Why Companies are Not Startups

In the last few years we’ve recognized that a startup is not a smaller version of a large company. We’re now learning that companies are not larger versions of startups.

There’s been lots written about how companies need to be more innovative, but very little on what stops them from doing so.

Companies looking to be innovative face a conundrum: Every policy and procedure that makes them efficient execution machines stifles innovation.

This first post will describe some of the structural problems companies have; follow-on posts will offer some solutions.

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Facing continuous disruption from globalization, China, the Internet, the diminished power of brands, changing workforce, etc., existing enterprises are establishing corporate innovation groups. These groups are adapting or adopting the practices of startups and accelerators – disruption and innovation rather than direct competition, customer development versus more product features, agility and speed versus lowest cost.

But paradoxically, in spite of all their seemingly endless resources, innovation inside of an existing company is much harder than inside a startup. For most companies it feels like innovation can only happen by exception and heroic efforts, not by design. The question is – why?

The Enterprise: Business Model Execution
We know that a startup is a temporary organization designed to search for a repeatable and scalable business model. The corollary for an enterprise is:

A company is a permanent organization designed to execute a repeatable and scalable business model.

Once you understand that existing companies are designed to execute then you can see why they have a hard time with continuous and disruptive innovation.

Every large company, whether it can articulate it or not, is executing a proven business model(s). A business model guides an organization to create and deliver products/service and make money from it. It describes the product/service, who is it for, what channel sells/deliver it, how demand is created, how does the company make money, etc.

Somewhere in the dim past of the company, it too was a startup searching for a business model. But now, as the business model is repeatable and scalable, most employees take the business model as a given, and instead focus on the execution of the model – what is it they are supposed to do every day when they come to work. They measure their success on metrics that reflect success in execution, and they reward execution.

It’s worth looking at the tools companies have to support successful execution and explain why these same execution policies and processes have become impediments and are antithetical to continuous innovation.

20th century Management Tools for Execution
In the 20th century business schools and consulting firms developed an amazing management stack to assist companies to execute. These tools brought clarity to corporate strategy, product line extension strategies, and made product management a repeatable process.

bcg matrix

For example, the Boston Consulting Group 2 x 2 growth-share matrix was an easy to understand strategy tool – a market selection matrix for companies looking for growth opportunities.

Strategy Maps from Robert Kaplan

Strategy Maps

Strategy Maps are a visualization tool to translate strategy into specific actions and objectives, and to measure the progress of how the strategy gets implemented.

StageGate

StageGate Process

Product management tools like Stage-Gate® emerged to systematically manage Waterfall product development. The product management process assumes that product/market fit is known, and the products can get spec’d and then implemented in a linear fashion.

Strategy becomes visible in a company when you draw the structure to execute the strategy. The most visible symbol of execution is the organization chart. It represents where employees fit in an execution hierarchy; showing command and control hierarchies – who’s responsible, what they are responsible for, and who they manage below them, and report to above them.

GM 1925 org chart

All these tools – strategy, product management and organizational structures, have an underlying assumption – that the business model – which features customers want, who the customer is, what channel sells/delivers the product or service, how demand is created, how does the company make money, etc – is known, and that all the company needed is a systematic process for execution.

Driven by Key Performance Indicators (KPI’s) and Processes
Once the business model is known, the company organizes around that goal and measures efforts to reach the goal, and seeks the most efficient ways to reach the goal. This systematic process of execution needs to be repeatable and scalable throughout a large organization by employees with a range of skills and competencies. Staff functions in finance, human resources, legal departments and business units developed Key Performance Indicators, processes, procedures and goals to measure, control and execute.

Paradoxically, these very KPIs and processes, which make companies efficient, are the root cause of corporations’ inability to be agile, responsive innovators. 

This is a big idea.

Finance  The goals for public companies are driven primarily by financial Key Performance Indicators (KPI’s). They include: return on net assets (RONA), return on capital deployed, internal rate of return (IRR), net/gross margins, earnings per share, marginal cost/revenue, debt/equity, EBIDA, price earning ratio, operating income, net revenue per employee, working capital, debt to equity ratio, acid test, accounts receivable/payable turnover, asset utilization, loan loss reserves, minimum acceptable rate of return, etc.

(A consequence of using these corporate finance metrics like RONA and IRR is that it‘s a lot easier to get these numbers to look great by 1) outsourcing everything, 2) getting assets off the balance sheet and 3) only investing in things that pay off fast. These metrics stack the deck against a company that wants to invest in long-term innovation.)

These financial performance indicators then drive the operating functions (sales, manufacturing, etc) or business units that have their own execution KPI’s (market share, quote to close ratio, sales per rep, customer acquisition/activation costs, average selling price, committed monthly recurring revenue, customer lifetime value, churn/retention, sales per square foot, inventory turns, etc.)

Corp policies and KPIs

Corporate KPI’s, Policy and Procedures: Innovation Killers

HR Process  Historically Human Resources was responsible for recruiting, retaining and removing  employees to execute known business functions with known job spec’s. One of the least obvious but most important HR Process, and ultimately the most contentious, issue in corporate innovation is the difference in incentives. The incentive system for a company focused on execution is driven by the goal of meeting and exceeding “the (quarterly/yearly) plan.”  Sales teams are commission-based, executive compensation is based on EPS, revenue and margin, business units on revenue and margin contribution, etc.

What Does this Mean?
Every time another execution process is added, corporate innovation dies a little more.

The conundrum is that every policy and procedure that makes a company and efficient execution machine stifles innovation.

Innovation is chaotic, messy and uncertain. It needs radically different tools for measurement and control. It needs the tools and processes pioneered in Lean Startups.HBR Lean Startup article

While companies intellectually understand innovation, they don’t really know how to build innovation into their culture, or how to measure its progress.

What to Do?
It may be that the current attempts to build corporate innovation are starting at the wrong end of the problem. While it’s fashionable to build corporate incubators there’s little evidence that they deliver more than “Innovation Theater.” Because internal culture applies execution measures/performance indicators to the output of these incubators and allocates resources to them same way as to executing parts of company.

Corporations that want to build continuous innovation realize that innovation happens not by exception but as integral to all parts of the corporation.

To do so they will realize that a company needs innovation KPI’s, policies, processes and incentives. (Our Investment Readiness Level is just one of those metrics.) These enable innovation to occur as an integral and parallel process to execution. By design not by exception.

We’ll have more to say about this in future posts.

Lessons Learned

  • Innovation inside of an existing company is much harder than a startup
  • KPI’s and processes are the root cause of corporations’ inability to be agile and responsive innovators
  • Every time another execution process is added, corporate innovation dies a little more
  • Intellectually companies understand innovation, they don’t have the tools to put it into practice
  • Companies need different policies,  procedures and incentives designed for innovation
  • Currently the data we use for execution models the past
  • Innovation metrics need to be predictive for the future
  • These tools and practices are coming…

Listen to this post here

Download the podcast here

Is This Startup Ready For Investment?

Since 2005 startup accelerators have provided cohorts of startups with mentoring, pitch practice and product focus. However, accelerator Demo Days are a combination of graduation ceremony and pitch contest, with the uncomfortable feel of a swimsuit competition. Other than “I’ll know it when I see it”, there’s no formal way for an investor attending Demo Day to assess project maturity or quantify risks. Other than measuring engineering progress, there’s no standard language to communicate progress.

Corporations running internal incubators face many of the same selection issues as startup investors, plus they must grapple with the issues of integrating new ideas into existing P&L-driven functions or business units.

What’s been missing for everyone is:

  • a common language for investors to communicate objectives to startups
  • a language corporate innovation groups can use to communicate to business units and finance
  • data that investors, accelerators and incubators can use to inform selection

While it doesn’t eliminate great investor judgment, pattern recognition skills and mentoring, we’ve developed an Investment Readiness Level tool that fills in these missing pieces.

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Investment Readiness Level (IRL) for Corporations and Investors
The startups in our Lean LaunchPad classes and the NSF I-Corps incubator use LaunchPad Central to collect a continuous stream of data across all the teams. Over 10 weeks each team gets out of the building talking to 100 customers to test their hypotheses across all 9 boxes in the business model canvas.

We track each team’s progress as they test their business model hypotheses. We collect the complete narrative of what they discovered talking to customers as well as aggregate interviews, hypotheses to test, invalidated hypotheses and mentor and instructor engagements. This data gives innovation managers and investors a feel for the evidence and trajectory of the cohort as a whole and a top-level view of each teams progress. The software rolls all the data into an Investment Readiness Level score.

(Take a quick read of the post on the Investment Readiness Level – it’s short. Or watch the video here.)

The Power of the Investment Readiness Level: Different Metrics for Different Industry Segments
Recently we ran a Lean LaunchPad for Life Sciences class with 26 teams of clinicians and researchers at UCSF.  The teams developed businesses in 4 different areas– therapeutics, diagnostics, medical devices and digital health.  To understand the power of this tool, look at how the VC overseeing each market segment modified the Investment Readiness Level so that it reflected metrics relevant to their particular industry.

Medical Devices
Allan May of Life Science Angels modified the standard Investment Readiness Level to include metrics that were specific for medical device startups. These included; identification of a compelling clinical need, large enough market, intellectual property, regulatory issues, and reimbursement, and whether there was a plausible exit.

In the pictures below, note that all the thermometers are visual proxies for the more detailed evaluation criteria that lie behind them.

Device IRL

Investment Readiness Level for Medical Devices

You can watch the entire presentation here

Therapeutics
Karl Handelsman of CMEA Capital modified the standard Investment Readiness Level (IRL) for teams developing therapeutics to include identifying clinical problems, and agreeing on a timeline to pre-clinical and clinical data, cost and value of data points, what quality data to deliver to a company, and building a Key Opinion Leader (KOL) network. The heart of the therapeutics IRL also required “Proof of relevance” – was there a path to revenues fully articulated, an operational plan defined. Finally, did the team understand the key therapeutic liabilities, have data proving on-target activity and evidence of a therapeutic effect.

Therapeutics IRL

You can see the entire presentation here

Digital Health
For teams developing Digital Health solutions, Abhas Gupta of MDV noted that the Investment Readiness Level was closest to the standard web/mobile/cloud model with the addition of reimbursement and technical validation.

Digital Health

Diagnostics
Todd Morrill wanted teams developing Diagnostics to have a reimbursement strategy fully documented, the necessary IP in place, regulation and technical validation (clinical trial) regime understood and described and the cost structure and financing needs well documented.

Diagnostics IRL

You can see the entire presentation here

For their final presentations, each team explained how they tested and validated their business model (value proposition, customer segment, channel, customer relationships, revenue, costs, activities, resources and partners.) But they also scored themselves using the Investment Readiness Level criteria for their  market. After the teams reported the results of their self-evaluation, the  VC’s then told them how they actually scored.  We were fascinated to see that the team scores and the VC scores were almost the same.

Lessons Learned

  • The Investment Readiness Level provides a “how are we doing” set of metrics
  • It also creates a common language and metrics that investors, corporate innovation groups and entrepreneurs can share
  • It’s flexible enough to be modified for industry-specific business models
  • It’s part of a much larger suite of tools for those who manage corporate innovation, accelerators and incubators

Listen to the blog post here

Download the podcast here

How to Be Smarter than Your Investors – Continuous Customer Discovery

Teams that build continuous customer discovery into their DNA will become smarter than their investors, and build more successful companies.

Awhile back I blogged about Ashwin, one of my ex-students wanted to raise a seed round to build Unmanned Aerial Vehicles (drones) with a Hyper-spectral camera and fly it over farm fields collecting hyper-spectral images. These images, when processed with his company’s proprietary algorithms, would be able to tell farmers how healthy their plants were, whether there were diseases or bugs, whether there was enough fertilizer, and enough water.

(When computers, GPS and measurement meet farming, the category is called “precision agriculture.” I see at least one or two startup teams a year in this space.)Optimized water and fertilizer

At the time I pointed out to Ashwin that his minimum viable product was actionable data to farmers and not the drone. I suggested that to validate their minimum viable product it would be much cheaper to rent a camera and plane or helicopter, and fly over the farmers field, hand process the data and see if that’s the information farmers would pay for. And that they could do that in a day or two, for a tenth of the money they were looking for.

Walnut orchard

(Take a quick read of the original post here)

Fast forward a few months and Ashwin and I had coffee to go over what his company Ceres Imaging had learned. I wondered if he was still in the drone business, and if not, what had become the current Minimum Viable Product.

It was one of those great meetings where all I could do was smile: 1) Ashwin and the Ceres team had learned something that was impossible to know from inside their building, 2) they got much smarter than me.

Crop Dusters
Even though the Ceres Imaging founders initially wanted to build drones, talking to potential customers convinced them that as I predicted, the farmers couldn’t care less how the company acquired the data. But the farmers told them something that they (nor I) had never even considered – crop dusters (fancy word for them are “aerial applicators”) fly over farm fields all the time (to spray pesticides.)

They found that there are ~1,400 of these aerial applicator businesses in the U.S. with ~2,800 planes covering farms in 44 states. Ashwin said their big “aha moment” was when they realized that they could use these crop dusting planes to mount their hyperspectral cameras on. This is a big idea. They didn’t need drones at all.

If you can’t see the video above click here

Local crop dusters meant they could hire existing planes and simply attach their Hyper-spectral camera to any crop dusting plane. This meant that Ceres didn’t need to build an aerial infrastructure – it already existed. All of sudden what was an additional engineering and development effort now became a small, variable cost. As a bonus it meant the 1,400 aerial applicator companies could be a potential distribution channel partner.

Local Crop Dusters

The Ceres Imaging Minimum Viable Product was now an imaging system on a cropdusting plane generating data for high value Tree Crops. Their proprietary value proposition wasn’t the plane or camera, but the specialized algorithms to accurately monitor water and fertilizer. Brilliant.

logo

I asked Ashwin how they figured all this out. His reply, “You taught us that there were no facts inside our building.  So we’ve learned to live with our customers.  We’re now piloting our application with Tree Farmers in California and working with crop specialists at U.C. Davis.  We think we have a real business.”

It was a fun coffee.

Lessons Learned

  • Build continuous customer discovery into your company DNA
  • An MVP eliminates parts of your business model that create complexity
  • Focus on what provides immediate value for Earlyvangelists
  • Add complexity (and additional value) later

Listen to the blog post here

Download the podcast here

What I Learned by Flipping the MOOC

Two of the hot topics in education in the last few years have been Massive Open Online Courses (MOOC’s) and the flipped classroom. I’ve been experimenting with both of them.

What I’ve learned (besides being able to use the word “pedagogy” in a sentence) is
1) assigning students lectures as homework doesn’t guarantee the students will watch them and 2) in a flipped classroom you can become hostage to the pedagogy.

Here’s the story of what we tried and what we learned.

MOOC’s – Massive Open Online Courses
A MOOC is a complicated name for a simple idea – an online course accessible to everyone over the web. I created my MOOC by serendipity. Learning how to optimize it in my classes has been a more deliberate and iterative process.

If you can’t see the video above click here

When my Lean LaunchPad class was adopted by the National Science Foundation, we taught our original classes to scientists scattered across the U.S.  We adopted WebEx, a web video conferencing tool, to hold our classes remotely. Just like my students at Stanford, these NSF teams got out of the building and spoke to 10-15 customers a week. Back in their weekly class, the scientists would present their results in front of their peers – in this case via Webex, as the teaching team gave them critiques and “guidance”. When their presentations were over, it was my turn. I lectured to these remote students about the next week’s objectives.

Is it Live or Is It a MOOC?
After the first NSF class held via videoconference, it dawned on me that since I wasn’t physically in front of the students, they wouldn’t know if my lecture was live or recorded.

Embracing the “too dumb to know it can’t be done,” I worked with a friend from Stanford, Sebastian Thrun and his startup Udacity, to put my Lean LaunchPad lectures online. Rather than just have me drone on as a talking head, I hired an animator to help make the lectures interesting, and the Udacity team had the insight to suggest I break up my lecture material into small, 2-4 minute segments that matched students’ attention spans.

If you can’t see the video above click here

Over a few months we developed the online lectures, then tried it as a stand-in for me on the NSF videoconferences, and found that because of the animations and graphics the students were more engaged than if I were teaching it in person. Ouch.

Now the NSF teams were learning from these online lectures instead of video conferenced lectures – but the online lectures were still being played during class time.

I wondered if we could be more efficient with our classroom time.

Flipping
Back at Stanford and Berkeley, I realized that I could use my newly created Lean LaunchPad MOOC and “flip” the classroom.  It sounded easy, I had read the theory:
1) A flipped classroom moves lectures traditionally taught in class, and assigns them as homework. Therefore my  students will all eagerly watch the videos and come to class ready to apply their knowledge, 2) this would eliminate the need for any lecture time in class.  And as a wonderful consequence, 3) I could now admit more teams to the class because we’d now have more time for teams to present.

So much for theory. I was wrong on all three counts.

Theory Versus Practice
After each class, we’d survey the students and combine it with a detailed instructor post mortem of lessons learned.  (An example from our UCSF Lean LaunchPad for Life Sciences Class is here.)

Here’s what we found when we flipped the classroom:

  • More than half the students weren’t watching the lectures at home.
  • Without an automated tool to take an attendance, I had no idea who was or wasn’t watching.
  • Without lectures, my teaching team and I felt like observers. Although we were commenting and critiquing on students presentations, the flipped classroom meant we were no longer in the front of the room.
  • No lectures meant no flexibility to cover advanced topics or real time ideas past the MOOC lecture material.

We decided we needed to fix these issues, one at a time.

  • In subsequent classes we reduced class size from ten teams to eight. This freed up time to get lecture and teaching time back in the classroom.
  • We manually took attendance of who watched our MOOC (later this year this will be an automated part of the LaunchPad Central software we use to manage the classes.)
  • To get the teaching team front and center, I required students to submit questions about material covered in the MOOC lecture they watched the previous evening. I selected the best questions and used them to open the class with a discussion. I cold-called on students to ensure they all had understood the material.
  • We developed advanced lectures which combined a summary of the MOOC material with new material such as lectures focused on domain specific perspectives. For example, in our UCSF Life Sciences class the four VC’s who taught the class with me developed advanced business model lectures for therapeutics, diagnostics, medical devices and digital health. (These advanced lectures are now on-line and available to everyone who teaches the class.)

The class, now taught as hybrid flipped classroom, looks like this: Lean LaunchPad Class Organization

There’s still more to do.

  • While we use LaunchPad Central to have the teams provide feedback to each other, knowledge sharing across the teams still needs to be deeper and more robust.
  • While we try to give students tutorials for how to do Customer Discovery we need a better way to integrate these into the short time in quarter/semester.
  • While we insist that an MVP is part of the class, we need a more rigorous process for building the MVP in parallel with Customer Discovery

Outcomes
Besides finding the right balance in a flipped classroom, a few other good things have come from these experiments. The Udacity lectures now have over 250,000 students. They are not only used in my classes but are also part of other educators’ classes, as well as being viewed by aspiring entrepreneurs as stand-alone tutorials.

My experiments in how to teach the Lean LaunchPad class have led to a 2 ½ day class for 75 educators a quarter (information here.) And we’ve found a pretty remarkable way to use the Lean LaunchPad to organize corporate innovation/incubator groups. (We opened source our teaching guide we use in the classes here.)Educator's Program cover

Lessons Learned

  • Creating engaging MOOC’s are hard
  • Confirming that students watched the MOOC’s is even harder
  • The Flipped classroom needs to be balanced with:
    • Student accountability
    • Instructor time in front of the class
    • Advanced lectures

Listen to the blog post here

Download the podcast here

Sometimes It Pays to be a Jerk

That he which hath no stomach to this fight,
Let him depart; his passport shall be made
William Shakespeare Henry V | Act 4, Scene 3

band of brothers

The concepts in my Lean LaunchPad curriculum can be taught in a variety of classes–as an introduction to entrepreneurship all the way to a graduate level “capstone class.”

I recently learned being tough when you select teams for a capstone class pays off for all involved.

Here’s why.

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Our Lean LaunchPad class requires student teams to get out of the building and talk to 10-15 customers a week while they’re building the product.  And they do this while they are talking a full load of other classes.  To say it’s a tough class is an understatement.  The class is designed for students who said they want  a hands-on experience in what it takes to build a startup – not just writing a business plan or listening to lectures.

The class syllabus has all kinds of “black box” warnings about how difficult the class is, the amount of time required, etc.

Yet every year about 20% of teams melt down and/or drop the class because some of the team members weren’t really committed to the class or found they’ve overcommitted.

This year that drop out rate went to zero when I ran an accidental “be a jerk” experiment.

Here Are the Rules
We set up the Lean LaunchPad class so that teams hit the ground running in the first class. Before students are admitted, they formed teams, applied as a team with a business model canvas, had homework and were expected to be presenting their business model canvas hypotheses on day one of the class. Our first class session is definitely not a “meet and greet”.  The syllabus is clear that attendance was mandatory for the first class.

This year, at one of the universities where I teach in the engineering school, our quarter was going to start right after the New Year.  Some of the teams had students from the business school, law school and education school whose start dates were a few days later.

To remind everyone that attendance at the first class was required, we sent out an email to all the teams in December. We explained why attendance at the first class was essential and reminded them they agreed to be there when they were admitted to the class. The email let them know if they missed the first class, they weren’t going to be allowed to register.  And since teams required 4 members, unless their team found a replacement by the first week, the team would not be allowed to register either. (We made broad exceptions for family emergencies, events and a few creative excuses.)

I had assumed everyone had read the syllabus and had planned to be back in time for class.

Then the excuses started rolling in.

Be A Jerk
About 25% of the teams had team members who had purposely planned to miss the first class.  Most of the excuses were, “I thought I could make it up later.”

In past years I would have said, “sure.”  This year I decided to be a jerk.

I had a hypothesis that showing up for the first class might be a good indicator of commitment when the class got tough later in the quarter.  So this time, unless I heard a valid excuse for an absence I said, “too bad, you’ve dropped the class.”

You could hear the screaming around the world (this is in a school where the grading curve goes from A to A+.)  The best was an email from a postdoc who said “all his other professors had been accommodating his “flexible” schedule his entire time at the school and he expected I would be as well.“  Others complained that they had paid for plane tickets and it would cost them money to change, etc.

I stuck to my guns – pointing out that they had signed up for the class knowing this was the deal.

Half the students who said they couldn’t make it magically found a way to show up.  The others dropped the class.

The results of the experiment?  Instead of the typical 20% drop out rate during the quarter none left – 0.

We had a team of committed and passionate students who wanted to be in the class.  Everyone else failed the “I’m committed to making this happen” test.

Lessons Learned

  • Commitment is the first step in building a startup team.
  • It washes out the others
  • Setting a high bar saves a ton of grief later

Listen to the blog post here

Download the podcast here

Time For Founders School

Having a film crew in your living room for two days is something you want to put on your bucket list.

photo 2

photo 3-1

With a ~$2 billion endowment the Kauffman Foundation is the largest non-profit focused on entrepreneurship in the world. Giving away $80 million to every year (~$25 million to entrepreneurial causes) makes Kauffman the dominant player in the entrepreneurship space.

Kauffman just launched Founders School - a new education series to help entrepreneurs develop their businesses during the startup stage by highlighting how startups are different from big companies. After weeks honing the script and days of filming, I’m honored to present the “Startups” section of Founders School.

And I’m in good company – also in the series is Noam Wasserman of Harvard teaching Founder’s Dilemmas, Craig Wortmann University of Chicago covering Entrepreneurial Selling, Peter McDermott helping understand Intellectual Property, and Nathan Gold offering how to give Powerful Presentations.

These videos are not only great tutorials for founders but also provide educators another source of well produced and curated resources.

These “Startup” videos are a great general purpose companion to my “How to Build a Startup” lectures on Udacity.

And you get a tour of my living room…

Startups” introduction is here

Module 1, What We Know About Startups

  • 0:17: A Startup is not a smaller version of a large company
  • 0:45: The definition of a startup
  • 1:53: Types of Startups
  • 2:18: Startups in an Existing Market
  • 3:10: Startups in a New Market
  • 4:31: Startups in a Resegmented Market
  • 5:28: Startups in a Clone Market

Module 2, Startups Versus Big Companies

  • 0:43: Business Plans versus Business Models
  • 1:46: The Differences: Accounting, Engineering & Sales
  • 2:21: Accounting Metrics in a Large Company vs. Metrics that Matter in a Startup
  • 3:35: Job Titles in a Large Company can Sink a Startup
  • 6:07: Engineering: Waterfall Development in a Large Company vs. Minimum Viable Product in a Startup

Module 3, The Lean Method

  • 0:50: There are No Facts Inside Your Building — Get Outside
  • 1:28: Using the Business Model Canvas
  • 1:49: Use Customer Development to Test Your Hypotheses
  • 2:44: What is a Pivot?
  • 4:24: No Business Plan Survives First Contact with Customers

Module 4, Building Your Startup

  • 0:41: Don’t outsource Customer Discovery
  • 1:33: How to build your startup
  • 2:48: How to building your team
  • 3:15: Look for overlapping skill sets and complementary temperaments

Module 5, Pivot or Proceed, How to Decide

  • 0:33: Is there Product-Market Fit?
  • 1:00: Most startups fail
  • 1:20: Adopt a mindset of learning
  • 1:27: Proceed, pivot or restart

The second half of the “Startups” series is coming in March.

Go watch Founders School now.

Listen to the blog post here

Download the podcast here

Engineering a Regional Tech Cluster-part 3 of 3 of Bigger in Bend

Dino Vendetti a VC at Bay Partners, moved up to Bend, Oregon on a mission to engineer Bend into a regional technology cluster.  Over the years Dino and I brainstormed about how Lean entrepreneurship would affect regional development.

I visited Bend last year and caught up with his progress.

Today with every city, state, country trying to build out a technology cluster, following Dino’s progress can provide others with a roadmap of what’s worked and didn’t.

Here’s Part 3 of Dino’s story…


As a transplanted Silicon Valley VC and now a regional investor, I often get asked, “How do we go about building up our local tech ecosystem?”

The short answer is, “One step at a time.”

In the beginning in Bend, “necessity was the mother of invention.” Local entrepreneurs just made it up as they went. But today we are intentionally engineering six distinct activities to support this tech cluster: entrepreneurial density, university, transportation, capital, accelerator, and business community.

Let’s look at each of these six elements in more detail and I’ll explain what we have been doing in Bend to accelerate each of these.

1. Entrepreneurial Density:
Density – the connection of like-minded firms and their support services – is a critical component of a cluster. The most fertile source of entrepreneurs is the population of existing entrepreneurial companies. But for clusters without sufficient firms you first need to attract companies to your region. However, it’s difficult to create density overnight. Entrepreneurs need to understand and believe the reasons why they should want to cluster in your region given there are other alternatives (nationally Silicon Valley or New York; regionally Seattle and Bellevue, Portland and Bend).

In addition to technical and entrepreneurial talent, a region also needs experienced executive talent with industry appropriate backgrounds and personal networks. The goal of this talent is to help mentor startups as they scale and navigate the myriad of issues they will face in growing their business.

Bend’s economic development agency (EDCO) and city leaders (Visit Bend, City of Bend) get it – and have started communicating that Bend welcomes and is friendly to entrepreneurs and startups. Word is spreading and there are lots of people up and down the West Coast who know of and have been to Bend. But it’s easy to get drowned out by the noise from Silicon Valley and other cities in Washington and Oregon. That means that in regional communities like Bend, everyone needs to turn up the volume to consistently sing praises that will not only put the community on the map but also ensure it doesn’t slip.

2. University
Almost every successful tech cluster has a local technical university. This provides a source of technical talent, research, etc. It’s extremely difficult to import enough talent to fuel a rapidly growing tech cluster, so a university is critical to organically generate and retain talent within the region. In particular it’s critical to offer technical degrees that train the talent pool needed to drive the local tech cluster

OSU-Cascades is a new four-year university in Bend that is beginning the build out of its new campus in Bend and offer computer science and user design courses. This effort was over a decade in the making and something that the local community fought hard for.

3. Transportation
Direct flights to the San Francisco Bay Area and other major metro areas (depending on location of the region) are vital to reduce the friction of conducting business, encourage talent to test drive your community, and attract investors and other ecosystem partners to the region.

Bend’s economic development agency (EDCO) has worked very hard to establish direct flights to major West Coast cities including San Francisco, Los Angeles, Seattle, Portland, and Denver. At times this required rallying local business leaders to make advance purchases of flights to ensure enough passenger volume for the airlines.

4. Local Early-Stage Risk Capital
Early stage venture funds are more important than your mother. If this doesn’t exist your regional cluster is dead-on-arrival.  Organize risk-capital in the form of angel funds or venture funds, particularly at the early stage where the largest capital gap exists. This should be a strategic initiative within your state to close the capital gap with in-region capital sources.

Bend is now home to Seven Peaks Ventures and Cascade Angels, both born over the past year in response to the opportunity in the region. The state of Oregon is also making funds available to invest in and support the formation of venture funds within the state.

bvc-winner

Bend Venture Conference Winner

5. Local Entrepreneurial Community Entrepreneurial-driven Events
The local entrepreneurial community has been active in running Startup Weekends, launching the FoundersPad accelerator, running hackathons and Ruby on Rails conferences (Ruby on Ales), building out shared tech space, offering incentives (The Big Bend Theory) for startups to relocate to Bend from the Valley, and building up the state’s largest tech/venture conference, the Bend Venture Conference which is now going on its 11th year. There are many more efforts underway to build upon what has worked and continue the process of evolving and learning.

6. Business Community Support
One of the most difficult things to do is technically the easiest – a dispassionate self-assessment to understand what assets your community has and what you lack.

First, what is your value proposition to a family or business to locate in your region? Recognize that a big part of your job is to remove friction, drive awareness, and amplify the efforts of your local entrepreneurs. Successful entrepreneurs attract other entrepreneurs, so it’s vital to kick start the cycle.

Next, identify your goal. Is it creating a job works program? Stopping brain drain in the region? Attracting and building some key core competency in the region? Ideally your existing talent base and ecosystem naturally support the “core competency magnet” you want to develop.

Finally, put your money where your mouth is – help fund the events and programs in the early years. Once the tech cluster forms, these activities will become self-funding. The ROI won’t be obvious for some early on, but will pay dividends in time.

Regional Cluster Ecosystem

Regional Cluster Ecosystem

Summary: Bend Is a Global Entrepreneurship Experiment
There are about 25,000 economic development agencies in regional markets across the U.S., all trying to expand the number of businesses that create products and services sold outside their region. These regional businesses create primary jobs that lead to the creation of local secondary jobs.

The Bend experiment is a model to consciously engineer an entrepreneurial cluster in a regional market to spur economic development and job creation.

In the past most regional growth strategies have focused on attracting established companies looking to expand or open a new plant. While it may be strategic for the region to recruit some of these established businesses, those deals usually involve huge tax subsidies and typically create a small finite number of jobs. What isn’t part of most regional growth plans is the organic growth of an entrepreneurial tech cluster in the region. If successful, sewing the seeds of entrepreneurship can lead to a more rapid and sustainable job growth for the region.

By engineering a regional tech cluster, we can impact the trajectory of growth in the region and:

  • Slow and even reverse the historical migration of tech talent and capital out of the region/state
  • Locally grow successful tech companies to become amazing primary job creators
  • Recycle the wealth that is created by re-investing in the region versus transferring wealth to Silicon Valley
  • Help local successful entrepreneurial and technical talent stay local – by creating their next startup in the region versus emigrating to Silicon Valley
  • Create a more diversified and healthy economic base that includes tech entrepreneurs

The democratization of entrepreneurship has created a huge opportunity for any region with the right characteristics to create its own sustainable tech cluster. But, as with any true democracy, it won’t happen without the combined participation of the community and desire of entrepreneurs to lead the movement. This is happening in Bend, and I look forward to hearing from others about your own experiments.

Lessons Learned:

  • Regional tech clusters can be engineered if …
    • the region has key attributes and a focused effort from the entrepreneurial and business community
  •  Opportunity exists for economic development in regions where tech clusters can be formed
    • potential to dramatically increase the growth of entrepreneurship and job creation in the region.
  • Entrepreneurs are the path to job creation and growth…
    • attract them, reduce the friction to growth, and do everything possible to cause the wealth created to recycle locally

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