What Makes a “Good” Company? Lessons for GE

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Graham Copley / Nick Lipinski

203.901.1629/203.989.0412

gcopley@/nlipinski@ssrllc.com

November 10th, 2017

What Makes a “Good” Company? Lessons for GE

  • Good companies share a few traits but the most important, generally overwhelming the others, is appropriate capital allocation. What that means varies for any good company.
    • Poor companies make errors with capital deployment driving down returns and increasing write downs. Better companies do not necessarily carry a lower proportion of intangibles on their balance sheet than the underperformers – they make better deals.
  • The most important word in the bullet above is “appropriate”; no strategies should be the same and the key difference between good and bad appears to be corporate “self-awareness”
    • Capital is only allocated appropriately by those who truly understand their competitive strengths and weaknesses:
      • Technology Edge; Production Cost Edge; Brand Edge; etc.
    • Companies that over-estimate the above invest with the wrong assumptions and generally sit in the lagging group in the analysis below.While GE is not bad enough to make the bottom cut below, if we had just done a 10-year analysis it would have been there.
  • Of the 123 companies in Industrials and Materials analyzed over 20 years – only 14 sit in the upper quintile in terms of years of both EBITDA growth AND stock outperformance.
    • 15 sit in the lower quintile overlap and both groups are shown below.
    • Companies that we believe COULD join the blue group are: GE, DWDP, PX/Linde.

Exhibit 1

Source: Capital IQ and SSR Analysis

*Entered group within past 5 years

Explaining Exhibit 1:

  • The blue group are the good companies (overweight) – the orange group the “bad” (underweight)
  • Any company with an asterisk has entered the group in the last 5 years – so in the blue group these are improving companies and in the orange group these are deteriorating companies. We identify a longer list below – companies that have exited both groups over the same period
  • The discount from normal value measure is a measure of relative value where we have long term consistent data.
  • The SI (Skepticism index) is a measure of alignment with profitability. For example: FSS is not only expensive but it is still discounting a huge improvement in profitability – CBT is expensive but this is more than supported by above normal profits.
  • In the “good” group, GGG, IEX, DHR and EMS Chemie all look like they have moved too far too fast. UTX, MIDD and ECL look most interesting
  • In the “bad” group, EMN, IP and OLN look most interesting to buy – notwithstanding their checkered past; FSS, AIN and Clariant look like shorts.

Overview

When meeting a prospective Institutional or Hedge Fund Client for the first time, I always ask what matters to them when working through their stock selection process. Generally, the answer is specific to the investment criteria of the fund, but invariably the subject of company/management quality comes up. This prompts the obvious second question “how do you measure or define a good company or good management?” At this point the discussion becomes a mixture of the objective and the subjective; focusing on capital allocation, return hurdles, style and credibility.

So, what makes a good company in the eyes of investors?

A good company to invest in with a 6-month horizon may not be a good company for the longer term – there is a price of everything! What we are trying to identify with this report is what are the characteristics of a successful company for the long-term.

The conclusion is that business “self-awareness” is critical.

Appropriate capital allocation decisions define the better companies; but for that to happen companies must know themselves and not pretend or hope that they are something they are not.

  • What are our REAL competitive strengths – things that allow us to drive pricing and margins?
    • How sustainable are they?
  • What are our customers and competitors doing that could disrupt our business?
    • How do we plan for and protect against?
  • Are we cost competitive – how do we stay ahead?
  • How wide is our technology moat – how do we keep it wide?

Whenever we are working for a corporate on a strategy related project our first question is always to ask the company to list what they are best in class at. Where are they number 1? How do they know that? How do they measure it? And what is it worth? It is staggering how many companies cannot answer some of these questions – especially the last one. Often the answers are based on opinion rather than data – if you can’t measure it, you can’t correct or improve it!

GE will be an interesting test case here: guilty of everything that defines a poor company for the last 10-15 years but now saying all of the right things. The test will be on the “self-awareness” front – GE can only develop appropriate strategies for its businesses if it correctly answers and understands the issues listed above.

In short, this analysis causes us to look positively on the companies with the best track record and negatively on those with the worst, but there has to be a valuation overlay as there is a price for everything – a price to sell a great company and a price to buy a bad one. In Exhibit 2 we plot valuation for our better companies and for the worst – in the better group we would be most interested in UTX and concerned about DHR. In the worst group EMN, IP, and OLN look cheap enough to buy and FSS, AIN, and Clariant look over-priced.

Exhibit 2

Source: Capital IQ and SSR Analysis

We have looked at the derivative of the analysis – who is improving/deteriorating. If we had stopped the analysis in 2011 rather than 2016, the improvers are those that have joined the top group or have dropped out of the poor group since 2011: EMS Chemie, IFF, NEU ODFL, and TTC. On the flip side, the following companies would not have been in the poor group if we had cut the analysis in 2011 (or have dropped out of the better group since 2011): Air Liquide, DE, HSC, OSK, PX, and Solvay – these are companies that are deteriorating. Our conclusions are summarized in Exhibit 1. In Exhibit 3 we look at a return on tangible capital measure for each of the two sub-groups – the “bad” guys generally have low returns.

Exhibit 3

Source: Capital IQ and SSR Analysis

So, What Does All This Tell Us? And How Do We Identify The Next Opportunity

In the sections below we outline the methodology behind the analysis in detail, but quickly conclude that Corporate optimism and Complexity are the major culprits.

In all our work on Optimism we have concluded that companies only change direction with regime change. Whether that is a CEO turnover, the arrival of an activist – a hostile take-over bid – something that causes a corporate “slap in the face”. Overly confident CEO’s only want to listen to outside advice that agrees with them rather than advice that challenges and makes them question either elements of strategy or the whole plan. Two anecdotes:

Years ago – as a consultant (much younger and much more naïve), I was asked to help a Southeast Asian country with a feasibility study for a large new chemical facility. We quickly concluded that the investment was inappropriate – the country demand was not there and would not be for years – not competitive for exports etc. We advised them to postpone for several years and were fired on the spot! They did not want advice – they wanted a rubber stamp – someone to agree with them to support financing. They went ahead with the project and the resulting company went bankrupt (twice). This was pre-Asian banking crisis.

Many years later, I was asked by a large US chemical company to help with due diligence with respect to a possible acquisition. Older and wiser, I had the discussion up front about whether the company wanted advice or a rubber stamp. I advised against the deal, as did others they had hired and no bid was made – with the benefit of hindsight this was the right decision for the company and its shareholders.

It comes down to whether a CEO is open minded, willing to listen, and recognizes that he or she cannot know everything and that only seeking internal input leads to potentially dangerous group-think.

  1. John Flannery is talking a very good game at GE – certainly he has acres of wood to chop and hopefully he is taking input from the right people – but if he is as self-aware as he sounds, GE could be as interesting here (or shortly), as Tyco was when Ed Breen took over.
  1. Which leads nicely into DWDP and Ed Breen. Two companies, chronically guilty of Optimism and very Complex which have turned themselves around dramatically over the two years prior to the merger and may only be scratching at the surface of the possible value creation – with simplification coming from the splits.
  1. PX management has the strongest track record for focused cost control and capital allocation and would have been top of the blue list had we stopped the analysis in 2011 (the slower global economy had a magnified impact on the industrial gas industry). The PX/Linde merger is another story that has the right trajectory to us – not complicated and likely to be conservatively managed.

THIS IS WHERE WE WOULD PUT OUR MONEY – THOUGH GE REMIANS A NEAR-TERM RISK. (See prior research.)

Methodology/Data Set

We have analyzed 123 Industrials & Materials companies with 20 years of publicly traded history – 114 US, 9 European – with all market cap ranges considered. When we sum the number of years of EBITDA growth each company has seen over that 20-year period we get the approximate bell curve in Exhibit 4 and have chosen to define a first quartile as the 27 companies with at least 16 years of EBITDA growth. Those companies are listed in Exhibit 5.

Exhibit 4

 Source: Capital IQ and SSR Analysis

Exhibit 5

Source: Capital IQ

Separately, we have done the same analysis for years of outperformance vs the S&P 500. We have taken the S&P 500 as a proxy for the European markets for the non-US stocks, which is clearly a simplification. We get the same shaped bell curve – Exhibit 6, but a different set of companies – Exhibit 7 – with the companies and the overlaps summarized for both sets of analysis in Exhibit 8.

Exhibit 6

Source: Capital IQ and SSR Analysis

Exhibit 7

Source: Capital IQ and SSR Analysis

Exhibit 8

Source: Capital IQ and SSR Analysis

If we do the analysis for the bottom quintiles in the same way we come up with the company lists and overlap shown in Exhibit 9, and when we index the two overlap group’s performance over the last 20 years we get the relative performance/return profile in Exhibit 10. Clearly you want to be in the better group! Note that the better group is not biased towards any specific sector and contains some large and smaller cap names – there is no overwhelming sector or size bias.

Exhibit 9

Source: Capital IQ and SSR Analysis

Exhibit 10

Source: Capital IQ and SSR Analysis

So what do they have in common?

It’s Not Acquisition Spend! The Underperformers Spend More!

Exhibit 11

Source: Capital IQ and SSR Analysis

Nor is it R&D or CapEx! No Real Correlation

Exhibit 12

Source: Capital IQ and SSR Analysis

Exhibit 13

Source: Capital IQ and SSR Analysis

Optimism IS The Key – Driving Overall Capital Allocation – And Complexity Matters

Optimism is, as expected given all of our prior work, inversely correlated with success and is shown clearly in Exhibit 14. We define optimism as consistent over-estimation of performance by management, using January 1st sell side estimates for any company as a proxy for corporate guidance and therefore expectations. We have a large body of work on this subject, but, in summary, optimists are almost always poor capital allocators because they overestimate the expected returns on most investments – most have declining trends to return on capital and most underperform.

In Exhibit 15 we show the results for business complexity. The correlation is not as pronounced as it is for Optimism, but it is there. More complex companies are harder to manage when it comes to appropriate capital allocation. Hard to get an accurate assessment of businesses when you have too many.

Exhibit 14

Source: Capital IQ and SSR Analysis

Exhibit 15