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.


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

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

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.


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.

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

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.


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


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