The word “uncertainty” tends to dominate economic news these days. Political uncertainty regarding the “fiscal cliff”, Washington’s self-imposed deadline that results in automatic tax increases and the repeal of the Bush tax cuts, turmoil in Europe, and a general slowdown in demand across Asia and the Eurozone have kept U.S. corporations on the sidelines in regards to hiring and new investment. An unclear picture on taxes, healthcare and a general lack of faith in Congress to get anything done has lead to companies hoarding cash despite posting record corporate earnings over the last few years. According to Thompson Reuters, the companies that make up the S&P 1500 index had over $1 trillion in cash or cash equivalents on their books at the end of Q2 2012. To put that in perspective U.S. GDP was $15 trillion last year.

In addition to all the news about the fiscal cliff and chaos in Europe, earnings per share growth (or lack thereof) is another data point we should be paying attention to. As of September 30, S&P 500 estimates that Q3 2012 EPS growth will be -3.1% [UPDATE: As more companies have reported earnings this quarter, EPS growth has been revised to -0.1%.] This is significant because a negative turn in EPS growth typically indicates a recession. Of the last four times EPS went negative, three (1989, 2001, and 2007) pointed toward massive economic slowdowns and one in 1998 was a single quarter blip.

EPS growth expected to go negative in Q3 2012, but analysts expect a bounce back in Q4 and 2013.

So is Q3 an outlier or the start of a slowdown? While analysts don’t believe we’ll see back-to-back negative EPS, they’ve begun revising their estimates downward. Since the end of the third quarter (September 30), analysts have reduced earnings growth expectations for Q4 2012 (to 5.6% from 9.3%), Q1 2013 (to 3.4% from 5.3%), and Q2 2013 (to 8.0% from 9.3%). A few trends might point to a more negative outlook.

From 2008 to 2011 corporate profits soared $578B, growing from a low point of $1.2T in 2008 to $1.8T in 2011. This was widely regarded as a jobless recovery as companies cut jobs and compensation, experienced low unit labor costs and significantly increased productivity per worker. Corporations also experienced relatively low commodity and material costs over this time period as shown in the graphs below:



But as you can see those trends have changed and corporations are experiencing increased material and labor costs, which provides one explanation a decrease in EPS. It makes sense that corporate earnings growth would slow during a recovery as companies spend excess cash (hiring new people, investing in R&D, etc.) to meet increased demand. But where will the demand come from this time around?

The consensus is that U.S. GDP growth will be relatively flat over the next few years, hovering around 2% to 3% growth for 2013 and 2014. For the rest of the world, the Eurozone is in turmoil and growth in China has slowed significantly. From 2008 to 2011, China’s GDP was growing at a double-digit rate, creating the demand necessary to offset recessions in the U.S. and Europe:




But with the U.S. economy stuck in a rut and demand in China and Europe waning, who will create the demand necessary to continue to fuel record earnings? If you look a little further back to earnings data from 2006, it paints a clearer picture of how important foreign demand has been to the earnings increase:

“Looking from 2006 – 2011 corporate profits grew by about $219 Billion. However, most of this growth came from outside of the U.S., around $182 Billion. U.S. domestic industries grew by only $36.6 Billion … While the U.S. growth figure is positive, the figure of $36.6 Billion includes a positive contribution of 42.1 Billion from “Federal Reserve banks”. This was over 17.5% annualized growth. All other domestic U.S. industries when aggregated together had a slight negative growth in profits from 2006 to 2011.

This means over the time period from 2006 to 2011, corporate earnings derived from the U.S. were actually negative if not for the federal stimulus! It looks more apparent that the U.S. cannot drive corporate profits alone.

There is evidence that the slowdown around the world has started to hurt topline revenue for S&P 500 companies. While 70% of companies reported EPS above the mean estimate in Q3, 60% are reporting a revenue miss. Guidance doesn’t look good either.  For Q4 2012, 72% of companies in the S&P 500 are reporting negative guidance, well above the long-term average of 61%. According to a survey by CEB, a membership based advisory firm, a little over half of managers expect production levels to increase in the next 12 months, down from 63% a year ago. Only 34% expect to hire in the coming year.


With all of the current risks in the market, you would think that the market would be cheap. There should be a correlation between negative guidance and stock prices (as there was until 2010), but the actual results have been the exact opposite:


It should be pointed out that sectors that are heavily tied to commodity prices (energy, materials, utilities, and industrials) make up the laggards of the group and commodity prices could be the culprit. There also might be some short-term fallout from insurance companies due to Hurricane Sandy, but this could be offset by increased production and investment in the rebuilding effort.

So is this past quarter a blip in the radar or the bearer of bad news? Is there a fundamental issue with the U.S. economy or a few sectors hurting earnings? Will there be a harsh correction in the market?

Uncertainty is most certainly driving corporate decisions and we’ve reached what Clayton Christiansen calls “The Capitalist Dilemma”. Christiansen explains this dilemma as the notion that executives and investors will fund three types of innovations: empowering, sustaining, and efficiency. Empowering innovations “transform complicated and costly products available to few, into cheaper products available to many”. By empowering innovations, companies spend money by creating jobs, increasing capacity to meet demand for new products (i.e. Model T, personal computers, etc). Sustaining innovations that simply replace old models with new ones (new HDTV to replace your old TV). This has a neutral effect on the economy because you’re eliminating your old product with a new one. Lastly, the efficiency innovations “reduce the cost of making and distributing existing goods and services”.  Replacing 100 workers with machines in an auto plant would fall into the efficiency innovation category.

According to Christiansen:

“Ideally, the three innovations operate in a recurring circle. Empowering innovations are essential for growth because they create new consumption. As long as empowering innovations create more jobs than efficiency innovations eliminate, and as long as the capital that efficiency innovations liberate is invested back into empowering innovations, we keep recessions at bay. The dials on these three innovations are sensitive. But when they are set correctly, the economy is a magnificent machine.”

In the current state of the U.S. economy the balance is off. Investments in efficiency have liberated capital, but have only lead to investments in more efficiency thus decreasing the number of jobs. Executives running Fortune 500 companies have been taught to do (and are doing) what’s right for their own companies and shareholders. Investing in efficiency innovations are what lead to record corporate profits and sky-high stock prices over the last few years. And there in lies the paradox. Uncertainty in the market has disrupted the balance between empowering innovation and investing in efficiency. We currently have a glut of cash and a lack of qualified workers, yet companies are refusing to spend money on training new employees (companies also blame the education system and want reform, i.e. the Government to pay for it, but that’s a whole different blog post). Until the fiscal cliff is resolved and there’s stability in Europe, companies are going to continue to do what’s right for them and that means keeping balance sheets flush with cash. Until companies have the incentives to invest in innovation, the U.S. economy will continue to be stagnate and unemployment will remain high.

Cutting costs and investing in efficiency can only go so far. Without an uptick in demand from the U.S. and slowing growth abroad, we may see earnings take a hit in the near future. All of this coupled with Congress’ “stellar” track record on determining economic policy, I would tend be a bit more pessimistic in 2013.

So you have just closed on your $1m seed round.  You’re excited and ready to get to work.  The first thing you do is contact TechCrunch and PandoDaily to get some PR, hire a few engineers, a marketing person and begin paying yourself.  Your burn moves from $15k per month to $75k per month overnight.  You are driving traffic to your site, building product and showing early signs of execution.  You were invited to sit on a panel; you’re mentoring some young teams; all in all, you’re feeling pretty good about yourself.

But, you can’t help beginning to think that the clock has started ticking – 12months and counting to get to that elusive Series A.

So, you begin to scour the blogs, absorb everything that other successful start-ups have done and decide that with 12 months of cash on hand, its time to double down on the business model that you got funded and crack the formula for a scalable user base and show “Fab-esque” growth.  You throw out the idea of the lean model and say “fuck it” time to take control of my own destiny!

Sound familiar?

In the age of Lean Lean Lean, it never ceases to amaze me how many companies at the seed stage fall into the trap.  They mistake maniacal focus on growth for “fire in the belly”.

And, at month 10 or 11, the entrepreneur begins to complain to his investor base that despite all of these great metrics of growth, the company is falling victim to the Series A crunch.

When, in reality, the Series A crunch was a proxy for focusing on the wrong things at the seed stage…

In our portfolio, we believe that exceptional entrepreneurs tend to have very similar characteristics regardless of their customer/market/product differences.  We believe that they have a genetic make-up different then regular entrepreneurs.  I like to call the super entrepreneur gene that distinguishes the winners from the losers, “The Random Walk Gene”.

This gene is displayed by founders who, at the seed stage, realize that they are embarking on a 10000 mile foot race.  They realize that momentum early on does not dictate success. They recognize that a random walk down a lot of different avenues will ultimately help them in the long run.  They realize that learning from mistakes at the seed stage is usually more important then continuing to pile on to the early successes that they have had (think about this for a second, imagine if you knew all of the customer acquisition strategies that don’t work and why… as a nascent business, that information is incredibly powerful – maybe more powerful then knowing one strategy that does work since you don’t have enough $$ to milk that strategy to get you to scale).

The other unique characteristic of this gene is that these entrepreneurs are always ok sacrificing short-term gains in exchange for long term goals – and they NEVER lose sight of this.  If that means that they sacrifice revenue opportunities to continue to build on a more lucrative business model, then they build for the long-term.  If it means giving up a little more equity to bring on the right partners (employees, advisors and investors) then they swallow the dilution.   These entrepreneurs don’t calculate their personal net worth based on the last round of their valuation – they calculate the value that their customers get everyday from using their products.

As a result, super-gene entrepreneurs become pillars of stability in their company and in their community’s – they stay calm, consistent and emotionally stable.

I can name these entrepreneurs and examples off how the gene has displayed itself off the top of my head.  Not because I talk with these guys everyday, or brag about their success, but because I truly admire their ability to prioritize what is important.  Amazingly, and without fail, each of these companies ALWAYS figures out a way to pull off a fundraise, or convince another recruit to come on board or get multiple acquisition offers at every stage of their development.

Building a great business takes a long time.  Slow and steady at the seed stage may mean that you sacrifice the sexiness of running a hyper-growth opportunity, but in exchange, you will have a much more stable business on your hands.  Oh yeah, and the chances that you will stumble on the sexy business model of the moment is like 1 in a 100,000…so at the least, play the game where the odds are more in your favor.

Towards the end of last year, my fellow associate, John Lanahan, and I started collaborating on a research project.  The goal of the project was to distill our views on the broader macro economy into discernible trends, which would inform LaunchCapital investment decisions moving forward.  The practice itself was nothing new – the LaunchCapital team spends a lot of time looking at particular companies and industries through a lens that is tinted by our own macro-economic views.  However, this was the first time that we had formalized the process.

John and I, as well as a few other members of the LaunchCapital team, collected and processed a significant amount of data – raw government data, industry reports, primary research, etc. – over a two-month time frame.  That data was organized into individual presentations along industry or conceptual lines – mobile, big data, h/w + s/w, education, etc.  From here we began to identify key trends – both those that were well established and confirmed by the data as well as those that were emerging and visible only after an examination across the various sets of data.

John and I indentified three broad trends that we believe stretch across industries and will accelerate over the next few years.  They include: 1) increased personal efficiency, 2) collision of the physical and tech world, and 3) speed is changing everything.  The following infographic walks you through these trends and some of the data behind them.  If you would like additional detail on our thought process for each of these trends, you can find it in our second MegaTrends post.

Since this is the first edition of what we hope will be an annual release, we would greatly appreciated your feedback.  For those interested, we are happy to discuss any of our sources and how the data informed our beliefs.  Please reach out in the comments section.

Continue on to Part II for more detailed information on the MegaTrends.

Last week I got my Lytro from pre-order in the mail and was excited to try it out in the field. I went to the California Academy of Sciences in SF to see what it could do.

About the Industrial Design

It fit well in the hand, although I was very scared of it slipping out and me dropping it. Since it is in a horizontal configuration, I wish it had a palm strap like camcorders do. The wrist strap was OK, but there was no way to tighten it on my wrist and I felt like it was swinging precariously as I walked around. Most of the time I just stuck it in my bag.

The magnetic cap in front was slick, but it kept falling off when I removed my camera from my bag. Couldn’t they have figured out some way of doing a built-in iris protector or attached cap? I’m pretty sure I’m going to lose it at some time in the future. At least a screw on cap won’t fall off, even if it is a pain to get off. Snap-ons might work but they aren’t perfect either.

The on/off switch is a small depression the bottom of the unit. It was hard to find, but eventually I got the hang of just pressing generally where it was.

There was a zoom but I totally didn’t know about it until I got home and read the instructions – who reads instructions right? This is a small row of dashes on the top of the unit. I suppose that could be better and more clearly labeled.

The button to take a picture was a small depression on top. I think I got the hang of where that was to take pictures.

The screen was too small in my opinion. You can press on it to refocus into some area, but the image was so small that you couldn’t tell if the focus changed or not.

The UI in the camera was pretty simple. At least there are no fancy menus to confuse you. The point is to just shoot a lot and not worry about things, right?


Reviewing images on the tiny screen sucked. So I downloaded them to take a look at home. Most of them were pretty good. Image quality is up there although it doesn’t match up to my favorite camera, the Canon G12.

It even seemed to deal with low light fairly well. The lens seemed set at f/2, supposedly to minimize field of view and get you the nice blurred surroundings effect. Noise seemed very limited.

However, I did not really enjoy what I perceive to be the main cool feature of this camera, which was to be able to focus in on different parts of the image while other elements blurred out. After just shooting around, I only had one image out of the whole set which I could do this with, an image of some funky blue jellyfish:

Lytro image of Funky Blue Jellyfish

Try clicking on some of the jellyfish, especially the ones in back. Very cool indeed!

So here is where my issues begin.

In order to see the coolness of the camera, I now have to think about the what is in the scene to make this feature come alive. I have to take pictures with things very close to me in the foreground, and then have things in multiple distances all the way into infinity. In that way, the blurriness is accentuated and I can pick around the image to see this happen. Most of the images I shot did not have this quality, and were good images but you can’t really see any blurriness come out when you pick around the image.

This is what happened when I bought a 3D camera, the Fujifilm Finepix Real 3D camera. I had to also think about what I could shoot that would really highlight the 3D-ness of the resulting image. If I just shot some random shot, the 3D effect may not really be noticeable because the elements are too far away and everything still seems flat, which is arguably what you would see in reality.

This makes me think too much. I want the camera to do magic, not make me think about how to make magic. If I wanted to think (and I do with my Canon 60D) then I would just use my old cameras.

But I think we’re in an era where we want cameras to take magical pictures, almost pictures of what we perceive, not what we actually see, or what physics says is out there in the scene.

Take high contrast scenes where there is brightly lit areas inserted in darkness for example. Most cameras fight to figure out how to expose such scenes. Bright light areas often are too bright if you try to expose more of dark areas. Or if you try to expose the bright light areas to get more detail there, then all of the darker areas go black.

However, we do not remember such scenes like that – our eyes are darting around and readjusting what we focus on, and our memories are of what is in the bright areas as well in the dark areas. Certainly there is artistry that results from high contrast images, taking the dark areas and making the mysterious silhouettes in the brighter areas. But sometimes, we want magic to happen. We want to see what is in the bright areas and more detail in the darker areas without having the bright areas wash out.

So I want magic and I want reality when I want them and don’t want to think. I just want to shoot and see awesome results.

This is where I think smartphone cameras like on the iPhone are really the next wave of photography. I would meld Lytro with a image computer that can take both reality and imagined reality and then produce the result I want later with ease and not making me think about the technology. I just want to shoot and have magic come out the other end.

Lytro has some really cool things going for it. As a first iteration, it’s pretty cool but I think I’m demanding more from cameras these days.

Today I just sent this email to a buddy of mine working on a startup:

If [] was a physical store on a street and you wanted to build a store right next to them, what would you build? Would you build exactly the same store or would you do something different?

I always talk about so many me-too products and startups out there today, and the ease of building competitors to just about anything. But entrepreneurs don’t seem to want to stop thinking they can exist and thrive with essentially a clone of something else out there.

My statement/question above is a problem about the internet. In the real world, if you were to build a store on a busy street, would you build exactly the same store? Probably not. You would see that if you wanted all those pedestrians to walk into your store, you’d want to build something with some kind of uniqueness to attract them, and rarely would you want to build the same business that already existed on the street. But on the internet, you can’t see what’s on your street so easily. The browser detaches ourselves from the brutal reality that your competition can be literally a virtual store or two down from you but yet you can’t perceive it as a problem because it’s virtual and not something physically experienced.

And this problem is exponential on the internet as the virtual street you’re building on is limitless in available storefront. Imagine a street with a limited number of pedestrians but tens, if not hundreds of storefronts are squeezing all onto that street, creating ever smaller slices of storefronts for internet pedestrians to walk by, all screaming at them to come in and buy my stuff please!

So ask yourself again – do you want to be yet another storefront on an infinite street or do you want to build something that is truly unique to attract internet pedestrians away from all the same stuff?

“Makers are enthusiasts who hack and modify the world around them in interesting and whimsical ways. Tools and services that used to be inaccessible to all but large manufacturers are now available to everyone. Foreign factories that were impenetrable before are now an email away. Design software costing thousands of dollars per seat is freely available (or very cheap). Hackers are mixing all of these elements together and re-imagining entire industries from the ground up.”

– Vinod Khosla, The Unhyped New Areas in Internet and Mobile, Techcrunch, February 19, 2012.

Vinod Khosla is right. The time is ripe for startups working on products combining hardware, software, and the internet.

Those who know me know that I have been tooting the HW+SW+Internet horn since early 2010. I hinted at it in my post Internet Startup Bubble and The Supposed Super Seed Crash back in July of 2010. But now, more than ever, the evidence is here that hardware is ready to make a comeback in startups. In fact, it already is.

But it’s been hard talking about this for the last 2 years. I’ve met nothing but resistance from the investor community. Practically every VC I’ve talked to has told me that hardware is awful and that software and internet is much better as an investment. And for a long time, it’s been true.

If you think about it, the last VC who was OK with investing in hardware startups entered into the VC business in 1994. After that, the internet came into being and from that point forward, every VC who didn’t jump on the internet bandwagon missed one of the biggest opportunities to make a ton of money. (Of course, those that didn’t jump off the bandwagon at the right time lost their shirts and more). Still, memories about the downsides of bubbles are short; those same VCs were heroes for the money they made and they continued to invest in the internet, and training hordes of emerging VCs along the way. This has continued for 17 years now. Think about it; 17 years of VCs whose thinking has been molded by the success of internet startups and investing in them. And also the advantages of not having to build physical product to get there.

I think the world has changed to the point where the previous advantages of internet/software startups has been declining, and the advantages of hardware startups are ascending.

For a long time, internet/software startups had a distinct advantage over hardware startups. You didn’t have to use up money in paying for inventory of product. Digital products cost so much less and upon copying the bits digitally, the cost of the product declined over time as you sold more. Plus, the internet created distribution mechanisms that were hard to compete with; customers could be reached with extremely low cost and sold to with great ease. But that has changed:

1. Competition in internet/software startups is way too fierce. You start something and competitors pop-up all over the place. With all the easy ways to create software, it is extremely easy to build something that somebody else has built and do it fast.

2. Given the rise of competition and the fact that consumers, along with B2B customers, are deluged by these startups screaming for your attention and your money, the money that you would need to pay for hardware inventory is now money required by internet/software startups to buy traffic. This was not true not too many years ago; now the competitive world has changed – the battle for consumer mindshare AND the IT manager’s mindshare in B2B customers has risen exponentially.

3. Some argue that distribution channels for hardware are limited. However, social, word of mouth, and viral mechanisms for internet/software startups do not work any more and you have to market traditionally to build awareness and brand. This more than equalizes the distribution channels for hardware. At least hardware is unique and not just another website product or service which gives hardware a leg up in customers’ eyes simply because of uniqueness. Do we need another photosharing app?

4. Because it takes longer to gain mindshare in today’s world, you must raise for longer runway – 18 months-24 months at least, which means more money is required in any case.

On the hardware side, advantages are emerging or here already:

1. Hardware technology is commoditized and cheap – what was previously rocket science is now readily available in chipsets to everyone. There is not much out there now that requires serious hardware design resources and custom chip fabrication resources. Advanced technologies of the past are now commonplace.

2. Contract manufacturing can make anything on contract – you don’t need your own factories now. When I worked at Apple back in 1990-93, we had our own manufacturing both here in California and in Asia. I designed plastic parts and oversaw the construction of metal tooling to shoot the plastic. We had to build prototypes, test them and their manufacturability, and arrange our own staff to build everything. Now you can hand off all the manufacturing to contract manufacturers, whether here in the US or in Asia.

Because you do not have to setup factories and manufacturing yourself, you don’t have to raise money to do so like in the past. You can raise the same amount of money as your typical internet/software startup and get product in boxes and on shelves.

3. In huge contrast to internet/software startups, there is *virtually no competition*. It is exceedingly rare that when I meet a hardware startup, that I can find another let alone two competitors! This gives hardware startups an unprecedented period of time where they can advance in the face of no competition and grow and learn.

Universities are graduating enormous numbers of software engineers and everyone is racing to internet/software. Hardware engineers, by comparison, don’t exist in nearly as much quantity. In fact, opportunities for hardware engineers are so limited by a wide margin as these skills have moved offshore to Asia. Thus, nowhere near as many hardware startups appear versus the hordes of internet/software startups.

The barrier to entry is experience and knowledge of hardware. Most people fear it because they have never done it; it is natural to avoid that which is unknown.

4. We are now at the edge of what software can do by itself with respect to the physical world. Having humans type in information or self reporting data is just not practical and filled with potential errors. To do better, you need hardware to do the actual touching and sensing of the physical world and connecting that via software to the internet. An example is Quantified Self – self reporting of physical condition has reached its limits; we need 24/7 monitoring of physical condition to get to next level of knowledge, usage, and innovation.

5. Hardware has become small enough, low power enough to do amazing things for long periods of time. Huge possibilities open up due to low power, small size, and accessibility of the technology. Instead of wearing a huge box that is heavy and uncomfortable and needs to be recharged every few hours, we can wear small, unobtrusive sensors all day long, broadcasting vital information to the internet all day and night.

6. By selling hardware, you make money off every sale. By selling software services on top, you further monetize users far beyond the money made from the sale of the hardware. Due to the intense competition, internet/software startups often need to give away services for free which means survival until customers get to a point where they will pay for something you offer, whereas selling hardware means you make money each time you sell it. But then you offer a recurring, monetizable service on top of that to get more revenue.

This is why hardware+software+internet is the key, not just hardware alone.

7. Accelerator programs are now emerging to bring like-minded and experienced people together to enable better hardware product development. Thes are people like PCH International’s accelerator program help new startups get off the ground and provide competitive advantage because the accelerator startups get access to PCH International’s manufacturing capabilities. Other great accelerator programs are HAXLR8R, a combination China and Silicon Valley hardware accelerator, whose purpose is to spend some time in China to learn how to access and manage Asian manufacturing resources.

Other great hardware accelerators are Lemnos Labs, based in San Francisco, and the newly formed Bolt, to be based in Massachusetts.

The declining advantages of internet/software startups and the increasing advantages of hardware+software+internet startups make hardware the next big emerging opportunity.

The evidence is clear. Over the last two years, here is a list of fantastic startups, using hardware+software+internet:

Evoz – advanced baby monitors, analyzing baby cries with recorded data, and giving advice to new parents. [Disclosure: I’m an investor].

Fitbit – activity monitor and scale for better health and fitness.

Lark – silent alarm clock and personal sleep coach.

Zeo – your sleep manager.

Withings – WIFI enabled scale, blood pressure, baby monitoring.

Lumoback – back health and posture tracking.

Green Goose – making everyday things more playful with tiny wireless sensors that automatically measure what you do.

Leapset – a hardware POS play transforming the cash register for local merchants. [Disclosure: I’m an investor].

Metawatch – a platform for wrist based technology development.

Nest – the learning thermostat.

Elacarte – tablet based menu system for enhancing and optimizing ordering for restaurants. [Disclosure: I’m an investor].

And the list goes on. Still, I meet resistance on this issue.

17 years of entrenched thinking, and exploding economies to power profits and return on capital via internet/software startups make the opinion hard to change. And certainly what I argue doesn’t apply to all hardware startups; for example, to build a new car business like Tesla would still require a ton of capital. However, for small, high technology, connected devices this is exceedingly true.

But that doesn’t mean the VC community has to believe what I believe. If there is anything I’ve learned about investing, it’s that the best returns are derived from not following the herd. This is definitely anti-herd, and I’ll either be totally right or I’ll be amazingly wrong – but if I’m right, I hope to be one of the first to ride the wave of this emerging class of startups to success.

It all started back in 2002 when I signed up for my first triathlon and joined Team in Training to help prepare me for it. It also set me on my big science experiment which was “how fast can Dave Shen really go?”

You see, I had a lot of negativity surrounding my first (and also subsequent) triathlon attempt. People told me that my knees would give out, that I better be careful or else I would get hurt. They told me that I was 37 and that trying to race a triathlon “at my age” was a risky proposition for my overall health.

But I didn’t believe them. And now, here I sit 10 years later and still going strong and injury free at 46 years of age. And getting faster each year.

When I got started on my big on-going science experiment, I decided that I was going to stop training with these programs provided by books and magazines. I was determined to train like what I thought a professional athlete trained like – lots of technological and physical support and a great coach too. Someday I should write what it was like to come from zero swim/bike/run experience to completing 6 Ironmans, numerous swim and run races, and ultimately becoming a Total Immersion swim coach last year. For now, I want to talk about one aspect of my training which has led to wiring myself up in many different ways, gaining insight into the future of training and health through technology.

My coach was Mike “M2” McCormack, a popular triathlon coach in the SF Bay area. It was he whom I credit with introducing me to truly data driven scientific, high technology bike training using a Computrainer. We also explored the training via heart rate zones, but we ultimately switched to training via perceived exertion which yielded better results. Logkeeping in Excel kept me on track and now I had a way to go back into my training and look at what went well and what went wrong. I also bought a Garmin 305 GPS watch to track at a detail level my heart rate and performance on runs.

Along the way, I read an article about Andy Potts training for triathlon and Ironman using a data driven, scientific approach. It was a fascinating look into an elite’s training regimen. His coach would take data from his previous workouts and derive workouts for the next day adjusted for his performance on the previous day, and what his condition looked like in the current day! Wow! This meant that if we could gather enough information about our bodies during workouts and our subsequent recovery, we could, in theory, generate an appropriate workout for the day after, whether hard intervals or total rest.

Fast forward to 2011. I was peaking for the LA Marathon and came across Tim Ferriss’s popular book 4 Hour Body. Yet another eye opener on two levels – one was the realization that there is a lot of crap out there on training, health, and fitness, and two, that you have to be data driven in your health and training or else you will never know if you are doing better than the day before.

Going on his suggested diet, I dropped in weight and body fat % to my usual race weight at the LA Marathon, but then I dropped even lower post marathon and plateaued underneath my racing weight! I would never have known that if I had not been tracking my weight and body composition daily. The constant feedback and monitoring were necessary to know that what I was doing had any effect at all, and whether I had to adjust or not. It was gratifying to see that I did not return to my higher pre-race weight.

In following the 4 Hour Body regimen, I got really interested in tracking everything about me. Here is my current complete list of gadgets for tracking me and what I track with them:

Withings Scale – Weight, Fat % sent to website!
Omron Body Composition Monitor – More weight, body fat %, muscle %

Tracking weight, body fat, muscle % for fat loss, and also muscle gain due to weight lifting.

Garmin 305 GPS Watch w/ Heart Rate Strap – the best training tool for running

I store all my runs here, in addition to storing them on Runkeeper. It is good to refer back to my workouts and see what my times are for certain distances.

Finis Swimsense Watch – swim metrics tracking – strokes, lengths

I can track a lot of swim metrics with this watch, but not nearly as many as the ones we need for Total Immersion. Still it’s the best swim watch out there. I now swim with two Swimsense watches to track the action of both arms and am working with the developers on creating a data driven training program for swimming.

Lark Sleep Monitor – tracks your sleep patterns

I don’t have problems sleeping, but I am interested in the amount of sleep I get versus athletic performance. It’s vibration alarm is best in class just as a simple alarm clock.

Fingertip Pulse Oximeter – measure heart rate in the morning

Measuring heart rate every morning can give you insight on whether you’re fully recovered from a previous day’s workout or not. A Pulse Oximeter is much easier to use than holding a heart rate strap onto your chest and reading a watch display.

Microlife Peak Flow Meter – Measures lung function

Following my discovery that had mild exercise induced asthma, I got interested in seeing what my typical air flow numbers are for my lungs. A fancy peak flow meter in my doctor’s office costs several thousand dollars; this little gadget only cost $39.99 on Amazon!

After discovering all these devices, I realized that the cost of these sophisticated instruments had dropped considerably. With the advent of the internet, we are able to take measurements and send them instantly to the Web for storage and further analysis. Most significantly, technology has commoditized a lot of the hardware components required to build these devices. At one time, it took rocket scientists with a lot of infrastructure to create these tools; this is not true any more. And the technology is getting smaller, cheaper, and requires less power than their predecessors. We can now wear these sensors and devices all day and have our measurements beamed to the internet for storage and analysis! Certainly, the Quantified Self movement is gaining momentum where self tracking is promoted and explored.

Still, we are early in the evolution of human data (see my post The Evolutionary Path of Data). Along the data continuum, we have just begun to enable data collection on a regular basis although we are just touching on being able to do it 24/7. For sure we can display/visualize/graph what data we do collect, but it needs to be more complete, consistent and frequent to enable discovery of more knowledge.

Coupled with my experiments in fitness, training, and health, I also realized that the insight we could gain from tracking our body’s metrics constantly was an enormous opportunity. For example, in the area of fitness and training, I see huge potential in guiding people to better health and fitness by exposing the results of what we are doing to ourselves at any time, like what we are eating, how we feel, and how we exercise. Already in Total Immersion, we are experimenting with individualized data driven training. It is my belief that beyond fitness and training, the ability to give us better feedback and guidance on treating our bodies better is untapped and presents the next horizon in health and wellness.

It is gratifying to see startups emerging in this area. Still, we are in very early days on the Quantified Self movement. At the moment, I am resigned to tracking and compiling metrics by hand and then working out insight from the data. I welcome the day when we are uploading our body metrics every second of the day and having intelligent systems tell us where we can do better, stop doing stupid things to our bodies, and live better, healthier lives.

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