Robotics capital intensive?! What are you smoking? Don’t believe it.

Robotic manufacturing is not capital intensive, contrary to the popular wisdom.  (Looking at you HBS.)

Unless someone can bring data to the contrary, we should treat this issue as thoroughly decided against the  conventional wisdom.  As we saw previously, robotics companies do not need a lot of fixed assets.  Now, we will see why people who blithely repeat the conventional wisdom that robotics companies are capital intensive are wrong–even if they claim robotics companies are hiding their true use of capital.

First off, robotics companies’ balance sheets look like technology companies’–the internet kind, not the aerospace/industrial kind.  Robotics companies have lots of cash and relatively little else.

Second, robotics companies have gross margins that even companies that don’t make stuff would envy.  The robotics gross margin would probably be even higher if iRobot and Aerovironment were not defense contractors.   There is a lot of pressure to bury as much expense as allowed into the cost of goods due to defense contract rules.   Intuitive and Cognex’s margins are around 75%.  They are even beating Google on gross margin!

Although, it does appear that robotics companies have a bit longer cash conversion cycle than the basket chosen for comparison here, their cash cycle appears to be in line with other complex manufacturers.  Plus, the robotics companies are holding so much cash their management may just not really care to push the conversion cycle down.

Look at the cash required to sell aircraft though!  Manned or unmanned it looks like it takes forever to get paid for making planes.

Although robotics companies have physical products, the value of a robot is in the knowledge and information used to create it and operate it.  The materials are nothing special.  Consequently, these companies look like part of the knowledge economy–few real assets, lots of cash, and huge attention to their workforce.   Next time someone tells you robotics companies are capital intensive, ask them to share what they’re smoking–it’s probably the good stuff–because they aren’t using data.

One thing that a venture capitalist may mean when he says that robotics is capital intensive is that it generally takes a long time and lots of money to develop a viable product in robotics.  This may be true, but it is not really the same thing as being capital intensive.   This observation should cause a lot of soul-searching within our industry.  What the venture capitalist is telling us is that we–as an industry–cannot reliably manage our engineering, product development, and business structures to produce financial results.

This is why the conventional wisdom is dangerous.  It suggests that the lack of investors, money, and talent flowing into our industry isn’t our fault and there’s not much we can do about it.  That is what needs to change in robotics.  We need to get better at management.  We need to start building companies quicker and producing returns for our investors.  If we do that the money, talent, and creativity will start pouring into industry.  Then robotics can change the world.

Notes on Data and Method
Data Source: Last 10-k


Accounts Receivable = All balance sheet accounts that seem to be related to a past sale and future cash, so accounts receivable plus things like LinkedIn’s deferred commissions.

Cash + Investments = All balance sheets I could identify as being financial investments not required to operate.   Assume all companies require zero cash to operate.

Did not account for advances in cash conversion cycle.

Where are the Ops Companies?

Really where are they?  Given how many companies are  building some form of robot it seems like there should be some proportionally greater number of companies out there forming to implement, service, and operate these robots.  Where are they?

Frank Tobe isn’t finding a lot of them forming in his start-up list.  Even the RIA seems to have fewer integrators than suppliers.  AUVSI has many more Lockheeds and Insitus than VT Services.  One could make a case that this is characteristic of the peculiar industries that we’re looking at.  The robotic counter example is perhaps the ROV industry which routinely provides the ROV as a packaged service to the off-shore oil and gas industry.  But most consumer robotics are still selling to early adopters.  Our consumer customers are all people who want tech for tech’s sake, not to mainstream customers that are just looking to solve a problem.

Think about other complex goods in our economy.  Computers have a vast cottage industry associated with servicing and maintaining them which is probably as big or bigger than the software industry proper.  All vehicle industries whether air, ground, or sea have vastly more businesses in the business of selling the services than engaged in construction of the vehicles–even if constructors do manage to capture a large share of the total revenues of the industry.

I think our industry has a problem.  I’ve talked to people at the oil and gas majors and heard straight out that robotics companies are producing robots which have a business case to be used several applications, but they will never be used until a credible organization to is there to provide the robot as a service.   It is a bit of chicken and egg, but I think this applies as you go down the chain, not just in large capital projects.

When doing sampling or reconnaissance, customers want actionable data not a fleet of robots or new employees.  I know from experience that infantry brigade commanders love having drone imagery of the battlefield, but don’t want to worry about having to support the drone unit, they just want to see the battle.  This is equally true in forestry, agriculture, infrastructure, and minerals.

Do I really want to own a cleaning robot? No, I would much rather have a business that comes to my house every week and keeps the place clean whether that business uses humans, robots, or both.

Even in medicine, if I were a hospital operator I’d love to be able to push the risk of owning the robot back onto someone else.  If I can pay per procedure and not worry about utilization, maintenance, or obsolescence–I’m much more game to adopt something new.

To date, our industry has done a relatively poor job of making robotics accessible to people and organizations who aren’t willing to organize around robotics and develop organizational competence in robotics.  Providing robotics as a service could greatly expand the number of potential customers.  I think when we see these businesses start cropping up, we will know that our industry is no longer in its infancy.

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.

Before we can even have a bubble in robotics…

Our industry needs a better methodology for managing robotics development.

I just a had a great entrepreneurship conversation.  My entrepreneur friend opened my eyes to the possibilities for robotics in an industry, platform space, and application that I had pretty much written off.  The application was using robots to collect data–the simplest and earliest task for any class of robots.  He had taken a fresh look at an industry he knew intimately and seen that there was an opportunity to do something extraordinary and make some money.

This friend is not a robotics expert, but he’s been awakened to the potential in the robotics field.  His big concern and great hesitancy to  jumping into this business is establishing a workable business model.  He sees the potential in the opportunity with the vividness of an insider, but when it comes to the robotics he could use, he sees the immature, expensive junk of an outsider’s eye.  He’s vividly aware of the danger he might not structure the business or implement the technology in such a way as to be the guy who becomes profitable and grows first.  He saw that it would take a lot of money and time just to prove out the concept and that it might take much longer to figure out the right business model.  Meanwhile, his fledgling robotics company would be burning cash at the combined rate of a software, hardware, and an operations company with a direct sales force–not a very pretty proposition.

I didn’t really have anything to say to him on that front other than hackneyed cliches about iterating, pivoting, and the value of moving early.  It really occurs to me that my friend is already following what little we know about how to build a robotics company.  Be a great whatever-you-are first (medical device, logistics solution, toy, etc.) then have it be a robot.   Don’t market the thing as a robot; market it as a new technology solution to a real problem that is worth money to solve.  Be willing it iterate (fail on first attempts).  Go to market with the least capability that you can get paid any money at all for.   All great principles, but it seems like we’re still missing the kind of prescriptions that have developed for software.

The Lean Start-up movement, combined with movements like Agile Development have brought much more rigor to how software development in early stage companies is managed.  More traditional software and engineer models are still applicable to projects where the desired outcome is well known.  In most of my conversations with engineers, it seems like robotics engineering has not reached a similar stage of maturity.  It is difficult for robotics engineers to communicate to business leaders when they will know something that allows for opportunities in business decision making, let alone accurately forecast the true cost of a development job.

The most successful robotics companies do a great job managing development.  However, when you talk to their founders or engineering leads, they are often at a loss to explain what they did differently from failed efforts.  They might explain how they avoided some basic pitfalls–like outsourcing design work–but they often have a very difficult time offering an affirmative description of what they did, why it worked, and how they kept the engineering process and the business on track towards the correct goal.  If robotics is ever going to be the semi-conductors of the 80’s, web of the 90’s, or social and mobile of today, our industry will need to develop a compelling description of how to stay on track towards successful technology and business outcomes.

Who are the top 20 academic roboticists?

In trying to compare the clusters, one of the most important and difficult to measure factors is the quality of the academic pipeline in each of the three clusters.  I thought about looking at patent filings, but that seems too hard and not truly indicative enough of what we are trying to measure.

A single lab, without a single patent could potentially blow the doors off company formation and economic impact in robotics.  I’d like to propose a different measure, the top 20 (or some other number) roboticists in academia… then lets see where they are and where their knowledge is creating value.  On the Pareto principle, we expect most of the useful output to be from the top researchers.  Also, I’d like to call attention to the fact that I don’t have criteria for what makes a researcher “top.”  I promise it is less trying to curry influence than the RB50, but I fully admit to not having the full insight especially into Boston, Japan, and Switzerland.

So here’s the start of my list in no particular order with blatant bias towards CMU:

Sebastian Thrun; Stanford; Corporate Work and Spinouts: Google Car, Google Glass, Udacity

Red Whittaker; CMU; Spinouts: Red Zone Robotics, Astrobotics

Rodney Brooks; MIT; Spinouts: iRobot, Heartland Robotics

Henrik Christensen; Georgia Tech; Non-spinout: National Robotics Initiative

Homayoon Kazerooni;  UC Berkeley; Spinouts: Ekso Bionics (Formerly Berkeley Bionics)

Rich Mahoney; SRI; License Arrangements: Intuitive Surgical, others

Sanjiv Singh; CMU;; Spinouts: Sensible Machines

Hagen Schempf; CMU;; Spinouts: Automatika (Acquired by QinetiQ-North America)

Howie Choset; CMU;; Spinouts: Medorobotics

Behrokh Khoshnevis; USC;; Spinouts: Contour Crafting

Better Coverage for Robotic Stocks

Unfortunately we’re still not a big enough industry that we get good news and analyst coverage on important events.  For instance, Hansen Medical (NASDAQ:HNSN) announced FDA approval of their new surgical device yesterday.  Expected perhaps, but still uncertainty reducing good news for the company, the stock should go up.  It does for a few minutes, then the market goes back to hammering them.   For a company of alumni from Intuitive Surgical, what gives?

I understand they are not growing, but it seems like they have the breathing room to perfect their product and growth does not occur linearly in these kinds of companies.  I’d love to see some good information on what the company should be valued at conditional on success and what the current market discount implies about the probability of success.

Check it out on Google finance:

Q1 2012 Conference Call Transcript: