Adapting as an investor

I remember well how much I loved to program computers. As a cadet at the Air Force Academy taking lots of astronautical engineering courses, I had to do a lot of computer programming.  These projects were very complex, requiring precise calculations (to 8 significant digits) of the velocity and position of satellites, antenna pointing angles, terrestrial positions, etc. They were done on 286 Zenith computers without hard-drives, so some programs could rake as long as 24 hours to run.

I love the process, though. No matter how difficult the problem, I could always solve it. It was like a big puzzle: figure out what part of the program went askew, make changes to that one part and test it repeatedly, and keep doing that until you got it right. Then move on to the next part and repeat until you got it all solved. My classmates were frequently amazed that I would have the projects done weeks in advance. I just loved the process.

Investing doesn’t work so easily. The difference is the noisy feedback loop. Orbital mechanics is like clockwork. You know the starting situation, you know the physics, so when something goes off track it is easy to see that it’s wrong, and it is easy to figure out where to jump in and fix it.

With investing, the data is much more noisy. By noisy, I mean there are lots of false signals that things are going well when they won’t in the long run, and that they are going poorly when they will go well in the long run. 

In other words, when you make a change to your investing process, it can take years, perhaps even decades to see if you really have it right. That’s not the happy feedback loop of computer programming with instant and clear feedback.

But, that is the nature of the beast. When you see your results aren’t doing what you expect, you need to make changes to adapt, and then wait another couple of years to see how that worked.

The process is the same as it is with computer programming, but the signal is very noisy, meaning you don’t know if things have actually gone wrong or not, and the feedback loop takes years instead of minutes to complete. 

I have to admit, I still love to solve the puzzle. Just like with computer programming, I’m as committed and convinced that I can get it right.

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

Adapting as an investor

The Lessons Of Oil

Not many outside the investing business have heard of Howard Marks. He is a very successful money manager at Oaktree Capital with a reputation built mostly around distressed debt investing.  

He also writes very well and publishes Memos that I eagerly read.

His latest is on the fall in the price of oil and what lessons we can learn from it.

I highly recommend it to anyone who wants clear thinking on the subject.

If you don’t want to read it, here are some quick highlights:

“…what ‘everyone knows’ is usually unhelpful at best and wrong at worst.”

“Not only did the investing herd have the outlook for rates all wrong, but was uniformly inquiring about the wrong thing.”

“Asset prices are often set to allow for the risks people are aware of.  It’s the ones they haven’t thought of that can knock the market for a loop.”

“Forecasters usually stick too close to the current level, and on those rare occasions when they call for change, they often underestimate the potential magnitude.”

 “This is an example of how hard it can be to appropriately factor all of the relevant considerations into complex real-world analysis.”

“Most people easily grasp the immediate impact of developments, but few understand the ‘second-order’ consequences…as well as the third and fourth.”

“…it’s hard for most people to understand the self-correcting aspects of economic events.”

“If you think markets are logical and investors are objective and unemotional, you’re in for a lot of surprises.”

“A well-known quote from economist Rudiger Dornbusch goes as follows: ‘In economics things take longer to happen than you think they will, and then they happen faster than you thought they could.'”

“The key lesson here may be that cartels and other anti-market mechanisms can’t hold forever.”

“…it’s hard to analytically put a price on an asset that doesn’t produce income.” 

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

The Lessons Of Oil

There’s no substitute for hard work

When it comes to improving at anything, there is just no substitute for good, old fashioned hard work.

I’ve been reminded of this lately as I build out my circles of competence through intensive research.

When I started out investing in 1996, I was still working full-time as a pilot in the Air Force and getting my MBA in night school. My research then was heavily focused on quantitative analysis, and my understanding of the qualitative side of investing was slim to none.

As I gained more experience, I also did a lot more research into the qualitative side of research starting in 1998. At that point, my investing results were about as good as the market’s, which isn’t outstanding, but is quite an accomplishment as a value investor at the end of one of the biggest bull markets in history.

As the dot-com bubble peaked and then exploded from 1999 to 2000, I found myself holding several very under-valued, small brick and mortar companies. Those companies’ out-performance was just incredible over the following years.

That was around the time I got out of the Air Force in late 2001 and started as an investing professional.  At that point, I had a lot more time to do qualitative research, but my quantitative method was still working so well that I wasn’t quite doing the best research I could. Because the quantitative method looked so easy at the time, I didn’t see any good reason to dramatically change.  If it ain’t broke, don’t fix it.

I found myself beating the market by over 8% annualized from 1995-2002 (71% more, cumulatively, than market returns) and 1995-2003 (85% more, cumulatively, than market returns). It was like shooting fish in a barrel. Because I was having a harder time finding my quantitative darlings in 2004, I was sitting in a lot of cash, but my returns were still beating the market by over 6.5% annualized over 9 years (76% more, cumulatively, than market returns).

What I didn’t realize at the time was that value investing was having it’s best run ever from 2000-2005. The quantitative method that had served me so well was about to sunset.

That was when I started my own value investing shop. Bad timing.

I knew the quantitative side wasn’t working like it had, but I didn’t fully grasp why. As time went by, I worked harder and harder to master the qualitative side of investing, but I wasn’t quite getting there because I was trying to do it without really working with as much focus as I needed to.

After beating the market by a small margin from 2005 to 2008, I started to realize I needed a more fundamental make-over of my investment research. Instead of quantitative screens, I needed to figure out which companies I wanted to own, qualitatively, and then figure out what they were worth.

I have been on that path ever since, and I’ve been working longer and longer hours at it. Getting to know one company, and all its competitors, all the other companies in the industry, and the company’s suppliers and buyers, the substitute products that may kill the business, and so on takes many hours of reading, re-reading, learning, researching, analyzing, etc.

When it comes time to improve, nothing really beats hard work. Hard work isn’t fun, per se, but it does produce great value. I’m ashamed to say that it took me so long to find and pursue this path, but now that I’m on it, I’m not sure why I thought any other method would work.  

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

There’s no substitute for hard work

John Deere: expected returns and potential downside

(Full disclosure: my clients and I own shares of Deere.)

In preceding articles, I’ve covered Deere’s (DE) general situation, competition, economics, management, and opportunities & risks. Now it’s time to put those thoughts together with some math to figure out what kind of returns can be expected from John Deere.

Before I jump in, I want to make it clear that my expected return discussion is based on the long run. For that reason, it is important to read the full article and see the second half, where I talk about how bad valuation can get in between now and the long run. Caveat emptor.

Long term expected return

My approach to projecting long term returns is to look at long term trends and normalize that for cyclical factors. I want to know what long term, normalized sales per share, net margins, growth and multiples are so that I can estimate a five year price (not necessarily as a five year price target, but a normalized level for price in five years).

Sales per share

In Deere’s case, sales growth from 1982 to 2013 (using the exponential fit function in Excel) is quite stable (96.7% R-squared function, Excel). If it weren’t, I wouldn’t use it. Deviating from this fit would have to assume a secular change in the farming or farm equipment market different from anything seen from 1982 to 2013. A fit from 1982 to 2013 shows a $33.8 billion normalized sales level a year from now. Applying 377 fully diluted shares (I take basic shares and add all options, restricted stock, etc. to that number) to that sales level implies around $90 in sales per share. 

To adjust for the ethanol boom, I also did a fit from 1982-2004, and that showed sales per share of $75. To estimate what things would look like if the last 10 years were the trend going forward, I also did a fit from 2004-2013, and that showed sales per share of $95. Now, I have estimates for normalized sales per share with low, average and high trends in mind.

Net margin

Net margins at Deere have moved a round a lot over the last 32 years. The median net margin over that time was 5.9%, but it has also been steadily trending up (due both to Deere being better managed and a nice tailwind from farming growth scaling up). Below are the the longer to shorter term median net margins:

  • 30 year: 6.1%
  • 25 year: 7.2%
  • 20 year: 7.7%
  • 10 year: 7.7%
  • 5 year: 8.2%
  • 3 year: 9.2%

With these numbers in mind, I’ll base my estimates on a low end net margin of 6%, mid point of 7.5%, and high end of 9%.


I break growth into three parts: sales growth, margin growth, and share growth/buybacks. For Deere, the historic growth trend has been 7.5% (the first fit referred to above). Looking at the trend from 1982-2004 (pre ethanol boom), the trend was 6.7%. These numbers were confirmed by looking at long term averages as well, which show and average of 7.6% and a median of 9.8%. For my estimation, I will use a low end sales growth estimate of 5%, a mid point of 6.5%, and a high end of 8% (I’m being conservative on this because I know the ethanol boom of the last 9 years won’t be repeated).

Margin growth has varied widely over the last 32 years, but has generally trended up at a median rate of 1.6%. I think it would be imprudent to assume that Deere can recreate that accomplishment in the coming 5 years, so I will use a low end of 0% margin growth, a mid point of 0.5%, and a high end of 1% (I’m still assuming management can bring margins up with scale, manufacturing efficiencies, etc.).

Share count has also varied a lot over the last 32 years. In the more distant past, share count actually grew, but as management has refocused on building shareholder wealth, and been incentivized to do so, share count has declined at a median rate of 2.3% over the last 18 years and 3.9% over the last 10 years. I don’t expect that high rate to continue assuming the agriculture market cools off, but I do expect a low end of 0% buybacks, a mid point of 0.5%, and a high end of 1%.

Putting together these pieces, I’m estimating 5% (5+0+0), 7.5% (6.5+0.5+.05) and 10% (8+1+1) growth rates at the low, mid and high ends.


What multiple of earnings has the market been willing to pay for Deere? That has fluctuated widely, too. Because Deere is a cyclical business, investors have been willing to pay high multiples when earnings were low and low multiples when earnings were high. Multiples have also trended up over time as Deere has become a better business with wider profit margins. Given that, the median, low and high multiple to earnings over the last 32 years has been 10.5x and 16.5x, with 13.5x in the middle, so that is what I will use.

Expected returns

If you put together all the low, medium and high end assumptions above over a five year period, plus dividends growing at the same rate as sales per share and an $85 price tag on Deere, you get return expectations (annualized) of -2.9% 11.2% and 23.2%. Now, I assign a range of probabilities to those returns to come up with expected returns. Assuming a probability of 45% and 20% for the low end, 50% to 65% for the mid range, and 5% to 15% for the high end, I come up with a return expectation of 5.5% to 10.2%. (If you plug different numbers into the framework above, you can come up with vastly different results, so a lot depends on your assumptions being valid, or at least reasonable.)

This may not be the barn-burning return you expected, but it looks good compared to my projection of a 3.4% annualized return from the S&P 500 (at $1,982.30) over the next give years.

Keep in mind that my 5-10% return expectation on Deere is a long term projection. The path to that return may be bumpy, as I highlight below in my section on how bad things can get.

How low can you go?

To buy a cyclical company like Deere, it’s not enough to have an idea what average future returns may be. You must also be ready to ride the cycle down to an uncomfortably low point, and be willing to buy more on that difficult trip down. This is particularly important with Deere because a long agricultural boom is coming to an end and farm equipment sales are clearly already tumbling. So, how bad can things get for Deere’s stock price in between now and the long term?

One way to look at how low Deere’s stock price can go is to look at multi-year sales per share (I use sales per share to account for the fact that earnings per share can get so low as to make earnings multiples meaningless) compared to the lowest multiples that have been experienced historically. Looking at an average of 3 year of sales per share relative to lowest annual prices, I can see that Deere got down to a 0.2x multiple of sales per share in 1986. Looking at 5 year average sales per share, 7 year, and 10 year, I see multiples of 0.4x, 0.5x and 0.5x. Below are the prices that Deere could get to, accordingly, from around $85 today:

  • 3 year sales per share, 0.2x multiple: $17
  • 5 year sales per share, 0.4x multiple: $29
  • 7 year sales per share, 0.5x multiple: $33
  • 10 year sales per share: 0.5x multiple: $29

I’m not predicting such low prices, but I am saying that Deere could get that low if history is a guide and an equivalently bad downturn occurs.  As I said above, caveat emptor. It should be noted, though, that I don’t think the 1986 scenario is likely because this farm boom did not include the debt binge of that period (Kansas City Fed study), but it is best to consider all empirical evidence.

Another way to think about how low Deere’s price can get is to look at prior peak to trough sales declines and apply low end multiples. Between 1982 and 1986, Deere’s declined peak to trough by 24%. From 1990-1992, 16%; from 1998-1999, 19%; from 2008-2009, 21%. The 1982-1986 scenario, the worst I have on record, would see Deere’s 7/31/13 LTM peak sales go from $35,250 to $26,920, or to $71 per share. The 1990 drop, the least bad drop, would pull sales down to $29,573 or $79 per share. Applying the 25th-percentile low multiple (0.5x in both cases) to those figures gives share prices of $35.50 and $39.50. 

A final way to prepare for low prices is to look at my normalized sales fits above and compare them to the lowest multiples of sales seen historically. The trough multiples on normalized sales were 0.2x sales per share in 1986, 0.4x in 1992, 0.6x in 1999, and 0.4x in 2009. Applying those multiples to the fitted sales per share above of $75, $90 and $95 gives price bottoms of $15-19, $30-38 and $45-47.  (Once again, keep in mind I consider the 1986 scenario quite unlikely.)

As I hope I’ve made clear, although I expect Deere to provide good long term returns, the path to those returns may be quite uncomfortable. Such is the nature of cyclical companies.

The upside is that Deere’s price getting that low would likely generate truly amazing returns going forward (as they did for smart investors who bought in 1986, 1992, 1998 and 2009). Prices may never get that low, but it is best to prepare for such an eventuality even if it never occurs. Forewarned is forearmed.

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

John Deere: expected returns and potential downside

John Deere’s opportunities and risks

(Full disclosure: my clients and I own shares of Deere (DE))

John Deere faces significant opportunities and risks that must be considered before a proper valuation can be done.


The biggest opportunity John Deere faces is booming growth for food in developing and emerging markets. This subject has been covered significantly by others, but I’d like to put a couple of data points out there for consideration. Middle class growth over the next 15 years from places like China, India, Indonesia, Brazil, Pakistan, Mexico, the Philippines, Vietnam, Bangladesh, Nigeria, etc. will be staggering. That middle class is expected to go from 29% of world population in 2008 to 50% by 2030 (Goldman Sachs, 2008). That larger middle class will lead to higher crop production over time and the need for higher efficiency farm equipment like Deere produces. Higher incomes will also lead to higher protein consumption in the form of meat like beef, pork, chicken, fish, etc. (as it has for every country that has achieved middle class income). It takes 2-6 times the pounds of crops to produce an equal pound of meat (Wikipedia, feed conversion ratio). The shift in middle class diets towards more meat consumption will also lead to the need for higher and more efficient crop production the world over.

A second opportunity for Deere is to boost the lower productivity of many farmers in the world. In corn production, Canada is the second most efficient producer to the U.S. at 96% and Nigeria is only 18% as efficient (looking at production relative to acres harvested, USDA data on Deere’s website). With soybeans, Brazil is the most efficient producer, 3% more efficient than the U.S., with Canada at 98% U.S. efficiency and India at 33%. With wheat, the E.U., China, Canada and Ukraine are more efficient than the U.S., but Kazakhstan is only 34% as efficient. The rest of the world can benefit from Deere’s high efficiency farming equipment in order to produce the growing demand for more food.

Although Deere dominates in manufacturing large tractors and combines for row crop production, they also have the opportunity to grow share and efficiency in building equipment for other crops, such as cotton, sugarcane, rice, etc. It may take time to build such expertise, but the returns for such effort, especially over the rest of the world, are great.

John Deere isn’t just a farm equipment manufacturer, they also make construction and forestry equipment. That division has been in a major slump as both the U.S. and the rest of the world has cut back dramatically on construction and forestry markets. But, the good news for Deere is that such markets are coming back and will come back to a normalized level over time. This recovery will, no doubt, come in fits and starts, but Deere has the opportunity to profit from significantly higher revenues and profit margins as those markets recover. 

A more defensive opportunity for Deere comes from its finance arm. Although this business is likely to decline over time (see risks below), it will decline more slowly than new equipment sales, and that will dampen earnings volatility over the full cycle.

Finally, Deere’s businesses have a significant service parts business. Although this is a smaller part of Deere’s business, it is profitable and much more stable than selling original equipment.


An understanding of Deere’s opportunities must be balanced against a solid understanding of its risks. Most of these risks relate to the long cyclical boom of farming over the last 5-10 years.

The ethanol production boom has led to great mal-investment over the last 5-10 years. By mal-investment, I’m referring to the Austrian economics term for investment that results from government manipulation of markets. Much more corn has been planted and harvested in order to meet government demands for ethanol production. That artificial demand has led more farmers to buy more equipment than they otherwise would have. Although Deere has benefited from that over the last 5-10 years (and you can see it in their volumes, margins and returns on capital over that time), they have also necessarily overbuilt production capabilities and pulled demand from the future. The boozy boom of the last decade is likely to turn into a nasty hangover over the next decade.

This long boom will take years to work out and for Deere to re-achieve economic equilibrium and then restore normalized growth. That means production will likely need to be cut significantly with a resultant decline in volumes, margins and returns on capital.

The long boom has also resulted in one of the youngest, most productive tractor and combine fleets in history. Farmers making less money (due to lower crop prices caused by supply getting ahead of underlying demand) will be reluctant to replace or even repair such young equipment. This will create the same headwind referred to in the two paragraphs above.

The farm equipment market depends heavily on government financing, especially in places like Brazil. Another risk to Deere is that such funding dries up as many emerging, developing and developed market governments try to right their own fiscal problems. This could create an additional headwind to production volumes and profitability.

John Deere also specializes in large, hyper-efficient farm equipment that most of the developing world is not as willing or ready to purchase. It will take Deere time to build up profitability of smaller tractors and harvesters and and adapt them to new local markets. Added to this, Deere doesn’t possess the same advantages in smaller scale farm equipment that they possess in large equipment, thus under-cutting one of their key competitive advantages. 

Although Deere’s finance arm dampens earnings volatility over the full cycle, it will also become a headwind over time as less new equipment is financed (thus shrinking the earning portfolio) and less profitable farmers default on their financing. Added to this, such problems will generate more used equipment to compete with Deere’s new equipment. Financing equipment sales is a double-edged sword that will be considered an increasing risk over time (until, that is, market equilibrium is restored).

Reviewing the opportunities above, you can see there are mostly secular growth opportunities offsetting cyclical decline risks. How these two forces play against each other is another risk for Deere. Will secular growth overcome the downturn due to mal-investment and a return to normalized economics? Or will it take time for secular growth to overcome the cyclical headwinds of over-production? I don’t know the answer, but I know it is a risk for Deere as an investment. I would expect the cyclical headwind to prevail over the short to intermediate term and for the secular tailwind to assert itself over the intermediate to long term.

Next week, I will take a hack at Deere’s valuation, keeping in mind the risk and opportunities highlighted above.

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

John Deere’s opportunities and risks

John Deere: Management

(Full disclosure: my clients and I own shares of Deere)

After covering John Deere’s (DE) general situation, competitive position, and economics, I will now take a hard look at management. Specifically, I want to examine the board of directors, executive team, and then evaluate both.

Board of Directors

Deere’s board consists of 11 members, which I think it too big. It consists of the CEO/chairman, an insider, 5 major executives (from Lockheed Martin, DuPont, Rockwell Collins, BMW, Cargill), 2 minor executives (Springs Company, New Vernon Capital), one professor, and one former general.

I like to see representation by executives who have real experience allocating capital, managing people and making hard decisions. Many of Deere’s board members serve on several other boards, though, so I wonder how focused they are on Deere. Professors are very intelligent people with unique knowledge, but that doesn’t qualify them to judge a business, capital allocation, or senior executives (any more than being an investor qualifies me to write treatises on economics). The same can be said for a retired general (as an ex-Air Force officer, that’s not blind prejudice). 

The average pay for the board of directors (not including chair/CEO) is $230,000 per year. That is not a large sum given the size and prominence of Deere. 

Directors own anywhere from $299,000 in Deere shares to $2.66 million. 7 members own more share value than 3 years worth of board salary, which I think makes them act more like owners. The other four own 1-3 times board salary, which makes them more inclined to vote their salary than their ownership. Unfortunately, board ownership is almost exclusively from restricted stock awards. In other words, the board hasn’t invested their own hard-earned money in Deere like investors.

Deere’s board resembles most large company boards, with lots of prominent members–some with business experience, some not–handsomely paid and with little ownership. I’d prefer members who’ve put their own dollars on the line like investors, and perhaps a couple of directors who are from the asset management world (private equity, money management, etc.). Instead, Deere’s board is filled with executives who are likely to feel sympathy with Deere’s management where I’d prefer some people willing to hold management accountable to tough standards.

Executive Team

The top five members of Deere’s executive team average 28 years at Deere. The CEO has been there 39 years and the CFO is the newbie at 18. I prefer management teams that are brought up in the business, especially a cyclical business like Deere’s. Each manager has a breadth of experience at different divisions inside the company and understand well Deere’s culture (and could not, perhaps, work as well outside that culture).

Pay at Deere is broken into salary, discretionary bonus, short-term incentives, mid-term incentives, long-term incentives and other. The board employs a compensation consultant, which tends to ratchet up pay because they look at peers who are doing the same peer reviews and, therefore, also ratcheting up their pay. 

Deere’s short-term incentive is based on operating return on operating assets for the operating side of the business and return on equity for the finance arm. The operating return metric is adjusted for low, medium and high volume years (which aren’t really in management’s control). This is a very good incentive program and one of the best I’ve seen.

The mid-term incentive is based on shareholder value added (operating profit minus cost of capital: 12% for equipment operations and 15% for finance). The metric is judged over rolling 3 year periods. Once again, an impressive incentive system that’s fair to shareholders and management.

The long-term incentive consists of performance stock units, restricted stock units, and stock options. The performance stock units are awarded 50% based on revenue growth and 50% on shareholder return relative to the S&P 500 industrial sector. Once again, a very shareholder-friendly reward system.

Other pay is another $153,000 to $520,000 a year, including: personal use of company aircraft, financial planning, relocation, medical exams, perquisites, tax gross ups, and defined contribution plans. That’s a bit steep, but not unusual for a company this size.

Deere shows the typical monster payouts that executives would receive upon death, disability, retirement, termination with or without cause, and voluntary separation. It’s not my favorite, but what can you do. All the other kids have one, too.

The CEO/chairman averaged $19 million in pay over the last 3 years, and the other 4 executives averaged $4.3 to $4.8 million. Just on a rough comparison with Caterpillar and AGCO in terms of pay relative to revenue and operating profit, Deere falls in between the two, which can be explained simply in terms of company scale (the size of pay relative to the size of sales and profits tends to go down, proportionately as companies get bigger).

Ownership at Deere is not exemplary. The CEO owns $8.1 million in shares (I’m not counting the options they give out as lottery tickets), which is one-half his salary each year. Other executives own similarly paltry amounts with pay anywhere from 1.7 to 12.5 times ownership. This management team’s ownership clearly makes them act as hired hands and not owners.

Pay is high, but the incentive to perform along the right dimensions is there. The record of competitive position and economics covered in my last two blog entries is, without doubt, a more important exhibit in judging management.


My overly-detailed analysis above just sets the context for evaluating Deere’s managers. What’s most important is that management understands the economics of Deere’s business and can maintain and expand its competitive advantages over time. Judging by their record over the past 20 years, I’d say they have been doing a good job improving margins, boosting capital efficiency, and making their products the best on the market. They’ve had a nice tailwind due to ethanol subsidies and global growth, but they’ve also played that hand well. 

The management team has been at Deere a long time. They have ridden through previous boom and bust cycles and should understand how to ride them out. As Martha Stewart would say, that’s a good thing.

I’d prefer to see a board with more owners and proven capital allocators. I’d prefer management owned more shares that they purchased with their own money, too. But, Deere also has a compensation scheme that rewards improvements in operating returns to assets and return on equity, awards bonus pay based on operating profits after a meaningful capital charge, and provides performance shares based on revenue growth and total return to shareholders relative to a relevant benchmark. 

Deere’s board and management may not represent perfect alignment with shareholders, but management is experienced and they are compensated for meaningful performance. They’ve also demonstrated a track record of improving the economics of the business.

Before I get into Deere’s valuation, I need to cover the risks and opportunities that Deere is facing. I’ll provide that in two weeks.   

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

John Deere: Management

John Deere’s economics

  • John Deere has exhibited good, but not great, operating and net margins over the last 20 years relative to the average industrial company
  • Deere has, however, produced above average returns on capital employed (that edge looked much better over the last 10 years than the 10 years prior)
  • The qualitative nature of Deere’s industry and Deere’s strong competitive position make those above average returns seem sustainable over time

John Deere stacks up well against its competition, but are its economics compelling?

A good long term investment has strong and sustainable economics. That is to say, it generates above average returns on capital invested and can maintain those returns far into the future. How does Deere look?

One measure of good economics is superior profit margins. That isn’t a necessary or sufficient condition, but a business that generates high margins shows it can add a lot of value (the difference between what customers will pay and the costs of production).

Below, I compare Deere to the Value Line Industrial Composite.

  • Operating Margins (after cost of goods sold and sales, general & administrative, but before depreciation)
    • Deere
      • 2009-2013 (last 5 years): 13.5%
      • 2004-2013 (last 10 years): 12.5%
      • 1994-2013 (last 20 years): 12.4%
      • 1994-2003 (10 years prior to last 10 years): 10.2%
    • Value Line Industrial Composite
      • 2009-2013: 16.4%
      • 2004-2013: 16.6%
      • 1994-2013: 16.6%
      • 1994-2003: 16.2%
(The reason why I look at prior 10 years is because Deere has had an unusually strong tailwind with ethanol mandates and strong global growth over the last 10 years. Because those beneficial conditions may not last, I thought it was prudent to consider Deere’s economics in the 10 years prior to that last 10 good years.)

Deere’s operating margins aren’t above average. In Deere’s case, that is mostly caused by a higher than average cost of sales relative to the average industrial company. 

  • Net Margins
    • Deere
      • 2009-2013: 8.2%
      • 2004-2013: 7.7%
      • 1994-2013: 7.7%
      • 1994-2003: 6.4%
    • Value Line Industrial Composite
      • 2009-2013: 7.4%
      • 2004-2013: 7.6%
      • 1994-2013: 6.8%
      • 1994-2003: 6.2%

Deere’s net margins have been superior over the last 5 years. When you look farther back in history, this margin edge decreases but doesn’t disappear. Deere generates an above average spread between the top and bottom line, but not by enough to be considered economically stellar.

Margins, by themselves, are an incomplete picture. More important to investors is return on invested capital.
  • Return on Assets
    • Deere
      • 2009-2013: 4.4%
      • 2004-2013: 4.6%
      • 1994-2013: 4.6%
      • 1994-2003: 3.7%
    • Value Line Industrial Composite
      • 2009-2013: 6.1%
      • 2004-2013: 6.5%
      • 1994-2013: 5.4%
      • 1994-2003: 4.8%

Deere’s returns on assets are significantly below average. I think this can be explained by Deere’s large finance arm, which produces high returns on equity but low returns on assets (like most financial businesses).

  • Return on Net Assets (working capital, long term debt, equity)
    • Deere
      • 2009-2013: 14.0%
      • 2004-2013: 13.8%
      • 1994-2013: 11.8%
      • 1994-2003: 8.7%
    • Value Line Industrial Composite
      • 2009-2013: 8.2%
      • 2004-2013: 8.7%
      • 1994-2013: 8.5%
      • 1994-2003: 8.1%
Deere’s return on net assets (a measure I look at because it includes the returns on working capital in addition to debt and equity capital) are superior. I think part of this can be explained by Deere’s finance arm, but also by Deere’s capital efficiency when it comes to managing working capital. Deere’s business looks quite strong by this measure, but you can see that in the period from 20 to 10 years ago, this edge was much smaller.
  • Return on Capital (long term debt, equity)
    • Deere
      • 2009-2013: 20.0%
      • 2004-2013: 18.6%
      • 1994-2013: 17.6%
      • 1994-2003: 13.5%
    • Value Line Industrial Composite
      • 2009-2013: 10.1%
      • 2004-2013: 10.5%
      • 1994-2013: 10.4%
      • 1994-2003: 10.0%
Deere’s return on capital also looks superior. In my opinion, this shows that Deere’s business may not run on high margins, but produces a lot of value relative to the capital employed. Notice, too, that Deere’s superiority is lower from 20 to 10 years ago, but still significantly above average.
  • Return on Equity
    • Deere
      • 2009-2013: 31.5%
      • 2004-2013: 26.0%
      • 1994-2013: 22.3%
      • 1994-2003: 18.5%
    • Value Line Industrial Composite
      • 2009-2013: 16.1%
      • 2004-2013: 16.4%
      • 1994-2013: 16.3%
      • 1994-2003: 16.3%
Deere’s return on equity is quite enticing. This is due to a combination of superior economics, I think, as well as a good balance of debt and equity capital deployed (particularly the finance arm). This margin of superiority diminishes when looking at 20 to 10 years ago, but does not disappear.

In addition to the quantitative data above, it’s important to consider the qualitative side. Deere’s business is a cyclical one, but a business that is unlikely to go away. I cannot conceive of a technology that could replace the physical nature of tractors and combines, and that qualitative nature makes for a high degree of sustainability. 

Deere’s competitive position gives it an edge, too, as I described in last week’s blog. Deere can stay ahead of its competition as long as management doesn’t squander its lead. In next week’s blog, I plan to tackle the subject of Deere’s management: how likely are they to maintain Deere’s competitive position and maximize its value over time? 

Nothing in this blog should be considered investment, financial, tax, or legal advice. The opinions, estimates and projections contained herein are subject to change without notice. Information throughout this blog has been obtained from sources believed to be accurate and reliable, but such accuracy cannot be guaranteed.

John Deere’s economics