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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


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.

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.

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.

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.

Recently, Jonathan coined the phrase “the drag of orthodoxy” as it relates to regulated industries and their inability to quickly adopt new technologies even when they provide the best use cases.  Often, this is due to both the inability to implement new technology (easier to solve) and the opportunity costs of losing trust (harder to solve).

Digital adoption in these industries requires buy-in from traditional institutional mechanisms and an evolution of norms as well as consumer trust.

Unquestionably, the push of consumer expectations will continue to combine with digital forces to propel these industries past their legacy infrastructures and into a new age of innovation and growth.

Bitcoin could very well be the inflection point that is needed for mass adoption of blockchain technology in regulated industries and launches them into a new era.

We’ve been here before with less revolutionary technologies.  Marketplaces, enabled by wide-spread adoption of the internet have been around for over 25 years.

However, industries such as insurance and energy are just now beginning to leverage technologies like API’s to offer consumers the chance to compare plans just as they have flights for years.

The adoption cycle also applies to business model innovation. Uber and Airbnb offer on-demand services to better match supply and demand of goods.  It may not seem like it, but those companies are over 10 years old.

Just recently, we’ve seen startups like Honor and Trov apply the same concepts to elderly care and property insurance respectively.

The important thing to note is that just like consumer adoption of technology is rapidly increasing, the same thing is occurring in institutionalized industries.

Where can we go from here with blockchain in regulated industries?

Electricity transactions are still tracked almost exclusively in Excel before being submitted into databases that rarely are connected.  This system adds millions in additional transaction costs and makes full transparency between market actors almost impossible.

If smart meters and API’s wrote these transactions into a decentralized ledger, the errors would be eliminated almost immediately and new entrants (i.e. consumers with excess power capacity due to solar panels) would be encouraged to enter the market.

Healthcare provides maybe the most obvious applications of blockchain technology.  Patient information, research data, and prescription purchases all require privacy, security, and have rigorous standards for quality.

In finance, the unbundling of the job will require new platforms for the reintegration of common services like payroll, insurance, and financial planning.  Blockchain technology provides the perfect solution for transaction and ID verification.

The rise of Bitcoin and other cryptocurrencies has started a conversation centered mostly around their skyrocketing prices.  Yet, what is most exciting for me are the potential use cases that will come as the masses become more comfortable with the underlying technology and its ability to improve the industries that most affect their everyday lives.

Jonathan and I are at the CBI Insights Innovation Summit in Santa Barbara this week. Below are a few quick takeaways from yesterday’s panels and discussions.  Enjoy.

  1. As can be expected, voice and text will be the biggest winners at the intersection of UI and AI over the next few years.  People can now interact with devices without knowing how to read and write. For developed nations, this means that toddlers now interact with computers for the first time by voice instead of touch.  However, the implications for the developing world are even greater. Since illiteracy will no longer be a limiting factor to bringing people online 2B additional people will have the chance to connect to the rest of the world.After the Q4 and CES success surrounding Echo and Alexa it’s pretty clear that Amazon is leading the way in voice. Yet, Google and Apple still have one big competitive advantage, an OS in your pocket.  Consumers generally want to interact with one OS across multiple devices so this hurdle is likely to be key for Amazon.The industries that will be impacted range from retail to content / media to healthcare.  The order of implementation is likely to go from low risk to high risk.  As Jeremy Liew of Lightspeed Ventures said, “health won’t be the first real domain, rather a something like shopping where no one dies if it goes wrong.”
  2. The IPO and M&A climate is changing.  Just as early as a few years ago, growth at any cost was the standard way to IPO  Now, companies are taking a growth at some reasonable cost approach. I wrote last week that non-tech firms entering the startup M&A fray is likely to put a focus on sustainable business models and the IPO market looks to be following suit.  Scott Kupor of a16z believes “companies with 30% annual growth and near-term profitability are likely to have good IPO prospects”
  3. Chamath Palihapitiya of Social Capital was his usual quotable self and several of his insights will be long-lasting in my mind.  Among them:More big companies should partner with VC firms. Combining their balance sheet with access to talent is a game changer. These large, incumbent companies should share the risk with talented startups instead of defining exactly what they do. This mindset prevents them from building big, meaningful businesses. FinTech is a great industry for incumbents to do this. because by definition there must be an ecosystem for consumer interactions.Working around regulatory is immature, Silicon Valley should being working with regulation.  Regulatory standards keep consumer trust in industries like finance, utilities and health where this is paramount.  This trust often leads to more users which leads to more revenue.  In addition to these benefits, regulation helps companies build a sustainable moat and weeds out those who don’t have the courage to run the gauntlet of starting a business.
  4. With the copious amounts of data coming online the way we think and work with data is changing rapidly.  Among the challenges businesses will face; cleaning data that comes from multiple collection points (IIoT, energy) and consumer privacy.AirBnB’s Chief Economist Peter Coles elaborated on both challenges on the panel focusing on big data.  AirBnB wanted to work within the regulatory frameworks of major cities as they expanded their footprint but in order to do so needed to share data with those cities without compromising customer privacy.  The solution: aggregating data in order for these cities to spot trends without violating user trust. Sometimes solutions are beautiful for their simplicity.The other insight Peter provided was on measuring data.  Most of us default to one off queries on our database to solve the problem of now.  Instead, AirBnB has taken the time to create “core metrics” in order to eliminate one-off problem solving.  This is something I know I have done in the past and am betting most of you have too.

There were several more great insights from panelists and presentations from amazing companies like SigOpt and Affective.  The future is filled with talented people solving massive problems.  I’m looking forward to another productive day focused on big industries like auto and insurance.

Recently on the “This Week in Startups” podcast Silicon Valley investor and CEO of Vayner Media, Gary Vaynerchuk was the featured guest and one of his insights added a unique dimension to the way I think about product development.  Gary asserted that all great products are actually in the time business; meaning they all give us back a resource of which we have a finite amount.

The specific example he used was Uber.  He explained that Uber is not selling car rides but instead focused on getting people where they need to go quicker and we are even willing to pay a surcharge to preserve our time.  Another example was Amazon which is the master of this technique dating back to the development of one-click ordering to one-hour delivery to the most recent Amazon Dash.

As I thought about ways this might apply to the industries in which I am particularly interested I turned my attention to the concept of the “smart” home. Over the last 5 years several companies have emerged as leaders in this field and all are marketing themselves with different value propositions but the one thing they are all offering their consumer is: more time.

Nest is far and away the most recognized product in this category and its primary marketing message is that it “pays for itself.”  I would certainly advocate that all homes should have a smart thermostat for efficiency reasons but the main feature of Nest is its ability to learn user occupancy habits.  While we may not spend more than 1-2 min a day setting our thermostat this time adds up over the course of a year to about 12 hours.  The future of these occupancy sensors have enormous potential.  Imagine 10 years from now if deliveries, home repairs, etc… are scheduled automatically based on when you are home according to the sensor in your thermostat or light bulbs.

Speaking of light bulbs, what Nest did for the thermostat several companies are attempting to do for the light bulb.   There is no clear winner in this space as of yet, but Phillips Hue, WeMo, Lifx, and Stack are all vying for poll position.  Again, all of these companies have different value propositions for the consumer but all are selling time savings in the form of not worrying about flipping a light switch, forgetting rather or not you turned off the lights, or in the case of Stack helping you rest better and wake up in a way that helps us be more productive with the limited time we have during the day.

These products combined with smart meter data being rolled out in some states present an exciting future where homeowners can make informed decisions about big purchases.  For instance, thermostat, light, and smart meter data could be used to let homeowners know which appliances they should upgrade, if they should install a rooftop solar system or new more efficient windows. Once a decision has been reached, the project would be scheduled automatically from the sensors placed in the thermostat or light bulbs.  This kind of possibility explains why so many companies from different industries (AT&T, Direct Energy, Comcast, and NRG) are vying to “own” the home.

While our society can sometimes seem “anti-technology” as evidenced by books and movies focused on dystopia via innovation the smart home presents an opportunity for us to live our lives more efficiently in terms of both time and money.