 3 cash flow policies should change over each stage.

Despite both charts displaying the obvious notion of a corporation’s life cycle in stages in the abscissa or horizontal axis, it may not be immediately clear how the ordinate or vertical axis in the Helmer figure (“Business Size ($)”) compares to Damodaran’s graphic of revenues and earnings. But because Helmer’s graph refers to Enterprise Value, the DCF he employed in defining Net Present Value in his Fundamental Equation of Strategy syncs with Damodaran’s.

This is where I try to initiate my differentiated view. Helmer’s Power Progression road as signposts that can be melded with Damodaran’s:

This introduces some cashflow guidelines an investor can expect while one sorts out if Powers are present/expected. But let’s go further. Enter Mr. Mauboussin. In “Trading Stages of the Company Life Cycle” his stages are near similar except there is just one “Growth” Stage instead of Damodaran’s “Young Growth” and “High Growth”. To clarify though, Mauboussin here has adopted the work of a Victoria Dickinson (“Cash Flow Patterns as a Proxy for Firm Life Cycle”, pg. 33). Comparing the two:

As most of us will easily attest, the bulk of returns respective to the life cycle are from growing/established companies. CounterPoint Global, Mauboussin’s firm, did studies to demonstrate this.

Moreover, we see that early stage (Introduction Stage) companies did no better than shakeout companies in rewarding shareholders. There is some fascinating data/theories backing this up too (for another day). The salient point here is that knowing where to fish can be just as important as knowing how to fish; and for us, it is identifying companies in their Growth and Maturity phases, while avoiding the rest.

Great, target companies who seem to be headed into their growth and maturity stages of the life cycle. How? Going back to Dickinson, this had nothing to do with firm age, but essentially just the cash flows, in particular, operating and investing cash flows. So to identify our optimal investment periods, I believe trying to identify the notable transition points might be helpful using this construct.

For experienced investors, the above slide is obvious but the nuances here are where the money is made and lost. The best risk-adjusted returns are where Mauboussin identifies companies being in the Growth and Maturity stages. Targeting companies that make the profitability inflection for further analysis calls for tracking their operating and investing metrics to confirm they are in the “sweet spot”.

Bookending this analogy, a company entering the Maturity phase, as evidenced by financing outflows via return of capital should alert us to monitor that cash flow type for the Shake-Out stage (where we look to exit or de-risk).

This leaves us with the critical middle, where overall operating and investing cash flows are unchanged (inflow and outflow, respectively); and likely where most of the money is made. Remember that even with a solid screening process, that there will be many seemingly qualified companies making the cut. We can further differentiate them by looking at their ROICs, as Mauboussin already showed that companies with rising 3 year ROICs are associated with the (most) profitable growth and maturity phases. As a reminder:

So ROIC is a hybrid metric tracking operating AND investing performance we will use to track the life cycle. ROIIC is similar but is more of a 2nd derivative which can be tracked as a canary in the coal mine for ROIC (meaning ROIIC often times will decline or go negative before ROIC and share price tends to follow that afterwards).

The last highlighted metric here, MEROI or Market Expected Return On Investment, is a Mauboussin term used to suss out if expectations for ROIC and ROIIC may be too high and signify possible risk to the downside. This was covered in “MEROI-torious: Parsing Out Expectations”. In a way it is a “reverse DCF”, or sanity check, for ROIIC. From that post, a summary table of the various iterations and normative results:

What range or magnitude of ROIC/ROIIC/MEROI values or spreads merit one’s dollars will be a mix of industry base rates (that may be hard for the retail investor). The majority of retail investors don’t journal their investing decisions based on specific metrics and internal forecasts, much less base rate or competitive analysis on their companies/peers/industries.

That’s all and fine as on my small sampling, the majority of RIAs/hedge fund portfolio managers (PMs) don’t do that either (different post for another time). The few that do are likely those “run silent, run deep” outfits with concentrated, low turnover and high active share portfolios and others heading family offices/smaller portfolios who rarely see the light of day. In my estimation, that has been a big part of my alpha/edge, having a differentiated view with the willingness to put in more work and “turn over more rocks” (hopefully in time and in the right way).

So now melding the 3 constructs:

The NPV curve concept here is important if not exact (as I stylized it). As an investor, it is helpful to visualize what our returns may be based on the life cycle stage we start investing. As to how I came up with this, I will employ the work of my R&D assistant, ChatGPT:

Helmer uses the Blockbuster-Netflix story as one can imagine so the corollary is a direct one. If I could nit-pick, it is important to consider that Damodaran’s “Midlife Crisis” catalyst and Dickinson’s “Shakeout Period” as the harbinger of ultimate decline happens within the “Mature Stable” phase; for Blockbuster, it came early on as it refused to adapt. For other companies or on average, it seems to appear mid to late phase. And another bit of consilience here is evident by the next slide:

Now one last stylized aspect of mine to introduce “Percent of Remaining (Total) Return” or “%RR”, which longitudinally replaces NPV and perhaps not coincidentally is the mirror image of Helmer’s Business size ($). Unlike Helmer who wrote the tome for the business owner, this construct thinks of return in terms of the investor. It tracks that during the desired growth phase, a business’ size will quickly increase, if we translate that to cashflows discounted to NPV and express it as remaining total stock return over time, we get its opposite, or mirror image.

All the concepts still apply: which stages in the lifecycle we want to invest, where the risk is and perhaps the signposts we can use to determine these transitions. If one will accept my stylized NPV and its conversion to Percentage of (Total) Return Remaining (%RR), I will put it ALL TOGETHER in one graphic . . . The AlphaDoc Investment Cycle.

Disclaimer: this is my stylized approximation and a generalization of a successful company’s investment cycle and its signposts . . . From Power To Profit. In practice, it is not as clean but has a higher degree of precision and specificity than my previous schemas and what others appear to use.

For those who have stuck it out this far . . . thank you. There’s just a bit more, a tiny little wrinkle to mark the end of Part II. In identifying the life cycle stage a company is at, in real life it is often NOT a linear progression.

In fact, the same Mauboussin’s article states “Dynamic capability, defined as “the capacity of an organization to purposefully create, extend, or modify its resource base,” explains how companies can migrate from one stage to another. It gave the example of Amazon (AMZN):

The Dot-com crash was the impetus causing Amazon’s 2001 stage to enter “Decline” as the massive bubble demonstrated how abrupt “truncation risk” can be. Note that Mauboussin’s chart on 3 year Transition Rates above, there is a 6% risk of companies starting in the Growth stage and going to the Decline stage. Interesting side trivia, Amazon’s CFO at the time got some timely advice to tap the European markets for funding (convertible bonds) from Morgan Stanley’s Global Technology co-head, who at that time was one Ruth Porat, now President and CIO of Google. So the future head of Google helped save the future of Amazon?!

Looking at other cycles, we see how varied they can be, even within an unusually successful group where they were mostly in the growth and maturity phases:

I also realize that these life cycle stages DO NOT encompass a company’s status in totem. Nvidia and Tesla came precariously close to bankruptcy and did not register a considerable blip. Remember that the reasons behind the characteristics of each stage have to be accounted for/explained. Here are other examples:

I know what some of you are thinking . . . if these stages don’t tell all of the story, what good are they in identifying good and bad investments? This is where the quantamental approach steps in. I had mentioned earlier that one must know what life cycle stage a company is in, but the stage itself does not determine whether to invest or not.

Just because Mauboussin has identified Growth and Maturity stages as the best 3 year TSR periods, doesn’t mean we only invest/stay invested in those stages. It does help us categorize investment in a company along the risk spectrum but the metrics and the story have to give us color.

Looking at the listed cycles of 6 of the Mag 7, except for the early days of Apple and a single year for Nvidia and Tesla, one would have remained invested in them according to the schema. That may have worked for someone ultimately confident in these businesses, but not for most shareholders. The fact you are reading this posts says that you are likely not that. You and I strive to understand and actively decide on how we make our money, even if at times that means exercising active patience and after much consideration, doing . . . nothing.

My approach would be to give those in the Growth and Maturity phases whose stories/metrics match, a lot of leeway (tend to hold/buy). Those whose stages are “unfavorable” (Introduction, Shake-Out, Decline) that one is already NOT invested in, should observe from afar for a more favorable set up. If you own a company and the story/metrics line up with an “unfavorable” stage, your risk management schema should kick in. For those in an “unfavorable stage but the YOUR MEASURED TAKE on the story/metrics are contrarian to MARKET sentiment, your risk management schema still kicks in though anything BUT selling (instead buying/hedging/holding) may make more sense. In flowchart form:

Part II Conclusion:

Helmer’s Power Progression and Fundamental Equation of Strategy as an expression of cashflows is best focused on certain stages of a chosen company’s life cycle. By melding Helmer’s, Damodaran’s and Mauboussin’s (by way of Dickinson’s) life cycles, there are certain sign posts (profitability inflection, capital return) and metrics (company-specific, ROIC, ROIIC and MEROI) that allow us to track and identify not only proven and favorable risk-adjusted periods to invest but also when to protect our money.

While Growth and Maturity stages are optimal and the remainder are riskier, this approach cautions not to rely on nomenclature at the risk of ignoring judgement. Even great companies during epic runs of economic profit and shareholder return had moments of true peril that this strategy seemed blind to, or even contradicted obvious outperformance. But I would not say that was the case, but instead a nugget of contrarianism that most investors lack, but the outstanding ones possess and internalize.

Michael Mauboussin said an investor’s one job is to find your edge . . . that differentiated view. So far in my Power to Profit series, I have attempted to substantiate where mine begins. Stay tuned for Part III.

Thanks for reading,

AlphaDoc