tech | growth | venture | Perspectives from an operator turned VC in an underserved market
home,blog,ajax_fade,page_not_loaded,,qode-title-hidden,qode-theme-ver-17.0,qode-theme-bridge,wpb-js-composer js-comp-ver-5.5.5,vc_responsive

If I had the answer to the question above, I’d likely have a different career.  However, this question seems to be at the top of my network’s mind as evidenced by a few articles that recently appeared in the Houston Chronicle being shared across email and social media.  Given that I do believe the middle of the country needs more startup growth and is ready for it, it’s also an important issue to have a framework around.

Can Houston Avoid Mistakes of the Past as it Tries to Build a Tech Scene?

For startup ecosystems, perpetual death by a thousand headlines?

The Problem Texas Business Leaders Are Afraid to Name  – Houston’s biggest industry is changing fast, can Houston lead the way?

This isn’t my typical format as I wanted to organize my thoughts around ecosystems and what can make them grow over time and thought this list would be a good way to do so.

It’s not meant to be comprehensive or even written in complete sentences, but it is a simple outline for thinking through the signs an ecosystem is ripe for more capital with a specific lens on factors that I believe are over-hyped and those that aren’t given enough attention / are harder to manufacture.

Over-Indexed Ecosystem Drivers

  • Density
    • Doesn’t exist in the most active and vibrant startup ecosystem in the world – Silicon Valley has three main hubs – Palo Alto, Menlo Park, and San Francisco
    • Localized density matters – i.e. Santa Monica in LA
    • Could matter around particular sectors, but the evidence isn’t there to support yet. Example, Houston doesn’t have outsized advantage on energy tech yet
  • Cost of living and cost of doing business
    • There’s an equilibrium here, but a sufficiently high cost of business or living means startups fail at the right rate or talent seeks jobs that are higher paying.  Often, not always, higher paying jobs are associated with companies that are growing.
    • Healthy failure rate results in a redistribution of talent and capital to new or better ideas
  • Government policy
      • Founders usually have decided to live somewhere based on other factors like connections, family, and quality of life long before starting a company.
      • Founders tend to value talent and customer access. However, the dynamic here is changing due to the decentralizing workforce and tools that have been built to accelerate that change.
      • Policies are usually slow and change depending on the administration, hard to count on them for long-term growth advantage.  Often slanted to bigger businesses and more geared to press than action.
      • The exception could be fund-of-funds like Renaissance Ventures, Detroit and Ann Arbor currently growing quickly with companies like Duo, StockX, and Rivian. However, secular trends are also at play, especially in the automotive industry.


Under-Indexed Ecosystem Drivers

  • Growth-tested talent
    • Silicon Valley has had this since Fairchild and Intel
    • Software and business talent that have scaled inside high-growth organizations is rare and can have outsized effects
  • Exits (yes, they’re under-publicized and definitely the hardest to “create”)
    • Create Wealth
      • Ideally both deep (bigger individual wealth) and wide (several people become wealthy)
    • Frees up talent
      • New executives available
      • New startup creation
  • Active networks
    • Mutually beneficial introductions
    • Follow up on said introductions/promises is the norm
    • Diversity – talent comes from varied backgrounds, universities, cultures, etc…
      • Gender and minority parity is still lagging behind in every metro, but ones that adapt quickly will likely have a competitive advantage
  • Universities with a history of technology or investing success
    • Not required, but help.  Can be supplemented with large companies producing talent as Amazon and Microsoft have done in Seattle.
      • Silicon Valley = Berkley and Stanford
      • Boston = Harvard and MIT
      • Chicago = University of Chicago (Booth) and Illinois
      • Austin = University of Texas
      • Boulder = University of Colorado
      • Atlanta = Georgia Tech
  • Customers
    • F1000 HQ’s or offices for enterprise software
    • Startups – great businesses are built off the growth of others, i.e. Twilio and Uber, PayPal and eBay, Salesforce Ecosystem


Today, I’m excited to announce that we are welcoming Ensemble Energy into the Intelis Capital portfolio to help them continue their mission to enable renewable energy sources to become more competitive by implementing more efficient operations and maintenance. Through their machine learning platform developed from years of industry knowledge, Ensemble empowers operators to better control costs, increase energy output, and lengthen the life of critical generation assets.

The Team

Sandeep and Rob are truly respected experts in their field – a quality that matters in industries like energy where the best entrepreneurs tend to bring domain-specific knowledge and can apply it with innovative software platforms to modernize operations and provide meaningful value.

Needless to say, the credentials of the team are impressive, Ph.D.’s and master’s degrees from top universities like Indian Institute of Technology, Stanford and Maryland, but more importantly in our conversations with Ensemble’s customers, all of them went out of their way to praise Sandeep and Rob not only as founders but as people.

Rising Expectations and Costs

As our grid continues to see the penetration of renewables and subsequently lower energy prices, wind farms will no longer operate in a passive, volatile way on our grid systems. Instead, they will be required to be more flexible and dynamically controlled to help maintain system integrity and respond to market conditions while operating at part-capacity. This change in operating conditions will require owners and operators to better model the impact of maintenance on lifetime assumptions and create turbine life projections that can be continuously re-evaluated and scrutinized.

In North America alone, wind turbine operators are projected to spend over $40B in O&M by 2025 a figure does not include issues like false positives and the opportunity cost of downtime due to equipment failure. Not only are O&M costs increasing, but the current fleet of wind turbines is aging and will reach an average age of 7 years in 2020 – the exact age where parts are significantly more at risk of breaking down.  As these trends play out, we believe Ensemble is well positioned to predict failure and will enable operators to protect themselves against significant downtime while extending asset life by refitting with spare parts that cost as little as 5-20% of a new turbine.

Offshore Wind Growth

The fastest growing segment within the wind industry is the offshore market, particularly in Europe and China. As you might expect, the operations and maintenance costs of these turbines are much higher than their onshore counterparts. In some cases, O&M costs can be as much as 5 times higher.


Two unique challenges lead to this significant uptick in operations and maintenance spend: weather and access. Ocean storms and significant waves can limit the windows of time O&M professionals can access a turbine thus predicting WHEN an asset will fail becomes a crucial feature.

Additionally, accessing an offshore wind turbine isn’t as simple as driving up to it in a truck and crane. Logistics account for as much as 50% of maintenance costs for offshore wind owners, and as a result, the industry places a higher priority on asset monitoring sensors and accurate insights since companies can’t afford to move people and equipment when it isn’t necessary.

We’re thrilled to be partnering with Sandeep and Rob as they look to build a company that optimizes one of the crucial renewable energy sources and are excited to see them grow with this new round of funding.

It’s possible I exaggerated a bit on the title above, while the Death of the MVP might be extreme, the days of the “minimum” (i.e. move fast and break things) approach to building high-growth software are long gone and we’re now in the golden age of “viable” (i.e. build something customers love) being the best path to sustainable growth.

To be clear, I’m not advocating for a completely blind launch without customer feedback. Instead, I look at the approaches of startups like Superhuman and Notion, both had very small, exclusive initial user bases from which they could collect feedback. Superhuman founder and CEO Rahul Vohra has discussed at length how his team built a process to discover product/market fit and a roadmap without a public launch.

Minimum = Low Cost 

The term MVP was coined in 2001 and made popular by Eric Ries and his book The Lean Startup, but a lot has changed since then.  In the last two decades, we’ve witnessed an exponential decline storage costs coupled with the rise in open-source software, and more recently no-code software is beginning to approach an inflection point for adoption by the masses.

The result: cost is significantly less of a factor in launching a software product than it was 20 years ago and almost anyone can or will soon be able to achieve a “minimum” product meaning viability/customer evangelism becomes the differentiating factor.

Look no further than your phone, US consumers had an average of ~100 apps installed on their phones in 2017, but only use 40 on a monthly basis (I’m betting daily is about 25% of that number) meaning attention and usability are at a premium to cut through the noise of home screens.

When You Can’t Move Fast and Break Things

The old Silicon Valley adage “move fast and break things” has worked extremely well for several decades, however the stakes for emerging technologies in analog industries are much too high for enterprise customers to accept this approach from would be vendors.

The firms in these industries utilize RFPs that often clearly define problem sets and require 12+ month procurement cycles rendering the “move fast” motive behind the MVP approach moot. They are searching for solutions that protect, connect, or extend the life of capital intensive assets that are 10+ years old – there are certain things that you cannot break and data you cannot lose.

However, the length of these sales cycles and need to work with trusted partners often means problem validation happens in a more transparent and organic nature. The trade-off for speed is the validation of a product that solves a material business case and results in a long-term paying customer.

Validation = Healthier Investing Climate

The result has been a healthy venture investing climate in industrial tech as the valuations are increasing where traction (validation, product/market fit) becomes apparent.  According to Energize Ventures partner John Tough, Series A valuations have been more or less steady over the last decade despite deal volume increasing 10x.  However, Series B and especially Series C valuations are increasing which indicates that capital is willing to pay for established winners.

This is great news for entrepreneurs and early-stage investors alike in that the market seems to be rewarding patience and the building of fundamentally sound business models.

Future Sectors

Rather it is through market forces as is the case in consumer software or necessity as in industrial tech, the decline of the MVP has arrived.  I expect the trend to be further compounded as founders and investors look to disrupt industries with high-barriers of entry due to regulation or consumer confidence.

Automotive and Biotech are perfect examples of sectors where anything less than near-perfection won’t be accepted by regulators or consumers, and industries like real estate and construction have decades of entrenched interests that won’t adopt products unless they are seamless and obviously better than the status quo.

The MVP era was the most productive in human history and the philosophy undoubtedly helped countless startups grow beyond their wildest dreams.  However, we’re now in a new age where customers expect the best and those who can reliably solve problems in a way that creates long-term customer value will have the upper hand on the competition.

Currently, there’s a fascinating game of 3D chess playing out in the energy industry as utilities are under siege from tech giants like Amazon and Google, oil and gas behemoths like Shell and BP, and startups.  The attacks from these new entrants are coming on multiple fronts – Amazon and Google want to own the customer, Shell and BP want to be the electricity provider and startups are attacking the business model with new technology.

This leaves utilities with a choice – do they become strictly the poles and wires company? Or do they pivot into the services industry in the same way e.On has in Germany and how telecom companies did post the Telecom Act?

Any founder that has met with me this year has most likely heard me rave about Hamilton Helmer’s 7 Powers: The Foundations of Business Strategy.  The book has provided me and countless others with a “simple, but not simplistic” framework to evaluate businesses and the markets they participate in.

My favorite power of the seven is counter-positioning which applies when the expected damage to the existing business prevents incumbents from challenging a disruptor in their market. The most basic concepts are:

  1. Newcomers adopt a superior business model or technology which the incumbent does not mimic due to anticipated risk to the existing business
  2. New product/business model has a high degree of substitutability for the products from the incumbent
  3. Risk-adjusted expected collateral damage to the incumbent is high due to the uncertainty of a new approach
  4. Addressing the new entrant requires upending the existing business and the turmoil risks destroying value as understood by public markets
  5. Incentives put in place for executive compensation are often tied to performance defined by stock price/market cap

Image result for counter positioning 7 powers

Historical examples of counter-positioning include:

Kodak and the digital camera: I used to believe Kodak inventing the digital camera and not capitalizing on it was one of the biggest blunders in business.  However, at the time digital photography as a stand-alone business was not interesting to Kodak because it would cannibalize the business where they had the most power (film), and they did not have the necessary resources to create power in the new market (image storage).  The negative NPV of creating that power in combination with no one understanding the impact of the semiconductor and it becomes easier to see why Kodak passed on the digital camera opportunity.

Netflix and Blockbuster: Blockbuster might have potentially competed with Netflix on a DVD subscription business, but once Netflix went to streaming, Blockbuster was done. By the time the realized what was going on, Netflix had too much share and too much power in a substitute good with a better business model.

Where does this leave utilities?

From a strictly growth and relevance perspective, utilities should absolutely start thinking about how they can add more value to the network than just the infrastructure or risk eventually getting left out of the growth that is ahead.  As smart-home devices continue to penetrate the market and EV’s gain share, “service providers” for consumers will become necessary and likely valuable, but it’s unclear if utilities will be able to make the transition, if regulators will allow it, or if the NPV trade-off makes sense since the opportunity cost might be giving up lucrative business units like transmission or generation.  e.On made a similar decision in 2018 when it swamped generation assets for the retail and transmission business with Innogy to focus on being a service provider so we’ll see how the new landscape begins to take place in the coming years.

It’ll be fascinating to see if the same regulations that have made utilities a monopoly for decades will be the regulations that prevent them from competing in a modernized energy system or if utilities can avoid the same fate as Kodak and Blockbuster by deploying strategies similar to AT&T and Verizon post de-regulation.



This thread on Twitter about the evolution of marketplaces is well worth a read to anyone working in that space.  Most of the low barrier, high-frequency markets have been built and marketplaces are now moving into managed services which are much more difficult.

There are still many areas where the purchase decision and actual completion of the purchase require extra work in the background.

The added complication here is that a lot of high-value marketplaces are in industries where the transactions are low frequency.  As a result, customer knowledge is low and the trust barrier to acquiring their business is high. Examples include home buying, car purchases, and in my experience energy choice.

Consequently, the largest return on $ spent in these industries is on providing the transaction layer while running lead gen on the services because the customer isn’t buying frequently enough (18+ months) to be brand loyal.

In these markets, until consumer confidence in online transaction grows or a dominant brand captures most of the share the costs to retain are too high to also offer services.

So, instead marketplaces focus on purchase & lead gen services b/c it’s the most immediate payback. If not VC backed, this creates great mailbox money for a founder.

All that to say the customer almost always has to be purchased in these markets and the services don’t buy a high frequency of repeat business. Even though their complexity/infrequency could use a high level of end to end service.

Last week, the Wall Street Journal published an article exploring the idea that the smart home is really part of a bigger strategy for Google and Amazon to enter the electricity industry. This has been talked about for a long time amongst people in the space as it’s always been clear Amazon and Google have an interest in becoming major players in energy.

Utilities have made their usage data hard to tap into for decades. Instead of playing a key role and monetizing that data, Google and Amazon have started going around them and, just as both have collected data on our purchasing trends for years, they’ll soon be able to not only understand when we consume energy but where and how.  Energy consumption is a “footprint” of our daily lives inside of our homes.

For example, how valuable would it be for a restaurant to know I get home on average at 6P every day, go to my kitchen looking for dinner, while listening to the jazz music station on Alexa?  You can extract all of that information from the following: connected locks or garage door openers, smart lighting, smart thermostat, and Alexa or Google Home.  Or, as a TV add exec – I want to know when you are in front of your TV and buy things on Amazon.  If you use a Fire Stick, smart lights, and your phone.  I now have a pretty good idea of when to place my ads.

Additionally, only 3 areas make up most of our residential energy consumption – HVAC, water heating, and lighting.  Now that we have “smart” versions of all three algorithms will begin to estimate usage in a far more valuable way than the current techniques used by utilities.  The current methods are optimized for commodity trading, the new methods will be optimized to capture the value in our purchasing and living trends.

It’s also important to note, but not talked about here that consumer expectations are changing. Google and Amazon aren’t just tapping into data, for the most part, they make customers happy across a variety of other products. To this point, they’ve built up enough consumer trust that we’ve allowed them to enter our lives in a deeply personal way without much push back.  Meanwhile, utilities are often at the bottom of customer satisfaction surveys and only thought about when things go wrong (outages and high bills).

Add these issues to things like the emergence of microgrids, storage, and more stringent rate regulations and it becomes easy to see why the current utility model is in big trouble despite increasing demand for its product and the value that can be extracted from our energy consumption data.

Often, when we’re talking about our thesis at Intelis we describe it as “the digitization of analog industries” or “the digital revolution for analog industries”. But what does that look like in practice?

For simplicity’s sake, we think of analog as not using software or technology to improve outcomes.  The pen and paper industries still rely heavily on older systems and intuition to drive results, but external forces like increased complexity and consumer expectations combined with internal forces like aging workforce and infrastructure are pushing them into the information economy.

The digital age has brought several business model innovations, but most have centered primarily on two new types of economic forces:

1. Information goods: anything that can be digitized where the value is determined by the information it contains.

2. Network effects: the multiplying force of the power information goods because they allow instantaneous consumption and distribution. That is they catalyze the distribution of a free, perfect copy from one to one or one to many.

History has shown that if companies are able to build/leverage these two economic powers the results can be transformative.  Uber and AirBnB are the prime examples for this, they both took excess capacity (information) and applied the network effect of a marketplace to multiply the power.

We’re finally seeing these forces permeate the energy industry via the following trends:

– Endpoints are growing exponentially: The data produced by sensors, drones, EV’s and smart home devices are turning various parts of the energy value chain into information goods.

– New data transparency/architecture: The groundwork is being laid by several companies looking to make information more readily available and easier to navigate.  These startups are working on new data architectures, API platforms, and real-time demand solutions that leverage the continuously growing number of data sources to drive reliability for grid operators and affordability for consumers.

The great thing about energy is that a lot of the hard groundwork has been done as a result of the 2007 boom in cleantech, similar to how the groundwork was laid for the internet before the bubble burst in 2000 or – if you prefer to go back centuries – how the railroad boom laid the foundation for the first Industrial Revolution.  Just because the first pass doesn’t end well, doesn’t mean the enormous amount of progress disappeared.

While we see energy as the industry most ready for this transformation, it is not the only “atoms” industry that fits the criteria above – transportation, agriculture, and manufacturing are also unlocking their potential by becoming more connected and data-driven than ever. We often hear about how “connected” our world is, but the truth remains we still have a massive opportunity to leverage digitization in the industries that contribute the most to global GDP.

The overarching theme of my goals this year is to stay more focused. It requires consistently organizing and de-cluttering my schedule and mind. Knowing that this was going to be the case, I started honing in on a productivity stack in late 2018 that allowed me to spend time on deeper work.

After a few weeks of tuning, and months of experimenting with different products, I think I’ve stumbled upon a setup that works really well and wanted to share. In addition to my email and calendar, below are the products that I’m finding I’ve worked really well to help keep me moving forward with purpose.



I’ve been using Airtable on and off for the last year or so, but the improvements they’ve made in usability over the last 6 months have turned me into a more loyal user.

The most useful thing I’ve built in Airtable is my Personal Relationship Manager (see above). I think of this as a happy medium between LinkedIn and my iOS contact list and the result is a curated professional network.

One of my favorite ways to use the database is the “needs” column on the contacts tab. This allows me to track the needs of my network in a quantitative way while also making better connections that are deeper than “you two should meet” across my network.

Most of the columns and tabs are self-explanatory, but one of the best features within Airtable is the ability to link multiple tables/records across a database with just a few clicks. For example, I have a “Companies” tab and an “Interactions” tab that are used for this purpose.

  • Companies: This is just a basic list all of the companies my contacts are connected with. The easiest way to do this is pulling a CSV (link) from your LinkedIn account and add the companies column from the resulting spreadsheet. This allows me to create a linked field in both the “Contacts” and “Interactions” tabs which is useful if contacts have multiple companies or interactions include multiple companies in attendance.
  • Interactions (the magic): Here is where I record all of the meetings I have with my contacts. Again, most of the fields are self-explanatory, but I’ve also included a hand-written notes column. There’s nothing like pen and paper in a meeting to show people you’re engaged and disconnected from your device plus it’s my preferred method of notetaking with a few exceptions like annotating decks or PDFs. I simply include a picture of my notes on the row once it’s over. If you take notes in something like Evernote or OneNote you could include a link to those notes instead.

Airtable is great for a multitude of things, but this is my favorite use case and highlights its flexibility extremely well. It’s also a great tool for project management and the site has several preformatted bases that you can customize to fit your needs.


A few months ago, I purchased a Microsoft Surface Go (link) and as a result, I’ve migrated from Evernote to OneNote. I’m as surprised as anyone that I actually favor the latter over the former.

Microsoft did a fantastic job developing the stylus for the Surface and OneNote’s freeform nature allows me to take advantage including annotating PDF’s as I mentioned above. Additionally, I like the overall layout of the app much better than Evernote because it feels more like Google Docs and Word.

I use the following notebook structure:

  • My Notes – think Cabinet or Inbox in the GTD method, but more organized. I have sections in the notebook for Ian, articles useful for startups that I share regularly with founders, podcast notes, email templates plus a few more that are personalized to my work style.
  • Kindle Notes – I occasionally read on Kindle and after I complete a book I clip the notes into OneNote (link). This makes the notes more readily accessible as well as searchable.
  • Saved Tweets – I set up an IFTTT integration to have all of my linked tweets sent to OneNote with the primary goal of having them be searchable. It also acts as a bookmark system for tweets.
  • Saved Articles – see above but with Pocket
  • Diligence – resources and templates for performing due diligence on prospective companies
  • Portfolio Companies – see above but for portfolio companies. This is where I track board and touch base notes as well.

OneNote still has some work to do on recognizing handwriting for the “ink-to-text” feature and searching notes that are scanned in from handwritten work. However, it is actually really great for most things. And speaking of things…


Things3 has become my default to-do list manager and I’ve tried just about all of them. Unfortunately, Things is available only on Mac devices but that hasn’t stopped me from becoming a power user.

The ability to email your to your to-do list (hint: create a contact) and the integrated calendar view are easily the two best features of Things. The “Today” and “Upcoming” lists will not only bring in the tasks you need to get done today but also your meetings which provides a holistic look at the time period ahead.

My to-do list is largely tasks that have come from email or one-line thoughts/tasks that come into my head randomly so my to-do isn’t where the details of the work come together. That’s where I use OneNote. For example, let’s say I had this post as a to-do. In Things, it would be under my “blog” list as “Productivity Stack” then the article itself is written in OneNote.


This is probably more than anyone cares to know about the way I work, but I’ve always been a fan of sites like Lifehacker and My Morning Routine that highlight how others go about their days.

Hopefully sharing this post, and the granular boring details that go with it will help prevent others from going through the hassle of tinkering with a setup for months like I’ve done previously and allow them to focus GTD rather than reading about how to GTD.

2018 was the year big tech announced it was leaving the west coast and moving to the middle of the county the other coast.  Apple, Amazon, and Google all announced expansions of their campuses in other locations and since Austin was the only city to be rewarded one of these HQ’s – I hope we’ll see cities like Dallas, Houston, Atlanta, and Nashville continue to invest in their startup ecosystems in order to grow the next great generation of tech companies.

Perhaps foolishly, I’m taking a stance and publishing my predictions for startups in the Southeast. Like most forecasts, the only inevitability is some of these, if not all, will end up wrong.  However, having a point of view to use as a starting point is important when everything in the startup world is far from certain.

A major Silicon Valley venture firm (or 2, or 3) leads a $50 million+ round (or 2, or 3) in the Southeast

By now, it’s become obvious that innovation is happening all across the country and is being highlighted by groups like Steve Case’s Rise of the Rest fund.  I suspect 2019 is the year major Silicon Valley firms lead significant rounds in Southeast-based startups.

This has happened before as Kabbage was able to raise $250 million from Softbank in August of 2017, but with the rise of mega funds we’re due to see the occurrence more often.

Within the last 24 months, several startups have raised meaningful rounds from coastal VC’s with deep pockets or close ties to them.  Those names include Bestow, Pull Request, New Knowledge, Map Anything, Spark Cognition, and OJO Labs.  It’s not hard to imagine one of these firms picking up a large round in 2019.

Early-stage deals decline as family-offices pull back from direct investing in startups…

Increasingly, family offices have become the de facto seed funds of the non-costal markets by leading deals and taking board seats. In 2019, I think it’s possible we’ll see a slowdown of that trend as family-offices become more likely to take cash to the sidelines due to public market uncertainty.  If the fed continues to raise rates, it becomes entirely possible FO’s turn to private debt and distressed assets or fund impact projects where returns are only part of the equation.

For most of these family offices, venture is a very small part of the portfolio and is complementary to another business segment where they have expertise.  Unlike those businesses, the startup economy is not as correlated with the macroeconomic trends.  Yet, this doesn’t mean that those investors won’t take a more cautious stance in 2019, especially at the margin where growth isn’t as obvious even with added synergy.

I’m not convinced those family offices won’t miss out on investing in a new wave of very important startups especially in the analog spaces where the Southeast will be a part of the conversion from an industrial economy to an information one.

…but Series A rounds attract more attention from coastal VC’s

The emergence of mega-funds has increased the size of Series A rounds dramatically in the last few years. In 2017, the average Series A was around $7 million according to Pitchbook but perhaps most astonishing is that 39% of valuations were $25 million+ and less than 25% of those deals were under $10 million.

Investors, especially mega-funds looking for options, are concentrating their capital into deals they view as higher-quality.  My guess is that when the 2018 numbers come out, we’ll see more attention being paid by coastal firms with “smaller” funds investing outside of the coasts as they are priced out of the “hot” deals in Silicon Valley by funds comfortable with deploying more capital earlier.

This is a trend I suspect will continue into 2019 as there is no shortage of capital to invest in early-stage companies, but the non-costal companies will have to prove they are worth the investment to overcome the perceived limitations of location.

If a slowdown occurs, it will look more like 2015-2016 than 2008-2009

I suspect we’ll see a slow down in venture investing this year, but it won’t look like 2008-2009.  Instead, the drop will be more similar to the one in 2015-2016 where the total number of deals fell by about 15%.

It’s unlikely we are headed for anything like the Q1 2009 where venture funding fell by 50% from Q1 2008 to a total of $3.9 billion and continued on that trend for the remainder of the year before 2009 ended up as the slowest year since 1998.

However, startups can most likely expect more diligence from investors, particularly family offices where fees on invested capital aren’t in play, and valuations to come down even for the highest growth companies. Regardless, the bear market can be a good time to invest as great companies are still founded during recessions.

Here’s a small sample of firms that many expect to IPO in 2019 that were founded during the last recession.

Airbnb (8/2008)

Uber (3/2009)

Slack (2009)

Cloudflare (2009)

Pinterest (2009/10)

It’s possible I sound both optimistic and pessimistic at the same time, and that’s the case.  I am incredibly optimistic that the focus on innovation and technology away from Silicon Valley will continue to propel the industry to the forefront in new metros.

On the macro side, I’m less sure as a slow down seems all but certain at some point in the near future and while tech is, in theory, an uncorrelated asset that’s never the case in practice as funding always slows when the economy does the same.

Regardless, there’s no doubt that 2019 is going to be an exciting year for startups between the coasts and I can’t wait to see the trends that emerge.

One of the most popular posts I wrote in 2018 recapped the books I’d read throughout the year, so I’m bringing it back in 2019.  I’m undecided on the format so it may change from time to time, but the three most likely candidates are:

  • Three takeaways, primarily consisting of the three passages I found most interesting
  • One big lesson / theme
  • Intuitive point v. counter-intuitive point (this is my favorite, but I am unsure it will apply to every book)

Below are the books I’ve finished in 2019 in reverse chronological order.

8. Farsighted – Steven Johnson

Really enjoyed this book for mental mapping around decisions with a lot of unknowns.  First half is really great, then the second half became redundant.

  • There are three types of unknowns:
    • Knowable unknowns – those you can research and can be found via good mapping of the problem
    • Inaccessible unknowns – the information to solve the problem exists, but for some reason can’t be obtained
    • Unknownable unknowns – uncertainies that arise from the unpredictablity of a system
  • The most essiential form of doubt involves questioning the options that appear to be on the table.  Making complex decisions is not about mappting the terrian that will influence each choice, but instead is a matter of discovering new choices. The key is to trick or train your mind into realizing additional options / possibilities exist.

7. Loonshots – Safi Bahcall

A must-read for anyone working in a large organization or startup that is now in the position of protecting franchise products.  Bahcall’s writing style is very enjoyable, he uses stories from history as the narrative for his unique insights. The stories also cover a wide range of industries from biotech to technology to military so there’s something for everyone for the entirety of the book.  My favorite takeaways:

  1. P-type v. S-type loonshots – product innovations are harder to develop and being a continual “hit-maker” is difficult, but competitors often die quickly.  e.g: streaming video  Strategy loonshots are difficult to understand or spot because of their complexity as a result competitors die more gradually but the strategy is hard to replicate.
  2. The Moses Trap – it’s easy to make sure ideas only advance at the pleasure of leadership, but a balanced exchange between those in the field and leadership making loonshot decisions is required to continue innovating in a way that grows power within a market.
  3. The Magic Number – balancing career and company interests is a tough challenge for any leader, Bahcall offers his reasoning as to why 150 is a magic number and the variables that prove it.


6.  Cradle to Cradle: Remaking the Way We Making Things – William McDonough and Michael Braungart

I really enjoyed this take on the history of our industrial processes, even if I strongly disagreed with some of the takes in the middle to latter half of the book.  Early on, the break down of linear processes built for an increasingly exponential world had me nodding along as our legacy manufacturing processes were largely built with nothing but growth in mind without considering several variables we did not understand at the time.  Given what we know today, would we choose differently?  A few key takeaways:

At its deepest foundation, the industrial infrastructure we have today is linear: it is focused on making a product and getting it to a customer as quickly and cheaply without considering much else.

To achieve their universal design solutions, manufacturers design for a worst- case scenario; they design a product for the worst possible circumstance so that it will always operate with the same efficacy.

Today’s industrial infrastructure was designed to chase economic growth. It does so at the expense of other vital concerns, particularly human and ecological health, cultural and natural richness, and is unintentionally depletive of resources.

5.  Best Practices for Equity Research Analysts: Essentials for Buy-Side and Sell-Side Analysts – James Valentine

Not as helpful as I had hoped.  I was looking for a book that would help me develop new frameworks for both quantitative and qualitative financial research. This book is not that – it’s more focused on the day-to-day of a great research analyst including where to get information and time management.  I did still pick up a few helpful tips like sector analysis and critical factor flow charts, but the book spends several chapters on Excel, information sourcing, statistics, etc.. all of which I already knew.

4. Red Notice – Bill Browder

It’s not often that I read a book mostly for fun, but I heard great things about this story so I decided to give it a shot especially since I’ve been behind the pace I’d like to have for the year.  Bill Browder’s story is amazing, he certainly followed the Keith Rabois approach of being the best at one thing, unfortunately, that thing was making money in Russia.  What follows is an unbelievable story of fraud, theft, and murder by some of Russia’s top oligarchs.

3. Influence – Robert Cialdini

This book highlights the 6 principles on which we all make our decisions, it’s a great book for anyone in sales or marketing that wants to better understand the behavioral psychology behind our decision-making process.

Lesson: We all make decisions on stereotypes, our rules of thumb that classify things intuitively.  Once we see a trigger connected to one of the six principles of decision making we almost always answer in the affirmative. This process has allowed us to advance as a species in that we’ve extended the number of operations we can perform without thinking about them.

2. How the Internet Happened: From Netscape to the iPhone – Brian McCullough

I knew a lot of the basic history behind the web and the dot-com bubble, but this book was a fascinating story of how it all came together, fell-apart, and came together again. Highly recommend if you’re interested in learning more about the dot-com era. There’s one thing that’s clear from this book: luck and timing matter.

A few favorite takeaways:

  • Microsoft was hesitant about the internet because it didn’t see how it would make money.
  • AOL bought Time Warner after considering eBay but didn’t want to double down on the web.
  • The middle-class suffered two major bubbles within 7-8 years after being told to a) invest and hold internet stocks and b) buy a home it’s a safe investment. Both of these events are likely to have played a role in the distrust we currently see in our political and economic system.


1. It Doesn’t Have to Be Crazy at Work – Jason Fried and David Heinemeier Hansson

I mentioned on my Twitter feed that this book was the first one I’ve ever read where one minute I was in staunch agreement and the next I was thinking “that will never work for most companies”.  It was the inspiration for format number three above and so I will use it here.

Intuitive: Your company is your product and so tweaking it in the same way you would actual software makes sense. Elon Musk has championed this theory in the past, build the machine that builds the machine.  Less waste, more production, and few distractions.

Counter-Intuitive: No long-term planning, make it up as you go. While I agree that no one knows what the world will look like in 36 months, it’s a great exercise to anticipate and think through scenarios.  Yet, the book is spot on here, “Seeing a bad idea through just because at one point it sounded like a good idea is a tragic waste of energy and talent.”

Recently, a good friend sent over the TechCrunch article “VC’s Urge Their Portfolios to Prepare for Winter”. Obviously, I’m new to this and as an operator have only known a bull market, but I suspect some market cyclicality will be introduced in the infancy of my investing career.

It’s important that I’m thinking about the potential impacts while researching lessons from past economic downturns. I figured it would be worthwhile to share a snapshot of my response to the article above as it highlights my thinking.

We went through something similar at Choose Energy, but instead it was a VC specific cooling off. Our Series C closed in 2015 and our leadership team anticipated the market could not stay as active as it had previously been.

While the decrease wasn’t as strong as anticipated, it did happen – YoY total deals declined by about 15% in 2016.  As a result, we raised a bit more than needed at a strong valuation allowing us to extend our runway through 2016 and eventually increase our operating leverage which also led to profitability.

This was also part of our thinking with our investment in WNDYR, we saw a strong services business that would be the backbone of a company as the software gained traction. Additionally, the efficiency gains they bring to businesses will become more important both to SaaS companies and startups looking for efficient growth as well as large firms looking to be more productive with fewer resources in the event of an economic downturn.

During the last recession, venture funding fell by 50% nationally in Q1 2009 from Q1 2008 to a total of $3.9 billion and continued on that trend for the remainder of the year. 2009 was the lowest total funding since 1998, yet here’s a small sample of firms close to an IPO and founded during that time:

Airbnb (8/2008)
Uber (3/2009)
Slack (2009)
Cloudflare (2009)
Pinterest (2009/10)

Lesson: the bear market can be a good time to invest if you are focused on building long-term value and expect your holding periods to be on the longer end, especially since you’ll see less yield everywhere else. Good companies are still founded during recessions.

Obviously, we think industrials are well suited for this shift as the larger companies usually shy away from startups that don’t have a path to a strong balance sheet. The flip side is that there have to be levers that allow that to happen. If you aren’t acquired, those levers can still be pulled if capital becomes less readily available.

Lastly, it’s possible the startup capital crunch could be smaller than anticipated if the downturn is a short one, though I’d advise startups to plan on the opposite.

Currently, there’s still a lot of dry powder on the sidelines from all of the mega funds VC firms have been raised ahead of the slowdown that’s supposedly been on the horizon for several months now. They’ll be in a great position to follow on to good deals if pricing decreases due to a cash crunch and startups should be aware of this in the event funding slows for a while.

2018 was an incredible ride between the birth of my first child, celebrating my 5th anniversary with Anita, and getting Intelis off the ground.  Last year, this post was more about growth, and in some ways it was right.

However, I fell short in one major way, focus and optimization.  That is my goal this year, extreme focus. I want to cut out the noise when it matters (e.g. family time, research blocks) and focus on the biggest levers in both my personal and professional lives.  This theme plays throughout my 5 goals for the new year.

1. Improving as a dad

This one is a given. Being a dad has been an incredible experience and I am looking forward to more of it in 2019.  While I’m new at it, and there’s no one right way to parent, I’m focused on being a better dad in 2019.  The first step for me will be no phone time between the time I get home and Ian goes to bed.  Since he’s starting daycare in the new year, our only real time with him during the week will be from 7-9P or so, I want to be present in those moments.

2. Write more

A goal I have had for the last few years and admittedly not succeeded at in the way I had hoped.  I posted 25 times in 2018, by far my best year since starting a blog, but also not close to the cadence I had in my mind.  My goal this year is once per week – an achievable amount without sacrificing the quality (loose usage of the word here) of the content.

3. Saying no more -> working deeply

The best part of being in venture capital is meeting really ambitious, driven people that have worked on or are currently working on projects that I’m interested in learning more about. The business is people-centric and meeting intensive, but I want to make sure I am providing value in those meetings/events in order to be respectful of other’s time.  I did a really poor job of this in 2018 and let my schedule get away from me.

I’ve put two placeholders on my calendar to get me started.  The first is 45-min blocks of email only time first thing in the AM, before lunch, and at the end of my day. I purposely went 15 minutes longer than I thought necessary and if I get that time back, great.  The second placeholder is no-meeting Fridays, which I realize will likely get interrupted from time-to-time but scheduling time to work-deeply is something I hope will have compounding benefits.

In short, my focus should be strictly focused on meeting companies where Intelis is a good fit, growing our firm, and supporting our portfolio companies.

4. Keep reading!

I’m happy with the momentum I built in reading regularly last year and want to continue that trend.  Last year, I read 23 books- just short of my goal.  I’m aiming for 30 books in 2019.

Additionally, I’m adding an additional sub-goal of reading 4 nights a week to Ian during the weeks when I am not traveling.

5. Cook more

Anita and I are in the process of buying a new home and one of our key purchasing criteria is having a place to entertain our friends which also includes having a kitchen we enjoy spending time in.  I love cooking and haven’t done enough of it in the past few years – my goal is to get back in the swing of cooking 1-2 times a week this year.  It’s a great outlet for creativity and relaxing without being tied to a screen.

There you have it, 5 goals for 2019.  As always, there’s the potential for things to change, they almost always do.  However, I’m hoping that by playing offense with my focus and getting these goals down on paper I’ll be more prepared for the inevitable chaotic times.

Happy New Year!

Like most, I figured I would write some form of recap or prediction post(s) at year’s end and this one is the first of what might be a few different articles to come over the next few days.  They’ll be a mix of industry, regional, and personal reflections that should be set up a great framework for growth and focus in 2019.

This one focuses on the themes I see taking hold in the power sector over the next 12 months. New technology-related trends like electric vehicles and cybersecurity have combined with on-going challenges surrounding aging assets, extreme weather, and regulatory uncertainty to create innovation opportunities in one of the world’s largest and most important industries.  As a result, here are the themes I’m particularly interested in next year as the utility business model continues to evolve.

Which network takes the lead in connecting the grid?

Utilities, along with the largest energy consuming industries (manufacturing and transportation), are in the middle of a transformation which includes connecting virtually everything to a network.  In total, these three verticals alone are projected to spend $132B related to the internet of things.

Yet, the available networks (3G, 5G, Bluetooth, and WiFi) all have shortcomings that keep them from becoming the industry standard. Verizon and AT&T are working on 5G IoT specific networks, but it is still incredibly difficult to get 3G coverage in some rural parts of the country where key assets are located, much less 5G and it is often cost-prohibitive at the enterprise level.

The answer is likely a combination of networks that are built on the tradeoffs for latency, computing power, battery life, and of course, cost. Where latency isn’t an issue and battery life matters, protocols like LoRWAN could begin to see wide adoption, especially at the computation and control layers.

How will the industry close the skill gaps in the workforce?

The energy workforce will look increasingly different in the coming years.  Today, 1/3 of the workforce is compromised of manual work rather it be administrative like accounting and data entry or physical labor in the field.  That number is expected to reduce to 1/4 in just the next few years.

With the continued rise of IIoT, it’s no surprise that the jobs most in demand require the data science and software skills the industry is sorely missing, especially given most utilities are HQ’d outside of traditional tech hubs.

However, the chart below from the World Economic Forum highlights a major hurdle for startups looking to grow within the sector- 64% of companies still don’t understand the opportunities for implementing new technologies.  As a result,  founding teams that have industry expertise or have developed go-to-market strategies tailored to helping customers in the industry uncover use cases are likely to have distinct advantages.


Will machine learning finally begin to reduce operational costs?

Regardless of demand growth or stagnation, operational costs will continue to move to the forefront.  If demand grows, the need for grid management will rise too and ML presents an interesting solution to load balancing and predictive asset maintenance.  If demand shrinks and/or power prices decline, operational efficiency will become even more important in preventing subsequent deterioration.

C3IoT and Uptake Technologies, both of which raised over $100M in the last year, are leveraging this trend for growth. However, the energy industry still has a large number of endpoints that are yet to be moved online and data fidelity remains a problem.

The efficacy of predictive analytics should continue to increase with the continued deployment of distributed assets (meters, lighting, thermostats etc..) while the data processing costs decline in large part due to edge computing and cheaper networks.

Can utilities begin taking steps to merge EV’s onto the grid?

EV’s present the most interesting dichotomy when it comes to the consumption of electricity in the next decade. On one hand, they will dramatically change the demand and shift the time of peak usage.  On the other, they can eventually be used at storage, demand response, and provide leading indicators into future power consumption (i.e. a utility tracks EV density and predicts consumption from that information).

Facing bold predictions of EV availability and adoption in the near future, utilities must begin thinking about how to serve this demand. However, if utility grids are not updated and expanded soon to support networks of widely available charging stations, EV adoption might become impaired or a drain on our already aging infrastructure.

Will a winner in the cybersecurity space emerge?

Source: Utility Dive

This year, Utility Dive’s annual state of the union had cybersecurity has the number one issue of concern according to executives with over 80% naming it a “very important” issue.

While power grid stakeholders will spend over $5 billion globally on securing infrastructure in 2018, only a small portion of that will be dedicated to operational technologies and smart systems.

These grid modernization efforts are an ideal time to design and implement digital security protocols and provide an opportunity for adapting existing mechanisms and processes to the OT space – from industrial control systems to smart meters. While the industry is still heavily service oriented, we’re starting to see hints of software companies gaining ground and expect that trend to continue into the new year.

Overall, I expect the industry to continue its evolution from a rate-based revenue model to one that is rewarded for efficiency and performance. If regulators begin to set those policies in-motion, the trends above will accelerate and tomorrow’s utility model will look very different than today’s.

One of the inherent risks of investing in companies at the earliest stages is revenue diversification which in turn helps to create operating leverage.  Most startups we meet are dependent on just a few customers, partners, or channels for the bulk of their early growth.  Ideally, these early-stage companies are investing in the business to accelerate and diversify revenue streams.

If executed to perfection, revenues and gross margins are growing faster than operating costs, and operating income (or losses) are increasing (or decreasing) faster than both of them.

But without analyzing a few key metrics, it’s impossible to understand, much less create, operating leverage in the business.  Namely, it’s crucial to know how effectively you turn revenue to actual cash and the contribution margin of each product.

Accounts Receivable – How much cash is owed to you?

Accounts receivable is a great metric to use when validating if revenues are “real” or inflated.  When I use the word real, it’s in the context that the revenues will become cash in a timely manner.  Revenues can easily be inflated by shipping product where payment is not expected or will take a while to collect (more on that in a bit).  Rather on purpose or not, in these scenarios cash will be going down while profits are steady and accounts receivable are growing rapidly.

Book to Bill Ratio – How effective are you at turning bookings into real revenue?

Book to bill ratio is simple to calculate by dividing periodic bookings by the same period’s revenues. If bookings are a lot higher than revenues, that can be a positive sign. But it can also mean that your company is having a hard time getting revenue realized, i.e. you have a higher accounts receivable balance than the peers in your industry or at your stage.

Days Sales Outstanding – How effective are you at collecting revenue?

Another easy metric to calculate is days sales outstanding (ending AR/revenue per day) but instead of tracing how efficient you are at converting bookings, it measures how long it takes on average to collect from customers.  This number provides insights into where contracts can/should be re-negotiated and also the amount of cash needed to finance your business. One quick note, DSO is an average. For a more granular analysis, be sure to highlight AR under 30 days, 30-60 days, and 90+ days outstanding.  This will give you a weighted average which provides more insight into how well the company is actually collecting revenue.

Contribution Margin – Which products/channels are most efficient?

In short, the contribution margin is the window into how each product or channel individually affects the business as a whole. CM highlights what’s available after variable costs to cover fixed expenses and provide profit to your company.  It’s as simple as sales minus variable costs and shows the profit on what you sell before fixed costs.

Variable cost is the key factor in this equation – with revenue or channel concentration these numbers are easy to calculate, but with the diversification comes a new equation for each new product or acquisition channel.

Without understanding your CM by product and/or channel, it’s impossible to make informed decisions about where to invest capital for continued growth, the levers that need to be pulled (pricing, CAC, etc..) to make products more profitable, or if products/channels must be entirely eliminated.

This was a fairly long post full of accounting jargon, but it’s important to understand which metrics translate the effectiveness of the business in creating operating leverage.  As revenues diversify, these calculations become exponentially more complicated with the addition of new products, customers and acquisition channels.  Understanding and tracking them now ensures you’ll have a good grasp on where to allocate new capital when the time comes.


Like many, I listen to podcasts on my commute to and from work.  Yesterday, I came across this podcast from Greentech Media featuring Shayle Kann, SVP of Research and Strategy at Energy Impact Partners.  Shayle had written an article about the future of energy and tied it to the life events of his colleague’s soon-to-be daughter which is due at the end of the year.

The podcast and article are worth your time – and not just for those interested in the future of energy.  Given that we just had a newborn, I thought it would be fun to duplicate the exercise using my son Ian and my thoughts on the “bets” Shayle puts forward.

Bet #1: Ian will control machines with his voice more than with his keyboard.  My answer: False*

My answer comes with a caveat, what’s the timeline?  In the podcast, Shayle discusses the growth in AI-enabled voice assistants over the last 3 years.  While the number of devices being sold is impressive, voice still has a real user-engagement problem.  These devices are primarily used for timers, audio, weather, and news.  I also think voice has a UX issue that most aren’t talking about, it’s hard to remember what all a device can do (your phone has apps you see every day and do not use).  Until voice-enabled devices do almost everything, I think the path to engagement will remain tough.

Bet #2: Ian will never personally drive a car. My answer: False

While there are several converging technologies and business model innovations in the automobile space, I believe purely out of curiosity Ian will drive a car at some point in his life.  AV’s, ride-sharing, and scooters are all disrupting the way we think about transportation, but pure curiosity gets the best of all of us.

Bet #3: By the time Ian buys his first home, especially if he’s in an urban environment, his surroundings will be transformed. My answer: True

A few of the major trends already impacting cities: WeWork, AirBnB, and EV’s.  Up next: drones (robotics), repurposed parking lots, and vertical farming.

Bet #4: By the time Ian shops for his own groceries, >20% of his produce will be grown indoors, up from virtually none today.  My answer: True

Given the current population growth, the impact farming has on climate change, and vice versa this is a given.  We’ll need more food and the way we grow it today isn’t sustainable for the three major reasons listed.  We need more food, it impacts our climate to grow it, and our climate is changing the way we will have to grow it.

Bet #5: Let’s turn to Ian’s house. I bet that in Ian’s first home of his own, more than half of his electricity load will dynamically respond to grid or price signals. My answer: True

I loved Shayle’s answer here because it was concise and spot on.  Control HVAC plus 1 or 2 additional devices and this goal is achieved.  It must happen in the background, consumers don’t know nor care what the impact could be.

Bet #6: By the time Ian reaches 30 (in the year 2048), electricity’s market share of final energy consumption will more than double. My answer: True

Another fairly simple answer, EV’s should change the demand significantly especially if they hit long-haul trucking in the near future.  The industrial applications of storage and efficiency should also play a large role in increasing electricity’s market-share.

Bet #7: More than 50% of Ian’s electricity, as represented by the national breakdown, will come from renewables by the time he’s a sophomore in high school.  My answer: False

It will be close, but I say we fall just short of this goal primarily due to the availability of natural gas.

Bet #8: Ian will live over 200 years, and for most of his life, electricity will be his only food.  My answer: False

So many ethical questions here, though companies are working on products that allow them to download your loved ones’ text (email, text messaging, social media) then build bots that mimic the physical manifestation of them.  Kann makes a compelling case by listing the major inventions of the last 85 years, but the regulatory and ethical hurdles might defeat this one.

There you have it, my take Ian’s future as it pertains to energy and innovation.  Thank you Shayle for writing this piece, it was a neat way to think about the future and possibly gives Ian something to look back on while having a laugh at his old man’s expense.

It’s been almost a month since I’ve posted, having a newborn will do that to you.  But I’m back and hoping to continue writing regularly from here until the end of the year.

During my time away, I traded-in an old MacBook Pro and iPad mini for a new Surface Go.

At least part of the reason I decided to try a Surface is that I love what Microsoft is doing as a company.  I’ve told anyone who will listen for the last 2 years that I am bullish on Microsoft under Satya’s leadership and the Surface is a big part of my reasoning.

The verdict: I’m only a week or so into using my Surface Go regularly, but so far I love it.


  • the keyboard – I love the feel and size even if it takes some getting used to
  • the size – it’s perfect for both tablet uses like reading/browsing and computer use cases like working on email/writing
  • the OS – I like having a full OS instead of a mobile version


  • power – the Surface Go does lag for some heavier tasks even though I purchased the 8GB RAM version
  • battery life – on a full charge the battery lasts only ~5-6 hours which is dismal compared to iPads
  • bezel – this is a minor complaint, but the bezel did not need to be so large with the advancements that have been made in screen technologies over the last few years

It’s not a device I’d recommend as your “daily driver”, but if you have a computer for heavy lifting and are looking for something more portable that is still powerful enough to get basic tasks done then the Surface is definitely worth considering.

I’ve attempted to use an iPad off and on for the last few years but the lack of a mouse kept me from using it as an additional computer.  The touchscreen UX just doesn’t work for me. The new iPads still do not solve this problem and so the Surface still feels like the right choice for most of my use cases.

The addition of the mouse and a great keyboard mean I pick up my Surface Go every chance I get and that means more productivity which is what having a secondary device is all about in my mind.

If you ask most early-stage VCs their number one criteria for investing in a startup, the answer you will get is “team.”  Even market first investors, like us, want to know why the team is best suited to tackle the problem.

In a fundraising environment that is becoming more crowded, differentiation is incredibly difficult and the question I’m often left asking after reviewing a deck is “why you?”  As in why are you the best person to solve this problem?

Yet, for some reason, most of the decks that come across my desk leave the team slide either somewhere in the middle or near the end instead of answering that question early and with clarity.

Team, team, team, market, team. — Mark Suster, General Partner at Upfront Ventures


The one thing that always stands out the most in an early stage startup is the team. We invest quite early in a company’s life; it will usually take 6–10 years for the company to reach giant success. Given that, many things will go wrong and the one mitigating factor for setbacks is a great team.  We spend the most amount of time thinking about the founders and the early team before investing. — David Pakman, Partner at Venrock


The answer can be as simple as the invention serves the need of the inventor.  Our first portfolio company all suffered from the disease they were working to monitor and as a result understood the daily life of their customer.   This has been a guiding force in their product design and cost.

Perhaps you have extensive work experience in the industry and have seen the problems from the inside.  This is especially important in industries that require the careful navigation of regulation, long sales cycles, entrenched incumbents, and/or bureaucracy.

While the best stories in Silicon Valley lore often involve a founder rescuing an industry with innovation from a fresh perspective, the truth is founder-market fit matters and in most cases is a strong advantage.

Be brutally honest with yourself,  are you uniquely qualified to execute on your business?  If so, trying leading with the team first – the risk is low and the rewards could be worth it.

By now you’ve likely seen this week’s The Economist cover story entitled Peak Valley, which features quotes from Claire Haidar.  Claire is CEO of WNDYR, an Intelis Capital portfolio company. The article highlights a mixture of outrageous costs-of-living, poor local government, and high operating costs as the catalysts behind an impending Silicon Valley collapse.


We’re skeptical Silicon Valley is “over.” However, we do see its influence dwindling in the next few decades as a direct result of a technological invasion into new sectors that drive the economies of the regions most dependent on them.


Every Industry is a Technology Industry 


It should come as no surprise by now that almost every industry has come to rely on technology for some core part of its operations.  Yet, there is a large variance in the degree of digitization across sectors that are cornerstones in regional economies outside of the Valley – these sectors have largely been ignored by coastal VCs until the last couple of years.


Industries like energy, agriculture, construction, and manufacturing are lagging behind the innovation curve and represent a multi-trillion dollar opportunity for startups and investors alike.  Their importance to regional economies like Texas, the Southeast, and Midwest can’t be overlooked.



We used the Bureau of Economic Analysis geographical definitions of the Southeast in addition to Texas for our analysis for the graph above.  Sectors such as power utilities (5.2% of SE GDP), oil & gas (2.54%), transportation (3.43%) and construction (4.83%) contribute much more to the regional economy than the US as a whole and while these percentages look may look small, it’s important to note the size of the US economy was $18.5T in 2016 and the region accounts for about 1/3 of total US GDP.


The ability to build software products is without a doubt Silicon Valley’s competitive advantage, made possible by an unmatched density of engineering talent. Yet because the aforementioned sectors are largely un-digitized, only a minimal level of improvement is necessary in order to replace current analog processes. Thanks to the spread of technology the requisite level of engineering talent can now be found, for less money, in most metropolitan areas.


Additionally, distribution of product is sometimes as important, if not more so.   The density of customers and potential partners in other regions provides startups with a ready-made strategy to build revenue from the outset.


These advantages can result in the healthier P&L’s highly-valued by potential acquirers in these sectors, leading to exits that drive ecosystem growth.



Founder / Market Fit


There’s a reason these analog industries have yet to be disrupted.  Often they require highly-skilled and specific knowledge, are encumbered by regulation, have entrenched bureaucracy throughout the entire value chain, or in the worst cases — all three.


Witnessing first-hand the ways an industry is broken is crucial to building the foundation of a big business within them.  More importantly, it removes any naïveté a founder might have and prepares them for the potential roadblocks ahead.  A few obvious and successful examples of this are: Flexport (freight), Robinhood (finance), and Farmers Business Network (agriculture).


Before, entrepreneurs would have had to move to SV to start these companies due to lack of local resources and talent. However, an explosion of cloud-based collaboration and communication software has now made it possible for these executives to tie into specialized talent from the Valley if and when needed.


Moving to the Valley as a contingent of funding is becoming less common distributed work becomes more of an accepted practice, and the rise of new firms focused specifically on not investing on the coasts has given founders more access to capital than ever before. This combination has solved one of the biggest problems of building a business outside of Silicon Valley – access to capital.


It’s clear there are several new sectors and regions are primed for the necessary disruption heading in their direction. Undoubtedly, Silicon Valley will play a direct or indirect role in many of the advances, but for the first time ever that role may not be from the driver’s seat.


Last week Apple became the first company to hit a $1T market-cap.  Lost in the hype of hitting that milestone and their Q2 earnings call was the announcement that they are also launching a $300M cleantech fund in China to “give fund participants greater purchasing power to pivot toward clean energy.”  


This looks eerily similar to a strategy Amazon has used for AWS, except applied to energy. Apple can be the first and best customer for new products and technologies as they’re incredibly large consumers of energy much in the way Amazon was for both data and deliveries.  It’s now a well-worn playbook and it would enable Apple to gain stability in energy consumption while being less exposed to the price volatility of the market… all while subsidizing development via their own purchasing power.


For consumers and startups, this development could be game-changing. In the same way healthcare needs Amazon as a major player because Amazon excels in efficiency and logistics, cleantech needs Apple to help it beat the economics of the alternative, and connect its evangelists to the mass market.  If Apple had superpowers, they would be the ability to create a luxury perception of their products, and the ability to create an ecosystem effect that makes their services sticky.


“It Just Works”
Apple’s DNA, dating all the way back to 1977 when Steve Jobs demanded the Apple II be as easy-to-use as any household appliance, is creating a product consumers can easily interact with on a daily basis.  Much like today’s early cleantech adopters, the tech evangelists of the 1970’s understood the potential impact of the technology to our every day lives, but could not actually figure out how to convince others of this fact until the Apple II was released.  Apple repeated this feat again when it released the iPhone in 2007.  These kinds of innovations add up over time and have created a bond between Apple and it’s consumers. With Apple you can feel safe trying the unknown, and in energy, as with all regulated industries, trust matters…A LOT.


Cheaper, but still expensive
The cost of chips and computer parts began their decline in the 1980’s and the same can be said for cleantech components today.  Solar panels, storage and the sensors are all experiencing some of the steepest price declines since their invention.  Yet, they are still more expensive than their alternatives which includes the status quo.  As it stands, there must be something stronger than economics to serve as the catalyst for massive adoption.  Who better to solve this problem than Apple? Case in point, Apple owns only 18% of the smartphone market and yet earns 87% of all profits and has done so by leveraging usability and lifestyle (i.e. community) to convince customers their most commoditized product is worthy of a price premium.


Tesla: The EV Elephant in the Room
Could a company that will repatriate over $200B in cash be interested in acquiring one that has a market cap of $60B and over $10B in debt?  Tesla is one of the first companies (the other being Nest) that has made an environmentally friendly product “cool.”  At the very least, they’ve provided Apple with a playbook to enter the market from the consumer side if they so choose, but an acquisition begins to make a lot of sense if current trends hold. 


Despite it’s success, Apple has been under increasing pressure to “do something innovative” as most of its hits post-iPhone have been comparatively minor.  AppleTV, Apple Watch, and AirPods are all best-in-class devices, but none of them triggered a major innovation cycle in the way the Apple II and iPhone did.  Could energy be the next step for the first $1T company to become the first $2T company?  Time will tell.



It’s not surprising that pricing plays a large role in the success of a startup.  When asked if he could put any one piece of advice to founders on a billboard in San Francisco,  Marc Andreessen famously said, “raise prices.”

However, pricing is more than what you charge your customer, it also includes how you incentivize engagement and create margin as well.  How does this work in practice for two of the most common pricing structures?

Incentivizing Engagement with Consumer-based Pricing

Consumer-based pricing works well when you are working to create a “sunk-cost” feeling or need your users to change behavior, rather that be from an existing software or workflow.

For example,  we work with startups in industries that still use Excel, or if they are really advanced SQL, for most of their workflows pertaining to data entry and analysis.  Charging these customers on per-use basis would be more likely to result in end-users  giving up on the software at the first sign of complication (i.e. MVP / new features have a higher bar to clear), or never using it again a few weeks after onboarding.

Instead, a per-seat charge or a flat-fee creates a sunk-cost feeling within the organization.  The internal manager or champion who initially went to bat for you is now incentivized to show this new cost isn’t going to waste.

Does this create a higher-barrier to sales?  Maybe, but sales were always going to be important.  More importantly, you now have allies working to ensure engagement with your product in their organization due to the effects you’ve had on the budget and their reputation at the company.

Creating Margin with Consumption-based Pricing

Consumption pricing is charging based on how much or often a consumer uses the product.  The two most obvious examples would be almost any cloud storage provider or Invision’s per workflow product.

This structure is perfect if your product could be accessed by an entire group or division with one login and not lose effectiveness.  In the example above, if pricing was consumer based (per seat) a design team could easily create one log-in to create as many prototypes as needed.

If Invision used a per-seat structure, it’s unlikely they could start pricing at $25/mo.  Instead, it would likely be in the neighborhood of $10/mo.  This structure likely allowed them to charge $15 more per month AND make it feel like a value to the end user.

Pricing often gets overlooked in the foundational aspects of company building.  Yet, when structured correctly, pricing strategy can create incentives that become powerful catalysts for early adoption and create extra margin over the long-term.