As our Lean LaunchPad for Life Sciences class winds down, a good number of the 26 teams are trying to figure out whether they should go forward to turn their class project into a business.
Given that we’ve been emphasizing Evidence-based entrepreneurship and the Investment Readiness Level, I guess I shouldn’t have been surprised when someone asked, “After we figure all this data out, should we pursue our idea based on the numbers?”
I pointed out that the “data” you gather in 10 weeks (talking to 100+ customers, partners, payers, etc.,) are not the first thing you should look at. There are three more important things you should worry about.
Now that you’ve gotten to know your potential channel and customers, regardless of how much money you’re going to make, will you enjoy working with these customers for the next 3 or 4 years?
One of the largest mistakes in my career was getting this wrong. I used to be in startups where I was dealing with engineers designing our microprocessors or selling supercomputers to research scientists solving really interesting technical problems. But in my next to last company, I got into the video game business.
My customers were 14-year old boys. (see 1:30 in the video) I hated them. It was a lifelong lesson that taught me to never start a business where you hate your customers. It never goes well. You don’t want to talk to them. You don’t want to do Customer Development with them. You just want them to go away. And in my case they did – they didn’t buy anything.
So you and your team need to feel comfortable being in this business with these customers.
2. Is this a scalable business? And if not, are you Ok with something small?
Is it a lifestyle business while you’re keeping your other job? Is it a small business that hits $4 million in revenue in four years and $8 million in ten years? Or is it something that can grow to a size that will result in an acquisition or some liquidity event?
You need to decide what your personal goal is and how it matches what you think this business can grow into. And you and your cofounders need to have that discussion to make sure that all the co-founders’ interests are aligned – before you make any decision to start the company. If one of you are happy making $500K/year and the other has visions of selling the company to Roche for a billion dollars, you have very different goals. Without clear alignment, one or both of you will be really unhappy later when you try to make decisions.
3. If I Didn’t Make Any Money After 4 Years, Did I Still Have A Great Time?
If your company fails, would you still say you had one hell of a ride? Founders don’t do startups because they’re searching for a huge financial windfall. They do it because it’s the greatest invention they can imagine. Most of the time you will fail. So if you’re not going to have a great time with your team and learn and build something you are truly excited about – don’t do it.
We talk a lot about Customer Development, but there’s nothing like seeing it in action to understand its power. Here’s what happened when an extraordinary Digital Health team gained several critical insights about their business model. The first was reducing what they thought was a five-sided market to a simpler two-sided one.
But the big payoff came when their discussions with medical device customers revealed an entirely new way to think about pricing —potentially tripling their revenue.
We’re into week 9 of teaching a Lean LaunchPad class for Life Sciences and Health Care (therapeutics, diagnostics, devices and digital health) at UCSF teaching with a team of veteran venture capitalists. The class has talked to ~2,200 customers to date. (Our final – not to be missed – Lessons Learned presentations are coming up December 10th.)
Among the 28 startups in the Digital Health cohort is Tidepool. They began the class believing they were selling an open data and software platform for people with Type 1 Diabetes into a multi-sided market comprised of patients, providers, device makers, app builders and researchers.
The Tidepool team members are:
Aaron Neinstein MD Assistant Professor of Clinical Medicine, Endocrinology and Assistant Director of Informatics at UCSF. He’s an expert in the intersection between technological innovations and system improvement in healthcare. His goal is to make health information easier to access and understand.
Howard Look, CEO of Tidepool, was VP of Software and User Experience at TiVo. He was also VP of Software at Pixar, developing Pixar’s film-making system, and at Amazon where he ran a cloud services project. At Linden Lab, delivered the open-sourced Second Life Viewer 2.0 project. His teenage daughter has Type 1 diabetes.
Brandon Arbiter was a VP at FreshDirect where he built the company’s data management and analytics practices. He was diagnosed at age 27 with Type 1 Diabetes. He developed a new generation diabetes app, “nutshell,” that gives patients the information they need to make the right decisions about their dosing strategies.
Kent Quirk was director of engineering at Playdom and director of engineering at Linden Labs.
A Five-sided Market In Week 1 the Tidepool team diagramed its customer segment relationships like this:
Using the business model canvas they started with their value proposition hypotheses, articulating the products and services they offered for each of the five customer segments. Then they summarized what they thought would be the gain creators and pain relievers for each of these segments.
Next, they then did the same for the Customer Segment portion of the canvas. They listed the Customer Jobs to be done and the Pains and Gains they believed their Value Proposition would solve for each of their five customer segments.
It’s Much Simpler Having a multisided market with five segments is a pretty complicated business model. In some industries such as medical devices its just a fact of life. But after talking to dozens of customers by week 3, Tidepool discovered that in fact they had a much simpler business model – it was a two-sided market.
They discovered that the only thing that mattered in the first year or two of their business was building the patient-device maker relationship. Everything else was secondary. This dramatically simplified their value proposition and customer segment canvas.
So they came up with a New Week 3 Value Proposition Canvas:
And that simplified their New Week 3 Customer Segment Canvas
Cost-based Pricing versus Value-based Pricing While simplifying their customer segments was a pretty big payoff for 3 weeks into the class, the best was yet to come.
As part of the revenue streams portion of the business model canvas, each team has to diagram the payment flows.
The Tidepool team originally believed they were going charge their device partners “market prices” for access to their platform. They estimated their Average Revenue per User (ARPU) would be about $36 per year.
But by week 6 they had spoken to over 70 patients and device makers. And what they found raised their average revenue per user from $36 to $90.
When talking to device makers they learned how the device makers get, keep and grow their customers. And they discovered that:
device makers own customers would stay their customers for 10 years (i.e. the Customer Life Time (CLT))
and the Life Time Value (LTV) of one customer over those 10 years to a device maker is $10,000
These customer conversations led the Tidepool team to further refine their understanding of the device makers’ economics. They found out that the device makers sales and marketing teams were both spending money to acquire customers. ($500 per sales rep per device + $800 marketing discounts offered to competitors’ customers.)
Once they understood their device customers’ economics, they realized they could help these device companies reduce their marketing spend by moving some of those dollars to Tidepool. And they realized that the use of the Tidepool software could reduce the device companies’ customer churn rate by at least 1%.
This meant that Tidepool could price their product based on the $1,800 they were going to save their medical device customers. Read the previous sentence again. This is a really big idea.
The Tidepool team went from cost-based pricing to value-based pricing. Raising their average revenue per user from $36 to $90.
There is no possible way that any team, regardless of how smart they are could figure this out from inside their building.
If you want to understand how Customer Discovery works and what it can do in the hands of a smart team, watch the video below. The team ruthlessly dissects their learning and builds value-pricing from what they learned.
This short video is a classic in Customer Discovery.
Investors sitting through Incubator or Accelerator demo days have three metrics to judge fledgling startups – 1) great looking product demos, 2) compelling PowerPoint slides, and 3) a world-class team.
We think we can do better.
We now have the tools, technology and data to take incubators and accelerators to the next level. Teams can prove their competence and validate their ideas by showing investors evidencethat there’s a repeatable and scalable business model. And we can offer investors metrics to play Moneyball – with the Investment Readiness Level.
We’ve spent the last 3 years building a methodology, classes, an accelerator and software tools and we’ve tested them on ~500 startups teams.
A Lean Startup methodologyoffers entrepreneurs a framework to focus on what’s important: Business Model Discovery. Teams use the Lean Startup toolkit: the Business Model Canvas + Customer Development process + Agile Engineering. These three tools allow startups to focus on the parts of an early stage venture that matter the most: the product, product/market fit, customer acquisition, revenue and cost model, channels and partners.
An Evidence-based Curriculum (currently taught in the Lean LaunchPad classes and NSF Innovation Corps accelerator). In it we emphasize that a) the data needed exists outside the building, b) teams use the scientific method of hypothesis testing c) teams keep a continual weekly cadence of:
Hypothesis – Here’s What We Thought
Experiments – Here’s What We Did
Data – Here’s What We Learned
Insights and Action – Here’s What We Are Going to Do Next
LaunchPad Central software is used to track the business model canvas and customer discovery progress of each team. We can see each teams hypotheses, look at the experiments they’re running to test the hypotheses, see their customer interviews, analyze the data and watch as they iterate and pivot.
We focus on evidence and trajectory across the business model. Flashy demo days are great theater, but it’s not clear there’s a correlation between giving a great PowerPoint presentation and a two minute demo and building a successful business model. Rather than a product demo – we believe in a “Learning Demo”. We’ve found that “Lessons Learned” day showing what the teams learned along with the “metrics that matter” is a better fit than a Demo Day.
“Lessons Learned” day allows us to directly assess the ability of the team to learn, pivot and move forward. Based on the “lessons learned” we generate an Investment Readiness Level metric that we can use as part of our “go” or “no-go” decision for funding.
NASA and the Technology Readiness Level (TRL) In the 1970’s/80’s NASA needed a common way to describe the maturity and state of flight readiness of their technology projects. They invented a 9-step description of how ready a technology project was. They then mapped those 9-levels to a thermometer.
What’s important to note is that the TRL is imperfect. It’s subjective. It’s incomplete. But it’s a major leap over what was being used before. Before there was no common language to compare projects.
The TRL solved a huge problem – it was a simple and visual way to share a common understanding of technology status. The U.S. Air Force, then the Army and then the entire U.S. Department of Defense along with the European Space Agency (ESA) all have adopted the TRL to manage their complex projects. As simple as it is, the TRL is used to manage funding and go/no decisions for complex programs worldwide.
We propose we can do the same for new ventures – provide a simple and visual way to share a common understanding of startup readiness status. We call this the Investment Readiness Level .
The Investment Readiness Level (IRL) The collective wisdom of venture investors (including angel investors, and venture capitalists) over the past decades has been mostly subjective. Investment decisions made on the basis of “awesome presentation”, “the demo blew us away”, or “great team” is used to measure startups. These are 20th century relics of the lack of data available from each team and the lack of comparative data across a cohort and portfolio.
We collect this data into a Leaderboard (shown in the figure below) giving the incubator/accelerator manager a single dashboard to see the collective progress of the cohort. Metrics visible at a glance are number of customer interviews in the current week as well as aggregate interviews, hypotheses to test, invalidated hypotheses, mentor and instructor engagements. This data gives a feel for the evidence and trajectory of the cohort as a whole and a top-level of view of each teams progress.
Next, we have each team update their Business Model Canvas weekly based on the 10+ customer interviews they’ve completed.
The canvas updates are driven by the 10+ customer interviews a week each team is doing. Teams document each and every customer interaction in a Discovery Narrative. These interactions provide feedback and validate or invalidate each hypothesis.
Underlying the canvas is an Activity Map which shows the hypotheses tested and which have been validated or invalidated.
All this data is rolled into a Scorecard, essentially a Kanban board which allows the teams to visualize the work to do, the work in progress and the work done for all nine business model canvas components.
Finally the software rolls all the data into an Investment Readiness Level score.
MoneyBall At first glance this process seems ludicrous. Startup success is all about the team. Or the founder, or the product, or the market – no metrics can measure those intangibles.
Baseball used to believe that as well. Until 2002 – when the Oakland A’s’ baseball team took advantage of analytical metrics of player performance to field a team that competed successfully against much richer competitors.
Statistical analysis demonstrated that on-base percentage and slugging percentage were better indicators of offensive success, and the A’s became convinced that these qualities were cheaper to obtain on the open market than more historically valued qualities such as speed and contact. These observations often flew in the face of conventional baseball wisdom and the beliefs of many baseball scouts and executives.
By re-evaluating the strategies that produce wins on the field, the 2002 Oakland A’s spent $41 million in salary, and were competitive with the New York Yankees, who spent $125 million.
Our contention is that the Lean Startup + Evidence based Entrepreneurship + LaunchPad Central Software now allows incubators and accelerators to have a robust and consistent data set across teams. While it doesn’t eliminate great investor judgement, pattern recognitions skills and mentoring – it does provide them the option to play Moneyball.
When scientists and engineers who’ve been working in the lab for years try to commercialize their technology they often get trapped by their own beliefs - including who the customers are, what features are important, pricing etc.
One the key tenets of the Lean LaunchPad class is that every week each team gets out of the building and talks to 10+ customers/partners to validate a new part of their business model. Back in class they present their findings to their peers and teaching team in a 10 minute Lessons Learned presentation. One of the benefits of the class is that the teams get immediate unvarnished feedback on their strategy.
For researchers and clinicians who’ve been working on a project in the lab for years, getting out of the building and talking to customers at times creates cognitive dissonance. While they’ve been in the lab they had a target customer in mind. However when they leave the building and start talking to these supposed customers there’s almost always a surprise when the customer is not interested in the product.
Often when they consistently hear that their expected customers aren’t interested the first reaction is “the customers just don’t get it yet.” Rather than testing a new customer segment they keep on calling on the same group – somehow thinking that “we just need to explain it better.”
Some times it takes a nudge from the teaching team to suggest that perhaps looking at another customer segment might be in order.
They Should be Our Customers The Mira Medicine Team is trying to accelerate the path to the right treatment for each patient in complex Central Nervous System diseases. They spent years building their first tool MS Bioscreen, which was developed for the physicians at the UCSF Dept of Neurology. So they naturally believed that their first customers would be neurologists.
This was a very smart team who ran into the same problem almost every smart researcher attempting to commercialize science faces. Here’s what happened.
This post is an update of what we learned about life science distribution channels.
Life Science/Health Care distribution channels differ by Category It turns out that for commercialization, the business model (Customers, Channel, Revenue Model, etc.) for therapeutics, diagnostics, devices, bioinformatics and digital health have very little in common.
This weeks topic was distribution channels; how your product gets from your company to your potential customer segments. You can get a feel for how each of the cohorts address the channel by looking at the distribution channel lectures below – covering the therapeutics, diagnostics, devices and digital health cohorts.
At the end of the lectures you can see a “compare and contrast” video and a summary of the differences in distribution channels.
Week 3 Todd Morrill Instructor
If you can’t see the presentation above click here
Week 3 Abhas Gupta Instructor
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Week 3 Allan May Instructor
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Week 3 Karl Handelsman Instructor
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Life Science and Health Care Differences in Distribution Channels This weeks lecture and panel was on distribution channels; how your product gets from your company to your potential customer segments. Therapeutics, diagnostics, devices and digital health use different different channels, in the video and the summary that follows the instructors compare and contrast how they differ.
Medical Device Distribution Channels in general are a sales team hired directly by the company.
A sales team typically includes a sales person and clinical applications specialists.
The specialists help train and educate physician users. They assist with the sale and work with marketing to create demand.
Some device industries are controlled by distributors (indirect sales.)
Distributors tend to resell commodity products from multiple suppliers.
Channel Cost = $350-400,000 per sales team. On average there’s 1 clinical applications specialist to 2 salespeople. A lean rollout for a startup would be 4-5 sales people plus 2-3 clinical applications specialists at a cost of ~$2.5 million/year
Increasing the number of sales people much past 4-5 for a rollout does not proportionally increase revenue in most cases, because you are on the front end of early adopters and wrestling to overcome and reduce the sales learning curve
Travel and Entertainment is a big part of the sales budget since they are all flying weekly to cover accounts
90-180 days for salespeople to become effective
Expect little or no revenue for 2- 3 quarters after they start
Major reason for failure = hiring sales and marketing staff too quickly
Generally an Educational Sale - Hire sales and clinical people first to help early adopters, such as Key Opinion Leaders (KOL’s), master the learning curve with your device so they can write and present papers to influence their peers
Diagnostics (Starting at 5:16)
Diagnostic Channels = Direct sales in the US, with limited Distributor options
Many Distributors in Europe and in Asia
Sold to hospital laboratories, reference laboratories, or performed in CLIA labs
Channel Cost = $350,000+ per supported salesperson
Direct to consumer is a (rapidly) growing channel
Digital Health (Starting at 7:25)
Digital Health Channels = Direct Sales but you’re selling software to both end users and enterprises
Can use existing tech channels and new emerging channels such as Wellness platforms. (Audax Health, Humana Vitality, ShapeUp, Redbrick Health, Limeade)
Cloud-based Electronic Medical Records (EMR) are quickly becoming another distribution platform
App Stores, and Box are also channels for consumers and enterprise customers, respectively
Therapeutics (Starting at 10:17)
Therapeutics Channel = what you’re selling in the early stage is data and Intellectual Property to the pharmaceutical and biotech companies
Complicated Sales process – takes 18 months
Led by the CEO with a dedicated business development person and your science team
You need to define the data they need – this is influenced by how they view their pipeline, and how your technology can fill gaps in their pipeline
Pharmaceutical and biotech companies have therapeutics heads, technology scouts and business development people all searching for technology deals to fill their pipeline
This is a bound problem – there’s probably 80 people you need to know that make up your channel
Each of these Life Science domains has a unique distribution channel
In Devices innovative products require hiring direct sales people
but for commodity device products you may use a distributor
Diagnostics requires a direct sales force in the U.S.
Distributors in Europe and in Asia
In Digital Health direct sales is a possible channel, as are traditional software channels (App Stores, Box, etc.)
other DHealth channels such as Wellness Platforms, and cloud-based EMR’s are also emerging
In therapeutics it’s a direct sale of data and Intellectual property
led by the CEO with a dedicated business development person and your science team
Vitruvian is one of the 28 teams in the class. The team members are:
Dr. Hobart Harris Chief of General Surgery, Vice-Chair of the Department of Surgery, and a Professor of Surgery at UCSF. Dr. Harris is also a Principal Investigator in the UCSF Surgical Research Laboratory at San Francisco General Hospital.
Dr. David Young, Professor of Plastic Surgery at UCSF. His area of expertise includes wound healing, microsurgery, and reconstruction after burns and trauma. His research interests include the molecular mechanisms of wound healing and the epidemiology and treatment of soft tissue infections.
Sarah Seegal is at One Medical Sarah is interested in increasing the quality and accessibility of healthcare services. Sarah worked with Breakthrough.com to connect individuals with professional therapists for online sessions.
Cindy Chang is a Enzymologist investigating novel enzymes involved in biofuel and chemical synthesis in microbes at LS9
Vitruvian’s first product, MyoSeal, promotes wound repair via biocompatible microparticles plus a fibrin tissue sealant that has been shown to prevent incisional hernias through enhanced wound healing. The team believed that surgeons would embrace the product and pay thousands to use it. In week 2 of the class 14 of their potential customers (surgeons) told the team otherwise.
Watch this 90 second clip and find out how the Lean LaunchPad class saved them years.
I can always tell when one of my students has been in the military. They’re focused, they’re world-wise past their years, and they don’t break a sweat in the fast pace and chaotic nature of the class and entrepreneurship. Todd Branchflower took my Lean LaunchPad class having been entrepreneurial enough to convince the Air Force send him to Stanford to get his graduate engineering degree.
True to his word, fast-forward three years and Todd is now Captain Todd Branchflower, teaching computer engineering at the Air Force Academy. He extended an invitation to me to come out to the Air Force Academy to address the cadets and meet the faculty. Besides the talk I brainstormed with Todd and other faculty on how to integrate the Lean LaunchPad into the Air Force Academy Capstone engineering class (a Capstone class puts together all the pieces that a students has learned in his or her major.)
Here’s Todd’s story of how we got there and progress to date.
Not That Long Ago In 2007, I graduated United States Air Force Academy as a computer engineer and entered the Air Force’s acquisition corps, excited and confident about my ability to bring technology to bear for our airmen.
Graduation day with classmate Joseph Helton (right), killed in action in Iraq in 2009
And I couldn’t have been put in a better place: testing the Air Force’s newest network security acquisitions. I was their technical man on the inside – making sure big defense contractors delivered on their promises. We were modernizing datacenters, buying vulnerability-scanning software, and adding intrusion detection appliances – all things typical of anyone running an enterprise-scale network..
I was in the thick of it – chairing telecons, tracking action items, and drafting test plans. I could recite requirements and concepts of operations from memory. I was jetsetting to team meetings and conferences across the country. I was busy.
Sure, I wasn’t working very closely with the airmen who were going to use the equipment. But they called into the weekly telecons, right? And they were the ones who had given the program office the requirements from the outset. (Well, their bosses had.) And I’d distilled those requirements into system characteristics we could measure. Well, more measurable versions of the original requirements. And meeting the requirements was the most important thing, right?
Doing it Wrong Here’s what I learned: I was doing it wrong. The way our process worked, customers were just a stakeholder that provided input – not drivers of the process. That meant that program offices were only accountable to a list of requirements, which were locked early. Success only consisted of passing tests against these requirements, not delighting our airmen. I began to wonder – how could we learn about user needs earlier? How could we deliver them solutions more quickly? More cheaply?
It was only after returning to Stanford and taking the Lean Launchpad class that I became convinced that a radically different, customer-centric approach was the solution. I returned to the Air Force Academy as an instructor in the Electrical and Computer Engineering Department, intent on spreading the gospel of Customer Development and Lean.
Our existing Capstone senior engineering design course followed the defense acquisition process; the focus of defense acquisition is to “nail down requirements” early and manage customer expectations to “avoid requirements creep”. I saw this as counter to the joint, iterative discovery process between entrepreneurs and customers I had experienced on my Lean Launchpad team.
I kept in touch with Steve as I started teaching. We discussed how the Lean Launchpad approach might find a place in our curriculum, and how it might be adapted to fit the unique Air Force Academy / military environment. We grew excited about how showing success here might prove a good model for how it could be done in the broader Air Force; how exposing future officers to the Lean philosophy might bring about change from within.
So when I invited Steve out to the Air Force Academy to speak last spring, there was more at stake than the talk. We set up a meeting with our department head, Col Jeff Butler, and Capstone course director, LtCol Charlie Gaona, to pitch the idea. They shared our enthusiasm about the impact it could have on our future design projects and how it might bring a change in perspective to our acquisition corps. They gave the go-ahead to send a pilot team through the program in the Fall semester, with the potential for it to be applied across the entire course if we delivered results.
I found a willing co-conspirator in Capt Ryan Silva, a star instructor who mentors a project named Neumimic, using technology to aid in the rehabilitation of patients with chronic loss of limb motion. In the first year, they had developed a proof of concept around the Xbox Kinect – and Ryan had high hopes for the future. But he found some elements of the traditional systems engineering process cumbersome and frustrating to cadets. Ryan signed on to lead our test class.
V-Model of Systems Engineering The current Capstone class follows the V-Model of Systems Engineering, with teams creating a detailed system design throughout the Fall semester and building their design in the Spring.
There are a series of formal reviews throughout the two semesters, in line with the Air Force acquisitions process. Requirements and a concept of operations are presented at the first, the System Requirements Review. Cadets receive instruction on the process in about a quarter of the course lessons.
What we decided to do instead was have semi-weekly informal reviews Lean Launchpad style, focusing on product hypotheses, customer interactions, learning, and validation / refinement. We emphasize customer interaction via “getting out of the building” and rapid iteration through “cheap hacks”. We’ve removed most of the structure and firm requirements from the original course in favor of a “whatever it takes” philosophy. Instruction is presented in tandem with the reviews, focusing on areas we see as problematic.
Last year’s team meeting with Dr. Glen House at Penrose-St. Francis Hospital
Back to the Present We’re about a quarter of the way through the fall semester. Team Neumimic consists of nine sharp cadets across multiple academic disciplines. Based on initial customer interactions, they divided themselves into two complementary but standalone teams. One will focus on design, execution, and measurement of therapy sessions – building on the original Xbox Kinect work. The other will work on adjustable restriction of patient motion – forcing patients to use the proper muscles for each movement.
Here’s Ryan on the impact of the process change:
“Last year the team found themselves handcuffed to a process that required a 100% design solution on paper before we could even think about touching hardware…crazy right?! We spent the entire first semester nailing down requirements for a system that was supposed to meet the needs of stroke and traumatic brain injury patients as prescribed by their occupational therapists. For five months we slogged our way through the process emerged with a complete design for our system, custom-built to meet the needs of patients and doctors alike. Our design was flawless. We had nuts-and-bolts details all the way down to the schematic level. We were ready to build! The fact that we had yet to even see a patient or spend any real time with an occupational therapist had not even registered to us as a problem, until we were invited to watch a therapy session.
Our entire team walked out of the hospital ashen-faced and silent. We knew we had just wasted half the course designing a system that wouldn’t work. We were back to square one. The remainder of the course was spent in a frenzy of phone calls with doctors and therapists paired with many design reviews, but this time with our customers in the room. We were able to iterate a few solutions before we ran out of time, but the customers were thrilled with what they saw. I could only imagine what we could have accomplished if we didn’t waste the first half of the course on a solution that ultimately wasn’t what the customers wanted. I was fired up when Todd approached me with his idea to fundamentally change the way we did business.
So far the results have been incredible compared to last year. The team has learned more about the problem in a month than last year’s team learned in an entire semester. I’m not saying this year’s cadets are any more capable than last year’s; just that I believe this year’s team has been given a better chance to succeed. They’re freed of a lot of stifling overhead and are embracing a process where requirements are derived from those who will actually use the system…imagine that! I’m excited to see what the team does with their remaining eight months.”
Current team members observing Dr. House conduct a therapy session
But we have experienced challenges in implementing this approach. Here’s what we’ve noticed so far:
In typical Lean Launchpad classes, students apply as teams with their own idea. There’s also the potential for teams to pursue the opportunity beyond the class if they’re successful. In our Capstone, projects are predetermined and cadets are assigned based on preference and skill set. Cadets will graduate and be commissioned as officers, doing various jobs throughout the Air Force. It’s highly unlikely they’ll be able to continue their project. These factors might make the initial motivation of our team less than that of other Lean Launchpad teams. We found that early interactions with customers excited about their work went a long way to remedy this.
We’re offering cadets much less structure than they’re used to. Some cadets are uncomfortable with the ambiguity of the requirements (“What are you looking for? What do I have to do to get an A?”). I’d imagine this is typical of most high-performing students.
We’re trusting cadets with more freedom and less oversight than they’re used to. There’s the potential for our trust to be abused. I’m hopeful that our cadets rise to this challenge. I think they’ll feel ownership of the project and empowerment, rather than see an opportunity to shirk responsibilities.
Since this course is a senior design experience, cadets expect to be “using their major”. There’s the tendency for some to sit on the sideline if the pressing work isn’t directly related to their area of expertise. It has taken some prodding for cadets to embrace the “hustler” mindset – to take any job necessary to move the team forward.
These are challenges we can overcome. I know we’re moving in the right direction. I know we have the right team and project to be successful. I know our cadets will make us proud.
Over the last three years our Lean LaunchPad / NSF Innovation Corps classes have been teaching hundreds of entrepreneurial teams a year how to build their startups by getting out of the building and testing their hypotheses behind their business model. While our teams have mentors, socialize a lot and give great demos, the goal of our class final presentations is “Lessons Learned” – about product/market fit, pricing, acquisition/activation costs, pricing, partners, etc. We think teaching teams a formal methodology around the Lean Framework (Business Model design, Customer Development and Agile Engineering) is a natural evolution of how successful incubators/accelerators will build startups.
Here’s the story of one such team; Jonathan Wylie, Lakshmi Shivalingaiah and the Evoke team.
Imagine if, in the course of ten rollercoaster weeks, your customer segment changed from executives on corporate campuses to moms on playgrounds, a tool that was just part of your product turned into the killer product, and the value of the problem you were solving went from number 47 to customers trying to give you money when you demo’d. Here’s how that happened.
We came to the Lean LaunchPad class wanting to build a mobile/web research management system aimed at helping qualitative researchers better manage the media they captured in the field. We were ready to learn, but pretty confident we would end the journey in the same market space in which we started. We had a killer team and all the right skillsets. I was a consultant and ethnographer, another teammate was a market researcher, and two others had the software engineering skills to build what the market needed. And what the market needed would, of course, be exactly what we had envisioned. After all, there must be a huge number of researchers struggling with the exact same problems we had, right? Not quite…
Out of the Building In the first 4 weeks, our team got out of the building and spoke with employees at 42 different companies. We spoke with people at all levels, from front line user experience researchers at large tech firms to the CMO of a fortune 500 consumer goods company. From the first 10 interviews, we learned that video is a big problem for researchers who use that medium. It takes an average of 4 hours to mine every hour of video for the relevant 10 seconds of insight that matters. Thus, we focused our early minimum viable product on helping researchers save money and time in finding insight in market research videos.
Wireframes We built wireframes as a Minimum Viable Product to elicit feedback and began showing them to customers during our interviews. At this point, things got real…and a bit ugly. Given something tangible, customers were able to start gauging their willingness to use and pay. Turns out, researchers were “just not that into us.” We heard consistently that the product looked good and solved a problem, but it was not an important problem. It was number 47 on their list, and there was no way they could justify paying to solve that problem.
First Pivot As disappointing as this was, we dug deeper with our questioning. To our surprise, customers started offering ideas on where there might be a true need; one of which was the legal market, specifically the deposition process. We thought this would be perfect for our product. There is a lot of video being recorded, and attorneys need to be able to pull out the insights quickly. After a solid week of speaking with lawyers and attending webinars on real-time deposition software, we had mapped both the technology and the buying relationships. What we learned was that, we would just be an incremental feature to the incumbents and would need to integrate our solution with theirs. This, combined with regulation from the courts, a 2-year sales cycle, and the realization that e-discovery groups are not early adopters, made this an unattractive market.
Technology in search of a market By this point, we were a technology in search of a market…not a good place to be. The next customer segment we tried was startup founders. After all, they are just like us – researching their markets and needing a way to share insights and keep their teams connected to customers. However, we found that most just assume that what they are building will have a market. The few who did get it felt uncomfortable using video during the interview process.
Pivot Two While at times we felt like we wanted to give up, we began to hear a positive signal in the noise of all the customer rejections. At first it was faint. While customers in all three markets were lukewarm for use at work, they got visibly excited telling us that it would definitely solve a problem at home. Say what?? They told us “too bad we weren’t making a consumer product so they could document their kids… they would pay a lot of money for that product.” Whoah…were customers telling us we are a consumer product rather than B-to-B??
We settled on a small-scale experiment to test the consumer market. We decided to speak with 10 parents over the course of a week. If 5 had a similar problem, we would dive deeper. What we got was a landslide of interest. All 10 parents had the problem. Even more amazing to us, 9 of them liked our solution!
We learned that parents capture moments with their families to:
remember and relive later
share with those closest to them
pass along a memoir to their kids
To our surprise, it turns out that none of these are being accomplished well with existing products, and parents are stressed because they feel like they are failing in an important responsibility.
Eureka! Since that initial experiment in class, we’ve validated these findings (and many others) during over 200 hour-long interviews.
We even partnered with the university on a 112-person design workshop to learn more about how photos and videos fit into people’s lives. It’s always an incredible experience to be invited into someone’s home to learn about how they capture their most precious family moments. Sometimes, the learning is immediate and conclusive. Other times, we have to do multiple rounds before we arrive at an answer to an important question.
The result of all this effort is that we have found a large and underserved market in hidden in plain sight, right in the middle of an area that gets a lot of attention – photos and videos!
Lessons Learned There’s no way we would have learned any of this unless we were out of the building and in the trenches, with parents over an extended period.
Knowing our customers and their problems first hand has given us a huge head start and a competitive advantage. Most entrepreneurs seem to just make this stuff up for a pitch deck or to please stakeholders, but the validated learning that we gained through these interviews and other methods of business model experimentation is not something that can be easily replicated.
As for our current status, we are building the product, continuing customer development, exploring and validating other aspects of our business model, and…oh yeah…hitting the pavement to raise our first round of funding! If you want to talk to us about that, or if you know parents that we should be speaking to, please feel free to reach out.
When I wrote Four Steps to the Epiphany and the Startup Owners Manual, I believed that Life Sciences startups didn’t need Customer Discovery. Heck how hard could it be? You invent a cure for cancer and then figure out where to put the bags of money. (In fact, for oncology, with a successful clinical trial, this is the case.)
In the real world a big pivot in life sciences far down the road of development is a very bad sign due to huge sunk costs. But pivoting early, before you raise and spend millions or tens of millions means potential disaster avoided.
Some of these pivots included changing their product/service once the team had a better of understanding of customer needs or changing their position in the value chain (became an OEM supplier to hospital suppliers rather than selling to doctors directly.) Other pivots involved moving from a platform technology to become a product supplier, moving from a therapeutic drug to a diagnostic or moving from a device that required a PMA to one that required a 510(k).
Some of these teams made even more radical changes. For example when one team found the right customer, they changed the core technology (the basis of their original idea!) used to serve those customers. Another team reordered their device’s feature set based on customer needs.
These findings convinced me that the class could transform how we thought about building life science startups. But there was one more piece of data that blew me away.
Control versus Experiment – 18% versus 60% For the last two and a half years, the teams that were part of the National Science Foundation Innovation Corps were those who wanted to learn how to commercialize their science, applied to join the program, fought to get in and went through a grueling three month program. Other scientists attempting to commercialize their science were free to pursue their startups without having to take the class.
Both of these groups, those who took the Innovation Corps class and those who didn’t, applied for government peer-reviewed funding through the SBIR program. The teams that skipped the class and pursued traditional methods of starting a company had an 18% success rate in receiving SBIR Phase I funding.
The teams that took the Lean Launchpad class – get ready for this – had a 60% success rate. And yes, while funding does not equal a successful company, it does mean these teams knew something about building a business the other teams did not.
The 3-person teams consisted of Principal Investigators (PI’s), mostly tenured professors (average age of 45,) whose NSF research the project was based on. The PI’s in turn selected one of their graduate students (average age of 30,) as the entrepreneurial lead. The PI and Entrepreneurial Lead were supported by a mentor (average age of 50,) with industry/startup experience.
This was most definitely not the hoodie and flip-flop crowd.
Obviously there’s lots of bias built into the data – those who volunteered might be the better teams, the peer reviewers might be selecting for what we taught, funding is no metric for successful science let alone successful companies, etc. – but the difference in funding success is over 300%.
The funding criteria for these new ventures wasn’t solely whether they had a innovative technology. It was whether the teams understood how to take that idea/invention/patent and transform it into a company. It was whether after meeting with partners and regulators, they had a plan to deal with the intensifying regulatory environment. It was whether after talking to manufacturing partners and clinicians, they understood how they were going to reduce technology risk. And It was after they talked to patients, providers and payers whether they understood the customer segments to reduce market risk by having found product/market fit.
Scientists and researchers have spent their careers testing hypotheses inside their labs. This class teaches them how to test the critical hypotheses that turn their idea into a business as they deal with the real world of regulation, customers and funding.
So after the team at UCSF said they’d like to prototype a class for Life Sciences, I agreed.
The goal of the Lean LaunchPad Life Sciences class at UCSF is to teach researchers how to move their technology from an academic lab into the commercial world.
We’re going to help teams:
assess regulatory risk before they design and build
gather data essential to customer purchases before doing the science
define clinical utility now, before spending millions of dollars
identify financing vehicles before you need them
We’ve segmented the class into four cohorts: therapeutics, diagnostics, devices and digital health. And we recruited a team of world class Venture Capitalists and entrepreneurs to teach and mentor the class including Alan May, Karl Handelsman, Abhas Gupta, and Todd Morrill.
The course is free to UCSF, Berkeley, and Stanford students; $100 for pre-revenue startups; and $300 for industry. – See more here
What if we could increase productivity and stave the capital flight by helping Life Sciences startups build their companies more efficiently?
We’re going to test this hypothesis by teaching a Lean LaunchPad class for Life Sciences and Healthcare (therapeutics, diagnostics, devices and digital health) this October at UCSF with a team of veteran venture capitalists.
In this three post series, Part 1 described the challenges Life Science companies face in Therapeutics and Diagnostics. This post describes the issues in Medical Devices and Digital Health. Part 3 will offer our hypothesis about how to change the dynamics of the Life Sciences industry with a different approach to commercialization of research and innovation. And why you ought to take this class.
Medical devices prevent, treat, mitigate, or cure disease by physical, mechanical, or thermal means (in contrast to drugs, which act on the body through pharmacological, metabolic or immunological means). They span they gamut from tongue depressors and bedpans to complex programmable pacemakers and laser surgical devices. They also diagnostic products, test kits, ultrasound products, x-ray machines and medical lasers.
Incremental advances are driven by the existing medical device companies, while truly innovative devices often come from doctors and academia. One would think that designing a medical device would be a simple engineering problem, and startups would be emerging right and left. The truth is that today it’s tough to get a medical device startup funded.
Class I devices are low risk and have the least regulatory controls. For example, dental floss, tongue depressors, arm slings, and hand-held surgical instruments are classified as Class I devices. Most Class I devices are exempt Premarket Notification 510(k) (see below.)
Class II devices are higher risk devices and have more regulations to prove the device’s safety and effectiveness. For example, condoms, x-ray systems, gas analyzers, pumps, and surgical drapes are classified as Class II devices.
Manufacturers introducing Class II medical devices must submit what’s called a 510(k) to the FDA. The 510(k) identifies your medical device and compares it to an existing medical device (which the FDA calls a “predicate” device) to demonstrate that your device is substantially equivalent and at least as safe and effective.
Class III devices are generally the highest risk devices and must be approved by the FDA before they are marketed. For example, implantable devices (devices made to replace/support or enhance part of your body) such as defibrillators, pacemakers, artificial hips, knees, and replacement heart valves are classified as Class III devices. Class III medical devices that are high risk or novel devices for which no “predicate device” exist require clinical trials of the medical device a PMA (Pre-Market Approval).
The FDA is tougher about approving innovative new medical devices. The number of 510(k)s being required to supply additional information has doubled in the last decade.
The number of PMA’s that have received a major deficiency letter has also doubled.
An FDA delay or clinical challenge is increasingly fatal to Life Science startups, where investors now choose to walk away rather than escalate the effort required to reach approval.
Business Model Issues
Cost pressures are unrelenting in every sector, with pressure on prices and margins continuing to increase.
Devices are a five-sided market: patient, physician, provider, payer and regulator. Startups need to understand all sides of the market long before they ever consider selling a product.
In the last decade, most device startups took their devices overseas for clinical trials and first getting EU versus FDA approval
Recently, the financing of innovation in medical devices has collapsed even further with most Class III devices simply unfundable.
Companies must pay a medical device excise tax of 2.3% on medical device revenues, regardless of profitability delays or cash-flow breakeven.
The U.S. government is the leading payer for most of health care, and under ObamaCare the government’s role in reimbursing for medical technology will increase. Yet two-thirds of all requests for reimbursement are denied today, and what gets reimbursed, for how much, and in what timeframe, are big unknowns for new device companies.
Venture Capital Issues
Early stage Venture Capital for medical device startups has dried up. The amount of capital being invested in new device companies is at an 11 year low.
Because device IPOs are rare, and M&A is much tougher, liquidity for investors is hard to find.
Exits have remained within about the same, while the cost and time to exit have doubled.
Life Sciences III – The Rise of Digital Health Over the last five years a series of applications that fall under the category of “Digital Health” has emerged. Examples of these applications include: remote patient monitoring, analytics/big data (aggregation and analysis of clinical, administrative or economic data), hospital administration (software tools to run a hospital), electronic health records (clinical data capture), and wellness (improve/monitor health of individuals). A good number of these applications are using Smartphones as their platform.
Business Model Issues
A good percentage of these startups are founded by teams with strong technical experience but without healthcare experience. Yet healthcare has its own unique regulatory and reimbursement issues and business model issues that must be understood
Most of these startups are in a multisided market, and many have the same five-sided complexity as medical devices: patient, physician, provider, payer and regulator. (Some are even more complex in an outpatient / nurse / physical therapy setting.)
Reimbursement for digital health interventions is still a work in progress
Some startups in this field are actually beginning with Customer Development while others struggle with the classic execution versus search problem
Digital Health covers a broad spectrum of products, unless the founders have domain experience startups in this area usually discover the FDA and the 510(k) process later than they should.
Seed funding is still scarce for Digital Health, but a number of startups (particularly those making physical personal heath tracking devices) are turning to crowdfunding.
Moreover, the absence of recent IPOs and public companies benchmarks creates uncertainty for VCs evaluating later investments too
Try Something New The fact that the status quo for Life Sciences is not working is not a new revelation. Lots of smart people are running experiments in search of ways to commercialize basic research more efficiently.
Universities have set up translational R&D centers; (basically university/company partnerships to commercialize research). The National Institute of Health (NIH) is also setting up translational centers through its NCATS program. Drug companies have tried to take research directly out of university labs by licensing patents, but once inside Pharma’s research labs, these projects get lost in the bureaucracy. Realizing that this is not optimal, drug companies are trying to incubate projects directly with universities and the researchers who invented the technology, such as the recent Janssen Labs program.
But while these are all great programs, they are likely to fail to deliver on their promise. The assumption that the pursuit of drugs, diagnostics, devices and digital health is all about the execution of the science is in most cases a mistake.
The gap between the development of intriguing but unproven innovations, and the investment to commercialize those innovations is characterized as “the Valley of Death.”
We believe we need a new model to attract private investment capital to fuel the commercialization of clinical solutions to todays major healthcare problems that is in many ways technology agnostic. We need a “Needs Driven/Business Model Driven” approach to solving the problems facing all the stakeholders in the vast healthcare system.
We believe we can reduce the technological, regulatory and market risks for early-stage life science and healthcare ventures, and we can do it by teaching founding teams how to build new ventures with Evidence-Based Entrepreneurship.
Part 3 in the next post will offer our hypothesis how to change the dynamics of the Life Sciences industry with a different approach to commercialization of research and innovation. And why you ought to take this class.
It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way.
Life Science (therapeutics- drugs to cure or manage diseases, diagnostics- tests and devices to find diseases, devices to cure and monitor diseases; and digital health –health care hardware, software and mobile devices and applications streamline and democratize the healthcare delivery system) is in the midst of a perfect storm of decreasing productivity, increasing regulation and the flight of venture capital.
But what if we could increase productivity and stave the capital flight by helping Life Sciences startups build their companies more efficiently?
It was the best of times and the worst of times The last 60 years has seen remarkable breakthroughs in what we know about the biology underlying diseases and the science and engineering of developing commercial drug development and medical devices that improve and save lives. Turning basic science discoveries into drugs and devices seemed to be occurring at an ever increasing rate.
Yet during those same 60 years, rather than decreasing, the cost of getting a new drug approved by the FDA has increased 80 fold. Yep, it cost 80 times more to get a successful drug developed and approved today than it did 60 years ago.
75% or more of all the funds needed by a Life Science startup will be spent on clinical trials and regulatory approval. Pharma companies are staggering under the costs. And medical device innovation in the U.S. has gone offshore primarily due to the toughened regulatory environment.
At the same time, Venture Capital, which had viewed therapeutics, diagnostics and medical devices as hot places to invest, is fleeing the field. In the last six years half the VC’s in the space have disappeared, unable to raise new funds, and the number of biotech and device startups getting first round financing has dropped by half. For exits, acquisitions are the rule and IPOs the exception.
While the time, expense and difficulty to exit has soared in Life Sciences, all three critical factors have been cut by orders of magnitude in other investment sectors such as internet or social-local-mobile. And while the vast majority of Life Science exits remain below $125M, other sectors have seen exit valuations soar. It has gotten so bad that pension funds and other institutional investors in venture capital funds have told these funds to stay away from Life Science – or at the least, early stage Life Science.
WTF is going on? And how can we change those numbers and reverse those trends?
We believe we have a small part of the answer. And we are going to run an experiment to test it this fall at UCSF.
In this three post series, the first two posts are a short summary of the complex challenges Life Science companies face; in Therapeutics and Diagnostics in this post and in Medical Devices and Digital Health in Part 2. Part 3 explains our hypothesis about how to change the dynamics of the Life Sciences industry with a different approach to commercialization of research and innovation. And why you ought to take this class.
Life Sciences I—Therapeutics and Diagnostics
It was the Age of Wisdom – Drug Discovery There are two types of drugs. The first, called small molecules (also referred to as New Molecular Entities or NMEs), are the bases for classic drugs such as aspirin, statins or high blood pressure medicines. Small molecules are made by reactions between different organic and/or inorganic chemicals. In the last decade computers and synthesis methods in research laboratories enable chemists to test a series of reaction mixtures in parallel (with wet lab analyses still the gold standard.) Using high-throughput screening to search for small molecules, which can be a starting point (or lead compound) for a new drug, scientists can test thousands of candidate molecules against a database of millions in their libraries.
The second class of drugs created by biotechnology is called biologics (also referred to as New Biological Entities or NBEs.) In contrast to small molecule drugs that are chemically synthesized, most biologics are proteins, nucleic acids or cells and tissues. Biologics can be made from human, animal, or microorganisms – or produced by recombinant DNA technology. Examples of biologics include: vaccines, cell or gene therapies, therapeutic protein hormones, cytokines, tissue growth factors, and monoclonal antibodies.
It was the Season of Light The drug development pipeline for both small molecules and biologics can take 10-15 years and cost a billion dollars. The current process starts with testing thousands of compounds which will in the end, produce a single drug.
The problem is that the probability that a small molecule drug gets through clinical trials is unchanged after 50 years. In spite of the substantial scientific advances and increased investment, over the last 20 years the FDA has approved an average of 23 new drugs a year. (To be fair, this is indication-dependent. For example, in oncology, things have gotten significantly better. In most other areas, particularly drugs for the central nervous system and metabolism, they have not.)
It was the Season of Despair With the exception of targeted therapies, the science and tools haven’t made the drug discovery pipeline more efficient. Oops.
There are lots of reasons why this has happened.
Regulatory and Reimbursement Issues
Drug safety is a high priority for the FDA. To avoid problems like Vioxx, Bexxar etc., the regulatory barriers (i.e. proof of safety) are huge, expensive, and take lots of time. That means the FDA has gotten tougher, requiring more clinical trials, and the stack of regulatory paperwork has gotten higher.
Additional trials to demonstrate both clinical efficacy (if not superiority) and cost outcomes effectiveness are further driving up the cost, time and complexity of clinical trials.
In a perfect world the goal is to develop a drug that will go after a single target (a protein, enzyme, DNA/RNA, etc. that will undergo a specific interaction with chemicals or biological drugs) that is linked to a disease.
To get FDA approval new drugs have to be proven better than existing ones. Most of the low-hanging fruit of easy drugs to develop are already on the market.
Venture Capital Issues
For the last two decades, biotech venture capital and corporate R&D threw dollars into interesting science (find a new target, publish a paper in Science, Nature or Cell, get funded.) The belief was that once a new target was found, finding a drug was a technologyexecution problem. And all the new tools would accelerate the process. It often didn’t turn out that way, although there are important exceptions.
Moreover, the prospect of the FDA also evaluating drugs for their cost-effectiveness is adding another dimension of uncertainty as the market opportunity at the end of the funnel needs to be large enough to justify venture investment
In Part 2 of this series, we describe the challenges new Medical Device and Digital Health companies face. Part 3 will offer our hypothesis how to change the dynamics of the Life Sciences industry with a different approach to commercialization of research and innovation in this sector. And why you ought to take this class.
Listen to the post here
There is nothing more powerful than an idea whose time has come
The Lean LaunchPad entrepreneurship curriculum has caught fire. This week 100 educators from around the world will come to Stanford to learn how to teach it.
Life is full of unintended consequences.
Ten years ago I started thinking about why startups are different from existing companies. I wondered if business plans and 5-year forecasts were the right way to plan a startup. I asked, “Is execution all there is to starting a company?”
It dawned on me that the plans were a symptom of a larger problem: we were executing business plans when we should first be searching for business models. We were putting the plan before the planning.
So what would a search process for a business model look like? I read a ton of existing literature and came up with a formal methodology for search I called Customer Development. I wrote a book about this called the Four Steps to the Epiphany.
Teaching “Search versus Execution” In 2003 U.C. Berkeley asked me to teach a class in Customer Development at Haas business school. In 2004 I funded IMVU, a startup by Will Harvey and Eric Ries. As a condition of my investment I insisted Will and Eric take my class at Berkeley. Having Eric in the class was the best investment I ever made. Eric’s insight was that traditional product management and Waterfall development should be replaced by Agile Development. While I had said startups were “Searching” for a business model, I had been a bit vague about what exactly a business model looked like. For the last two decades there was no standard definition. That is until Alexander Osterwalder wrote Business Model Generation.
Finally we had a definition of what it was startups were searching for. Business model design + customer development + agile development is the process that startups use to search for a business model. It’s called the Lean Startup. The sum of these parts is now the cover story of the May 2013 Harvard Business Review. Bob Dorf and I wrote a book, The Startup Owners Manual that put all these pieces together.
But then I realized rather than just writing about it, or lecturing on Customer Development, we should have a hands-on experiential class. So my book and Berkeley class turned into the Lean LaunchPad class in the Stanford Engineering school. The class emphasizes experiential learning, a flipped classroom and immediate feedback as a way to engage students with real world entrepreneurship.
Students learn by proposing and immediately testing hypotheses. They get out of the classroom and talk to customers, partners and competitors and encounter the chaos and uncertainty of commercializing innovations and creating new ventures.
Then in July 2011, the National Science Foundation read my blog posts on the Lean LaunchPad class. They said scientists had already made a career out of hypotheses testing, and the Lean LaunchPad was simply a scientific method for entrepreneurship. They asked if I could adapt the class to teach scientists who want to commercialize their basic research. The result was the NSF Innovation Corps, my Lean LaunchPad class now taught at 11 major universities to 400 teams/year. ARPA-E joined the program this year, and in the fall we’ll teach a Life Science version of the class at UCSF. And other countries are adopting the class to commercialize their nations scientific output.
Unexpected Consequences One of the most surprising things that came out of the National Science Foundation classes was the reaction of the principal investigators (these were the tenured professors who leading their teams in commercializing their science.) A sizable number of them went back to their schools and asked, “How come we don’t offer this class to our students?”
While I had open-sourced all my lectures and put them online via Udacity, I was getting requests to teach other educators how teach the class. I wasn’t sure how to respond, until Jerry Engel, the National Faculty Director of the NSF Innovation Corps suggested we hold an educators class. So we did. The Lean LaunchPad Educators program is a 3-day program designed for experienced entrepreneurship faculty. It is a hands-on program where you experience the process, and be given the tools to create, a curriculum and course plan you can put to immediate use.
We offered the first class in August and had 50 attendees, the January class had 70, and the one being held this week we had to cap at 100.
As part of each of the classes we open source our educators guide here
Where are we in Entrepreneurial Education? Entrepreneurial education is in the middle of a major transition.
Entrepreneurship educators are realizing that curricula oriented around business plans and “execution” fail to prepare students for the realities of building or working in startups. Startups are a fundamentally a different activity than managing a business and “search versus execute” require very different skills. Therefore entrepreneurial education must teach how to search the uncertainties and unknowns.
Educators are now beginning to build curricula that embrace startup management tools built around “searching for a business model” rather than the “execution of a business model” tools needed in larger companies.
But we’re just beginning the transition. Like other revolutionary changes there are the early adopters and others who adopt later. For the Lean LaunchPad classes we’ve seen adoption fall into five categories:
Those who get how teaching students how to “search versus execute” changes our curriculum.
They say, “Here’s how we are going to add value to what you started.”
Those who get how teaching students how to “search versus execute” changes our curriculum.
They say, “We’re teaching the Lean Launchpad class as is. Thanks!”
Those who get that there is a major shift in entrepreneurial education occurring and we understand business model design + customer development + agile engineering is at it’s core
They say, “We are going to rename each of these components so we can take credit for them at our business school.”
Those who are not changing anything
They say, “We don’t buy it.”
Those who really don’t understand the key concepts but we need to be “buzzword compliant” to seem relevant
They say, “We’re throwing Lean on top of our “how to write a business plan” and other standard classes.”
The good news is that it’s the marketplace that will eventually drive all schools to adopt experiential classes that teach Lean principles. We’re incredibly proud of those educators who already have. There is nothing more powerful than an idea whose time has come
The next Lean LaunchPad Educators Class will be held in New York, September 25-27th. Info here.
We’ll also offer a version for incubators and accelerators in New York, September 22-24th. firstname.lastname@example.org
Entrepreneurial education is in the middle of a major transition
Transition from startups are a smaller version of a large company, teaching execution
To teaching that startups search for a business model
Business model design + customer development + agile development is the process that startups use to search for a business model
Lean LaunchPad is an experiential class that teaches students how to search
It’s part of a broader new entrepreneurial curriculum
We teach this in the Lean LaunchPad Educators Class
In a startup instead of paying consultants to tell you what they learned you want to pay them to teach you how to learn.
Roominate, one of my favorite Lean LaunchPad teams came out to the ranch last week for a strategy session. Alice and Bettina had taken an idea they had tested in the class – building toys for young girls to have fun with Science, Technology, Engineering, and Math, and started a company. The Roominate dollhouse building kits are being sold via their own website and soon, retail channels. They’ve shipped over 5,000 to enthusiastic parents and their daughters.
As soon as they had designed the product, they found a contract manufacturer to build the product in China. Alice and Bettina are hands-on mechanical and electrical engineers, so instead of assuming everything would go smoothly, they wisely got on a plane to Dongguan China and worked with the factory directly. They learned a ton.
But we were meeting to talk about sales and marketing. They outlined their retail channel and PR strategy and told me about the type of consultants they wanted to hire.
Hiring Channel Sales “So what would the retail channel consultant do?” I asked. Alice looked at me like I was a bit slow, but went on to describe how this consultant was going to take their product around to buyers inside major retail chains like Target, Toys R Us, Walmart, and others to see if they could get them to buy their product. “That sounds great.” I said, “When are you leaving for the trip?” They looked confused. “We’re not going on any of these calls. Our consultant is going and then he’s going to give us a report of how willing these stores are to carry our product.” Oh…
I said, “Let me see if I understand this correctly. What if a buyer asks, can you make a custom version of your product? Can your consultant answer that question on the spot? What if a buyer said no? Will your consultant know what questions to ask right then to figure out how to get them to yes?” I let this sink in and then offered, “Think about it for a minute. You’re going to pay someone else to learn and discover if your product fits this channel, and you’re are not going to do any of the learning yourself? You didn’t skip the trip learning how to manufacture the product. You got on a plane yourself and went to China. Why doesn’t this sound like the right thing to do for channel sales?” They thought about it for a moment and said, “Well we feel like we understand how to build things, but sales is something we thought we’d hire an expert to do.”
Hiring PR Agencies We had an almost identical conversation when the subject turned to hiring a Public Relations agency. Bettina said, “We want to drive customer demand into our channel.” That’s smart I thought, a real clear charter for PR. “What are they going to do for you?” I asked. “Well all the agencies we interview tell us they can survey our customers and come up with our positioning and then help us target the right blogs, influencers and press.
This felt like déjà vu all over again.
I took a deep breath and said, “Look this is just like the channel consultant conversation. But in this case it’s even clearer. Didn’t you get started by testing out every iteration with girls and watching firsthand what gets them excited? Don’t you have 5,000 existing customers? And haven’t you been telling me you’ve been talking to them continuously?” They nodded in agreement. I suggested, “Why don’t you guys take a first pass and draft a positioning brief with target messages, think through who you think the audiences are, and you take a first pass at who you think the press should be. The team looked at me incredulously. “You want us to do this? We don’t know the first thing about press, that’s why we want to hire the experts.” It was the answer I expected.
“Let me be clear,” I explained. “At this moment you know more about your customers than any PR agency will. You’ve spent the last six months testing positioning, messages, and talking to the press yourself. What I want you to do is spend an hour in a conference room and write up all you learned. What worked, what didn’t, etc. Then summarize it in a brief – a one, max two-page document that you hand to prospective PR agencies. And when you hand it to them say, “We know you can do better, but here’s what we’ve learned so far.”” They thought about it for a while and said, “We want to hire a PR agency so we don’t have to do this stuff. We’re too busy focusing on getting the product right.”
I pushed back, reminding them, “Look, half the agencies that see your brief are going to decline to work with you. They make most of their money doing the front-end work you already did. You do need to hire a PR agency, but I’m suggesting that you start by raising the bar on where they need to start.”
You Need to Do the Learning Thinking that founders hire domain experts to get them into places and do things they don’t have any clue about is a mistake most founding CEOs make. It’s wrong. If you plan to be the CEO who runs the company, you need these resources teaching you how to do it, not reporting their results to you. For Roominate I suggested that Alice and Bettina needed to try to find a channel consultant who would take them along on the sales calls and have the founders meet buyers directly. Why? Not to turn them into channel sales people but to hear customer objections unfiltered. To get data that they – and only they, not a consultant – could turn into insight about iterations and pivots about their business model. And to see how the process works directly.
A year from now when they will be hiring their first VP of Channel Sales, they want the interview to go something like, “Well we sold the first three channel partners ourselves – what can you do for us?”
The same is true for hiring the PR agency. The conversation should be, “Here’s what we learned, but we know this is your expertise. Tell us what we’re missing and how your firm can do better than our first pass.”
As a founder – when you’re searching for a business model make sure that you’re the ones doing the learning… not the outsourced help.
There’s Not Enough Time The biggest objections I get when I offer this advice is, “There’s not enough time in the day,” or “I need to be building the product,” or the more modern version is, “I’m focused on product/market fit right now.”
The reality is that they’re all excuses. Of course product and product/market fit are the first critical steps in a startup – but outsourcing your learning about the other parts of the business model are the reasons why your investors will be hiring an operating executive as your replacement - once you done all the hard work.
You need to do the learning not your consultants
Most consultants will think that’s their secret sauce and not want your business
The smart ones will realize that’s how they’ll build a long-term relationship with you
Not understanding the other parts of your business model is a reason investors hire an operating executive
Todd Branchflower was one of my Lean LaunchPad students entrepreneurial enough to convince the Air Force send him to Stanford to get his graduate engineering degree. After watching my Secret History of Silicon Valley talk, he became fascinated by how serendipity created both weapon systems and entrepreneurship in World War II – and brought us federal support of science and Silicon Valley.
In class I would tease Todd that while the Navy had me present the Secret History talk in front of 4,000 cadets at the Naval Post Graduate School, I had yet to hear from the Air Force Academy. He promised that one day he would fix that.
Fast-forward three years and Todd is now Captain Todd Branchflower, teaching electrical engineering at the Air Force Academy. He extended an invitation to me to come out to the Academy in Colorado Springs to address the cadets and meet the faculty.
Out of the airport the first stop was in Denver – an impromptu meetup at Galvanize and a fireside chat with a roomful of 200 great entrepreneurs.
U.S. Military Academies Then it was on to Colorado Springs and the Air Force Academy. All officers in the U.S. military need a college degree. The Air Force Academy is one of the four U.S. military service academies (academy is a fancy word for 4-year college.) The oldest is the Army’s U.S. Military Academy at West Point in New York, founded in 1802 to educate Army officers. The next military college was the Naval Academy in Annapolis Maryland, set up in 1845 to train Navy officers. The Coast Guard Academy opened in New London Connecticut in 1876. The Air Force, originally part of the U.S. Army, wasn’t an independent military branch until 1947, set up their academy in 1955 in Colorado Springs. Only ~20% of officers go through a service academy. Over 40% get the military to pay for their college by joining via the Reserve Officers Training Corps (ROTC) program. The rest get their college degree in a civilian college or university and then join their branch of the military after a 10-week Officer Training School.
Secret History Given my Air Force career I came thinking that sharing the Secret History of Silicon Valley talk with 1000 soon to be Air Force Officers would be the highpoint of the visit. And it was as much fun as I expected – a full auditorium – a standing ovation, great feedback and a trophy – but two other things, completely unexpected, made the visit even more interesting.
First, I got to meet the faculty in both electrical/computer engineering and management and share what I’ve learned about Lean and the Lean LaunchPad class. In their senior year all Air Force cadets on the electrical engineering track have a two-semester “Capstone” class project. They specify, design and build a project that may be of use. Unfortunately the class operates much like the military acquisition system: the project specification has minimal input from real world users, the product gets built with a waterfall engineering process, and there’s no input on whether the product actually meets real world needs until the product is delivered. This means students spend a ton of time and effort to deliver a “final” product release but it’s almost certain that it wouldn’t meet real world users’ needs without extensive rework and modification.
I was surprised how interested the faculty was in exploring whether the Capstone class could be modified to use the Customer Development process to get input from potential “customers” inside the Air Force. And how the engineering process could be turned Agile. with the product built incrementally and iteratively, as students acquire more customer feedback. Success in the Capstone project would not only be measured on the technical basis of “did it work?” but also on how much they learned about the users and their needs. I invited the faculty to attend the Lean LaunchPad educators’ course to learn how we teach the class.
We’ll see if I made a dent.
Table for 4000 In between faculty meetings I got a great tour of the Academy facilities and some of the classes. As on any college campus there are dorms, great sports facilities (sports is not optional), classrooms, etc. The curriculum was definitely oriented to practical science and service. However not on too many other college campuses will you find dorms arranged in squadrons of 40 of 100 students each, where students have to make their beds and have full-time hall monitors, and simultaneously eat lunch with 4,000 other cadets in one dining room (an experience I got to participate in from the guest tower overlooking the dining hall.) All the hierarchal rituals were on display; freshman have to run on the main quad walking on narrow strips, carry their backpacks in their hands, daily room inspections, etc.
And I saw things that made this uniquely an Air Force college – they had their own airfield, flying clubs, the Aero Lab with three wind tunnels, heavy emphasis on engineering and aeronautics, etc. (And it was fun to play “what aircraft is that” with those on static display around the grounds.) But the second surprise for me was the one that made me feel very, very old – it was the Academy’s Cyber Warfare curriculum.
Cyber Warfare I visited the Cyber 256 class and got a look at the syllabus. Imagine going to college not only to learn how to hack computers but also actually majoring in it. The class consisted of basic networking and administration, network mapping, remote exploits, denial of service, web vulnerabilities, social engineering, password vulnerabilities, wireless network exploitation, persistence, digital media analysis, and cyber mission operations. In addition to the class in Cyber Warfare, there was also a cadet Cyber Warfare Club and an annual National Security Agency Cyber Warfare competition. The Air Force competes with other military branches and National Guard units; the instructor proudly told me that the Air Force has won for the last two years. I only wish I had taken a picture of the huge trophy in the back of the classroom.
We do what? On the plane ride home I had time to process what I saw.
When I was in the military the battle was just ending between the National Security Agency (NSA) and the military branches over who owned signals and communications intelligence. Was it the military (Air Force, Navy) or was it our intelligence agencies? In the end the NSA became the primary owner, the NRO (National Reconnaissance Office) owned and built the spacecraft that collected the intelligence and the military branches had organizations (Air Force Security Services, Army Security Agency or Naval Security Group) that manned the collection platforms (airplanes, listening posts, etc) which all fed back into the National Security Agency.
Cyber Warfare has been through the same battles. While each of the military branches have Cyber Warfare organizations reporting into a unified military Cyber Command, the head of the National Security Agency is its director, making the NSA the agency that owns Cyber Warfare for the U.S. Cyber Warfare has three components:
1) Computer Network Attack (CNA) – shut down an enemies ability to command and control its weapon systems in a war (i.e. Chinese satellite and over the horizon radar systems targeting U.S. carriers) or prevent potential adversaries from creating weapons of mass destruction, (i.e. Stuxnet targeted at the Iranian nuclear weapons program),
2) Computer Network Defense (CND) – stop potential adversaries from doing the same to you.
3) Computer Network Espionage (CNE) – steal everything you can get your hands (China and RSA’s SecureID breach, hacks of Google and AWS.)
Unfortunately, potential adversaries have much softer targets in the U.S. While the military is hardening its command and control systems, civilian computer systems are relatively unprotected. Financial institutions have successfully lobbied against the U.S. government forcing them to take responsibility in protecting your data/money. Given our economy is just bits, the outcome of a successful attack will not be pretty.
Thanks to the Air Force Academy, it’s faculty, cadets and Captain Todd Branchflower for a great visit
The Lean LaunchPad class may find a place in the military
We should be glad that the military is taking Cyber Warfare seriously, you should wish your bank did the same