Cognex [NASDAQ:CGNX]: Economic Valuation of A Robotics Company

I prepared this valuation for Prof. Joel Stern.

If you would like to see a chart or table with a white background, click through it twice.  Use the back button to return to the article.

Executive of Summary

Cognex is correctly valued in the market.

A aiagram from a machine vision patent assigned to Cognex

A diagram from a machine vision patent assigned to Cognex

Overview of Cognex

Cognex is a machine vision systems corporation—they focus on computers which can see—particularly in industrial automation applications.  Originally an MIT spin-out, whose name stood for Cognition Experts, they are headquartered in Natick, Massachusetts—though one of their two main divisions is in the Bay Area like a respectable technology company should be.  They have been public since 1989 and have been paying an extremely modest dividend since 2003.

CGNX Share Price Chart

Figure 1 – Source:  Google Finance

As of close on December 7th, Cognex stock was trading at $36.62 a share with 42,961,000 shares outstanding and a market capitalization of $1.573 billion.   Their revenues are well diversified with 66% coming from outside the United States and the top five customers only account for 7% of revenue.  Like most robotics companies, Cognex has no debt and exhibits the cash anomaly of the knowledge economy.  For tax reasons, Cognex is planning to pay a large 4th quarter dividend, but before paying the dividend, Cognex will have over $400 million in cash and securities on its balance sheet.  Cognex’s non-financial, GAAP capital, net of operating liabilities was only about $200 million and of that $80 million was goodwill.  Contrary to popular wisdom, it does not take a lot capital to build robots.

Cognex is a classic, mid-sized, public robotics company if there if ever was one.  Financially, it looks very similar to other successful robotics companies like Brooks Automation (BRKS), iRobot (IRBT), Aerovironment (AVAV), and to a lesser extent Intuitive Surgical (ISRG)—although none of these companies are direct competitors.

Cognex has unique technologies, a portfolio of successful and related products, and a habit of expanding its business with both organic growth and prudent, related acquisitions.  The macroeconomic trends of the coming decades probably favor Cognex.  The growth of on-shoring, higher labor and environmental standards, rising third-world wages, continued growth of the global middle class, and the increased pace and automation of supply chains all favor the growth of Cognex’s business.  There is some threat of emerging competition or economic disruption from start-up companies like ReThink Robotics, but Cognex’s cash and industry relationships make it equally likely that they are the distribution and exit strategy for such start-ups.

Valuation Process

The valuation process relies on data gathered from market reporting and the SEC’s EDGAR database.  Historical returns allowed me to compute the cost of capital.  Following this, I made adjustments to discover Cognex’s historical assets and economic returns to assets.  I assumed that the 7 year historical return, approximately one economic cycle, would be a good guide to future returns as this is not Cognex’s first economic cycle.  This means that we are assuming that Cognex returns 21.3% on its economic assets every year.

I used a somewhat roundabout way to get investment.  First, I assumed that the GAAP assets required to produce these sales would remain unchanged and so depreciation would exactly equal GAAP investment.  Compared to other robotics and tech companies Cognex has too many GAAP assets, see Figure 2.  To estimate future R&D spending, I observed Cognex has been remarkably consistent in spending 14% of gross revenue on R&D, so I backed into gross revenue from the economic return on assets by assuming a fixed ratio from historical data.  From there, I took 14% of gross revenue and added it to capitalized R&D.  From this capitalized R&D figure, I removed 1/12 annually for obsolescence, to arrive at a capitalized R&D figure.  This figure was added to GAAP non-financial assets to get the economic assets of the firm.

Reader, my apology for overuse of this chart

Reader, my apology for overuse of this chart

Figure 2 – Source: 2011/2012 10-Ks on EDGAR as of July 2012

From this forecast of the company growth, I used three valuation methods.  First, I estimated a free cash flow, which is the economic return of the assets of the company less the addition to capitalized R&D.  Because they have no debt and no GAAP investment beyond depreciation, this is equal to Cognex’s operating profit.  Next, I calculated the economic value added, this is the spread on the total economic assets employed by the company in any given year.  I calculated both of these methods for the next 20 years, with a perpetuity value beyond the forecast period.  Finally, I calculated a long form economic value driver model of the firm.  For this, I ran the calculation two ways.  One way, the forecast period is 20 years, the other has an investment period of 10 years.  The ten year period brought the value in line with the other methods.  This may be a consequence of the way that I dealt with the changing investment amounts.  However, the long form is mostly intended to talk about the sources of value in the stock price, not accurately predict what the price should be.

Cost of Capital

To estimate the cost of capital for Cognex, I regressed the monthly returns to Cognex over the ten year treasury return for the last five years against the equity premium of the Russell 3000.  The result is below in table 1.  The alpha is not significant—and even if it was, this alpha could not be expected to be permanent—however forcing it to zero does not yield a significantly different beta, so I used a beta of ~1.38.

Cost of Capital Regression

Table 1 – Regression of Cognex Premium Returns to Russel 3000 Premium Returns

This beta times a future equity risk premium of 6% and on top of a ten year risk free rate of 1.626% results in cost of capital 9.89%.  Since Cognex has no debt, this is the weighted average cost of capital as well.  The ten year bond may not be a perfectly appropriate choice given our forecast period of twenty years, but it should be an adequate estimator for our purposes.  Using the 30-year yield would raise the cost of capital by about 1% to be almost 11% instead of just under 10%.  Given the economic spread that Cognex returns, this would change the valuation by about 10-15%, but it probably wouldn’t change many of the company’s investment decisions.

Free Cash Flow Valuation

Using the method above, I prepared a forecast of the free cash flows Cognex can be expected to produce.   The table below shows the forecast with the intervening years truncated.  Of course this forecast does not adequately capture the cyclicality of Cognex’s business selling industrial equipment.  However, it gets very close to the share price in the market.

FCF Valuation

Table 2 – Free Cash Flow Valuation of Cognex [Entries 2018-2031 Omitted for Clarity]

Discounted Economic Value Added Valuation

R&D should be capitalized in the firm.  This is the key asset which Cognex derives its revenues from.  Robotics factories tend to be singularly unimpressive and largely undifferentiated affairs.  The basis of the 21.3% return the Cognex has historically earned on its economic assets is largely the R&D.  As pointed out above, Cognex is probably not very efficient at managing its real GAAP assets.  My R&D capitalization schedule relies on assumptions, but I think reasonable ones based on my experience in the robotics industry.  These assumptions, along with the spread on employed economic capital, drive the value in the discounted economic value added method.  The spread that I used has to be pretty close to a fair estimate given the R&D depreciation method that I used, which assumes that R&D useful life is a random exponentially distributed variable with a mean of 12 years.

Discounted EVA Valuation

Table 3 – Discounted EVA Valuation of Cognex [Entries 2018-2031 Omitted for Clarity]

Long Form Economic Valuation

The long form model of the firm show in table 3 looks at the drivers of value.  As investment is variable over the period, I used the starting value of economic investment to .  This will likely understate the long form value of the firm slightly.  However, the long form appears to overstate the value of the firm compared to the other methods.  If an investment period of 10 years is used, the long form comes much more into harmony with current prices and the other methods.

Long Form Economic Value Drivers Model Table 4 – Long Form Valuation of Cognex

Conclusion

I’m not very enamored of public equity investing so I’m a little foggy on what the analyst terms mean.  In recent periods it has seemed like analyst terms like, “strong buy” and “buy,” mean things quite contrary to their common meaning—perhaps closer to “Be careful” and “Call your broker with a sell order ASAP.”  Going by conservative assumptions derived from historical data of the last economic cycle, I got prices that were very close to, and bracketed, the market price of the stock.  Cognex would be reasonable to hold in a portfolio if you expect earn the market cost of capital on your portfolio.  There is upside potential, but there are also risks the current price.  All in all, it looks set to return the cost of capital for the foreseeable future.

There is power in being able to say what amount of economic capital you are employing—regardless of where the accountants hid it.  It also allows you to look at any company like it is a bank.  The firm takes in capital from whatever sources, and using it for purposes that earn a spread over the cost of capital, then returning the capital and pocketing the spread for the owners.  This uniformity of treatment, really gets at the heart of what is creating value in the firm.

However, I’m not sure that any of the methods of valuation adequately speak to what the real risk of this company is—which is that it needs its research to match the needs of its customers.  The dogs might not eat the dog food, or they might unexpectedly ask for seconds.  These changes in customer demand are going drive immense fluctuations in all the assumptions that financial forecasts make.  It is a messy and localized business, but fundamentally, this is what really creates the value.  Just doing R&D is not going to necessarily create value, true of any asset, but the matching problems are much more severe in R&D and the rate of economic return incorporates a lot implicit assumptions about how management will make the assets perform.

Appendix

Data and Estimates

Data and Estimates

Table 5–Data and Estimates

Full Calculation

Table 6 — Printable Full Discount Calculations

Four Steps to the Epiphany: the Moby Dick of start-up books

Image: Front Cover; Source: Amazon

If your experience of Moby Dick was that you were constantly aware that you were reading one of the best books of all time that was opening your mind to new ideas if only you could keep your eyes open, you understand.  Four Steps to the Epiphany is the great white whale of start-up books for a reason.  Although it is not nearly as easy to read as his disciple Eric Ries’s more famous book, The Lean Start-up, it is much more systematic.  This books has some profound insights about understanding why some start-ups can do it one way and others need to do it completely opposite.

Instead of abstracting and generalizing the insights, Blank focuses on the issues of managing under extreme uncertainty in their native context.  He tackles every aspect of the non-engineering side of the business.  Most of the book is about how to systematically eliminate the market risk for your product, this will be somewhat familiar to you if you’ve read the Lean Start-up.  However, seeing the original idea and seeing it laid out in full detail, in the context it originally sprang from adds a lot of richness and practicality to the idea.  Blank devotes a good deal of time to understanding how to make technology push and market pull work together.  He covers when to go for broke spending money to enter a market and when to hold back and let the customers come to you.  Most importantly, this comes with some practical steps to discover when to do each.  He even covers how to start converting to mature company once you’ve almost made it.

Much like Melville, Steve Blank will say something really profound and insightful, then launch into a description of whaling–er, uh–start-up processes that are needed to implement that idea.  This can make the book a tough slog, because reading a process description around bed time can definitely have soporific effect.  However, this tough slog is absolutely worth it if your a practitioner in the world of technology start-ups.  You can’t hand it to your cousin that works at a big company and expect him to read it.  This is meant for the start-up community.  If you are a start-up practitioner, get this book and make yourself read it.   You will not be disappointed.  I expect my copy to become much more dog-eared than it already is before it gets confiscated for some future company museum.

So how does this relate to robotics…

Reading this book will further persuade you that many if not most management teams of robotics companies don’t have a clue.  You’ll even be able to look at robotics success stories and realize–wow–compared to software our industry’s state of management practice is pretty dismal.  Many successful robotics companies just fell bass-ackwards into their success.  Many were product driven companies to a fault that were able to expensively keep trying until they finally hit a success.  This is not the same thing as systematically eliminating and consciously balancing market versus technical risk to produce the greatest chance of creating successful business that uses robotic technology to make money and make the world a better place.

We’ve got a long way to go as an industry.  Luckily, now that we know that there’s nothing inherently ‘capital intensive’ about the robotics industry we can start addressing why we have so often screwed it up before.

U.S. Robotic Stocks: Speculators Wanted (the real kind, not the financial kind)

The first part of the robotic stock tracker is up.  The index is coming!

First observation:  It is amazing how volatile robotic stocks are and how much idiosyncratic behavior each stock has exhibited since the start of the year.   With this much volatility, one would expect robotic stocks to produce market beating performance over the long run, but they certainly haven’t done it so far this year.  In the short run, it is very difficult to value real assets that have uncertain financial prospects.  In the long run, I’m banking on an extremely bright future, powered by robots.

What cluster does a company with HQ in Boston but more offices in Silicon Valley belong to?

I’ve got more comprehensive data on public robotics companies due to some updates suggested over at hizook.  However, I’m at a loss as to how to classify Brooks Automation and Cognex.  They both make automation components for various kinds of industrial applications and they both have corporate HQ outside of Boston with two offices each (probably the legacy of acquisitions) in Silicon Valley.

At a loss as to how to classify them, I’ve made a new category for them on my charts.  If you have thoughts about how to get good acquisition data–especially as a lot robotics companies can be acquired in a transaction that is ‘immaterial’ to a 10-K/Q for public company–I’d love to hear them.

And here is the raw data.  Not all market caps were taken on the same day.

East Coast Chauvinism in Robotics: Time to Face Facts, Silicon Valley is Kicking Our Ass

A cleaned-up version of this article became my first post on Hizook.  http://www.hizook.com/blog/2012/06/25/east-coast-chauvinism-robotics-time-face-facts-silicon-valley-kicking-our-butt#comment-971

_______

I have lots of love for Pittsburgh in particular, but it really pisses me off when people on the East Coast repeat a bunch of falsehoods (See #8) about how Boston and Pittsburgh compare to Silicon Valley and the rest of the world.  Many people in Pittsburgh and Boston—including people I call friends and mentors—smugly think that the MIT and CMU centered robotics clusters are leading the world in robotics.  This is demonstrably false.

If leadership in robotics means forming companies, making money, or employing people, then Silicon Valley is crushing everyone—no matter what the Wall Street Journal editorial page says about their business climate.  I’ve previously published an analysis of the Hizook 2011 VC Funding in Robotics data that shows that the Valley gets 49% of total VC robotics investment worldwide.

I’d now like to add an analysis of U.S. public companies (see bottom of the page).  Basically, the ‘Pittsburgh and Boston are the center of the robotics world’ story is even more ridiculous if you look at where public robotics companies are located.  Silicon Valley is crushing the other clusters in the U.S. at creating value in robotics and in building a robotics workforce in public companies.  (A forthcoming analysis will show that this true worldwide and if you include robotics divisions of public companies not principally engaged in robotics such as Boeing and Textron.)

77% of the workforce at public robotics pure plays is in Silicon Valley companies.  An astounding 93% of the market capitalization is headquartered in Silicon Valley and even if you exclude Intuitive Surgical (NASDAQ:ISRG) as an outlier, the Silicon Valley cluster still has twice as much market capitalization as Boston.

The public companies that I deemed to meet the criteria of being principally engaged in robotics, that they had to make and sell a robot, and not have substantial value creating revenues from businesses not related to robotics are listed in the table below.

The one company that I believe might be controversial for being excluded from this list is Cognex (NASDAQ:CGNX).  However, while trying to do decide on whether to include them, I found their list of locations.  They have three locations in California including two in Silicon Valley.  That means that this ‘Boston’ company has more offices in Silicon Valley than in Boston.  I’m not an advanced (or motivated) enough analyst to find out what the exact employee breakdown is, but combined with the fact that they make vision systems and supply components rather than robots, I elected to exclude them. I acknowledge that a similar case could be made about Adept (NASDAQ:ADEP) that just made a New Hampshire acquisition, but I have decided to include them and count them towards Silicon Valley.   I do not believe that either of these decisions, substantively impact my finding that Silicon Valley is the leading cluster when it comes to public company workforce and value creation.

I’m hoping the people who are spreading the misinformation that Silicon Valley has to catch-up to Boston and Pittsburgh will publish corrections.  I believe that this is important, particularly because I want to see Pittsburgh reclaim its early lead in robotics.  So many robotic inventions can trace their heritage back to Pittsburgh, it is a real shame that Pittsburgh has not used this strength to create the kind of robotics business ecosystem that one would hope.

It is impossible for communities to take appropriate action if they do not understand where they stand.  I hope that this new data will inspire the Pittsburgh community to come together and address the challenges of culture, customer access, and capital availability that have been inhibiting the growth of Pittsburgh’s robotic ecosystem before they lose too many more aspiring young entrepreneurs—such as me—to the siren song of California.

Company (1) Ticker Employees (2) Market Cap $M (3) % of Employees % of Market Cap Robotics Cluster
Accuray NASDAQ:ARAY

                   1,100

  463

20%

2%

SV
Adept NASDAQ:ADEP

                       183

43

3%

0%

SV
Aerovironment NASDAQ:AVAV

                       768

  577

14%

2%

SV
Hansen NASDAQ:HNSN

                       174

 135

3%

1%

SV
Intuitive Surgical NASDAQ:ISRG

                   1,924

  21,840

36%

88%

SV
iRobot NASDAQ:IRBT

                       619

  606

12%

2%

BOS
MAKO Surgical NASDAQ:MAKO

                       429

  1,110

8%

4%

Other
Stereotaxis Inc. NASDAQ:STXS

                       171

 13

3%

0%

Other
Total

                   5,368

24,787

100%

100%

(1) Companies are U.S. public companies that have been identified by Frank Tobe’s or my own research as principally engaged in robotics
(2) Employee Count as of Last 10-K Filing
(3) Market Capitalization as of 6/24/2012

Who is investing in robotics

Inspired by getting a second e-mail about Grishin Robotics, I was parsing the VC data from Hizook to see who actually does invest in robotics.  I was surprised to see that there are firms that actually make multiple investments in robotics.

1)  The Foundry Group has invested in both Orbotix and the Makerbot.  This makes some sense in that this is the Techstars crew.  They get consumer technology and nerd culture Makerbot and Orbotix both cater to the maker / gadget-lover / nerd-cool market with consumer products.  Although I’m sure that both companies have possibility of being onto something much bigger whether that is distributed 3D printing changing manufacturing or augmented reality games changing the way that we think about the world, they are both at this point in the toy / hobby market.

2)  Draper Fischer Jurvetson shows up once with Heartland Robotics (now Rethink Robotics) and once again through their ‘Midwest’ affiliate Draper Triangle on Aethon‘s latest raise.  You’ll notice that both of these are practical, safe around humans, commercial applications with predictable, well understood businesses as the customers of these robots.

3) Bezos Expeditions also shows up as an investor on Hizook’s list twice.  He (they?) splits the difference by investing in Makerbot Industries and Heartland/Rethink Robotics.  I guess you could deduce a theme around making stuff, but I think that it might have more to do with personal relationships or just what Jeff Bezos thinks is cool as shit.  I know this post is full of links, but take a look at Bezos Expeditions.  Their portfolio is a space company, a fusion company, a 10,000 year clock with no commercial purpose, and a bunch of other really cool stuff that might scare the bejeezus of a regular VC–along with some relatively conventional investments like Air BnB.

I hope that when Grishin Robotics makes investments, it becomes the kind of investor that signals to follow-on investors that companies it chooses are solid and likely to become profitable.  We need more people entering the business of robotics and investing in robotics if this technology is going to reach everyone it should.   I commend Dmitry Grishin on putting his money where his convictions are.

Incubation in the Clusters

Once again, Silicon Valley is showing the rest of us how its done (see “Incubation” for the data).  Robotics only feels like it is poorly incubated in the Valley, because it doesn’t have incubators with multiple branches in the Valley like biotech and software do.  At least traffic sucks so bad in the Valley that when robotics gets going in the Valley it will need multi-branch robotics incubators just so people won’t have to drive.

All jealousy of California’s good fortune aside, robotics businesses are hard to start.  Not only do they have all the complexities of a software business (with a much more challenging test cycle), but they also have other parts that are equally challenging.  They are a hardware business, a manufacturer, and often a distribution or operations company as well.  I don’t see too many 22 year old college drop-outs running manufacturing and distribution businesses–they are too complex and require too much capital to just let them fail like a VC can do with a mobile app company.  Hence these kinds of companies are run by people who know what they are doing.  How do we create more entrepreneurs who ‘know what they are doing?’

For robotics to take off, we are going to have to find models that produce profitable companies with much less wasted capital than software venture capital does.  Incubation and mentorship are probably going to be really key to making this happen–good job to the Bay Area for getting on this.  If community leaders want to lay the foundation for something really extraordinary in their community, get a robotics incubator going in your community.