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Modern entrepreneurship began at the turn of this century with the observation that startups aren’t smaller versions of large companies – large companies at their core execute known business models, while startups search for scalable business models. Lean Methodology consists of three tools designed for entrepreneurs building new ventures:

These tools tell you how to rapidly find product/market fit inside a market, and how to pivot when your hypotheses are incorrect. However, they don’t help you figure out where to start the search for your new business.

A new tool – the Market Opportunity Navigator – helps do just that. It provides a wide-lens perspective to find different potential market domains for your innovation, before you zoom in and design the business model or test your minimal viable products. This new framework can act as the front-end of Customer Development. It helps figure out the most promising starting position – market domain – for your customer development process. And it helps identify promising Plan B’s and new growth options if you have already embarked on your innovation journey.

Over the years, I have seen many startups and innovation projects perform a painful “re-start” to completely new market domains. With a little more thinking up front these entrepreneurs and innovators could have identified more promising business contexts to play in, and thus avoided this difficult pivot down the road. But while the academic literature is full of papers covering market selection and the literature has some popular books (Blue Ocean Strategy, et al.) there is a lack of easy-to-use tools to do so.

In large companies and government agencies the problem is even more acute. Where do we spend our limited time and resources on our next moves? While the Innovation Pipeline tells us how to go to from sourcing to delivery how do we prioritize our choices? The Market Opportunity Navigator is a useful adjunct to the curation and prioritization steps.

Just like the Business Model Canvas, the Market Opportunity Navigator has closed the gap between academic theory and books by offering a simple, visual way to navigate the process of how to select what market to start with. Developed by Prof. Marc Gruber and Dr. Sharon Tal and based on hundreds of cases they studied during their practical and academic work, the Market Opportunity Navigator is described in their new book, Where to Play.

In three simple steps the Market Opportunity Navigator can help you:

  • Identify a portfolio of market opportunities stemming from your technology or unique abilities
  • Reveal the most attractive domain(s) by evaluating the potential and challenges of each option
  • Prioritize market opportunities smartly to set the boundaries for your lean experimentations

I asked Sharon and Marc to summarize why market selection is important and describe an example of how to use it.

Different Playgrounds mean different Rules of the Game
There are many ways in which you may have identified a market for your business. Some of you may have identified a market need based on your own experience, or you may have been approached by potential customers, or if you are corporate innovator you may have applied an innovative solution to an existing target market. Yet, are you sure that this is the best opportunity? Could there be greener pastures (larger markets, more profitable markets, etc.) out there for commercializing your technology or unique abilities?

Taking the time to reveal the most promising market – the best starting position – before you engage in a focused customer development process is critical, because market domains vary in their value creation potential, competitive landscape, regulatory regime and risks associated with launching new products. In fact, by not asking “Where to Play” innovators risk choosing an inferior playground – one that does not allow the project to prosper. Beyond the possible loss of revenues, this early decision may be difficult to change, or even irreversible: it influences how you develop your technology going forward, raise money, write patents, recruit employees and pick a brand name. If re-start in another target market is required, such a pivot is painful, costly, and sometimes even impossible.

Finding the best starting position is a learning process that takes time and bandwidth – two scarce resources. So instead of taking a deliberate step back to understand their portfolio of opportunities, entrepreneurs and innovators often just start running. They make a bet and engage in customer development experiments – adopting “local” pivots in a relatively fixed context, until a scalable business model is (hopefully) revealed. This can be a big bet! The search for product/market fit and for a scalable, promising business model should therefore begin with uncovering and understanding the different market contexts in which you can play. In fact, by adopting a wider lens, the search process shifts from 2D (finding a product-market fit) to 3D (finding multiple product-market fits in different market contexts).

Academic research published in Management Science investigated 85 VC-backed startups and offered a conclusion that seems obvious in hindsight: “look before you leap.” The big idea was that experienced entrepreneurs tend to generate a portfolio of market opportunities before deciding where to play, thereby laying the ground for significant performance benefits. In other words, understanding your arena of opportunities is a key asset for entrepreneurs and innovators.

Identifying your Arena and Choosing Where to Play
The Market Opportunity Navigator provides a visual framework to discover, compare and prioritize different market domains and business contexts. It helps you to think about your arena, rather than your industry – a key mindset shift in today’s competitive landscape.

The Navigator walks you through a three-step process that helps you to make a more informed choice. It does so in a friendly, intuitive manner, with a visual design board and 3 worksheets to guide the process.

You can download the Navigator and its worksheets here.

Putting it all together: A Superset of Tools
Mapping out your market opportunities to understand your most promising starting position generates valuable insights for your innovation journey. In short, the big-picture view provided by the Navigator helps you zoom-out to understand “where to play,” while the detailed views of the lean approach and the Business Model and Value Proposition Canvases help you zoom-in and understand in detail “how to play.” Together, they create a superset of tools that supports you in an iterative learning process until you find a scalable, promising business.

Having a market opportunity portfolio to draw from offers an additional benefit. By having gamed out multiple markets, you can bake agility into the DNA of your venture – a key component in the Lean methodology. It allows you to carefully select and keep open backup and growth options.  If a “re-start” is eventually required, it will be less painful and less costly.

Let’s take a look at an example from the startup world to see how the Market Opportunity Navigator works.

We Can Fly Anywhere – but Where Do We Go First?
Flyability develops drones to inspect difficult-to-access locations. In theory, they can custom-build their drone to perform different jobs in completely different markets: industrial inspection, search and rescue, entertainment or surveillance – to name but a few. Each of these markets varies significantly in its business context and in its promise for growth. Furthermore, each market would require its own customer development process to reveal a scalable, repeatable business model – clearly a demanding process that is difficult to run simultaneously in multiple domains.

So how did Flyability find its best starting position – the initial market domain where the founders should engage in detailed customer discovery and build their business? They used the Navigator and its three worksheets to guide their process.

Worksheet 1: Generate your market opportunity set
The founders’ first idea was to use the drone for observing critical disasters, like the reactor meltdowns in Fukushima, Japan. Yet, by going through the first step of the Navigator, the team began to uncover alternative markets where their drone could add value for customers. Among others, they considered drone-based inspection of boilers in thermal power plants, the inspection of oil & gas storage tanks, and intelligence-gathering by police forces. Overall, five market domains seemed interesting and required further evaluation.

Worksheet 2: Evaluate market opportunity attractiveness
Using the second step of the Navigator, the team systematically examined the potential of each market and its unique challenges. This allowed Flyability to map out their options and visually compare their attractiveness. Gradually, it became clear that thermal power plants were a “gold mine” option worth playing in. They could now use the Business Model Canvas and the lean experimentation processes to design and validate a scalable business model within this market.

Worksheet 3: Design your agile focus strategy
Once the founders chose their primary market, they could leverage alternatives to create a more agile company by mitigating risk and avoiding locking-in. Specifically, using the third step of the Navigator, the founders designed a small portfolio of backup and growth options that they would keep open. This foresight laid the ground to early key decisions that have long-term consequences, like how they developed their drone or chose their brand name. In addition, it helped them clearly define which options they would place in storage for now (as focusing is about saying no more than anything else).

By employing the Market Opportunity Navigator, Flyability has not only figured out “Where to Play” it has mapped out an interesting growth path that is appealing to investors. To get a better sense of this process, you can view Flyability’s Navigator below, or read the full case study by clicking here.

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A version of this article first appeared in the Harvard Business Review

VC’s have just changed the ~50-year old social contract with startup employees. In doing so they may have removed one of the key incentives that made startups different from working in a large company.

For most startup employee’s startup stock options are now a bad deal.

Here’s why.

Why Startups Offer Stock Options
In tech startups stock options were here almost from the beginning, first offered to the founders in 1957 at Fairchild Semiconductor, the first chip startup in Silicon Valley. As Venture Capital emerged as an industry in the mid 1970’s, investors in venture-funded startups began to give stock options to all their employees. On its surface this was a pretty radical idea. The investors were giving away part of their ownership of the company — not just to the founders, but to all employees. Why would they do that?

Stock options for all employees of startups served several purposes:

  • Because startups didn’t have much cash and couldn’t compete with large companies in salary offers, stock options dangled in front of a potential employee were like offering a lottery ticket in exchange for a lower salary. Startup employees calculated that a) their hard work could change the odds and b) someday the stock options they were vesting might make them into millionaires.
  • Investors bet that by offering prospective hires a stake in the company’s future growth- with a visible time horizon of a payoff – employees would act more like owners and work harder– and that would align employee interests with the investor interests. And the bet worked. It drove the relentless “do whatever it takes” culture of 20th century Silicon Valley. We slept under the tables, and pulled all-nighters to get to first customer ship, man the booths at trade shows or ship products to make quarterly revenue – all because it was “our” company.
  • While founders had more stock than the other employees, they had the same type of stock options as the rest of the employees, and they only made money when everyone else did (though a lot more of it.) Back then, when Angel/Seed investing didn’t exist, to get the company started, founders put a lot more on the line – going without a salary, mortgaging their homes etc. This “we’re all in it together” kept founders and employees aligned on incentives.

The mechanics of a stock option was a simple idea – you received an option (an offer) to buy a part of the company via common stock options (called ISOs or NSOs) at a low price (the “strike price”.) If the company was successful, you could sell it at a much higher price when the company went public (when its shares were listed on a stock exchange and could be freely traded) or was acquired.

You didn’t get to own your stock options all at once. The stock trickled out over four years, as you would “vest” 1/48th of the option each month. And just to make sure you were in the company for at least a year, with most stock option plans, unless you stayed an entire year, you wouldn’t vest any stock.

Not everyone got the same amount of stock. The founders got most of the common stock. Early employees got a smaller percentage, and later employees received even a smaller piece – fractions of a percent – versus the double digits the founders owned.

In the 20th century, the best companies IPO’d in 6-8 years from startup (and in the Dot-Com bubble of 1996-1999 that could be as short as 2-3 years.) Of the four startups I was in that went public, it took as long as six years and as short as three.

One other thing to note is that all employees – founders, early employees and later ones – all had the same vesting deal – four years – and no one made money on stock options until a “liquidity event” (a fancy word to mean when the company went public or got sold.) The rationale was that since there was no way for investors to make money until then, neither should anyone else.  Everyone—investors, founders and startup employees—was, so to speak, in the same boat.

Startup Compensation Changes with Growth Capital – 12 Years to an IPO
Much has changed about the economics of startups in the two decades. And Mark Suster of Upfront Capital has a great post that summarizes these changes.

The first big idea is that unlike in the 20th century when there were two phases of funding startups–Seed capital and Venture capital–today there is a new, third phase. It’s called Growth capital.

Instead of a startup going public six to eight years after it was founded to raise capital to grow the company, today companies can to  $50M+ funding rounds is a  deferring the need for an Initial Public Offering to 10 or more years after a company is founded.

Suster points out that the longer the company stays private, the more valuable it becomes. And if during this time VC’s can hold onto their pro-rata (fancy word for what percentage of the startup they own), they can make a ton more money.

The premise of Growth capital is that if that by staying private longer, all the growth upside that went to the public markets (Wall Street) could instead be made by the private investors (the VC’s and Growth Investors.)

The three examples Suster uses – Salesforce, Google and Amazon – show how much more valuable the companies were after their IPOs. Before these three went public, they weren’t unicorns – that is their market cap was less than a billion dollars. Before these three went public, they weren’t unicorns – that is, their market cap was less than $ 1 billion. Twelve years later, Salesforce’s market cap was $18 billion, Google’s was $162 billion, and Amazon’s was $17 billion.To Suster’s point, it isn’t that startups today can’t raise money by going public, it’s that their investors can make more money by keeping them private and going public later – now 10-12 years. And currently there is an influx of capital to do that.

Founders Rule
The emergence of Growth capital, and pushing an IPO out a decade or more, has led to a dramatic shift in the balance of power between founders and investors. For three decades, from the mid-1970s to the early 2000s, the rules of the game were that a company must become profitable and hire a professional CEO before an IPO.

That made sense. Twentieth-century companies, competing in slower-moving markets, could thrive for long periods on a single innovation. If the VCs threw out the founder, the professional CEO who stepped in could grow a company without creating something new. In that environment, replacing a founder was the rational decision. But 21st century companies face compressed technology cycles, which create the need for continuous innovation over a longer period of time. Who leads that process best? Often it is founders, whose creativity, comfort with disorder, and risk-taking are more valuable at a time when companies need to retain a startup culture even as they grow large.

With the observation that founders added value during the long runup in the growth stage, VCs began to cede compensation and board control to founders. (See the HBR story here.)

Startup Stock Options – Why A Good Deal Has Gone Bad
While founders in the 20th century had more stock than the rest of their employees, they had the same type of stock options. Today, that’s not true. Rather, when a startup first forms, the founders grant themselves Restricted Stock Awards (RSA) instead of common stock options. Essentially the company sells them the stock at zero cost, and they reverse vest.

In the 20th century founders were taking a real risk on salary, betting their mortgage and future. Today that’s less true. Founders take a lot less risk, raise multimillion-dollar seed rounds and have the ability to cash out way before a liquidity event.

Early employees take an equal risk that the company will crater, and they often work equally as hard.  However, today founders own 30-50 times more than a startup’s early employees. (What has happened in founder compensation and board control has mirrored the growth in corporate CEO compensation. In the last 50 years, corporate CEO pay went from 20 times an average employee to over 300 times their compensation.)

On top of the founder/early employee stock disparity, the VC’s have moved the liquidity goal posts but haven’t moved the vesting goal posts for non-founders. Consider that the median tenure in a startup is 2 years. By year three, 50% of the employees will be gone. If you’re an early employee, today the company may not go public until eight years after you vest.

So why should non-founding employees of startups care? You’ll still own your stock, and you can leave and join another startup. There are four problems:

  • First, as the company raises more money, the value of your initial stock option grant gets diluted by the new money in. (VC’s typically have pro-rata rights to keep their percentage of ownership intact, but employees don’t.) So while the VCs gain the upside from keeping a startup private, employees get the downside.
  • Second, when IPO’s no longer happen within the near time horizon of an employee’s tenure, the original rationale of stock options – offering prospective hires a stake in the company’s future growth with a visible time horizon of a payoff for their hard work – has disappeared. Now there’s little financial reason to stay longer than the initial grant vesting.
  • Third, as the fair market value of the stock rises (to what the growth investors are paying), the high exercise price isn’t attractive for hiring new employees especially if they are concerned about having to leave and pay the high exercise price in order to keep the shares.
  • And finally, in many high valued startups where there are hungry investors, the founders get to sell parts of their vested shares at each round of funding. (At times this opportunity is offered to all employees in a “secondary” offering.) A “secondary” usually (though not always) happens when the startup has achieved significant revenue or traction and is seen as a “leader” in their market space, on the way to an IPO or a major sale

The End of the High-Commitment/High-Performance Work System?
In the academic literature, the work environment of a startup is called a high-commitment/ high-performance work system. This is a bundle of Human Resources startup practices that include hiring, self-managing teams, rapid and decentralized decision-making, on-boarding, flexible work assignments, communication, and stock options. And there is evidence that stock options increase the success of startups.

Successful startups need highly committed employees who believe in the goals and values of the company. In exchange for sharing in the potential upside—and being valued as a critical part of the team, they’re willing to rise to the expectation of putting work and the company in front of everything else. But this level of commitment depends on whether employees perceive these practices to be fair, both in terms of the process and the outcomes.

VCs have intentionally changed the ~50-year-old social contract with startup employees. At the same time, they may have removed one of the key incentives that made startups different from working in a large company.

While unique technology or market insight is one component of a successful startup everyone agrees that attracting and retaining A+ talent differentiates the winners from the losers. In trying to keep companies private longer, but not pass any of that new value to the employees, the VC’s may have killed the golden goose.

What Should Employees Do?
In the past the founders and employees were aligned with the same type of common stock grant, and it was the VCs who got preferential stock treatment. Today, if you’re an employee you’re now are at the bottom of the stock preference pile. The founders have preferential stock treatment and the VC have preferred stock. And you’re working just as hard. Add to that all the other known negatives of a startups– no work-life balance, insane hours, inexperienced management, risk of going out of business, etc.

That said, joining a startup still has a lot of benefits for employees who are looking to work with high performance teams with little structure. Your impact likely be felt. Constant learning opportunities, responsibility and advancement are there for those who take it.

If you’re one of the early senior hires, there’s no downside of asking for the same Restricted Stock Agreements (RSAs) as the founders. And if you’re joining a larger startup, you may want to consider those who are offering restricted stock units (RSUs) rather than common stock.

What Should Investors Do?
One possibility is to replace early employee (first ~10 employees) stock options with the same Restricted Stock Agreements (RSAs) as the founders.

For later employees make sure the company offers “refresh” option grants to longer-tenured employees. Better yet, offer restricted stock units (RSUs). Restricted Stock Units are a company’s promise to give you shares of the company’s stock. Unlike a stock option, which always has a strike (purchase) price higher than $0, an RSU is an option with a $0 purchase price. The lower the strike price,..

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It’s the same, but different

We just finished the 8th annual Lean LaunchPad class at Stanford. The team presentations are at the end of this post.

It’s hard to imagine, but only a decade ago, the capstone entrepreneurship class in most universities was how to write – or pitch- a business plan. As a serial entrepreneur turned educator, this didn’t make sense to me. In my experience, I saw that most business plans don’t survive first contact with customers.

So in 2011, with support from the Stanford Technology Ventures Program (the entrepreneurship center in the Stanford Engineering School), we created a new capstone entrepreneurship class – the Lean LaunchPad. The class was unique in that it was 1) team-based, 2) experiential, 3) lean-driven (hypothesis testing/business model/customer development/agile engineering). This new class aimed to mimic the uncertainty all startups face as they search for a business model while imparting an understanding of all the components of a business model, not just how to give a pitch or a demo.

(It’s worth reading the blog post that became the manifesto of the class here as well as what we learned when we first taught it- here.)

Ninety days after we first offered this class at Stanford, the National Science Foundation adopted the class calling it the NSF I-Corps (the Innovation Corps) to train our country’s top scientists how to commercialize their inventions. I-Corps is now offered in 88 universities. The National Institute of Health teaches its version in the National Cancer Institute. (I-Corps @ NIH). (The NIST report on Unleashing Innovation recommended expanding I-Corps and the House just passed the Innovators to Entrepreneurs Act to do just that.) The Lean LaunchPad/I-Corps syllabus is the basis for a series of Mission-Driven Entrepreneurship classes; Hacking for Diplomacy, Defense, Energy, Oceans, non-profits and cities.

If you had dropped by in 2011, the first time I taught the class, and then stuck your head in today, you’d say it was the same class. The syllabus is almost identical, the teams still get out of the building to do customer discovery every week, then come back to class and present what they learned weekly, etc.

But while it’s the same, it’s different.

After thousands of students taking this class, here are a few ways the class has changed.

—-

A Great Class Endures Beyond Its Author
I’ve always believed that great classes continue to thrive after the original teachers have moved on. While I created the Lean LaunchPad methodology and pedagogy (how to teach the class) and the train-the-trainer course for the NSF I-Corps, the sheer scale and success of the class is due to the efforts of the 100’s of National Science Foundation instructors and the NSF. And while I created the original course, the Stanford class is now led by Jeff Epstein and Steve Weinstein.

To be honest, as I watch other instructors now run these classes, I feel a proud “passing of the torch” though touched by moments of King Lear and Kurosawa’s Ran. Way past my ad hoc activities, the Stanford teaching team has thoroughly professionalized the class.

Expanded Teaching Team
In addition to the lead instructors, the Stanford teaching team now includes George John, Mar Hershenson, and Tom Bedecarre, all generously volunteering their time. Each of them brings decades of industry experience to the class. This type of teaching firepower and headcount was necessary as the teaching team expanded the class size to meet student demand.

Class Size
For the first few National Science Foundation classes, we taught 24 teams at a time with three instructors. We did it by breaking the class into three separate sections, having all teams together for our lectures and separating into sections of eight teams each when the teams presented. (After painful trial and error, we had discovered that the teaching team could listen to 8 teams present before our brains melted down.)

At Stanford we limited the class to 8 teams – four students per team. However, this year, the class was so oversubscribed, and the quality of the teams applying was so high, the teaching team admitted 14 teams and reverted to the original NSF model of separating into sections. The additional teaching team members made it possible.

Class Velocity/Depth
When we started this class, the concept of Lean (business models, customer development, agile, pivots, mvp’s) was new to everyone. Now they’re common buzzwords, and most of the students come in with an understanding of Lean. This head start has allowed the teaching team to accelerate the velocity and depth of learnings past the basics.

Women
In past years, the student teams in the Stanford classes were weighted toward men, reflecting the makeup of the applicants. While Ann Miura-Ko was part of the original teaching team, having all male instructors for the last five years didn’t help. After Mar Hershenson joined the teaching team last year, she made an all-out effort to recruit women to apply. A role model as a successful CEO and VC, Mar successfully sparked interest in women students and sponsored women-only lunch sessions, mixers and meetings to introduce them to the class. As you’ll notice from the presentations below, the result was that this year 50% of the applicants and accepted teams were women.

The lessons for me were: 1) the class had been unintentionally signaling a “boys-only” environment, 2) these unconscious biases were easily dismissed by assuming that the class makeup simply reflected the applicant pipeline, and 3) when in fact it required active outreach by a woman to change that perception and bring more women into the pipeline and subsequent teams.

Product/Market Fit Versus The Business Model Canvas
My original vision for the class was to use the business model canvas as a framework to teach engineering students all the nine elements of the business model: customer, distribution channel, revenue, get/keep/grow, value proposition, activities, resources, partners and costs. And instead of the traditional income statement, balance sheet and cash flow, discover the key “metrics that matter” for their business model.

While students want to spend their time focusing on product/market fit (who’s the customer and what should we build for them) and building product-centric minimum viable products, I thought that Y-Combinator and other accelerators already did an excellent job of that. My goal was to use the canvas to expose engineering students to other essential aspects of a successful business they may be less familiar with (sales, marketing, finance, operations.)

Admittedly this was tough to do, because in one quarter teams haven’t yet found product/market fit and are loath to move off it until they do. But since my goal was to teach a methodology rather than to run an accelerator, I traded off time on product/market fit for exposure to the rest of the canvas.

If we were designing a curriculum rather than just a single class, we’d offer it as two semesters/quarters – the first searching for problem/solution and product/market fit, and the second half focusing on the rest of the canvas testing feasibility and viability.

As you look at this year’s presentations, you can see the presentations still tend to focus on product/market fit. Obviously, there is no right answer to what and how to teach, and the answer may change over time.

TAs/ Diagnostics/Mentors
Our Teaching Assistants keep all the moving parts of the class running. Each years TAs have continued to make the class better (although I must admit it was interesting to watch the TAs remove any uncertainty from what students need to do week-to-week, as I had designed a level of uncertainty into the class to mimic what a real-world startup would feel like.) The teaching team and TA’s have added an enormous number of useful diagnostics to measure student reactions to each part of the pedagogy and the overall value of the class. However, the real art of teaching is to remember that the class wasn’t designed by a focus group.

Finally, the mentors (unpaid industry advisors) who volunteer their time have been professionalized and managed by Tom Bedecarre. Each mentor’s contribution gets graded by the students in the team they coached.

Things That Needed Constant Reminders
Every time we slipped up and admitted an all engineering or all MBA team we were reminded by their struggles that successful teams need to be diverse – that they include both innovators and entrepreneurs (typically engineers and MBA’s.)

The same holds true for pushing the students. Every time we slacked off relentlessly direct feedback we saw a commensurate drop in the quality of the teams output.

The Teams
In the end, this class is not only about what the instructors try to teach the students but also about whether students processed what we intended for them to learn. Over time, two of our major insights were: 1) teams needed a week to process all they learned, and 2) we needed to teach them how to turn that learning into a story of their journey.

This year all our teams accomplished that and much, much more.

And after 9 years of classes, students still find that this class is the closest thing to being in a real startup.

Take a look at their presentations below.

AgAI

If you can’t see the presentation click here

If you can’t see the video click here

AgAi_Lean Launchpad W19 - YouTube

BeaconsAI

If you can’t see the presentation click here

If you can’t see the video click here

BeaconsAI Final Video - YouTube

Equify

If you can’t see the presentation click here

If you can’t see the video click here

Equify Presentation Video Final - YouTube

Equipped

If you can’t see the presentation click here

If you can’t see the video click here

Equipped LLP Quarter Recap - YouTube

HardHats

If you can’t see the presentation click here

If you can’t see the video click here

Team Hard Hats Video - YouTube

Lemnos

If you can’t see the presentation click here

If you can’t see the video click here

Lemnos Lean Launchpad Journey - YouTube

NanoSense

If you can’t see the presentation click here

If you can’t see the video click here

nanoSense Final Video - YouTube

Neuro

If you can’t see the presentation click here

If you can’t see the video click here

Neuro Promo 1080 - YouTube

NeuroDiversity Nerds

If you can’t see the presentation click here

If you can’t see the video click here

PocketRobin LLP Video - YouTube

Praxis

If you can’t see the presentation click here

If you can’t see the video click here

Praxis Final Video - YouTube

Promote.It

If you can’t see the presentation click here

If you can’t see the video click here

LLP Promote It Short version - YouTube

RightFoot

If you can’t see the presentation click here

If you can’t see the video click here

Lean Launchpad Team Rightfoot Final Video - YouTube

Topt

If you can’t see the presentation click here

If you can’t see the video click here

LLP FINAL VIDEO - YouTube

Wanderwell

If you can’t see the presentation click here

If you can’t see the video click here

Wanderwell Final Video - YouTube

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If you’re an early employee at a startup, one day you will wake up to find that what you worked on 24/7 for the last year is no longer the most important thing – you’re no longer the most important employee, and process, meetings, paperwork and managers and bosses have shown up. Most painfully, you’ll learn that your role in the company has to change.

I blogged about this earlier here and got the chance to talk about the topic at the Startup Grind conference.

Below is a video of the talk.

How to Keep Your Job as Your Company Grows — Steve Blank (Author, The Four Steps to Epiphany) - YouTube

1:40: Having The Talk: How I lost my job after helping the company succeed
5:30: You need different skills as your company grows
6:47: A visceral blow: What just happened?
8:02: How I blew an opportunity
9:55: What you’ll feel if this happens to you
15:40: Why there should be no job titles at your startup
18:00: Why founders often come from dysfunctional families — and what that means for them as a company transitions
22:39: If you can see your future, you can change your future
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I’m a big fan of McKinsey’s Three Horizons Model of innovation. (if you’re not familiar with it there’s a brief description a few paragraphs down.) It’s one of the quickest ways to describe and prioritize innovation ideas in a large company or government agency.

However, in the 21stcentury the Three Horizons model has a fatal flaw that could put companies out of business and government agencies behind their adversaries. While traditional analysis suggests that Horizon 3 disruptive innovations take years to develop, in today’s world this is no longer the case. The three horizons are not bound by time. Horizon 3 ideas – disruption – can be delivered as fast as ideas for Horizon 1 – existing products.

In order to not be left behind, companies / government agencies need to focus on speed of delivery and deployment across all three horizons.

When first articulated by Baghai, Coley and White in the 20th century, the Three Horizons model was a simple way to explain to senior management the need for an ambidextrous organization – the idea that companies and government agencies need to execute existing business / mission models while simultaneously creating new capabilities.

The Three Horizons provided an incredibly useful taxonomy. The model described innovation occurring in three time horizons:

  • Horizon 1 ideas provide continuous innovation to a company’s existing business model and core capabilities.
  • Horizon 2 ideas extend a company’s existing business/model and core capabilities to new customers, markets or targets.
  • Horizon 3 is the creation of new capabilities to take advantage of or respond to disruptive opportunities or to counter disruption.

Each horizon requires different focus, different management, different tools and different goals. McKinsey suggested that to remain competitive in the long run a company allocate its research and development dollars and resources across all three horizons.

And here’s the big idea. In the past we assigned relative delivery time to each of the Horizons. For example, some organizations defined Horizon 1 as new features that could be delivered in 3-12 months; Horizon 2 as business/mission model extensions 24-36 months out; and Horizon 3 as creating new disruptive products/business/mission models 36-72 months out.  This time-based definition made sense in the 20th century when new disruptive ideas took years to research, engineer and deliver.

That’s no longer true in the 21st century.

Today, disruption Horizon 3 ideas – can be delivered as fast as Horizon 1 ideas.

For example, Uber took existing technology (smartphone app, drivers) but built a unique business model (gig economy disrupting taxis) and the Russians used existing social media tools to wage political warfare. Fast disruption happens by building on existing technologies uniquely configured, packaged and/or delivered, and combining them with a “speed of good-enough deployment as a force multiplier” mindset.

What’s an Example of Rapid Horizon 3 Implementation?
In the commercial space AirBnB, Uber, Craigslist, Tesla, and the explosion of machine learning solutions (built on hardware originally designed for computer graphics (Nvida)) are examples of radical disruption using existing technologies in extremely short periods of time.

In the government space, Russian interference with elections, and China building island bases in the South China Sea as well as repurposing ICBMs as conventional weapons to attack aircraft carriers, are examples of radical disruption using existing technologies deployed in extremely short periods of time.

What’s Different about Rapid Horizon 3 Disruption?
These rapid Horizon 3 deliverables emphasize disruption, asymmetry and most importantly speed, over any other characteristic. Serviceability, maintainability, completeness, scale, etc. are all secondary to speed and asymmetry.

To existing competitors or to existing requirements and acquisition systems they look like minimum viable products – barely finished, iterative and incremental prototypes. But the new products get out of the building, disrupt incumbents and once established, they then refactor and scale. Incumbents now face a new competitor/threat that obsoletes their existing product line/infrastructure/business/mission model.

Why Do the Challengers/new Entrants Have the Edge?
Ironically rapid Horizon 3 disruption is most often used not by the market leaders but by the challengers/new entrants (startups, ISIS, China, Russia, etc.). The new players have no legacy systems to maintain, no cumbersome requirements and acquisition processes, and are single-mindedly focused on disrupting the incumbents.

Four Strategies to Deal With Disruption
For incumbents, there are four ways to counter rapid disruption:

  • Incentivize external resources to focus on your goal/mission. For example, NASA and Commercial Resupply Services with SpaceX and OrbitalATK, Apple and the App Store, DARPA Prize challenges. The large organizations used startups who could rapidly build and deliver products for them – by offering something the startups needed – contracts, a distribution platform, or prizes. This can be a contract with a single startup or a broader net to incentivize many.
  • Combine the existing strengths of a company/agency and its business/mission model by acquiring external innovators who can operate at the speed of the disruptors. For example, Google buying Android. The risk here is that the mismatch of culture, process and incentives may strangle the newly acquired innovation culture.
  • Rapidly copy the new disruptive innovators and use the incumbent’s business/mission model to dominate. For example, Microsoft copying Netscape’s web browser and using its dominance of operating system distribution to win, or Google copying Overture’s pay per click model and using its existing dominance in search to sell ads. The risk here is that copying innovation without understanding the customer problem/mission can result in solutions that miss the target.
  • Innovate better than the disrupters. (Extremely difficult for large companies/government agencies as it is as much a culture/process problem as a technology problem. Startups are born betting it all. Large organizations are executing and protecting the legacy.) Successful examples, Apple and the iPhone, Amazon and Amazon Web Services (AWS). Gov’t agency and armed drones.

Lessons Learned

  • The Three Horizons model is still very useful as a shorthand for prioritizing innovation initiatives.
  • Some Horizon 3 disruptions do take long periods of development
  • However, today many Horizon 3 disruptions can be rapidly implemented by repurposing existing Horizon 1 technologies into new business/mission models
  • Speed of deployment of a disruptive/asymmetric product is a force multiplier
  • The attackers have the advantage, as the incumbents are burdened with legacy
  • Four ways for the incumbents to counter rapid disruption:
    • Incentivize external resources
    • Acquire external innovators
    • Rapidly copy
    • Innovate better than the disrupters
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Five years ago we brought evidence-based entrepreneurship to Life Sciences – teaching the first Lean Lean Launchpad class at UCSF, then the NIH and Imperial College. But it’s been awhile since I was in a room made up entirely of Life Science entrepreneurs. So I was excited to visit IndieBio, a life science accelerator in San Francisco. Think of IndieBio as “Y-Combinator for Life Sciences with a wet lab” and you get what they are trying to do. It’s a 4-month program to help biotech startups build their company and it comes with $250k in seed funding.

I sat down with Arvind Gupta, Founder and Managing Director of IndieBio and talked about how Lean methods apply to Life Sciences.

Designing Science with Arvind Gupta & Steve Blank - YouTube

If you can’t see the video click here

The first half of the conversation talks about Lean and its origins.

The second half focuses on its applicability in Digital Health and Life Sciences.

18:19: Why the Lean Startup works for life science startups
19:20: The origins of Lean and I-Corps
22:34: Your science is not a company
26:53: Your investors may like you but it’s not why they fund you
28:53: Do you have a crazy person in the room — Innovators vs. entrepreneurs
32:30: Reducing startup risk – Evidence-based entrepreneurship in Life Science
35:30: Lean is a bounding box around infinite uncertainty
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I know a change is going to come

If you’re an early employee at a startup, one day you will wake up to find that what you worked on 24/7 for the last year is no longer the most important thing – you’re no longer the most important employee, and process, meetings, paperwork and managers and bosses have shown up. Most painfully, you’ll learn that your role in the company has to change.

I’ve seen these transitions as an investor, board member and CEO. At times they are painful to watch and difficult to manage. Early in my career I lived it as an employee, and I handled it in the worst possible way.

Here’s what I wish I had known.

I had joined MIPS Computers, my second semiconductor company, as the VP of marketing and also took on the role of the acting VP of Sales. During the first year of the company’s life, I was a fireball – relentless in creating and pursuing opportunities – getting on an airplane at the drop of a hat to fly anywhere, anytime, to get a design win. I worked with engineering to try to find product/market fit (big endian or little endian?) and get the chip designed into companies building engineering workstations – powerful personal computers, all while trying to refine how to find the right markets, customers, and sales process. I didn’t get much sleep, but I was having the time of my life.

And after a year there was good news. Our rent-a-CEO was being replaced by a permanent one. Our chip was nearing completion, and I had convinced early lighthouse customers to design it into their computers. I had done amazing things with almost no resources and got the company on the radar of every tech publication and into deals we had no right to be in. I was feeling 10 feet tall. Everything was great… until the new CEO called me in for a chat.

I don’t remember much about the details, but I do remember hearing him tell me how impressed he was with what I had accomplished so far, then immediately the visceral feeling of shock and surprise when his next words were that now the company needed to scale, and I wasn’t the right person to do that… Wait! What??

For a minute I couldn’t breathe. I felt like I had been punched in the gut. How could that be?  What do you mean I’m not the right person??? Hadn’t he just listed all the great work I had done? He acknowledged it was a lot of progress but offered that it was a flurry of disconnected tactics without a coherent strategy. No one knew what I was doing, and I couldn’t explain why I was doing it when asked. “You’re just throwing stuff against the wall. That doesn’t scale.” I was speechless. Wasn’t that what the first year of a startup was supposed to be like?

Scrambling to save my job, I regained the power of speech, and asked him if I could be the person to take the company to the next level. And to his credit (which I only appreciated years later) he agreed that while he was going to start a search, I could be a candidate for the job. And to top it off he got me a coach to help me understand what taking it to the next level meant. In preparation I remember buying all the management books I could find and reading what little literature there was at the time about how small company management transitioned into a larger one.

And herein lies the tale….
I vaguely remember going to lunch with my coach, a nice white-haired “old guy” who was trying to help me learn the skills to grow into the new job. The problem was I had shut down. Even as we were meeting, I was obsessively thinking about the change in my role, my title and my status. “I don’t get it, I did all this work, and everything was great. Why does anything have to change?”  But I never shared any of how I felt with my coach. To do this day I am really embarrassed to admit that I have no idea what my coach tried to teach me over multiple lunches and weeks. As we went to lunch, all I could think about was me and how I was being screwed. I literally paid zero attention. In my righteous anger I was unreachable.

I shouldn’t have been surprised, but yet again I was, when a month later the CEO said, that the report from the coach said, “I had a long way to go”. The company was going to hire a VP of Marketing. I was devastated.

I quit.

It’s Not About Change – It’s About Loss
If you had asked me a decade later what had been going on in my head and why I handled this so badly, I would have simply said, that: 1) I was resistant to change, and that 2) I had made this all about me and never once considered that our new CEO was right. All true – to a point.

It took me another decade to realize if I had been really honest with myself it wasn’t about fighting change at all. Heck every day something new was happening at our startup. I was agile enough to keep up with innumerable changes and I was changing lots of things myself. It was actually about something much more personal I wouldn’t admit to myself – it was that these changes made me fear what I was losing;

  • I felt a loss of status and identity – I had been judged inadequate to continue in my role and my stature and the value of my skills and abilities had dropped.
  • I felt a loss of certainty – I was now competing to hold a job I thought was mine forever in the company. At least that’s what I thought my business card said. Now I was adrift and didn’t know what the future held.
  • I felt a loss of autonomy – Up until now I used my best judgment of what was needed and I was doing what I wanted, when I wanted it. I was fine making up a strategy on the fly from disconnected tactics. Now we were going to have plans and a strategy.
  • I felt a loss of community – we had been a small tight team who had bonded together under extreme pressure and accomplished amazing things. Now new people who knew none of that and appreciated little of it were coming in. They had little trust and empathy with us.
  • I felt the process lacked fairness – no one had warned/told me that the job I was doing needed to change over time, and no one told me what those new skills were.

What was going on?
Researchers have found there’s a link between social connection and physical discomfort within the brain. “Being hungry and being ostracized activate similar neural responses because being socially connected is necessary for survival. Although a job is often regarded as a purely economic transaction, the brain experiences the workplace first and foremost as a social system.”

Looking back over the decades it’s clear that the new CEO was right. Even though these losses triggered something primal, I did need to learn discipline, pattern recognition, time management, separating the trivial from the important and the difference between tactics and strategy. I needed to learn to grow from being a great individual contributor to being a manager and then a leader. Instead I walked away from learning any of it.

I probably added five unneeded years to my career.

What should I have done?
Today it’s understood that all startups go through a metamorphosis as they become larger companies. They go from organizations struggling for survival as they search for product/market fit, to building a repeatable and scalable business model, and then growing to profitability. And we are all hard-wired for a set number of social relationships. This mental wiring defines boundaries in growing an organization – get bigger than a certain size, and you need a different management system. The skills needed from employees differ at each stage.

What I wish I knew was that if you’re an early company employee, it’s not likely that the skills you have on day one are the skills needed as the company scales to the next level. This sentence is worth reading multiple times as no one – not the person who hired you, the VC’s or your peers -is going to tell you when you’re hired that the company will likely outgrow you. Some (like your peers or even the founders) don’t understand it, and others (the VCs) realize it’s not in their interest to let you know. The painful reality is that products change, strategies change, people change…things have to change for your company to stay in business and grow.

What should my CEO have done?
When my CEO was explaining to me how the company needed to change to grow, he was explaining facts while I was processing deeply held feelings. The changes in the organization and my role represented what I was about to lose. And when people feel they’re going to lose something deeply important, it triggers an emotional response because change feels like a threat. It’s not an excuse for my counterproductive behavior, but explains why I acted out like I did.

Startup CEOs need to think about these transitions from day one and consider how to address the real sense of loss these transitions mean to early employees.

Loss of status? It’s almost impossible to take away a title from someone, give it to someone else and still retain that employee. Think hard about whether titles need to be formal (VP of Engineering, VP of Marketing, VP of Sales, etc.) before the company finds product/market fit and/or tens of people – as you can almost guarantee that these people won’t have those roles and titles when you scale.

Loss of Certainty? Startups and VC’s have historically operated on the “I’ll deal with this later” principle in letting early employees know what happens as the company scales. The common wisdom is that no one would want to work like crazy knowing that they might not be the ones to lead as the company grows. I call this the Moses-problem – you work for years to get the tribe to the promised land – but you’re not allowed to cross over. The company needs to give formal recognition for those individuals who brought the tribe to the promised land.

Loss of Autonomy? This is the time you and your employees get to have a discussion about the next steps in their career. Do they want to be an individual contributor? Manager of people and process? Special projects? These shouldn’t be random assignments but instead, offer a roadmap of possible choices and directions.

Loss of Community? Your original hires embody the company culture. Unless you have them capture the unique aspects of the culture, it will become diluted and disappear among the new hires. Declare them cultural co-founders. Help them understand the community is growing and they’re the ambassadors. Have them formalize it as part of a now needed on-boarding process as the company grows. And most importantly, make sure that they are celebrated as the team that got the company to where it is now.

Loss of Fairness? Just telling employees “a change is going to come” it is not sufficient. What are the new skills needed when you scale from Search to Build to Grow – from tens to hundreds and then thousands of people? How can your existing employees gain those new skills?

Lessons Learned

  • VC’s, Founders and CEOs now recognize that startups grow through different stages: Search, Build and Grow
    • They recognize that employees need different skills at each stage
    • And that some of the original employees won’t grow into the next stage
  • But while these changes make rational sense to the CEO and the board, to early employees these changes feel like a real and tangible personal loss
    • Loss of Status and Identity
    • Loss of Community
    • Loss of Autonomy
    • Loss of Certainty
    • Loss of Fairness
  • CEOs need to put processes in places to acknowledge and deal with the real sense of loss
    • These will keep early employees motivated – and retained
    • And build a stronger company
  • For employees, how you handle change will affect the trajectory of your career and possibly your net worth
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If you haven’t gotten a new car in a while you may not have noticed that the future of the dashboard looks like this:


That’s it. A single screen replacing all the dashboard gauges, knobs and switches. But behind that screen is an increasing level of automation that hides a ton of complexity.

At times everything you need is on the screen with a glance. At other times you have to page through menus and poke at the screen while driving. And while driving at 70mph, try to understand if you or your automated driving system is in control of your car. All while figuring out how to use any of the new features, menus or rearranged user interface that might have been updated overnight.

In the beginning of any technology revolution the technology gets ahead of the institutions designed to measure and regulate safety and standards. Both the vehicle’s designers and regulators will eventually catch up, but in the meantime we’re on the steep part of a learning curve – part of a million-person beta test – about what’s the right driver-to-vehicle interface.

We went through this with airplanes. And we’re reliving that transition in cars. Things will break, but in a few decades we’ll come out out the other side, look back and wonder how people ever drove any other way.

Here’s how we got here, what it’s going to cost us, and where we’ll end up.

Cars, Computers and Safety
Two massive changes are occurring in automobiles: 1) the transition from internal combustion engines to electric, and 2) the introduction of automated driving.

But a third equally important change that’s also underway is the (r)evolution of car dashboards from dials and buttons to computer screens. For the first 100 years cars were essentially a mechanical platform – an internal combustion engine and transmission with seats – controlled by mechanical steering, accelerator and brakes. Instrumentation to monitor the car was made up of dials and gauges; a speedometer, tachometer, and fuel, water and battery gauges.
By the 1970’s driving became easier as automatic transmissions replaced manual gear shifting and hydraulically assisted steering and brakes became standard. Comfort features evolved as well: climate control – first heat, later air-conditioning; and entertainment – AM radio, FM radio, 8-track tape, CD’s, and today streaming media. In the last decade GPS-driven navigation systems began to appear.

Safety
At the same time cars were improving, automobile companies fought safety improvements tooth and nail. By the 1970’s auto deaths in the U.S averaged 50,000 a year. Over 3.7 million people have died in cars in the U.S. since they appeared – more than all U.S. war deaths combined. (This puts auto companies in the rarified class of companies – along with tobacco companies – that have killed millions of their own customers.) Car companies argued that talking safety would scare off customers, or that the added cost of safety features would put them in a competitive price disadvantage. But in reality, style was valued over safety.

Safety systems in automobiles have gone through three generations – passive systems and two generations of active systems. Today we’re about to enter a fourth generation – autonomous systems.

Passive safety systems are features that protect the occupants after a crash has occurred. They started appearing in cars in the 1930’s. Safety glass in windshields appeared in the 1930’s in response to horrific disfiguring crashes. Padded dashboards were added in the 1950’s but it took Ralph Nader’s book, Unsafe at Any Speed, to spur federally mandated passive safety features in the U.S. beginning in the 1960’s: seat belts, crumple zones, collapsible steering wheels, four-way flashers and even better windshields. The Department of Transportation was created in 1966 but it wasn’t until 1979 that the National Highway Traffic Safety Administration (NHTSA) started crash-testing cars (the Insurance Institute for Highway Safety started their testing in 1995). In 1984 New York State mandated seat belt use (now required in 49 of the 50 states.)

These passive safety features started to pay off in the mid-1970’s as overall auto deaths in the U.S. began to decline.

Active safety systems try to prevent crashes before they happen. These depended on the invention of low-cost, automotive-grade computers and sensors. For example, accelerometers-on-a-chip made airbags possible as they were able to detect a crash in progress. These began to appear in cars in the late 1980’s/1990’s and were required in 1998. In the 1990’s computers capable of real-time analysis of wheel sensors (position and slip) made ABS (anti-lock braking systems) possible. This feature was finally required in 2013.

Since 2005 a second generation of active safety features have appeared. They run in the background and constantly monitor the vehicle and space around it for potential hazards. They include: Electronic Stability Control, Blind Spot Detection, Forward Collision Warning, Lane Departure Warning, Rearview Video Systems, Automatic Emergency Braking, Pedestrian Automatic Emergency Braking, Rear Automatic Emergency Braking, Rear Cross Traffic Alert and Lane Centering Assist.

Autonomous Cars
Today, a fourth wave of safety features is appearing as Autonomous/Self-Driving features. These include Lane Centering/Auto Steer, Adaptive cruise control, Traffic jam assist, Self-parking, full self-driving. The National Highway Traffic Safety Administration (NHTSA) has adopted the six-level SAE standard to describe these vehicle automation features:

Getting above Level 2 is a really hard technical problem and has been discussed ad infinitum in other places. But what hasn’t got much attention is how drivers interact with these systems as the level of automation increases, and as the driving role shifts from the driver to the vehicle. Today, we don’t know whether there are times these features make cars less safe rather than more.

For example, Tesla and other cars have Level 2 and some Level 3 auto-driving features. Under Level 2 automation, drivers are supposed to monitor the automated driving because the system can hand back control of the car to you with little or no warning. In Level 3 automation drivers are not expected to monitor the environment, but again they are expected to be prepared to take control of the vehicle at all times, this time with notice.

Research suggests that drivers, when they aren’t actively controlling the vehicle, may be reading their phone, eating, looking at the scenery, etc. We really don’t know how drivers will perform in Level 2 and 3 automation. Drivers can lose situational awareness when they’re surprised by the behavior of the automation – asking: What is it doing now? Why did it do that? Or, what is it going to do next? There are open questions as to whether drivers can attain/sustain sufficient attention to take control before they hit something. (Trust me, at highway speeds having a “take over immediately” symbol pop up while you are gazing at the scenery raises your blood pressure, and hopefully your reaction time.)If these technical challenges weren’t enough for drivers to manage, these autonomous driving features are appearing at the same time that car dashboards are becoming computer displays.

We never had cars that worked like this. Not only will users have to get used to dashboards that are now computer displays, they are going to have understand the subtle differences between automated and semi-automated features and do so as auto makers are developing and constantly updating them. They may not have much help mastering the changes. Most users don’t read the manual, and, in some cars, the manuals aren’t even keeping up with the new features.

But while we never had cars that worked like this, we already have planes that do.
Let’s see what we’ve learned in 100 years of designing controls and automation for aircraft cockpits and pilots, and what it might mean for cars.

Aircraft Cockpits
Airplanes have gone through multiple generations of aircraft and cockpit automation. But unlike cars which are just first seeing automated systems, automation was first introduced in airplanes during the 1920s and 1930s.

For their first 35 years airplane cockpits, much like early car dashboards, were simple – a few mechanical instruments for speed, altitude, relative heading and fuel. By the late 1930’s the British Royal Air Force (RAF) standardized on a set of flight instruments. Over the next decade this evolved into the “Basic T” instrument layout – the de facto standard of how aircraft flight instruments were laid out.

Engine instruments were added to measure the health of the aircraft engines – fuel and oil quantity, pressure, and temperature and engine speed.

Next, as airplanes became bigger, and the aerodynamic forces increased, it became difficult to manually move the control surfaces so pneumatic or hydraulic motors were added to increase the pilots’ physical force. Mechanical devices like yaw dampers and Mach trim compensators corrected the behavior of the plane.

Over time, navigation instruments were added to cockpits. At first, they were simple autopilots to just keep the plane straight and level and on a compass course. The next addition was a radio receiver to pick up signals from navigation stations. This was so pilots could set the desired bearing to the ground station into a course deviation display, and the autopilot would fly the displayed course.

In the 1960s, electrical systems began to replace the mechanical systems:

  • electric gyroscopes (INS) and autopilots using VOR (Very High Frequency Omni-directional Range) radio beacons to follow a track
  • auto-throttle – to manage engine power in order to maintain a selected speed
  • flight director displays – to show pilots how to fly the aircraft to achieve a preselected speed and flight path
  • weather radars – to see and avoid storms
  • Instrument Landing Systems – to help automate landings by giving the aircraft horizontal and vertical guidance.

By 1960 a modern jet cockpit (the Boeing 707) looked like this:

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I’ve been thinking why the ethical boundaries of todays founder/VC interactions feel so different then they did when I was an entrepreneur. I’ve written about the root causes in an HBR article here and an expanded version here. Worth a read.

Stanford eCorner captured a few minutes of what I’ve been thinking in the video below.

Why Tech Founders Need a Moral Compass - YouTube

If you can’t see the video click here

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