Entrepreneur Tools: The Returns Analysis

tl;dr: To successfully target VCs, view your deal through their eyes.

pov2I got an outstanding piece of advice in my first job: “Always see the world from the other person’s point of view.”

If you’re trying to sign the pivotal customer, think from their perspective about what price they can accept. If you’re trying to recruit the killer engineer, understand how she weighs moving her kids when they’re halfway through elementary school.

And if you’re trying to raise capital from a VC – someone who invests other people’s money, and is out of a job if there’s insufficient return – analyze your own deal the same way he will.

I learned this the hard way.

In 2007 a somewhat younger and substantially less gray-haired Matthew was out raising a venture capital round for my previous company Lux Research. The good news is that it ended well – we were fortunate to bring on west coast VC firm Catamount Ventures, where partner Mark Silverman brought a rare combo of vision and pragmatism to the board. The bad news is that I wasted a lot of time pitching to firms that I should have known weren’t a good fit in advance, because the returns math couldn’t work for them.

My mission today is to arm you so you don’t make the same mistake.

When a VC investor hears your pitch, he’ll do math in his head to figure out if your company is in-bounds. (While bigger factors like team and market determine a “yes,” the math can rule out a “no.”) Typically, he’s answering two questions:

over90001) Can this investment move the needle? A venture investor can only attend to so many portfolio companies at once. To earn one of these limited slots, an investment has to be “needle-moving:” A successful outcome must be big enough in absolute terms to warrant a spot (regardless of the ratio of dollars out to dollars in).

As you can imagine, what’s needle-moving depends on the size of the fund that’s making the investment. A billion-dollar fund needs billion-dollar IPOs to return a profit; while investing $1 million into a company and getting $10 million back would yield a phenomenal 10x return multiple, you’d need 100 such outcomes just to break even! On the other hand, the same $10MM-for-$1MM return would be massive to a $10MM seed fund, where that single investment would put the fund in the black.

While there’s no magic number, a decent rule of thumb is that a needle-moving investment must return at least 10% of the fund to the VC in the success case. Here’s a close-to-home example: At Venrock we’re currently investing out of a $350MM fund. “Needle-moving,” according to this heuristic, is therefore $35MM. We tend to own 20% or so of the companies we invest in on average, so any one of them must be capable of being worth $35MM / 20% = $175MM when it’s bought or goes public – at an absolute minimum. If a successful outcome for your company would be getting acquired for $20-30 million dollars, you should not pitch me; target other investors with more appropriately-sized pools of capital who would view this outcome as a big win.

returnpaint2) Is the return multiple big enough? After assessing the absolute return, the math moves on to the return multiple, which is a relative measure. If everything goes right, how many dollars will I get out for each dollar I put in?

The return multiple that a VC investor seeks depends on the stage at which it invests, because of the time value of money: You earn about 8%/year if you make 2x your money over 10 years, but you could earn the same 8% by getting 1.08x in one year. As a result, early-stage investors (who invest at company founding and go 5-10 years before seeing an outcome) target higher returns than growth-stage investors, who aim to put in money shortly before the acquisition or IPO. Also, early-stage investors fund younger, riskier companies, most of which fail. Therefore they seek higher multiples in the success case than do growth-stage investors, who make some profit on most of the companies they back.

Again, there’s no magic number, but a good rule of thumb is that an early-stage VC needs to be able to envision a 10x return multiple if everything goes right. (A growth-stage investor, on the other hand, may see 2x to 5x as the target to hit.)

Armed with these principles, you can model the investment returns that a VC would get by putting money into your company, and use that information to target your investor search. Use the spreadsheet template that you can download here (which I’m archiving on the tools page) to do the math and model the return from the VC’s perspective. As inputs, you’ll need your financial projections (revenue, cost of goods sold, and opex); your capital plan (how much money you’ll need to raise and when); and a valuation metric (the spreadsheet uses price-to-sales, but you could also use price-to-earnings – in any case, set the metric by looking at comparable companies that have gone public or been acquired, and use a conservative consensus number in the model). What you’ll get out is the VC’s absolute return and return multiple.

As an example, consider this case:

returns_example3

Let’s say that this company is an energy analytics start-up trying to figure out if it should pitch to VC X, an early-stage investor with a $300MM fund. The company is raising a $10MM Series A aiming for a $15MM pre-money valuation, and thinks it will need another $25MM in two years to get to profitability. It believes it will have $80MM in revenue at year six, and an analysis of comparables shows that similar companies have been bought or gone public at 5x revenue. VC X would do half the A round ($5MM, purchasing 20% ownership) and invest its pro rata amount of the round to follow (i.e., 20% of the $25MM B round = $5MM more in two years), for $10MM invested over the life of the company (if everything goes right).

The good news is that, from VC X’s perspective, the investment clears the “needle-moving” hurdle. If the company hits its $80MM revenue target in six years, it’s worth $80MM x 5x = $400MM; VC X will own 20%, so its absolute return of $80MM is well above 10% of VC X’s $300MM fund size.

The bad news is that VC X can’t quite see its way to a 10x return. It’s going to put in $10MM in total ($5MM now and $5MM later) for an $80MM absolute return, yielding a multiple of $80MM / $10MM = 8x. This is good, but not excellent if it’s an upper bound; if it represents a true maximum it may not be enough. There would likely need to be compensating positive factors (phenomenal team, opportunity to expand to other markets, a pivotal early partner, demonstrably active acquirers) for this opportunity to compete against others.

A secondary point worth noting: The $10MM invested over the life of the company would be 3.3% of VC X’s fund – big enough to be a “real” investment worth a partner’s time, but not so large that it sucks up too much of the fund (VCs generally avoid putting more than 5%-10% of a fund behind any one company).

When you go through this exercise, run multiple scenarios – the VC you’re pitching certainly will! See what things look like with a slower revenue ramp, a lower valuation metric, a higher capital requirement (Venrock lore holds that companies typically require 2.5x more money over their lives than they anticipate at first fundraising), etc. However, I don’t recommend putting this kind of analysis into your pitch deck – it presupposes too much knowledge of the other party’s motivations and comes off as kind of arrogant. Keep it to yourself and use it to inform your financial plan.

Hopefully this tool will equip you for more successful fundraising. Let me know your feedback, and please point out my inevitable Excel errors for correction in an update…

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Posted in Numbers, Unsolicited advice, Venture capital | 1 Comment

Installing a Nest, Investing in Nest

tl;dr: Nest Labs performs magic – making energy efficiency awesome, even for the nontechnical and non-green. We’re delighted to invest in the company.

Back in February I acquired a Nest Learning Thermostat, famously designed by Apple’s original iPhone team. Looks cool! Learns your habits! Controlled from your phone! At the time, I felt the product was something of an overhyped fetish object for energy nerds, but I was happy to get one as I sit squarely in that demographic. (Plus, while the Honeywell thermostats in our home were nominally programmable, their interface was so obtuse that we never set them and thus wasted money.) Behold the tweet:

And then it sat in the box for four months.

It’s not that I didn’t want a beautiful piece of industrial design on my wall – it’s that I believed installing a thermostat was a perilous project that would consume a weekend afternoon. Every time Mrs. Nordan and I thought “you know, we really ought to put that thing up,” we quickly found a reason to do something else. And so it sat in the box.

Until June, when my colleague Matt Trevithick came over for dinner and asked me how we liked our Nest. I sheepishly responded that it hadn’t made it to the wall. Matt assured me that the setup was super-easy (he had one) and declared that we’d be doing the installation that very second.

Mrs. Nordan and I accepted the challenge. The ground rules: she’d 1) do the whole thing, 2) use only what came in the box, and 3) time it (it’s supposed to be a half-hour job). If you want the details, see this photo log, but the bottom line is that Matt was right. The entire process was simple; every conceivable thought was given to user-friendliness (down to the bubble level built into the backplate, so as not to install the thing crooked); and the network and app connectivity “just worked.” We clocked in at 22 minutes for the install, followed by 15 minutes’ worth of software updates (that’s what I get for waiting months to activate the thing).

Done. Niche nerd product: operational.

But in the two months that followed, it became clear that this was not a niche nerd product. I had underestimated Nest. As I used the thing, I saw that:

  • The experience was legitimately great. Our old beige box seemed out of place in a house otherwise filled with stainless steel; the Nest just looked better. We never programmed the old box because it was so awkward; the Nest had an iPad app. Even basic stuff was better – the AC would kick right in after we set the dial on the Nest instead of incurring a mysterious delay like before. I’d thought that setting the temperature from your phone was a stupid idea, until I found myself doing exactly that when I’d land at the airport late at night and wanted the downstairs to be cool before I got home.
  • It appealed to non-techies and the non-green. Most people who walked into our house and saw the thing wanted one, even those lacking a sustainability gene; they looked at it like an iPhone, not a climate controller. It became a living room conversation piece, like a stereo in the 1960s (I think of Pete on Mad Men). When Mrs. Nordan – a deeply nontechnical gadget-phobe – decided that it would make a great Christmas gift, the breadth of appeal became clear.
  • It delivered energy efficiency effortlessly. Nest’s default mode is to learn your schedule and make your house more efficient – thus saving you money – without you having to do anything. Little things that are transparent to the user, like turning on just the fan instead of the A/C compressor when it makes sense to do so, simply happen; you don’t have to know (or care). Every Nest household is a potential demand response node that doesn’t require the utility to roll a truck. Combined, those homes are a trove of fine-grained data that can be used to target retrofits.

I concluded that I wasn’t looking at a better thermostat. This was something else: the reinvention of an unloved category via thoughtful design. Nest was to its ilk what the Prius was to cars, what Tivo was to VCRs, or – best comparison – what Dyson was to vacuum cleaners (20% market share in the U.S. at 4x the average price point just three years after introduction). And if this team could make a thermostat (of all things) into an engaging product, who knows what else they’d come up with?

Shortly thereafter our energy team at Venrock evaluated Nest Labs as a venture investment. I’ve written before in this space that the smart grid has been a failure for consumers because it’s all too complicated and no one cares. To change the input/output ratio of consumption, the experience has to be awesome, winning on merits instead of getting by on shame. Having looked at this field for many years we’ve seen a ton of consumer energy propositions; Nest was the first one to clear this essential bar.

We’re pleased that Venrock is investing in Nest and backing a phenomenal team with an expansive vision. Matt, Ray Rothrock, and I – all of whom happened to be users before we were investors – are on the case. For her part, Mrs. Nordan has the second Nest unit going in upstairs.

Posted in Consumers, Energy efficiency, Smart grid | 4 Comments

Nest Installation Photo Log

tl;dr: Mrs. Nordan vs. Nest thermostat! Will it take an afternoon to install? Will we ruin our house in the process? No on both counts!

In June we installed a Nest Learning Thermostat in chez Nordan; I helmed the camera for the obligatory unboxing post, but promptly got occupied with other things and left the pics to languish on my laptop. Better late than never? For context on why I’m posting this months after the fact, see “Installing a Nest, Investing in Nest.”

Challenge accepted.

What’s in the box. What you can’t see here (because we were speeding through it and/or I am a lazy photographer) is that the screwdriver, wall screws, anchors, etc. needed to get the thing mounted are in the box too.

On the chopping block: The inscrutable Honeywell thermostat that we’re replacing.

Honeywell with the faceplate off. See those wires? They provide power and talk to the HVAC system. Our mission is to get them plugged into the right spots on the Nest.

The Nest box includes little labels to wrap around the wires as you unplug them, so you won’t forget which is which when you have to plug them back in. We duly attach them.

Penciling in holes where we’ll put the anchors for the wall screws. More user-friendliness: Note that the Nest’s backplate has a level built into the front of it so you won’t mount the thing crooked.

Drillin’. We probably could have just bored a hole, but, you know, completeness.

In go the anchors.

Attaching the backplate.

Good. Now time to plug the wires into the tabs. The labels on the wires have letters on them that match up to the tabs, so even we can’t screw this up.

Fiddling…

Done. Once the wires are plugged in you moosh them back before attaching the faceplate.

Faceplate goes on…

…and we’re up! Note that the display doesn’t actually look like that – it looks like a normal LCD display – it just showed up with these artifacts when captured through my camera.

Connecting the Nest to WiFi. Once we’ve done this, the stopwatch reads 22 minutes, at which time we’re done with the physical install. But, this being 2012, we wouldn’t be done without…

…software updates, of which we got three, totaling 15 minutes altogether; the Nest rebooted itself between each. This was the only annoying part of the installation and one that took longer than I expected (how big can a thermostat firmware update be?) I presume that if we hadn’t waited four months between getting the thing and installing it we wouldn’t have had three of these in a row. While it’s downloading, let’s get the iPhone app running:

App store entry. Confidence-inspiring rating.

On its way…

The app finds the Nest automatically; we have to click the thermostat itself to complete the enrollment. (I find myself wondering if/how/when this could be hacked. Be ever vigilant, Nest Labs.)

Success!

Total time: 37:09.6, roughly 22 minute install + 15 minutes of software updates.

Posted in Consumers, Energy efficiency, Smart grid | 2 Comments

What Makes a Great Cleantech Team?

tl;dr: Winning cleantech start-up teams are complete at founding, have strong pre-existing relationships, and include the inventor of the core technology.

This post was co-written with Josh Rogers, a former Venrock intern who’s now in National Grid’s Strategic Planning and Corporate Development group. A version of it also appeared at GigaOM.

A year ago I published a post called “What It Takes to Build A Cleantech Winner” based on an analysis of 18 cleantech success stories – venture-backed start-ups that executed big IPOs. The conclusion was that it’s not the technology (the best one rarely wins) and it’s not the market (if the market’s already big and attractive, you’re probably too late); instead, it’s the team that determines success.

That begs the question: What makes a great team?

To answer this question, you’d need to do two things. First, you’d need to analyze the personal histories of core team members at a slew of successful cleantech start-ups to figure out what they had in common. Second, you’d need to compare these people against their peers at unsuccessful companies in the same domains, to learn whether the winning teams differed from the losing ones.

Taking up the challenge was Josh Rogers – then a student at Tufts’ Fletcher School of Law and Diplomacy – who interned with me and conducted this research for his master’s thesis. Josh went about it like this:

  • First, he established a set of 27 winners – VC-backed cleantech start-ups that had either gone public on a major exchange since 2000 or filed an outstanding S-1 at the time of the analysis, and for which we could build fine-grained histories of the executive team. Examples: Tesla, Color Kinetics, Silver Spring.
  • Second, he assembled a set of matched-pair companies that were in the same industries as the winners and were founded at about the same time, but which unambiguously failed: They either went bankrupt or sold in a fire sale. We would have liked to have had a counterpart for every winner, but because so few companies have tanked completely instead of limping forward, we were limited to ten matches. Examples: Solyndra, GreenFuel, WebGen.
  • Then he collected exhaustive data about the backgrounds of every key executive in each of these 37 businesses – 122 people total – including their age, education, country of origin, past work experience, and a host of other variables (39 altogether).

When Josh began his work, we joked that maybe he’d crack a hidden code: Perhaps I’d hear “Well, Matthew, at all the winning start-ups the CEOs were in their 40s and joined from large companies, while the CTOs hailed from the following five universities.” If so, I could simply ignore all the other business plans I get and focus on the ones that matched the template. Hey, a man can dream, right?

That didn’t happen.

In fact, when we looked at the winners, we found that nothing at all seemed to correlate with success. Founding team members’ ages were all over the map, from Genomatica CEO Chris Schilling (26 years old at company founding) to First Solar impresario Harold McMaster (an octogenarian at 83):

No variety of undergraduate education dominated (although Ivy League degree-holders should perhaps beware):

Among graduate degree-holders, no university stood out. In fact, across the 51 successful team members with advanced technical degrees, 39 universities were represented with only three appearing more than twice (MIT, U. Illinois, and CMU):

And so on. In fact, the only interesting correlation we found was that team members at winning companies tended to be industry outsiders: A mere 28% of them had direct work experience in their start-up’s industry. However, this attribute didn’t predict success because it was the same for our sample of failed companies too (where 26% of execs had prior direct work experience).

At this point, we changed our approach. Perhaps we were asking the wrong questions? Instead of studying the individuals, Josh began looking at the relationships between them. It’s here that we found the trends hiding in plain sight:

Winning teams were complete at company founding. Of the 88 key executives profiled in the 27 successful companies, 74% were present at founding and another 9% joined during the first year. Only one out of six joined after that.

CEOs changed rarely. MBA orthodoxy holds that different stages of a company’s life require different leadership skills, so the CEO should be swapped out as companies develop. Our data didn’t support that. Eleven out of 27 successful companies had a CEO at founding who stayed through the IPO or S-1 filing; another eight were founded without a CEO, but recruited one (usually in the first year) who stayed for the long haul. Only eight winning companies changed CEOs, with only one clearly hostile transition (namely Elon Musk’s takeover at Tesla).

Successful founding teams had strong pre-existing relationships. At 74% of successful companies, at least two of the founding team members had strong relationships before the company was formed – either from working together in past lives (e.g. the four Color Kinetics co-founders, who shared lab space at CMU) or knowing one another well outside of work (e.g. Solazyme’s CEO and CTO, who became close friends as freshmen at Emory).

Winning start-ups included the accomplished core scientist who invented the technology as part of the founding team. Two-thirds of the winning companies exhibited this trait – think Frances Arnold at Gevo or Yet-Ming Chiang at A123Systems. I frequently see start-ups out of universities where the key technologist declines to join the founding team, choosing to remain in academia instead and consult with the company at most; this behavior doesn’t seem to correlate with success.

When Josh examined our matched-pair set of failed companies, they exhibited the opposite trends:

  • Six out of 10 failed companies replaced their CEOs along the way (versus three out of ten).
  • Only half had strong pre-existing relationships (versus three out of four).
  • Only three out of ten had the accomplished core scientist as part of the founding team (versus two out of three).

The conclusion: Great founders hail from every age, background, and school. What differentiates winning teams is their relationships. Successful cleantech companies tend to be bands of brothers and sisters – including the core inventor – that come together on their own, form a complete team, and have a leader fit for the long haul. In contrast, here’s the recipe for a failure: Find an interesting technology, assemble a team of competent people around it who didn’t previously know one another, and don’t worry about bringing the original inventor along.

I don’t want to present false absolutism here: There’s a great deal of subjectivity involved, the sample sizes are small, and the errors bars are wide. But these trends whacked me over the head hard enough that they changed the way I look at energy and environmental start-ups. It’s the team – and relationships make the team.

Posted in Numbers | 5 Comments

Bright Future for the Marginal Megawatt

tl;dr: Life is about to get a lot better for demand response and energy efficiency companies.

One of the challenges of venture capital is that you invest in companies now based on what you know now, but the world may look very different by the time the company exits (i.e., when it’s bought or goes public).

When people talk about this, they usually cite the investment bets that look dumb in retrospect – where investors deployed capital at a time of heady expectations and woke up to cold reality later on. (Amidst dot-com hysteria, otherwise-smart people could envision their morning coffee delivered by Kozmo and paid for with Flooz; afterward, not so much.)

However, one can also make the opposite blunder: Deciding not to place bets in a downer environment, and then missing the opportunity to reap returns when things look up.

This is the milieu that demand response and energy efficiency start-ups face today.

Whether they are reducing electricity demand at peak times (Enernoc, Gridium), deploying energy-efficient retrofits (NextStep Living, Ameresco), or doing high-tech real-time stuff to balance the grid (Enbala, CUE), these companies all have one thing in common. They traffic in what I call marginal megawatts – the MW at the very top of the load curve that determine whether the peaker plant gets turned on or whether a new transmission line must be built. The demand response players do this by clipping peaks while the energy efficiency ones do it by dropping the baseline, but they deliver a similar net result. (You could add grid-scale energy storage to this grouping if you wanted to.)

Such companies are poorly valued today. Public stocks tell the tale – for example, as I write this, Enernoc, Ameresco, and PowerSecure are all trading at less than 1x sales and 12x EBITDA. (For those of you who don’t often think about valuations: That’s bad for a growth company.)

This situation is about to change.

What’s the value of a marginal megawatt? In my mind, it should be proportional to two things – 1) the cost to deliver that same MW from conventional generation resources, and 2) the amount of free capacity that’s available to do the generating. Both are hitting inflection points right now.

First, let’s take the marginal cost per MW. For this analysis, let’s consider the market for “frequency regulation,” a horrible misnomer of utility-speak that means “injecting or removing power on the grid over fine time scales to balance supply and demand.” (The name comes from the fact that imbalances cause the grid to deviate from its 60 Hz AC frequency.) Frequency regulation is traded in open marketplaces on a $/MW/hr basis, and its price is probably the purest measure of a marginal megawatt.

As it turns out, the price of frequency regulation correlates very closely with the price of natural gas, because gas plants are usually the market price-setters. See the chart below, which plots the clearing price for frequency regulation (in the United States’ biggest electricity market, the 13-state PJM region) against the price of natural gas (as measured at the Henry Hub distribution center). The r2 on this is 0.80, meaning that natural gas accounts for 80% of the variance in frequency regulation price:

Natural gas prices started plummeting in 2008 due to the hydrofracking revolution and reached a 12-year low of $1.82/MMBtu this past April. As that price was below most producers’ breakeven levels, many folks speculated that drilling only continued because the exploration companies would lose their land leases if they didn’t keep making holes. Since then, new drilling in gas plays has cratered and the price has started climbing back up – it’s at $3.15 as of this writing, and the futures market has it north of $4 by the end of next year.

As the price of natural gas rises, so will the value of marginal megawatts. And there’s reason to believe that the price will increase sharply beyond 2013 if U.S. natural gas starts getting used in new ways – like being exported. Export applications currently filed at the DOE would ship out 16 billion cubic feet per day, which is two-thirds of current U.S. shale gas production!

So higher gas price = more valuable marginal megawatts. Now let’s look at generating capacity.

As goes GDP, so goes electricity demand. When U.S. GDP peaked in 2007, so did our electricity consumption. And when the economy tanked, electricity consumption fell. 2012 should be the first year that these indicators exceed their 2007 levels.

When there’s idle generating capacity around, the companies that own it get hammered. Consider independent power producers, the companies that operate conventional power plants. Their share prices closely track total electricity generation, which in turn tracks GDP – all of which dropped sharply after 2007:

So do I need to write this next paragraph? Only now is electricity demand getting back to its 2007 peak. Doubtless there were new plants getting built five years ago which were completed but unused, so excess capacity will likely persist for a couple more years. But, inexorably, that capacity will get mopped up as GDP rises and electricity demand grows with it, and sooner or later we’ll find ourselves bumping into a new ceiling. Just as predictably, the value of companies that resolve this supply/demand imbalance – those that deliver marginal megawatts – will jump. Note that when Enernoc went public right before the 2007 electricity demand peak, it did so at 20x the previous year’s revenues. It’s now trading at 0.6x. I’ll bet that looks really different in, say, 2016.

The kicker: Demand response and energy efficiency companies will slaughter conventional generators on cost. A new fossil generator costs $1 million per MW in capex, plus or minus, and requires fuel and transmission on top of that. Setting a big user of electricity up to curtail its demand by 1 MW costs maybe $50k – and that’s it. As we climb to a new electricity peak, generators will lose the battle for the marginal megawatt.

So whether your start-up is trimming peaks, lowering baselines, or synchronizing supply and demand, take heart. It’s been a long, hard five years. But a brighter day is just around the corner.

Posted in Demand response, Energy efficiency | 9 Comments

“Financing Your Start-up 101” in 45 Minutes

For this year’s ARPA-E Summit I was asked to give a talk about different ways to finance an energy start-up. The challenge as it was given to me was “cover all sources of financing – VC, angels, grants, debt, everything – in 45 minutes.” The ARPA-E folks have now posted the presentation publicly, embedded below.

If you’re looking for a high-speed primer on start-up financing, feel free to watch the whole thing. If you’d prefer to laugh, check out:

  • Live-playing NES Zelda as an start-up CEO analogy at 3:55
  • The investor reward system in one image at 12:30
  • A visual on venture capital demographics at 16:50

Posted in Unsolicited advice, Venture capital | Leave a comment

Why I Suspend Disbelief

tl;dr: Arrogant humans think we have the natural world all figured out. We don’t.

I spend a small but meaningful amount of my time at Venrock intentionally looking at crazy stuff. If you are developing a cold fusion generator or a zero point energy harvester and you have spoken to a venture capitalist, there’s a high probability that it’s me.

These topics account for, at most, a few percentage points of my investment scouting activity. But they’re enduring percentage points. There’s a lot of this kind of work out there, and I recognize that 99%+ of it falls somewhere on the spectrum between experimental error and deliberate fraud – so I narrow the funnel very quickly, much more so than in other domains. With that said, I endeavor to treat innovators with integrity and respect throughout, and on those exceedingly rare occasions where extraordinary claims hold up under initial scrutiny, I dig in with the same diligence I’d devote to the most-credentialed academic. (Of course, sometimes it’s a credentialed academic who brings the crazy idea.)

There are a few fellow travelers in the venture capital/angel financier community who share these investment interests and devote resources to them. Most, however, view these possibilities with derision – or simply feel they’re so improbable that every last second of one’s time is better spent elsewhere.

Let me give you an example of why I choose to suspend disbelief.

I got my first dose of middle-school biology in the mid-80s. And the living world as I learned it was pretty simple: DNA makes RNA, RNA makes proteins, and proteins do stuff. Information flows only in one direction, so the idea that you could pass on a characteristic that you acquired during your life was silly talk. We’d already figured out the handful of letters in the genetic code (easy!) and the sequences that corresponded to each amino acid (no prob!), so the only thing left was to decode the genome and the proteome, and then match the DNA up with the proteins.

Congratulations, you’ve solved life! Stanley Cohen and Herbert Boyer’s creation of the first recombinant organism in 1973 seemed to drive the point home – if we could insert foreign DNA into a living being to make it do what we wanted, certainly we had everything figured out? There were a few little things left to clear up – it wasn’t obvious why DNA was so often chemically modified, or why it was wrapped around these things we called histones, or why so much of it appeared to be non-coding junk – but surely those were minor points.

As we now know, that view of the world wasn’t wrong per se. It was just radically oversimplified.

The holes in the story began appearing almost immediately after Cohen and Boyer’s landmark achievement. In 1975 Robin Holliday and John Pugh (and independently, Arthur Riggs) observed that the methyl groups regularly seen hanging off cytosine and adenosine weren’t, as previously thought, errors in DNA’s signal: They formed a vital mechanism by which cells ramped expression of genes up and down. Shortly thereafter Michael Grunstein and his collaborators demonstrated that the histone proteins around which DNA winds were not simply passive spools, but that histones regulated gene activation depending on how they were chemically altered. In 1999, David Baulcombe showed that short strands of RNA could silence the effect of otherwise-activated genes – information flowed backward; the product of genetic expression could affect the expression itself! Finally, in the last decade, work by researchers such as Larry Feig and David Sweatt has controversially suggested that a mother’s life experiences can endow her developing fetus with features that weren’t in the fetus’s DNA at conception.

These exceptions to the rule have piled so high that we have a name for them: Epigenetics. And a whole slew of start-up companies are aiming to profit from what was heterodoxy 30 years ago.

I have a sneaking suspicion that physics today is something like biology in the 1970s.

Once you split atoms with such destructive force as to kill tens of thousands of people, it’s pretty easy to convince yourself that you’ve got it all figured out. And, as I see it, that’s what the academy did post-World War II after the nuclear genie left the bottle. Sure, there were some minor details to clear up – like the particulars of the units of matter and force that shape atomic interactions, and how to harmonize the way things work at large scales with how they work at small ones – but for the most part, we had it nailed.

Half a century onward, our list of known and suspected subatomic particles exceeds 200, and it continues to grow. We can’t precisely predict the size, structure, or properties of anything more complex than hydrogen. We’re no closer to integrating quantum mechanics with general relativity than we were when I was a child. (Flame shield up: I realize there will be healthy disagreement on these points).

Perhaps these anomalies aren’t anomalies at all. Maybe they are evidence that we don’t, in fact, have everything figured out.

Improbable, yes. Impossible, no. So with a wink to Jean-Baptiste Lamarck, who is doubtless shaking his fist from the grave – mocked for decades for suggesting that inherited characteristics could be acquired, and now facing an ounce of vindication through epigenetics – I suspend disbelief. I trust that there are improbable breakthroughs in the physical sciences yet to be made: breakthroughs which will transform how energy is produced and used. I’m with Bill Gates – we need more crazy energy entrepreneurs!

Takeaway: Whether you are a university scientist or a garage inventor, if you’re working on a way-out-there energy idea and you have data that shows something extraordinary, call me. Casimir effect, solar antennae, low-energy nuclear reactions, electricity crops: The door is open! I won’t (and can’t) promise you time or engagement a priori; if I did, I couldn’t do the other 98% of my job. But I do promise you a hearing – and respect.

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